Glom: Information Agglomerates-an Organic Representation for Quantitative Information

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Glom: Information Agglomerates-an Organic
Representation for Quantitative Information
Matthew Richard Grenby
BA, English and American Literature (June 1993)
Harvard University
Submitted to the Program in Media Arts and Sciences
School of Architecture and Planning
in partial fulfillment of the requirements for the degree of
Master of Science
at the Massachusetts Institute of Technology
June 1998
0 Massachusetts Institute of Technology, 1998
All rights reserved.
Author:
tProgram in Media Arts
and Sciences
May 8, 1998
Certified by:
John Maeda
Assistant Professor of Design and Computation
MIT Media Laboratory
Thesis Advisor
Accepted by
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Stephen A. Benton
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Glom: Information Agglomerates-an Organic
Representation for Quantitative Information
Matthew Richard Grenby
Submitted to the Program in Media Arts and Sciences
School of Architecture and Planning
On May 8th, 1998
In partial fulfillment of the requirements for the degree of
Master of Science
Massachusetts Institute of Technology
Abstract
There exists an imbalance between the sheer mass of information we feel
responsible for and the tools we use to help us make sense of this information. This thesis describes a new approach to representing large bodies of
quantitative information called GLOMS. These information agglomerates
take advantage of the user's innate visual faculties and familiarity with
everyday objects to provide an interactive, visual and computational representation that facilitates retention of the salient features of a given data
set. The defining characteristics of a GLOM representation are introduced through a series of prototypes and the description of a large controlled system: BLITZGLOM. This system visualizes data garnered from
the web-based game BLITZ that was created for this thesis.
Thesis Advisor:
John Maeda
Assistant Professor of Design and Computation
This research was sponsored by the Things That Think Consortium
Glom: Information Agglomerates-an Organic
Representation for Quantitative Information
Matthew Richard Grenby
The following people served as readers for this thesis:
1A
fl'
Reader:
\
William J. Mitchell
Dean of the School of Architecture and Planning
Massachusetts Institute of Technology
Reader:
/VL
Hiroshi Ishii
Associate Professor of Media Arts and Sciences
5
Acknowledgm ents ...........................................................
7
Introduction ...................................................................
M otivation ....................................
Accomplishments .....................
Thesis Scope and Overview .............
Related W ork ..............................................
Sandia Labs .......................
Intel Research.......................
ChernoffFaces ......................
First Prototypes ..........................................
Gradus ...........................
M unsell ...........................
StockGLOM .......................
Chicago Tribune .....................
BLITZ .......................................................
Introduction........................
Related Work and Meta-Design ..........
FirstPrototypes: GLOP................
Implementation......................
Level Editor/Level Graphics .............
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37
38
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50
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GLOM .........................................................................
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Introduction ..............
GLOM characteristics.............................
Implementation: BLITZGLOM ......................
The Layers.....................................
The A xes ......................................
Conclusion ..................................................................
Summary .....................................
Future Directions ................................
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Appendix A: Interview with a BLITZ Player........................92
101
Appendix B: Game Statistics ............................................
Bibliography...................................................................139
1 Acknowledgments
I would like to thank the readers of this thesis, Professor Ishii and Dean
Mitchell for their time and insight.
This thesis and the work it comprises was not created in a vacuum; it
would not have been possible without the help and understanding of
many others. First, I would like to extend my sincere gratitude to Professor John Maeda. For all my peculiarities, there are only a few people
whom I feel really understand my goals and ambitions, John is one of
them. I am indebted for his unfailing assistance and faith from the days
before there was any reason to believe I could do the things that needed to
be done. Next, I would like to thank the other inaugural members of the
Aesthetics and Computation group. Reed, Tom, David and Chloe: it's
been an interesting and rewarding ride. Thank you for all your enthusiasm
and for putting up with my nalvet6. I would also like to thank the urops in
ACG, especially the Doctor, Jarhead, and Melissa for all your help and
hard work.
Thanks too to those I could always turn to for help or just to take my
mind off things for a while: the crew in NECSYS. Mas, Jon, Will you are
the salt of the earth. I would also like to send my appreciation out to those
on the second floor who always treated me with professionalism and a
smile: Santina, Laurie, Linda, Deb... thank you. Thanks too to Ellen for
helping me publicize BLITZ!
GLOM:Information Agglomerates
For suggesting I apply to the Media Lab when I did and for helping me to
do so, Bob Stein.
For directly or indirectly making it all possible, Nicholas Negroponte.
For putting up with our need for Lebensraum, the boys of TMG: Brygg,
Matt, Scott, and the most talented cantakerous designer-boy I know-D.
For adapting his PERL server to feed the StockGLOM project with current market information, Jon Orwant.
For providing the environment that made Gradus possible and for giving
me the freedom to continue work on and publicize it, Art Center College.
For organizing and supporting my part in the Tribune project, Glorianna
Davenport, Ron MacNeil, and the editors, reporters, photographers and
videographers at the Chicago Tribune who worked with us.
For enduring my persistent programming questions and for passing on
various gems of wisdom, Reed Kram, Doug Soo, Rob Poor, John
Underkoffler, Phillip Tiongson, Scott Brave, Chloe Chao, Matt Gorbet,
Christopher Kline, Nelson Minar, Jon Orwant, David Small, Tom White,
Brygg Ullmer.
For support, Tony, Connie, Elizabeth, Barbara.
Kudos to my roommates for putting up with me. Love to my parents who
have always supported me however crazy the endeavor. Wulfie: "woof!"
In memory of Rosita Grenby.
May 1998
Cambridge,Massachusetts
GLOM:Information Agglomerates
2
Introduction
The artist became the foundation on which progress in the reconstruction of life could advance beyond the frontiers of the all-seeing
eye and the all-hearingear.Thus a picture was no longer an anecdote nor a lyric poem nor a lecture on morality nor a feast for the
eye but a sign and symbol of this new conception of the world.
(Lissitzky, 1920)
The purpose of this thesis is to identify new visual techniques to be
employed in the representation of quantitative information. Three years
shy of the new millennium, the world finds itself awash amid the overwhelming mass of implicit and explicit streams of data. Sensor technologies-our augmented senses of seeing and hearing-and processor
technologies have improved at an exponential rate. In combination with
an increasing level of connectivity, these technologies provide us with and
give us access to a historically unprecedented volume of raw information.
Our ability to process this flow of information depends largely on innovative software tools. Not thirty years have passed since the introduction of
new and powerful tools such as the electronic spreadsheet and the relational database. These tools were developed to streamline the flow of
information processing. In this domain, they have enjoyed enormous success. At the same time, the approach to information visualization that this
type of tool demonstrates falls short in many respects, particularly in
leveraging off our enormous innate abilities to process visual, i.e. pictorial,
information.
GLOM:InformationAgglomerates
As the thesis title suggests, our efforts have focused on the identification
of organic techniques for the visual representation of information. By
organic we refer to methodologies that are characterized by a. lifelike
motion, b. agglomerations or grouped masses of atomic components. We
choose to employ organic techniques because these kinds of techniques
have yet to be invented for or implemented at a significant scale in this
domain of information visualization. We ask the question: can an organic
approach to the visual organization and display of quantitative data be
identified and implemented? In striving to answer this question, we have
grounded our thesis research in the creation of a series of small-scale prototypes. Individually, these prototypes feature different techniques. As a
series, these prototypes share a common theme in that they all are working
examples of an organic approach to information visualization. In addition,
we have striven to demonstrate that the organic approach to information
visualization is versatile. To this end, the prototypes have been designed to
represent bodies of raw data from different domains.
Drawing from our experiences with the prototype applications, the thesis
advances the organic approach to information representation through the
description of a large-scale, work in progress implementation of these concepts: BLITZGLOM. The completed companion system that generates
the data for the BLITZGLOM representation is also considered in detail.
Before proceeding, it is important to note that the work described in this
thesis is the product of a close collaboration between the author and Professor John Maeda. This collaboration persisted through the formation
and first two years of the Aesthetics and Computation Group at the MIT
Media Lab. The prototypes, projects and many of the ideas described in
this thesis are the direct result of this collaboration, as evidenced by the
frequent use of the pronoun "we".
2.1 Motivation
We are motivated by the perception of a pervasive frustration with traditional methods of visualizing information. The popular press is filled with
pieces that point to shortcomings in existing tools and methodologies for
processing bodies of data. We hope to provide an alternative to existing
GLOM:Information Agglomerates
methods of representation. We do not seek to replace current tools; rather
we strive to augment our ability to process information by creating new
opportunities for the user to increase their awareness of the underlying
trends and biases that exist in their data.
The last century has seen considerable advances in the practice and theory of visual design. For the most part, the goal of refinement in this field
has been to facilitate the subjective experience that surrounds the communication of information. Historical movements have approached this challenge in various ways, proposing a variety of approaches to the problem of
visual communication. On one extreme, we find proponents of the dogmatic application of identified guidelines of design. This approach is
exemplified by manifesto-driven movements such as Futurism. Perhaps a
more enlightened approach, formalized in early Modernist circles, is a
methodology that involves the identification of the elements that comprise
the fundamental mechanisms of communication design. We are motivated
by, and seek to incorporate this approach in our definition and exploration
of the emerging field of organic information visualization.
"Overemphasis", Paul Zelanski notes, "on either form or function can be
carried to extents that some people judge negatively." (Zelanski, 1996)
Existing tools and methodologies for the processing and interpretation of
data are exceedingly functional. Issues of form are not considered at
length. Spreadsheet representations, for example, are heavily gridded; the
information they present is primarily alphanumeric. We are motivated to
push beyond the existing boundaries in the domain of "formal" information. We seek to integrate form-based solutions with proven text or number based methods. In short, the thesis proposes and describes the
implementation through computational means of visual representations
informed by a traditional aesthetic sensibility.
2.2 Accomplishments
- Formal definition of the key features of the organic architecture that
characterizes the ideal GLOM system.
- Description and implementation of four discrete methods for agglomerating data sets including the "Vector Slide" and "AutoGlommit" techniques.
GLOM:Information Agglomerates
- Deployment of GLOM systems on SGI, Macintosh, Windows and Java
platforms.
- Development of four key prototype GLOM systems: Gradus, Munsell,
StockGLOM and TribuneTOC.
- Development of BLITZ, the web-based Java game.
- Design and early development of BLITZGLOM, a GLOM visualization
for data collected from the BLITZ game system.
- Development of the communications and database layers for the BLITZ
system.
- Development of GLOP, a falling brick puzzle game and an early candidate for generating data.
- Gradus prototype accepted as a Design Sketch at SIGGRAPH '97.
- BLITZ receives peer acclaim on the web: "new" and "cool" on
www.gamelan.com (98-04-07); www.jars.com rated in the top 5%,
receives a score of 976/1000 (98-05-07); www.happypuppy.com reviews
BLITZ and posts a link (98-05-08); solicited by SEGAsoft to develop a
game for their site (98-04-29); several sites post links or request that we
upload the game to their site: among them are www.bonus.com and
www.atomicjava.com.
- Approximately 5,000 people play BLITZ during the first forty days it is
posted.
2.3 Thesis Scope and Overview
The thesis document develops the notion of organic information architecture through the description and evaluation of prototype implementations
of our ideas. In order to establish a sense of context, the document begins
in Chapter 3 with a consideration of related work. We consider related
work of two kinds.The first kind is work that has changed our ideas about
what is possible in the realm of information visualization. This work has
served as an inspiration to us in our attempts to break new ground. The
second kind is related work that we feel parallels our own efforts in specific domains. This work is compared and contrasted against our own
efforts in order to provide the reader with an opportunity to differentiate
and evaluate our findings.
Chapter 4 is dedicated to the description and evaluation of early thesis
prototypes. These early prototypes include: GRADUS, a proposed visual-
GLOM:Information Agglomerates
ization of the English language; Munsell, a three-dimensional GLOM
representation of RGB color space; the Chicago Tribune project, a
GLOM table of contents for online newspapers; and StockGLOM, a visualization of a live feed of mutual fund information.
Chapter 5 introduces BLITZ, the online Java-based game that was conceived as a controlled source of data to be visualized. The development
phase of BLITZ is documented, along with issues of implementation and
residual projects such as the level editor that was implemented to extend
the functionality of the game.
Finally,Chapter 6 generalizes glomming techniques deployed in the early
thesis prototypes through the description of BLITZGLOM: a GLOM
representation based on the data generated by the BLITZ game and
related database systems.
GLOM:Information Agglomerates
3
Related Work
The related work presented in the following section can be broken down
into at least two main classifications in juxtaposition with our own work.
Firstly, there is the work that we have found to be directly inspirational.
This class of work has had a significant impact on the way we think about
visualizing information. The work itself may or may not have broken new
ground in the field of information architecture, but at the time we came
across it our eyes were opened and a new realm of possibilities seemed to
open up. This type of work moved us, and more often than not resulted in
a sea change in our methodology. The second main classification of
related work encompasses work we feel runs in parallel or intersects with
our established direction. Works of this kind serve to encourage us in a
particular direction or warn us with regards to the pitfalls inherent in
unforeseen eventualities.
While varied in terms of the individual source, upon first review it seems
to us that our inspiration rests on a relatively constricted foundation. The
majority of our stimulus seems to come from within the field of information architecture. Certainly, this is a responsible approach. After all, it is of
paramount importance to familiarize oneself with the history and state-ofthe-art of the field in which you seek to innovate. However, we aspire to
create systems that lie "outside the box". It is our intuition that inspiration
for this type of innovation comes from within. That said, this notion of
"within" is not a self-sustaining one. Simply, it is our belief that a diverse
GLOM:Information Agglomerates
AnnaUal Returns
Fig.3-1: Lisa Strausfeld's FinancialViewpoints and David
Small's Navigating Shakespeare two seminal projects from the
former Visual Language Workshop at the MIT Media Lab.
Both pieces focused on the three-dimensional representation
of text and numerical information. These works inspired us to
begin the study of computational information architecture.
set of inputs increases one's ability to synthesize an increasingly variegated
set of outputs. Although not formally documented here, it bears mentioning that a significant portion of inspiration comes from the study of nature
and natural systems. Thus, methodological books such as D'Arcy Thompson's "On Growth and Form" (Thompson, 1942) and surveys such as
"The Parsimonious Universe: Shape and Form in the Natural World"
(Hildebrandt, 1996) receive special attention. In addition, we find tremendous encouragement in the study of the history of aesthetics. On the
surface, our work is easily reconciled with the field of graphic design. In
GLOM:Information Agglomerates
this area, we are guided by the masters: individual such as the late Paul
Rand, Jan Tschichold and El Lissitzky.
Perhaps less immediately evident is the inspiration we draw from the field
of architecture. In that the bulk of our solutions are implemented as
numerical codes, there is of course the problem of software system architecture to be considered for each project. This relationship to the study of
architecture, while exceedingly abstract, is very real; and it is our two and
three-dimensional visual representations that are most closely aligned to
the ancient discipline. We are concerned with issues of lighting, space,
form and navigation. Our materials are not mortar and stone, but polygons and parametric curves. We constrain the viewer's eye and their ability
to move through our constructs. We control the source of light. Our structures collapse under their own complexity-simply refusing to render-in the
same way the under-engineered building fails under its own bulk. This
level of control, and the desire to wield it in a responsible and effective
manner spurs our interest in the study of sacred and natural geometries.
Numbers such as eand pi, ratios and sequences that occur throughout the
natural world are at once intriguing and dangerous. In that they are so
well known, one runs the risk of cliche through an unconsidered application of these "ingredients". In spite of the potential drawbacks, we maintain a stolid belief in the merits and potency of these numbers and look to
the fields of design and architecture for successful examples their integration.
Fig.3-2: The Cone Tree. Developed at Xerox Parc
it is now marketed by Xerox spinoff InXight.
The Cone Tree organizes vast numbers of files in
a tree structure. Multi-page documents can be
seen on a single screen. The structure transforms in real-time, allowing the browser to navigate the entire document heirarchy by wrapping
it in a 3-dimensional cone.
GLOM:Information Agglomerates
Of particular interest are four fields of architecture: Classical, Gothic,
Modern and Structural Rationalism. We look to the Classic and the Modern for their seeming lack of complexity: N.B. this quality of simplicity, of
conservation is distinct from a lack of sophistication. Both of these
approaches to design exhibit an interest in the identification and glorification of the essential elements of design. In isolation, these elements of
course have inherent limitations; i.e. systems based solely on these basic
components run the risk of sterility. It is for the successful integration of
these elements in intensely complex systems that we strive. This is why we
find inspiration in portions of the Gothic. It is not so much the pure aesthetic of the style as much as it is the pervasively organic nature of these
projects. Many Gothic cathedrals are the products of generations of labor
and design. The final construct bears varying degrees of similarity to the
original plan. What is impressive is not the simply the amount of time it
took to construct these buildings, but rather the process of that construction: the way in which the final form was realized.
These are stratified, living monuments: fossils of vision. In our own
projects, we have complete control over the same building process. In the
computer, we have a "workforce" that is able to labor at a tireless pace. As
such, we aspire to implement the essence of the lessons of organic architecture we are able to extract from the study of the history of the field.
This implementation will use the digital medium to full advantage in an
attempt to drastically compress the production timeframe.
Among the individual architects from whom we garner inspiration is the
Catalan Antoni Gaudi. We are particularly impressed by the organic
nature of his structures. In Gaudi, we sense a synthesis of craftsmanship
and technology. This magical tension is perhaps best introduced by the
words of the French architectural theorist Eugene Viollet-le-Duc, a voice
of the Structural Rationalists and undoubtedly an early influence on
Gaudi. "In architecture, there are two necessary ways of being true. It
must be true according to the programme and true according to the methods of construction. To be true according to the programme is to fulfil
exactly and simply the conditions imposed by need; to be true according
to the methods of construction, is to employ the materials according to
their qualities and properties.. .purely artistic questions of symmetry and
GLOM:Information Agglomerates
AfT herews
h, k
Fig.3-3: Stills from The Millenium Projectand
PerspectaView. These projects by Earl Rennison and Lisa Strausfeld of Perspecta exemplify
the "overview-and-zoom" approach first presented in Rennison's Galaxy of News project.
The user flies through the data set, thereby
increasing the specificity of available information.As the user is increasingly separated from
the initial vantage point this approach may
introduce complications with disorientation.
apparent form are only secondary conditions in the presence of our dominant principles (Eugene Viollet-le-Duc, Entretiens sur l'architecture, 186372) Powerful sentiments, but perhaps only the first half of the equation.
As an end in itselfViollet-le-Duc's approach is lacking; the assumption of
the superfluity of the "artistic questions" is a regrettable notion. We are
reminded of software engineers who pronounce a project done when the
underlying algorithms are stabilized and the source code has been
debugged. Time for the designers to "make it look good". Masterfully executed, this process of "making it look good" is as critical to the success of
a project as the underlying engineering. We are inspired by Gaudi's Casa
Mil&, a daringly unique building that exhibits a highly organic aesthetic
resting upon a-for its time-technologically advanced armature.
The peaks and chimneys of the Casa Mil&rise out of the rational
grid of Barcelona as the crown of an undulating cliff face, a
cyclopean gesture whose overwhelming sense of weight seems to
GLOM:InformationAgglomerates
contradict its free and delicate organization about three irregularly shaped courts. This contradiction finds its parallel in the
perverse suppression of the building's steel structure behind
massive stone facing. As in the Park Guell, the articulation of the
structure has been sacrificed to the evocation of some primal
force. Nothing could have been further from Viollet-le-Duc, for
neither the fabric nor its mode of assembly was explicitly rendered. (Frampton, 1992)
The suppression of the engineering substructure may have been "perverse", but it was calculated and executed to great and lasting effect.
What follows is a collection of projects, individuals and fields that we consider to be inspirational or related to our current work.
3.1 Sandia Labs
Chuck Meyers and his team at the Sandia Labs in New Mexico are working on an intriguing project in virtual reality information visualization.
Meyers and his team have taken the phrase "information landscape" to
heart, creating virtual landscapes of information. Upon first glance, the
"Navigating Science" interface looks like a tropical island as seen from an
airplane approaching from above. Mountains and valleys colored green
and fading to a clay-like brown color at the lower altitudes, rise up from
sand-colored shores out of a blue ocean that stretches to infinity. The
stated goal of the project is "to develop a method of exploring and analyzing scientific literature using virtual reality. This method will allow users to
explore a three dimensional terrain of scientific papers which are spatially
graphed by their similarity." (Fig. 3-4) In their schema, individual papers
are represented either as colored dots or spheres. This geometry is given x,
y and z coordinates based on its similarity to other papers in the system.
These coordinates have meaning only in the localized sense, i.e. in juxtaposition to other papers in the same vicinity. In the global sense, this
implies that the coordinates have no absolute meaning: all relationships
are relative to a given data set. "Mountains" occur where there is a density
of similarity: individual papers are displaced in the positive vertical axis (z
in this instance).
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Fig.3-4: Navigating Science. Chuck Meyers and his team at Sandia Labs created this information landscape to represent a large-scale collection of scientific papers.
The Navigating Science project is still in the prototype phase. At this
point it generates its visualizations from the manipulation of approximately 50,000 individual records: bibliographical documents provided by
the Institute for Scientific Information. The project's stated goal is to
increase this database to 3,000,000 records. Meyers states that the Navigating Science front-end visualization is fully integrated with the underlying database engine. This allows the user to formulate custom queries to
manipulate the visualization. For example, users could choose to consider
only a subset of the larger body of documents, records that fulfil a given
search criterion. The system affords spatial and temporal navigation. As
such, the user can "fly" about and through a particular snapshot of the
environment, or dynamically deform the environment by filtering the
database according to the date associated with individual records. In a
sense, this suggests that the system is capable of animated queries, for the
temporal filter can be considered to be nothing more than a simple query
by field values.
Meyers suggests that their "technology provides an entirely new Data
Mining technique. Exploration of new and existing data sets can be done
in an easy and intuitive manner. This allows the user to visually "pick up"
connections and relationships in the data that were buried within the flat,
featureless, data archives of the past." It is their belief that presenting a
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body of unfamiliar information in the guise of the familiar will aid the user
in their attempts to extract salient information from that database. Certainly, there are common themes between our work and the Navigating
Science initiative. For example, we are also interested in creating visualizations that leverage off the user's sense of the familiar. We are used to
navigating terrain in the real world, so logic suggests that we would have
an easy time navigating a representation of the real world, hence the
attempt to create virtual islands, mountains and valleys. In our own experience, we have discovered several areas of ambiguity and potential difficulty with this approach. The simple distillation of the complications
involved in the representational approach is that under current technology, any reproduction of real world objects in the digital realm can only be
mere shadows of their physical counterparts. There is just not enough
computational horsepower to generate a simulation of reality that is
detailed enough even to lull the user into a suspension of disbelief. As a
result, the information architect is doomed to failure: it is impossible to
flesh out all the details. It is our belief that given this limitation an appropriate course of action involves the abstraction of the user's sense of
expectation. It is not prudent to attempt the simulation of a real world
object, but it does make sense to extract the essence of that object and
implement those characteristics in a unique, digital manifestation. For
example, a flower petal in the real world bruises if you handle it with too
much force. This bruising results in discoloration and a deterioration of
certain structural characteristics: the petal droops. A successful migration
of this phenomenon to the digital realm would involve no petal, only the
behavioral characteristics. Using this approach, designers do not set themselves up to disappoint the user. No one will expect to see that flower
bloom because it wont look like a flower and yet when they "touch" the
virtual object and it bruises they will be pleasantly surprised, greeted by
the familiar in an unfamiliar domain.
The necessary abstraction of the real in information architecture is what
prevents us from accepting the notion of an information landscape as the
ultimate solution to the problem of data mining. This is why we balk at the
colors and initial appearance of the Navigating Science environment. If
the universe of scientific publication is to be represented as island with
hills and valleys, why aren't there any waterfalls and rivers? Why aren't
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inxight44
Fig.3-5: Two examples of shape-based information design. On
the left, InXight's "Perspective Wall". On the right, Interval
Corporation's Strickland/Gould "CubeOctahedron". Both systems use geometric juxtaposition to their advantage, establishing relationships between data through the position of
categories and other organizing principles on the various surfaces of foundation geometry.
there any clouds? No animals? No people? The analogy quickly degenerates. Our answer is an increased level of abstraction in tandem with nonspecific, i.e. displaced, mappings of familiar traits and characteristics.
3.2 Intel Research
Mr. John David Miller working for Intel in their Portland Oregon Architecture Laboratory has been developing a visualization project known as
"Grand Canyon". The goal of this project is to visualize approximately
forty year's worth of personal information in relation to the same period's
worth of world news. In essence, the Grand Canyon project has the
potential to provide the user with a contextualized history of their own life
or of the life of someone they care about or are interested in. In its current
manifestation, the Grand Canyon project juxtaposes news stories from
LIFE magazine with a compilation of the major events in the designer's
life. Grand Canyon organizes the information it comprises on a series of
gridded planes within the three-dimensional environment. The planes are
semitransparent and are mapped with the grid with a horizontal frequency
of approximately 12 divisions and a vertical frequency of 10 on edge.
Floating above the individual planes are rectangular planes texturemapped with photographs specific to the time slice represented by a given
GLOM:Information Agglomerates
plane. Colored text also floats above a given plane with the headlines
related to the pictures. In addition, pictures from the individual's life
interweave among the other elements along with large text indicating the
year that all this information ties into. As the gridded planes overlap, the
user begins to get a sense of their transparency. Stacks of four or more
planes viewed head-on give the impression of a cumulative opacity as the
combined effect on the light cast into the scene is calculated. The planes
are organized in a periodic manner, avoiding the problems of limited visibility inherent in a straight ordering. Thus, the foremost plane appears offset to the left of the user's viewpoint, the next closest plane to the right etc.
to infinity. The planes are offset just enough to allow for a small amount of
overlap which heightens the transparency effect, especially since the body
of the geometry is set against an otherwise featureless black void. Early
prototypes we observed also incorporated sound samples from the specific
news stories or life events. The user navigates in the global sense by simply
flying back and forth through the time line. During this navigation, the
user experiences aural shifts of focus as certain items come into view and
their associated sound is played. The effect is similar to walking down a
hallway populated by a series of loudspeakers positioned at regular intervals. If the user becomes interested in a particular photo or body of text
they can simply click on that item and the camera is brought to bear. The
point of view shifts from the central browsing lie of sight and zooms in on
a particular asset. When the user wishes to return to a position that allows
for general browsing, the camera returns smoothly and proceeds with its
progress along the central line.
We found in the Grand Canyon project an interesting contrast to our own
Fig.3-6: Grand Canyon by
John David Miller. This
project presents the user
with 3-D view of an interactive timeline that spans forty
years of world events juxtaposed with the happenings
in an individual's life.
GLOM:Information Agglomerates
P1 W-
0-
Fig.3-7: Clockwise from above: InXight's
"Table Lens", two views of Spotfire's
"Spotfire Pro 3" tool. These programs
could be categorized as interactive spreadsheets. Tight integration between the underlying data sets and the visual/symbolic
representation of that data enables the user
to view up to 100 times the information they
might using traditional spreadsheet representations. Spotfire embodies the Schneiderman mantra of "Overview first, zoom
and filter, then details-on-demand".
efforts with Glom representations. Our work shares several of the challenges and limitations faced by Mr. Miller in the realization of his work.
For example, both projects push the visual and computational limits for
the sheer mass of text and geometry that can be displayed at any given
time. Grand Canyon runs on a consumer-grade PC system powered by a
Pentium Pro processor. The hardware configuration we use in the implementation of current GLOM systems is similar. Our working platform is a
300MHz Pentium II that includes identical 3D acceleration hardware to
that employed by Miller. We take away at least two design lessons from the
Grand Canyon project's use of gridded planes. The planes are extremely
useful for giving the project a sense of place. This is a good thing. However, the form of the planes contributes little to the quality of the underlying data they help to organize. A ruler is striped with measurements that
allow its owner to impose a standardized system of measure on an arbitrary object. Similarly, the planes in the Grand Canyon project serve to
slice up the individual information assets of the system into uniform temporal divisions. In both cases the measuring device is a layer on top of the
GLOM:Information Agglomerates
underlying information; alone it demonstrates its autonomy from this
data. If we were to remove all the contents of the environment other than
the dividing planes, we would be left with only the measuring device. An
alternative might be to integrate the measurement with the content itself.
If the individual assets could somehow suggest their position along the
axis they are associated with without the assistance of additional geometry, the user could avoid any unnecessary distraction. In one scenario, hue
could be used to indicate magnitude as in a thermometer that progresses
from blue to red as the temperature rises. In conjunction with an inobtrusive visual reminder, perhaps a line, to indicate the individual axes this
approach might simplify the scene. This simplification could lead to fewer
problems with occlusion and general crowding in a scene that incorporates more fully articulated metric geometry like the gridded planes.
3.3 Chernoff Faces
Certainly, the most anthropomorphic of the related works considered here
are the Chernoff faces. The supposition that Chernoff makes in presenting
his faces as a viable method of representing points in k-dimensional space
graphically is that of all objects in our world we are perhaps most familiar
with the human face. Even in the earliest stages of development as a baby,
humans start to read other faces as a means to beginning to interact with
something beyond or outside of themselves. Before we fully develop our
facility of speech, we are able to discern a mother's smile from her frown.
As such, Chernoff maps the various attributes of his simplistic faces to
dimensions of the given data set. A sad face could mean that whatever
data we are tracking has taken a turn for the worse. A smiling, welcoming
visage denotes a favorable turn of events. If a given data set has multiple
dimensions, then different aspects of the face can be individually manipulated to reflect trends in these further dimensions. A single eyebrow can be
tilted, an eye closed to a given degree or a nose pinched to indicate disdain. Thus rendered, individual faces can be plotted in a simple x/y plot
and considered both as a gestalt and as an individual in the crowd of faces.
GLOM:Information Agglomerates
I__
AM".-
nazards
nOn-USa eCO nOr
fashion
hr
arts
GLOM:InformationAgglomerates
Fig.3-8: Five variations of an approach characterized by
nodes and explicitly rendered links. Clockwise from the
top left: Apple's "HotSauce" meta-content format web
browser; InXight's "Hyperbolic Tree" VizControl; Plumb
Design's "Visual Thesaurus"; Earl Rennison's "Galaxy of
News"; and Semio's "SemioMap". These techniques in
either 2 or 3-dimensional space, allow the user to click on
specific nodes to burrow deeper along a particular vector
of interest. While integrally functional, the shapes formed
by the hulls of these interfaces offer limited additional
information. In general, once the user has "mined" into
one of these interfaces they are offered no reminder/reference to the shape of the overall body of information.
Chernoffs idea is unique among proposals we
Ey"spc"
Headeocenmot
have come across in our survey of the field of
Eyebrow slope
information representation. In a way, Chernoffs
Eye emrbot
ideas speak to the spirit of what we are trying to
Eyji
accomplish in the production of GLOM represenPupflstce
tations. In building a GLOM we hope to incorpoNoselenof
Nos wl
rate the essence of familiar behavioral
Mouth
$M
tb
opermnss
characteristics from a variety of objects that can
MM&~vWth
be found in the physical world. It is our hope that
Fig.3-9: A Chernoff face. This technique
the use of these behaviors will both facilitate the
was conceived to represent k-dimensional
user's ability to get acquainted with the navigation
data sets. The human face is an extremely
and understanding of a given GLOM system as
familiar construct. As such, we are able to
well as encourage the user to develop a sense of
read minute variations in nuance with ease.
expectation and familiarity with the unique
GLOM object. It is in this last point that our approach differs definitively
from Chernoffs proposals. Using a face to signify the performance of a
given data point in a data set may allow the user to identify trends quickly,
comparing one face to another within the context of a given plot. However, between plots there is no individuality of representation. This lack of
uniqueness, in our opinion, limits the ability of the user to retain an
impression of a given data set. This limitation is further exaggerated by the
uniformity of the technique used to render a particular Chernoff face. In
every example of a Chernoff face plot that we have encountered, the faces
in an individual plot were rendered using an identical technique. Line
thickness, color, and character was the same in every face. The plots give
the impression of a random series of stills taken from a single animation
sequence that have been subsequently scattered on the floor of the editing
room. Given the simplicity of the rendering style, we also found it difficult
to read the expressions on the faces. Again, the deliberate lack of differentiation in the rendering style got in the way. Perhaps this limitation is overcome through repeated exposure, but it seemed uncertain.
GLOM:InformationAgglomerates
4
First Prototypes
4.1 Gradus
4.1.1 Motivation and Scenario
Is there a way to make a meaningful shape from a collection of the individual words of the English language? What would that shape look like? Why
would this approach be preferable to a traditional representation, i.e. a
printed dictionary?These were among the questions we asked when we set
out to visualize the English language as a single entity.
The first assumption we made in the search for a meaningful way to represent the English language as an expressive form was that our daily interaction with three-dimensional objects would give us leverage in establishing
meaning through familiarity. We set out to create an object that wouldthrough regular observation-begin to afford the same level of information
about its state as do objects we interact with through the course of a normal day. For example, as you walk out your front door in the morning
undoubtedly you encounter a shrub or a tree that is part of the landscaping of your environs. In that you consciously or unconsciously take a mental note of the appearance of that plant, you are building up a familiarity
with it. This is a visceral familiarity. The plant becomes an ambient source
of information. On the odd occasion that you do pause for a moment to
take a more considered impression of the plant, the months of cursory
examination come into play. Suddenly, you are able to discern the season
GLOM:Information Agglomerates
4A I
-d bt)Ok
Fig.4-1: A sequence of
stills from the Gradus
project. From the top left
turning clockwise: overview of the form indicating historical trends in the
English language; zooming into the structure
heading toward selected
keyword; macroscopic
view, user extracts an
illustration and definition
of the requested work;
thesaurus mode, synonyms surround the initial word according to
relative similarity.
I, k, n
by the color of the leaves or lack thereof. Droplets falling from branches
can signal a recent bout of precipitation. Cracked bark or fungal growth
signifies the presence of disease in the area that may extend beyond this
single organism. As we began to think about how we might structure an
object of this sort, our instincts suggested that this level of expression
could only come from a form that exhibited a significant level of cohesion.
This meant the data points would need to be packed. Plants grow or
wither; if their forms were not cohesive to begin with, these transformations would be less apparent. Because we have seen a plant in its healthy
state, we are able to compare and contrast its overall form to the shape we
find it in when it is desperately in need of water or light.
The initial step in the process of developing the formal attributes of the
object was the identification of salient ways to categorize our data (individual words). The intent of the project was to propose a system that
would function primarily as a reference tool. Resultantly, the dimensions
we chose were tailored both to enable the retrieval of a particular word
and to facilitate the recognition of broad trends throughout the base of
data. These trends, we decided, would be most salient if they were intrin-
GLOM:Information Agglomerates
sically related to the history of the development of the English language.
To get a sense of that history, we turned as a reference to the Oxford
English Dictionary (OED). (Fowler, 1990)
Presumably, we are all used to locating words in a dictionary by wading
through the alphabetic ordering it presents us. Based largely on this familiarity and the resultant efficiency this familiarity affords, we chose alphabetic organization as our first axis of description. The remaining axes of
description, or "descriptors", were chosen for their perceived ability to
contribute to the overall expressiveness of the resultant form: word familiarity and temporal etymology. Determined on a word by word basis, the
most likely methodology to be used in the measurement of the familiarity
of a particular word would be based on the number of times that word
appeared in a statistically significant corpus. (Zipf, 1945) Temporal etymology would be determined by the first recorded use of a word as provided by the definitive etymological dictionary: the OED. Once plotted
along the axes, the polygonal representations of the words would be
packed along their vectors to the origin. Additional expressiveness would
be added to the resultant form through the assignment of color to a particular word based on the national origin of that word: for instance, words
with a Germanic root would share a common hue.
The interface to this reference tool would allow the user to extract information specific to a particular word such as its definition, etymology or
illustration (if appropriate). As well, one could use Gradus to browse synonyms and antonyms, replicating the essential functionality of a thesaurus. The form would be freely navigable. This would allow the user to
browse a small area that would represent, for example, "words beginning
with the letter g that came into the language during the Elizabethan period
that are relatively unfamiliar to the modern English speaker."
The emergent form would be tornado-like: relatively few words at the tail
of the object, i.e. the beginning of the language, and a burgeoning of
words following the industrial revolution through the twentieth century.
Even a quick glance at the shape of the object will give the user information about the history of the English language. If one were to explore the
area around the bottom of the shape, they would discover words like eat,
GLOM:Information Agglomerates
Fig.4-2: In the bottom left diagram we see a
metaball model. Metaballs have several attractive
characteristics that make them ideal candidates
for the role of Glommit in an organic GLOM.
Metaballs are implicit surfaces, esentially a surface defined by a contour in a continuous field of
potentials. As such, they flow smoothly into each
other, giving an illusion of physical interdepence
not unlike the phonmenon of two droplets of
water coming into contact and connecting to
become a single volume. To the left are two
screenshots of early 2-D Java implementations of
metaball glommits.
drink, speak, work, house, door and man. These are all words with Ger-
manic roots, attributed to the Anglo-Saxons who settled in Britain from
the fifth century and eventually established several kingdoms together corresponding roughly to present-day England. As the user moved up the
shape, it would gradually swell. The predominant hue of the form would
shift accordingly, as the Danish and other Scandinavian invaders of the
ninth and tenth centuries-collectively called the Vikings-demonstrated
their influence on the language. On through the Norman Conquest beginning in 1066. "The arrival of the French-speaking Normans as a ruling
nobility brought a transforming Romance influence on the language. The
Romance languages (chiefly French, Italian, Spanish, Portuguese, and
Romanian) have their roots in the spoken or vulgarLatin that continued
in use until about AD 600. For two hundred years after the Norman Con-
GLOM:Information Agglomerates
quest, French (in its regional Norman form) was the language of the aristocracy, the lawcourts, and the Church hierarchy in England.. .During
these years many French words were adopted into English." (Fowler,
1990) Beginning at the end of the Middle Ages and through the Renaissance, the culture and the history of the ancient Greek and Roman worlds
were rediscovered and popularized. Through the fifteenth to the seventeenth centuries "scholarship flourished, and the language used by scholars and writers was Latin. During the Renaissance words such as arena,
dexterity, excision, genius, habitual,malignant,specimen, and stimulus came
into use in English." (Fowler, 1990) At this point, the structure of Gradus
would swell dramatically only to taper off briefly during the time of the
Industrial Revolution. The topmost portion of the structure would expand
beyond even the limits of the Renaissance levels. Multicolored words from
around the world entered the language, spurred on by the electronic revolution and the trend towards Internationalism we have experienced during
the twentieth century.
Herein lies one of the major advantages of this approach over traditional
means: unlike printed dictionaries, Gradus offers information about its
content-in this case the history of the English language-through its form.
Gradus, as an expressive, sculptural representation of the English language offers an efficient way to develop an understanding of the nature
and the history of specific words and the language as a whole.
4.1.2 Implementation
Gradus was conceptualized on paper and in 3D modeling packages on the
Macintosh such as Strata Studio Pro and Pixel Putty Pro. Test QuickTime
movies were rendered out to validate or refute ideas presented as sketches
on paper or in Adobe Photoshop. The final piece was created using Alias/
Wavefront Power Animator software and Macromedia Director.
4.1.3 Design Lessons
Gradus has enjoyed a protracted period of popularity starting from its
introduction in December 1995. Perhaps the most concrete manifestation
of this popularity was its acceptance as a Design Sketch in the ACM's
1997 Siggraph Conference. Gradus was our first significant proposal for a
new approach to thinking about and organic three-dimensional represen-
GLOM:Information Agglomerates
tation of multi-variate data sets. Nonetheless, it has also served as a constant reminder of the importance of implementing a proof-of-concept
prototype. In addition, the discourse between those we have shown the
project and us has helped us recognize the different characteristics of a
proof-of-concept prototype can be expected to have by both designers and
engineers. Gradus is a conceptual piece. At the time it was conceived, we
did not have the resources or the skill-set required to implement Gradus
as a real-time, interactive three-dimensional environment. In addition, we
did not have access to the necessary data to complete the project. The
Oxford English Dictionary, while online, is not available in the public
domain. Corpora of headwords with and without definitions are readily
available, as are various thesauri. However, we were not able to locate a
source of etymological information as robust as that offered by the OED.
GLOM:Information Agglomerates
4.2 Munsell
Fig.4-3: The Munsell Project. With this
GLOM representation our intention was to
re-think the traditional 2-dimensional color
picker. A typical example can be found at
the bottom right. This picker comes from
the latest version of Adobe's Photoshop
product, considered one of the most successful tools in its class. Our idea was to utilize the Munsell system of color
organization-seen on the right half of the
three images straddling this text-in conjunction with a 3-dimensional GLOM representation of the RGB cube. In these stills,
a random sample of two hundred colors
are selected and plotted according to their
Se
-
RGB coordinates. The true plot is shown in
the top left image. The remaining two
images demonstrate the advantage of glomming techniques in emphasizing the underlying trends in a data set. The pronounced
"tail" indicates a tendancy to the black corner of the cube. This trend is not readily
apparant in the true plot.
4.3 StockGLOM
4.3.1 Motivation and Scenario
Part of my responsibilities as an Interval Fellow for the academic year
1997-98 involved an extended working visit to Interval Corporation in
Palo Alto California. While at the company, I was expected to complete a
project appropriate to the duration of my tenure. I was also afforded the
GLOM:Information Agglomerates
privilege of being encouraged to explore the various research initiatives
and other projects undertaken by the various staff members at Interval.
My stay was to last a total of three weeks. After an initial week of getting
my bearings and familiarizing myself with many of the projects, I settled
on my own project: a GLOM visualization of a mutual fund. Late in
1997, Andrew Lippman proposed to Jon Orwant the idea of tracking the
progress of a chimera mutual fund comprised of the publicly traded sponsor companies of the MIT Media Laboratory. Orwant programmed a
PERL server that would parse timely market data from pages Yahoo!
served up for public access. I began to work on a Java applet that would
visualize this market data.
4.3.2 Implementation
The StockGLOM project had two driving directives: 1. Reconsider the
shape of the atomic unit in the visualization, 2. Develop the "seek and
approach" behavioral model of the individual data units. Mid-fall 1997 I
had been examining the book "Algorithms in C" by Robert Sedgewick.
Sedgewick's chapter on Closest-Point Problems makes brief mention of
Fig.4-4: Scott Snibbe's
Bubble Harp.we first
encountered this project
during our stay at Interval
Research during the Spring
of 1998. The Bubbleharp, a
beautifully conceived interactive Voronoi diagram,
served as an inspiration for
the StockGLOM project.
GLOM:Information Agglomerates
theVoronoi diagram (also called the Dirichlet tessellation) and its dual the
Delaunay triangulation. Sedgewick defines the Voronoi diagram thusly:
"The set of all points closer to a given point in a point set than to all other
points in the set is an interesting geometric structure called the Voronoi
polygon for the point.The union of all the Voronoi polygons for a point set
is called its Voronoi diagram. This is the ultimate in closest-point computations..." (Sedgewick, Algorithms in C) I shelved implementation for a
later date.
For the final problem set in John Maeda's fall 1997 MAS962 "Digital
Typography" class, Tom White presented a solution which used an implementation of the Voronoi diagram to visually distribute packets of communication from a reflector server. This implementation, while
compelling, appeared to run at a frame-rate unacceptable for smooth animation. Then, at the beginning of my visit to Interval I saw a demonstration of the Bubble Harp project by Scott Snibbe and Golan Levin.
Implemented on a Pentium-class PC, The Bubble Harp allows the user to
interactively add and subtract points from a point set which is continually
interpreted into a Voronoi diagram. Users can drag given Voronoi polygons through the two-dimensional plane in real-time to see the effects this
movement has on the overall diagram. In line with Snibbe's long-standing
interest in abstract animation, the system allows the user to assign animation characteristics to the individual polygons.
We were attracted to the Voronoi diagram as a means of dividing the
design plane for at least two reasons. Firstly, in that this kind of triangulation appears naturally-in, for example, the natural separation of growing
trees, the drying of mud, and varied rock formations-it has an easy,
organic feel to it. Secondly, dividing a plane in this manner would allow us
to pack individual data units in a dynamic and efficient manner. In the
implementation of earlier GLOMS we had been limited to packing individual pieces of geometry according to a grid or, alternately, we had
impacted the geometry which led to issues with occlusion and legibility.
However, as attractive as it is, the Voronoi diagram has certain characteristics that proved undesirable for the project at hand. Given a relatively
sparse point set, the resultant Voronoi polygons are rather large. Even as
GLOM:Information Agglomerates
the number of points increases, the various polygons could not be
described as uniform with respect to comparative size or shape. The individual sponsor companies, while unique, can be considered to be similar
components-at least in the context of a mutual fund-and we strove to
emphasize this similarity in the representation. Another apparent limitation of the Voronoi diagram was the existence of infinite rays at the edge of
the plane upon which the points rested. These rays would serve to further
differentiate the individual companies in an undesirable manner.
Fig.4-5: These images demonstrate the functionality of the StockGLOM representation. Individual companies in a mutual fund are
represented as living cells in the system. The user can access information about a particular company by mousing over its cell.
The solution to circumventing these perceived limitations came through
the realization that a Voronoi diagram could be interpreted as a collection
of simple conic intersections. The Voronoi polygons could be identified
through the intersections of a series of uniformly spreading cones of infinite height. These cones lie with their vertical axis orthogonal to the point
plane and with their tip concurrent with it. The tip of these cones plays the
role of the individual point in a given point set. By limiting the spread or
maximum diameter of the base of the cone we produced what were in
GLOM:Information Agglomerates
effect clippedVoronoi diagrams. The resulting effect is more akin to intersection of bubbles or small cells.
Several standard algorithms were considered for the solution to this problem. Of these, the divide-and-conquer approach to solving the Closest
Pair Problem (Bentley-Shamos 1976; Bentley 1980) and the sweeping
plane solution proposed by Steven Fortune seemed to enjoy the most
popularity. Due to time constraints, we implemented a naive algorithm
based purely on geometric intersections. The intention was to replace the
algorithm if it could not produce animations of up to thirty frames a second with the expected data set of approximately fifty points. In the end
our algorithm produced a frame rate of approximately 15fps on a Macintosh under MRJ 2.0 and over 30fps on a Pentium 200 class PC under IE
4.x.
The StockGLOM project contained several useful lessons. The primary
lesson from all of our efforts to instill lifelike motion and dynamics in
GLOM systems is that there is no such thing as a halfway commitment.
As soon as you start down this path, you must deliver on all inherent
expectations. For example, in the StockGLOM system individual glommits appear as circles. When these circles intersect they act as though they
were two bubbles: they share a common border which is the perpendicular bisector of the line connecting their two midpoints. Many users have
wondered about the meaning of two of these glommits colliding. Does this
mean the two companies have merged?Was there a hostile takeover. In the
current system there is no mapping for this action. The bottom line is,
organic representations afford many "channels" that can be mapped.Your
user will not forgive you if in your design you neglect to map these channels.
GLOM:Information Agglomerates
36
4.4 Chicago Tribune
Fig.4-6: The Chicago Tribune
Project.Media assests for a particular story
or feature are represented as appropriate
icons: text pieces are marked with a letter,
photographs a thumbnail icon etc. This is a
one-dimensional GLOM where the vertical axis represents an increasing level of
relevance to a particular theme (indicated
on the right). Individual layers of the
GLOM represent integer steps on this
scale of similarity. The top image is a still
from the transitional phase as the GLOM
reconfigures itself according to a user's
request for a new thematic organization.
Glommits are abstracted to squares for
efficiency. The bottom pane shows the
visual weighting tool developed by Chloe
Chao for this project. Individual assets are
grouped according to theme-note the starlike cluster-and ranked numerically
according to a theme by rough placement
on the graduated scale seen at the bottom
right of the image.
GLOM:Information Agglomerates
5 BLITZ
5.1 Introduction
How is it that a Java-based arcade game came to comprise a significant
portion of this thesis? My passion is information visualization. As such, for
the past several years I have found myself trying to figure out new ways to
begin thinking about representing data in a compelling and efficient manner. When I first began to think about how I might structure my thesis my
instinct was to first locate a set of data to work with.
This body of data would ideally satisfy several constraints. Firstly, it would
be large. Increasingly, it has become apparent that my current approach to
visualization is best suited to voluminous amounts of data. At this juncture, a fundamental quality of GLOMS is the deliberate distortion of the
data to emphasize its peculiarities. This approach seems to be best supported by overwhelming amounts of raw data. As in any amplification, if
the underlying signal is thin the product of that amplification is rarely palatable.
A second quality the ideal database would demonstrate would be variety.
A uniform or predictable stream of data beyond being uninteresting not
would be challenging. The ability of a GLOM system to emphasize or deemphasize the nuances of a database factors heavily into any assessment
of the success of that implementation. Next, the data would come from a
source that is constantly generating new data-points. One aspect of the
GLOM:Information Agglomerates
"information anxiety" that is common in contemporary society is the
sense of feeling overwhelmed by the sheer volume and flow of the information we perceive we are required to maintain a mastery of.Which newspapers should I read? Which magazines? If I don't watch this or that
television show will I somehow be out of the loop? Ultimately one either
goes crazy and retreats entirely or perhaps they fall back into a comfort
zone, considering only sources of information which are known quantities. Both approaches are censorious and ultimately limit the reader in
their ability to consider an issue from a balanced position. Unfortunately,
many contemporary online news services take a similar approach in their
attempts to customize their product for the reader. Users are polled for
their particular interests and the information stream is suitably reduced to
meet those specifications. For example, a user may express an interest in
local news, weather and computers. In this way a rich and varied news
stream is reduced to a narrowcast which has the potential to reinforce previously held views and opinions. The editorial voice is compromised in
this process, and an appreciation for the larger body of available information is scuttled. If a GLOM can maintain a sense of the whole while letting the user reach any level of specificity there is hope for both the
Fig.5-1: The web-based, Java
game BLITZ as it appears
online. Above, a screenshot
from "Combat" the original
game for the Atari 2600 system that inspired our work.
BLITZ is conceived as generative source of data for
GLOM systems currently
under development. Data
from every game play is collected and recorded in our
databases.
GLOM:Information Agglomerates
editorial voice and the serendipitous discovery that architectural contextssuch as libraries-facilitate with such seeming ease.
Given these constraints, I set out to locate a suitable source of data. My
initial instinct was to tie into a live feed of stock market information. Securities information is timely, voluminous and relevant. Many initiatives
have been undertaken to visualize this type of information in new and
increasingly efficient ways. These parallel efforts would allow me to contextualize and compare my results. Aspects of stock market data that are
less desirable include the costliness of the most current and accurate
information. Also, market data that is freely available, i.e. from public
sources such as www.stockmaster.com orYahoo! would involve extra,
irrelevant effort to parse and the life-span of any such effort would be contingent on the arbitrary periodicity of site revision for a given source.
Other data sets I considered included the ever-changing catalogue of Nike
shoes designs. Nike, as a sponsor company, sent two representatives in
early spring 1997 to inspect the work of the members of the Aesthetics
and Computation group. At that time I demonstrated my work which then
included Gradus and the Munsell project. These two individuals, Hanmi
Hubbard and Keith Burgess were members of Nike's Digital Media
Group. In an effort to foster a relationship between ACG and Nike, Hub-
Fig.5-2: The set of tiled graphics
used in the game BLITZ to represent each level and the bad guys
who inhabit them. Below are samples of additional sets of graphics
for higher levels developed by urop
Jocelyn Lin.
GLOM:Information Agglomerates
bard and Burgess sent ACG a CD-ROM with over 600MB of shoe model
data.This data included compressed photographs of every new shoe in the
spring 1997 product line. This promising initiative was cut short when the
process of information exchange was frozen: Nike postponed a planned
trip to the Portland campus until an unspecified future date.
Electronic Data Systems Corporation-also a sponsor of the Media Labproposed yet another source of data for potential use in a GLOM system.
As a company with a primary focus on the management of computer
information systems, EDS took a particular interest in the possibilities
inherent in GLOM representations. One of EDS' clients at the time was
Blue Shield/Blue Cross. Our contact at EDS, Mr. JimYoung proposed
that we might work in conjunction with Blue Shield to visualize one of
their patient claims databases. Initial contact was made during the Spring
1997 Sponsor open house, but subsequent progress was put on hold as
Blue Shield and EDS' local field office reconsidered the proposal through
the summer of 1997.
A final source of data that was considered, was the web navigation database compiled by Alan Wexelblat and his associates in the Intelligent
Agents group at the MIT Media Lab. Wexelblat's project "Footprints" is
an initiative to track people's paths through web sites. In Wexelblat's
words:
Footprints is a system to help people browsing the web. You use
our software and we give you additional information, based on
the history of what people have done in the past. Ultimately, this
can lead to the creation of communities of people with similar
interests browsing the same information for similar purposes.
This is not about selecting the "best" or "hot" pages. We assume
you know where you want to go, but would benefit from knowing
where people who came before you have gone. We try to aug-
ment what you're doing, without interfering. We try to help by
providing promising directions to go and help understanding the
context of where you are. (Wexelblat, 1998)
GLOM:Information Agglomerates
My involvement in this project would have centered on thinking about
representing the path that people chose through various web sites. This
data interested me on several levels. Firstly, although unequivocally objective on the surface-there is no contesting that person x from IP number y
visited so-and-so pages at a particular time-the decision process behind
that particular path is anything but objective. The fact that semi-anonymous people's progress was being tracked through a given web site and
that inadvertently these people were helping to establish a sense of place
and history in a virtual space was particularly compelling to me. As it
turned out, we were able to incorporate many of these desirable traits in
the final candidate source of information: the online game BLITZ.
Late in July 1997 I came to the point where I felt it necessary to make a
final decision with respect to where the data that I would visualize was
going to come from. At that time John Maeda suggested that he felt
strongly that whatever the source turned out to be, that it was of paramount importance that the source be entirely of my conception and, as
much as possible, under my control. At the time it seemed unclear to me
why it should be considered so important that the data source be so much
under my control. However, subsequent experience has revealed the wisdom of this direction to me; a topic I consider at length in the evaluation
portion of this chapter.
Given this freedom, I began to consider how to generate data in a manner
that would be fun and yet sophisticated enough to satisfy the requirements
for an information source as I have outlined above. Since childhood, I
have been fascinated by computer games in their myriad manifestations.
My earliest experimentation with programming a computer was motivated by the desire to create a game. The first programmable computer I
owned was a Commodore 64. My parents agreed to buy this computer for
me on the condition that I learn how to touch type. To this end they covered the keys of the keyboard with stickers that obscured the letters
imprinted on the key, thus (if I did not peek) I was presented with a completely undistinguished interface to the machine. I did not own a mouse, I
am not even certain the Commodore 64 supported a mouse. As a result, I
was motivated to learn how to touch type as quickly as possible. To help
GLOM:Information Agglomerates
Fig.5-3: Two complete level designs for the game
BLITZ. The top level "shipped" with the original posting of the game. The bottom level was designed by a
player, Noah McNeil. An interview with Noah is presented in Appendix A.
myself achieve my goal, I decided to create a game that would facilitate
the learning process. In the end I created "Letter War", a simple game
where letters and numbers fell from the top of the screen, descending
towards helpless "friendly" cities on the terrain at the bottom of the
screen. If the letters reached the bottom of the screen, they would inflict
damage on the cities and eventually when your cities were completely
destroyed the game would end. The player could prevent damage to their
cities by typing the falling letter or number before it traveled the length of
the screen. It came as no surprise then in the summer of 1997 when I
began to wonder if I could write a new game and use it as a source of data
for visualization.
If I could write a game that was popular, many people would play it. Thus,
the resultant database would be large, satisfying the first constraint that
had been established concerning the nature of the data. People would play
the game at largely unpredictable times and at a frequency I could not
anticipate. As such, the incoming data stream would be varied fulfilling
the second constraint. The final quality of the ideal source of data is that it
constantly generates new information. Again, if the game were to become
popular I could satisfy this constraint.
GLOM:Information Agglomerates
I began to consider issues of implementation. How would the game be
delivered? What type of game would it be? What would the game play be
like? I felt that rather than develop a game for a particular platform it
would be to my advantage to attempt to create a program that could be
executed on as many different types of machines as possible. I began to
seriously consider using the Java language as a means to this end. Java's
portability and increasingly popularity as well as the relative simplicity of
implementing network-based applications/applets in this language factored into my decision to favor it as a serious candidate for use in this
endeavor.
In the sections that follow, I describe the research phase of the development of this game as well as the implementation and reception it received.
Inspirational forerunners and early prototypes are considered along with
related projects, such as the level editor that was implemented to complement the game that was produced: BLITZ. The mechanics of the game
are examined in detail with additional sections that outline problems
encountered during the building phase of development.
5.2 Related Work and Meta-Design
The decision to use Java in the development of the game portion of this
thesis meant that suddenly both the advantages and the limitations this
language presented needed to be considered in detail. Java was conceived
as a multi-platform product with extended networking capabilities: these
characteristics were among those that contributed the most to my decision
to use Java. However, Java is an interpreted language. Even with the most
up-to-date JIT compilers, Java cannot approach the performance of native
binaries in particular areas, among them graphics. 1 Challenged in this
way, I decided to look to for inspiration in successful games that had been
created under similar constraints. This process is presented in detail in
subsequent sections dedicated to particular implementations, i.e. GLOP
and BLITZ.
Before we considered specific issues related to implementation, a significant amount of thought went into what the game play characteristics of
our ideal game would be. Midsummer 1997, we organized a series of dinner discussion sessions where we brought together various groups of dedi-
GLOM:Information Agglomerates
cated game players to help with the identification of particularly desirable
game characteristics. At that time Nintendo had only recently introduced
its 64-bit gaming system: the Nintendo 64. For the period between March
and June 1997 the members of this impromptu gaming committee had
been dedicated fans of a particular cartridge game called "Mario Kart
64". Mario Kart 64 or "Kart" was engaging for several reasons, and by
identifying these qualities we hoped to be able to consolidate several or all
of them in the game we planned to create.
Kart was a legacy title. Originally it had been released as "Super Mario
Kart" on Nintendo's 16-bit gaming system the Super Nintendo. Super
Mario Kart had enjoyed enormous success on this now outdated system
which was encouraging because it suggested that the secret to Kart's success did not hinge on workstation quality full-motion graphics and cinematic sound as much as it did on the essence of the game play. This was a
quality that could ostensibly be abstracted and if it proved to be scalable,
could be implemented at any level. At heart, Kart is a racing game. One to
four players can play simultaneously, racing on a single track. The simple
goal is to reach the finish line first in the shortest time possible. The game
is complicated by the fact that all players have the ability to affect/impede
the progress of the other players. As a result, Kart can become intensely
competitive. As you drive around a particular track you are presented with
the opportunity to collect any number of "power-ups". These run the
gamut from offensive weapons that the player can use to directly affect
1. It is interesting to note that with the introductionof the Java 3D API it appearseven
this limitation may become less of a concern. "JavaSoft will release implementations of
Java 3D for JavaOS,MacOS, UNIX, andWindows. The initial reference implementations of the Java 3D API will be layered on top of existing lower-level immediate-mode
3D renderingAPI's, specifically OpenGL, Direct3D,and QuickDraw3D.The initial
Java 3D implementations will be written mostly in Java but will also take advantage of
native methods. We expect the initialJava 3D implementations to perform quite well
because they will use existing, accelerated,low-level graphicsAPI's such as Direct3D,
OpenGL, and Quickdraw3D." (Deering, 1998)
On Windows platforms, Java 2D uses the DirectDrawlibrary,ddraw.dll, if available... If ddraw.dll is not available,Java 2D will use GDI calls, but using DirectDraw
will boost performance.
GLOM:InformationAgglomerates
their compatriots, to performance enhancers that increase a player's ability
to move through the pack towards the goal. The best times for a particular
track are recorded for posterity and are viewable on demand by any
player.
The pace of the action is hectic and when a player is competing against
other humans of course no two games are alike. In addition, the nature of
the tracks is mutable. For instance, a player can rarely expect to find the
same power-ups in the same place twice. The nature of the power-ups
awarded a particular player is affected by that player's current position and
ranking in any given game. Thus, the leader of the pack is usually awarded
the more benign of the power-ups, while those at the back of the pack can
expect to pick up more powerful awards. In this way, the game attempts to
level the playing field in a dynamic manner.
From Mario Kart 64 we identified several desirable characteristics of the
Fig.5-4: Screenshots from games that
served as an example and inspiration for
BLITZ. Clockwise from the top left:
Karl Hornell's Java classic, "Warp"; Pac
Man; Starforce; and Mario Kart 64.
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Fig.5-5: Inherent performance limitations in the Java language meant that games orginally developed for legacy
systems such as the Apple Ie and original Macintosh
were ideal role-models during our design process. From
the top left: BOLO (above and below), a classic, mazebased tank game for the Apple II; Oxyd, action puzzle
game for the Macintosh with physically-based motion
dynamics.
game we aimed to create. First and foremost was the ability to play against
another person in some manner. In Kart this meant real-time interaction.
Although challenging, this type of interaction would not be impossible to
implement on a web-based action game, but the nature of this interaction
would require careful consideration. (N.B. These individual characteristics are identified here and considered in context in the subsequent sections that are dedicated to the two implementations of the final game:
GLOP and BLITZ.)The racing format also was identified as desirable.
The fact that Kart was a three-dimensional simulation was not as interesting to us as was the compelling nature of the racing experience: this we
hoped to implement in our own game. Kart also served to cement our
belief that when it came to crafting an impressive game it was not necessarily the shaded, sorted, clipped polygons-per-second that counted so
much as it was an eye for detail. The recoiling motion a player's car performed when struck from the side by another player vehicle or weapon, or
the cute but ominous "squeak" the animated driver would emit/emote
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when it was near to death. It was unique details like these that we challenged ourselves to create for our own game.
Emulating the success of a game like Kart seemed somewhat ambitious
considering the technical limitations the Java language presented. As such,
we looked for other relevant inspiration in different computational realms.
One area that seemed particularly appropriate was the arcade games of
the 1980's. As of 1998, there is a trend towards preserving the hardware of
yesteryear through complete emulation. As the actual chipsets and their
ROM's go the way of the dinosaur, they live on in software emulation on
the newer, faster hardware that relentlessly replaces its predecessors. Currently, there is a piece of software available known as MAME: Multi
Arcade Machine Emulator. This project is counted among the many nonprofit initiatives that have been springing up around the world that exist
only, it seems, to better our communal lot. An incredible initiative, the
MAME project 2 to date supports emulation of no fewer than 500 discreet
games. These games were written to run on dedicated hardware such as
the Motorola 68000 chip (Motorola's first 16-bit 2MIP chip introduced in
1979). For certain tasks, an interpreted language like Java running on
"older" (i.e. Pentium 90 class) hardware exhibits performance characteristics similar to these legacy chips. This characteristic in conjunction with
the fact that these early games are justifiably approaching archetypal significance in their field reinforced the importance of considering these
games. Through MAME we were able once again to play many of the
games we grew up on in an attempt to evaluate their relevance to the game
we were beginning to write.
2.3 MAME is strictly a no profit project.Its main purpose is to be a reference to the
inner workings of the emulated arcade machines. This is donefor educationalpurposes
and to preserve many historicalgames from the oblivion they would sink into when the
hardware they run on will stop working. Of course to preserve the games you must also
be able to actuallyplay them;you can see that as a nice side effect.
It is not our intention to infringe any copyrights orpatents pending on the original
games. All of the source code is either our own orfreely available.To work, the emulator
requires ROM's of the originalarcade machines, which must be provided by the user.No
portion of the code of the originalROM's is included in the executable. (Buffoni, 1998)
GLOM:InformationAgglomerates
In the end, at least three games stood out from the crowd: Pac Man, Starforce and Xevious. Pac Man was most interesting not for the nuances of
its game play but for the font it employed. Although there were many different typefaces developed for the 68000-class gaming machines, none
proved as popular or as prevalent as the font used in the classic Pac Man
game and its relatives. To our knowledge these typefaces were never collected or distributed by a central foundry, rather they were developed
piecemeal through successive generations of games. As such, the Pac Man
font cannot be presented as the standard typeface as much as it can be
considered a fine example of its category. We felt that using this particular
typeface would accomplish at least two goals. Firstly, the Pac Man face
would be a welcome relief from the fonts that are usually used by Java programmers such as Arial/Helvetica and Times Roman. Programmers
default to these fonts because they are readily available and require no
additional coding. Although in their conception fine typefaces, beginning
with the Macintosh in 1984 -which gave the world its first widely-available
WYSIWYG interface-fonts like Helvetica and Times have suffered the
double abuse of misuse and overuse. Implementing the Pac Man font
would distance us from that predictability while also paying homage to the
great games of the 80's.
GLOM:Information Agglomerates
.
.
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wvl
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5.3 First Prototypes: GLOP
Fig.5-6: Screenshot and preliminary sketches
for GLOP, a prototype game for the BLITZ
game system. At this point we considered producing a Tetris-like game where players played
against each other over network protocols.
Above two gems were modelled in 3-D rendering packages on SGI and Macintosh platforms
to be used as falling game pieces in GLOP.
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GLOM:InformationAgglomerates
-
5.4 Implementation
5.4.1 Strategy
The name of the game, BLITZ, is misleading when it comes to considering a strategy for advancing through existing levels. This disparity is by
design. If the player adopts an approach characterized by a headlong rush
against the enemy, cannon blasting their efforts will almost without fail be
met with overwhelming force resulting in a failure to complete the mission. In the first level, this approach will more often than not result in
total destruction of the player's tank at a point within the range of 0.2-0.4
percent towards the end of the level. During the second phase of deployment, which commenced approximately one week after the initial posting
of BLITZ to glom.net, we began collecting information concerning how
far players were penetrating the levels they attempted to complete. Interestingly, the blitzkrieg style of attack seems to be the strategy adopted by
newcomer players of BLITZ. Statistics tabulated from the master database in the appendices of this document corroborate this phenomenon.
At least in the existing levels, the strategy that will get a player the farthest
is one of conservative guerilla warfare. Although the player's tank is resilient, and health medical cells to augment a player's health rating are
readily available the enemy possesses superior firepower and numbers.
Resultantly, the player is well advised to follow a strategy of "hide, seek,
destroy". The bunkers and bosses have a sighting range that is somewhat
shorter than the range of the player's tank. By remaining just outside this
sighting range, a player can pick off the enemy without being fired upon.
The trick is in finding the optimal cell from which to commence firing.
The level has been designed in such a way as to provide these "staging"
cells for the player. What is required is a cool head under fire. As Noah
McNeil so eloquently put it in his interview, "My strategy is don't destroy
what you don't have to." 3 This approach will prevent unnecessary damage
from being inflicted by bunkers or bosses. In addition, in several locations
autonomous Baddies are enclosed by retaining walls. Granted, these Baddies can shoot at the player through the green Destructo-Walls that are
transparent to their fire. However, if the player keeps their distance they
3.Please refer to Appendix A for a full transcriptof the interview with Noah McNeil.
GLOM:InformationAgglomerates
will not be sighted and therefore not fired at. In most cases, if the player
destroys the retaining wall that hold the Baddies back, they will be
engaged under undesirable circumstances where the outcome is heavily
weighted in the enemy's favor.
Fig.5-7: Level editor designed
and programmed by Melissa
Hao. This editor is publicly
posted and allows any player of
BLITZ to design and submit a
level for inclusion in future versions of BLITZ.
5.5 Level EditorLevel Graphics
BLITZ was not produced in a vacuum. During the IAP 1998 I worked
with Undergraduate Research Opportunity (UROP) participants Melissa
Hao and Jocelyn C. Lin to extend the effective functionality and extensibility of the game. In terms of the hardware infrastructure, immediately
prior to the Christmas holiday I worked with Melissa Hao to lay the
groundwork for the entire project. At that time the domain www.glom.net
had just been secured and we began hosting it from a Pentium Pro 200
(glum.media.mit.edu). With the assistance of NECSYS (specifically Jon
Ferguson and Will Glesnes) and ACG member Richard W DeVaul I
installed Red Hat Linux v5.0 on the Pentium and began serving up the
BLITZ-related pages. We wanted to be able to easily track access and traffic through the site, so Melissa began work on setting up server side
includes (SSI) for our Apache web server. After completing that task she
wrote a CGI script to nicely format the hit information for the various
pages of the site. At this point the group decided that the Pentium we had
GLOM:Information Agglomerates
been working on was too valuable a resource to dedicate entirely to the
glom.net domain and requested that it be wiped and reclaimed as a communal machine running the Windows NT operating system. The same
machine that hosts the acg.media.mit.edu site would subsequently host
Glom.net: buzz.media.mit.edu. Buzz is a DEC Alpha running Digital's
version of the UNIX operating system. ACG memberTomWhite assisted
in the transfer. This turned out to be an advantageous switch in the long
run. We gained experience with system administrator duties on the Linux
box before it was wiped which gave us a better appreciation of the lower
level intricacies of hosting and serving up a web domain. After glom.net
was transferred to buzz.media.mit.edu we experienced a marked increase
in stability over the Linux system which had been required system shutdowns and reboots for various reasons at a minimum two times a week.
We also gained the advantage of being included in the lab-wide file system
daily backup which took us a long way towards guaranteeing the integrity
of the BLITZ database, the game code and that of the database server and
their related HTML pages.
After the Christmas break, beginning January 5th Melissa began to learn
how to program in Java with the long-term goal of creating a level editor
for BLITZ. After producing a suite of entry-level applets, Melissa began
her work on the level editor in earnest. We had decided on implementing
the level editor in Java for at least two reasons. Firstly, writing an applet
meant that we could embed the level editor on a web page which would
allow us easy access wherever we were when we sat down to design a level.
As well, we hoped that the purported platform-independent characteristics of Java would result in the greater longevity of the editor. Finally,
delivering the editor on a web page meant that, like the game BLITZ, it
could be accessed by anyone around the world who was interested enough
in BLITZ to want to help in the effort to extend its functionality by
designing a level for others to play.
The underlying design of the editor as it was eventually produced, is simple yet effective. The majority of the graphics for BLITZ reside in a single
CompuServe GIF file. This modular design allows us to modify easily the
entire look and feel of a given level by simply switching out this particular
file with a new one that contains the alternate graphics. This single file
GLOM:Information Agglomerates
11 - . ___;_.11-;.
- 111.. -
-
I -
also increases the efficiency of the process of loading BLITZ. At this time,
there is limited support for ZIP or JAR files in browsers. As such, at run
time the individual resources that go into making an applet such as class
files, sounds or graphics all require separate HTML requests. Fewer calls
lead to a speedier load.
Fig.5-8: Attraction screen
and still from game play.
The goal of BLITZ is to
reach the end of the level as
quickly as possible with the
highest score.
Melissa's level editor by default loads in the GIF file associated with the
first level of BLITZ, but it does include a feature which will allow you to
specify a path to an arbitrary GIF. This enables the designer to design any
number of custom levels. The interface itself is straightforward and does
not require a significant amount of effort or time to learn. As you can see
in Figure 5-7, the applet canvas is broken down into four major areas. The
first area is dedicated to the specification of the overall features of the
level. A text field titled "level width" prompts the user to specify the number of columns that make up the sideways dimension of the level. N.B. all
levels are twelve rows high. The scrolling motion of the level does not
extend in the vertical dimension which accounts for this constraint. The
code, however, does not restrict in any way the width dimension of a particular level. Immediately to the left of the width specification text field are
GLOM:Information Agglomerates
two small windows which allow the user to set which tile will be used as
default for the ground and for the wall. These default to tile 6 for the
ground and 0 for the wall (Indestructo wall).
The top left corner of the canvas displays the cell graphics. The user
selects a given cell by positioning the mouse over that cell and clicking
once. A light red outline surrounds the cell, indicating the selected state.
Once a cell has been selected, the user can begin to design a level by
"painting" in the large preview window that fills the upper right quadrant
of the canvas. The preview window straddles a scroll bar that allows the
user to access any part of the level they are creating. By positioning the
mouse over a target cell in the preview window the user can specify the
final appearance of that cell with a single click. When the level is ready for
testing, the two button widgets and text area residing in the bottom left
quadrant of the preview window come into play. The leftmost button
labeled "display array" instantaneously converts the graphical representation of the level that appears in the preview window into an integer array
that fills the text area straddling the two buttons. The integers that comprise this array are simply the cell number from the original level graphics
file. This array is used in the BLITZ Java code to represent the level during game play. The second button, labeled "load array" allows the user to
load a previously designed level into the preview window. This action is
achieved by pasting the properly formatted existing one-dimensional integer array into the text window and subsequently pressing the "load array"
button.
At the time of this writing, this is the extent of the functionality of the level
editor. Future improvements planned for the editor can be separated into
two categories: interface design and underlying feature set augmentation.
While functional, the overall appearance of the interface could be
improved. The general experience of interaction could be greatly
enhanced by replacing the standard Java widgets with ones of our own
design. One proposal calls for replacing the widgets with a single offscreen
buffer that draws its pixels from a graphics resource file. This arrangement, closer to the model championed by score-driven software like Macromedia's "Director" suite of software, would allow periodic updates.This
update process could be accomplished by the simple manipulation of a
GLOM:Information Agglomerates
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-
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m
Fig.5-9: Two levels designed by hand by
urop Jocelyn Lin during the early developmental stages for the game BLITZ.
single GIF or JPEG file in a 2D graphics editor like Adobe's Photoshop.
Events such as mouse clicks would be handled and mapped to an internal
representation of a rectangular "hot spot" portrayal of the interface. In
addition, we would like to implement the ability to test out a level that is
currently under design. Instead of simply outputting an integer array for
inclusion in the BLITZ code, the level editor could incorporate a modified version of the BLITZ game. Thus, as a user designed a level they
could test out their design by actually playing the unfinished level. This
refinement would greatly simplify the current design/implementation
pipeline that involves pasting the newly generated integer array into the
BLITZ code followed by a fresh recompilation of the BLITZ code. This
model could write to a file or-in order to circumvent Java's security restrictions-could register the level in progress with a level server. This server
could communicate with the level editor using standard network protocols
in order to maintain a dynamic record of all possible levels. The server,
running as an application on the domain server, could write a file on the
server's filesystem. This would allow us to tag a level as a WIP (work in
progress) or F (finalized). Given this designation and a unique level ID,
the level server could serve double duty: concurrently servicing the level
editor and the BLITZ code. As new levels came online, BLITZ could list
them along with information about the designer. In this way players could
select which level they wanted to play at the start of their game.
Working with Jocelyn Lin, we developed preliminary design for three levels along with accompanying graphics files. Jocelyn's charge was to create
GLOM:Information Agglomerates
I
-
U
-
three unique sets of tiles, based loosely on the original set, for inclusion in
the more advanced levels of BLITZ. The final product can be observed in
figure 5-2.What is not so apparent in this black-and-white reproduction is
the shift in color palette that Jocelyn applied to each set of tiles. Through
her designs, Lin proposed a significant re-design of the wall elements, the
one-cell bunker and the four-cell boss bunker. The ground and terrain
cells she created tile, creating an overall patterned impression to any continuous stretch of unobstructed flooring. Lin's schematics for higher level
designs are visible in figure 5-9. Originally sketched out on long, accordion-like pieces of paper, these level designs are distinct from our own and
promise to add a welcome variety to BLITZ when they are incorporated.
*len
game gamecliet
Liserver
database
database
*
glom
Fig.5-10: Schematic of the BLITZ system and its relationship to the database and BLITZGLOM layers. An
unlimited number of clients load the BLITZ game (Java) from our web servers. These game clients broadcast
their scoring information to our database server (Java) which reflects all it receives to the database (Visual
Basic) where it is parsed and recorded. The GLOM system (Visual Basic)then queries the database in order to
gather the information it needs to build its visualization.
GLOM:Information Agglomerates
6
GLOM
6.1 Introduction
What is this word GLOM? What is a GLOM? The word glom comes from
the abbreviation of agglomeration.Defined in the OED as "a mass or collection of things"(Fowler, 1990), the word is also used as a verb as in "to
collect into a mass". In the context of this thesis, a GLOM is a purely
computational collection: a visual representation of a given set of data. In
this section of the thesis, we introduce the concept of a GLOM through a
description of its ideal characteristics. The concept is further developed
through the presentation of a GLOM system based on the data generated
and collected by BLITZ: BLITZGLOM. BLITZGLOM is the culmination of our research at the Media Lab. As such, it leverages off many of the
ideas presented in the previous sections of this document. In effect, the
description of the characteristics of the ideal GLOM system are a distillation of the lessons learned through the design and implementation of the
several sub-systems heretofore described.
More than a mere series of isolated implementations, these computational
artifacts serve as dynamic manifestations of what purports to be a new
doctrine in the field of information architecture: Organic Information
Display (OID). OID celebrates the lessons of traditional fields of aesthetics and computation, seeking a symbiosis between the products of reason
and emotion. This is not a new goal: mankind has struggled from time
immemorial with the tension between the tools he has forged and their
GLOM:Information Agglomerates
P"011010 I OP
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interplay with his affective being. What is unique about OID is its raison
d'irre: the synthesis of the organic and informational for the betterment of
our communal wisdom. In the modern world, we find ourselves at an
imbalance; we are overwhelmed by the creation of our creations. As our
machines collect and generate, we are smothered under a blanket of data.
OID seeks to find the balance between knowing and understanding, by
design.
6.2 GLOM characteristics
6.2.1 Form and Meaning
In your mind's eye, consider an ancient oak tree, solitary on the crest of a
hill in an open field. From a distance, you can appreciate the over-all form
of the tree: the strange symmetries of the branch network, the shape and
color of the canopy. As you come nearer, you notice the leaves rustling in
the breeze. Strong winds have torn certain branches away from the trunk.
You see faint traces of charred bark, indicating that at one point this tree
survived a fire in the field. The tree is teeming with life, from the birds that
temporarily alight on a branch to rest, to the ants and grubs that make a
meal of leaves. We know a significant amount about this particular tree.
No text. No numbers. All this information has been gleaned from a quick
examination of only the formal qualities of an object: its shape, not its
numbers.
Now consider the stock pages of the Wall Street Journal. Columns and
columns of minuscule sans-serif type, accurately detailing the smallest
Fig.6-1: 1he original GLOM.
This GLOM, created on a Macintosh using the Quickdraw 3D
graphics library, was the first
GLOM ever. It demonstrated the
viability of the Vector Slide algorithm for agglomerating an arbitrary set of data.
GLOM:Information Agglomerates
fluctuation in price, volume and thereby intrinsic value of any particular
security you care to track. Step back from the page. Observe the larger
structures: line-spacing, margins, column width, the dimensions of the
pages. These pages are the picture of refinement: carefully managed, rational, terminally specialized. Unlike the tree, separate representations are
required to meaningfully express the micro and the macro. The listings are
the micro view of a particular exchange; separate graphs and charts are
used to communicate the macro: trends in the over-all market, the state of
national economies.
In our research, we strive to create representations of information that
incorporate the qualities of natural expectation and familiarity usually
found in organic systems with the efficacy and focus of traditional alphanumeric descriptions. As such, a necessary characteristic of any GLOM
representation is that its form is related in a meaningful way to the content
that it comprises. This quality cannot be overemphasized. It is our observation that there has been an enormous effort in response to the perceived
threat of information overload. The popular press is full of sensationalistic
headlines like "Data Smog, Surviving the Info Glut" (Shenk, 1997) or
"Information Anxiety: What to Do When Information Doesn't TellYou
WhatYou Need to Know". (Wurman, 1989) Most of these articles and
books offer suggestions about how to streamline your information flow.
They tell you which articles to read, which web sites to visit which day
planners to use to make the most efficient use of your time. In addition, a
few of these works go as far as to suggest new spiritual approaches to the
problem of feeling overwhelmed by the flow of information. Another
genre of literature, championed by Edward R. Tufte in his three-book
series and through his lectures, concerns itself with the taxonomy of information display. These pieces catalogue the myriad methods of representing bodies of information while offering informed opinions about the
efficacy of the various techniques along with suggestions for the refinement of extant methods. Less common is literature outlining entirely new
approaches to dealing with information representation. In part, this is
what we strive to accomplish with the OID initiative.
GLOMS should present the user with unique and interesting forms.
These forms must be derived from the data itself, and ideally these forms
GLOM:Information Agglomerates
Fig.6-2: A hanging Petunia plant.
Physical objects that we interact
with on a regular basis, afford a
sense of familiarity and expectation.
This plant served as the inspiration
for the DataBloom Glommit, a
Glommit that embodies the mechanisms of a physical flower in order
to visualize n-dimensional data sets.
will be uniquely memorable. This is an important distinction because it
sets GLOM representations apart from traditional representations on at
least two fronts. The first distinction, which is considered in further detail
below, is that this implies the data sets are somehow subjectively distorted.
The second is that GLOM representations are individually distinct with
respect to their nuances of emphasis. That is to say, the way an individual
GLOM emphasizes the particular maxima and minima of its data set may
or may not share anything in common with the next GLOM. This is different in a subtle but critical way from existing representations. Consider
for a moment your typical graph or bar chart. From one graph to the next
the values assigned the axes are certainly mutable. However, aside from
deliberate distortions of scale, the viewer can expect certain homogeneity
between all graphs. We have all come to internalize the meaning of what
appears to be an exponential curve. Periodic undulations offer no surprise. Through protracted exposure to this kind of representation we have
learned to read certain biases with relative ease. This is a good thing.
However, there is nothing unique about a given type of curve between
representations. Even the manipulation of hue, line width or use of clipart fails to differentiate these plots in any meaningful or-perhaps more
importantly-memorable way.
Traditional techniques invite the user to build up a generic familiarity
between individual representations. For lack of a better term, this pervasive familiarity could be considered to be a "meta-familiarity". Emphasis
GLOM:Information Agglomerates
of the unique character of individual representations is not seen as desirable as much as conformation to established conventions and avoidance of
common pitfalls. The antithesis of this success has been suitably labeled
"chart-junk" by Tufte. (Tufte, 1990) We agree, of course, that extraneous
or gratuitous design elements are undesirable in most if not all situations,
but this is beside the point. What OID calls for, and what every GLOM
representation should exemplify in addition to a quality of meta-familiarity is an unforgettable individual uniqueness.
Fig.6-3: Early rendereing of
the representational DataBloom. For the first time, we
see an articulation of the petals
that will allow the bloom to
open and close. The petals are
also layered and of varying
hues and saturations. Inset
image demonstrates the polar
distribution of differently-aged
petals.
It is certainly advantageous to establish a language of design for any but
the most political of design systems. The Wall Street Journalis successful in
part because of its well-conceived layout. A reader can come to the paper
every day with a sense of expectation, knowing that a given feature will
appear in a certain position on the page or section of the paper. Embedded pen and ink illustrations generally signify a particular type of story as
do in-line graphs or charts, etc. These are all facets of uniqueness of The
Journal.The designers have taken elements of newspaper meta-familiarity
and made them their own. Thus, at a newsstand The Journalstands out
from the rest. It has a distinctive style while remaining within the vocabulary of the genre. In a like manner, GLOM's strive to push a similar individuality to the maximum extent while remaining within the bounds of a
certain commonality. The constitution of this commonality is tied up in
issues of form, surface and dynamism, the elements of which are consid-
GLOM:Information Agglomerates
-
-
IM IM-0* - -
-
ered in detail in the remaining sections of this chapter. Thus, a user could
approach a new GLOM expecting a completely unique overall form but
with the comfort of knowing that the manipulation and navigation of that
form will be achieved through familiar means.
Why strive for this individual uniqueness couched in systematic familiarity? Certainly, providing the user with the foregone understanding of the
interface they will encounter can be considered to be an advantage rather
than a liability. In this way the user is shielded from the inconvenience of
having to re-learn their way around every time they encounter a new
GLOM. Of course, there is an inherent danger in any system of stagnation
with the inevitable progression to the eventuality of irrelevance. Any
established component of meta-familiarity should be a candidate for systematic review and revision if necessary. In addition, the underpinnings of
the system should never be considered set in stone. Paranoia in this case is
a good thing. Regular relevant revision should be considered a necessity.
Given the comfort and convenience of a systematic underlying architecture of familiarity, the necessity for case-by-case uniqueness must be reiterated. An intrinsic part of the power of a GLOM lies in the extent of the
Fig.6-4: Early sketches for
the DataBloom. Here we
-.
see the development of the
polar distribution scheme
SCA
for the player's scores.
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7
GLOM:Information Agglomerates
Also, this page shows the
first attempts at designing
aparametric hull for the
[DataBloom's
petals.
degree that a particular representation is memorable. Empirical evidence
to support this supposition comes from the reactions of observers of the
Gradus project. Almost without fail, everyone who has seen Gradus has
referred to it in subsequent discussions in terms of an assumed shape. To
most, the swirling cloud of words appears to be a tornado of sorts. To others it appears as a brain stem. Still others consider the form akin to a giant
jellyfish. The individual mapping although interesting is not as interesting
as the proclivity of the viewer to create this kind of connection. Herein lies
the potential fundamental strength of any well-conceived GLOM representation. It seems humans have a natural tendency to attribute a familiar
object to if not anthropomorphize unfamiliar complex systems. Case in
point, the creation of the constellations in the night sky. Here, among others, navigators use this particular mapping to aid their memorization of
the many stars in process of their job of determining position or plotting a
course. In this instance the mapping becomes a natural mnemonic device.
A less utilitarian and as such perhaps a more convincing argument for our
innate inclination towards such activity, is cloud watching. It is natural,
even enjoyable for one to perceive the familiar in the protean vapors. One
person may see a bunny in a cloud while another sees a flower. In any
case, the result is greater retention. This point has been demonstrated in
controlled circumstances. It has been shown that "despite the fact that
imagery and mnemonic-generation skills develop slowly, it is always possible to obtain positive imagery and mnemonic benefits by providing a
prompt.. .If the goal is simply to build up an associative knowledge base,
providing pictorial mediators is a solution that can be implemented at
almost any age." (Pressley, 1987)
In the same way that traditional mnemonic systems provide an entree to
the underlying information that is to be retained, so do GLOM representations demonstrate a continuum between the universal and atomic viewpoint. Ancient Greek orators were said to have constructed elaborate
architectures in their minds to which they established connections to the
body of knowledge they were concerned with. For example, if one were to
attempt to memorize an entire four-act play they could create in their
mind a four-roomed house. Particular objects could stand in for a specific
character. In this way the main protagonist could become a vase, or a mirror. Each room could signify an act in the play. As the characters ran
GLOM:Information Agglomerates
Fig.6-5: Early sketch demonstrates the desired organic look
and feel of the ideal GLOM
represenation. Individual glommits are distinguished yet are
perceived to be a natural part of
a much larger whole.
through their dialogue the orator could be mentally travelling down a
table or credenza in their memory palace. This table could be covered in
an orderly manner with the objects related to a particular character. As
such, when the storyteller encountered a gilded box it would serve as a
mental trigger for a young maiden's monologue on the occasion of her
marriage. In the following passage Quintilian, "the dominating teacher of
rhetoric in Rome in the first century A.D." (Yates, 1966) describes the
process invented by the Greek Simonides.
This achievement of Simonides appears to have given rise to the
observation that it is an assistance to the memory if places are
stamped upon the mind, which anyone can believe from experiment. For when we return to a place after a considerable
absence, we not merely recognise [sic] the place itself, but
remember things that we did there, and recall the persons whom
GLOM:Information Agglomerates
we met and even the unuttered thoughts which passed through
our minds when we were there before. Thus, as in most cases, art
originates from experiment.
Places are chosen, and marked with the utmost possible variety,
as a spacious house divided into a number of rooms. Everything
of note therein is diligently imprinted on the mind, in order that
thought may be able to run through all the parts without let or
hindrance. The first task is to secure that there shall be no difficulty in running through these, for that memory must be most
firmly fixed which helps another memory. Then what has been
written down, or thought of, is noted by a sign to remind of it.
This sign may be drawn from a whole thing, as navigation or warfare, or from some word; for what is slipping from memory is
recovered by the admonition of a single word. However, let us
suppose that the sign is drawn from navigation, as, for instance,
an anchor; or from warfare, as, for example, a weapon. These
signs are then arranged as follows. The first notion is placed, as it
were, in the forecourt; the second, let us say, in the atrium; the
remainder are placed in order all round the impluvium, and
committed not only to bedrooms and parlours, but even to statues and the like. This done, when it is required to revive the
memory, one begins from the first place to run through all,
demanding what has been entrusted to them, of which one will
be reminded by the image. Thus, however numerous are the particulars which it is required to remember, all are linked one to
another as in a chorus nor can what follows wander from what
has gone before to which it is joined, only the preliminary labour
of learning being required.
What I have spoken of as being done in a house can also be done
in public buildings, or on a long journey, or in going through a
city, or with pictures. Or we can imagine such places for ourselves.
GLOM:Information Agglomerates
We require therefore places, either real or imaginary, and images
or simulacra which must be invented. Images are as words by
which we note the things we have to learn, so that as Cicero says,
"we use places as wax and images as letters". It will be as well to
quote his actual words: "One must employ a large number of
places which must be well-lighted, clearly set our in order, at
moderate intervals apart, and images which are active, which are
sharply defined, unusual, and which have the power of speedily
encountering and penetrating the mind." Which makes me wonder all the more how Metrodorus can have found three hundred
and sixty places in the twelve signs through which the sun moves.
It was doubtless the vanity and boastfulness of a man glorying in
a memory stronger by art than by nature.(Yates, 1966)
In a more abstract sense, this is what we are providing in GLOM representations. The hull of the GLOM is akin to the house in the previous
example; its rooms are the shifts and biases within and without the structure. An important advantage of the GLOM however, is the ability to
move visually from the macro view to the level of specificity that is
required. In the Gradus project this quality is demonstrated by the bulge
that represents the burgeoning of words during the period that spanned
the end of the Middle Ages through the European Renaissance. From a
distant vantage point, all the user appreciates is the shape of the bulge in
contrast to the rest of the form: a room with respect to a building. As the
user zooms in, they move through an appreciation for fields of color (in
this case zones of words with differing national origins) to a final resting
position where the individual word becomes the focus. For the orators this
progression would be akin to increasing in level of detail from the name of
the play down to the individual sentence of a character in that play.
This process has effectively substituted symbology for the less efficient
practice of providing the user with the simply formatted bulk of data.
Spreadsheet applications are perhaps the best example of the latter
approach, simply tabulating data in rows and columns which offer a sense
of order that is only superficially related to the underlying data. In this
model, one could group the names of the months in a single column. This
GLOM:Information Agglomerates
would establish a real but shallow relationship between the words. A more
profound connection might be made if in addition to being identified as
similar quantities, the names of the months could somehow give the
viewer a sense for the individual length of a month, or perhaps the type of
weather one might expect in that month. It is our belief that this level of
concentrated meaning might be achieved through increasingly symbolic
representations (as demonstrated in the Munsell, StockGLOM and DataBloom projects). To this end, we take heart in the words of Charles Babbage. "I soon felt that the forms of ordinary language were far too
diffuse.. .I was not long in deciding that the most favorable path to pursue
was to have recourse to the language of signs. It then became necessary to
contrive a notation which ought, if possible, to be at once simple and
expressive, easily understood at the commencement, and capable of being
readily retained in the memory." (Charles Babbage, "On a method of
expressing by signs the action of Machinery," 1826). This passage distills
the essence of what we are striving for in the creation of GLOM systems.
6.2.2 Organic/subjective representations
In our efforts to create memorable shapes, we have chosen to aim for an
organic rather than an inelastic or inorganic representation. This approach
has several implications. First, our forms should appear to be "alive". This
animate quality is not related to the ability of a system to pass a Turing test
or any other trial that is designed to establish an objective criterion for distinguishing the presence of "original" thought in a computational device.
Rather, we seek to provide the impression of life through manipulation of
form. More specifically, we propose the implementation of animations
based on simple rules that begin to mimic the types of decisions living or
growing things make. Our definition of "living" then becomes inexorably
linked to the notion of change. Without change, or inanimate periods
book-ended by postponed change there is no life.
Another implicit characteristic of organic representations is the tension
between the perfect and the imperfect. Current display technologies are at
the same time moving away the analog while further enabling the programmer to simulate an analog signal. For instance, CRT displays are by
nature more analog that LCD displays, at least in appearance. The scanning electron beam excites phosphors inside the glass tube, resulting in
GLOM:Information Agglomerates
Fig.6-6: The DataBloom. On the left a
final rendering, accompanied by the
original conception sketches. The DataBloom is a highly representative Glommit, capable of illustrating trends in highdimensional data sets. The DataBloom
incorporates a sense of familiarity and
expectation that aid the user in the process of learning the nuances of the
GLOM interface.
the impression of an emissive source of light. Calculated combinations of
these micro-excitations using different colored phosphors, allow us to
simulate a broad spectrum of color. However, different batches of phosphors result in slightly different color representations, as do variously calibrated beams and differing lighting conditions. In this way, the digital
world is introduced to some of the same limitations the world of print has
struggled with for generations. Liquid crystal displays offer fewer limitations of this sort due to the nature of the technology. As in a dye-sublimation printout, the individual pixels of a CRT display are hardly
discernible; there is a measured amount of overflow depending on the
shadowmask used in the particular monitor. LCD displays are overtly
pixellated. In this way, displays are moving away from the analog. In that
resolutions are increasing at the same time, along with brute processor
performance our ability to introduce a calculated "analog" quality to our
GLOM:Information Agglomerates
designs. The overflow of the glowing phosphor can be simulated through
anti-aliasing. This is not the same as introducing an analog film grain/
scratch to a digital movie. This kind of trompe-l'oeil is not related to our
current discussion. Our point is simply that the level to which we as information designers are able to control the visual qualities of our representations is constantly increasing. It is this increased level of control that will
allow us to increasingly articulate our designs, giving us the opportunity
to create organic constructs that are inspired by real world counterparts
but that can only exist in the digital realm. The less the viewer is aware of
this distinction the better. For our purposes, there is no advantage in
emphasizing the medium, only the message.
Similar difficulties exist in rendering techniques. Even scenes rendered
with radiosity techniques are clearly computer generated. The surfaces are
too perfect, the geometry impossibly precise. This kind of perfection can
be related to issues of symmetry and asymmetry. As Ian Stewart notes:
Something in the human mind is attracted to symmetry. Symmetry appeals to our visual sense, and thereby plays a role in our
sense of beauty. However, perfect symmetry is repetitive and predictable, and our minds also like surprises, so we often consider
imperfect symmetry to be more beautiful than exact mathematical symmetry. Nature, too, seems to be attracted to symmetry,
for many of the most striking patterns in the natural world are
symmetric. And nature also seems to be dissatisfied with too
much symmetry, for nearly all the symmetric patterns in nature
are less symmetric than the causes that give rise to them. (Stewart, 1995)
Our studies of typography, particularly the ideas and examples of Jan
Tschichold have reinforced this bipolar approach to the question of symmetry. People in the fields of cinematography and game design, have
introduced one approach to breaking the too-perfect symmetries of polygonal systems: texture mapping and parametric distortions. Elaborate texture maps, often generated from photographs of physical environments
help to introduce an element of imperfection to rendered scenes. Pictures
GLOM:Information Agglomerates
of rusted metal, cracked and peeling paint, soiled surfaces and dirt are
employed in this process. Alternately, custom shaders are created to simulate hair or the scaled surfaces of a dinosaur's body. Our solutions, for the
moment eschew these solutions in favor of heavily populated systems with
only the simplest of geometry. This approach gives us at least two advantages. First, with the extra computational cycles this approach affords we
can concentrate on the development and incorporation of increasingly
sophisticated behavioral models for the individual components of our system. A second advantage is the avoidance of the onus of the representational. Humans are very good at telling the difference between a real
object and an ersatz representation. This is particularly true for representations of humans or other living beings. As long as we keep our geometry
abstract, we can avoid this difficulty. As long as that geometry "behaves"
in an interesting enough manner, we can begin to build up a relationship
with that object along with a sense of familiarity and expectation. This
familiarity will begin to allow the user to process information about a
given system in a more efficient manner.
6.2.3 A designed "distortion" of the data
It is important to note that attempts to instill a living quality into GLOM
systems have led without exception to the distortion of the system's underlying data set. The successful manipulation of this distortion is fundamental for the overall success of any GLOM visualization. Moreover, it is our
belief that the overt introduction of distortion in the representation of our
data is an important distinguishing characteristic of GLOM's and instrumental in their ability to communicate. It is a communal conceit and perhaps an inherent disinterest/lack of time that keeps us from questioning
Fig.6-7: An illustration of
the Vector Slide technique
for glomming. Individual
glomnmits slide along their
vector to the origin until
they reach it or collide.
GLOM:Information Agglomerates
the veracity of the charts, figures and statistics we encounter day to day.
Certainly, at an instinctual level we are for the most part well aware of the
pervasive manipulation of information that is common practice by statisticians. As Disreali reminds us, "there are three kinds of lies: lies, damned
lies and statistics." We seek to distort data, but we aspire to an aesthetic
distortion. This is distortion by design. Certainly, those who wish to
deceive through their designs do so with malice of forethought. It is true,
these people also distort by design. However, an important distinction
exists between our work and this other kind.The distortions we introduce
are designed to enhance the user's ability to glean desired information
from a given set of data.
Speaking of the field of graphic design and fine art, Paul Rand suggests:
"Aesthetics is the standard by which a work of art is judged. It is essentially the study of the successive or simultaneous interaction of form and
content. How skillfully these components are fused will determine the
aesthetic quality of the work in question. There are two parts to this
hypothesis. One relates to the artist, who, unlike the spectator, is intensely
involved-intuitively, emotionally, and perceptually; the other, to the
object, which possesses a plastic unity that differentiates it from the ordinary artifact." (Rand, 1996) Our interpretation of these sentiments goad
us on to seek out the most harmonious techniques for the introduction of
advantageous distortion into GLOM systems. It is through the subtle
manipulation of the techniques of the designer that we will successfully
integrate a targeted focus of interest to our designs. Ultimate success is
achieved when this manipulation is not the user's primary concern
although they are aware of the underlying methods. Hence, the importance of honest system dynamics.
The "vector-slide" technique, introduced in the Munsell project and early
GLOM prototypes serves as a useful example of the difficulties involved in
maintaining an honesty throughout the distortion process. This technique
for achieving an agglomerated state can be described as follows. In an
attempt to reach an agglomerated state, one approach might be to "scale"
the plot, that is to draw a vector from the origin to each of the coordinates
and slide the cubes in toward the center along these various vectors.There
are two disadvantages to this approach. The first is that at any given point
GLOM:Information Agglomerates
-I
-
-5
-6
-5
-4
-3
-2
-1
-10
1
iFig.6-8:
On the right, athree-dimen-
sional representation of Brsenham's
2
3
4
5
classic scan-converting algorithm.
On the left, a potential scenario for
the Vector Slide technique. B is the
origin.
during the scaling process any one cube might intersect another, thus
adding confusion to the scene. The second major drawback of this
approach is that taken to its natural conclusion all cubes end up at the origin that does not leave us with a very interesting GLOM representation.
A modified version of the scaling process will however yield some interesting results. In order to solve the first problem of intersecting cubes we can
break up our world into "voxels" or "volume pixels", essentially an infinite
number of imaginary cubes. The next step is to establish the rule that no
piece of geometry, in this example our cubes, can be plotted to a coordinate other than an integer value (which corresponds to the voxel space we
have created). In order to achieve this we employ a scan-converting algorithm, such as Bresenham's Line Algorithm, 4 to determine the legitimate
intermediate points along the vector to the origin. Figure 6-7 shows a
three-dimensional representation of this process. Another method is introduced into the system to avoid the possibility of two cubes being plotted
to the same voxel. Before geometry is translated, find out the distance
between the individual cubes and the origin. Tell all cubes that they want
4.Foley, JD,Van Dam,A "Fundamentalsof Interactive Computer Graphics" (Reading, MA: Addison-Wesley PublishingCompany, 1982) 433-6.
GLOM:InformationAgglomerates
to be at the origin. From the closest cube outwards, follow these steps:
having calculated the scan-converted line to the origin, tell the cube it is
okay to move as close to the origin as possible. Thus, every cube after the
first will occupy the unoccupied voxel closest to the origin along their vector. Figure 6-8 illustrates this process. Cube "C" will be polled before
cube "D" and will be assigned to voxel "A" (the origin voxel having been
occupied by the rightmost cube which has the closest initial position of
the bunch). When cube "D" is finally polled it will plot to the next cube
out along its vector beyond "A".This approach also solves the second
problem we identified: the cubes no longer converge to a single point.You
now have a glom. Refer to Figure 6-1 for an illustration of a simple one
hundred point glom.
6.2.4 The Battle with the Representational
A fundamental limitation of abstraction is its initial lack of context and the
resulting unfamiliarity that lack engenders. The temptation is to offer ever
more representational forms as a solution. After our initial experiments
with purely abstract geometry at the atomic level, we entered a phase of
experimentation with the representational that culminated with the DataBloom glommit. The DataBloom was the result of our search for an
increasingly complex atomic unit for a given GLOM system. The earliest
GLOM prototypes, including Gradus, Munsell and the Tribune project
all sported rather simplified glommits. In these systems individual data
points or records of data were proxied by unsophisticated abstract geometry or by text. As such, the communicative potential of the glommit was
severely curtailed. Certainly, there are situations that call for the simplest
and most elegant solution. However, we were interested to explore new
ways of mapping an increased number of variables to the component
pieces of a GLOM. For example, the cubes in Munsell were colored
according to the specific RGB triplet in the system they were there to represent. Even at this level we had the option of mapping additional vectors
of information-perhaps the emotional characteristics, or trend/popularity
statistics-to an individual cube through the manipulation of its localized
motion or its transparency, scale etc. These freedoms were not new. What
we sought was an increased density of mappings for a given piece of
geometry. To this end we looked to nature.
GLOM:Information Agglomerates
Objects in the natural world are already familiar and for the most part
densely packed with information that tells the user about the state of that
object. Take for example a typical trip to the local grocer. As the shopper
makes their way through the produce department they are presented with
a number of display bins filled with various fruits and vegetables. If one
were to consider the bin of oranges for a moment, they could begin to
appreciate the amount of information we are able to glean from even a
cursory examination of this type of organic mass. A bin like the one introduced above might contain upwards of a hundred separate oranges. The
shopper's goal might be to pick out six or seven oranges with the intention
of making orange juice. As they pick up particular oranges they can take
note of the weight of that orange. Conventional wisdom suggests that the
juicier an orange is the heavier it will be. The thickness of the skin, the size
and spacing of the dimples and the presence of bruises or any type of parasitic growth: these are all characteristics of oranges that we have come to
be familiar with through prolonged exposure.
With the DataBloom we began to explore ways of incorporating similar
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Fig.6-9: Designs for the modified DataBloom Glommit.
Original designs proved too
representational, producing in
the user an expectation for
articulation in areas that seemed
superfluous or harmful to the
visualization process. By
abstracting the familiar mechanisms of physical objects, we
aim to maintain the user's sense
of familiarity/expectation while
avoiding the need to implement
gratuitous detailing.
characteristics into our GLOM systems in an overtly representational
manner. The DataBloom, as it name suggests, looks like a flower. During
the summer of 1997 I was inspired by a potted plant (Fig. 6-2). Hanging
in stark relief against the white wall of my parent's house, this petunia
plant struck me with its cohesive yet completely transparent complexity.
The plant was a tangled organic mass. Thousands of leaves in varying
states of health crowded together along with several hundred pink, funnelshaped blooms. The flowers were also in various states of health: running
the gamut from freshly bloomed to mostly decomposed. (N.B. it must
have been an oversight, my mother is an excellent gardener!) This collection of leaves, stems and flowers was quite dense, forming a roughly pearshaped mass. Upon reflection, we were impressed by the amount of information the state of a flower could hold and the ease with which we were
able to perceive this state. We began to think about how to isolate the discreet characteristics of a flower: what were the individual components,
and how did they change as the flower moved through its life cycle? As
well, the single flower was clearly a small part of the larger body of the
plant. Each flower was richly endowed as an individual in the community
of the plant; it kept its own record of state.Yet, each bloom was inexorably
linked to the state of the overall plant. If the plant did not receive enough
water or nutrients, every component of the plant would be affected in its
own way. Still, this did not prevent the single leaf or flower from being
affected on an individual basis. Finally, the plant as seen from a distance
had a strange and satisfying symmetry. It was pear-shaped, but like a pear
no single slice could yield a consistent diameter or two identical halves.
At this point, we had already decided that the data set we would be working on for this thesis would be the statistics gathered from people who
played an online game of our making. Thus, in the initial concept stage for
the design of the DataBloom we began to map its characteristics to the
kinds of data we anticipated from the game. The petals of the DataBloom
would represent and individual game play. They would be distributed
according to polar coordinates around the center of the bloom. The angle
of distribution would be determined by normalizing the score from that
game play against the overall high score in the system. Under this arrangement, if a player were just learning how to play the game their scores
would in all likelihood be clustered between the one and three o'clock
GLOM:Information Agglomerates
Fig.6-10: Sketch of the essential
functionality of the BLITZGLOM system that is currently
under development. In the foreground the star-like structure
represents an individual player's
score record. Here we see what is
in effect a highly abstracted version of the original databloom.
Outlying shapes are the player's
previous games. The polar distribution of these "petals" is
according to the date of that
game. In the background you
can see the layered GLOM representation from which the central record was picked. In the top
left we see a miniature version of
the overall structure used to give
the user a sense of orientation
when they are zoomed inside the
structure.
position. As the player improved their abilities, their scores might begin to
spread out somewhat, and as they began to log the higher scores in the
system, they would introduce petals closer to ten o'clock or midnight.
Each time a new score was added, it would be added slightly beneath the
petal that preceded it. In this manner, we would prevent the eventuality of
impacted geometry: the petals would spiral downward at time progressed,
like some spiral staircase with impossibly placed steps. The hue and saturation of the individual petal would be determined by the time at which
that particular score had been logged. Older score petals would appear
desaturated and of a less vibrant hue; fresh scores would be colorful and
bright. Under this scheme, a user could glance at a particular DataBloom
and quickly get a sense of how the player whose scoring history was
embodied in that bloom had progressed in their abilities over time.
The DataBloom is also animated. It has the ability to close to what in the
GLOM:Information Agglomerates
physical world might be considered a nocturnal state. Upon command,
the flower blooms revealing its petals for easy consideration. This feature
was added for at least two reasons. First, people expect a flower to bloom
and the process is an aesthetically pleasing one. One should never underestimate the importance of providing the user with a pleasant subjective
experience in the manipulation and use of information systems. If the
project can communicate and satisfy on a more spiritual level, it is doubly
successful. The second reason for giving the DataBlooms the ability to
bloom was purely a matter of efficiency. In any three-dimensional computational environment there is a persistent trade-off between polygon count
and render speed. We were interested in introducing a rudimentary imageloading scheme to increase rendering speed while maintaining the appearance of the same quantity of raw geometry. Having the DataBlooms close
upon themselves led to occluded geometry: the inner petals were simply
not visible after they were wrapped up by the outer ones. Right away, we
were able to cut down on our overall polygon count by culling the
occluded geometry. In addition, as individual DataBlooms moved farther
away from the viewer's camera we dynamically reduced the complexity of
the bloom's geometry. The individual petals of a given DataBloom were
represented internally as a simple triangle-strip set. The edges of this set
were defined by two three-dimensional Bezier curves. If we desired to
reduce the polygon count on a particular petal, we simply lowered the
sample rate on these curves. The result, of course, was a coarser rendition
of a petal, but in that the petal was distant from the viewer it was not a
readily perceivable degradation.
We also designed and implemented a system that integrates the DataBloom representations with a three-dimensional tracking device: the Polhemus FasTrac system. The Polhemus FasTrac system is made up of a
sensing cube 2" on a side-that is tethered by a 6' cord to an external unit
that is in turn connected the controlling computer by a serial cable. The
external FasTrac unit allows the user to connect up to four sensors that
are themselves connected by a 6' cable. The Polhemus device transmits
data at approximately 60Hz. The programmer can extract information
about the position, pitch, roll and yaw of the various sensors. We used the
Polhemus technology as a means to picking and navigating in early prototypes of the DataBloom environment. In these systems, the user can inter-
GLOM:Information Agglomerates
actively pick various DataBlooms by positioning the Polhemus trackers
appropriately. The user holds one of the Polhemus sensors and waves their
hand about, moving from bloom to bloom. As the user nears a particular
DataBloom, it opens in response revealing the score history it embodies.
The Polhemus device becomes a sort of magic wand, activating all it
touches.
The design and implementation of the DataBloom representation was
educational. Through this project, we learned that for the type of information representation we are currently interested in it is not suitable, perhaps
even detrimental to deploy shapes that are highly representational, i.e.
very similar to a real world counterpart. The closer a virtual shape is to its
physical double, the more difficulties you run into with respect to your
ability to deliver on expectation. If a user sees what they perceive to be a
flower, they expect it to behave like a flower in as many ways as possible. If
your virtual flower is not fragrant, it could be perceived as a shortcoming.
It would be best if you could water your polygonal blooms, or the user will
be disappointed. In addition, aligning yourself with a real world object
brings with it all the associations people make with that object. This can
be distracting. After observing this reaction to the project, we froze work
on it because we were not interesting in implementing the kinds of expectations users presented to us. Undoubtedly, these suggestions would have
led to a more lifelike representation of a flower. This was not our goal. We
were interested in communicating information about something beyond
the flower: the player's score history. In order to proceed toward this chosen goal, we decided that an intelligent course of action would be the pursuit of increased abstraction. This would be achieved through a studied
distillation of the essence of familiarity. In the future, we would not focus
on the outward shape of familiar object as much as the underlying mechanisms of familiarity. Behaviors would be separated from specific shapes,
systems of organization from their expected components. Under this
approach, it would not be so important to have a series of petals blooming. Rather, the process of opening would be separated from the polar
organization of a series of small multiples.
6.2.5 Axes
There are two main components to any GLOM representation: the axes
GLOM:Information Agglomerates
of organization and the atomic data units that conform to the established
system of organization, the Glommit. The axes serve to contextualize the
entire system. Here, the user or the designer makes the decision to separate the component parts of the GLOM according to an arbitrary metric
of distribution. The successful identification of these metrics factors
heavily into the ability of a particular representation to successfully communicate the nuances of its underlying data set. The process of identification for these axes is extremely specific to the given data set. Who should
decide which axes should be used? How are these axes identified? These
critical questions must be answered on a case-by-case basis. The StockGLOM project is a useful example in the illustration of this process. It is
likely that the designer of a GLOM representation is not an acknowledged
expert in the field of the information they are seeking to represent. An
Fig.6-1 1: Here we see a closeup of a
layer from the proposed BLITZGLOM system. An individual layer
contains a sampling of the overall
population that is determined by a
stepped distribution. Individual
glommits roam about the layer. Darkened glommits signify game plays
where the level was completed successfully.
GLOM:Information Agglomerates
Total GamePlays by Day
Fig.6-12: This graph illustrates the total game plays
~BLITZ
350
has received on a
20
daily basis in the forty day
period since it was posted.
The early swell around
7 coincides with
appearing on
300
Zday
.50
SBLITZ
www.gamelan.com. Note
the even decay following.
large peak on day 33
.The
150
and then on day 39 coincide with postings on
100.,
www.jars.com and
Swww.happypuppy.com.
q
0
1
3
5
7
9
11
13
15
17
19
21
23
25
27
29
31
33
35
37
39
information architect is not necessarily a stockbroker and vice versa.
However, an information architect possesses the skills necessary to successfully present the information that a stockbroker knows to ask for when
it comes to stock and bonds. The information designer is given a set of raw
data pertaining to securities: yield percentages, the number of stocks
traded in a day, the closing price of a stock, the change in price between
that day's close and the previous day's close, the price/earnings ration, the
stock's highest and lowest prices during the previous 52 weeks, the dividend and finally the stock's highest and lowest prices of the day. The information designer is given a set of raw data pertaining to securities: yield
percentages, the number of stocks traded in a day, the closing price of a
stock, the change in price between that day's close and the previous day's
close, the price/earnings ration, the stock's highest and lowest prices during the previous 52 weeks, the dividend and finally the stock's highest and
lowest prices of the day. An optimal approach to determining the most
appropriate axes for the problem at hand is for the designer and the expert
to work together. Ideally, the designer should plan to spend at least a week
in a purely observational role, seeing how the expert deals with their information flow. At the end of the observational period the designer should sit
down with the expert, compare notes and in this manner determine the
best axes to use in the GLOM representation.
GLOM:Information Agglomerates
6.3 Implementation: BLITZGLOM
This section of the thesis describes the work-in-progress implementation
of the second half of the thesis: the BLITZGLOM visualization. BLITZGLOM is conceived as a real-time, interactive interface to the data warehoused in the Microsoft Access database generated from the reports of
those who have played BLITZ. As such, BLITZGLOM represents the
state-of-the-art in GLOM representations as of this writing. This section
describes the functionality of BLITZGLOM and its unique characteristics
in contrast to extant GLOM systems. Specific mappings are introduced
and described.
6.3.1 The Hull
BLITZGLOM is unique among existing GLOM representations in both
its underlying architecture and surface characteristics. We are involved in a
continuous process of refinement when it comes to the issue of glommit
figuration. Initial systems, best represented by the Gradus project, proposed that the glommit be defined as two-dimensional text in a threedimensional environment. The Munsell GLOM used a different stratagem, pointing towards an increased level of abstraction. In the Munsell
GLOM individual glommits were rendered as colored cubes. These cubes
exhibited no external markings and offered no extended information as a
part of their geometry. Later GLOMS, like the Tribune project and StockGLOM extended this approach in the two-dimensional realm by using a
scaled-down version of the original content-such as a photograph or a text
piece-as the glommit. In situations where this approach was not advisable
or even possible, call-outs were used instead when the user moused over
or clicked to select a particular glommit. An alternative approach is move
away from abstraction in favor of increasingly representational forms. This
was first attempted in earnest with the DataBloom prototype. With
BLITZGLOM the emphasis is on performance and economy of form.
BLITZGLOM is designed to run under TGS'V3Space control in the
Visual Basic environment on a Pentium Pro 200Mhz PC with hardware
3D graphics acceleration. In terms of performance, this configuration is
several orders of magnitude faster than anything running under current
Java technologies on the same machine. As such, certain limitations previously encountered are rendered irrelevant while others require re-evalua-
GLOM:InformationAgglomerates
tion. Nonetheless, a PC is not an SGI Octane. In order to guarantee
performance and maintain a decent frame rate, it proved necessary to
carefully plan our approach.
In order to guarantee performance, we simplified the underlying geometry
of the representation. In the BLITZGLOM system, the glommit is made
Fig.6-13: This graph shows the
strong corellation between the
number of shots fired and bad-
dies killed. It may be an expected
0.0
relationship, but from this we
* 70
know that players are not wasting
their time shooting at random targets (or missing much).
O+t adskle
0.50
0.30
0 20
0.10
0.01
3
5
7
9
11
13'
15
'17 '19. 21
23
25
'27
29
31'
3
35
37
39
Average Percentage of Level Penetration by Day
1
Ths graph
00Fig.6-13:
0 g
shows that over time those
who play BLITZ are on
average getting no closer to
the goal. This is true in
.90~
0.8o
0.70
spirt
~~
~
.~.
~:over
4.
of the** wi..de
variation
in number of game plays
the period of the sample. Perhaps it is time to
-O"
0.50
make the level
i
hisistru just a little
thegoa.
0.40
0
0
.
40
easier.
.....
30
0 20
0.10
0.00
1
3
5
7
GLOM:Information Agglomerates
9
11
13
15
17
up of only two polygons. This dramatically simplified form precludes
geometry-based representation like the original DataBloom. However, the
gains in performance allow us to enhance the animated characteristics of
the glommit to create a much more lifelike feel to the GLOM. In order to
maintain some level of perceived complexity, we turned to texture mapAverage Duration of Game in Seconds by Day
-~
1400.00-
1200.00
1000.00
800.00
500.00
400.00
200.00
0.00
1
3
5
7
9
11
13
15
17
19
21
23
25
27
29
31
33
35
37
39
Average Score in Points by Day
25000.00
20000 .00
Fig.6-14: These two graphs
show the life of a bug in
BLITZ. Around day 5 we
realized that the timer and
score were not resetting
after every game, hence the
huge spike. Although telling, these graphs are not as
useful as the BLITZGLOM system in allowing
the user to access information about an individual
game play.
15000.00
10000.00
5000.00
0.00
3
5
7
9
11
13
15
GLOM:InformationAgglomerates
17
19
21
23
25
27
29
31
33
35
37
39
ping. Affordable hardware acceleration directly addresses texture mapping
which allows us to use it prudently in our designs. Each glommit in
BLITZGLOM, when selected is texture mapped with the information
specific to it. This arrangement allows us to leave the majority of the glommits unmapped. When they are distant from the user or when they are not
picked the glommits are not mapped. This arrangement increases performance in the rendering pipeline.
With BLITZGLOM we introduce a modified version of the DataBloom.
Increasingly abstracted, this DataBloom keeps the functional and organizational characteristics of the original while making no attempt to simulate a physical flower. When the user clicks on a particular glommit, the
camera zooms in to focus on it. The glommit fills approximately sixty percent of the screen and is texture mapped with the information that is specific to that glommit. An icon on the surface of the glommit allows the
user to click to summon aliases of all other glommits associated with the
original, i.e. that player's entire game play history. These copies are summoned and fall into place surrounding the original glommit which
remains in the center. The satellite glommits are linked to the original by
thin lines and are distributed around the original according to normalization against the high score in the system. For example, if the majority of
the player's scores fall in the range of 0.2-0.5 of the system high score,
then the outlying "petals" will be distributed between the 2:30 and 6:00
positions.
6.4 The Layers
The BLITZGLOM is organized into a series of layers to facilitate comprehension of trends in the data. Each of these implicit cylindrical divisions is populated with the series of glommits that fall between the bounds
imposed by this division. For example, if the vertical axis was assigned to
be time, a natural division might be a twenty-four hour period. Under this
division, a single layer would comprise the data for a single day. Individual
glommits signify a single game play. Within the petri-dish layer, glommits
roam about according to a set of deterministic behaviors. The quality of
the motion serves to emphasize an assigned characteristic. In the StockGLOM system, increased activity was mapped to the volatility of an individual security. In BLITZGLOM, two candidate mappings are the
GLOM:Information Agglomerates
"freshness" of a particular game play, i.e. how recently that play was
entered in the system, and how close that play came to the system-wide
high score. High scores and level completions are marked by hue, their
age by decreased saturation.
The user is able to specify the granularity of the division between the layers of the BLITZGLOM. Instead of considering an entire day's worth of
data, the user might choose to consider the data from a morning. In this
way, each layer might comprise the game plays from only a few hours. The
user is able to determine the extent to which the layers are separated or
compressed. This allows the user to shift the focus between a particular
slice of the data and the overall form of the body of data.
6.5 The Axes
The axes in the BLITZGLOM system can be assigned by the user. Initially, the vertical axis is set to date: the earliest game plays are distributed
among the bottom levels of the shape. Unlike earlier GLOMS, the horizontal and depth axes are not assigned by default. Work with Gradus and
other early prototypes suggest that not only is it difficult to remain oriented in a three-dimensional environment organized in this manner, but
that issues of occlusion make it difficult to appreciate the distribution.
BLITZGLOM avoids this difficulty by leaving organization within a layer
until later. At any time, the user may choose to focus in on a particular
layer. The camera shifts to a position directly above the chosen layer. All
other layers fade out through increased transparency. Even though the
individual pieces of geometry that make up the layer is three-dimensional,
the user is presented with a two-dimensional view of the layer. At this
point the user might choose to distribute the individual glommits in a
layer in any of two ways. First, glommits can be distributed in a radial
manner. Similar to the scheme used in the DataBloom models, this distribution results in glommits being positioned between noon and midnight
on the virtual clock face of the BLITZGLOM layer. The second way in
which the glommits can be organized is by distance from the center of the
layer. Those glommits that are most "fit"are closest to the center, while
others move further away.
We are currently developing the BLITZGLOM system. The underlying
GLOM:Information Agglomerates
technology is already in place (see Fig. 6-15). We have successfully run
prototype versions of BLITZGLOM with 10-20,000 glommits in realtime. As we proceed, it is with the utmost confidence that through the
development of the BLITZGLOM we will advance our study of organic
architecture and identify new models and mechanisms for future visualizations.
GLOM:InformationAgglomerates
Fig.6-15: A view of the future. Screenshot from
prototype implementations of BLITZGLOM,
the GLOM representation for the data generated by and collected for the BLITZ game. In
this shot you see 10,000 individual transparent,
pickable Glommits. The user can manipulate
the GLOM and the Glommits in real time on a
Pentium Pro 200 PC.
GLOM:Information Agglomerates
7
Conclusion
7.1 Summary
In this thesis, we have introduced GLOMS: data visualization systems
that utilize an organic information architecture as a means to structuring
an interface to arbitrarily-sized databases. We have presented specific prototype GLOM implementations that move beyond the traditional notion
of alphanumeric representation for quantitative information. These prototypes provide intuitive, interactive visual interfaces to underlying data sets.
These GLOMS leverage off the "picture superiority effect." (Paivio,
1969) Paivio's results demonstrate that "pictures are remembered better
than words; words for which subjects imagine referents are better remembered than words studied without such coding.. .and mnemonic devices
employing imagery can produce dramatic effects on retention." (Roediger
III, 1987) In addition, GLOMS incorporate the components of imagerybased mnemonics stressed by professional mnemonists, which are that the
images should be interactive in nature and unusual rather than common.
(Lorayne, 1974) In this thesis, we have also developed a new database
infrastructure to support the collection of data from users around the
world. We have presented BLITZ, the web-based Java game that interfaces
with the database server to provide information for visualization. We have
also described and begun the implementation of BLITZGLOM, a
GLOM visualization for the data collected from BLITZ.
In particular, we have presented early work on a series of seminal GLOM
GLOM:Information Agglomerates
prototypes: Gradus, Munsell, the Chicago Tribune project and StockGLOM. These prototypes were developed with Maeda and others over
the term of thesis research. In all of these projects, special emphasis has
been placed on the articulation of realistic motion and the relationship of
the atomic unit of representation to the agglomerated whole.
With Gradus we introduced the concept of subjective distortion. The individual words of the English language were mapped along three axes and
subsequently packed. The process of packing, while introducing a distortion to the plot, resulted in a much more memorable and unusual external
form. The result of selecting the particular axes of organization also demonstrated the ability of a form to indicate the historical characteristics of a
set of data. Gradus also demonstrated the advantages for legibility of constraining two-dimensional geometry in an orthogonal orientation to the
implicit spherical division of a three-dimensional environment. Gradus
introduced the idea of spatio-distributed aliased indexing through its thesaurus function. Importantly, the success of Gradus demonstrates the
effectiveness of GLOM techniques for visualizing a database of prose.
The Munsell project introduced new generalized methodologies for the
meaningful distortion of data sets: theVector Slide.This technique utilizes
a custom voxel-based algorithm for the efficient creation of non-perforated agglomerated masses. An innovative technique for the minimization
of occlusion-Inclusive Transparency-was proposed. This technique allows
for the efficient examination of the occluded components of an agglomerated mass. The Munsell project illustrates the viability of GLOM techniques for visualizing a data set of color coordinates.
The Tribune initiative introduced the concept of the single-dimension
GLOM representation. Algorithms developed for this technique organize
the component information units into stacked, stratified layers according
to relevancy. This project also established the effective limitation of utilizing iconic representations of photographic assets in a GLOM representation. Here we introduced the idea of quantified thematic axes of
organization for GLOM systems. This project established the efficacy of
glomming techniques for databases of multimedia assets along with the
need for effective glomming techniques designed for small-scale (less than
GLOM:Information Agglomerates
100 data point) data sets.
The final prototype system, StockGLOM, presented a new technique for
introducing natural motion and cohesion into a GLOM system: Autonomous Agglomeration. This algorithm, inspired by cellular autonoma, gives
the atomic units of representation in a GLOM system the ability to roam
about the environment according to a set of rules with the goal of unified
cohesion. StockGLOM introduced the concept of honest system dynamics: the refinement of glomming techniques to reflect the subjective distortion they introduce to the databases they represent. StockGLOM further
articulates the notion of an organic subdivision within agglomerated
masses. To this end, a modified Voronoi/Delaunay triangulation algorithm
was developed. StockGLOM establishes the viability of glomming techniques for stock-market data.
This thesis presents the DataBloom, a highly representational atomic unit
of representation-Glommit-for use in GLOM system. Based on a physical
flower, DataBlooms demonstrate the advantage and limitations of referential visualizations. User feedback suggests that in utilizing this approach,
the designer must be prepared to provide the ersatz model with an extensive inventory of characteristics from its physical counterpart. This inventory serves to satisfy the user's sense of familiarity and expectation
concerning the original and does not necessarily contribute to the success
of the GLOM representation. Nonetheless, the DataBloom Glommit
demonstrated an ability to embody "physically" at least triple the number
of informational dimensions previous Glommits were.
A networked database system was produced to facilitate the background
calculations necessary to provide for the GLOM representations that lie
on top of it. This system was integrated with the web-based Java game
BLITZ-created for this thesis-in order to collect a controlled set of data
for future GLOM visualization implementations. BLITZ integrated
essential aspects of successful legacy arcade and home system games.
BLITZ enjoys persistent success and is identified by independent sources
to be an innovative example of the potential of the Java language.
Finally, this thesis describes and begins the implementation of a next-gen-
GLOM:Information Agglomerates
eration GLOM system: BLITZGLOM. Based on the data generated by
BLITZ, BLITZGLOM introduces a revision of the DataBloom which
incorporates increasingly abstracted dynamics and appearance. This revision is a response to the limitations of DataBloom representations identified in earlier prototypes.
In summary, the methods and forms identified and implemented through
the research and development phase of the thesis serve to create a solid
foundation for future implementations of organic information display. We
have identified and formalized a series of techniques that can be utilized to
create effective and communicative visual representations for quantitative
information.
7.2 Future Directions
The goal of the process of identification recorded in previous sections of
this thesis is the creation of visualizations that provide the user with a positive subjective experience. Future goals include the verification of the
supposition that GLOM visualizations can afford both a more efficient
method of representing information along with a more positive subjective
user experience. We hope to substantiate this claim through the design of
experiments that challenge the user to complete information retrieval
tasks using traditional and GLOM techniques of information visualization. In addition, we would like to identify metrics by which the user's
subjective experience could be meaningfully quantified.
Finally, it is our intention to continue to identify new techniques for representing natural motion and progression to an agglomerated state. We
have initiated consideration of annealing techniques as well as more elaborate "artificial intelligence" algorithms for Glommits based on insects and
flocking species. We will continue to test our techniques in new realms of
information. Of particular interest are databases of human interaction.
GLOM:Information Agglomerates
Appendix A: Interview with a
BLITZ Player
A-I: Introduction
Noah's father, Ron McNeil, stopped me one day at the office to mention
that his son had become a "big fan" of BLITZ and was playing the game
on a regular basis. This was a Tuesday. At the time, Noah was making routine visits on Wednesdays to the lab to see his father and participate in an
experiment conducted by the members of the Epistemology and Learning
group under Mitch Resnick's aegis. I wondered to Ron if he would give
his son permission to participate in an interview with me concerning his
impressions of BLITZ. Ron agreed, and the next day I met with nine
year-old Noah.
When Noah arrived, I did not know his age. From his appearance, he
seemed to be between eleven and twelve years old. I was surprised to find
out he was only nine. My goal in interviewing Noah was to secure an
impression of the game from someone who a. had not been involved in the
original development, and b. was representative of my target audience.
These impressions would be used to improve particular characteristics of
BLITZ with an eye to attracting a greater number of regular players.
Noah fit the bill. I was struck by Noah's ease and familiarity with the
underlying technologies involved. Dressed in a broadly striped blue and
red shirt, jeans and skater's shoes, Noah talked easily about internet con-
GLOM:Information Agglomerates
nections, gaming conventions and processor speeds. When he encountered a concept he was unfamiliar with, Noah was not disheartened.
Instead, he took these new ideas in stride adding them easily to his already
impressive knowledge of the digital world.
What follows is a transcript of the first half our conversation held at
5:00PM on Wednesday, April 22, 1998. The second half of our interview
concerned the level editor and the design of a custom level for BLITZ.
This level was produced with slight modification, and is available for play
from the www.glom.net site.
GLOM:Information Agglomerates
A-I: Transcript
MG: How did you find the game BLITZ?
NM: Um, because my dad just told me.
MG: How long ago did you firstplay the game?
NM: About two weeks ago. Oh, see uh usually whenever I get in there
without killing those two first it crashes right there.
MG: Really, can you show me?
NM: Ok. Well see when I kill them from there it doesn't happen. Here
watch this. Usually I am standing right there and the guys pop out. They
keep on popping out and then, just, it will just stop.
MG: How do you work around that?
NM: Here I'll show you. I kill them from the top.
MG: The computer you play this on at home, does it have a modem? How do
you connect to the Internet?
NM: I just go on the Internet and I have a bookmark and I am just sort of
there.
MG: Do you have a modem?
NM:Yeah.
MG: How long does it take to load the game?
NM: Um, I don't know maybe thirty seconds. I don't know.
MG: Really? So it is a 56.6k modem?
NM: I'm not sure it is my sister's modem.
MG: But it does not take too long to load?
NM: No. See this is how I fix it [the bug]
MG: Didyou know you could turn the turret by itself?
NM:Yeah, you do shift and then one of these, but it's kind of hard to get it
back to normal.
MG: Didyou know if you hit "c"the turret will return to its normalposition?
NM: It does?
MG:Yes.
NM: Oh, so I am just going to go here. Shall I hit "c"? Ha, that's cool.
MG: Just so you know. And you know you can turn the sound on and off with
NM: Oh, I didn't know that actually. Nobody really minds.
MG: No? That's great because aroundhere I can'tplay with the sound on all the
time.
NM: See that's how I fix it.
GLOM:Information Agglomerates
MG: And then it doesn't usually crash?What type of machine do you play
BLITZ on?
NM: I play on a PC.
MG: Do you know which processorit has?
NM: The processor?
MG: Does it run as quickly as this one [300mHz Pentium II]?
NM: It's just a little bit slower.
MG: What other types of games do you play these days?
NM: I don't know. I have some games like Lucas Arts.
MG: How about things like Nintendo 64 or things like that?
NM: No, I don't really like video games.
MG: Really? But you have fun playing BLITZ sometimes?
NM: I once got around where those four barreled things are, but I haven't
got past that. I died.
MG: How would you rate the difficulty of this level? Is it too hard, too easy?
NM: I like it the way it is because it's a challenge.
MG: If it was easier it might be too easy?
NM: Yeah I guess. It could be a little easier when you got around there,
but I kind of like it that way because...
MG: Is there anything about the way I have set up the interface,forexample
there it says "goal",that is confusing, or does it all make sense?
NM: It makes sense pretty much. The goal is, I'm pretty sure that's how
many people are destroyed or something. Or how far...what I want to
know is there an end to this or is it once you've destroyed everybody is that
the end?
MG: No, what the goal is showingyou is how close you are to the end. So there
really is an end. If you want I can make you invincible andyou go through the
level? Do you want me to do that?
NM: Ok, I'll try.
MG: So don't look. [I press the secret key combination] Ok, now you can just go
and nothing can shoot you. You will still have to shoot things but... Ok, so it was
not clear that there is an end to the level?
NM: No it wasn't. I thought it was just like how many guys you killed. I
thought that because when you go through the maze it can be both.
Because when you go through the maze you kill more guys and when you
go through the maze you are getting farther.
MG: That's true. So how old areyou?
NM: I'm nine.
GLOM:InformationAgglomerates
Fig.A-1: Noah McNeil
designs a level using the
level editor created by Melissa Hao. The level Noah
created, with only slight
modifications, was
included withthe general
distibution of BLITZ.
MG:You're nine? Do you know what type of games other people your age are
playing?
NM: They like video games. That's not really my type though. I don't
know.You hold little thingies and they're...I think it is more interesting to
have a screen in front of you and then...um...
MG:You mean the controllersfor Nintendo?
NM:Yeah.
MG: So you prefer the keyboard?
NM:Yeah.
MG: A lot of games that are really popular right now are like Doom and
Quake: 3D...
NM: I tried to load Quake. I like Quake pretty much but I have never
played it with the enemies because the demo version you get has no guys
in it.
MG: Many of the graphics in BLITZ are based on games from the 80's. It
is definitely an older style game.
NM: Can you fall in those? [crater from exploded turret]
MG: No.
NM: Hey you know what? At the end you should have one of them at the
end that you just go in and then it drops you down to the second level or
something, or is this the only level?
MG: That's a cool idea. Right now this is the only level, but there is no reason
there can't be more levels. There is actually a level editor that I put out there so if
GLOM:Information Agglomerates
anyone wants to design a level then I can include it in the game.
NM: That's cool.
MG: So Iput this game on the web and lots of different people play it all the time
and I collect their scores and other information.Would it be interesting to you to
a. play againstsome of those other people....
NM:Yeah, if you could do a multi-player mission or something.
MG: How would you do that?You mean you would play at the same time?
NM:Yeah.You would start at, say, different ends. And if one person killed
the other person then they would win. But then you should have the invincible not work, and the green guys would just be interference.
MG: What would the main goal be?
NM: The main goal would be to destroy the other person playing and the
other people, but I guess they would be just interference. But you should
leave out the big guys because they are too tough.
MG: The originalidea was that two people would be racingto get to a common
goal. [Noah gets to the end]. Does it change your attitude now thatyou have
reached the end?
NM: I think it, now that I know where to go it is sort of different.
MG: More of a challenge?
NM:Yeah. Well, now that I know where to go, there are some distractions,
like the place where you go up it doesn't really lead anywhere. I like that. I
think what you could do is have dead ends and a place where you would
go down a column and then there would be a dead end.
MG: So what do you like most about school?
NM: I think.. .I like Phys. Ed. a lot, that's my favorite class.
MG: So what grade are you in now?
NM: Third grade. Sometimes we played basketball, sometimes we play
medical wars...and also about this: what would be nice would be if you
could have a save game or just pause it or something. Usually what they
do is you hit "escape" and then you load or save.
MG: Why would it be cool to have thatfeature?
NM: I don't know.
MG: So what do you think of math class?
NM: Oh, I have an advanced math class. We are doing a lot of thinking
problems. And sometimes we do stuff that is like pre-algebra almost. In
regular math class we are learning fractions. That's where I usually die.
MG: So what is your general strategy when playing BLITZ?
NM: My strategy is don't destroy what you don't have to.
GLOM:InformationAgglomerates
MG: Ok, how come?
NM: Because it could be just sort of a trap that kills you. I don't have to
destroy them because they can't hurt me if I don't blow up those blocks.
MG: Now that you know that the goal of the game is to get to the end as quickly
as possible, does that change how you might play? How would you try to get as
far as possible as quickly as you can?
NM: As far as possible? I would just sort of...I don't know. I would find
the most possible squares to be in that are the best. Say I want to destroy
that I usually get in this square and slant myself so it can't shoot at me.
MG: I was thinking of adding afeature that would indicate on the level where
each player dies. I think everyone is dying aroundhere, like you saidyou died
down here a lot. You would see lots of little gravestones...
NM: Or you could see rubble or something where the dead tanks were.
MG: Is it interesting to you that lots of people could be playing this game all
aroundthe world, or is it more interestingto you that it is just you playing the
game?
NM: I don't know. I think that is interesting in a way. Um...
MG:Are you interestedto know how you perform compared to those other people
in terms of your scores and times?
NM: Sort of, but not really. I think my personal score is my score. I don't
really mind if other people know my score, it's just.. .I don't know.
MG: The focus is not so much on the fact that otherpeople know your score as
much as it is you would be able to compareyour scores and times againstthose of
other players...
NM: Oh, you mean like a high-scores table?
MG: Exactly. I could have an area that could show all the high scores. Would
that be interesting?
NM:Yeah.
MG: So how did you figure out how to play the game without making it crash?
NM: I just said, well up here there's two guys there so I can...
MG:You shot them from up there?
NM:Yeah.
MG: And then itjust didn't crash. That's pretty cool. What do you think of the
sound effects?
NM: I like the sound effects.
MG: [game speaks] Do you ever wonder who that guy is?
NM: He sounds kind of like a German laugh. Um....
MG: What do you think of the graphicsbecause they are very different in some
ways than many new games...
GLOM:InformationAgglomerates
NM:You could make obstacles of some sort, like mounds you could move
around or holes you could fall in or something. Or at the end-right in the
middle of that checkered area-that could be like a red spot that is black
and the bad guys come out of it and once you've destroyed them I guess
you are supposed to drop in. Then you drop to the next level. Or you
could make mines. You could make an "x" and then if you ran over it...
MG:You blew up as opposed to the medical one...
NM: You could do both.
MG: Do the graphics as they exist now, do they strikeyou as differentfrom other
games that you have played or not really?
NM: I think so because they are mostly squares and you are looking down
at you and.. .um... I don't know usually you are the person.
MG: In 3D you mean?
NM: Right, in 3D you are the person.
MG: How does this compare to that in your opinion?
NM: I don't know, just different.
MG: It doesn't botheryou?
NM: No.
MG: What do you think about the way the tank moves?
NM: Um...
MG: Hey, you are getting prettyfar [in the level].
NM: Rats, he noticed me. Also, maybe if the enemy learned how to
destroy walls or something. Say if you shot at some walls and they noticed
that or if they learned how to follow you like in the game Descent. In
Descent the enemies learn how to follow you if you run away from them.
MG: I agree. What do you think of the idea of somehow recording the path that
everyone took and over time it changed the characterof the level. In the same
way that in a house if everyone walks the same way...
NM: Well if it changed almost every time depending on where you go. If
you die there or if you are successful there then the next level will be the
same except there are different traps and different paths.
MG: Ok, but I mean take this level for example. Perhaps the next time you
played it there would be tire treads where otherpeople went.
NM: Or you make dirt mounds that made you or the enemy slow. Or you
could make the bottom more realistic, they could be dirt.You could make
it terrain or leave it the way it is. I don't know.
MG: Would it be interestingto see where other people have driven through the
level before you?
GLOM:Information Agglomerates
100
NM:Yeah.
MG: Would you go that way, or would you go some other way?
NM: Well if I saw them come to an end then no, but...
MG: I guess that's about right.Thanks for your time Noah I really appreciateit.
NM: No problem.
After this conversation Noah was introduced to the level editor. He went
on to design his own level which was only slightly modified and then
posted to the http://www.glom.net site as an alternative level for players to
attempt. A player can select Noah's level by clicking through the link
[Noah's level]. In the weeks since this level was posted, it has received a
healthy number of plays.
GLOM:Information Agglomerates
101
date
time
score
duration
baddies
hits
shots
ip
address
of player
id#
Appendix B: Game Statistics
In the following pages the reader will find a subset of the data collected
during the forty days preceeding the submission of this thesis. The data is
complete except for the omission of level completion codes and ending
health percentages. Below is an explanation of the column headings.
date:
time:
score:
duration:
baddies:
hits:
Shots:
ip:
id#:
the date the score was recorded.
time of day.
the score, in points, the player was awarded.
the duration, in seconds, the game lasted.
total number of bad guys the player managed to destroy. This
count includes stationary bunker emplacements as well as
roaming enemies.
count of successful hits the player made with their shots. A
successful hit includes any shot that strikes and enemy or
Destructo-wall.
total number of shots a player has made during the game.
the internet protocol address of the player.
the unique score id for the particular game play.
GLOM:InformationAgglomerates
102
date
time
score
duration
baddies
hits
shots
980401
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12:46:25 P4
1:37:31 P4
2:00:17 P4
2:02:452M
2:06:592M
5:17:1724
5:17:2324
5:17:5824
5:18:53R4
5:20:07PM
5:21:222M
5:23:542M
5:29:5724
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1:03:33AM
3:19:14AM
4:21:32AM
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8:15:30AM
8:25:09AM
8:30:17AM
8:37:32AM
8:41:04AM
8:44:20
AM
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9:14:52AM
9:18:17AM
9:55:40AM
10:03:51
AM
10:07:40
AM
10:36:52
AM
10:38:14
AM
11:16:57
AM
11:28:38
AM
11:31:49
AM
1:10:4224
1:11:532M
2:29:082M
3:02:542M
4:06:352M
4:07:082M
4:07:392M
4:08:082M
4:11:4024
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4:13:212M
4:13:392M
4:14:1324
4:14:372M
4:15:04
4:22:432M
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4:28:47
4:33:452M
4:38:4324
4:42:392M
4:44:142M
4:48:512M
4:52:5824
4:55:082M
4:59:352M
5:08:54FM
5:09:27
5:21:08 4
5:28:342M
5:36:572M
5:40:322M
5:44:2724
5:50:0624
5:57:17PM
6:00:23PM
7:47:212M
8:00:032M
8:01:312M
8:08:022M
8:08:5424
8:20:262M
9:50:172M
9:59:0224
11:29:032M
11:34:412M
11:46:532M
11:53:392M
1:13:31AM
1:17:08AM
1±19:02
AM
1:20:44
AM
1:21:16AM
1:23:31AM
1:26:53AM
1:28:31AM
1:29:04AM
1:30:56AM
1:31:15AM
1:34:19M
1:35:06AM
1:36:22AM
1:39:23AM
1:41:02AM
3500
32050
0
0
100
0
0
0
0
1200
5050
11000
32100
32600
5450
1200
2500
5200
9550
1350
250
1250
3850
9550
0
0
2900
0
0
650
0
200
0
1000
0
200
0
0
2800
0
1100
250
14700
200
1800
1800
2000
2500
250
500
78
605
23
8
15
75
7
5
24
50
58
138
338
47
99
56
56
73
115
38
85
171
104
153
7
9
65
2
3
131
5
54
4
23
15
7
15
19
113
43
14
40
154
81
36
7
11
11
16
7
7
59
0
0
0
0
0
0
0
2
8
19
58
60
9
2
5
10
18
5
0
5
8
21
0
0
6
0
0
0
0
0
0
4
0
0
0
0
9
0
3
1
19
0
3
3
3
5
1
2
89
757
17
0
25
0
0
0
0
42
117
257
859
920
103
20
90
159
259
54
22
51
58
179
12
25
35
0
0
21
17
34
0
40
0
25
23
0
115
0
42
29
182
4
18
18
56
116
22
27
158
1840
17
6
24
14
4
0
0
182
374
773
2465
2560
287
79
192
319
547
123
27
73
613
1069
20
32
133
0
2
26
17
35
5
91
7
22
25
3
304
3
107
29
6
28
3
4
47
105
55
45
1000
23
6
64
0
500
500
250
500
0
1350
9400
11950
3400
3200
10100
4300
4550
8700
0
0
4200
20100
4350
7550
9400
16300
14150
10450
2
5
9
12
55
10
43
191
282
87
74
259
88
113
252
34
9
169
446
84
159
209
318
388
171
6
8
10
11
2
2
2
20
40
8
20
38
12
21
39
0
0
8
34
9
23
42
76
102
119
64
108
135
159
27
27
15
288
706
68
177
479
170
230
418
3
3
72
586
51
221
518
1030
1418
1654
980402
980402
980402
980402
980402
980402
980402
980402
980402
980402
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980402
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980403
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980403
980403
980403
980403
980403
980403
980403
980403
980403
980403
FM
M
M
M
ip
address
of
player
id#
glum.media.mit.edu/18.85.25.34
tunnel-nt-endpoint-2.media.nmit.e-u/18.85.25.3
kirby.media.mit.edu/18.85.21.34
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nsl.ratgut.cunV204.96.52.22
pinotnoir.media.rit.edu/18.85.16.104
cooper.nedlia.mit.edu±/18.85.21.70
cooper.media.mit.e-u/18.85.21.70
cooper.nedia.mit.edu/18.85.21.70
cooper.adia.it.edu/18.85.21.70
cooper.edia.miit.edu/18.85.21.70
cooper.nedia.mrit.edu/18.85.21.70
753
754
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117
ooper.media.mit.edu/18.85.21.70
808
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166
229
254
65
65
39
1510
3854
140
458
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359
565
1200
19
20
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2497
313
965
2151
4423
6041
6973
cooper.media.mit.edu/18.85.21.70
ooper.media.nit.edu/18.85.21.70
cooper.edia.mit.edi/18.85.21.70
cooper.media.mit.edu/18.85.21.70
cooper.nia. it.edu/18.85.21.70
cooper.media.mit.edu/18.85.21.70
wireless-89.nedia.nit.edu/18.85.18.89
cooper.nedia.mit.edu/18.85.21.70
cooper.media.±it.edu/18.85.21.70
diversions.nedia.mit.edu/18.85.8.235
diversions.media.m±it.edu/18.85.8.235
diversionm.edia.mit.edlu/18.85.8.235
diversio.
divrosmedia.it.edu/18.85.8.235
diversions.edia.±it.edu/18.85.8.235
opr.nedia.mit.edu/18.85.21.70
cooper.media.mit.edu/18.85.21.70
wirles-23.mBlia.mit.edu/18.85.18.23
cooper.n±dia.mit.edu/18.85.21.70
cooper.media.rit.edu/18.85.21.70
cooper.nedia.ndt.edu/18.85.21.70
cooper.media.m±it.e-li/18.85.21.70
cooper.nedia.nit.edu/18.85.21.70
cooper.media.mit.edu/18.85.21.70
ooper.media.nit..tu/18.85.21.70
809
810
811
812
813
814
815
816
817
818
819
820
821
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824
825
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828
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madia.mit.edu/18.85.8.235
500
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frtiger
.ndia.mtit.edu/18.85.21.72
834
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24050
14500
10350
8950
29350
38650
2050
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27750
6550
22050
470
70
447
427
170
5369
387
287
106
130
394
179
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185
192
42
222
17
32
51
76
82
101
147
19
187
2401
2492
621
2903
378
718
733
517
620
804
1455
135
1836
9823
10153
3462
11892
595
1135
2613
1637
2137
2695
5220
659
5743
cooper.media.mit.edlu/18.85.21.70
cooper.media.m±it.edu/18.85.21.70
frutiger.media.mit.edu/18.85.21.72
cooper.nedia.±it.edu/18.85.21.70
frutiger.media.mit.edu/18.85.21.72
frutiger.nedia.mdt.edu/18.85.21.72
frutiger.nedia.rit.edu/18.85.21.72
cooper.ndia.mit.edu/18.85.21.70
7
cooper.media.mit.edu/18.85.21. 0
cooper.n±dia.mit.edu/18.85.21.70
±ooper.media.Rdt.edlu/18.85.21.70
kaze.nedia.mit.edu/18.85.5.79
oor.media.mit.edui/18.85.21.70
835
836
837
838
839
840
841
842
843
844
845
846
847
4950
98
198
1933
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cooper.n.dia.mit.edu/18.85.21.70
848
5250
15400
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6250
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152
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ooper.media.m±it.edu/18.85.21.70
kaze.media.mit.edu/18.85.5.79
cooper.media.mit.edu/18.85.21.70
frutiger.nedia.mit.edu/18.85.21.72
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frutiger.nedia.mit.edu/18.85.21.72
kaze.n9dia.mit.edu/18.85.5.79
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849
850
851
852
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856
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861
GLOM:Information Agglomerates
103
data
tim.
980403
980403
980403
980403
980403
980403
980403
980403
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980403
980403
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1:43:14 A84
1:48:31 AM
1:50:58AM
2:08:28AM
2:11:42AM
2:14:21AM
2:14:35AM
4:01:38AM
4:08:12AM
4:16:46AM
5:05:23AM
10:28:49
AM
11:20:44
AM
11:58:23
AM
12:26:232M
12:33:14
0M
12:34:05
8M
2:03:210M
3:21:250M
4:09:580M
4:11:58R4
4:14:350M
4:44:258M
5:58:38PM
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104
id#
date
time
score
duration
baddies
hits
shots
ip address of
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
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980407
980407
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980407
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980407
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980407
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980407
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980407
980407
980407
980407
980407
980407
980407
980407
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980407
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980407
980407
980407
980407
980407
980407
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980407
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980407
980407
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980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
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980407
980407
980407
980407
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980407
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980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
12:14:25 FM
12:16:47 2M
12:19:03
12:19:072M
12:24:37
FM
12:25:242M
12:30:4724
12:30:51
12:31:16
PM
12:31:56
PM
12:41:20PM
1:10:3724
1:11:32PM
1:27:17
1:29:282M
1:34:152M
1:35:16EM
1:38:0024
1:41:392M
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1:46:40O4
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1:50:40
1:51:46
1:51:53PM
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2:37:39M
2:39:41R4
3:17:47PM
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3:35:46
3:36:00FM
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4:10:15FM
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6:52:36PM
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8±06:05FM
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8:22:15PM
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8:27±42EM
8:34:50
8:57:30
8:58:45
9:32:542M
9:37:452M
9:44:13
10:04:28 2M
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10:06:4424
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ge.media.mit.edu/18.85.11.1
ge.media.mit. edu/18.85.11.175
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john-nir.mndia.mit.edlu/18.85.5.
nrkay.nedia.mit. edu/18.85.21.80
8 8
nekay.mndia.mit.edu/1 . 5.21.80
westham.media.mit. edu/18.85.16.53
gate04.nry.us. ihn.cc/198.133.22.21
joln-nuir.media.mit.edu/18.85.5.88
westhamnudia.mit. edu/18.85.16.53
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gate04.ny.us.ihn.<xan/198.133.22.21
gate05.ny.us.ihn.com/198.133.22.22
austin.ih cn.com/192.35.232.13
wstham.nedia.mit.edu/18.85.16.53
tachichold.nedia.mit.edlu/18.85.21.71
tschiclold.media.it.edu/18.85.21.71
tschichold.nedia.it.edu/18.85.21.71
co/198.133.22.37
gatelO.ny. us.hn.c
cm/192.35.232.115
s05.autin.ihn.
tschichold.nedia.it.edu/18.85.21.71
basquiat.nedia.mit.edlu/18.85.40.29
tschicold.nedia.nit.edu/18.85.21.71
207.92.110.134/207.92.110.134
tschichold.nedia.nit.edu/18.85.21.71
s05.austin.ihn.c/192.35.232.115
tschiclold.nedia.mint.edu/18.85.21.71
tschichold.media.nit.edu/18.85.21.71
tschichold.nedia.mit.edu/18.85.21.71
tschichnld.nediamit. edu/18.85.21.71
tschicold.nsedia.nit.edu/18.85.21.71
209.82.24.234/209.82.24.234
BUEBCK-315.MIT.EW/18.162.2.132
BLUEBC-3l5.MIT.EW/18.162.2.132
86
kgb.loc3.tandem.cc/l55.1 .76.114
dhep271.fh.tzw.cc,/140.171.177.87
dhcp271.fh.tzw.cmV140.171.177.87
7
7.87
dhcp271.fh.trw.cc±/140.171.1
dhcp271.fh.trw.ccW/140.171.177.87
ur14-18.provide.net/207.206.120.82
8
7
2
usrl4-18.provide.net/20
2 7 .206.120.
2 6
82
07 . 06 .120.
uro14-18.provide.net/
8
.20 .120.2
usr14-18.provide.net/20
usrl4-18.provide.net/207.206.120.82
tschichold.nedia.mit.edu/18.85.21.71
205.181.121.144/205.181.121.144
205.181.121.144/205.181.121.144
205.181.121.144/205.181.121.144
205.181.121.144/205.181.121.144
205.181.121.144/205.181.121.144
205.181.121.144/205.181.121.144
205.181.121.144/205.181.121.144
tschichold.media.mit.edu/18.85.21.71
205.181.121.144/205.181.121.144
205.181.121.144/205.181.121.144
205.181.121.144/205.181.121.144
205.181.121.144/205.181.121.144
205.181.121.144/205.181.121.144
tschichold.media. mit.edu/18.85.21.71
205.181.121.144/205.181.121.144
tschichold.media.mit.edu/18.85.21.71
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tchichold.media.mit. edu/18.85.21. 1
tschichold.media.it.eiu/18.85.21.71
tschichold.media.mit.edlu/18.85.21.71
tschichold.media.mit.edu/18.85.21.71
dyn-107-148.interval.canu/199.170.107.148
dyn-107-148.interval.com199.170.107.148
dyn-107-148.interval.o-n/199.170.107.148
205.181.121.144/205.181.121.144
205.181.121.144/205.181.121.144
205.181.121.144/205.181.121.144
dyn-107-119.interval.=cn/199.170.107.119
7
ppp-106-167.interval.can/199.170.106.16
dyn-107-242.interval.can/199.170.107.242
ppp-106-167.interval.ccan199.170.106.167
7
7
0.10.119
dyn-107-119.interval.canv199.1
7
pp-106-167.intral.can/199.170.106.16
dyn-106-120.interval.can/199.170.106.120
guilhamet-pc.interval.can/199.170.105.38
guilhamet-pc.interval.ca/199.170.105.38
dyn-105-53.interval.can/199.170.105.53
dyn-107-191.interval.caV199.170.107.191
dyn-107-100.interval.canV199.170.107.100
6 6
iris6.inteal.can/199.170.10
7. 2
9 7
. 9.1 2
1repc--10.uced.edu/132.23
FHD.MIT.EIJ/18.237.0.36
FHD.MIT.E[U/18.237.0.36
mHAVAKALI.MIT.EIU/18.237.0.39
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
GLOM:Information Agglomerates
player
8 8
sOl.
24
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
105
date
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980407
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980408
980409
980409
980409
980409
time
10:07:42 2M
10:14:212M
10:16:10 2M
10:17:18 2M
10:24:05 R4
10:27:18 PM
10:34:03 2M
10:35:06 P4
11:14:53
11:15:27FM
11:16:47 EM
11:19:03EM
11:40:45 2M
1:43:19 A14
2:16:25 AM
2:17:50 AM
2:20:56 AM
8:15:27 A14
8:17:30 AM
10:06:05 AM
10:30:53 AM
10:56:23 AM
11:05:36 AM
11:08:46 AM
11:09:47 AM
11:27:29 AM
11:31:54 A1
12:23:59 24
1:16:58
1:44:43 2M
2:43:46
2:45:08 24
2:48:57 2M
3:07:4724
3:19:09 24
3:21:17 2M
3:24:14 2M
3:32:43 PM
3:54:26 24
4:11:39 4
4:20:22 24
4:22:11 2M
4:25:12
4:25:27 2M
4:26:27
4:27:27 2M
4:29:5524
4:36:37 24
4:50:42 24
4:53:21 2M
4:58:07 24
5:00:16 24
5:02:11 2M
5:02:30 24
5:03:25 2M
5:05:20 2M
5:06:38 2M
5:12:54 PM
5:14:30 2M
5:25:44 2M
5:28:02 24
5:28:40
5:29:50 24
5:30:07 2M
5:31:21
5:32:43 EM
5:34:28 2M
5:52:06 PM
5:54:41 2M
6:08:29 24
6:20:24 2M
6:24:49 2M
6:26:28 FM
6:51:12 24
7:22:40 2M
7:23:37 2M
8:09:39 24
8:10:42 24
8:13:34 2M
8:14:55 2M
8:16:39 24
8:45:03 2M
8:55:13 2M
8:56:09 FM
8:58:01
8:59:40 2M
9:04:46 2M
9:05:50 M
9:09:54 FM
9:11:15 2M
9:15:45
9:25:40 PM
9:43:35 2M
10:00:10 24
10:35:44 24
10:40:11 2M
10:56:10 24
11:02:57 24
11:56:09 2M
11:57:07 2M
1:25:41A1
1:27:52 AM
1:28:49 AM
1:33:17 A1
M
M
M
M
M
M
M
M
M
score
2400
14650
2100
7600
7700
2400
100
1350
231100
600
3050
0
8050
500
0
0
5000
2300
5800
0
2100
6050
400
1500
0
2500
4850
16600
1600
1700
1550
2700
4750
200
4500
4500
1700
2950
2600
0
2100
3450
7800
4850
2650
1850
7900
8950
1350
3450
9950
500
3750
6950
200
10750
6150
13650
5950
15450
22300
600
50250
9100
1200
2250
10250
4350
2600
3750
35750
11200
2800
6750
1250
1000
2450
3600
3400
9150
2200
4650
3550
1450
3150
2000
2750
7250
3650
3100
9800
11600
0
0
1000
2500
12750
16000
1500
2300
750
5150
2200
14450
duration
baddies
58
440
87
161
233
217
54
54
66
19
65
15
98
7
13
75
171
54
107
1
59
166
6
62
32
121
249
174
130
86
122
68
212
45
195
115
34
401
200
81
68
93
1160
150
60
44
176
329
94
142
272
40
88
246
208
151
207
248
201
417
18
16
27
246
74
65
247
297
139
75
279
442
64
82
94
41
169
142
147
296
57
108
112
41
97
84
436
355
100
64
255
312
33
124
161
216
317
392
38
43
47
117
40
391
17
37
4
56
14
4
0
5
380
381
386
386
14
2
0
0
13
4
14
0
6
13
0
1
0
10
27
30
3
2
3
13
26
0
9
22
4
6
4
0
8
19
16
37
21
27
18
37
3
9
30
2
11
46
0
18
13
64
14
33
37
38
83
54
4
9
78
13
5
8
66
25
7
13
5
4
7
7
8
31
7
13
7
3
7
7
11
14
6
11
23
25
0
0
4
10
24
32
6
4
3
9
4
30
GLOM:Information Agglomerates
hits
133
518
25
775
146
24
2
63
2476
2484
2555
2555
168
27
0
0
114
28
144
0
80
177
8
24
3
107
257
237
35
27
22
112
251
6
77
217
39
39
33
1
62
187
194
333
270
357
132
282
37
84
336
42
161
528
21
263
136
489
81
406
225
247
536
616
56
119
807
86
34
45
775
371
112
137
43
74
80
47
80
194
58
120
103
23
39
108
96
429
37
97
187
273
0
48
48
118
380
492
67
28
34
70
57
385
address
of player
shots
ip
979
1245
59
1832
496
143
11
121
350
401
749
749
337
46
0
2
858
105
319
0
148
300
0
7
7
182
658
500
119
67
315
846
2213
42
319
712
76
420
157
7
205
460
1029
938
1232
1445
253
605
184
659
1632
106
334
2631
43
892
269
1030
288
2800
24
97
34
4208
244
422
5607
365
450
227
1009
1723
226
329
537
214
483
155
309
2802
178
298
189
79
95
190
380
1397
174
174
744
767
1
15
330
927
927
1323
389
101
57
194
75
1050
FHD.MIT.EIJ/18.237.0.36
GIAVAKALI.MIT.E2/18.237.0.39
dyn-106-105.interval.cam/199.170.106.105
CHAVAKALI.MIT.EJ/18.237.0.39
HIT0DIMENSICN.MT.EDJ/18.237.0.97
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209.143.210.201/209.143.210.201
209.143.210.201/209.143.210.201
7
9
eisner.media.mit.ou/18.85.21.
eisner.media.mit.edu/18.85.21.79
7
9
eisner.nedia.mit.edu/18.85.21.
79
eisner.nedia.mit.edu/18.85.21.
tunnel-nt-endpoint-2. media. mit. edu/18. 85.25. 3
tunnel-nt-endpoint-2.nedia.mit.edu/18.85.25.3
henul.gmp.usyd.edu.au/129.78.231.120
homul.gnp.usyd.edu.au/129.78.231.120
78 3
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heaul.gnp.usyd.edu.au/129.
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uest225.graypeak.cnV208.224.1
host225.graypeak.con/208.224.166.225
nordine.nog.onV207.70.119.85
canel.netgen.cn/206.33.100.28
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bos-nM8-03.ix.netccmn.can/199.183.202.
8 8 6
leggett.media.it.eu/1 . 5. .156
ruislip.media.mit.edu/18. 85.16.222
ruislip.nedia.mit.edu/18.85.16.222
gesturalia.neia.mit.edu/18.85.21.59
gesturalia.nedia.mit.edu/18.85.21.59
tschichold.media.mit.edu/18.85.21.71
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Ntickenson.studioarchetype.o-n/19 . 1.6. 1
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lib7.jts.put.k12.ne.us/169.24 .10 .9
dia1147.panam. c-ccm.net/204.95.131.177
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h23.s3.ts31.hinet.net/163.31.3.23
tschichold.nedia.mit.edu/18.85.21.71
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BLAZIrf-TRAIL.MIT.EI0/18.251.2.96
B1AZ89--TRAILMT.2EJ/18.251.2.96
tntl-166.HiWAAY.net/208.147.147.166
8[AZIn-7RAIL.MT.mEJ/18.251.2.96
tnt-166.HiWAAY.net/208.147.147.166
tntl-166.HiWAAY.net/208.147.147.166
205.181.121.144/205.181.121.144
205.181.121.144/205.181.121.144
198.104.40.27/198.104.40.27
198.104.40.27/198.104.40.27
198.104.40.27/198.104.40.27
eucalyptus.pingsite.cnV205.216.250.100
eucalyptus.pingsite.ccnV205.216.250.100
198.104.40.27/198.104.40.27
nox1-190.public.uni-hurg.de/134.100.43.190
tschichold.media.nit.edu/18.85.21.71
ElS340-08.ece.utexos.eduL/146.6.101.158
205.181.121.144/205.181.121.144
2 6
ww.taiwanshopping.co/' 0 .149.145.168
205.181.121.144/205.181.121.144
cooper.media.it.edu/18.85.21.70
cooper.media.mit.edu/18.85.21.70
8
nrkay.nodia.mit.edu/18.85.21. 0
205.181.121.144/205.181.121.144 7
dialup05.kortrijk.eunet.be/193. 4.5.5
dialup05.kortrijk.eunet.be/193.74.5.5
205.181.121.144/205.181.121.144
etc7-71.flash.net/208.194.201.71
etc7-71.flash.net/208.194.201.71
1ego.ftp.ccV/128.127.125.56
bos-m8-03.ix.neto.ooWl99.183.202.67
h15.s2.to3l.hinet.net/163.31.2.15
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frutiger.media.mit.edu/18.85.21. 2
134.54.1.16/134.54.1.16
134.54.1.16/134.54.1.16
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unknown-123-168.evolveinc.cnV9
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172-20-34.ipt.ol.ccaV152.1
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unnlon-123-168.eoolveinc.ccn/198.
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dyn-107-157.interval.c/199.1 0.10 .157
klai.ee.StCloudstate.edu/199.17.39.249
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klai.ee.StCloudState.edu/199.1 . .
klai.ee.StCloudstate.edu/199.17.39.249
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89.249
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3 68
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unknon-123-168.olveinc.can/19
lveinc.oa198.70.123.168
unknown-123-168.eo
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unknow-123-168.eolveinc.caVl9B.
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adsh2-125.flash.net/209.30.92.125
7
4
lostl2.tntl4.nyc3.da.uu.net/153.3
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1Cot12.tnt14.nyc3.da.uu.net/153.37.142.12
CHAVAKALI.MIT.EDUl/18.237.0.39
CHAVAKALI.MIT.EIU/18.237.0.39
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157.dallas-02.tx.dial-access.att.net/12.
157.dalla-02.tx.dial-access.att.net/12.67.1.157
mtrix.meodia.mit.edu/18.85.23.44
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pc-33516.on.rogers
106
id#
date
time
score
duration
baddies
hits
shots
ip address of player
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980409
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
980410
1:44:23 AM
1:54:57AM
2:48:10AM
2:53:36AM
3:25:42AM
3:29:37AM
3:35:51AM
4:40:00AM
5:09:54AM
5:54:43AM
8:49:408M
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s24-prn35.nwoestsac.carrpu.nci.net/20
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baddies
hits
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1393
1395
120
1035
16
387
176
252
275
50
96
242
793
181
205
477
583
419
905
180
280
137
345
857
66
130
444
131
frutiger.nodia.dt.edu/18.85.21.72
frutiger.nodia.mit.edu/18.85.21.72
18.85.14.163/18.85.14.163
frutiger.nedia.mit.edu/18.85.21.72
2 72
frutiger.nedia.mit.edu/18.85. 1.
18.85.14.163/18.85.14.163 7
futiger.media.mit.eu/18.85.21. 2
207.113.114.70/207.113.114.70
3
7 4
7
.15 .16
proxy.xpnse.canV20
7
99 .
.170.10.250
dyn-107-250.interval.can/l
anarmth.lyn.net/207.150.17.10
204.179.66.99/204.179.66.99
anarmnth.lyn.net/207.150.17.10
204.179.66.99/204.179.66.99
c2p18.dialin.iupui.edu/134.68.241.68
206.129.250.168/206.129.250.168
206.129.250.168/206.129.250.168
207.15.215.155/207.15.215.155
207.15.215.155/207.15.215.155
207.15.215.155/207.15.215.155
6
slip-32-100-52-146.no.us.ihn.net/32.100.52.14
slip-32-100-52-146.no.us.ihn.net/32.100.52.146
46
32
slip-32-100-52-146.no.us.iin.net/ 7 .100.52.1
sciroco.ndia.mit.edu/18.85.5.8
diall5.gtn.net/207.176.194.115
stornlp07.storn.ca/207.245.246.7
7
stornO1p07.storm.ca/207.245.246.
7
sto0xO1pO7.storm.c/207.245.246.
dial15.gtn.net/207.176.194.115
stormnlpO7.stonn.ca/207.245.246.7
diallS.gtn.net/207.176.194.115
2 6
usr8-dialup34.mix2.Boston.nci.net/166.55.68. 2
diall5.gtn.net/207.176.194.115
stornOlp07.storm.ca/207.245.246.7
6 7
7
.245.24. 66
ston31p07.storm.ca/20
8
.55.6.226
usr8-dialup34.mix2.Boston.±ci.net/1
6 7
7
.245.24.
stonrJlp07.storn.ca/20
6 8 26
.2
usr8-dialup34.mix2.Boston.nci.net/166.55.
stornOlp7.storm.ca/207.245.246.7 6 8 6
.22
usr8-dia1lup34.mix2.Bosto.nci.net/166.55.
198.104.40.27/198.104.40.27
7
6.194.115
dial15.gtn.net/207.1
stornDlp07.ston.ca/207.245.246.7
198.104.40.27/198.104.40.27
7
stonOlpO7.storn.ca/207.245.246.
ascend104.lkdllink.net/206.10.52.153
77
pn±2-p77.Bayu.CM/208.143.113.
oak-usr4-31-31.dialup.slip.net/209.152.137.31
204.245.216.16/204.245.216.16
1Cust88.nex48.chicago.il.m.uu.net/153.35.122.88
204.245.216.16/204.245.216.16
204.245.216.16/204.245.216.16
c020h153.ipchom.reed.edui/134.10.20.153
torl-30.uninet.net.nx/200.38.205.30
1Cust112.tnt2.key1.da.uu.net/208.250.180.112
kit-onl-18.netccom.c/207.181.77.82
p134.sunbeach.net/205.214.199.156
202.186.53.130/202.186.53.130
cc1007196-a.bwrd1.nd.hoe.ccrtV24.3.17.161
2 2
0 .191.50
rsP-naxl-50.grin.net/208.
ppp-ne~x1-50.grin.net/208.202.191.50
cc1007196-a.hwrd1.nd.hcne.cc±/24.3.17.1618
1Cst98.tnt4.seal.da.uu.net/208.253.68.9
93
6
7
.1 .210.2
pop-477.tig.can.au/207.214.7.222
3
5
ts3-5.slip.uwo.ca/129.100.99.2
indigo22.arsc.edu/137.229.75.122
indigo22.arsc.edu/137.229.75.122
HAlems-0C.MIT.EINJ/18.236.0.21
HAltWS-C.MIT.EI0J/18.236.0.21
HANNAS-P.MIT.EDUL/18.236.0.21
ibb0233.ibb.ruu.nl/131.211.124.233
203.38.133.103/203.38.133.103
i0233.ibb.ruu.nl/131.211.124.233
203.38.133.103/203.38.133.103
203.38.133.103/203.38.133.103
203.38.133.103/203.38.133.103
203.38.133.103/203.38.133.103
1279
1280
1281
1282
1283
1284
1285
1286
1287
1288
1289
1290
1291
1292
1293
1294
1295
1296
1297
1298
1299
1300
1301
1302
1303
1304
1305
1306
1307
1308
1309
1310
1311
1312
1313
1314
1315
1316
1317
1318
1319
1320
1321
1322
1323
1324
1325
1326
1327
1328
1329
1330
1331
1332
1333
1334
1335
1336
1337
1338
1339
1340
1341
1342
1343
1344
1345
1346
1347
1348
1349
1350
1351
1352
1353
1354
1355
1356
1357
1358
1359
1360
1361
1362
1363
1364
1365
1366
1367
1368
1369
1370
1371
1372
1373
1374
1375
1376
1377
1378
1379
1380
1381
1382
M
M
M
M
M
M
M
M
M
M
M
M
M
GLOM:Information Agglomerates
ppn-207-193-210-26.hstntx.swb~ell.net/20
s176.odopool.kth.se/130.237.37.102
s176.noudpool.kth.se/130.237.37.102
cvap08.nada.kth.se/130.237.218.77
3 24 4 36 4
0.7 .2 . 1
dialup236-1-41.swi-net.e/1
2
xtsd0412.it.wu.edu/134.121.3.
143.233.119.38/143.233.119.38
ppp-9.ts-1.pro.idt.net/169.132.225.9
}opkins.cs.jyu.fi/130.234.49.78
pythia-Epp10.ccf.auth.gr/155.207.1.234
pythia-pP10.ccf.auth.gr/155.207.1.234
pni62-32.inage.dk/194.234.60.96
199.6.62.21/199.6.62.21
199.6.62.21/199.6.62.21
patricke.ne.medione.net/24.128.52.89
tc1-23.utah-inter.net/208.14.200.33
tcl-23.utah-inter.net/208.14.200.33
tcl-23.utah-inter.net/208.14.200.33
cx51872-a.alsvl.occa.han.can24.1.166.129
cx51872-a.alsvl.oca.me.can±/24.1.166.129
slcl20h.nolen.xmission.can/166.70.9.120
4
3
47
.25 .5.
ppp-ft12-47.netrox.net/20
pi-ft12-47.netrox.net/204.253.5.47
oak-alg-gw2-2.ncal.verio.cn/207.21.138.65
ok-alg-gw2-2.ncal.verio.can207.21.138.65
oak-alg-gw2-2.ncal.verio.cn/n207.21.138.65
.gatech.edu/130.207.239.10
0310ECE010.ecn
108
date
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980411
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980412
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
time
3:11:32 O4
3:17:23 O4
3:55:44
5:03:42
5:14:450M
5:37:15OM
5:38:41OM
5:58:58OM
6:01:31
7:28:11
8:00:55
8:03:25
8:07:32OH
8:14:46
8:55:10
9:03:02
9:17:46
9:19:17
9:21:21
10:32:35OM
10:44:40OM
10:53:40OM
11:24:09OM
11:26:36OM
11:28:29OM
OM
11:58:15
11:59:53OH
12:02:25AM
12:03:07A14
1:04:37AM
1:04:59AM
1:06:23AM
1:08:09AM
1:10:26AM
1:12:39AM
4:18:03AM
6:19:31AM
6:37:44AM
9:12:58AM
9:19:19AM
9:29:30AM
9:42:09AM
AM
10:37:14
AM
10:46:28
AM
10:46:44
12:02:03
1:12:55 OH
1:15:50 OH
1:23:45OH
1:3110 OH
1:42:14
1:43:46OH
3:49:24OM
3:56:36OM
4:00:03OM
4:01:18O
4:06:59OH
5:36:44OM
5:38:24OM
6:33:03OM
7:08:08OM
7:51:40OM
7:55:53
7:58:12
7:59:03OH
7:59:09OM
8:48:34OM
8:52:03OM
8:55:33OM
9:01:31
9:22:54 OM
9:29:09M
9:33:29 OH
9:39:46
9:42:14
9:49:06
9:51:20
10:10:50
10:15:11
10:15:32OM
10:19:54OM
10:27:49OH
10:30:01
10:32:41OH
10:41:55OH
10:53:50OM
11:05:19
11:18:37
OM
11:26:57
11:36:22
11:39:48
11:50:23
11:55:49M
AM
12:02:49
12:20:29
AM
AM
12:21:51
AM
12:23:58
AM
12:25:02
AM
12:28:40
12:34:59
AM
AM
1:02:05
AM
1:06:18
AM
1:09:32
AM
1:13:24
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
score
3100
8800
2950
3550
4050
3850
3850
3000
6200
3050
5300
4850
11400
2550
8600
9700
2000
2450
2250
7300
3400
7650
3550
2650
600
3250
2750
0
10400
19250
0
900
500
3750
750
5700
3200
3000
5200
29950
100
3100
5050
850
7100
5100
650
4550
1000
3200
4750
3000
5800
0
3400
17300
14100
100
2550
7850
2050
5750
2850
1900
10250
8650
3750
7600
7400
15350
2000
800
4050
8950
0
21550
600
7750
3650
7900
4750
2500
6250
9300
20050
10050
13600
27050
13050
8700
5850
10850
10050
9200
13850
3000
5600
2900
7250
14850
3200
8400
6650
18100
duration
111
333
202
99
08
136
58
50
138
138
201
261
293
105
359
456
103
57
85
242
252
528
97
181
52
117
81
1
342
950
128
67
89
118
58
200
227
122
167
623
50
50
211
50
224
243
91
159
106
99
211
75
471
143
262
449
325
96
83
260
213
162
84
163
227
152
95
194
266
549
164
76
217
612
195
523
268
236
394
263
206
59
116
145
776
315
582
773
475
323
190
387
273
394
406
63
159
161
261
363
46
212
179
299
GLOM:Information Agglomerates
baddies
6
19
6
7
10
8
7
5
13
11
12
11
23
6
19
20
5
5
4
18
8
25
8
5
2
6
5
0
22
48
0
1
2
15
1
12
7
6
13
52
0
5
11
2
15
13
1
12
2
5
13
9
20
0
13
35
38
0
9
16
4
13
10
3
20
16
8
15
14
28
8
3
9
31
0
80
2
14
12
14
12
4
13
20
70
31
46
100
41
20
15
28
19
18
54
12
14
6
15
35
7
18
11
30
hits
38
144
40
48
58
116
47
30
137
130
132
64
404
45
166
285
49
31
45
132
51
197
65
84
29
41
38
0
281
559
7
12
35
92
9
135
104
44
104
728
2
35
101
11
156
106
7
122
17
81
139
116
184
13
136
485
357
2
102
189
33
94
96
20
262
179
49
136
210
453
90
65
83
229
8
475
59
171
135
170
133
29
105
177
433
233
304
579
302
237
149
222
204
224
317
94
144
34
189
452
80
204
190
424
shots
206
491
193
233
174
497
261
90
401
378
470
234
753
80
740
1003
212
121
138
451
316
1477
111
154
47
131
101
0
712
3050
21
31
166
281
69
397
396
269
500
1593
10
88
299
29
321
449
36
308
58
183
479
365
1839
17
355
1075
999
76
406
457
158
299
223
41
556
344
177
359
819
1708
117
151
309
1969
87
2446
68
462
1134
383
704
89
289
375
6605
2463
3492
8175
2619
1647
882
2162
1072
1266
1778
367
851
318
1264
2125
193
810
619
1983
id#
1383
1384
1385
1386
1387
1388
1389
1390
1391
1392
1393
1394
202-218-168.ipt.ol.com152.202.218.168
23 2 2 4 8
1395
. .
1396
power.cocon.kiev.ua/195.5.24.194
1397
chicago.il.ne.uu.net/153.35.122.55
lCust55.nex48.
1398
1Cust55.nex48.chicago.il.ms.uu.net/153.35.122.55
1399
p2-30.z016.glo.be/206.48.181.94
2
1400
p -30.zo016.glo.be/206.48.18.94
1401
p2-30.z016.glo.be/206.48.181.94
1402
ts003d17.ksc-o.oncentric.net/206.173.129.77
1403
fctntsOlc43.nbnet.nb.ca/198.164.201.49
8 6 2 01 49
1404
.14. .
fctntsOlc43.ntnet.nb.ca/19
1405
-stancu.tel.insa-lyn.fr/134.214.61.117
8 98
05 2
1406
. 11. . 8
nexl-34.netinc.ca/2
1407
nex1-34.netinc.ca/205.211.8.9
1408
206.101.127.92/206.101.127.92
1409
206.101.127.92/206.101.127.92
1410
ppp-x9-1.ecn.purdue.edu/128.46.112.1
1411
dd45-248.dlub.ccupuserve.ccnV199.174.177.248
1412
205.181.121.156/205.181.121.156
1413
175-240-253.ipt.aol.com/x152.175.240.253
7
4 2 3
1414
5.20. 5
175-240-253.ipt.ol.ccan/152.1
1415
175-240-253.ipt.aol.ccm/152.175.240.253
7 24 2 3
1416
5. 0. 5
175-240-253.ipt.ol.ccm/152.1
1417
175-240-253.ipt.aol.can/152.175.240.253
1418
hh2133062.direepc.ccn/207.168.133.62
1419
pC19E9562.dip.t-enline.de/193.158.149.98
1420
user33-i.erlangel.netsurf.de/194.163.170.225
1421
pve-pn3-4-200.harborcan.net/208.4.184.200
1422
glum.media.mit.edu/18.85.25.34
1423
shaw.c/24.64.141.94
cybers141d94.nt.wave.
1424
195.67.46.122/195.67.46.122
1425
p>92.vif.ccn207.219.108.92
1426
p>92.vif.<m207.219.108.92
7
4
1427
.10
pn11040.teleccan.alles.or.jp/203.139.9
1428
dialup46.tnt0O.livenet.net/206.156.31.47
1429
dia1151.bway.net/205.198.117.151
9
7
1430
8.11.151
dial151.bwy.net/205.1
1431
BAA.MIT.E[U/18.241.1.64
1432
BAA.MIT.E[/18.241.1.64
1433
Tl-Aviv-194-180.access.net.il/192.116.194.180
1434
Tel-Aviv-194-180.access.net.il/192.116.194.180
1435
BETSYM.MIT.E[U/18.63.1.89
6
1436
pop-annex-0614.t1.total.net/205.236.55.9
1437
E[U/18.63.1.89
BEISYM.MIT.
1438
nO105h038.thezane.net/198.165.105.38
1439
n105h038.thezone.net/198.165.105.38
1440
slipl39-92-12-152.Ssn.de.ihn.net/139.92.12.152
1441
slipl39-92-12-152.hm.de.ihn.net/139.92.12.152
50
7
8
1442
.2
2.12
207-172-128-250.s59.as4.col.erols.cc/207.1
1443
gate5.ca.us.ihn.ccn/198.133.22.211
1444
pp4a.nerlin.net.au/203.20.229.132
1445
pp4a.nerlin.net.au/203.20.229.132
1446
idthrandir.uced.eclu/132.239.58.106
1447
po4a.nerlin.net.au/203.20.229.132
32
1448
jpp4a.nrlin.net.au/203.20.229.1
6
6 2 27
1449
.55.9. 7
usr12-dialup35.mix2.Bostn.ni.net/16
1450
usrl2-dialup35.mix2.Boston.oni.net/166.55.69.22
1451
igarashi.nedia.mit.edu/18.85.21.69
7
1452
usr12-dialup35.mix2.Boston.nci.net/166.55.69.22
1453
LFSH.MT.EJ/18.98.0.249
1454
LFSHEN.MIOT.H/18.98.0.249
1455
ts0310.powep.ccm.au/203.18.83.106
1456
LFMEN.MIT.E[/18.98.0.249
1457
dt083n5d.san.rr.coc/204.210.25.93
1458
LFSOEN.MIT.lE[/18.98.0.249
7 7 2 3 3 22
1459
erols.can207 .17 .1 3 3 .1 22
207-172-133-122.s59.as22.ol.
1460
.12.1 .1
207-172-133-122.s59.as22.ml.erols.om/20
1461
LFSHEN.MIrT.EIJ/18.98.0.249
207-172-133-122.s59.as22.col.erols.can/207.172.133.1221462
1463
LFSHEN.MIT.EI2J/18.98.0.249
1464
EE3 .MIT.E[LJ/18.207.0.48
1465
EI/18.207.0.48
EERKi.MIT.
1466
BEN37.Mr.EI./18.207.0.48
1467
LFOIEN.MIT.3EIJ/18.98.0.249
1468
EDJ/18.98.0.249
LFS-hEN.MIT.
1469
LFSHEN.M.IET.EIJ/18.98.0.249
1470
LFSHEN.MIT.EJ/18.98.0.249
1471
E[J/18.98.0.249
LFSHEN.MT.
1472
LFSHEN.MIT.ME[/18.98.0.249
1473
LFSHEN.MIT.EJ/18.98.0.249
1474
LFSHM.MIT.E[I/18.98.0.249
1475
LFSHEN.MT.E[2/18.98.0.249
1476
LFSHEN.MIT.E3J/18.98.0.249
1477
coosbay4-35.transport.cnrr/209.51.87.35
1478
coosbay4-35. transport.co/209.51. 87.35
1479
69
igarashi.media.mit.eu/18. 85.21.
1480
coosbay4-35.transport.can/209.51.87.35
1481
igarashi.media.mit.edu/18.85.21.69
1482
igarashi.ndia.mit.edu/18.85.21.69
1483
cooper.mdia.miit.edu/18.85.21.70
2 6
8
1484
1.
9
.85.
igarashi.media.oit.edu/1
1485
igarashi.nedia.it. edu/18.85.21.69
1486
ooper.media.m±it.edu/18.85.21.70
ip address of player
bbd1-s5.nt1.colba.net/209.89.92.15
bhdl-s5.ntl.colba.net/209.89.92.15
noder63.kimanet.ccWrn208.6.38.170
pdx94-b48-45.teleport.crn/198.106.152.123
ap-08.netexpress. ee/194.204.2.138
FHD.MIT.EIUJ/18.237.0.36
FHD.MIT.EIJ/18.237.0.36
dreams.media.mit. edu/18.85.21.31
dreams.media.it.edu/18.85.21.31
ts3ip112.cadvision.ccm207.228.66.112
rpp-2-48.infanie.be/212.232.2.48
pp-2-48.infonie.be/212.
109
date
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
980413
time
1:17:39 AM
1:24:00 AM
1:53:56AM
1:59:06AM
2:03:35AM
2:07:42AM
2:21:34AM
2:23:19AM
2:30:27AM
2:37:33AM
2:42:46AM
2:53:56AM
3:19:06AM
4:42:38AM
4:45:58AM
4:48:11AM
4:52:00AM
4:53:56AM
4:58:47AM
4:59:29AM
5:09:56AM
5:11:50AM
5:21:31AM
5:24:55AM
5:51:37AM
5:52:51AM
5:54:09AM
5:55:42AM
6:00±43AM
6:06:33AM
7:51:50AM
8:37:27AM
9:40:23AM
9:43:21AM
9:45:41AM
9:46:07AM
9:47:21AM
9:47:41AM
9:48:50AM
9:49:27AM
9:49:39AM
9:54:17AM
9:56:02AM
9:56:26AM
9:57:19AM
10:01:57
AM
AM
10:32:41
AM
11:27:29
11:35:10
AM
1M
12:06:04
12:33:15
EM
12:39:24
R4
R4
12:40:56
12:44:342M
EM
12:46:20
12:47:42
RM
12:49:26
EM
12:50:26R4
12:53:15 PM
12:59:208M
1:15:071M
1:19:251M
1:43:362M
2:02:13EM
2:27:122M
2:46:252M
2:49:47
2:50:47PM
3:13:582M
3:16:30
3:19:12PM
3:22:442M
3:24:5124
3:29:17R4
3:29:322M
3:31:182M
3:38:392M
3:42:352M
3:47:312M
3:50:522M
3:50:552M
4:05:002M
4:31:562M
4:33:462M
4:38:032M
5:56:18
6:00:10m
6:00:482M
9:39:322M
9:41:4024
R4
10:02:39
10:04:064
10:06:09
10:13:07
10:13:48
10:15:212M
10:20:542M
10:23:452M
R4
10±53:06
10:55:4224
10:58:592M
11:02:2324
11:05:152M
11:07:362M
M
M
M
M
M
M
score
18350
11050
4500
9000
7250
9050
29700
4100
12750
21400
13400
23450
10200
3750
12250
8350
3600
9650
21500
12800
4600
33550
1050
7450
11200
4600
5050
4750
12200
26200
0
11100
2500
2400
4850
850
2550
4150
2650
3650
4000
6750
6200
1100
4350
5350
8400
4250
10200
5500
400
2350
2000
2500
3500
3500
3700
1200
5450
700
1750
4750
7850
750
50
50
7750
3400
4250
3700
3800
18500
4800
11450
4500
3950
7050
3750
4650
7350
8550
3150
3000
3000
0
4300
2000
3250
27250
0
5350
1000
3150
2400
3450
4200
9750
350
3750
7850
10700
10050
9150
7150
duration
240
256
133
283
252
227
678
131
330
411
297
649
186
167
263
118
44
261
259
316
73
727
47
187
121
60
63
78
286
338
49
411
63
77
104
89
85
104
73
89
185
262
225
75
166
262
405
160
446
102
113
152
211
59
91
65
88
45
153
176
115
273
329
95
16
60
900
241
366
135
160
887
228
302
532
372
424
220
95
274
190
476
281
149
11
86
51
116
551
2
71
68
200
165
229
119
263
80
107
141
180
188
156
125
GLOM:Information Agglomerates
baddies
31
19
9
22
14
20
53
10
24
42
24
43
25
8
29
18
7
23
33
22
10
67
3
14
19
8
9
12
21
44
0
20
7
4
11
3
4
11
4
9
14
18
13
3
9
13
21
8
20
15
1
8
4
4
7
7
7
2
13
2
7
12
23
3
0
0
19
8
9
7
14
47
10
24
9
8
17
8
11
15
18
6
5
5
0
7
3
7
44
0
13
4
7
4
8
9
23
0
8
14
20
19
16
14
hits
434
306
82
218
143
200
785
75
339
525
328
533
240
59
333
179
84
229
489
318
73
928
21
140
273
100
148
146
299
637
0
307
58
27
82
55
31
112
29
83
122
169
80
28
68
88
173
59
334
139
8
63
30
29
45
40
44
31
212
17
79
104
189
47
1
1
194
44
61
44
114
489
67
364
103
50
102
45
83
155
166
40
30
43
0
114
22
61
760
0
139
83
76
25
47
54
215
18
53
178
283
276
233
122
shots
1515
1097
116
392
457
369
4032
473
1629
1983
1452
3459
1087
275
1413
605
175
1778
2121
1758
619
5712
104
299
770
229
266
421
2359
2629
0
2364
298
241
285
127
152
470
138
506
541
826
138
76
283
1001
1677
248
1171
245
81
666
89
105
188
194
241
52
733
34
251
1634
3459
357
2
46
1156
226
231
136
340
3893
106
654
828
156
261
95
182
511
380
244
849
597
1
174
42
536
4837
0
320
164
237
115
228
156
441
121
133
313
544
502
426
312
id#
1487
1488
1489
1490
1491
1492
1493
1494
1495
igarashi.media.mit.edu/18.85.21.69
1496
igarashi.mdia.miit.edu/18.85.21.69
6
1497
9
igarashi.nedia.mit.edu/18.85.21.
1498
igarashi.nedia.mit.edu/18.85.21.69
1499
igarashi.media.mit.edu/18.85.21.69
1500
wildcazd.strong-fund.cc/204.154.227.254
1501
igarashi.miedia.dit.edu/18.85.21.69
1502
igarashimedia.mit.edu/18.85.21.69
7
1503
0
cooper.ndia.mit.edu/18.85.21.
1504
igarashi.media.mit.edu/18.85.21.69
1505
cooper.ndia.idt.edu/18.85.21.70
1506
igarashi.media.mit.edlu/18.85.21.69
7
1507
0
coopr.ndia.mit.edu/18.85.21.
1508
igarashi.nedia.nt.edu/18.85.21.69
1509
195.188.152.12/195.188.152.12
1510
195.188.152.12/195.188.152.12
1511
cooper.nedia.nit.edu/18.85.21.70
1512
cooper.ndia.mit.edu/18.85.21.70
1513
cooper.nedia.mit.edu/18.85.21.70
1514
ooper.nedia.mit.edu/18.85.21.70
8 2 7
1515
5. 1.7 0
cooper.nodia.dt.edu/18.
1516
cooper.media.mit.edu/18.85.21. 0
1517
t6o48p21.telia.canVl95.198.255.81
1518
igarashi.nedia.mit.edu/18.85.21.69
88
98 2 2 77
1519
. 0 .177 .18
hapc45.hmeaccount.can/l
1520
hapc45.meounot.omV198.202.1 .18
1521
c
t.can/198.202.177.188
hapc45.hc
1522
dialin30.hamilto.globalserve.net/209.90.138.93
88
98 2 2 77
1523
hapc45. nreaccount.can/l . 0 .1 .1
1524
hapc18.hnsaccount.can/198.202.177.128
1525
hapc45.nteacount.mn/198.202.177.188
1526
hapc18.1tneaccount.can/198.202.177.128
1527
dialin30.hamiltno.globalserve.net/209.90.138.93
1528
dialin3.hailton.globalerv.net/209.90.138.93
1529
hapc19.hunmaccomt.mn/198.202.177.129
1530
193.167.166.62/193.167.166.62
1531
.net/209.90.138.93
dialin30.hanilton.globale
1532
dialin3O.hiailtmo.globalserve.net/209.90.138.93
1533
205.181.121.144/205.181.121.144
9 7
1534
pc-1933.cn.rogero.wave.ca/24.112.4 9 . 72
1535
pc-1933.cn.roger.iave.ca/24.112.4
2 28
97 . 2
1536
.1
opo75a.nrlin.net.au/203.20.
1537
tolinen.tdb.uu.se/130.238.136.138
1538
dig01-34.can.sota-oh.cca/209.190.83.37
1539
204.62.44.150/204.62.44.150
1540
204.149.86.2/204.149.86.2
1541
204.149.86.2/204.149.86.2
1542
204.149.86.2/204.149.86.2
1543
204.149.86.2/204.149.86.2
1544
204.149.86.2/204.149.86.2
1545
204.149.86.2/204.149.86.2
1546
dt030n31.san.rr.com/204.210.19.49
1547
pete.nntevideo.can.uy/207.3.115.131
1548
xcurrmt-proxy.njec.ccm/165.254.249.17
1549
xcurrost-proxy.njec.can/165.254.249.17
1550
209.2.60.60/209.2.60.60
0 5 89 2 10
1551
.1 . .5
actor.conveyor.ccm/2
1552
nbalab2-dhcp-gsb--dynamic-182.Stanford.EIU/171.64.223.182
1553
fctntsl0c43.nhnet.nb.ca/198.164.201.241
1554
host-040.rumrec.ccm/207.181.124.40
1555
131.156.20.39/131.156.20.39
1556
131.156.20.39/131.156.20.39
1557
molette.tau. edu/165.91.218.5
1558
tc3-41.utah-inter.net/208.14.202.51
1559
hapc19.h-neaccount.can/198.202.177.129
7
1560
port197.ster.prodigy.net/204.237.138.19
1561
mimolette.tanm. eu/165.91.218.5
1562
hapc19.hnaccount.com198.202.177.129
1563
hapc19.hcnoaccont.aon/198.202.177.129
1564
hapc19.hneraccount.cc/198.202.177.129
1565
port197.str.prodigy.net/204.237.138.197
1566
/208.225.65.92
1567
port197.ster.prodigy.net/204.237.138.197
3
1568
ugsparc3.eeag.tornto.edu/128.100.1 .53
7
1569
xcurrent-poxy.njec.ccml65.254.249.1
1570
194.215.211.28/194.215.211.28
22
8 8
1571
. 5.5. 1
noe2g.ndia.oit.edu/1
1572
du79-2.ppp.algonet.se/195.100.2.79
1573
host-040.rmercn.ccW/207.181.124.40
1574
198.178.150.240/198.178.150.240
7
1575
0.123.168
unknon-123-168.o1lvinc.<xn198.
1576
p;s1-27.shaohw.net/209.4.39.47
8 8 2 7
1577
cooper.nedia.mit.edu/1 8 . 5. 1. 7 0
1578
.85.21.0
ooper.nedia.it.edu/1
207-172-133-253.s62.as24.c1.erols.-m/207.172.133.253 1579
1580
dyn-106-202.interval.can/199.170.106.202
1581
dove.cow.cc/207.155.14.39
1582
dyn-106-202.interal.ccm199.170.106.202
207-172-133-253.s62.as24.col.erols.xc/207.172.133.253 1583
1584
van-52-0840.direct.ca/204.174.253.136
1585
kirkO8-8.accessone.anm209.43.129.104
1586
kirk08-8.accesone.cm209.43.129.104
1587
kirk08-8.accessone.ccm/209.43.129.104
1588
kirk08-8.accessoe.cV209.43.129.104
1589
kirkO8-8.accessone.cn/±209.43.129.104
1590
kirkO8-8.accessone.com/209.43.129.104
ip address of player
cooper.media.mit.edu/18.85.21.70
igarashi.media.mit.edu/18.85.21.69
xtod1317.it.wsu.edu/134.121.4.57
xtsd1317.it.wou.edu/134.121.4.57
xtsd1317.it.wsu.edu/134.121.4.57
xtsd1317.it.wsu.edu/134.121.4.57
igarashi.media.mit.edu/18.85.21.69
mp-208-18-64-222.wchtks.owbell.net/20
pp-22.rb5.exit109.cc
110
duration
179
223
193
62
358
598
191
310
477
154
105
38
34
104
124
161
46
246
baddies
16
23
24
4
25
49
21
36
54
22
2
2
3
6
0
4
2
39
hits
shots
228
339
405
25
412
775
238
446
810
195
29
13
20
56
6
34
15
599
411
642
625
42
663
3191
719
981
1914
575
35
39
45
336
62
219
38
1427
ip address of player
kirk8-8.accessone.can/209.43.129.104
9
.43.129.121
kirk08-25.aceonoe.omn/20
kirk08-25.accessone.cV/209.43.129.121
ppp42.pulluhn.ceV204.227.174.42
4 2 27 7 4 42
.
.1
prp042.pllno.ccn/20
2
27
17
4 .42
2
4
4
0 . . .
ppp02.pullen.can/
kirk01-9.accesoe.canV209.43.128.9
kirkOl-9.accesone.can/209.43.128.9
kirk01-9.accessone.can/209.43.128.9
kirkOl-9.accessone.con/209.43.128.9
2
93
67 6
2
aws11.kyamk.fi/1.1 .5 .11
ad-012.infooe.ccn/206.30.91.12
ad-012.infohouse.cce/206.30.91.12
194.215.211.8/194.215.211.8
194.192.151.189/194.192.151.1897 3
0.2 2
user40-i.erlange.netsurf.de/194.163.1
station17.ultimm-nia.isdnet.net/194.149.174.114
kaze.mndia.mit.edu/18.85.5.79
id#
1591
1592
1593
1594
1595
1596
1597
1598
1599
1600
1601
1602
1603
1604
1605
1606
1607
1608
23900
196
36
599
1197
kaze.nieia.mit.edu/18.85.5.79
1609
5000
7250
3900
4000
7250
0
1800
2750
0
3500
2400
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3350
3950
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11350
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3800
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5600
4950
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3050
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5600
15400
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8950
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11700
9650
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7850
33350
31850
9550
7000
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5300
9200
160
203
142
125
218
15
171
89
236
131
86
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130
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143
147
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186
83
175
888
72
267
115
78
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106
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292
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271
93
312
79
193
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89
112
216
108
62
54
24
44
202
35
628
243
328
106
102
64
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15
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1010
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197
221
281
216
218
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1110
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164
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183
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195
492
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196
48
285
388
256
128
226
10
15
9
7
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3
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7
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0
10
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3
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3
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11
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4
18
7
32
7
5
7
9
2
8
5
17
14
8
3
3
4
22
5
6
2
14
9
0
8
1
0
14
61
2
19
12
30
23
15
0
19
11
5
28
10
4
15
67
61
20
14
1
23
22
20
10
20
112
134
76
55
147
0
22
71
4
48
24
5
129
96
103
43
82
20
91
33
174
1038
21
161
29
55
54
53
52
19
128
60
82
232
55
272
41
33
47
110
20
48
34
101
144
51
38
46
79
255
57
41
17
120
91
0
99
9
5
161
342
12
170
113
230
208
155
6
208
207
63
212
264
24
304
812
823
245
148
66
132
127
302
92
214
416
451
191
331
490
3
71
94
16
120
97
5
311
196
176
171
211
27
232
338
287
3432
76
561
125
101
84
163
148
70
505
237
211
813
219
1992
175
200
164
567
208
332
92
422
274
127
87
51
127
366
95
151
47
203
162
0
271
41
25
734
1780
129
1786
237
3062
2063
1672
26
2789
343
595
3607
435
248
570
2271
2373
1748
1365
114
3119
654
1737
828
1470
h136.s3.ts3l.hinet.net/163.31.3.136
h136.s3.ts3l.hinet.net/163.31.3.136
fw.ban.nl/194.229.190.5
fw.ban.nl/194.229.190.5
9
0.5
fw.baan.nl/194.229.1
9 2 3 7 3
. 1 .5 .
ww.cesvit-rtrt.regioe.toscana.it/15
6
3
4.8
bibelot.gr.osf.org/130.105.
pc.ne-uk.co.uk/193.130.154.101
nastrond.ifi.uio.no/129.240.64.65
131.215.82.174/131.215.82.174
7
.199.252
167-199-252.ipt.aol.<xxn/152.16
167-199-252.ipt.ol.cco/152.167.199.252
131.215.82.174/131.215.82.174
131.215.82.174/131.215.82.174
131.215.82.174/131.215.82.174
131.215.82.174/131.215.82.174
eeoasis.cityu.edu.hk/144.214.41.62 78 33
.
pionO4.tphys.physik.uni--tuebingon.de/134.2.
onc2ppl7.alltel.net/166.102.105.18
rnnc2ppl7.alltel.net/166.102.105.18
eoasis.cityu.edu.hk/144.214.41.62
tcl-59.utah-inter.net/208.14.200.69
rembrandt.cs.tod.ie/134.226.38.70
204.165.32.159/204.165.32.159
199.93.176.6/199.93.176.6
1610
1611
1612
1613
1614
1615
1616
1617
1618
1619
1620
1621
1622
1623
1624
1625
1626
1627
1628
1629
1630
1631
1632
1633
1634
1635
1636
1637
1638
1639
1640
1641
1642
1643
1644
1645
1646
1647
1648
1649
1650
1651
1652
1653
1654
1655
1656
1657
1658
1659
1660
1661
1662
1663
1664
1665
1666
1667
1668
1669
1670
1671
1672
1673
1674
1675
1676
1677
1678
1679
1680
1681
1682
1683
1684
1685
1686
1687
1688
1689
1690
1691
1692
1693
1694
date
980413
980413
980413
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
11:10:51 2M
11:33:06FM
11:36:34
12:38:15AM
12:44:29AM
12:54:380M
1:43:02AM
1:48:30AM
1:56:35AM
1:59:26AM
2:48:00AM
2:59:36AM
3:02:22014
3:21:12A14
3:46:59A14
3:52:12AM
4:09:06AM
4:41:38AM
score
8250
13400
12350
2400
14150
28850
9450
17750
30250
10050
550
1250
1600
3050
150
2450
1350
25650
980414
4:48:07AM
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
6:18:42AM
6:22:21AM
7:04:31AM
7:06:52AM
7:10:48AM
8:22:16AM
8:42:14AM
9:14:000M
9:47:02
10:12:12
AM
0M
10:16:26
014
10:16:33
10:16:5214
AM
10:24:22
10:33:110M
10:37:31
10:50:480M
0M
11:17:03
A14
11:33:16
0M
11:34:55
11:48:180M
12:53:2624
1:22:32
1:26:492M
1:41:0924
2:17:362M
2:23:442M
2:25:132M
2:27:15
2:28:18
2:43:29
2:45:49M
2:47:17
2:52:272M
3:08:082M
3:14:552M
3:20:092M
3:25:38
3:29:39
3:33:122M
3:34:182M
3:36:142M
3:41:152M
3:43:49R4
3:44:07FM
3:45:2524
3:46:32
3:47:05
3:48:06
3:49:162M
3:49:382M
4:03:52
4:09:052M
4:10:4624
4:20:4124
4:25:582M
4:32:26EM
4:34:082M
4:34:392M
4:35:102M
4:43:102M
5:33:392M
6:12:59
6:13:2724
6:17:55
6:21:4724
6:26:512M
6:33:112M
6:45:362M
7:08:052M
7:11:4724
7:24:1624
7:25:43
7:27:232M
7:29:15R4
8:18:3924
8:28:2124
9:02:3824
9:06:18R4
9:07:52
9:11:19
9:15:082M
9:15:53FM
9:21:542M
9:25:55
time
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
GLOM:Information Agglomerates
wn16-071.paris.worldnet.fr/195.3.16.7
209-142-3-48.stk.inreach.net/209.142.3.48
209-142-3-48.stk.inreach.net/209.142.3.48
209-142-3-48.stk.inteach.net/209.142.3.48
209-142-3-48.stk.inreach.net/209.142.3.48
8
4
.151.
nuc80.mik.npled.kl2.ca.us/204.9
80
0
nac80.milk.npusd.kl2.ca.us/204.94.151.
nmc80.mik.npuad.k12.ca.us/204.94.151.80
8
4 4
.9 .151.0
rc80.mk.npasd.k2.ca.us/20
n-&c81.mlk.npusd.k2.c.us/204.94.151.81
205.181.121.144/205.181.121.144
unkorwn-35-6. nwhse.ocanV/206.189.35.6
unknon-35-6.nhe. car/206.189.35.6
6
unknown-35-6.nwhse.can/20.189.35.6
unknown-35-6.nwhe.can/206.189.35.6
host-124.concretemdia.cn/207.240.49.124
host-124.concreteedia.can/207.240.49.124
hot.njit.edu/126.235.35.181
unkmown-35-6.nwhse.can/206.189.35.6
7
38 44
.1 .2
port244.ster.prodigy.net/204.23
port244.ster.prodigy.net/204.237.138.244
9 6
7
slnck-096.sluktech. can/20 .155.10 .9
skunk-096. skunktech.ccn207.155.109.96
6
7 55
skunk-096.skunktech. can/20 .1 .109.9
port244.ster.prodigy.net/204.237.138.244
skunk-096. slunktech. c±xn/207.155.109.96
unknon-35-6.nohse.can/206.189.35.6
geekboy.concretenedia.can/V207.240.49.115
6
6 89 3
.1 . 5.
unknown-35-6.nthse.can/20
199.6.62.21/199.6.62.21
ts67ip131.cadvision.can/207.228.75.131
208.206.247.169/208.206.247.169
EW/18.63.1.89
BEISYM.MIT.
BETSYM.MIT.m.J/18.63.1.89
208.206.247.169/208.206.247.169
ts67ipl3l.cadvision.can/207.228.75.131
204.245.151.238/204.245.151.238
205.181.121.144/205.181.121.144
adn-ts-002florlaPl3.dialsprint.net/206.133.72.48
205.181.121.144/205.181.121.144
205.181.121.144/205.181.121.144
205.181.121.144/205.181.121.144
rpp55.ko.tele.dk/194.239.168.55
205.181.121.144/205.181.121.144
bb-011.nylink.axn208.129.65.11
ts70ip229.cadvision.canfV207.228.75.229
ts70ip229.cadvision.ca207.228.75.229
hb-011.nylink.can/208.129.65.11
ts70ip229.cadvision.can/207.228.75.229
tb-011.nylink.cam208.129.65.11
162.pl.'Iht02.MIA.Icanect.Net/206.142.168.162
6 8 62
.1
162.pl.'Iht02.MIA.Icanect.Net/206.142.1
BETSYM.MIT.H12J/18.63.1.89
BETSY4M.MlIT.EW/18.63.1.89
7 22 8 8 8
. .6 .1
ts82ip18.cadvision.amV20
BETSYM.IT.E/18.63.1.89
ts82ip18.cadvision.ca/207.228.68.18
BETSMM.MIT.E/18.63.1.89
BETSYM.MIT.9J/18.63.1.89
BETSYM.MIT.EWU/18.63.1.89
111
date
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980414
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980415
980416
time
score
duration
baddies
hits
shots
ip address of player
id#
9:29:25 FM
9:32:30 PM
9:38:50 FM
9:43:14 M
9:47:25 FM
9:52:21 PM
9:57:42 EM
10:01:58FM
10:06:57FM
10:10:45FM
10:14:22PM
10:18:19FM
10:23:17FM
10:25:46PM
10:27:35FM
10:28:36FM
10:30:49FM
10:32:38FM
10:34:36FM
10:39:47FM
10:44:42FM
10:50:22FM
10:59:10
11:02:14FM
11:06:59FM
11:08:59FM
11:16:38
11:23:31FM
11:31:42FM
1:05:58AM
1:15:06AM
2:45:36A14
7:55:58AM
8:27:59AM
8:28:21AM
9:30:27AM
9:44:00AM
9:44:14AM
9:50:52AM
9:56:34AM
9:58:32AM
10:12:12 AM
10:56:51
AM
AM
11:13:44
11:24:38AM
11:33:05
AM
1:04:27FM
1:04:54FM
1:06:57FM
1±07:41FM
1:34:33FM
1:44:53FM
1:46:43FM
1:48:37FM
1:55:11FM
2:04:43FM
2:07:30FM
2:09:01FM
2:09:32FM
2:12:36FM
2:12:58FM
2:23:25FM
2:24:50FM
2:26:00FM
2:27:52FM
2:36:27FM
2:41:12FM
3:36:52FM
3:37:57FM
3:43:31FM
4:08:14FM
4:09:01FM
4:09:55 FM
4:22:38FM
4:26:47FM
4:28:33FM
4:30:22FM
5:01:00FM
5:02:57FM
5:04:43FM
5:28:45FM
5:32:07FM
6:07:51FM
6:22:20FM
6:22:24FM
6:41:18FM
7:02:42FM
7:03:33FM
8:19:57FM
8:22:07FM
8:24:29FM
8:26:12FM
8:28:47FM
8:47:51FM
8:52:05FM
9:01:12FM
10:07:08FM
10:19:47FM
10:26:01FM
11:02:19FM
11:03:09FM
11:06:34FM
11:08:18FM
12:42:18AM
8300
5100
9800
10200
9250
12700
9100
6600
6600
7350
7700
5450
8050
1250
3350
13500
3650
9550
4850
10900
10650
11150
16100
6750
10900
4350
11850
12550
12700
9800
32600
1200
0
29100
2700
0
0
1100
8950
0
10500
2350
350
7150
5500
2250
1100
1300
4050
600
1250
900
2450
3900
2550
6800
4650
2500
8650
9350
7250
3150
600
2200
500
5700
3200
150
1500
0
6400
30550
2100
1200
0
4700
3700
3000
2400
3750
0
3450
13750
33850
0
30850
5250
10150
3400
5350
2000
4350
8850
9850
3250
400
11100
1150
3650
2750
800
2900
4350
2400
192
166
191
245
235
279
302
239
283
205
200
90
266
101
92
303
175
225
101
296
277
262
328
160
266
104
347
396
475
203
536
58
20
301
49
22
95
184
383
87
442
68
38
133
179
64
167
84
104
25
111
137
58
98
92
463
149
70
153
169
285
100
69
54
134
223
134
64
49
93
169
591
85
85
12
766
93
70
95
91
1
127
419
857
100
601
182
403
78
114
56
87
139
321
231
45
526
68
162
183
30
190
153
47
15
12
21
21
23
24
21
11
16
14
14
10
14
2
7
22
9
19
11
21
18
20
31
13
19
9
23
21
23
19
64
2
0
50
5
0
0
3
17
0
21
5
0
13
22
4
1
2
10
1
2
2
4
9
5
13
11
4
16
16
15
7
1
3
2
14
5
0
6
0
20
54
7
2
0
8
6
6
4
8
0
8
29
69
0
57
14
25
8
13
8
9
20
24
7
0
24
3
9
5
3
6
9
4
209
66
186
273
167
312
201
135
158
197
184
115
189
15
46
383
117
255
61
298
287
306
423
178
262
52
355
314
470
321
729
16
32
659
30
21
4
21
211
0
220
39
8
162
178
29
23
14
108
7
13
12
38
73
35
165
63
37
160
226
119
39
6
36
43
121
35
25
47
1
172
816
104
17
0
80
55
37
24
45
0
96
465
947
6
892
96
218
81
101
98
88
228
169
43
8
385
20
68
31
41
37
54
31
1160
1841
1203
2025
1961
2685
2059
987
2325
1544
1100
678
2040
52
138
2451
352
1765
875
2781
2679
2501
3024
1107
2599
612
3773
4066
4029
525
2197
48
32
2256
131
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20
100
479
17
706
124
10
308
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464
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139
499
26
108
56
115
244
207
412
187
89
259
360
314
119
25
78
121
354
109
62
79
2
795
3832
441
61
3
224
143
96
49
149
0
495
1962
4412
16
3195
374
790
132
579
281
228
560
626
211
26
1402
80
237
218
61
586
171
51
BEISM.MIEDU/18.63.1.89
BEISM.MTrr.EW/18.63.1.89
BEISM.MIT.FEW3/18.63.1.89
EW/18.63.1.89
BETSYM.MIT.
El/18.63.1.89
BETSM.MIT.
EIJ/18.63.1.89
BEISYM.M1T.
BEISYM.MT.EW/18.63.1.89
BETSYM.MIT.EIIJ/18.63.1.89
BETSYM.MIT.EW/18.63.1.89
ETSYM.MIT.EIJ/18.63.1.89
BEISM.MIr. E1W/18.63.1.89
BETSYM.MIT.EIFJ/18.63.1.89
BETSYM.MIT.EIJ/18.63.1.89
6
199.canbridg-06.nn.dial-access.att.net/12.
9
88.105.199
6
199.canbridge-0 .nn.dial-access.att.net/12.6 .105.19
BETSYM.MIT.EW/18.63.1.89
68
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199.canbridge-06.na.dial-access.att. net/12.
EW/18.63.1.89
BETSYM.MIr.
BEISM.MITr.
EW/18.63.1.89
BETSYM.MIT.EW0/18.63.1.89
BETSYM.MIT.EIJ/18.63.1.89
BETSYM.MIT.EWU/18.63.1.89
BETSYM.MIT.EW/18.63.1.89
63.1.89
BETSYM.MIT.E/18.
89
BEISYM.MIT.EJ/18.63.1.
E[J/18.63.1.89
BETSM.MIT.
BETSIYM.MIT.EIJ/18.63.1.89
BETSYM.MIT.
EIU/18.63.1.89
EI3J/18.63.1.89
BETSM.MIT.
kirk09-7.accesone.com/209.43.129.151
kirk09-7.acconoe.can/209.43.129.151
ex794947-a.phnx3.az.hane.can/24.1.193.25
7
07
cooper.media.mit.edu/18.85.21.
frutiger.media.mit.edu±/18.85.21. 2
194.68.71.65/194.68.71.65
douze.meca.polyntl.ca/132.207.40.22
ocis.astro.uni.edu/129.2.163.239
0 4
1.444
dynlOlpp44.pacific.net.sg/210.24.1
24
.101.
dyn101ppp44.pacific.net.sg/210.
abs404.nmntganery.kl2.va.us/198.82.215.100
24
44
2
10. .101.
dynlOlp44.pacific.net.sg/
199.212.60.58/199.212.60.58
grunblO.stud.kvl.dk/130.225.189.44
du124-5.ppp.algonet.se/195.100.5.124
ts72ip88.cadvision.can/207.228.76.88
ns.fkgb.fr/195.115.8.113
205.169.77.97/205.169.77.97
eq002.equinox1t.a195.12.166.2
eq002.equinox1t.caW195.12.166.2
eq002.equinox1t.caV195.12.166.2
32
.1 7
adair.qwest.net/204.154.2
9
shinto.twofish.o-n208.211.96.1
ger.nhn.ac.uk/157.140.3.96
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1695
1696
1697
1698
1699
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1701
1702
1703
1704
1705
1706
1707
1708
1709
1710
1711
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1717
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1720
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1790
1791
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1796
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M
M
GLOM:InformationAgglomerates
on/206.25.18
conovergis.ci.conaver.nc.u/198.252.16
112
date
time
score
duration
baddies
hits
shots
ip
980416
980416
980416
980416
980416
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980416
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980416
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12:56:29 AM
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12:58:55AM
1:58:59AM
4:51:58AM
6:40:35AM
7:22:30AM
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7:37:45AM
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12:00:11 PM
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10:29:43 AM
10:40:30 AM
10:40:30 AM
10:42:42 AM
11:16:33 AM
11:19:46 AM
11:41:42 AM
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11:49:41
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M
GLOM:Information Agglomerates
address of player
id#
1799
1800
1801
1802
1803
1804
1805
1806
1807
1808
1809
1810
1811
1812
1813
1814
1815
1816
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1818
1819
1820
1821
1822
1823
1824
1825
1826
1827
1828
1829
1830
1831
1832
1833
1834
1835
1836
1837
1838
1839
1840
1841
1842
1843
1844
1845
1846
1847
1848
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1853
1854
1855
1856
1857
1858
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1860
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1889
1890
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1893
1894
1895
1896
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1898
1899
1900
1901
1902
113
date
time
980417
980417
980417
980417
980417
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980417
980417
980417
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980418
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980418
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2:34:33 1M
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3:18:1584
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7:01:42HA
7:02:17HA
7:08:25 HM
7:29:46HM
7:36:37HM
7:39:05
8:46:57
9:22:13
9:27:48
9:37:32HA
9:51:16HA
HM
10:09:43
10:09:51
HA
10:11:45HM
11:08:12HM
11:10:49HA
11:13:21HM
AM
12:49:08
12:51:37
12:52:28 AM
AM
12:53:23
1:53:10AM
3:00:38AM
3:14:48AM
6:20:51AM
7:41:08AM
8:48:23AM
10:04:27
AM
AM
10:35:52
AM
10:46:06
AM
10:51:36
AM
10:53:36
12:32:02HA
12:46:18HA
12:47:52HA
2:27:52HM
2:28:38HM
2:31:57
2:32:42HM
2:34:13HM
2:35:07HM
2:36:14HM
2:37:52
2:38:44HA
2:39:52HA
2:40:18HA
2:42:22HA
2:55:32HA
3:10:20HA
3:13:02HM
3:56:25HM
4:24:09HM
4:39:09HM
4:43:56HA
4:53:46
5:00:22HM
5:56:47
6:06±09
6:11:32 HA
6:29:10 HA
6:30:44
6:32:31 HA
6:43:10HA
7:45:24HA
7:49:34HM
8:19:19HA
9:27:52HM
9:30:34HA
9:34:38HA
10:03:08
HM
10:14:00
HA
10:15:06
10:27:57
11:08:34
AM
12:12:37
AM
12:15:08
AM
12:16:42
M
M
M
M
M
M
M
M
M
M
M
M
M
M
score
3800
1350
3950
4850
9450
2900
250
9550
1350
1700
7750
3050
4700
1050
8450
8400
2850
0
10600
26900
29400
9350
4450
10200
28850
3800
28100
28650
2850
0
0
4500
5150
13550
11150
9500
5100
600
3600
0
5350
2250
5650
4700
4700
4650
1500
1500
0
50
2350
0
6550
0
5150
8950
4950
8400
5050
4000
2700
3700
14050
1450
4350
3400
3750
5200
5000
1150
6400
2250
5150
6250
4650
4500
7150
5000
2650
13050
2250
3850
31600
200
4700
13650
2800
1950
3500
0
15450
9350
16000
3250
4050
6100
1800
13750
31350
16500
2850
4850
3900
28500
duration
215
44
86
229
230
117
25
346
82
60
219
76
227
172
262
311
87
7
226
445
447
217
174
227
455
142
408
386
109
36
34
122
128
395
315
319
159
22
89
3
99
103
196
135
122
133
34
37
18
65
161
98
282
98
150
188
129
314
102
195
103
79
274
100
130
78
75
171
103
99
194
103
115
115
179
125
144
158
153
245
173
84
470
89
127
307
123
79
90
165
693
227
381
111
146
228
266
421
554
493
105
256
136
445
GLOM:Information Agglomerates
baddiss
hits
8
5
8
11
23
6
0
22
2
5
17
5
11
4
17
21
5
0
27
46
51
22
11
24
49
8
46
47
6
0
0
9
14
31
20
19
12
1
6
0
13
7
20
9
11
11
6
2
0
0
8
0
16
0
12
14
11
18
9
9
5
6
27
3
9
8
8
12
13
4
17
9
15
18
11
9
12
11
5
25
8
7
60
0
10
22
5
3
7
0
46
21
30
6
10
16
3
36
59
35
5
10
10
49
46
51
49
89
193
34
5
205
17
29
196
33
111
60
180
157
33
0
208
766
816
165
82
218
767
46
710
723
61
1
0
83
127
363
253
274
87
6
50
0
96
92
161
89
66
97
48
40
0
24
87
15
105
0
71
189
73
162
75
53
36
40
329
83
52
69
63
81
138
63
163
113
147
163
95
132
159
68
32
346
100
58
825
34
88
323
32
35
97
3
363
244
390
41
87
144
42
397
819
538
33
82
88
676
shots
170
114
149
395
467
418
31
692
84
109
340
129
710
221
1243
1044
214
0
1342
2694
2686
1260
688
1578
2512
679
2466
2123
123
39
0
385
378
1235
576
662
775
25
140
2
322
291
332
225
268
595
131
76
0
70
234
16
505
20
194
237
220
500
193
191
185
111
1008
266
215
181
139
355
663
146
579
338
839
687
353
300
463
660
114
1352
497
136
3567
105
216
666
131
90
160
8
2704
660
1087
178
285
1652
186
1079
2572
1414
140
229
240
1230
ip address of player
id#
s148.nc2-car.ccan/204.107.238.148
1903
1904
1905
1906
1907
1908
1909
1910
1911
1912
1913
1914
1915
1916
1917
1918
1919
1920
1921
1922
1923
1924
1925
1926
1927
1928
1929
1930
1931
1932
1933
1934
1935
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
s148.nr2-esr.ccan204.107.238.148
8
s148.nr2-car.cm204.107.238.14
38 4 8
7
.2 .1
s148.n2-car.can/204.10
s148.nr2-cr.can/204.107.238.1486
8
4.12
lCostl2B.tntl.det3.da.uu.net/208.254.
1Cust128.tntlO.det3.da.uu.net/208.254.64.128
208.137.84.48/208.137.84.48
43
noss243.c io.can207.251.15.2
165.29.121.246/165.29.121.246
165.29.121.246/165.29.121.246
7
ge.nedia.mit.edu/18.85.11.1 5
scient.media.mit.edu/18.85.11.177
s2n±33.dialup.HAIH-Aachen.rE/137.226.3.33
ge.nedia.it.edu/18.85.11.175
77
8
5.11.1
scient.media.mit.edu/18.
tcl-25.utah-inter.net/208.14.200.35
7
ge.nedia.rit.edu/18.85.11.1 7 5
5
ge.media.mit.edu/18.85.11.1
tcl-25.utah-inter.net/208.14.200.35
tcl-25.utah-intr.net/208.14.200.35
ge.mEodia.mit.edu/18.85.11.175
175-147-153.ipt.aol.can/152.175.147.153
7
5
ge.media.mit.edu/18.85.11.1
tcl-25.utah-inter.net/208.14.200.35
175-147-153.ipt.ol.ccan/152.175.147.153
tcl-25.utah-inter.net/208.14.200.35
tcl-25.utah-inter.net/208.14.200.35
22
7
A17-202-12-122.apple.cca/1 .202.12.1
A17-202-14-79.apple.can/17.202.14.79
0022SEL.BICS.UIC.EDJ/131.193.234.119
33 96
7 7
.19.1 .
fctnts06c42.ntnet.nb.ca/20
fctnt906c42.nbnet.nb.ca/207.179.133.96
p164.snbeach.net/205.214.199.186
DIALUP55.73IL.USIT.NET/208.24.80.55
DIAUP55.IL.USIT.NET/208.24.80.55
7
1.238
ts238.wnet.org/205.133.1
brap.conectnet.can/207.110.0.58
circ-ras2-1-co-11.dial.bright.net/209.143.14.115
circ-ras2-1-cs-11.dial.bright.net/209.143.14.115
ciro-ras2-1-cs-11.dial.bright.net/209.143.14.115
2
dialup-B089.europa.o-v/204.2073 .55.89
4 9 39
173-149-39.ipt.ol.can/152.1
73 .1
4 9 .39
.1 .
173-149-39.ipt.ol.can/152.1
dialup13.nvt.net/207.3.71.122
dialup13.nvt.net/207.3.71.122
2
7
7
.3.1.12
dialup13.vt.net/20
dialup13.nyt.net/207.3.71.122
s34-px0l.gatech.carpu.nci.net/168.14.1.53
209.60.126.45/209.60.126.45
userl09.ascep2.snowl1l.cm/208.134.11.118
mino-casl-cs-8.newnorth.net/208.155.6.202
156-195.butte.cc.ca.us/198.189.156.195
167.152.154.183/167.152.154.183
207.245.233.91/207.245.233.91
199.6.62.24/199.6.62.24
DIA1iP43.IMDIL.USIT.NEr/208.24.80.43
DIAU1P43.TEIL.USIT.NET/208.24.80.43
DIAL1P43.ThDIL.USIT.NET/208.24.80.43
pr02-46.sac.ns.net/209.162.64.65
3
4 6 88
.35.16 .188
102stlB8.tnt12.tou2.da.uu.net/15
.1
1Cust188.tntl2.tco2.da.±.unet/153.35.14
69
8
5.21.
igarashi.nedia.nit.edu/18.
7 2 22
8
. .1
.dialup.online.n/130.6
tiO01aO9-005
tso002d10.-tn.oncentric.net/206.83.83.70
circ-ras1-4-cs-18.dial.bright.net/209.143.14.96
circ-rasl-4-cs-18.dial.bright.net/209.143.14.96
ts002d10.nmw-tn.conctric.net/206.83.83.70
circ-rasl-4-cs-18.dial.bright.net/209.143.14.96
van-as-02a09.direct.ca/204.174.248.57
ts002d10.non-tn.coetric.net/206.83.83.70
v-as-02a09.direct.ca/204.174.248.57
circ-rasl-4-cs-18.dial.bright.net/209.143.14.96
circ-rasl-4-Cs-18.dial.bright.net/209.143.14.96
cs-15.pot.ptd.net/204.186.34.15
8
7
custcas543.ipass.net/20 .120.205.10
custcs543.ipass.net/207.120.205.108
ibb0224.ibb.ruu.nl/131.211.124.224 87
tc2-30.riverfalls.Spacestar.Net/206.191.194.1
igarashi.nedia.mit.edu/18.85.21.69
dt083n5d.san.rr.co/204.210.25.93
8
6
8.3 .205
ppp13.annex1.stip.net/194.1
igarashi.media.mit.edu/18.85.21.69
8
76
dynmic-48.media.nit.edu/18. 5.12.1
DIA.N3IL.2UIT.NET/208.24.80.6
DIA19. 1IL.USI.NET/208.24.80.6
olip129-37-121-61.n.us.ihn.onet/129.37.121.61
37
-121-61.mo.us.ihn.net/129.37.121.61
slipl291 29
slip -37-121-61.mo.us.ihn.net/129.37.121.61
84
6
.2
2 37
slipl9- -119-162.nc.s.ihn.net/129.37.119.162
slip129-37-119-162.nc.us.ihln.onet/129.37.119.162
tc1-115.utah-inter.net/208.14.200.125
134.132.207.131/134.132.207.131
134.132.207.131/134.132.207.131
134.132.207.131/134.132.207.131
anex-d-5.nedia.mit.edu/18.85.14.222
dialinO9.internetl.net/206.250.31.209
tc3-11.utah-inter.net/208.14.202.21
dialin09.internetl.net/206.250.31.209
Dc.MIT.EDU/18.232.0.7
ipl03.vegas.quik.ca/207.38.35.103
7
3
3
.38.
ipl03.vegas.quik.ccnV20
3 5.10
4
glum.ndia.mit.edu/18.85.25.
sdn-ts-001lcoviP07.dialsprint.net/206.133.1
114
date
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980419
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
980420
time
12:29:51 AM
12:30:54AM
12:32:18AM
12:33:27AM
12:33:32AM
12:36:49AM
2:19:34AM
2:21:17AM
2:22:47AM
2:41:21AM
5:05:28 AM
5:07:32AM
5:27:13AM
5:32:00AM
6:55:14AM
7:23:26AM
7:35:22AM
9:02:19AM
12:07:262M
12:17:548M
12:28:062M
12:33:2424
12:36:492M
12:46:41FM
12:51:282M
12:57:472M
1:52:06 4
2:05:2824
2:12:57
2:31:21
2:44:0324
4:41:482M
4:48:412M
5:19:292M
7:37:592M
8:07:512M
8:12:122M
8:30:302M
8:32:1024
8:37:4524
8:46:4324
9:28:5224
9:30:1424
9:32:432M
9:34:0324
9:35:072M
11:28:36
2:41:13AM
3:51:30AM
4:28:05AM
5:07:04AM
5:23:41AM
6:57:45 AM
7:08:34AM
7:20:12AM
7:33:41AM
7:36:15AM
7:40:23AM
7:50:57 AM
8:31:28AM
8:38:17AM
8:41:51 AM
8:44:00AM
8:44:08AM
8:45:21AM
8:45:34AM
8:57:32AM
8:57:56 AM
9:03:33AM
9:34:19AM
9:35:47AM
9:47:46AM
9:52:42AM
AM
10:17:37
AM
10:56:06
AM
11:18:25
11:51:15 AM
12:11:262M
12:11:332M
12:13:232M
12:41:41
12:42:312M
12:47:05 2M
1:28:552M
1:30:1224
3:05:15 24
3:06:5524
3:10:482M
4:34:3624
6:39:2624
6:46:3424
6:56:15 24
7:01:292M
7:16:40
8:23:4924
8:43:102M
8:54:342M
8:55:3724
8:58:4024
9:02:592M
9:07:122M
9:17:4824
10:35:092M
10:37:332M
M
M
M
M
M
scor.
400
1300
3950
3650
2800
4900
3550
3250
4300
3250
0
1050
4150
10950
0
0
7100
1050
2550
7250
6150
8750
6400
3200
5450
8000
8500
5400
29350
22600
15700
3800
7200
8150
700
3050
7200
6500
4650
9200
11350
1250
2100
14250
4650
1250
350
8850
2800
4850
8350
1200
1050
1800
5400
14200
6100
9050
200
750
3000
4850
3700
2300
2000
3850
0
0
2850
2200
7650
2900
1050
5350
50
600
500
1500
4600
1500
2800
1200
2950
1150
650
5550
2400
9650
0
3750
3050
6850
4850
4200
29850
5550
1100
900
3400
4750
6950
8000
2050
5050
duration
43
21
68
115
58
190
113
88
176
226
131
110
112
275
52
13
272
60
128
614
411
300
187
246
265
323
398
266
606
1536
740
113
179
255
64
134
245
261
191
320
369
88
66
537
214
49
627
177
160
148
208
56
115
78
334
533
138
190
65
121
48
199
112
160
48
74
3
1
230
269
153
111
136
382
55
113
124
62
144
55
160
62
104
113
61
177
183
291
8
102
283
564
295
103
544
267
174
46
165
236
237
163
59
129
GLOM:Information Agglomerates
baddies
0
2
9
9
7
18
8
10
11
6
0
2
11
27
0
0
19
1
4
21
18
34
23
7
16
26
25
14
51
75
38
8
13
17
1
6
17
17
10
27
37
2
8
43
13
5
1
20
5
11
18
2
3
3
13
28
16
20
0
3
5
11
9
5
7
9
0
0
5
4
14
6
1
13
0
1
2
6
9
6
5
2
6
1
1
13
4
24
0
8
5
21
13
9
53
14
2
1
5
9
15
18
3
11
id#
hits
shots
ip address of player
12
14
111
83
115
160
61
109
99
35
0
20
77
296
0
1
160
16
54
155
152
243
190
58
153
204
207
80
733
488
557
112
121
187
17
38
108
96
67
177
192
22
70
317
121
46
19
183
35
128
174
23
27
25
72
460
154
211
6
34
32
96
70
68
92
72
0
0
33
31
148
34
23
86
1
9
10
48
111
49
41
12
58
18
7
138
26
216
0
51
34
159
91
88
745
124
30
14
40
101
124
186
30
73
29
31
440
443
540
1086
241
186
450
908
18
165
547
1502
3
1
599
63
105
1937
1407
1715
770
568
1046
1330
1859
1139
4226
4860
3467
191
213
382
46
69
242
288
812
2026
1677
84
168
1130
326
134
62
513
520
349
529
73
62
84
1061
2371
919
718
9
164
80
549
444
736
150
385
0
0
118
189
296
511
67
365
36
18
29
83
234
94
175
89
768
62
28
400
61
803
0
195
159
1315
762
201
3767
499
96
21
109
197
334
402
47
358
2007
GS141.SP.CS.CMJ.KU/128.2.203.153
2008
GS141.SP.CS.QU.EIU/128.2.203.153
2009
GS14l.SP.CS.OU.EDJ/128.2.203.153
2010
GS16.SP.CS.aU.KU/128.2.203.216
2011
GS141.SP.CS.OJ.EIJ/128.2.203.153
2012
GS16.SP.CS.C2U.EIU/128.2.203.216
2013
ip77.an3-new-york4.ny.pub-ip.psi.net/38.26.14.77
2
2
2014
29.16
ppp34a.nerlin.net.au/203.20.
2015
ip77.an3-new-york4.ny.pub-ip.psi.net/38.26.14.77
3
2016
0
dyn1-30.SanDiego.connectnet.ccm206.251.151.
2017
acyl-238.abo.wanadoo.fr/193.252.140.238
2018
ancy1-238.abo.wanaco.fr/193.252.140.238
2019
and-is&Ol-12.dial.xs4all.nl/194.109.46.13
2020
and-isdn01-12.dial.xs4all.nl/194.109.46.13
2021
ruche.ms-info.uvsq.fr/193.51.26.201
2022
bartlet.df.1th.se/194.47.252.146
2023
dialup-11-36.netccnuk.co.uk/194.42.230.228
2024
brok.ifi.uio.no/129.240.64.29
2025
p5-term3-mn.netdirect.net/204.248.214.94
4 24 8 2 4 4
2026
. . 1 .9
p5-term3-nun.netdirect.net/20
2027
dynamic-55.nedia.it.nedu/18. 85.12.183
2028
dynaic- 55.mv8dia.mit.eu/18. 85.12.183
2029
dynamic-55.me.dia.mit. edu/18.85.12.183
2030
dynamic-55.media.nit.edu/18.85.12.183
2031
dynaic-55.media.mit. edu/18.85.12.183
2
83
8 8
2032
.85.1 .183
dynam±ic-55.media.mit.edu/1
2033
dynamic-55.media.mit.edu/18. 5.12.1
2034
dynamic-5.mdia.mit.edu/18.85.12.133
2035
igarashi.media.m±it.edlu/18.85.21.69
33
2036
dynaric-5.media.mrit.edu/18.85.12.1
33
8
2037
dynamic-5.mdia.m-Lit.edu/18. 5.12.1
2038
195.198.30.20/195.198.30.20
2039
1Cust178.tntl.jacksonville.ar.da.uu.net/208.255.128.178
2040
s148.mc2-csr.ccn/204.107.238.148
34
2
2041
glum.media.mit.edu/18.85.
7 5.
2042
.51.85.117
pn3s17.shsemputer.cm/o20
2043
85.117
pn3s17.shscoupter.cra/207.51.
2044
nkiOO1.netknnect.net/208.198.32.98 87
2045
dynamic-59.nedia.mit. edu/18.85.12.1
2046
dynamnic-59.media.mit.edu/18.85.12.187
8
2
87
2047
5.1
.1
dynamic-59.nedia.rit.edu/18.
2048
209.116.228.37/209.116.228.37
2049
209.116.228.37/209.116.228.37
2050
2051
209.116.228.37/209.116.228.37
2052
209.116.228.37/209.116.228.37
2053
p43-53.tnt-2.ij.net/209.4.43.53
2054
pc19F8C66.dip.t-online.de/193.159.140.102
2055
fire.abo.fi/130.232.208.35
2056
194.223.233.40/194.223.233.40
2057
gate.uth.boras.se/148.160.250.12
2058
193.129.185.156/193.129.185.156
2059
sara.wu-ien.ac.at/137.208.107.101
7
2060
9.91
raf2l.iiic.ethz.ch/129.132.1
2061
edu/18.85.12.176
dynamrkic-48.
media.m±it.
7
2062
dynamic-48.media.mit.edu/18.85.12.1
76
2063
dynamic-48.media.mit.edlu/18.85.12.1 6
2064
pc-33516.cn.rogers.wave.ca/24.112.34.115
2065
194.129.182.204/194.129.182.204
2066
jwf27.acan.m.1/137.246.14.245
2067
209.160.99.22/209.160.99.22
2068
209.160.99.22/209.160.99.22
2069
209.160.99.22/209.160.99.22
2070
209.160.99.16/209.160.99.16
2071
209.160.99.16/209.160.99.16
2072
209.160.99.22/209.160.99.22
2073
gwinston-isd-h-m.cio.can/171.68.166.90
2074
gwiston-isd-hcm.cisc. cl7l.68.166.90
2075
de±--10-13.dialup.netins.net/167.142.14.142
2076
A101015.sf0l.as.cr.oc/168.75.101.15
2077
AS52-06-34.aa-kitcheer.golden.net/209.183.129.34
2078
195.223.57.106/195.223.57.106
2079
Sanliegol-2.SanDiego.Accessl.net/207.104.109.155
2080
156-195.butte.cc.ca.us/198.189.156.195
2081
drag73208.stud.ntnu.no/129.241.73.208
2082
rfhsi8005.fh-regenshurg.de/194.95.108.67
2083
207.8.84.77/207.8.84.77
7
2084
balok.psrw. cc/199.99.166. 9
2085
pawnaig.resnet.uconn.edu/137.99.157.37
79
2086
balok.perw.ccm/199.99.166.
7
2087
3
iax-vidalia-pp064.iam±erica.net/207.101.55.
2088
dynadc-41.
2089
209.160.99.8/209.160.99.8
2090
EK2.PSY.6U.EIJ/128.2.248.58
2091
BK2.PSY.CHU.EIJ/128.2.248.58
2092
196-31-19-60.iafrica.ccV196.31.19.60
2093
davinci.math.duke.edu/152.3.25.30
2094
196-31-19-60.iafrica.ccn/196.31.19.60
2095
198.30.208.58/198.30.208.58
2096
dynamic46.pn09.n.best.ccuV209.24.242.46
2097
nax8.joplin84.getonthe.net/208.142.6.84
2098
nx8.joplin84.getonthe.net/208.142.6.84
2099
nex±.joplin84.getonthe.net/208.142.6.84
2100
199.201.192.150/199.201.192.150
2101
igarashi.nedia.mit.edu/18.85.21.69
2102
glacier21.ccdt.uscg.mil/199.211.149.21
2103
-08.nax±1.gvi.net/208.12.255.8
±ndn1
8 2 2
2104
.1 . 55.8
ndn-08.nxl.gvi.net/20
2105
ndn1-08.naxl.gvi.net/208.12.255.8
2106
n±dl-08.nmx1.gvi.net/208.12.255.8
2107
n±dl-08.nex1.gvi.net/208.12.255.8
2108
dialup-117.publab.ed.ac.uk/129.215.38.117
2109
203.241.133.183/203.241.133.183
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203.241.133.183/203.241.133.183
adn-ts-003kylouiPO7.dialsprint.net/20
mEdia.it.edu/18.85.12.169
115
date
time
score
duration
baddies
hits
shots
ip address of player
id#
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980421
980422
980422
980422
980422
980422
980422
980422
980422
980422
980422
980422
980422
980422
980422
980422
980422
980422
980422
980422
980422
980422
980422
980422
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980423
980424
980424
980424
980424
3:37:35 AM
5:40:24AM
5:49:14AM
5:59:23AM
5:59:36AM
6:08:31AM
6:10:06AM
6:27:55AM
6:28:11AM
8:30:59AM
10:16:36AM
1:17:09O4
1:39:49EM
1:44:23
1:44:30
1:45:31OH
1:46:39
1:47:38O
1:52:10OH
1:53:08OH
2:22:35OH
2:23:52OH
2:25:14OM
5:09:54 OM
5:28:24 OM
5:31:32 OM
5:58:07OM
6:15:47OM
6:15:56OM
6:19:45OM
6:26:49OM
6:34:36OH
6:49:04OM
6:51:34
7:04:18OH
7:05:58OH
8:13:52OM
8:24:55OH
8:27:50OH
8:40:32OM
8:42:57OH
9:21:08OM
10:28:52OH
10:30:05
1:10:51AM
8:13:00AM
AM
11:17:54
AM
11:34:14
12:39:03
12:45:13OH
4:30:55OM
4:32:22OM
5:10:19OH
5:10:39OM
5:29:26OH
5:30:58OM
5:33:20
5:39:46OM
5:41:06OM
5:44:11OM
5:54:25OM
6:37:58OM
7:14:59OM
7:16:05
9:11:09
OM
10:32:39
11:57:10OM
12:36:32 AM
6:53:04AM
7:22:31AM
7:27:29AM
7:38:34AM
7:44:06AM
8:04:07AM
8:05:46AM
8:10:05AM
8:12:35AM
8:15:48AM
9:22:46AM
9:49:46AM
10:11:01AM
10:17:11AM
10:33:23AM
4:14:57OM
4:57:05OM
5:43:49OM
5:48:50
7:19:33OM
7:22:33OM
7:50:29OM
7:57:40OM
8:20:47
8:21:52
8:28:21OH
8:33:20
8:58:12OH
9:01:08
9:08:56OM
9:10:24OM
10:36:47OM
8:16:17AM
8:19:29AM
8:20:43AM
8:23:07AM
300
50
2000
50
0
5000
1600
500
5200
150
0
3900
3150
250
7400
500
1500
1000
3500
5550
3250
3700
2350
2900
2800
4850
450
0
9650
3750
2400
6350
3650
6900
6500
3300
0
1250
6450
9450
5050
0
7250
1900
1200
0
700
9300
11700
13400
600
850
4200
0
4450
4300
4700
29850
5800
6250
12400
10350
4050
2650
3000
250
0
0
4150
2400
4550
1800
2300
5350
2400
4100
6250
7350
2000
0
30250
28100
200
4450
31950
550
3500
2050
8200
3300
0
0
0
0
2700
0
0
0
600
650
15050
30050
7800
24600
310
109
385
45
603
113
79
22
136
86
215
206
63
41
264
47
55
44
255
139
123
141
49
71
108
164
46
3
1986
197
287
410
852
230
149
73
28
117
159
322
129
731
231
65
79
6
29
165
363
353
78
53
161
4
151
127
126
371
140
245
597
343
58
50
85
29
50
89
148
303
281
64
74
127
84
84
134
171
187
101
936
359
82
185
599
89
176
106
169
75
26
16
1
10
162
1
1
2
21
41
90
181
42
128
0
0
8
0
0
20
5
2
12
0
0
10
8
1
22
2
6
4
7
15
7
9
8
6
5
11
0
0
21
7
4
14
14
13
12
6
0
2
13
21
10
0
14
4
2
0
1
19
37
38
2
2
9
0
9
10
10
53
12
16
29
25
7
5
6
0
0
0
11
4
11
3
5
12
4
8
11
14
8
0
88
46
0
9
54
0
7
3
16
6
0
0
0
0
6
0
0
0
1
2
25
53
12
43
6
3
61
5
0
117
77
42
68
8
15
54
69
48
173
32
65
48
40
115
45
117
76
36
65
80
12
0
197
58
24
99
124
123
107
36
0
13
163
259
125
11
170
100
22
1
8
181
315
338
59
23
92
0
70
92
65
746
115
89
352
209
59
47
39
8
0
0
95
38
61
18
35
96
24
68
113
157
103
0
748
823
8
106
830
11
78
39
156
72
18
0
0
18
84
0
0
0
6
43
256
610
125
405
50
30
812
22
470
1327
346
58
180
27
53
652
167
90
778
146
173
158
237
679
214
955
333
131
112
437
41
0
619
283
86
223
1628
351
193
139
5
32
261
875
239
114
520
284
41
1
45
342
2937
1947
108
85
487
1
181
278
339
1350
320
464
1749
1130
131
122
135
19
11
5
627
269
296
98
66
276
505
360
594
740
196
1
4224
1720
14
309
2750
118
184
95
319
97
20
0
0
21
148
0
0
0
9
80
774
1873
302
1085
IC)01590.reshall.uidaho.edu/129.101.139.107
192.116.226.209/192.116.226.209
192.116.226.209/192.116.226.209
7
.10
Iol.sic.se/193.220.7
192.116.226.209/192.116.226.209
192.116.226.209/192.116.226.209
192.116.226.209/192.116.226.209
glum.media.mit.edu/18.85.25.34
193.129.185.156/193.129.185.156
193.78.125.38/193.78.125.38
derf.cs.nu.ca/134.153.1.55
46
tcpac32.earthorld.ccs/198.145.145.
204.185.27.75/204.185.27.75
204.185.27.76/204.185.27.76
204.185.27.75/204.185.27.75
204.185.27.76/204.185.27.76
204.185.27.76/204.185.27.76
204.185.27.76/204.185.27.76
204.185.27.76/204.185.27.76
pc156.max4060.ftech.co.uk/195.200.17.157
206.222.71.16/206.222.71.16
195.242.45.65/195.242.45.65
195.242.45.65/195.242.45.65
user-381carO.dialup.mindspring.mn/209.86.43.96
nex8.joplin9O.getanthe.net/208.142.6.90
nex8.joplin9O.getonthe.net/208.142.6.90
wk05.bard.edu/192.246.229.60
porter.bevd.blacksturg.va.us/198.82.228.152
166.41.205.41/166.41.205.41
porter.bevd.blacksburg.va.us/198.82.228.152
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ndnla-13.nax2.gvi.net/208.12.252. 5
nin-13.nax2.gvi.net/208.12.252.65
ndl-13.nax2.gvi.net/208.12.252.65
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ndn±1-13.nax2.gvi.net/208.12.252.65
205.152.23.2/205.152.23.2
nex8.joplin93.getonthe.net/208.142.6.93
nex8.joplin93.getonthe.net/208.142.6.93
rhicknan.oapus.vt.edu/198.82.64.30
rhicknan.canus.vt.edu/198.82.64.30
user-37kb5js.dialup.mindspring.cc/207.69.150.124
m159.doubled.comr209.84.193.159
m159.doubled.can/209.84.193.159
143.216.14.30/143.216.14.30
glum.nlia.mit.edu/18.85.25.34
204.7.161.88/204.7.161.88
grunbO.stud.kvl.dk/130.225.189.44
Dialup243-169.Tleet.NET/208.13.243.169
Dialup243-169.Telnet.NET/208.13.243.169
port10.waverider.co.uk/194.207.148.39
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port10.waverider.o
media.mdt. edu/18.85.21.80
nrkay.
8
nrkay.media.mit. edu/18.85.21. 0
207.22.218.77/207.22.218.77
nrkay.nedia.mit.edu/18.85.21.80
n
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nkay.media.nt.edu/18.85.21.80
89
h189.ozenill.ozeil.ccm.au/203.108.15.1
nekay.nedsia.mit.edu/18.85.21.80
n=kay.meqdia.mit.edu/18.85.21.80
pool-207-205-150-13.chia.grid.net/207.205.150.13
gagerpp2.ln.org/199.212.94.194
gageppp2.lcn.org/199.212.94.194
203.240.157.24/203.240.157.24
pp98.207.redestb.es/195.122.207.98
celerity.deton.co.uk/194.222.167.110
PPP-86-11.HJ.HUJ/128.197.8.191
33 2
66
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123.usrO4.shef.dialup.force
castle.bank.lv/159.148.33.253
castle.bank.lv/159.148.33.253
castle.bank.lv/159.148.33.253
castle.bank.lv/159.148.33.253
castle.bank.lv/159.148.33.253
3
castle.bank.lv/159.148.33.25
3
8 33
castle.bak.lv/159.14
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2 3
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castle.bank.lv/159.14
castle.bank.lv/159.148.33.253
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207-172-62-121.s121.tnt2.ra.erols.ccV20
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205.138.223.69/205.138.223.69
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A17-202-13-85.aople.om/17.202.13.85
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7 7
0.10
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dyn-107-175.interval.cun/199.1
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ppp-011.m2-16.tor.ican.net/142.15
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42
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ppp-011.m±2-16.tor.ican.net/1
glumo.media.mit.edlu/18.85.25.34
glum.nedia.mit.edu/18.85.25.34
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glum.nedia.mit.edu/18.85.25. 4
glum.nedia.mit.edu/18.85.25.34
glum.media.mit.edu/18.85.25.34
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unknc 151-167.segasoft.can/206.189.151.16
glum.media.mit.edu/18.85.25.34
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glum.media.mit.edu/18.85.25. 4
glum.media.mit.edu/18.85.25.34
glum.media.mit.edu/18.85.25.34
beowulf.ucsd.edu/132.239.17.2
frutiger.nedia.mxit.edu/18.85.21.72
frutiger.media.mit.edu./18.85.21.72
frutiger.nedia.m±t.edu/18.85.21.72
2 72
frutiger.nedia.miit.edu/18.85. 1.
2111
2112
2113
2114
2115
2116
2117
2118
2119
2120
2121
2122
2123
2124
2125
2126
2127
2128
2129
2130
2131
2132
2133
2134
2135
2136
2137
2138
2139
2140
2141
2142
2143
2144
2145
2146
2147
2148
2149
2150
2151
2152
2153
2154
2155
2156
2157
2158
2159
2160
2161
2162
2163
2164
2165
2166
2167
2168
2169
2170
2171
2172
2173
2174
2175
2176
2177
2178
2179
2180
2181
2182
2183
2184
2185
2186
2187
2188
2189
2190
2191
2192
2193
2194
2195
2196
2197
2198
2199
2200
2201
2203
2204
2205
2206
2207
2208
2209
2210
2211
2212
2213
2214
2215
M
M
M
M
M
M
M
M
M
M
M
M
M
M
GLOM:Information Agglomerates
116
date
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980424
980425
980425
980425
980425
980425
980425
980425
980425
980425
980425
980425
980425
980425
980425
960425
980425
980425
980425
980425
980425
980425
980425
980425
980425
980426
980426
980426
980426
980426
980426
980426
980426
980426
980426
980426
980426
980426
980426
980426
980426
980426
980426
980426
980426
980426
980426
980426
980427
980427
980427
980427
980427
time
9:11:20 AM
10:19:11 AM
10:41:11AM
11:11:00 AM
11:15:46AM
11:18:48 AM
11:26:23AM
11:31:58 AM
11:37:03AM
11:39:05AM
11:42:34AM
11:45:01AM
11:47:33AM
11:50:43AM
11:51:50AM
11:52:48 AM
11:52:59AM
11:59:58AM
12:00:150M
12:02:02FM
12:05:02FM
12:05:27FM
12:12:29
rM
3:50:10FM
3:55:53FM
4:08:12 1M
4:29:26FM
5:31:52FM
5:34:36 FM
5:36:03FM
5:38:10 FM
5:39:30 FM
5:41:20FM
5:45:39FM
5:49:36M
5:52:55FM
6:12:50FM
6:14:41FM
6:48:50FM
6:52:21FM
6:52:31FM
6:57:03FM
7:51:23FM
7:53:03FM
8:29:00FM
8:31:11FM
8:49:54FM
8:52:03FM
10:43:45FM
10:44:19FM
10:45:59FM
10:46:45FM
1:24:47AM
5:57:31AM
6:07:19AM
6:14:43AM
6:24:46AM
6:52:30AM
6:55:15AM
6:56:33AM
6:57:46AM
AM
11:21:01
3:21:57FM
4:13:55FM
4:15:50FM
4:32:02FM
5:13:35FM
5:29:25FM
5:32:55FM
5:34:59FM
5:38:08 FM
5:39:27FM
5:40:13FM
6:01:12FM
6:06:35FM
8:53:28 FM
12:04:58AM
12:14:58AM
12:16:21AM
12:51:58AM
12:58:16AM
1:01:32AM
7:13:03AM
8:10:00AM
1:03:10FM
1:04:01FM
2:05:46FM
2:06:01FM
2:22:18FM
2:34:55FM
4:30:54FM
6:43:43FM
6:45:38FM
6:46:29FM
6:47:31FM
6:50:09FM
6:56:54FM
6:57:10FM
7:32:27FM
6:31:12AM
7:11:06AM
7:11:29AM
7:12:13AM
7:12:51AM
score
21300
3300
0
3400
3000
2600
15650
4350
8100
4050
0
7400
7500
8300
1200
8400
4300
22250
9250
8450
9900
8100
10750
37350
9650
4750
3350
3450
4450
3000
6000
4100
4950
25800
25650
19300
6350
5400
5400
19050
50
4750
3500
1850
2850
5100
3400
3550
300
0
300
0
0
0
1
0
0
3100
8100
0
7800
4250
250
2900
1500
0
3500
2300
6100
3300
7000
12100
8150
3500
4250
3900
4500
500
1100
2550
7900
11650
2400
0
1850
600
0
600
0
1250
7100
2650
2050
4250
1850
3950
0
8400
0
3750
1850
6050
3650
1850
duration
145
236
125
234
156
140
440
103
282
97
48
130
137
110
40
311
116
400
299
103
143
292
272
456
90
162
129
80
147
69
114
64
56
244
216
185
151
100
49
200
37
184
140
85
87
113
105
113
140
23
82
29
54
3
1
2
1
90
140
1
136
129
147
165
95
71
82
56
117
108
53
249
65
30
56
109
197
61
55
170
363
485
90
31
173
37
baddias
30
6
0
6
6
4
57
7
17
9
0
17
14
16
2
19
10
43
21
18
19
18
31
77
18
10
6
8
10
5
10
8
9
52
54
41
18
11
12
31
0
12
8
3
10
13
6
8
0
0
0
0
0
0
1
0
0
5
18
0
17
10
0
8
6
0
6
5
13
7
10
20
12
5
7
8
11
2
4
7
23
25
4
0
3
1
253
0
78
20
44
218
183
99
265
46
253
74
404
114
92
35
128
95
86
3
0
2
20
6
5
10
6
15
0
18
0
8
3
14
7
6
GLOM:Information Agglomerates
hits
290
47
0
38
36
28
340
72
166
51
120
231
262
372
12
179
191
613
182
221
403
167
303
862
399
59
38
63
59
43
105
46
262
740
710
580
133
125
103
317
67
70
46
43
96
91
43
88
87
18
101
41
4
0
1
0
0
40
154
0
253
73
13
114
98
2
43
35
186
43
194
278
193
75
101
53
60
37
53
55
164
322
24
0
19
8
0
61
0
13
148
75
57
58
90
110
0
138
0
48
24
175
64
65
shots
914
287
1
480
618
709
6427
242
1141
456
371
1015
924
1069
27
565
1004
3436
754
1066
1269
1218
1431
3632
1060
243
158
348
703
214
359
205
725
3225
2620
2846
409
255
590
1254
82
219
152
118
256
235
88
170
161
22
128
46
23
0
1
0
0
104
316
0
397
389
32
247
254
3
160
97
346
121
219
470
285
125
119
173
268
90
113
189
975
739
308
1
70
27
0
116
3
45
524
192
184
153
114
216
0
611
7
199
55
355
374
177
ip address of player
7
tschichled.nedia.mit.edu/18.85.21. 1
150.113.82.96/150.113.82.96 7
64
5.1 .20
unrtinique.ai.fh-nuernberg.de/141.
206.65.39.26/206.65.39.26
206.65.39.26/206.65.39.26
206.65.39.26/206.65.39.26
206.65.39.26/206.65.39.26
206.65.39.26/206.65.39.26
206.65.39.26/206.65.39.26
206.65.39.26/206.65.39.26
206.65.39.26/206.65.39.26
206.65.39.26/206.65.39.26
206.65.39.26/206.65.39.26
206.65.39.26/206.65.39.26 7
2
frutiger.nedia.mit.edu/18.85.21.
193.189.235.63/193.189.235.63
206.65.39.26/206.65.39.26
206.65.39.26/206.65.39.26
155.33.46.180/155.33.46.180
206.65.39.26/206.65.39.26
206.65.39.26/206.65.39.26
155.33.46.180/155.33.46.180
155.33.46.180/155.33.46.180
dynic-10.media.mit.e4u/18.85.12.138
dynami-c--10.media.mnit.edu/18.85.12.138
147.4.20.87/147.4.20.87
client.cabrillo.cc.ca.us/207.62.186.254
6
6
sp8.mth.unn.edu/160.94. .13
sp8.nmth.unn.edu/160.94.6.136
sp8.mth.tmn.edu/160.94.6.136
sp8.mth.urn.edu/160.94.6.136
sp8.mth.un.edu/160.94.6.136
sp8.mth.unn.ed.u/160.94.6.136
sp8.mth.unn.edu/160.94.6.136
sp8.mth.un.edu/160.94.6.136
sp8.mth.unn.edu/160.94.6.136
77
t-csec-10-6-p16.dialup.wisc.edu/144.92.210.1
77
44 92 2
. . 10.1
t-cssc-10-6-p16.dialup.wisc.edu/1
igarashi.nedia.mit.edu/18.85.21.69
igarashi.n-edia.m±it.edu/18.85.21.69
unkrnn-151-225.segasoft.ac206.189.151.225
ts4-241.njcc.ccm/199.224.2.241
wlc77.cablelan.net/139.142.84.77
wlc77.cablelan.net/139.142.84.77
203.101.14.201/203.101.14.201
203.101.14.201/203.101.14.201
203.101.14.201/203.101.14.201
203.101.14.201/203.101.14.201
ttyB06.our-towtn.cn/206.64.104.69
ttyB06.our-town.ccV206.64.104.69
ttyB06.our-town.ccn/206.64.104.69
ttyB06.our-town.a-fV206.64.104.69
74
an.ne.nvetdiaoe.net/24.128.101.
2 34
5.
glun.edia.nit.edu/18.85.
glum.edia.rit.edu/18.85.25.34
glun.media.rit.edu/18.85.25.34
glum.media.dt.edu/18.85.25.349 4 6 4
ztm-isdn2-03.dial.xs4all.nl/194.10
64
94
9 .4 8.1
ztm-isdn02-03.dial.x-4all.nl/1 .10 . 8.1
glum.mdia.mit.edu/18.85.25.34 94
64
9 4
.10 . 8.1
ztm-iodn02-03.dial.xs4all.nl/1
208.25.184.62/208.25.184.62
id#
2216
2217
2218
2219
2220
2221
2222
2223
2224
2225
2226
2227
2228
2229
2230
2231
2232
2233
2234
2235
2236
2237
2238
2239
2240
2241
2242
2243
2244
2245
2246
2247
2248
2249
2250
2251
2252
2253
2254
2255
2256
2257
2258
2259
2260
2261
2262
2263
2264
2265
2266
2267
2268
2269
2270
2271
2272
2273
2274
2275
2276
2277
2278
2279
2280
2281
2282
2283
2284
2285
2286
2287
2288
2289
2290
2291
2292
2293
2294
2295
2296
2297
2298
2299
2300
2301
2302
2303
2304
2305
2306
2307
2308
2309
2310
2311
2312
2313
2314
2315
2318
2319
2320
2321
1C19F3D8E.dip.t-online.de/193.159.61.142
199.6.61.73/199.6.61.73
199.6.61.73/199.6.61.73
plne ec.toronto.edu/128.100.2.146
195.60.92.156/195.60.92.156
7
cx36536-a.vistal.edca.hcue.am24.0.1 8.52
cx36536-a.vista1.sdca.hce.can/24.0.178.52
vanc01O1-25.bctel.ca/206.108.197.25
cx36536-a.vistal.sdc.hce.can/24.0.178.52
va±nc01O1-25.bctel.ca/206.108.197.25
cx36536-a.vistal.sdca.bsecncc/24.0.178.52
cx36536-a.vista.sdca.he.cacn/24.0.178.52
cx36536-a.vistal.sdca.hcne.can/24.0.178.52
phxOltap160.sgum.mci.ccm/205.218.173.160
ridkenia.xnet.caV204.248.48.27
.in.da.uu.net/153.37.208.247
1Cust247.tnt.valparais
7
1Cust247.tnt1.valparais.in.da.uu.net/153.37.208.24
171-213-114.ipt.aol.can152.171.213.114
171-213-114.ipt.aol.ccv152.171.213.114
spc-isp-tor-uas-18-14.sprint.ca/209.5.19.115
men-54.aul.b.uunet.de/149.229.255.54
49 2 9
.1
dul29-249.ppp.algonet.se/195.100.2
qtae0320.singnet.can.sg/165.21.56.150
qtas0320.singnet.ccmn.sg/165.21.56.150
fr-hall-student-54.lut.ac.uk/131.231.242.54
fwasc6-19.flash.net/209.30.15.19
su1l-8.ida.liu.se/130.236.186.127
nrex8.joplin88.getonthe.net/208.142.6.88
7
6
.3
fw.itasnet/142.176.1
7
207-172-131-71.s8.as14.col.erols.canV207.172.131.
71
1
207-172-131-71.s8.as14.col.erls.cacn/207.172.131.
WS-69
SO-04.dyess.af.mil/131.59.193.84
iM-1SFO--04.dyess.af.mil/131.59.193.84
0 .1 .131.1
207-172-131-71.s8.as14.col.erols.can/
2 7
72
7
e.tccw.wku.edu/161.6.9.13
cpc04-a
7
3 7
2.1 1. 1
207-172-131-71.s8.asl4.col.erols.can/207.1
hp-99.cae.wisc.edu/144.92.241.119
194.68.71.65/194.68.71.65
firewall.krak.dk/193.89.85.2
beluga.cs.mlumbia.edu/128.59.22.148
beluga.cs.columbia.edu/128.59.22.148
6
pax--166.cis.ru/194.58.133.16
117
date
time
score
duration
baddies
hits
shots
ip address of
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980427
980428
980428
980428
980428
980428
980428
980428
980428
980428
980428
980428
980428
980428
980428
980428
980428
980428
980428
980428
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980429
980430
980430
980430
7:13:19 AM
7:13:47AM
7:14:09AM
AM
10:24:43
11:03:23
AM
AM
11:27:51
11:29:55AM
11:44:59AM
1:41:222M
3:16:4489
3:19:31R4
5:07:53H4
6:56:282M
6:58:38PM
6:59:14PM
6:59:45PM
7:10:372M
7:11:06PM
7:11:3324
7:12:17
7:12:582M
7:13:302M
7:15:30PM
7:16:11
7:16±54
7:17:34
7:29:1624
8:03:302M
8:49:522M
8:53:122M
8:57:222M
11:21:14AM
11:28:17 AM
11:57:59 AM
12:56:00
2:08:0524
2:22:41
2:23:34
5:47:33
5:56:00
6:24:12
6:48:3324
8:22:41
8:38:0524
8:40:4224
8:41:412M
8:42:082M
9:53:082M
10:18:1024
11:37:0824
1:35:33AM
2:43:36AM
4:31:03AM
5:19:31AM
6:44:08AM
6:47:04AM
8:16:23AM
9:58:20AM
10:06:00AM
11:07:31AM
11:08:48AM
11:32:06AM
11:33:22AM
12:39:492M
12:41:142M
2:10:522M
2:13:422M
2:15:0224
2:17:07
2:21:382M
2:24:252M
2:26:0224
3:13:442M
3:20:552M
3:53±06PM
3:55:162M
4:24:00
4:27:372M
4:29:08PM
4:31:21FM
4:34:472M
4:39:372M
4:41:182M
4:42:5424
4:45:002M
4:47:492M
4:48:062M
4:52:2124
4:53:4824
5:27:1524
5:29:462M
5:33:392M
5:48:352M
7:08:2824
7:47:09PM
7:48:18
7:51:52
8:50:14
2M
10:37:09
2M
10:39:06
2M
11:36:48
1:38:08AM
1:38:52 AM
1:39:24AM
8800
1250
1550
1800
3350
0
0
0
2250
9400
18500
0
3700
0
0
1100
0
0
1300
250
750
600
1700
600
600
50
1750
5050
2550
5350
7050
200
4050
3400
3200
600
1550
2700
1800
2400
2300
3900
650
3300
10100
0
4750
0
5850
1250
7750
0
5250
0
3900
10250
2650
5200
4300
3250
2400
2200
350
1400
2300
0
4550
2700
2900
2900
5250
3750
3000
44950
20000
1250
3550
4800
3400
3800
4000
6950
4250
250
7900
5150
0
8400
4100
10450
7000
6800
3450
0
0
750
3750
7700
1800
2050
2300
5200
50
50
154
90
62
153
138
149
101
154
109
168
155
96
87
21
21
15
11
13
11
21
27
16
80
26
27
26
137
262
161
169
65
322
128
303
82
133
61
37
67
83
77
131
85
231
778
4
168
48
177
109
244
50
269
131
79
161
75
129
153
58
60
84
65
64
28
69
153
56
92
102
151
80
51
1898
996
90
140
181
92
119
187
191
84
62
206
151
4
170
60
223
134
195
171
53
77
52
198
240
74
100
98
143
24
17
17
4
6
3
5
0
0
0
9
19
31
0
9
0
0
1
0
0
1
0
1
1
4
1
1
0
3
11
6
8
10
0
9
9
7
1
4
4
3
5
5
9
2
6
25
0
11
0
17
5
17
0
21
0
10
21
5
13
11
6
5
5
0
2
3
0
9
5
6
6
12
9
5
106
46
4
7
10
8
15
15
27
8
0
17
12
0
18
8
22
17
17
8
0
0
2
9
15
3
3
7
11
0
0
143
50
49
25
50
3
0
5
81
430
492
0
70
7
27
34
18
21
38
5
9
6
39
9
14
13
41
75
102
173
179
11
54
101
40
52
61
31
55
73
60
88
15
36
236
0
88
0
144
69
206
3
173
0
100
229
39
108
103
43
34
43
14
23
109
0
58
53
34
38
78
51
30
1288
614
71
48
119
47
130
114
173
67
5
167
68
0
155
67
287
125
124
57
3
0
53
112
190
18
23
57
179
41
30
317
106
143
101
458
26
0
23
234
924
867
0
253
19
27
35
18
22
38
30
37
8
112
9
21
51
106
242
251
400
268
24
181
433
115
79
79
82
178
178
90
307
50
390
720
0
232
15
425
149
588
11
920
43
165
424
135
323
288
101
148
110
53
59
131
2
186
128
98
127
286
175
53
4846
2104
223
139
423
132
246
235
328
212
9
539
530
0
477
179
664
506
544
231
10
6
137
368
463
30
95
157
360
82
48
pox-166.cis.ru/194.58.133.166
anduin.et.tudelft.nl/130.161.39.34
anduin.et.tudelft.nl/130.161.39.34
208.223.32.151/208.223.32.151
194.47.138.86/194.47.138.86
cynthiav.hu.bonus.cmc/195.228.57.122
cynthiav.hu.bonus.ccm/195.228.57.122
198.36.224.177/198.36.224.177
p17.tc9.metro.MA.tiac.cm/209.61.77.18
dynamic-18.media.mit.edu/18.85.12.146
8 8
dynamic-18.nedia.mit.edu/1 . 5.12.146
198.243.81.15/198.243.81.15
nesis.hlib.washington.edu/128.95.122.69
tschicnld.media.dit.edu/18.85.21.71
tschichold.nlia.nit.edu/18.85.21.71
tschichold.media.nit.edu/18.85.21.71
tochichold.media.mit.edlu/18.85.21.71
tschicr1d.nelia.nit.edu/18.85.21.71
it.edu/18.85.21.71
tochicrld.nedia.
tschichold.nlia.mit.edu/18.85.21.71
tschichold.media.mit.edu/18.85.21.71
tschichold.oedia.mit.edu/18.85.21.71
tschichold.media.nit.edu/18.85.21.71
tschichold.nedia.mit.edu/18.85.21.71
tschiclld.media.mit.edu/18.85.21.71
tschichold.nedia.mit.edu/18.85.21.71
205.149.126.101/205.149.126.101
nibusO08.und.edu/129.2.4.22
cust174.webbernet.net/208.205.95.174
7
cust174.wehoernet.net/208.205.95.1
74
4
cust174.welbernet.net/208.205.95.1
s1-3.vipxlnet.cca/206.47.93.13
206.215.193.2/206.215.193.2
aladin.eur.nl/130.115.1.102
194.215.211.28/194.215.211.28
198.36.224.178/198.36.224.178
207.73.129.121/207.73.129.121
207.73.129.121/207.73.129.121
207.15.215.156/207.15.215.156
207.15.215.156/207.15.215.156
firew11.sdnet.net/137.118.11.193
199.201.192.150/199.201.192.150
62.76.6.15/62.76.6.15 0 0
7
.62.15
200-62-175.ipt.aol.cu/152.2
128.100.46.54/128.100.46.54
128.100.46.54/128.100.46.54
202-131-203.ipt.aol.cc/152.202.131.203
207.194.176.164/207.194.176.164
ppp077.connect.ab.ca/207.34.79.77
7
liv16-43.idirect.ccn/207.136.108.10
es208-15.studet.washington.edu/140.142.171.118
lithium.helios.nd.edu/129.74.220.3
7
dialup97-2-13.swipnet.se/130.244.97.7
cynthiav.hu.bnus.cam/195.228.57.122
d84.ryd.studet.liu.se/130.236.235.84
d84.ryd.student.liu.se/130.236.235.84
7
10-26-17.amapolis.nsec.ns.a/142.227.26.1
38.230.14.107/38.230.14.107
38.230.14.95/38.230.14.95
ws107.ini.cz/195.212.195.107
wsl07.ini.cz/195.212.195.107
ws103.ini.cz/195.212.195.103
porsche.pd.lonn.sco.camV150.126.9.73
h0010107.smdth.ilstu.edu/138.87.201.7
h0010107.smith.ilstu.ed.u/138.87.201.7
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
wireless-83.media.m±it.edu/18.85.18.83
38.230.14.95/38.230.14.95
38.230.14.95/38.230.14.95
205.218.188.79/205.218.188.79
168.28.83.151/168.28.83.151
168.28.83.151/168.28.83.151
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
6
66
.21
c266216.exten.laowrmeeille.org/38.162.
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
208.148.188.31/208.148.188.31
206.6.58.134/206.6.58.134
thelonious.ne.o.ac.uk/163.1.145.129
68
du68-1.P.algonet.se/195.100.1.
68
du68-1.pp.algonet.se/195.100.1.
du68-1.ppp.algnet.se/195.100.1.68 0 7
.20
208-211-100-207.dynamic.nol.net/208.211.10
trt-on20-34.netcn.ca/207.181.87.162
trt-n20-34.netccm.ca/207.181.87.162
ol-31.kclab.nuhave.cc.az.us/206.207.55.210
dul32-4.op.algonet.se/195.100.4.132
du132-4.ppp.algonet.se/195.100.4.132
dul32-4.ppp.algonet.se/195.100.4.132
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
GLOM:Information Agglomerates
player
id#
2322
2323
2324
2326
2327
2328
2329
2330
2331
2332
2333
2334
2335
2336
2337
2338
2339
2340
2341
2342
2343
2344
2345
2346
2347
2348
2349
2350
2351
2352
2353
2354
2355
2356
2357
2358
2359
2360
2361
2362
2363
2364
2365
2366
2367
2368
2369
2370
2371
2372
2373
2374
2375
2376
2377
2378
2379
2380
2381
2382
2383
2384
2385
2386
2387
2388
2389
2390
2391
2392
2393
2394
2395
2396
2397
2398
2399
2400
2401
2402
2403
2404
2405
2406
2407
2408
2409
2410
2411
2412
2413
2414
2415
2416
2417
2418
2419
2420
2421
2422
2423
2424
2425
2426
118
date
time
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
1:40:19 AM
1:45:53AM
2:51:35AM
4:18:15AM
4:38:23AM
4:42:27AM
5:15:54AM
6:32:00AM
6:36:39AM
6:54:31AM
7:07:18AM
7:25:14AM
8:02:23AM
8:15:54AM
8:16:26AM
8:19:08AM
8:19:46AM
8:25:08AM
9:05:58AM
9:13:42AM
9:14:55AM
9:15:05AM
9:15:31AM
9:16:20AM
9:17:24AM
9:19:14AM
9:26:36AM
9:34:26AM
9:40:05AM
9:45:50AM
10:00:07
AM
10:45:44
AM
10:46:19
AM
11:15:47AM
11:22:27AM
11:28:25
AM
11:29:10AM
11:32:16
AM
11:32:35AM
11:34:53AM
AM
11:34:55
11:37:51
AM
11:39:15
AM
11:41:26
AM
11:41:36
AM
11:43:18
AM
11:44:36
AM
11:45:20
AM
11:45:40
AM
11:45:54
AM
AM
11:48:54
11:50:24
AM
11:55:11
AM
11:55:13
AM
12:08:17
RM
12:14:2294
12:31:23
R4
12:34:26
rM
1:20:26SM
1:23:30PM
1:31:4624
1:33:32SM
1:46:00EM
1:54:28PM
2:02:27PM
2:07:36SM
2:31:01SM
2:35:52FM
2:37:58IM
2:40:07SM
2:40:11PM
2:42:12PM
2:43:27SM
2:44:01SM
2:56:10PM
2:59:32SM
3:14:04SM
3:36:14SM
3:38:39SM
3:39:54SM
4:01:25FM
4:14:40
4:15:37SM
4:16:36SM
4:18:31 4
4:21:49
4:22:40SM
4:23:52EM
4:24:15SM
4:28:48FM
4:32±50SM
4:36:56SM
4:43:35SM
4:49:28
4:49:31SM
4:53:06
5:25:10SM
5:27:06
5:28:06SM
5:31:05EM
5:33:09SM
5:33:43SM
5:36±18SM
5:37:08SM
M
M
M
M
M
score
3350
4900
3200
2600
6550
7450
0
5000
8600
4800
4600
4600
0
2200
5500
4700
3100
3350
250
950
0
5850
2100
1700
600
3800
8300
9750
7900
7650
3750
1950
0
4500
6150
500
2400
4300
4000
3500
1550
3900
1900
3750
1950
1400
550
1400
100
3750
1050
2750
950
0
0
11000
6850
4050
4100
1200
7100
24950
750
1300
4950
1450
3250
3550
2450
1950
4550
4450
4800
5800
350
4500
18750
1900
1350
2200
5250
750
1650
1750
0
11550
2400
4850
3700
1250
4800
7350
3900
1200
7800
1850
3500
3000
750
3700
3750
1650
200
2900
duration
37
109
542
218
216
220
356
260
262
176
151
107
1
142
274
308
185
305
181
92
49
298
292
59
96
158
532
442
322
327
168
49
92
390
382
144
182
399
188
122
142
157
245
289
142
81
90
28
134
376
158
253
242
85
109
339
269
166
545
36
191
180
171
124
503
161
69
80
110
93
119
105
173
94
172
197
898
104
130
61
257
75
41
44
79
295
159
107
60
107
155
231
175
104
300
352
141
100
42
163
112
92
195
133
GLOM:Information Agglomerates
baddies
4
11
7
6
12
15
0
12
32
15
11
11
0
4
15
10
10
6
1
1
0
17
7
6
1
8
15
22
15
15
8
6
0
10
19
2
5
11
8
7
5
10
3
14
5
2
1
4
0
9
1
9
3
0
0
42
12
9
9
1
13
41
1
2
10
3
6
6
4
3
7
10
12
14
1
9
49
6
5
6
14
3
6
7
0
42
4
13
6
5
10
15
10
3
17
5
7
5
3
7
10
6
0
5
hits
79
81
57
77
101
139
0
91
234
112
62
113
0
26
82
62
105
41
38
13
12
163
82
100
6
46
226
251
169
139
45
74
11
93
155
19
32
101
102
75
89
60
21
135
50
18
28
63
18
53
83
88
67
0
2
276
143
85
56
90
157
402
49
19
105
91
41
49
35
21
86
125
83
137
7
118
551
58
95
83
121
34
50
52
0
268
27
132
38
45
96
138
60
31
159
99
45
33
36
44
117
84
4
51
shots
105
548
262
223
289
432
18
444
588
561
296
336
0
302
448
448
531
878
130
75
14
1317
591
162
57
519
1014
658
579
489
298
105
48
440
675
49
345
512
344
198
200
237
247
715
216
78
276
117
108
333
231
220
238
2
5
687
446
298
344
92
246
1606
62
91
433
195
112
144
69
106
148
259
471
342
10
328
1895
315
554
192
348
124
190
207
7
1563
139
379
110
140
308
456
262
95
634
616
96
81
61
157
226
186
27
271
ip address of player
du32-4.ppp.algonet.se/195.100.4.132
h0010107.siLth.i1stu. edu/138.87.201.7
F502-37.nrin r.or.jp/202.239.141.37
dnitche.doa.state.1a.us/192.206.109.131
ad114-169.nngix.cm.sg/165.21.114.169
ad114-169.negix.ccrm.sg/165.21.114.169
h38.s25.ts3O.hinet.net/163.30.25.38
SY-A08-pool-189.tan.net.au/139.134.92.189
SY-A08-pool-189.tun.net.au/139.134.92.189
21.new-york-10.ny.dial-access.att.net/12.68.9.21
210.112.207.253/210.112.207.253
193.45.130.36/193.45.130.36
t1o63p74.telia.crn/195.198.44.74
150.104.89.177/150.104.89.177
id#
2427
2428
2429
2430
2431
2432
2433
2434
2435
2436
2437
2438
2439
2440
2441
168.221.114.152/168.221.114.152
2442
2443
o4-33.dialup.seed.net.tw/139.175.4.33
o4-33.dialup.seed.net.tw/139.175.4.33
2444
pp108.brandywine.net/207.106.54.40
2445
2446
norph.grd.de/192.76.245.44
2447
orph.grrd.de/192.76.245.44
stk-pw223.gotnet.net/207.104.58.223
2448
pppl08.brandywine.net/207.106.54.40
2449
stk-pw223.gotnet.net/207.104.58.223
2450
2451
ppp108.brandywine.net/207.106.54.40
stk-pw223.gotnet.net/207.104.58.223
2452
psplO8.brandywine.net/207.106.54.40
2453
ppp108.brandywine.net/207.106.54.40
2454
2455
2456
apl108.brandywine.net/207.106.54.40
2457
dialup187-2-12.swixpet.se/130.244.187.76
2458
ws103.ini.cz/195.212.195.103
2459
208.158.171.12/208.158.171.12
2460
168.221.114.131/168.221.114.131
2461
168.221.114.131/168.221.114.131
2462
h187n105.cpsboe.kl2.oh.us/198.203.105.187
2463
168.221.114.131/168.221.114.131
2464
desm-16-55.dialup.netins.net/167.142.17.184
2465
168.221.114.131/168.221.114.131
2466
168.221.114.131/168.221.114.131
2467
deno-16-55.dialup.netins.net/167.142.17.184
2468
168.221.114.131/168.221.114.131
7
7
2469
.142.1.184
den-16-55.dialup.netins.net/16
2470
168.221.114.132/168.221.114.132
2471
168.221.114.125/168.221.114.125
2472
168.221.114.125/168.221.114.125
2473
jam.calibresys.can/208.206.170.15
2474
jam.calibresys.can/208.206.170.15
2475
168.221.114.126/168.221.114.126
2476
desm-16-55.dialup.netins.net/167.142.17.184
2477
desm-16-55.dialup.netins.net/167.142.17.184
2478
168.221.114.126/168.221.114.126
2479
168.221.114.126/168.221.114.126
2480
170.143.130.162/170.143.130.162
2481
204.133.199.140/204.133.199.140
2482
209.2.245.26/209.2.245.26
2483
pp108.brandywine.net/207.106.54.40
2484
2485
202.175.3.111/202.175.3.111
2486
168.99.152.81/168.99.152.81
2487
su±n21.enin.brown.edu/128.148.54.31
2488
kirby.media.mit.edu/18.85.21.34
2489
st227.d50.tazewell.k12.IL.US/207.63.38.227
2490
st227.d50.tazeell.kl2.IL.US/207.63.38.227
2491
st227.d50.tazewell.k12.IL.US/207.63.38.227
2492
st227.d50.tazewe11.kl2.il.us/207.63.38.227
2493
206.135.224.253/206.135.224.253
2494
208.224.45.32/208.224.45.32
2495
208.224.45.32/208.224.45.32
2496
208.224.45.42/208.224.45.42
2497
208.224.45.32/208.224.45.32
2498
208.224.45.32/208.224.45.32
2499
208.224.45.42/208.224.45.42
2500
208.224.45.32/208.224.45.32
2501
dynO11psp47.pacific.net.g/210.24.101.47
7
2502
dyn101ppp47.pacific.net.sg/210.24.101.4
7
2503
pp>-6-19.nn.visi.net/206.246.199.14
2504
wav4-cs-2.dial.bright.net/205.212.155.54
2505
2506
vav4-cs-2.dial.bright.net/205.212.155.54
2507
209.66.196.173/209.66.196.173
7
7
2508
.228.6.52
ts71ip52.cadvision.ccm/20
2509
ts71ip52.cadvisio.ccm/207.228.76.52
2510
ts7lip52.cadvision.a-M/207.228.76.52
dyn1-tntl-28.cleveland.oh.aneritech.net/199.179.175.28 2511
2512
ts71ip52.cadvision.ccf/207.228.76.52
2513
pub-10-a-7.dialup.unn.eu/160.94.25.7
2514
ts7lip52.cadvision.coc/207.228.76.52
2515
knx-tn7-14.ix.netcan.ccm/205.184.139.174
2516
168.28.82.83/168.28.82.83
2517
user-37kb6tk.dialup.mindspring.ccu/207.69.155.180
2518
user-37kb6tk.dialup.mindspring.Amn/207.69.155.180
2519
van-as-06b02.direct.ca/204.174.249.66
2520
slipl66-72-247-107.no.us.ih±n.net/166.72.247.107
2521
van-as-06b02.direct.ca/204.174.249.66
2522
dial-as2-34.poci.net/206.160.255.36
2523
rewl-01-40.dialup.netins.net/209.152.68.105
2524
rewl-01-40.dialup.netins.net/209.152.68.105
2525
cewl-01-40.dialup.netins.net/209.152.68.105
2526
rcwl-01-40.dialup.netins.net/209.152.68.105
2527
dialin-12.poughkeepsie.bestweb.net/209.94.109.46
2528
AS52-15-240.cas-kit.golden.net/209.183.130.240
2529
slip129-37-206-39. in.us.ihnm.net/129.37.206.39
2530
AS52-15-240.cas-kit.goldms.net/209.183.130.240
s4-33.dialup.seed.net.tw/139.175.4.33
pplO8.brandywine.net/207.106.54.40
mp108.brandywine.net/207.106.54.40
Amv4-cs-2.dial.bright.net/205.212.155.54
119
dats
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
980430
985430
985430
980430
980430
980430
980430
980430
980501
980501
980501
980501
980501
980501
980501
980501
time
5:37:46 24
5:42:41 FM
5:44:24 2M
5:48:24 R4
6:01:25 2M
6:02:482M
6:03:54R4
6:05:492M
6:07:03P4
6:07:422M
6:08:202M
6:11:20 2M
6:11:58 2M
6:12:03 24
6:12:122M
6:14:19PM
6:16:5224
6:19:372M
6:22:03R4
6:27:412M
6:28:482M
6:29:462M
6:30:2924
6:33:322M
6:33:372M
6:35:4124
6:39:542M
6:41:5624
6:43:4824
6:48:5824
6:49:182M
6:52:1424
6:53:5924
6:55:0624
6:57:4224
6:59:5824
7:10:112M
7:12:4224
7:13:022M
7:14:4224
7:26:1524
7:29:52EM
7:37:0824
7:42:012M
7:43:252M
7:47:002M
7:48:5024
7:49:532M
7:51:0924
7:52:5824
7:57:0924
7:57:332M
8:14:06 24
8:17:53 24
8:18:0324
8:19:102M
8:19:5124
8:24:472M
8:24:542M
8:26:00 2M
8:26:57 24
8:30:352M
8:31:052M
8:31:142M
8:32:27 2M
8:36:06 2M
8:54:07 2M
9:09:33
9:13:08
9:23:12P
9:24:3524
9:25:10
9:25:58 24
9:27:52 2M
9:29:47
9:32:12
9:33:11 24
9:40:1624
9:41:3824
9:57:5524
9:59:142M
10:00:292M
10:20:10
10:21:082M
10:28:08
10:43:392M
10:50:14PM
10:55:1524
10:55:3024
11:03:4124
11:16:40
11:31:15PM
11:41:17
11:45:48PM
11:56:332M
11:59:21
12:57:41AM
1:16:47A4
2:29:23AM
2:51:46AM
5:14:42AM
7:39:34AM
7:44:42AM
7:55:11AM
M
M
M
M
M
M
M
M
M
M
score
3200
5150
7850
2150
1750
5500
8850
9350
1250
4600
1200
2400
5400
3250
6150
4850
8200
5200
7950
3550
3850
2950
3000
4800
3100
5000
7650
11200
8150
3850
2450
2650
1900
10150
4150
3600
2700
3550
1750
3050
4150
3650
1300
3150
2950
3800
3450
6350
1650
5350
10850
10750
4500
50
0
1000
10550
300
0
10250
1350
3800
100
4400
400
2650
7800
3750
8500
0
3400
3800
1800
4600
4500
3750
9100
5000
11550
450
1700
2650
23150
1150
4300
0
8450
5100
0
9350
0
0
2300
250
9100
4900
4300
5700
1200
5100
5150
4550
2950
44750
duration
baddies
hits
shots
ip address of player
164
375
378
128
151
481
412
534
62
159
156
208
534
243
248
160
270
239
288
138
116
103
79
168
84
113
345
254
83
186
121
248
88
307
206
120
180
134
104
105
221
204
195
126
143
81
187
226
59
233
344
331
142
71
4
49
437
131
3
419
100
172
41
243
162
248
276
161
191
53
106
100
67
146
101
220
189
127
547
162
71
59
179
114
181
1
383
284
4
474
98
40
116
88
228
139
107
170
23
383
131
222
270
917
9
12
17
8
5
11
20
22
3
9
4
4
13
5
13
11
13
12
15
7
7
6
5
8
8
8
15
23
12
7
9
5
7
25
7
7
4
7
5
5
11
7
2
7
5
7
7
14
6
12
22
22
9
0
0
4
25
1
0
34
2
7
0
9
0
7
16
8
16
0
8
6
7
11
9
8
19
13
38
1
6
6
36
1
9
0
25
9
0
22
0
0
9
0
19
9
9
12
2
16
10
18
6
179
52
80
157
81
46
104
165
213
21
80
59
30
75
61
102
66
186
87
178
44
52
35
42
66
143
79
151
342
231
48
102
29
74
269
80
44
39
44
80
35
97
43
16
39
42
64
46
114
67
91
284
276
56
1
0
58
287
6
0
238
15
50
2
77
8
47
237
85
192
0
54
41
91
89
73
45
171
105
252
9
95
64
346
58
108
0
179
89
0
162
15
0
109
7
234
194
110
115
12
121
101
125
38
932
148
354
360
392
211
523
604
869
46
243
141
96
421
266
524
136
377
219
321
170
159
160
109
204
196
187
386
584
310
142
302
212
127
606
307
126
121
147
146
133
504
609
34
130
209
117
239
332
138
290
1220
656
191
14
1
80
854
25
0
1843
32
199
2
263
14
195
526
173
292
0
237
121
289
277
308
306
512
216
1225
45
224
172
1535
88
419
0
885
655
0
1012
98
1
307
39
544
340
195
246
37
1176
258
1198
126
7070
167-143-192.ipt.aol.omn/152.167.143.192
us.ih±n.net/129.37.206.39
slipl29-37-206-39.in.
67
1 -143-192.ipt.aol.o n/152.167.143.192
cybers20d05.cg.wv.shaw.ca/24.64.20.75
tcl-135.constant.crnV208.6.184.135
slip129-37-206-39.in.us.ib.net/129.37.206.39
206.187.101.120/206.187.101.120
aus-tx23-21.ix.netoc.caV207.221.68.245
131.187.143.2/131.187.143.2
gpl8.brandywine.net/207.106.54.40
slip129-37-112-136.pa.us.ihn.net/129.37.112.136
lax-ca38-54.ix.netcan.oon/205.184.226.118
slip129-37-206-39.in.us.im.net/129.37.206.39
ppp108.brandywine.net/207.106.54.40
131.187.143.2/131.187.143.2
lax-ca38-54.ix.netcan.can/205.184.226.118
op108.brandywine.net/207.106.54.40
deerfieldnet71.voyager.net/198.109.118.71
GLOM:Information Agglomerates
id#
2531
2532
2533
2534
2535
2536
2537
2538
2539
2540
2541
2542
2543
2544
2545
2546
2547
2548
2549
2550
CP22.CS.CLL.E /128.84.248.153
2551
ppp108.brandywine.net/207.106.54.40
2552
4CP22.CS.CENELL.EW/128.84.248.153
2553
ppp108.brandywine.net/207.106.54.40
2554
ppp108.brandywine.net/207.106.54.40
2555
CP22.C.CGNELL.EINJ/128.84.248.153
2556
p108.brandywine.net/207.106.54.40
69.new-orleas-01.1a.dial-access.att.net/12.65.208.69 2557
2558
2559
CP22.CS.CENM.L.EIJ/128.84.248.153
ppp-207-214-212-42.sntc0l.pacbell.net/207.214.212.42 2560
2561
2071599883.bellatlantic.net/207.159.98.83
2562
206.187.133.133/206.187.133.133
2563
206.187.133.133/206.187.133.133
2564
2071599883.bellatlantic.net/207.159.98.83
2565
206.187.133.133/206.187.133.133
2566
206.187.133.133/206.187.133.133
2567
up-248-015.ppp-net.buffalo.edu/126.205.248.15
2568
utssp-248-015.ppp-net.uffalo.edu/128.205.248.15
2569
200-33-93.ipt.aol.ccrV152.200.33.93
2570
utgp-248-015.ppp-net.buffalo.edu/128.205.248.15
2571
crasl0p47.navix.net/205.242.144.176
2572
crasl0p47.navix.net/205.242.144.176
2573
192.138.182.94/192.138.182.94
2574
usr-twin-55.rnci.net/208.14.168.55
2575
24.138.26.141/24.138.26.141
2576
pd02-pn2-02.teleport. m/204.202.160.34
2577
d363n6.hsonline.net/208.10.214.134
2578
206.78.76.205/206.78.76.205
2579
206.78.76.205/206.78.76.205
2580
d363n6.hsonline.net/208.10.214.134
2581
206.78.76.205/206.78.76.205
2582
pdx02-pn-2-02.teleport.ccn/204.202.160.34
2583
usr40-dialup11.mix2.Atlanta.nri.net/166.55.60.203
2584
209.24.202.130/209.24.202.130
2585
209.24.202.130/209.24.202.130
2586
209.24.202.130/209.24.202.130
2587
204.183.206.97/204.183.206.97
2588
pr6-209.tstonranp.ccm/206.55.137.209
2589
pr6-209.tstnranp. ccu/206.55.137.209
2590
pn15-12.nagicnlt.net/206.104.204.205
2591
pr6-209.tstanranp.ccrn/206.55.137.209
2592
du5-ts2.lascruces.ccv/205.166.1.141
2593
cyber98d198.ss.ave.shaw.ca/24.64.98.198
2594
pr6-209.tstonranp.cn/206.55.137.209
2595
client-120-34.be1llatlantic.net/151.198.120.34
2596
cybers98d198.s.wave.shaw. ca/24.64.98.198
2597
surf182.naplesfl.net/24.129.24.182
2598
pnd1dn18.eg1.net/208.159.114.51
2599
pndni18.egl.net/208.159.114.51
2600
236.chicago-34.il.dial-access.att.net/12.67.129.236
2601
cybers45d241.nt.wave.shlaw.c/24.64.45.241
2602
236.chicago-34.il.dia1-access.att.net/12.67.129.236
2603
cybers45d241.nt.wave.shaw.ca/24.64.45.241
2604
236.chicago-34.il.dial-access.att.net/12.67.129.236
2605
236.chicago-34.il.dial-access.att.net/12.67.129.236
2606
hdn94-145.hil.ccpn-userve.ccrn/209.154.56.1457 2
36
.19.2
2607
236.chicago-34.il.dial-access.att.net/12.6
2608
usrtc-tl-27.olypen.ccn/208.229.228.32
2609
hdn94-145.hil.ca±ruserve.ccrn/209.154.56.145
2610
dialup18.altonet.ca/206.66.163.118
8
6 6
2611
. 6.163.11
dialup18.altonet.ccan/20
2612
dialu1±8.altcnet.cx±V206.66.163.118
2613
edu/18.85.21.34
kirby. media.rdit.
2614
208.14.240.106/208.14.240.106
2615
'ITMPLE.MIrT.EI/18.237.0.33
ppp-207-215-86-116.scraO1.pacbell.net/207.215.86.116 2616
pp-207-215-86-116.sczmol1.pacbell.net/207.215.86.116 2617
pgp-207-215-86-116.scrmD±1.pacbell.net/207.215.86.116 2618
2619
7
6
6
2620
.215.8 .11
ppp-207-215-86-116.sczO1.pacbell.net/20
8
2621
.6.13.3
rus.nrutgers.edu/12
2622
spc-isp-van-so -34-17.sprint.ca/209.148.184.18
2623
1Cust90.tt1.elkhart.in.da.u.net/208.254.26.90
2624
209.75.203.40/209.75.203.40
2 9 76
2625
pn1-pp-90.ke-prinary.net/ 0 .1 .130.90
2626
pn1-pp-90.kc-prinnry.net/209.176.130.90
2627
whitelll.uwyo.edui/129.72.235.111
2628
B99.cocc. edtu/206.163.25.99
2629
hockinghills.org/206.222.12.58
2630
punch.ca. olunbia.edu/128.59.19.11
2631
sjoback.medkan.gu.se/130.241.76.95
2632
cc660582-a.vron1.nj.lnhe.ccrn/24.3.148.18
2633
nagenta.afip.org/192.239.86.126
2634
c660582-a.vronl.nj.hOxn.ccnV24.3.148.18
o108.brandywine.net/207.106.54.40
MP22.S.CENELL.EIIJ/128.84.248.153
mp-207-215-86-116.scznO1.pacbell.net/
120
date
time
score
duration
baddies
hits
shots
ip address of player
id#
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
8:23:10 AM
8:43:56AM
8:49:07AM
AM
10:06:03
10:13:49 AM
10:15:34
AM
10:20:54
AM
10:23:45
AM
AM
10:25:02
10:34:19 AM
10:37:42
AM
AM
10:38:03
10:40:48
AM
AM
10:41:47
10:43:25 AM
AM
10:45:37
10:48:34
AM
11:05:01
AM
AM
11:10:59
11:13:22
AM
11:17:17 AM
11:19:47AM
11:27:10
AM
AM
11:29:27
11:30:54AM
12:09:05
1:17:32FM
1:26:48PM
1:35:41PM
1:36:07RM
1:38:53FM
1:41:53FM
1:43:54R4
1:49:37RM
1:50:01RM
1:51:01RM
1:51:54RM
1:53:07RM
1:53:39RM
1:54:43RI
1:55:31RI
1:56:45R
1:57:19
1:57:20RI
1:58:24
1:58:58RI
2:01:08RM
2:04:04RM
2:04:05
2:04:38RM
2:06:10M
2:08:15 M
2:10:42
2:12:31 RI
2:16:10
2:18:32
2:19:51 M
2:27:14
2:29:19 M
2:31:44 M
2:32:56
2:34:20
2:35:32 RM
2:36:57RM
2:37:45
2:40:20 RI
2:50:01 RM
3:21:39 RM
3:23:08
3:24:39 M
3:27:18 M
3:32:54 RI
3:34:40 M
3:36:43 RM
3:38:45
3:40:24
3:43:09 RI
3:44:14
3:45:31 RM
3:47:01 RI
3:52:09 RI
3:53:52 RI
3:56:06 RI
3:59:43 RM
4:01:55
4:14:47
4:17:29
4:21:33 RI
4:21:45 R4
4:22:09 RI
4:23:16RI
4:23:23RI
4:27:48RM
4:29:31RM
4:30:29RM
4:36:06RI
4:39:21
4:48:09RM
5:04:14RM
5:07:11RM
5:09:42RM
5:16:35RI
5:23:24RI
5:24:53RI
3550
6450
8150
6900
250
8400
3050
4350
13900
10200
2200
6100
2700
4000
3650
2900
4750
9150
3550
5200
11400
2400
3650
3650
1850
6150
4250
4100
1600
7700
5400
4600
8550
3300
9150
9250
4650
3000
3500
5350
3800
2750
4100
1900
5850
4000
4150
1400
5000
9550
4250
3300
4150
3000
3650
3100
2450
4850
4800
7250
2700
2900
1300
3700
750
6600
0
1100
250
1750
4050
9450
3800
5900
8800
3350
50
2050
950
9850
11450
2800
12550
11900
5900
2400
3350
3200
2850
4350
8850
7700
5700
7500
3700
7900
4000
5400
4800
3450
6500
3650
3650
8500
155
276
293
237
103
259
134
157
525
499
162
208
168
92
142
114
156
101
68
129
218
110
104
175
71
278
216
130
251
160
137
133
252
215
653
386
119
109
82
238
93
105
205
243
154
118
142
97
161
423
111
105
124
94
204
127
64
427
86
129
53
69
48
61
32
140
115
95
63
60
129
320
180
205
229
122
50
222
60
393
244
283
529
325
332
279
143
22
242
21
283
58
346
358
145
320
177
200
336
94
147
366
219
252
7
21
27
12
0
13
5
9
22
17
6
14
4
6
7
5
11
18
7
11
26
4
7
14
6
15
8
8
2
13
9
10
14
6
27
15
10
5
7
11
6
11
11
6
16
9
11
2
14
31
11
9
9
6
9
8
4
11
10
15
5
6
3
6
3
11
0
3
1
4
9
21
9
16
24
6
0
8
2
23
23
5
28
22
18
4
7
5
6
7
21
16
13
24
7
16
9
11
9
8
16
13
9
23
41
173
190
181
6
182
32
168
362
279
86
119
30
83
71
34
91
314
41
97
353
29
46
119
34
168
63
55
20
139
77
67
196
97
154
391
89
30
43
94
67
111
82
51
87
68
117
19
144
205
114
82
121
77
100
66
25
111
116
146
36
121
88
68
47
119
1
50
34
64
106
228
80
141
160
37
36
84
13
195
278
32
385
374
118
42
51
63
44
82
209
309
97
186
44
149
58
77
59
101
117
118
74
298
100
2010
3593
536
14
480
97
242
1681
1238
200
501
171
191
195
161
301
1067
282
789
1372
57
181
435
126
477
150
181
70
277
344
233
497
845
1177
1015
487
187
325
348
367
259
280
115
734
272
631
73
928
1296
482
444
574
374
915
530
186
645
331
417
167
213
181
162
82
457
1
92
41
123
251
518
257
356
399
296
36
499
87
629
485
193
1056
1002
576
148
126
165
230
306
1186
629
313
1288
181
284
178
306
153
227
356
527
159
666
dialup240.brussels2.skynet.be/195.238.23.240
cheog.ica.kth.se/130.237.44.139
cheog.ics.kth.se/130.237.44.139
ppp102.brandywine.net/207.106.54.34
beelzebub-53.tcg-nex.mteract.ccn/207.229.150.53
2635
2636
2637
2638
2639
2640
2641
2642
2643
2644
2645
2646
2647
2648
2649
2650
2651
2652
2653
2654
2655
2656
2657
2658
2659
2660
2661
2662
2663
2664
2665
2666
2667
2668
2669
2670
2671
2672
2673
2674
2675
2676
2677
2678
2679
2680
2681
2682
2683
2684
2685
2686
2687
2688
2689
2690
2691
2692
2693
2694
2695
2696
2697
2698
2699
2700
2701
2702
2703
2704
2705
2706
2707
2708
2709
2710
2711
2712
2713
2714
2715
2716
2717
2718
2719
2720
2721
2722
2723
2724
2725
2726
2727
2728
2729
2730
2731
2732
2733
2734
2735
2736
2737
2738
IM
M
M
M
M
IM
M
M
M
M
M
M
M
M
IM
IM
M
M
IM
GLOM:Information Agglomerates
gPP102.brandywine.net/207.106.54.34
207.125.29.174/207.125.29.174
207.125.29.174/207.125.29.174
pgp102.brandywine.net/207.106.54.34
ppp102.brandywine.net/207.106.54.34
ws-2.1df.k12.wi.us/208.155.7.98
ppp102.brandywine.net/207.106.54.34
ws-2.ldf.kl2.wi.us/208.155.7.98
Epp102.brandywine.net/207.106.54.34
ws-2.ldf.k12.wi.us/208.155.7.98
ws-2.1df.k12.wi.us/208.155.7.98
ws-2.ldf.k12.wi.us/208.155.7.98
8 33 2 3
. .5
castle.bank.lv/159.14
castle.bank.lv/159.148.33.253
csotle.bank.lv/159.148.33.253
castle.bank.lv/159.148.33.253
206.30.7.191/206.30.7.191
194.133.55.71/194.133.55.71
206.30.7.149/206.30.7.149
206.30.7.149/206.30.7.149
dynamic22.pYn3.pleasanton.bst.mcu/204.156.131.150
207.125.29.180/207.125.29.180
ppp105.brandywine.net/207.106.54.37
208.137.84.94/208.137.84.94
pppl05.brandywine.net/207.106.54.37
ppp105.brandywine.net/207.106.54.37
slip166-72-116-215.tx.us.ihn.net/166.72.116.215
ppp105.brandywine.net/207.106.54.37
ws-207-215-129-153.brawleyanline.can/207.215.129.153
slipl29-37-206-151.in.us.ihn.net/129.37.206.151
ppp105.brandywine.net/207.106.54.37
ws-207-215-129-153.brawleyonline.ca/207.215.129.153
ppp105.brandywine.net/207.106.54.37
ws-207-215-129-153.brawleyonline.an/207.215.129.153
DallaADP42-16.SplitRock.net/209.156.42.16
ws-207-215-129-153.brawleyonline.canv207.215.129.153
IllasTADP42-16.SplitRock.net/209.156.42.16
ascend33.netrover.can/205.209.21.34
st227.d50.tazewell.k12.il.us/207.63.38.227
ws-207-215-129-153.brawleyonline.can/207.215.129.153
Da11asTXDP42-16.SplitRock.net/209.156.42.16
we-207-215-129-153.brawleyonline.canV207.215.129.153
152.34.24.28/152.34.24.28
ws-207-215-129-153.brawleyonline.can/207.215.129.153
ascend33.netrover.can/205.209.21.34
ws-207-215-129-153.brawleyoline.o-n/207.215.129.153
ws-207-215-129-153.brawleyonline.can/207.215.129.153
ws-207-215-129-153.brawleyonline.can/207.215.129.153
ws-207-215-129-153.brawleyonline.cn/207.215.129.153
we-207-215-129-153.brawleyonline.can/207.215.129.153
we-207-215-129-153.brleyonline.can/207.215.129.153
ws-207-215-129-153.brawleyonline.can/207.215.129.153
w-207-215-129-153.brwleyanline.can/207.215.129.153
ws-207-215-129-153.brawleynline.can/207.215.129.153
ws-207-215-129-153.brawleyonline.caV207.215.129.153
ws-207-215-129-153.brawleyonline.om/207.215.129.153
w-207-215-129-153.brwleyonline.crV207.215.129.153
we-207-215-129-153.brawleyanline.can/207.215.129.153
ws-207-215-129-153.brawleycnline.can/207.215.129.153
7
.215.129.153
ws-207-215-129-153.brleyonline.can/20
ws-207-215-129-153.brawleyonline.cxW207.215.129.153
168.28.82.147/168.28.82.147
209.2.245.88/209.2.245.88
209.2.245.88/209.2.245.88
209.2.245.88/209.2.245.88
209.2.245.88/209.2.245.88
209.2.245.88/209.2.245.88
oismepc.uio.n/129.240.209.242
209.2.245.88/209.2.245.88
oisenepcl.uio.no/129.240.209.242
federal-pn3-04-165.nnbell.net/207.252.105.165
168.99.169.63/168.99.169.63
168.28.82.149/168.28.82.149
168.28.82.149/168.28.82.149
tor-pn-3-93.netrover.can/205.209.27.93
besttsl2c90.ntnet.nb.ca/207.179.185.96
pp-207-193-28-7.snantx.swbell.net/207.193.28.7
7
tor-pn--3-93.netroe.can205.209.2 .93
btstts2c90.ntnet.nb.a/207.179.185.96
tor-pn-3-93.netrover.can/205.209.27.93
pn3-ip134.kent.net/207.81.19.134
pn3-ip134.kct.net/207.81.19.134
ge.media.mit.edu/18.85.11.175
pn3-ip134.kent.net/207.81.19.134
ge.neia.mit.edu/18.85.11.175
166-133-92.ipt.aol.cn/152.166.133.92
ge.nedia.mit.edu/18.85.11.175
pn3-ip134.kmt.net/207.81.19.134
166-133-92.ipt.aol.canV52.166.133.92
7 8
9 34
. 1.1 .1
p3-ip134.ket.net/20
pn±3-ip134.koet.net/207.81.19.134
pn3-ip134.kmt.net/207.81.19.134
nexll-21.stc.net/208.210.134.149
sdn-ts-002flhhilP06.dialsprint.net/206.133.79.41
megalon-34.opmface.ca/209.89.24.44
193.212.10.61/193.212.10.61
158.103.102.13/158.103.102.13
k56-ip-240.therarp.net/205.212.95.240
207.163.53.23/207.163.53.23
121
130
82
480
206
410
421
276
356
100
136
1116
685
218
41
331
238
300
213
269
704
1836
422
1948
1189
300
651
371
311
146
0
121
244
58
124
470
156
1188
321
235
522
2045
236
133
49
229
366
376
369
399
357
1307
1042
1417
347
1338
15
127
1270
86
801
1
239
222
3414
68
83
288
96
201
318
441
98
943
134
171
175
83
0
2212
902
726
27
290
398
87
147
ip address of player
79 84
usr50-dialup2O.mix2.Boston.nci.net/166.55.
79 . 4
6
usr50-dialup20.mix2.Boston.noi.net/166 .55. 7 .8 4
usr50-dialup20.mix2.Boston.nci.net/1 6.55. 9.8
slip166-72-161-154.tx.us.ihm.net/166.72.161.154
7
9.84
usr50-dialup2O.mix2.Boston.nci.net/166.55.
4
7
2.161.15
slipl66-72-161-154.tx.us.in.net/166.
slip166-72-161-154.tx.us.ihn.net/166.72.161.154
ws-207-215-129-118.brawleyonline.can/207.215.129.118
lCustl09.tnt8.lax3.da.uu.net/153.37.75.109
206.144.90.176/206.144.90.176
ws-207-215-129-118.brawleyonline.caV207.215.129.118
8
ws-207-215-129-118.brawleymline.con/207.215.129.11
8
ws-207-215-129-118.brawleyonline.coan/207.215.129.11
ppp046.au.centuryinter.net/209.142.147.60
pp105.brandywine.net/207.106.54.37
ptrmiO-sh8-port206.snet.net/204.60.42.206
194.125.61.188/194.125.61.188
1out141.tnt21.at12.da.uu.net/153.36.124.141
p16-39.tstonranp.can/206.55.137.39
li2stl4l.tnt21.atl2.da.uu.net/153.36.124.141
ppp-207-215-85-38.scnOl.pacbell.net/207.215.85.38
7 38
rc-pnl-05.enetis.net/208.141.21
3 2 238 .67
7
.1 . .
media3.creativity.se/19
ppp-207-215-85-38.scnD1.pacbell.net/207.215.85.38
ppp-207-215-85-38.scnOl.pacbell.net/207.215.85.38
7
8 38
2
.215.5.
ppp- 07-215-85-38.sczn01f.pacbell.net/20
lCust206.tnt2.krkl.da.uu.net/153.37.252.206
198.236.73.165/198.236.73.165
141.133.118.182/141.133.118.182
eagan-rip08.cray.orn/204.73.50.8
8
7
3.50.
eagan-rip88.cray.caun204.
engan-rip08.cray.canV204.73.50.8
eagan-ripO8.cray.can/204.73.50.8
73
.50.8
eagan-rip08.cray.can/204.
w-207-215-129-138.brawleyonline.can/207.215.129.138
ws-207-215-129-126.brawl e yonline.an207.215.129.126
ws-207-215-129-126.brawleyonline.can/207.215.129.126
29
7
ws-207-215-129-126.brawleyonline.can/20 .215.1 .126
2 7
17.san-francisco-15.ca.dial-access.att.net/12.64.16 6 .1
ws-207-215-129-126.brawleyanline.oan/207.215.129.12
spc-isp-van- uas-36-13.sprint.ca/209.148.184.214
np99mnden173.tusco.net/207.206.99.173
np99noden73.tusco.net/207.206.99.173
np99oden173.tusco.net/207.206.99.173
np99nrden73.tuso.net/207.206.99.173
np99noden173.tuso.net/207.206.99.173 7
0.121
121.lexington-01.ky.dial-access.att.net/12.66.
7
73
.206.99.1
np99ndsen173.tuso.net/20
7
7
np99dedn13.tuco.net/207.206.99.1 3
ts48ipl95.cadvision.canV207.228.72.195
ts48ip195.cadvision.c-rn207.228.72.195
ts48ip195.cadvision.cau207.228.72.195
8 6
. 1
techl2.javnet.can/209.94.12
0
port06l.vta.fishnet.net/205.216.133.21
techl1.javanet.can/209.94.128.60
c1005378-a.plstnl. sfba. xre. ca/24.1.96.9
c1005378-a.plstnl.sfba.hane.can24.1.96.9
port06l.vta.fishnet.net/205.216.133.210
techll.javanet.ar/209.94.128.60
8
202-38-218.ipt.ol.o-nr/152.202.38.21
ttyl46.softdisk.caV208.143.104.82
1Cust234.tnt8.lax3.da.uu.net/153.37.75.234
1Cust234.tnt8.lax3.da.uu.net/153.37.75.234
202-38-218.ipt.aol.cn/l52.202.38.218
6
3 93
.10 .
p29-Q-hn5.dialup.xtxa.o.nz/203.9
ts7-27.frd.cyberhighwy.net/209.161.34.191
cybersl5dl39.ed.vave.shaw.ca/24.64.15.139
ts7-27.frd.cyberhighway.net/209.161.34.191
29
p -m2-hn5.dialup.xtra.co.nz/203.96.103.93
}ost-209-138-13-9.sg.bellsouth.net/209.138.13.9
host-209-138-13-9.sh2.bellsouth.net/209.138.13.9
hst-209-138-13-9.shg.bellsouth.net/209.138.13.9
host-209-138-13-9.sbg.bellsouth.net/209.138.13.9
3
3 37
1cust15.nx18.santa-clara.ca.m.uu.net/15 . .15 .15
1Cistl5.rnx18.santa-clara.ca.s.uu.net/153.37.153.15
7
dal-tsal6-35.cyberranp.net/207.158.8 .99
SY-A04-pool-140.tnns.net.au/139.134.90.140
slip-32-100-115-98.ny.us.ihn.net/32.100.115.98
166-148-97.ipt.ol.ccn/152.166.148.97
1Custl44.tntl.det2.da.uu.net/153.34.37.144
1Custl44.tntl.det2.da.uu.net/153.34.37.144
8 9
173-118-29.ipt.aol.ccmr/152.173.11 .2
173-118-29.ipt.aol.cc/l52.173.118.29
173-118-29.ipt.aol.cc/152.173.118.29
nbtel3-243.nbtel.net/207.179.142.243
tntl-42.focal-chi.ngsinet.net/209.81.175.42
id#
2739
2740
2741
2742
2743
2744
2745
2746
2747
2748
2749
2750
2751
2752
2753
2754
2755
2756
2757
2758
2759
2760
2761
2762
2763
2764
2765
2766
2767
2768
2769
2770
2771
2772
2773
2774
2775
2776
2777
2778
2779
2780
2781
2782
2783
2784
2785
2786
2787
2788
2789
2790
2791
2792
2793
2794
2795
2796
2797
2798
2799
2800
2801
2802
2803
2804
2805
2806
2807
2808
2809
2810
2811
2812
2813
2814
2815
2816
2817
2818
2819
2820
2821
2822
2823
2824
127
160
255
487
tt1-42.foca-chi.negoinet.net/209.81.175.42
und-s4p3.und.Noak.edu/134.129.135.152
2825
2826
225
52
21
181
102
49
263
869
89
30
133
167
211
126
81
55
446
256
262
1262
174
194
928
3362
582
73
328
880
1323
311
215
872
tntl-42.focal-chi.megsinet.net/209.81.175.42
8
ftw-tsa5-48.cyberranp.net/207.158.119.4
tek.engin.und.uidch.edu/141.215.9.49
8
47 88 4
.1 . 0.10
apc11.ph.lham.ac.uk/1
2827
2828
2829
2830
2831
2832
2833
2834
2835
2836
2837
2838
2839
2840
2841
2842
score
duration
baddias
400
150
4500
4650
3450
9550
5000
4000
3250
3150
8100
4100
3000
0
6150
4000
5900
2750
4000
4150
19400
3500
24650
9850
3900
5850
6150
6150
2950
0
1100
1250
550
1250
3250
1800
8700
3000
5350
3500
10950
3500
1300
800
3850
6050
5450
9350
8550
2400
10050
7550
10500
6700
10800
600
4350
9650
500
3300
50
3350
3100
23100
1650
0
1450
400
3050
4750
3050
1000
4550
2550
4250
4200
1350
0
13550
10100
2500
0
1250
0
1000
3050
123
116
177
115
188
205
157
99
114
136
232
127
59
361
274
248
173
132
241
302
640
271
357
477
124
229
352
178
194
1
88
91
28
60
111
55
237
78
230
91
599
145
49
49
133
131
386
292
232
72
205
193
243
408
504
48
143
1329
877
443
34
249
137
1011
161
47
184
64
325
118
125
40
184
188
115
76
124
2
476
375
314
71
123
150
102
70
0
0
17
10
12
21
8
9
6
7
17
8
5
0
12
9
15
11
9
9
43
9
46
21
6
12
12
13
6
0
4
5
2
4
6
3
19
5
11
8
36
13
5
3
9
18
11
22
20
9
28
15
20
21
25
1
8
26
2
6
0
7
12
86
5
0
5
1
5
9
6
4
11
4
10
8
2
0
34
25
5
0
5
0
1
8
hits
60
3
148
87
131
204
190
101
36
42
199
91
30
4
105
51
99
81
139
73
581
103
551
277
89
142
97
139
45
0
62
45
38
56
86
18
233
40
85
98
243
108
45
16
70
162
93
185
157
78
244
195
341
131
259
6
51
172
47
45
1
47
110
474
33
34
58
90
39
67
41
76
109
29
56
48
22
0
506
213
49
11
60
9
22
43
9:40:35AM
9:41:53 AM
6850
7000
130
637
12
16
9:43:53AM
10:04:59
A14
AM
10:14:25
AM
10:26:45
AM
10:27:29
10:27:52 024
10:28:38
A14
AM
10:37:52
AM
10:57:09
11:08:49824
11:42:52
AM
11:49:05
A14
11:50:23
AM
11:52:53
AM
11:55:01
11:56:56 AM
9200
3650
1950
7600
1700
3950
10500
33600
1600
3000
3250
6850
7800
7750
4450
3900
181
181
138
249
32
73
1016
608
214
95
152
357
528
190
114
373
18
8
3
17
6
8
26
64
5
5
13
21
29
15
8
8
date
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980501
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
time
5:25:20 PM
5:27:33 2M
5:30:48FM
5:33:350M
5:34:122M
5:37:240M
5:40:192M
6:17:052M
6:18:48 2M
6:20:2524
6:21:1324
6:23:35EM
6:24:492M
6:35:23
6:35:3924
6:38:04EM
6:51:10R4
6:54:41
6:59:47
6:59:59
7:14:12
7:16:132M
7:22:2424
7:22:2524
7:24:462M
7:29:012M
7:51:152M
8:04:452M
8:14:51
8:51:13
8:52:56
8:54:54
8:55:38
8:56:56
8:58:15
9:05:22 24
9:09:35 24
9:11:08 2M
9:11:34 2M
9:13:34 2M
9:43:47 24
9:47:27 2M
9:48:31 2M
9:49:34
9:52:02
9:54:31
10:00:362M
10:02:17EM
10:06:51
10:44:04
10:47:49
10:51:172M
10:51:37
11:02:112M
11:13:332M
11:22:412M
11:25:212M
11:26:532M
11:29:452M
11:35:572M
11:41:132M
11:48:372M
11:51:122M
11:53:192M
11:59:2224
12:05:45AM
12:05:52AM
12:07:04AM
12:08:56AM
12:09:45AM
12:12:05 AM
12:13:01 A14
12:16:20 AM
1:33:01 AM
1:35:09 AM
3:57:50 AM
6:37:10 AM
7:42:44AM
7:48:12 AM
8:29:57 AM
8:35:27 A14
8:55:58 AM
8:58:19 AM
9:01:06 AM
9:13:50 A14
9:38:08 AM
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
GLOM:Information Agglomerates
shots
mpc11.ph.ham.ac.uk/147.188.40.108
btstts11c06.nbnet.nb.ca/198.164.242.108
und-as4p3.und.bb18k.edu/134.129.135.152
apcll.ph.bham.ac.uk/147.188.40.108
ts003d04.ind-in.octric.net/206.173.97.64
6 6
4 2
.12.11 . 5
psx6.bayareaca.net/20
nanitou3-9.usask.ca/192.139.76.73
76 7 3
.
mnnitou3-9.usask.ca/192.139.
2 7 4 78 4
. . . 1
41.denver-16-17rs.oo.dial-access.att.net/1
nnnitou3-9.usask.ca/192.139.76.73
onnitou3-9.usask.ca/192.139.76.73 2 7 4 78 4
. . . 1
41.denver-16-17rs.co.dial-access.att.net/1
122
date
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
time
12:02:33 FM
12:24:13
12:25:05
12:26:31
12:26:422M
12:28:32
12:30:022M
12:32:022M
12:33:432M
12:34:092M
12:35:052M
12:37:572M
12:38:33R4
12:41:342M
12:41:56
12:46:0524
12:49:0724
12:50:394
12:51:582M
1:26:57
1:30:30
1:35:19
1:43:552M
2:04:29 24
2:06:57 2M
2:08:56 2M
2:11:1124
2:40:362M
2:41:402M
2:42:23R4
2:50:512M
2:57:382M
3:04:202M
3:09:132M
3:13:53
3:18:50R4
3:22:59
3:23:0924
3:27:1724
3:30:582M
3:31:052M
3:36:312M
3:40:3424
3:43:172M
3:59:49
4:08:3224
4:12:222M
4:19:59
4:36:09
4:43:40
4:51:58
4:57:09
5:06:2824
5:13:31
5:43:55
5:45:122M
5:46:312M
5:48:2224
6:01:392M
6:04:432M
6:14:232M
6:31:52
6:32:54 24
6:37:15
6:42:52
6:45:07
6:48:38
6:52:06
6:52:4524
6:52:49
6:55:1024
6:57:11
6:58:4924
6:59:162M
7:04:2524
7:13:42 2M
7:16:4924
7:21:302M
7:36:1724
7:39:4724
7:41:29 2M
7:48:17
7:52:44
7:55:0224
7:55:27 EM
8:00:0724
8:03:51
8:09:03
8:11:43 2M
8:19:49 24
8:29:58 2M
8:31:52 2M
8:32:06 24
8:33:4724
8:38:23 2M
8:44:31 2M
8:50:12
8:50:17
8:56:462M
8:59:59 2M
9:01:35 2M
9:09:05 2M
9:11:37 2M
9:15:18 2M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
score
0
0
0
250
2500
4950
4050
1900
2400
550
1900
1100
7650
3550
4400
4750
3600
800
4600
2450
0
9000
3900
800
3550
4050
2250
600
0
5200
8200
3650
0
3100
4550
2300
3650
4950
3400
5750
9000
6850
4600
16100
11400
4700
5800
0
3000
0
6250
13750
4850
5550
3400
1250
3250
1500
0
8200
3950
3150
1900
6300
4500
4250
9350
3050
0
0
0
350
1250
7050
5950
4450
4800
1950
300
8300
2350
10600
450
2250
0
3800
5100
0
0
600
2450
0
0
1250
3600
6450
5450
9400
2900
4550
2750
6150
2100
3250
duration
46
100
37
68
161
155
195
103
106
82
65
267
376
198
186
234
149
349
154
216
37
468
487
126
153
342
128
52
48
289
293
258
118
160
265
162
130
242
239
207
451
317
514
704
431
177
215
54
311
8
214
296
106
242
151
37
64
93
239
256
197
87
46
154
490
167
201
150
7
3
119
146
83
228
320
221
173
149
87
408
296
494
100
104
64
239
204
133
141
63
191
88
4
81
259
307
664
329
133
175
77
286
143
204
GLOM:Information Agglomerates
baddies
0
0
0
1
4
10
8
3
3
1
3
4
16
6
9
12
10
1
10
7
0
22
7
3
7
15
6
0
0
12
20
8
0
12
9
4
7
12
8
16
28
18
10
42
32
9
12
0
7
0
14
39
11
11
8
2
6
3
0
18
10
7
5
15
11
9
20
8
0
0
0
1
2
28
13
12
10
5
0
17
4
27
0
9
0
7
12
0
0
1
5
0
0
5
7
18
12
20
6
10
11
12
8
13
hits
0
0
0
5
34
75
53
20
32
24
42
60
214
47
70
116
122
15
56
80
6
170
161
33
50
134
60
15
4
70
173
64
0
127
97
31
44
76
44
108
218
105
70
493
248
106
147
1
42
0
202
316
65
182
45
14
35
106
0
180
108
74
108
108
77
88
194
43
0
0
5
13
42
184
98
104
74
87
6
174
42
258
9
62
0
61
86
0
0
6
39
23
0
59
42
140
77
183
64
64
103
101
63
82
of player
shots
ip address
0
0
0
40
133
283
234
71
148
107
99
115
1022
136
777
1439
520
365
925
156
9
472
328
54
155
531
165
20
62
373
457
156
0
408
621
123
120
240
227
615
751
479
293
2613
809
274
316
48
212
0
1054
1944
135
410
149
32
87
199
4
427
367
265
298
239
376
247
462
436
0
0
37
80
80
619
371
533
490
165
21
392
247
675
38
176
0
195
300
0
0
13
381
87
1
173
385
709
1516
639
130
397
254
193
136
472
djaafar.ne.mediaone.net/24.128.59.12
ntp20.cac.psu.edu/128.118.140.20
nhppp20.cac.psu.edu/128.118.140.20
2
8
8
.11.140.0
nbppp20.cac.psu.edu/12
xlate2-70.office.aol.ccrV204.148.99.70
dsr.db.dk/130.226.186.56
np20.cac.psu.edu/128.118.140.20
2
0
ntppp2.cac.psu.edlu/128.118.140.
207-172-52-203.s203.tntl.brd.erols.cco207.172.52.203
199.250.252.14/199.250.252.14
207-172-52-203.s203.tntl.brd.erols.cam/207.172.52.203
98
adnline243198.adnc.ccr/206.251.243.1
nkpp20.cac.psu.edu/128.118.140.20
adnline243198.adnc.ccs/206.251.243.198
ntppp20.cac.psu.edu/128.118.140.20
npip2O.cac.psu.edu/128.118.140.20
noipp20.cac.pu.edu/128.118.140.20
246.kansas-city-06.n.dial-access.att.net/12.66.101.246
2
ntppp2O.coac.psu.edu/128.118.140. 0
crinoth-3.ndn.rnd.execpc.ccm/169.207.45.19
205.130.199.130/205.130.199.130
crinoth-3.ndn.rnd.execpc.cxxn/169.207.45.19
crinoth-3.ndn.rnd.exeqcp.ccm/169.207.45.19
outh.net/207.53.6.169
host-207-53-6-169.atl.bell
98.birminghl01.al.dial-access.att.net/12.67.64.98
id#
2843
2844
2845
2846
2847
2848
2849
2850
2851
2852
2853
2854
2855
2856
2857
2858
2859
2860
2861
2862
2863
2864
2865
2866
2867
2868
0 2 2 2 3
2869
s15.netfox.net/2 8. 2 . 1 .15
2870
ctvO70.ctv.es/195.57.143.70
7
7
2871
.143.0
ctv807O.ctv.es/195.5
2872
n.net/207.253.121.131
pp131.121.nrtl.vidotr
6 20 8 2 7
2873
5. . 1
217.new-orleans-01.la.dial-access.att.net/12.
0
2874
9
k56aip09.mdis.net/209.44.12.1
7
2875
2.66.152
207-172-66-152.s25.as7.nrf.erols.can/207.1
2 69
67
2876
.1
.19
169.cleveland-01.oh.dial-acces.att.net/12.
169.cleveland-01.oh.dial-access.att.net/12.67.192.169 2877
2878
tor-p±-3-90.netrover.ccm±/205.209.27.90
2879
b-1.dialup.northernnet.ccm/205.139.165.71
2880
tor-pg-3-90.netrover.can/205.209.27.90 6 7
2881
hb-1.dialup.northernnet.ct/205.139.1 5. 1
2882
hb-1.dialup.northernnet.ccn/205.139.165.71
2883
tor-pm-3-90.netrover.oan±/205.209.27.90
7
2884
1
hb-1.dialup.northennet.cun/o205.139.165.
2885
crinoth-9.ndn.rnd.execpc.canVl69.207.45.25
2886
gsv105.gator.net/207.243.60.105
7
2887
noden157.nwidt.canV199.120.82.15
2888
1ICst48.nex12.cleveland.oh.neuu.net/153.35.13O.48
48
3 3
2889
lCust48.nux±12.cleveland.oh.n.u.net/15 . 5.130.
2890
198.30.208.63/198.30.208.63
3
2891
2.166
166.los-angele-O01.ca.dial-access.att.net/12.64.
2892
HAYmrN-7.MIT.E[U/18.51.1.37
us-207-215-129-147.brawleyonline.ocm/207.215.129.147 2893
us-207-215-129-147.brawleyonline.ccnV207.215.129.147 2894
2895
p018.tsvr4.rnx.canV199.190.118.19
2896
hb-1.dialup.northennet.canV205.139.165.71
2897
tsl-04.omld.cyberhigh±y.net/209.161.17.71
2898
tol-04.nld.cyberhighmy.net/209.161.17.71
7 7
2899
.1
tsl-04.mld.cyberhighay.net/209.161.1
2900
tol-04.mld.cyberhighmy.net/209.161.17.71
2901
port89-202.uss.net/209.100.89.202
6
2 67
2902
.10 . .196
pn3mbrl-67-196.intrepid.net/20
2903
ppp117.brandywine.net/207.106.54.49
7
9
43 3
2904
tin35.spso.net/20 .14 .2 . 3 5
2905
tin35.spwo.net/207.149.243. 5
2906
daga2pp2l.alltel.net/166.102.118.22
2907
2908
56K-004.MaxIN4.pck.net/209.144.230.4
2909
hn85-134.hil.ccrnguserve.can/'206.175.96.134
2910
nbl5gpp6O.cac.psu.edu/128.118.72.60
77
3
2911
hlfx09-34.ns.synpatio.ca/142.1
3
77 .10.10
2912
ca/142.1
h1fx09-34.ns.synpati.c
3
77 .10.10
2913
.10.10 7 7 26
h1fx09-34.ns.synpatic.ca/142.1
2914
26.bridgeton-10.no.dial-access.att.net/12.6 .1 .
2915
26.bridgeton-10.no.dial-access.att.net/12.67.17.26
3
77
2916
.10.10 7 7
h1fx09-34.ns.syrpatico.ca/142.1
2917
.26
.1
26.bridgeton-10.no.dial-access.att.net/12.6
8 96
2918
dip226.inav.net/205.160.20 . 6
2919
dip226.inav.net/205.160.208.9
2920
lcust229.tnt4.krkl.da.uu.net/208.254.1.229
2921
dialup5-3-07.doitnow.coen/207.211.43.135
2922
ontrldhcp27.spl.org/209.63.97.27
2923
dialup5-3-07.doitnow.ccr207.211.43.135
7 7
2924
.2
ontrldhcp27.spl.org/209.63.9
114.kansas-city-05.o.dial-access.att.net/12.66.100.1142925
2926
afoon-dyn66.afcon.net/209.26.60.66
2927
204.185.202.44/204.185.202.44
2928
afcon-dyn66.afcon.net/209.26.60.66
2929
afcon-dyn66.afcon.net/209.26.60.66
2930
1Cust25.tnt2.o.d.uu...net/208.250.78.205
2931
1Cust2O5.tnt2.orll.da.uu.net/208.250.78.205
2932
storO3p33.storm.ca/207.245.246.161
2933
207.33.152.171/207.33.152.171
2934
2935
s42.netfox.net/208.222.213.42
2936
3 4
2937
42.netfox.net/208.222.21 . 2
7
2938
ttyD22.redding.snowecrest.net/209.148.36.6
2939
7
2940
ttyD22.recdincg.sicnrrest.net/209.148.36.6
2941
prp286.1r.centuryinter.net/209.142.153.65
2942
2
2943
2944
ttyD16.recding.snowcrest.net/209.148.36.23
67
7
2945
80.ojus-01.fl.dial-acces.att.net/12. 7 0. 67 .80
2946
80.ojus-01.fl.dial-access.att.net/12. 0. .80
sl5.netfox.net/208.222.213.15
IC-3.IC.Omton.MN.US/209.114.2.100
s42.netfox.net/208.222.213.42
s42.netfox.net/208.222.213.42
e42.netfox.net/208.222.213.42
pp286.lr.coituryinter.net/209.142.153.65
mP286.1r.cturyinter.net/209.142.153.65
123
date
time
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980502
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
9:19:49 PM
9:21:28 R4
9:28:57
9:29:14EM
9:30:232M
10:05:47
43 3 2 2M
10: : 7 2M
10:45:5 2M
11:07:230M
11:19:562M
11:23:122M
11:27:552M
11:37:572M
11:39:552M
2M
11:40:55
48
11: 5 1 :59
17
11: :
12:23:25
12:26:58
12:32:53AM
12:58:22A4
1:04:11AM
1:06:44AM
2:08:23AM
2:08:32AM
2:14:06A14
2:14:22AM
2:17:20AM
2:21:01AM
2:22:512M
2:23:06AM
3:05:502M
3:08:11AM
3:54:17AM
3:57:382M
3:59:54AM
4:03:40AM
4:08:04A4
5:02:11AM
5:03:38AM
6:41:47A4
6:46:13AM
7:12:08A4
7:13:04
5 58 AM
7
:1 : AM
7:39:01AM
7:42:28AM
7:48:21A4
7:49:31A4
7:52:44AM
7:53:10A4
7:54:15AM
7:56:58A4
7:58:33A4
8:00:03A24
8:02:04A4
8:07:31AM
8:30:32AM
8:30:32 AM
8:31:30 AM
8:35:33 AM
8:39:53 AM
8:45:04 AM
8:48:13 AM
8:52:32AM
9:01:02AM
9:08:45AM
9:10:21AM
9:13:18AM
9:13:49A4
9:25:55A24
9:31:45A4
9:32:19A4
9:35:20AM
9:35:50AM
9:40:00AM
10:13:54
AM
10:14:13
AM
AM
10:17:26
AM
10:22:39
10:22:53
A4
AM
10:26:41
10:26:49M
AM
10:28:05
A4
10:28:20
A4
10:30:44
AM
10:57:43
AM
11:00:55
11:13:54A24
11:15:41A24
11:15:572M
11:18:03AM
11:19:03AM
AM
11:24:15
11:27:20AM
11:28:22A4
11:33:27 AM
11:34:23 AM
11:35:40 AM
11:39:29AM
11:39:57AM
11:49:49A4
11:52:38A4
11:54:54A4
M
M
M
M
M
score
6400
4250
20600
12250
5050
350
10100
4500
1900
4500
4600
5100
0
0
0
3100
4100
0
250
450
3400
8400
5300
3000
0
6700
0
3750
5600
3500
0
3700
4150
2900
4100
3150
4400
6300
1750
2450
4350
7250
3350
1300
7800
9400
0
0
8100
6000
250
11150
3900
3500
4950
4800
6750
3500
7600
1050
3200
7000
3750
4100
3600
3750
8900
6500
2400
8400
0
2700
9000
5600
7350
0
1350
5550
0
650
3400
0
950
3200
0
1900
8450
9000
3700
7400
100
3800
2400
3650
5000
0
0
2450
1250
5300
3450
3300
350
3000
duration
256
186
532
255
140
86
397
435
89
244
180
235
69
76
44
105
107
3
194
156
165
330
135
210
4
319
4
162
202
93
3
133
127
142
187
119
209
248
110
71
212
253
91
37
152
262
424
1
278
170
101
337
238
301
170
185
288
102
338
214
236
237
109
258
93
280
445
486
173
737
24
147
198
310
230
157
314
230
2
95
206
28
71
137
4
111
158
175
169
322
59
108
101
193
168
37
87
134
117
319
182
143
113
241
GLOM:Information Agglomerates
id#
baddies
hits
shots
ip address of player
20
8
82
24
11
0
30
9
3
9
11
13
0
0
0
12
8
0
0
1
8
27
10
6
0
16
0
8
12
12
0
6
8
11
9
6
10
12
3
5
9
18
7
5
22
22
0
0
26
15
0
28
8
7
18
15
20
7
24
4
7
14
6
10
8
8
19
22
4
32
0
8
19
14
14
0
5
22
0
1
7
0
3
7
0
3
18
16
7
20
0
8
4
7
13
0
0
4
2
11
8
6
1
6
126
55
467
269
87
17
234
58
26
60
82
79
0
0
0
100
46
0
5
27
95
183
78
41
1
115
0
49
82
121
0
56
67
93
52
39
75
122
36
36
54
107
76
84
165
206
7
0
170
147
5
223
77
47
161
107
177
55
196
56
47
137
40
87
48
54
163
186
26
166
0
73
216
105
148
0
61
130
0
7
60
0
41
46
2
21
162
193
71
133
6
48
29
61
93
59
7
42
14
127
50
39
28
62
512
104
2328
550
342
67
1511
331
103
300
184
365
1
0
0
306
248
0
20
56
233
657
240
141
1
411
4
176
358
309
0
127
251
504
436
222
512
497
177
104
125
290
205
133
698
643
18
0
421
290
11
670
319
146
325
227
331
166
611
198
630
315
131
151
152
156
488
1061
61
684
0
309
368
305
502
0
506
297
0
12
355
0
72
159
5
110
319
409
266
976
26
145
54
228
255
64
21
170
67
340
261
134
48
177
.80
80.oju-O01.fl.dial-access.att.net/12.70.6
gard.aces.net/205.243.37.119
80.ojus-01.fl.dial-access.att.net/12.70.67.80
hdn95-107.hil.cr-puserve.canV209.154.57.107
mn-104.au2.m.uunet.de/149.229.231.104
203-96-99-203.ipnets.xtra.mo.nz/203.96.99.203
7
spc-isp-van-uas-36-7.sprint.ca/209.148.185.
3
3 63
5.1 5.
user-381d15b.dialup.mcindspring.can/209.86.132.171
7
33
2.13 3
ppp-206-171-172-133.sktnl1.pacbell.net/206.171.1
72
7
pp-206-171-172-133.sktnl.pacbell.net/206.1
71.1
7 .1
33
1.1
opp-206-171-172-133.sktnOl.pacbell.net/206.1
22 2.1
7
7 2
.137 .1 . 0
sd11.california.Internet-Coffee.oxn20
.12.220
sdll.california.Internet-Coffee.cm/207.137.12.220
206.97.184.211/206.97.184.211
206.97.184.211/206.97.184.211
238.portland-03.or.dial-access.att.net/12.65.66.238
6
6 238
5.6 .
238.portland-03.or.dial-access.att.net/12.
4
7
.33.5 7
pgrad5.eee.utas.ecc.au/131.21
3
3.15
1Cstl35.tnt6.seal.da.uu.net/208.253.
3 73
. .135
1Cout35.tnt6.seal.da.uu.net/208.25
10Cstl35.tnt6.seal.da.uu.net/208.253.73.135
7
7
.11
h117.s57.ts.hinet.net/168.95.5
h117.s57.to.hinet.net/168.95.57.117
h117.s57.ts.hinet.net/168.95.57.117
h117.s57.to.hinet.net/168.95.57.117
h117.s57.to.hinet.net/168.95.57.117
hll7.s57.to.hinet.net/168.95.57.117
h117.s57.ts.hinet.net/168.95.57.117
7
h117.s57.ts.hinet.net/168.95.57.11
SY-A21-pool-185.tnn.net.au/139.134.96.185
8
5
SY-A21-pool-185.tnns.net.au/139.134.96.1
h99.s21.ts3O.hinet.net/163.30.21.99
h99.s21.ts3O.hinet.net/163.30.21.99
h99.s21.ts3O.hinet.net/163.30.21.99
h99.s21.ts3O.hinet.net/163.30.21.99
h99.s21.ts30.hinet.net/163.30.21.99
7 7
dialup-70.Napa.CA.InterX.Net/209.0.3
7 .70
.0
dialup-70.Napa.CA.InterX.Net/209.0.3
7
zzkyau.dialin.uq.net.au/203.101.23
3
7 .183
zzkyau.dialin.uq.net.au/203.101.23
24 .18
5
mnjy2.nogd.cam.ac.uk/131.111.221.
mnjy2.nagd.cam.ac.uk/131.111.221.245
rnjy2.nmgd.cam.ac.uk/131.111.221.245
6 87
2.
196-31-162-87.iafria.cun/196.31.1
heres-apl-digital-ip193-58.athmet.net/209.103.193.58
8 37 7 8 62
.1
.
.1
wisc3-aOl.sc.tds.net/20
0
gp2-68.eisa.net.au/203.63.233.14
ppp2-68.eisa.net.au/203.63.233.140
166-248-61.ipt.aol.ca/152.166.248.61
7
.192
dhcp-893508532.qualaom.cunVl29.46.23
pg,2-68.eisa.net.au/203.63.233.140
166-248-61.ipt.aol.cunV152.166.248.61
opp2-68.eisa.net.au/203.63.233.140
8 6
166-248-61.ipt.ol.can/152.166.24 . 1
166-248-61.ipt.aol.crsn/152.166.248.61
npts-03-22.imnet.net/206.112.140.176
client-151-197-114-14.bellatlatic.net/151.197.114.14
7
2947
2948
2949
2950
2951
2952
2953
2954
2955
2956
2957
2958
2959
2960
2961
2962
2963
2964
2965
2966
2967
2968
2969
2970
2971
2972
2973
2974
2975
2976
2977
2978
2979
2980
2981
2982
2983
2984
2985
2986
2987
2988
2989
2990
2991
2992
2993
2994
2995
2996
2997
2998
2999
3000
3001
3002
3003
3004
3005
3006
3
3007
0
3008
port-57-35.access.one.net/209.50.121.35
3009
76.newark-08.nj.dial-access.att.net/12.68.39.76
7
3010
opP3.voltage.net/208.15.104. 5 7 7
3011
ppp75.coladlp3.scsn.net/209.12.5 . 5
3012
dd24-045.dub.caopuserve.ocn/199.174.181.45
3013
dd24-045.dub.ccapuserve.cun/199.174.181.45
3014
dial-38-1--BI--01.ranp.together.net/208.13.202.38
3015
lCustl43.tntl.dothan.al.da.uu.net/208.254.21.143
8 9
3016
.1 5
hut3.southwind.net/206.53.9
3017
206.217.166.248/206.217.166.248
3018
184.new-york-28.ny.dial-access.att.net/12.68.135.184
63
3019
gate53.planet.fi/195.156.155.
3020
opp22.northnet.net/156.46.235.107
84
3021
184.new-york-28.ny.dial-access.att.net/12.68.135.1
3022
171-1-112.ipt.aol.ano/152.171.1.112
3023
173-226-229.ipt.aol.can/152.173.226.229
3024
okcasc3-121.flash.net/209.30.84.121
7
3025
4
tsOl4dl8.cup-ca.concentric.net/209.31.12.1
3
3026
8.45
ocal-pnl-28.mfi.net/205.161.2
4
6
3027
2.15
154.ft-worth-01.tx.dial-access.att.net/12.65.1
3028
sap2.cray.can/137.38.96.91
3029
202-165-60.ipt.aol.ccVl52.202.165.60
3030
204.244.96.97/204.244.96.97
3031
204.244.96.97/204.244.96.97
3032
205.211.60.28/205.211.60.287
3033
pp326.rtp.intx.net/209.42.198.
2
42 98 71
3034
09. .1 . 1
opp326.rtp.intrex.net/
3035
npts-03-22.inenet.net/206.112.140.176
8
3036
bir.fellows.denios.ec/140.141.3.8
3037
208.20.8.54/208.20.8.54
3038
208.20.8.54/208.20.8.54
3039
mnxlppp-4.visn.net/209.115.29.53
3040
1Cust222.tnt3.seal.da.uu.net/208.253.65.222
3 6 22 2
3041
.65.
1Cust222.tnt3.sea1.da.uu.net/208.25
7
3042
3.11
lax-cal1-01.ix.netcon.cnV204.30.
3043
unio-csl-c-35.dial.bright.net/209.143.16.165
3044
user-381clig.dialup.idpring.o-n/209.86.6.80
3045
unio-ca1-cs--35.dial.bright.net/209.143.16.165
3046
202.137.1.142/202.137.1.142
3047
147.253.192.248/147.253.192.248
3048
205.211.60.113/205.211.60.113
92
2 2
3049
4. 40.1
dyn240ppp192.pacific.net.sg/210.
3050
208.11.231.85/208.11.231.85
s43.nextdim.can/205.2
sd11.california.Internet-Coffee.Ccm/207.13
sAl-al.dreamscape.canu/206.114.185.130
sAl-al.dreamscape.can/206.114.185.1
124
date
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
time
11:56:34 AM
11:57:30AM
12:13:45PM
12:18:58PM
12:20:15PM
12:21:329M
12:26:04FM
12:32:32FM
12:34:340M
12:38:35PM
12:40:468M
12:42:290M
12:44:550M
12:47:370M
12:49:4304
12:57:11R4
12:58:29 M
1:02:050M
1:02:340M
1:03:44098
1:04:2909
1:05:1608
1:05:2809
1:06:440M
1:07:560M
1:10:440M
1:12:4304
1:13:128M
1:14:0409
1:17:41R4
1:19:0609
1:20:42H4
1:20:57PM
1:25:42EM
129:21 0M
1:33:04 8M
1:36:43 0M
1:36:44 0M
1:38:40
1:39:19 81
1:41:468M
1:43:180M
1:44:370M
1:45:5709
1:48:40098
1:50:288M
1:51:088M
1:51:278M
1:53:520M
1:57:180M
2:00:1709
2:01:3089
2:01:418M
2:03:47EM
2:06:258M
2:07:078M
2:07:228M
2:09:058M
2:10:408M
2:11:050M
2:12:558M
2:13:338M
2:15:390M
2:21:320M
2:26:250M
2:28:54R4
2:31:4109
2:34:30
2:35:192M
2:37:312M
2:37:4028
2±37:462M
2:43:3528
2:46:1128
2:47:542M
2:49:0928
2:51:252M
2:51:322M
2:52:04
2:53:06
2:54:542M
2:56:37
3:00:52
3:08:212M
3:12:482M
3:13:072M
3:15:092M
3:28:11 2M
3:31:04 2M
3:31:05 28
3:32:28 2M
3:33:33 2M
3:37:222M
3±41:2328
3:45:502M
3:48:342M
3:52:272M
3:53:16
3:54:58
3:58:0928
3:59:3628
4:00:5128
4:03:132M
4:09:302M
M
M
M
M
M
M
M
M
score
duration
baddies
hits
shots
ip address of player
id#
0
4100
3050
9200
6500
3750
3950
3550
1850
0
1800
1400
2400
5150
6500
9650
4850
5550
50
0
900
3450
1750
5350
1250
4000
0
13200
1800
5050
8200
6050
3750
3500
6600
4700
8950
1500
8050
2500
2450
8250
28600
2400
2400
1550
2000
18150
2700
3200
4800
600
5450
4800
30400
10000
2700
4150
3000
4200
8300
100
4950
1100
0
3000
2800
400
11650
4750
0
8800
4750
8850
5100
2300
6300
4400
7500
8000
5550
3100
7600
1550
36750
250
2750
7750
0
0
0
10350
10650
12050
11750
11900
1950
21150
9050
7600
8750
7550
4400
5600
91
87
236
297
122
61
158
287
91
89
201
86
131
220
110
207
63
300
139
43
86
267
86
263
130
152
69
798
65
200
346
781
180
206
267
168
390
42
320
196
127
260
461
232
131
06
123
391
115
121
347
287
166
215
577
388
150
342
86
205
306
114
258
99
2
162
151
111
413
336
75
182
296
221
193
79
150
130
234
305
186
88
239
187
1153
92
107
269
251
133
74
287
212
212
219
148
201
239
264
826
412
276
202
244
0
8
8
20
19
8
8
10
6
0
3
2
4
11
12
21
11
13
0
0
3
9
7
13
5
10
0
34
2
18
17
23
9
7
18
10
18
6
14
4
4
19
49
4
4
4
3
39
4
5
12
2
12
11
55
19
9
11
5
11
15
0
15
4
0
5
7
0
25
16
0
17
11
20
12
5
13
7
14
32
11
6
16
5
145
1
11
17
0
0
0
26
23
19
21
18
5
32
25
29
28
15
10
11
0
56
70
183
145
48
54
133
99
1
21
20
39
111
117
195
63
77
2
4
52
90
86
78
79
106
21
346
29
169
412
149
119
40
154
60
182
49
201
31
25
154
649
24
28
66
24
469
31
34
88
41
86
100
718
292
97
62
31
91
188
16
140
50
0
30
56
22
296
151
0
167
116
216
100
28
157
116
137
206
88
41
151
55
780
65
123
204
0
1
0
237
313
277
261
246
70
466
235
220
197
130
97
127
0
150
180
358
711
255
179
824
213
5
131
63
171
466
375
574
187
367
11
37
67
271
180
530
845
537
100
1716
320
1844
940
1937
2390
554
911
118
607
93
296
110
118
303
1444
175
100
121
106
1340
103
96
336
64
175
582
2076
710
331
194
240
416
378
22
790
103
0
134
399
34
655
1565
0
407
944
470
431
217
386
240
398
473
455
227
535
245
3239
535
667
991
0
2
1
735
762
551
854
544
174
928
995
1598
854
329
294
389
p03-14.hartford.dialin.ntplx.mn/204.213.188.114
141.164.138.172/141.164.138.172
SHR01822.DMf.UJL.J/138.237.149.216
DOM.'T1J.HJ/138.237.149.216
SER01822.
209.16.236.61/209.16.236.61
209.16.236.61/209.16.236.61
241.arlingtcn-06.va.dial-access.att.net/12.68.69.241
s09.ts4.rb.wizzards.net/206.100.190.89
s09.ts4.rb.wizzards.net/206.100.190.89
d97.nnb2.interaccess.ca/204.149.98.97
195.100.66.2/195.100.66.2
195.100.66.2/195.100.66.2
195.100.66.2/195.100.66.2
7
0.14.155
170-14-155.ipt.ol.can/152.1
170-14-155.ipt.ol.can/152.170.14.155
170-14-155.ipt.ol.can/152.170.14.155
7
4
0.1 .155
170-14-155.ipt.aol.aoVl52.1
129.109.155.141/129.109.155.141
pn2-68.vegas.infi.net/206.97.53.68
98.ntimi.videtron.net/207.253.98.66
ncdenwable066.
2
pn -68.vegas.infi.net/206.97.53.68
7
usr-x2-aln-08.libertyaccess.-n/s209.176.111.11
±nderable066.98.ntimi.videotron.net/207.253.98.66
129.109.155.141/129.109.155.141
nodenrble066.98.ntimi.videtron.net/207.253.98.66
3051
3052
3053
3054
3055
3056
3057
3058
3059
3060
3061
3062
3063
3064
3065
3066
3067
3068
3069
3070
3071
3072
3073
3074
3075
3076
3077
3078
3079
3080
3081
3082
3083
3084
3085
3086
3087
3088
3089
3090
3091
3092
3093
3094
3095
3096
3097
3098
3099
3100
3101
3102
3103
3104
3105
3106
3107
3108
3109
3110
3111
3112
3113
3114
3115
3116
3117
3118
3119
3120
3121
3122
3123
3124
3125
3126
3127
3128
3129
3130
3131
3132
3133
3134
3135
3136
3137
3138
3139
3140
3141
3142
3143
3144
3145
3146
3147
3148
3149
3150
3151
3152
3153
3154
GLOM:Information Agglomerates
oderable066.98.ntind.vidotron.net/207.253.98.66
getdbwns.pr.ncs.net/204.95.35.92
34
7
5
.215.85.
p-207-21 -85-34.scrnO1.pacbell.net/20
3 92
5.
gettbns.pr.n=s.net/204.95.
getcbns.pr.ncs.net/204.95.35.92
34
7
.215.85.
ppp-207-215-85-34.scrnOl.pacbell.net/20
rp009.sf.hac.net/208.154.136.41
getda1ns.pr.ncs.net/204.95.35.92
s22.netfox.net/208.222.213.22
client-151-198-132-13.bellatlantic.net/151.198.132.13
243
2 9
poo1043-nnx2.s13-ca-us.dialup.earthlink.net/ 0 .178.15.
pr092.kiski.net/208.22.46.142
3 2 7
.<xmV24. . 2 .131
cx45836-a.coanl.n.lre
7
3
pool043-nex2.ds13-ca-us.dialup.earthlink.net/209.1 8.15.24
dip-01.nux-01.seeca.conline.net/206.101.113.101
dip-01.nox-01.seneca.csnline.net/206.101.113.101 7
43
pool043-nx2.ds13-ca-us.dialup.earthlink.net/209.1 8.15.2
prO92.kiski.net/208.22.46.142
dip-01.nox-01.secn.csonline.net/206.101.113.101
dip-O.nex-±01.smeca.csonline.net/206.101.113.101
slipl66-72-157-96.ca.us.ihn.net/166.72.157.96 3
.101
dip-01.nex-01.senca.csonline.net/206.101.11
pn092.kiski.net/208.22.46.142
dip-l.nux-01.ooeca.csonline.net/206.101.113.101
dip-01.nox-01.eneca.csonline.net/206.101.113.101
142.204.84.53/142.204.84.53
gp-206-170-2-83.sntc0l.pacbell.net/206.170.2.83
NEAL.uwsp.edu/143.236.55.208
sherwood-142.foothill.net/209.77.113.142
kirkOl-5.accessone.om/209.43.128.5
gplO8.brandywine.net/207.106.54.40
sc24.c.siue.eda/146.163.15.54
eb-pn1--27-59.dialup.slip.net/207.171.198.59
eb-pnl-27-59.dialup.slip.net/207.171.198.59
sc24.ac.siue.edu/146.163.15.54
gp108.brandywine.net/207.106.54.40
ts1-06.f1701.quebectel.cc/142.169.136.9
4
sc24.ac.siue.edu/146.163.15.5
pn3170.spectra.net/204.177.130.170
166-93-76-79.nTr.net/166.93.76.79
208.31.5.249/208.31.5.249
208.31.5.249/208.31.5.249
pc-4514.on.rogers.wave.ca/24.112.40.198
plO9b.rtn.mzt.edu/129.138.35.69
208.31.5.249/208.31.5.249
172-222-235.ipt.ol.cc/152.172.222.235
3
7
1.20.155
171-203-155.ipt.aol.c/152.1
208.31.5.249/208.31.5.249
171-203-155.ipt.aol.cc/152.171.203.155
ip23.cws-inc.ccV208.6.203.151
208.31.5.249/208.31.5.249
68.chattanooga-01.tn.dial-acces.att.net/12.69.76.68
208.31.5.249/208.31.5.249
ip23.cws-inc.<xn/208.6.203.151
202-36-248.ipt.aol.cn/152.202.36.248
208.31.5.249/208.31.5.249
208.31.5.249/208.31.5.249
208.31.5.249/208.31.5.249
206.153.71.83/206.153.71.83
202-36-248.ipt.ol.ccn/152.202.36.248
sa7-p43.dremscape.ccm/209.4.228.171
a7-p43.dremcape.ccn/209.
4 24. 228.171
7 22 7
travelsys.cnn/20 .1 . 5.2
97
3
.121. 6
client-151-197-121-36.bellatlantic.net/151.1
irvnetserver_11.ploenix.cc/134.122.60.61
clieit-151-197-121-36.bellatlantic.net/151.197.121.36
bradfordOl6-ResHalls.Mines.EI3/138.67.72.16
bradfordOl6-ResHalls.Mines.EIU/138.67.72.16
bradfordOl6-ResHalls.Mines.EDIJ/138.67.72.16
bradfordOl6-ResHalls.Mines.EIU/138.67.72.16
bradford016-ResHalls.Mines.EIU/138.67.72.16
t2-34.tznet.ccm/205.216.108.34
bradford016-ResHalls.Mines.EIlJ/138.67.72.16
2 3
7
1. 0 .155
171-203-155.ipt.aol.ccnV152.1
hlfx36-26.ns.synpatico.ca/142.177.29.95
t2-34.tznet.con205.216.108.34
1Cust221.tnt16.sfo3.da.uu.net/153.37.46.221
t2-34.tznet.ccu/205.216.108.34
208.230.216.250/208.230.216.250
125
id#
date
time
scors
duration
baddise
hits
shots
ip address of player
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
4:12:57 24
4:15:54
4:16:26 24
4:16:33
4:18:37
4:18:38 EM
4:23:03 2M
4:23:15
4:26:31 24
4:41:292M
4:46:172M
4:50:132M
4:55:072M
4:55:25
4:58:0424
4:59:4124
5:08:29
5:15:15
5:20:35
5:21:09m
5:26:57
5:29:48
5:32:26
5:33:552M
5:34:11
5:34:452M
5:34:572M
5:38:08
5:38:542M
5:39:432M
5:42:5724
5:43:4824
5:44:59 4
5:47:5424
5:52:2324
5:55:422M
6:55:462M
6:55:482M
6:55:48
6:55:4924
6:55:4924
6:55:502M
6:55:512M
6:55:512M
6:55:522M
6:55:522M
6:55:5324
6:55:542M
6:55:542M
6:55:552M
6:55:562M
6:55:5624
6:58:442M
7:00:352M
7:00:562M
7:01:5924
7:04:11
7:05:0624
7:13:2524
7:20:262M
7:21:12 4
7:21:372M
7:26:2424
7:28:212M
7:29:502M
7:52:31PM
7:54:132M
7:56:16 4
7:57:19 2M
8:22:12
8:34:2224
8:43:17
8:56:11 4
8:59:50
9:11:072M
9:17:232M
9:19:362M
9:21:352M
9:22:27 4
9:23:48 4
9:24:252M
9:25:56 24
9:28:16
9:31:19 4
9:34:352M
9:36:0324
9:36:57
9:38:16 2M
9:44:452M
9:45:02
9:48:36
9:54:462M
9:57:57 2M
9:58:312M
10:01:112M
10:07:482M
10:11:344
10:12:4024
10:13:444
10:17:13
10:17:2324
10:27:09
10:28:59
10:29:10
12650
2150
3250
500
2650
6150
2500
650
11100
4000
7550
6350
8350
2450
2400
1800
2650
3750
350
3800
3750
5200
0
1200
3250
4800
3500
5850
3600
4300
3350
4600
800
2950
2950
4600
4750
3700
7900
4800
700
9400
4700
2750
9650
2450
4750
4700
3000
3650
2050
6950
3950
0
5550
6650
5550
6600
2950
6050
1800
9300
7700
11400
9050
700
11500
3950
2150
0
1750
200
5450
400
5250
4950
8700
5450
2350
900
1450
8600
7550
6300
7550
450
0
0
12500
0
1800
4350
6000
3350
11550
11650
3400
6600
3150
4200
4750
10750
1500
1450
569
236
201
31
148
324
144
67
423
171
271
220
276
367
137
166
94
315
85
163
332
152
40
74
245
149
86
181
267
333
159
279
84
223
96
181
195
157
501
114
41
366
250
202
302
120
267
536
178
304
146
201
203
53
234
217
294
171
190
403
110
381
296
371
191
324
314
108
261
4
111
83
425
65
247
459
266
167
37
64
23
493
463
272
248
242
38
64
748
391
66
157
211
131
370
535
80
333
110
488
263
567
88
65
25
4
12
2
5
16
4
1
29
10
13
11
18
4
4
3
5
7
1
8
8
12
0
2
6
10
14
16
8
11
5
12
1
10
6
10
13
9
19
11
1
21
11
6
17
4
11
12
11
13
3
18
9
0
12
18
20
19
6
18
3
28
21
32
19
1
29
10
3
0
7
0
12
0
10
17
25
19
8
3
5
33
20
18
17
1
0
0
40
0
3
16
23
5
30
43
6
15
7
9
16
20
6
5
359
26
133
44
35
90
26
9
228
66
133
137
182
57
27
19
36
46
9
53
61
78
13
18
43
61
115
88
72
108
48
95
10
106
37
57
111
89
191
83
14
241
65
67
232
34
68
162
99
141
24
196
123
0
87
166
162
171
38
118
23
185
167
310
218
19
286
140
29
0
75
4
88
13
118
132
164
165
109
86
75
240
167
153
161
28
6
9
233
24
18
149
163
39
278
292
53
154
90
58
151
290
72
62
964
62
388
52
113
779
91
44
927
156
361
258
450
459
155
76
102
196
37
146
264
200
59
89
119
274
247
344
197
456
256
340
72
428
219
791
495
309
1068
206
66
718
593
163
433
102
387
1011
285
1670
124
615
968
0
238
970
531
863
63
607
49
1435
578
1342
536
60
1220
422
57
0
208
12
223
67
366
544
521
864
218
391
160
1235
799
727
520
232
26
48
692
182
72
509
327
110
1501
1871
78
366
253
313
394
672
172
109
3155
t2-34.tmet.o/205.216.108.34
3156
spm13-lardtx.ICSI.Net/199.1.102.131
3157
141.85.134.3/141.85.134.3
3158
node29.nophersonx2.mida.net/208.137.165.29
2
3159
.131
3160
t2-34.tznet.ccmV205.216.108.34
3161
1Cust43.nex7.cleveland.oh.no.uu.net/153.35.127.171
8 9
3162
.1 6.56.109
oaturn-109.internet-frotir.net/20
3
3163
4
t2-34.tznet.can/205.216.108.
4
3164
1Cust26.nex43.chicago.il.no.uu.net/153.35.119.15
3165
1Cust26.onx43.chicag.il.ne.uu.net/153.35.119.154
3166
1Cust26.nax43.chicago.il.neuu.net/153.35.119.154
3167
1Cust26.nex43.chicago.il.no.uu.net/153.35.119.154
3168
dynamoic9.buf.adelphia.net/24.48.32.9
3169
dynmc9.buf.adelphia.net/24.48.32.9
7 36
3170
kngga3-19.gate.net/20
9 . 24.2.82
42
3171
.1. .1
chal2.ramlink.net/19
3172
206.81.150.102/206.81.150.102
3173
38.186.109.18/38.186.109.18
3174
C P154-224.SplitRock.net/209.156.154.224
Kansascity
3175
KansasCityKCDP154-224.SplitRock.net/209.156.154.224
3176
KansascityICDP154-224. SplitRock.net/209.156.154.224
3177
ho.cn/24.1.166.211
cx64525-a.alsv1.occa.8
3178
cx64525-a.alsvl.occa.hcne.caV24.1.166.211
3179
KansasCityKCDP154-224.SplitRock.net/209.156.154.224
3180
ci85061-a.nashl.tn.xmre.cn/24.2.97.219
3181
epc-isp-wpg-uas-05-17.sprint.ca/209.103.40.68
3182
ci85061-a.nashl.tn.hcoe.can/24.2.97.219
4 2 4
6
3183
.15
.
2
Kma9nsCityIP154-224.SplitRock.net/209.15
3184
cx64525-a.all.occa.rme.ocan/24.1.166.211
3185
cx64525-a.alsvl.occa.hcne.caV24.1.166.211
3186
KansasCityKCDP154-224.SplitRock.net/209.156.154.224
3187
c64525-a.alvl. occa.hcae.ccrv24.1.166.211
4
3188
KnsaoCity4P154-224.SplitPock.net/209.156.154.22
00
3189
.182
tc2-52.utah-inter.net/208.14.2
3190
tc2-52.utah-inter.net/208.14.200.182
3191
ocal-pr2-04.mfi.net/205.161.238.51
4
8
34
3192
.26.1 .18
d01oa6b8.dip.cdsnet.net/20
3193
bay6-2.dial.umd.edu/128.8.23.66
3194
d01o86b8.dip.cdsnet.net/208.26.134.184
3195
d01oa86b8.dip.cdsnet.net/208.26.134.184
3196
t3-125.tznet.ccan/205.216.108.125
3197
t3-125.tznet.can/205.216.108.125
7 3
7
3196
.21 .22.100
pool050-nxl2.ds6-ca-us.dialup.earthlink.net/20
6
8
3199
.10
.l25
t3-125.tznet.can/205.21
6
3
3200
.2 9.151
lgdtppl5l.eoni.can/0192.21
7 232
7
3201
.100
pol050-nx12.ds6-ca-us.dialup.earthlink.net/20 .21 .
3202
client-207-68-63-65.bellatlantic.net/207.68.63.65
39
3203
.151
1gdgp±151.eoni.caW192.216.2
3204
pol050-naxl2.ds6-ca-us.dialup.earthlink.net/207.217.232.100
3205
guyas52004al.ptsi.net/207.50.2.132
3206
tntO-080115.k.sound.net/209.153.80.115
3207
130.160.36.85/130.160.36.85
3208
cet1.cray.can/137.38.96.10
3209
guyas52004al.ptsi.net/207.50.2.132
3210
tntO-080115.kc.sound.net/209.153.80.115
3211
pn-14.ili.net/206.250.201.38
9
3 8
3212
.157. 0.115
tntO-080115.ke.ound.net/20
46
3213
201-170-46.ipt.ol.co/152.201.1
7 0.
3214
0.46
201-170-46.ipt.ol.can/152.201.1
77
3
3215
.25
1Cust253.tnt1.orll.da.uu.net/208.250.
7
3216
07
203-51-170.ipt.aol.cano/152.203.51.1
3217
7.253
1Cut253.tnt.orl.da.uu.net/208.250.
3218
203-51-170.ipt.aol.cn/152.203.51.170
3219
lCust253.tntl.or11.da.uu.net/208.250.77.253
3220
ostbllO.capecod.net/208.204.67.110
3221
sa3-p34.dreamscape.can/207.198.19.98
3222
sa3-p34.dreamscape.can/207.198.19.98
3223
ostbllO.capecod.net/208.204.67.110
3224
cc1004774-a.1vxnml.pa.1xue.ca/24.3.108.110
6
3225
tns02046.singnet.can.sg/165.21.204.23
3226
1Cusstll9.tnt24.sfo3.da.uu.net/208.255.67.119
7
3227
.69.224.51
us-37kbo1j.dialup.mindspring.cam20
36
3228
.228
hnte.panedics.can/207.203.1
3229
205-123-176.ipt.aol.cn/152.205.123.176
3230
1Cust193.tnt3.beavertan.or.da.uu.net/153.35.224.193
3231
p89.p.wr.ic.net/l52.l60.l7.92 7 2 3 98 6 6
3232
mnoecableO66.98.timi.videotran.net/20 . 5 . .
3233
nodmicableO66.98.ntii.videotran.net/207.253.98.66
3234
mndaable066.98.ntini.videotron.net/207.253.98.66
3235
nodacable066.98.ntimi.videotran.net/207.253.98.66 93
3236
1Custl93.tnt3.baverton.or.da.uu.net/153.35.224.1
3237
194.binminghO-01.al.dial-access.att.net/12.67.64.194
9
3238
3
1Cust193.tnt3.beaverton.or.da.uu.net/153.35.224.1
6 9
3239
.5
ip226-59.cc.interlog.can/207.34.22
93
3240
1Cust193.tnt3.beaertn d..a.net/153.35.224.1
3241
1Cust193.tnt3.beaerton.or.da.uunet/153.35.224.193
93
3 3
2 4
3242
. 5. 2 .1
1Cut193.tnt3.bevertn.or.da.uu.net/15
3243
oak-port34.jps.net/209.142.28.41
3244
1Cust193.tnt3.beaerton.or.dak.uu.net/153.35.224.193
3245
128.100.46.51/128.100.46.51 37 3
3246
.6
sil-wa2-04.ix.netcan.can/206.214.1
3247
line14.vernonia.can/206.58.139.145
3248
204.244.96.78/204.244.96.78 37 36
3249
.
sil-wa2-04.ix.netcan.can/206.214.1
3250
linel4.vernonia.can/206.58.139.145
7 6
9
3251
0.
.2
29.orlando-07.fl.dilal-acess.att.net/12.
3252
dialup4.pn2.caerns.can/206.206.164.25
7 6 29
3253
0. .
29.orlanc&-07.fl.dial-acess.att.net/12.
3254
dyn72ppp169.pacific.net.sg/210.24.72.169
4
3255
.25
dialup4.pn2.caverns.om/206.206.16
64
6 2
3256
.25
dialup4.pa2.caverns.an/20 . 706.1
7
4
3257
vchase1port10.hileot.can/20 . 1.2. 6
3258
pppa163.oke.nstar.net/209.131.174.163
M
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GLOM:Information Agglomerates
pp131-lardtx.ICSI.Net/199.1.10
126
date
980503
980503
980503
980503
980503
980503
980503
980503
980503
980503
980504
980504
980504
980504
980504
980504
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980504
tim
10:30:53 R4
10:33:19
10:34:48 24
10:36:05
10:36:092M
10:48:30PM
11:11:232M
11:15:24PM
11:26:01R4
11:45:2624
12:08:18AM
12:41:17
12:43:11AM
1:46:36AM
3:52:13AM
3:58:49 AM
6:07:36AM
7:25:16AM
7:39:58AM
7:52:33AM
8:21:070M
8:22:35A14
8:41:480M
8:43:09
8:45:19004
8:45:270M
8:51:08004
9:11:12AN
9:22:310M
9:34:460M
9:42:150M
9:44:180M
9:46:590M
9:47:000M
9:47:150M
9:52:28AM
9:55:29A04
0M
10:02:13
10:04:35M
10:23:58 AM
10:28:38 AM
10:33:20 008
10:35:58004
10:40:34004
AM
11:00:04
11:05:43004
11:07:220M
11:16:44AM
11:18:290M
12:07:52
12:13:55
12:21:082M
12:51:542M
12:55:422M
12:56:172M
12:57:582M
1:12:212M
1:14:332M
1:15:482M
1:18:202M
1:18:51R4
1:20:452M
1:25:172M
1:38:132M
1:57:1424
2:31:11FM
2:31:14FM
2:39:442M
2:40:082M
2:42:5524
2:50:3924
3:22:27
3:24:502M
3:25:0824
3:27:43
3:42:33
3:46:0524
3:49:212M
3:54:022M
4:06:12
4:09:312M
4:17:50M
4:22:3224
4:25:322M
4:28:3924
4:29:022M
4:30:362M
4:35:48
4:39:0124
4:39:422M
4:39:5524
4:40:092M
4:41:27FM
4:43:1324
4:48:512M
4:51:1424
4:51:27
4:52:382M
4:54:302M
4:55:352M
4:57:0924
4:58:5024
5:00:212M
5:02:492M
M
M
M
M
M
M
M
M
M
M
M
M
id#
scors
duration
baddias
hits
shots
ip address of player
2300
5000
500
1400
200
4900
2550
7500
8350
6600
4350
3200
4000
5300
7300
6600
3450
11000
0
0
700
2400
0
1300
1950
1850
7400
0
3700
0
8400
3350
7650
2450
0
20550
5000
9150
4100
4000
3400
0
1550
2650
650
1400
4300
0
0
8600
6500
0
4000
0
6600
4150
6450
1400
1250
2350
0
3500
3500
300
5650
50
0
0
4100
4350
800
8350
4600
3550
4450
1800
800
1250
10100
4100
2900
4650
7950
7050
6850
7550
3000
1800
3750
2200
13750
2550
3200
7500
4850
3650
12450
850
150
9000
0
6200
7150
4000
97
355
52
551
65
162
109
290
242
333
171
132
104
394
438
300
82
451
7
62
49
73
92
88
66
111
402
45
214
25
349
111
353
40
4
296
234
386
124
171
154
40
142
398
102
98
247
697
1
230
628
128
145
27
154
121
325
116
61
137
15
100
80
118
363
117
54
119
161
156
62
208
106
154
662
77
79
88
358
169
258
146
202
164
169
386
100
32
177
149
638
163
89
237
213
309
674
59
103
388
30
241
269
83
9
11
1
4
0
14
6
24
25
16
10
5
10
21
23
18
6
38
0
0
2
8
0
3
7
4
24
0
9
0
21
7
19
9
0
37
14
22
8
16
8
0
6
5
2
3
11
0
0
19
13
0
8
0
18
9
20
4
4
7
0
13
11
1
22
0
0
0
9
16
1
18
10
8
8
3
2
5
23
9
6
10
17
14
12
21
5
6
8
6
39
4
5
23
11
9
35
2
0
20
0
16
12
7
93
64
10
84
10
94
75
189
158
104
68
43
85
163
159
150
48
245
0
0
19
80
1
31
94
69
192
0
67
6
240
79
178
105
0
662
110
185
46
114
84
0
61
29
47
40
129
0
0
166
142
0
54
20
162
79
173
96
61
109
18
121
127
7
167
9
0
0
53
135
10
162
88
65
172
28
35
64
189
55
37
64
220
188
116
165
45
53
55
53
300
30
34
154
67
52
308
11
16
171
0
122
133
73
318
372
36
277
29
376
182
1078
914
311
375
254
210
1311
343
296
119
1065
1
0
42
197
4
140
206
277
1053
0
385
14
759
202
497
149
0
1102
290
504
177
302
350
0
123
251
125
115
522
0
0
604
565
34
346
23
532
411
826
242
141
301
49
348
302
32
853
55
0
5
163
540
30
418
237
186
397
70
86
103
529
242
98
143
609
408
306
867
165
186
749
91
1608
55
65
1450
226
294
1051
42
73
454
0
336
215
116
3259
vchaselportlO.hilcont.om/20 . 1.2.
3260
dialup4.pn2.caverns.can/206.206.164.25
3261
209.210.180.13/209.210.180.13
3262
1c091.zianet.cVn204.134.124.191
3263
209.210.180.13/209.210.180.13 2 6 7 3 88
3264
. . .1
188.dallas-10.tx.dial-access.att.net/1
3265
coltrane-a-asy-16.rutgers.edu/165.230.208.84
3266
131.denver-18-19rs.co.dial-access.att.net/12.74.79.131
2 7 4 79
3267
. . .131
131.de r-18-19rs.co.dial-access.att.net/1
3268
a16-41.itis.co-V209.83.14.233
3269
ts233.ver.wis.net/204.191.170.233
3270
58.seattle-08.wa.dial-access.att.net/12.65.80.58
2 6 8
3271
. 5. 0.58
58.seattle-08.wa.dial-access.att.net/1
3272
203.35.209.212/203.35.209.212
3273
209.58.12.189/209.58.12.189
3274
209.58.12.189/209.58.12.189
3275
194.168.203.189/194.168.203.189
67 37
3276
net.au/202.1 . .150
nodan31-syd-isp-10.ne.
3277
sfo-ca5-18.ix.netcan.caV199.35.210.178
3278
207.87.132.10/207.87.132.10
3279
cxjcave-3-15.cgocable.net/24.226.3.15
3280
cgave-3-15.cgocable.net/24.226.3.15
4 94
3281
0.
lvl-nuc079.usc.edu/128.125.1
3282
1vl-nmc079.usc.edu/128.125.140.94
3283
lvl-nc079.usc.edu/128.125.140.94
4 94
3284
0.
lvl-nc079.usc.du/128.125.1
3285
nesx-09-2-11.1033.cybervity.dk/195.8.139.172
3286
rotc8.rotc.ntu.edlu/141.219.41.148
3287
rotc8.rotc.ntu.edu/141.219.41.148
3288
206.26.220.6/206.26.220.6
3289
inkling.cba.uga.edu/128.192.100.227
2 7
3290
2 3
inkling.cba.uga.edu/128.192.100.
3291
5
pulaski-2-12.netnet.net/206.40.105.
3292
inkling.cba.uga.edu/128.192.100.227
3293
pulaski-2-12.netnet.net/206.40.105.35
7
0
3294
0.22
inkling.cba.uga.edu/128.192.1
3295
pulaski-2-12.netnet.net/206.40.105.35
3
6 4
3296
. 0.105.5
pulaski-2-12.netnet.net/20
3297
pulaki-2-12.netnet.net/206.40.105.35
3298
host-209-215-184-27.c1t.bellsouth.net/209.215.184.27
3299
host-209-215-184-27.clt.bellsouth.net/209.215.184.27
3300
odec1.ar1.mil/128.63.56.81
3301
odepc1.arl.mil/128.63.56.81
3302
209.174.249.15/209.174.249.15
7
3303
8.168.101
robert.nic-inc.cm±/207.
3304
207.74.186.132/207.74.186.132
3305
gbe.ne.nediaone.net/24.128.3.917
3306
.92
lCust92.tnt1.chi2.da.uu.net/208.250.11
3307
207.240.172.237/207.240.172.237
4 7
3308
.5
du75.wb.ptd.net/204.186.1
3309
ts29111.pathccm.cam/209.112.18.62
3310
160.7.64.192/160.7.64.192
3311
Ectnosion-131B.CSS.CSr.EIU/128.193.102.154
3312
t2o39p9.telia.cm/o195.198.43.69
3313
Extension-131B.CSS.CPSr.E[U/128.193.102.154
3314
t2o39p9.telia.cm/195.198.43.69
3315
199.176.126.236/199.176.126.236
3316
199.176.126.236/199.176.126.236
3317
199.176.126.236/199.176.126.236
3318
199.176.126.236/199.176.126.236
3319
199.176.126.236/199.176.126.236
3320
199.176.126.236/199.176.126.236
3321
199.176.126.236/199.176.126.236
3322
164.116.208.135/164.116.208.135
3323
lCust95.tnt3.det3.da.uu.net/208.254.241.95
3324
209.12.85.104/209.12.85.104
3325
209.12.85.106/209.12.85.106
3326
64 37
7 6
3327
g2-p5.hamilton.wochat.on.ca/20 7 . 1.1 . 7
3328
.61.164.3
g2-p5.hamilton.wchat.on.ca/20
3329
149.127.130.115/149.127.130.115
3330
han96-105.hil.ccupuserve.cm/209.154.58.105
3331
hdn96-105.hil.copuserve.ccm/209.154.58.105
3332
us030.rdyne.hn aboeing.cPV134.57.58.141
3333
1Custl8O.tntO10.bos2.da.u.net/208.254.152.180
3334
195.64.37.42/195.64.37.42
3335
204.244.239.36/204.244.239.36
8 222
68
3336
.1 0.
}ost-222.inter-tel.ccn/192.
3337
pulaski-5-2.netnet.net/206.40.105.88
3338
pulaski-5-2.netnet.net/206.40.105.88
3
3339
1Cust2.nex35.cleveland.oh.m.uu.net/153. 5.141.130
3340
rpp645.pdn.net/207.226.201.145
3
3341
5
35.new-york-27.ny.dial-access.att.net/12.68.134.
3342
35.new-york-27.ny.dial-access.att.net/12.68.134.35
3343
35.new-york-27.niy.dial-access.att.net/12.68.134.35
3344
172-193-29.ipt.aol.ccn/152.172.193.29
3345
s.att.net/12.68.134.35
35.new-york-27.ny.1ial-acso
3346
1Cust10.nex2.neyork.ny.ne.uu.net/153.35.0.138
3347
1Cust10.nnx2.new-york.ny.n.uu.net/153.35.0.138
8 96 32
3348
.1 . .105
hag3.info xc.ca/20
3349
172-193-29.ipt.aol.cc/152.172.193.29
3350
198.76.226.137/198.76.226.137
3351
hag3.infoccm.ccn/208.196.32.105
38
3352
1CustlO.nex2.new-york.ny.ms.uu.net/153.35.0.1
3353
hag3.infoocm.ccV/208.196.32.105
3354
198.30.208.65/198.30.208.65
7 2 93 2 9
3355
.1 .
172-193-29.ipt.aol.±on/152.1
3356
198.30.208.65/198.30.208.65
3357
ipP3158.qc.bellglobal.com/206.172.222.86
3358
hag3.infoccm.ccn208.196.32.105
3359
c00980-247dan.eos.ncsu.edku/152.1.21.80
9
7 64
3360
. .15
159.birminghoa-01.al.dial-access.att.net/12.6
3361
cV/208.196.32.105
hag3. infocom.
3362
206.144.90.176/206.144.90.176
GLOM:Information Agglomerates
7 7
46
apool270.sbceo.k12.ca.us/204.48.133.70
127
date
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980504
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
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980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
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980505
time
5:04:57 2M
5:06:28 2M
5:07:42PM
5:09:14PM
5:11:21
5:11:222M
5:11:340M
5:13:56PM
5:13:582M
5:14:20PM
5:16:28EM
5:17:32
5:20:442M
5:20:582M
5:22:45
5:26:05
5:27:17
5:50:07
5:51:14
5:52:41
5:54:15
5:58:58
5:59:28
6:01:18
6:08:232M
6:10:0424
6:30:312M
6:46:5424
6:48:1924
6:55:352M
6:56:202M
6:57:57 4
7:14:062M
7:25:472M
7:29:20
7:29:362M
7:29:55
7:32:21
7:36:54R4
7:38:33
7:41:13
7:43:0124
7:43:322M
7:44:522M
7:46:142M
7:47:082M
7:49:082M
7:52:392M
7:54:32FM
7:58:582M
7:59:222M
8:01:472M
8:03:33
8:04:132M
8:28:462M
8:32:162M
8:43:342M
8:52:20
9:21:042M
9:23:592M
9:26:502M
9:29:092M
9:32:052M
9:42:272M
9:50:44
9:52:042M
10:02:082M
10:11:08
EM
10:26:072M
10:31:052M
10:50:14
10:52:2924
10:56:56
R4
10:59:47
11:08:03
11:14:43
11:34:4624
EM
11:55:09
11:59:352M
A14
12:04:36
12:21:54M
12:26:45M
12:28:390M
12:34:11 2
12:49:24M
1:17:52M
1:20:45
1:29:17M
4:01:08M
4:44:26M
4:46:48M
4:50:27
5:37:47M
5:40:59
6:06:21M
6:17:54M
6:21:16M
6:25:27M
6:39:20M
7:20:23M
7:49:21M
7:51:55M
8:07:01M
9:18:21M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
MA
MA
MA
score
8000
0
10000
7700
800
2550
0
950
0
1300
0
8550
1100
0
2000
10650
1750
2700
1900
1950
2450
3350
5100
4100
750
750
2500
11700
0
5000
900
1700
20200
3550
3000
1750
3950
6350
2500
14150
3150
8850
3850
3200
7900
4650
7100
5100
4000
10600
2300
4350
650
5150
5250
4150
4400
0
4150
3450
2750
2400
3200
22200
1300
10000
0
36050
0
3300
1100
1450
4400
4850
5350
10250
4300
2950
4900
9050
2900
7050
7300
3350
400
1850
4400
11000
8600
3900
3800
4000
7750
3850
3400
3500
5600
8150
9150
8300
6050
4750
2500
3500
duration
252
8
282
224
23
204
4
215
80
227
307
312
113
4
92
869
56
125
51
72
74
212
174
123
130
92
210
761
96
207
66
77
265
225
63
184
229
141
137
358
205
253
157
207
178
200
159
195
98
693
226
131
87
188
146
516
177
62
179
343
157
123
162
741
77
566
11
1126
72
162
90
118
249
154
247
384
374
149
169
284
221
276
387
238
82
109
159
496
178
166
125
190
524
174
140
187
187
235
236
228
213
139
93
120
GLOM:Information Agglomerates
baddies
16
0
23
15
1
4
0
3
0
4
0
27
3
0
8
27
5
10
7
4
4
9
11
8
1
3
6
29
0
13
3
6
29
7
12
7
7
11
4
26
7
20
7
7
16
11
18
13
9
36
6
9
1
11
14
9
9
0
8
8
5
4
5
73
2
24
0
106
0
7
2
3
17
11
13
20
12
6
11
18
6
28
18
7
1
7
9
22
15
10
9
9
24
11
8
8
16
20
24
17
17
13
4
7
hits
136
0
220
125
10
29
0
50
0
82
0
188
51
0
74
208
81
122
106
27
26
89
68
92
26
33
67
252
0
87
47
87
345
49
101
58
59
188
43
397
52
213
47
48
173
69
175
129
101
256
54
51
15
109
110
53
55
0
66
47
31
25
34
491
21
288
0
971
0
77
45
17
156
139
95
303
130
36
63
162
101
192
140
59
47
72
53
320
279
61
80
55
165
76
75
46
120
201
186
185
112
106
26
40
shots
307
0
660
230
26
108
0
98
2
241
7
534
196
4
468
1991
194
465
232
186
213
433
388
234
48
92
158
1147
8
437
118
280
600
211
327
98
175
346
93
1272
251
974
129
326
524
259
671
1064
267
1551
251
290
30
469
313
373
138
7
117
642
167
135
244
3959
46
1451
1
5092
0
392
117
217
792
322
267
545
358
131
304
453
636
655
497
275
145
142
408
1005
481
234
225
236
1065
784
153
371
557
765
729
660
493
381
257
98
id#
ip address of player
3363
hag3.inf±oan.can/208.196.32.105
3364
pp15.loflink.amn/199.173.65.115
3365
206.144.90.176/206.144.90.176
3366
hag3.inflo.cV208.196.32.105
3367
nat-soc-248-1.tdbank.ca/142.205.248.1
3368
198.76.242.183/198.76.242.183
3369
198.76.242.183/198.76.242.183
3370
198.243.102.142/198.243.102.142
3371
207.221.223.193/207.221.223.193
usr32-dialup23.mixl.WilloSprings.ni.net/166.55.42.215 3372
3373
208.214.94.67/208.214.94.67
38 24 4 2 9
3374
. .1
ntro-244pgp219.epix.net/205.2
3375
198.76.242.187/198.76.242.187
3376
198.76.242.187/198.76.242.187
3377
198.76.242.187/198.76.242.187
3378
nat-soc-248-1.tdbank.ca/142.205.248.1
3379
nat-oc-248-1.tdbank.ca/142.205.248.1
6
3380
derable066.98.ntimi.videotron.net/207.253.98. 6
3381
nodmrable066.98.ntimi.videotron.net/207.253.98.66
3382
nodacable066.98.ntimi.videotron.net/207.253.98.66
3383
nodeable066.98.ntimi.videotron.net/207.253.98.66
3384
PS41.RESNEr.CRNELL.EI/128.253.136.43
3385
lCust44.tnt1.stl1.da.uu.net/153.34.192.44
3386
PS41.RESNE0TJEL.EIIJ/128.253.136.43
3387
198.76.216.127/198.76.216.127
3388
198.76.216.127/198.76.216.127
3389
pn202.newulntel.net/206.10.54.131
3390
2Custll.tnt3.ne--port-richey.fl.gt.uu.net/208.255.195.139
7
3391
F101-7.cc.berkshire.org/208.200.68.10
3392
206.144.90.176/206.144.90.176
3393
192.san-juan-01.pr.dial-acces.att.net/12.70.52.192
7
2 92
3394
0.5 .1
192.s
a-jua-O01.pr.dial-accss.att.net/12.
3395
ci85061-a.nashl.tn.hcue.cca/24.2.97.219
0 67
8 38
3396
.2 .20 .
dialinl403c.carol.net/20
6
3397
r.net/207.253.98.6
ondecableO66.98.ntii.vidot
3398
p224-20.atlas.co.uk/195.54.224.20
0 67
3399
0.
dialinl403c.carol.net/208.238.2
3400
ndecable066.98.nitimi. vidotron.net/207.253.98.66
3401
rice-b-04.altoona.nb.net/209.161.76.196
3402
nodorable066.98.nt±ii.videotron.net/207.253.98.66
3403
d01a80oe7.dip.cdsnet.net/208.26.128.231
3404
nodsakble066.98.ntimi.vidootron.net/207.253.98.66
3405
nodm61.trun.edlu/150.243.190.51
8 3
3406
.21
d01a80e7.dip.cdsnet.net/208.26.12
3407
=ndmcable066.98.ntimi.videotron.net/207.253.98.66
3408
nodem51.trun.edu/150.243.190.51
66
3409
nndecable066.98.ntii.vidotron.net/207.253.98.
3410
odeacable066.98. nt-ii.videotron.net/207.253.98.66
6
7
3411
.253.98.6
ndmcable066.98.nitimi.vidotron.net/20
9
3412
0.516
nd6l.trumn.edu/150.243.1
3413
stn-onl-22.netcan.ca/207.181.100.8
3414
st
l-22.netcrn.ca/207.181.100.86
3415
stn-on1-22.netcn.ca/207.181.100.86
39
3416
s152.coolink.net/199.190.82.2
3417
haddona26.snip.net/208.211.70.26
3418
204.229.212.92/204.229.212.92
3419
patron.library.ci.nrnview.ca.us/207.201.60.22
207-172-245-190.s63.all.nrf.erols.canV207.172.245.190 3420
3421
dt031n70.neine.rr.canV204.210.85.112
3 3 6 9 23 6
3422
. . 4.
1Cust236.tntl5.atl2.da.uu.net/15
3423
1Cust236.tntl5.at2.da.uu.net/153.36.94.236
3 3 6 94 23 6
3424
. . . 6
1Cust236.tnt15.atl2.da.uu.net/15
3425
1Cust236.tntl5.at2.da.uu.net/153.36.94.23
3
3
3426
.146
gra-il0-15.ix.netcan.can/207.220.13
3427
15.san-jose-03.ca.dial-access.att.net/12.
3 4.105.15
3
3428
3.14
gra-mil0-15.ix.netcan.can/207.220.1
8
3429
kr-205-38.gou.edu/129.1.205.3
3
3430
gra-milO-15.ix.netcan.om/207.220.133.14
3431
pgp-208-15-147-241.tulook.swbell.net/208.15.147.241
3432
bvi7-245.d2ialup.acossus.net/207.206.141.245
3433
sfdn9-054.sf.acapuserve.cam/206.175.228.54 4
3434
sfdn9-054.sf. carpsrve.cnV206.175.228.5
3435
sfdn9-054.sf.corpuerve.canm/206.175.228.54
3436
sfdn9-054.sf.carpuserve.cao/206.175.228.54
3437
199.106.87.109/199.106.87.109
3438
199.106.87.109/199.106.87.109
3439
portal4-ppp-005.ingina.canV206.163.82.104
9 29 2 2
3440
.1 . 5
169-129-252.ipt.ol.on/v152.16
3441
199.106.87.109/199.106.87.109
3442
199.106.87.109/199.106.87.109
9 8
7
3443
6
1r908-n6.pgp.tErple.edu/155.24
2 2 9. 8 6
24 7 .22
3444
.
.
lr908-r6.ppp.terple.edu/155.
3445
1Cust223.tnt1.indio.ca.da.uu.net/153.34.180.223
3446
ip83.vanll.pacifier.can/206.163.57.83
3447
cvip-nod3-psp30.csufresno.edu/129.8.212.150
3448
137.132.189.176/137.132.189.176
3449
137.132.189.176/137.132.189.176
3450
137.132.189.176/137.132.189.176
7
3451
.110
d45-tsO5.anug.org/198.182.12
3452
sclOO.softnet.se/192.176.122.100
3453
sclOO.softnet.se/192.176.122.100
3454
sc100.softnet.se/192.176.122.100
3455
sclOO.softnet.se/192.176.122.100
3456
sclOO.softnet.se/192.176.122.100
3457
pg05.mic.ul.ie/136.201.110.183
83
36 2
3458
pg05.mic.ul.ie/1 . 01.110.1
3459
pg05.mic.ul.ie/136.201.110.183
83
3460
pg05.mic.ul.ie/136.201.110.1
83
3461
pgO5.mic.ul.ie/136.201.110.1
3462
pg05.mic.ul.ie/136.201.110.183
3463
194.18.60.179/194.18.60.179
3464
194.18.60.179/194.18.60.179
3465
209.21.199.3/209.21.199.3
3466
pn24-3.inage.dk/194.234.169.195
128
date
time
score
duration
baddies
hits
shots
ip address of player
id#
980505
980505
980505
9:23:44 AM
10:01:52 AM
10:08:13AM
8100
0
1200
308
20
95
17
0
2
170
8
19
399
13
120
pn24-3.inage.dk/194.234.169.195
dlls-94ppp65.epix.net/199.224.94.65
dynamic1.poD2.pleasanton.best.m/204.156.131.65
3467
3468
3469
980505
10:20:49AM
0
72
0
2
3
209.45.210.189/209.45.210.189
3470
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
10:26:20AM
10:27:37AM
10:35:20AM
10:37:35
AM
AM
10:48:10
AM
11:02:59
11:22:02
AM
11:29:16
AM
AM
11:31:47
11:42:54
AM
11:43:16
AM
AM
11:49:02
11:54:05
AM
11:54:43
AM
AM
11:57:55
12:04:39
2M
12:21:4224
12:42:372M
12:44:412M
12:44:44FM
12:55:142M
1:10:23EM
1:13:40
1:23:12 4
2:16:12 24
2:49:0724
2:54:16 4
2:57:02
3:24:45
3:27:59
3:29:032M
3:31:4024
3:47:232M
3:55:3524
4:04:5724
4:07:242M
4:07:332M
4:08:402M
4:10:14 2M
4:13:532M
4:19:222M
4:20:322M
4:25:44 4
4:25:4524
4:29:5524
4:38:21R4
4:41:4524
4:44:1824
4:49:45
4:49:57
4:52:25
4:52:54
4:53:572M
4:57:092M
5:00:582M
5:04:142M
5:06:412M
5:06:462M
5:11:202M
5:24:10
5:29:01
5:31:3724
5:33:5624
5:39:4624
5:40:2524
5:46:0124
5:46:16 4
5:54:5224
6:10:1824
6:11:2324
6:13:4024
6:16:0224
6:17:46
6:19:16 2M
6:20:042M
6:20:452M
6:27:012M
6:32:442M
6:38:2524
6:56:252M
7:05:332M
7:05:592M
7:16:142M
7:18:2524
7:22:4424
7:23:462M
7:25:422M
7:28:1424
7:29:532M
7:31:45PM
7:32:462M
7:34:37
7:34:58
7:38:05
7:43:34
7:53:5724
8:05:112M
8:09:282M
8:11:10
8:12:422M
0
0
400
5600
0
0
4250
4350
7950
7100
2650
8000
3000
5450
1700
0
0
2500
6150
4100
3650
2850
3550
0
0
2300
1450
3300
4150
6300
1750
5600
4900
10600
5050
3800
0
1750
2200
7650
250
11400
0
2350
2300
600
4250
3450
7850
9100
6650
25050
3850
7250
5150
7450
5000
4250
4700
6100
22050
10950
1400
7850
4750
6850
0
8000
1600
1200
3700
3750
1850
850
1050
2900
3150
3800
14750
50
2300
600
850
1350
4700
7400
7500
4600
2500
3850
1650
6300
5750
1800
100
5050
10450
2650
2300
3100
21
47
64
111
126
3
253
112
136
235
2710
253
507
326
214
61
20
68
268
104
140
418
113
38
119
198
114
151
156
179
48
141
239
473
288
130
1
101
85
373
101
311
74
517
232
76
349
132
257
341
146
858
76
173
468
210
106
137
259
363
1662
429
103
207
372
316
4
304
112
48
123
123
87
85
32
166
139
232
416
189
189
141
193
123
158
301
212
136
83
95
94
157
116
95
75
402
621
219
87
76
0
0
0
14
0
0
10
9
15
13
5
15
5
12
6
0
0
6
12
8
10
8
8
0
0
6
3
11
11
15
7
9
11
27
10
8
0
5
6
16
0
26
0
5
5
2
7
8
16
21
14
94
6
15
13
15
11
10
9
22
81
37
5
16
18
25
0
20
5
4
9
8
3
3
4
6
5
7
42
0
5
1
3
5
9
29
23
9
4
7
3
10
13
3
0
14
22
5
9
12
0
0
8
111
0
0
57
51
130
148
29
230
30
177
88
0
17
39
131
66
75
82
78
0
0
85
26
108
98
145
69
99
71
252
66
48
0
94
42
147
9
205
0
45
28
41
71
47
135
168
106
525
51
122
74
174
82
110
102
180
462
252
79
159
163
199
3
148
60
51
50
46
19
46
58
34
33
46
416
3
56
11
58
78
112
170
183
56
26
41
43
110
131
18
3
104
344
32
92
79
2
29
32
589
1
0
196
104
213
555
68
933
165
606
150
0
31
87
360
427
197
310
269
0
3
271
178
479
404
668
229
348
487
1159
185
137
0
164
258
377
29
744
53
324
464
122
293
155
286
490
189
3998
74
184
1219
530
147
524
274
946
6294
1219
237
780
2150
3116
7
874
91
90
199
132
162
92
87
301
314
288
2250
18
114
30
287
211
388
721
723
268
117
139
78
290
301
38
19
264
705
230
225
218
st227.d50.tazeell.k2.IL.US/207.63.38.22
7
st227.d50.tazewell.k12.IL.UL/207.63.38.22
ul407-kiv-pcl4.zcu.cz/147.228.63.163
ul407-kiv-pcl4.zcu.cz/147.228.63.163
pO3-1-177.htg.net/209.136.26.177
pg06.nic.ul.ie/136.201.110.184
dhcp-204.millernertin.cam/209.42.142.204
206.30.9.172/206.30.9.172
206.30.9.172/206.30.9.172
modrcable66.98.ntimi.vidotron.net/207.253.98.66
gateway.bookpges.co.uk/194.217.205.17
6
7
.253.98.6
nderable066.98.ntimi.vidotron.net/20
gateway.bookpages.on.uk/194.217.205.17
nodenbleO066.98.ntii.videotron.net/207.253.98.66
204.133.199.140/204.133.199.140
spc-isppe--uas-01-19.sprint.ca/209.103.30.20
tvavp23.televar.ocan/208.8.147.246
8
0
nmil.unie.cz/195.70.129.1
52.new-orleans-01.1a.dial-acces.att.net/12.65.208.52
nail.uniie.cz/195.70.129.180
crcssdl.tac.net/205.233.109.99
7
st227.d50.tazewell.kl2.il.us/207.63.38.22
nail.unie.cz/195.70.129.180
jt.netgroup.dk/195.41.198.105
7
st227.d50.tazewell.kl2.il.us/207.63.38.22
205.152.23.2/205.152.23.2
166-149-198.ipt.ol.canVl52.166.149.198
166-149-198.ipt.aol.cnV152.166.149.198
7
7
2.2.10
grxa6-ppl70.triton.net/209.1
grxa6-pppl70.triton.net/209.172.2.170
grxa6-pppl70.triton.net/209.172.2.170
grxa6-ppp170.triton.net/209.172.2.170
207.73.99.254/207.73.99.254
207.73.99.254/207.73.99.254
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
GLOM:Information Agglomerates
7
3471
3472
3473
3474
3475
3476
3477
3478
3479
3480
3481
3482
3483
3484
3485
3486
3487
3488
3489
3490
3491
3492
3493
3494
3495
3496
3497
3498
3499
3500
3501
3502
3503
3504
3505
3506
3507
3508
3509
3510
3511
3512
3513
3514
3515
3516
3517
3518
3519
3520
3521
3522
3523
3524
3525
3526
3527
3528
3529
3530
3531
3532
3533
3534
3535
3536
3537
3538
3539
3540
3541
3542
3543
3544
3545
3546
3547
3548
3549
3550
3551
3552
3553
3554
3555
3556
3557
3558
3559
3560
3561
3562
3563
3564
3565
3566
3567
3568
3569
3570
s3.pr2.cybrtom.can/208.19.155.61
s3.pn2.cybrtomn.can/208.19.155.61
adn-cust26.advdata.net/209.57.91.48
lkc-ts2-ip-07.atlantic.net/209.26.53.71
lkc-ts2-ip-07.atlantic.net/209.26.53.71
s3.pn2.cybrtomc.cn208.19.155.61
207.96.224.212/207.96.224.212
cpc204.axion.net/209.17.191.204
7
7
.11
117.detroit-07.nmi.dial-access.att.net/12.67.21
7
9
nyc-ny7O-51.ix.netcno.can/209.109.226.1
7
117.detoit-07.mi.dial-access.att.net/12.67.217.11
slip166-72-162-201.ne.us.ihn.net/166.72.162.201
198.30.208.139/198.30.208.139
198.30.208.139/198.30.208.139
hagll.infoo-m.ccr/208.196.32.113
4
7
5
.226.201.1
pop645.pdn.net/20
hagll.infoon.can/208.196.32.113
66 7
6
slip1 - 2-12-201.ne.usi.ih.net/166.72.162.201
hagll.infocon.ccn208.196.32.113
hagll.infoco.cna/208.196.32.113
slip166-72-162-201.ne.us.ihn.net/166.72.162.201
nedmncbleO66.98.ntimd.videotrm.net/207.253.98.66
hagll.infocan.coa/208.196.32.113
nodeanble066.98.ntid.videotron.net/207.253.98.66
nodacable066.98.ntimi.vidotron.net/207.253.98.66
booden.bio.psu.edu/128.118.180.192
slipl66-72-162-201.ne.us.ihn.net/166.72.162.201
benden.bio.psu.edu/128.118.180.192
benden.bio.psu.edu/128.118.180.192
nodemable066.98.ntini.videotron.net/207.253.98.66
benden.bio.pu.ediu/128.118.180.192
8
8
92
benden.bio.pu.edu/128.11 .1 0.1
benden.bio.pou.edu/128.118.180.192
20 5 2 38 24 4 23
. .7 . 0
ntrs-244mpp230.epix.net/
nodem1-19.no-net.can/206.242.114.
79
9
nedenl-19.no-net.o-on/206.242.114.
nodemi-19.o-net.oon/206.242.114.79
noendl-19.o-net.can/206.242.114.79
7
9
nodEnt-19.on-net.omn/206.242.114.
209.67.72.110/209.67.72.110
209.67.72.110/209.67.72.110
4 7
.
onden1-19.on-net.can/206.242.11 79
nedenl-19.o-net.ocan206.242.114. 9
198.76.242.183/198.76.242.183
175-147-1.ipt.ol.can/152.175.147.1
user-2113.fiber.net/204.250.13.113
dhack4-065.cybex.net/207.198.208.65
dreadnought.ce.nu.edu/134.114.64.90
slip129-37-92-130.i.u.ihn.net/129.37.92.130
slip129-37-92-130.n.us.ihn.net/129.37.92.130
rbedcpl.spl.org/209.63.97.197
slip129-37-92-130.mi.us.ihn.net/129.37.92.130
rbedhcpl.spl.org/209.63.97.197
rbedhcpl.spl.org/209.63.97.197
rbedhcpl.spl.org/209.63.97.197
7
7
.19
rbedhcpl.spl.org/209.63.9
7
.195
gv1237195.columbus.rr.cxxn/204.210.23
rbedhcpl.spl.org/209.63.97.197
gv1237195.columbus.rr.cn/'204.210.237.195
lCustllO.tnt22.tco2.da.uu.net/153.36.40.110
M1IwNl4-8.stlnet.can/209.96.5.8
lpazl04c.life.Arizona.E3J/150.135.70.245
7
0.245
lpazlO4c.life.Arizona.EDJ/150.135.
dabcc-03p88.NMSU.Fdiu/128.123.41.198
dabcc-03p88.SU.Flu/128.123.41.198
dabcc-03p88.NMSU.Eduti/128.123.41.198
129
date
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980505
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
980506
time
8:20:49 H4
8:42:04FM
8:43:14PM
8:47:251M
8:48:58PM
8:49:03PM
8:53:07R4
9:06:3624
9:09:42 8M
9:13:1024
9:14:55R4
9:19:082M
9:50:53PM
9:57:20 2M
10:02:46 9M
10:04:38 8M
10:07:11 R4
10:09:40 R4
10:18:14 24
10:28:55 R4
10:46:20 2M
10:54:45 EM
10:57:00R4
11:03:05EM
11:16:2024
11:21:01R4
11:24:4924
12:02:10AM
AM
12:03:34
0M
12:54:10
1:40:48 AM
1:43:55 AM
6:27:080M
6:59:06AM
8:49:080M
9:57:33AM
10:16:25
0M
10:52:11
094
11:03:00014
AM
11:04:14
11:05:530M
11:36:540M
11:38:170M
11:42:260M
11:47:140M
11:51:130M
11:53:45084
11:53:51
A14
11:57:00084
11:58:460M
R4
12:31:21
12:36:4724
12:44:412M
PM
12:50:45
1:57:022M
2:34:11PM
2:37:442M
3:15:421M
4:09:282M
4:32:5024
4:36:292M
4:40:1024
4:43:2724
4:46:47
4:49:55PM
4:54:392M
5:09:252M
5:21:212M
5:32:3824
5:38:552M
5:43:512M
5:48:4724
5:55:022M
6:09:0124
6:19:262M
6:20:42
6:42:31
6:48:240M
6:58:42
7±02:03 4
7:04:59
7:17:01 4
7:17:102M
7:18:09R4
7:18:5924
7:21:362M
7:24:00EM
7:31:01PM
7:34:4824
7:35:412M
7:37:42
7:41:3024
7:45:16
8:04:2724
8:06:2524
8:08:012M
8:09:472M
8:13:4724
8:16:34FM
9:22:222M
9:24:402M
9:37:33
10:28:0724
10:36:3924
M
M
M
M
M
M
M
M
score
29100
2450
3150
50
1850
8500
4500
3750
9750
6900
2150
9150
8100
13550
0
18700
4650
5900
3500
11350
4150
3400
3250
1450
4700
8250
1900
250
3850
3500
0
2850
6850
6550
0
1900
10750
0
0
100
300
500
500
8500
2200
4150
0
1500
4150
0
6200
10900
15650
6000
0
0
1300
1800
0
7900
10450
8600
8600
9350
9850
7000
3400
3000
3850
9500
9050
8300
8700
4450
5250
3100
5300
8800
11350
1450
4350
3400
11550
600
3700
8750
800
29800
0
500
3150
5450
1700
3700
2950
1450
3600
3850
2400
8350
4000
0
200
4700
duration
910
359
220
137
85
324
184
56
170
337
277
254
264
370
54
423
127
122
150
226
126
129
120
69
145
264
205
246
174
114
55
171
196
577
112
117
379
13
155
59
75
207
64
231
271
219
217
101
330
48
363
366
780
301
77
118
93
181
69
226
203
196
185
180
175
160
97
258
184
360
281
279
261
177
268
180
325
373
300
102
156
104
376
43
104
191
253
554
75
44
87
442
210
144
76
69
87
72
112
285
125
2
418
245
GLOM:Information Agglomerates
baddias
50
4
5
0
7
18
9
6
17
21
4
18
18
24
0
32
10
11
8
21
8
8
5
2
9
22
5
0
8
6
0
4
13
12
0
4
27
0
0
0
1
2
2
34
4
11
0
4
10
0
19
28
31
14
0
0
2
3
0
16
17
19
16
17
21
12
6
11
9
22
18
16
15
9
12
6
11
17
20
3
9
8
21
1
6
19
2
52
0
2
6
21
5
9
6
3
6
7
4
18
8
0
0
13
hits
778
31
47
1
94
152
118
51
297
136
48
192
145
361
0
353
64
181
47
228
65
63
35
18
66
165
97
5
52
41
0
33
125
168
0
58
214
0
5
2
6
39
42
221
78
93
33
58
113
2
156
249
525
123
0
0
14
18
0
131
198
172
171
280
239
142
48
114
60
172
178
163
208
55
69
42
146
244
280
18
52
82
285
10
73
155
18
779
0
31
54
146
89
50
35
17
36
41
49
249
86
0
9
138
shots
1672
332
252
29
262
508
665
93
387
1139
289
676
253
707
7
795
273
256
146
412
241
176
177
65
255
639
237
56
224
103
25
154
291
422
3
240
600
0
19
18
16
148
116
534
471
332
56
119
442
18
718
836
1648
492
2
1
107
57
0
266
480
371
350
383
489
297
317
383
193
502
407
411
391
202
441
89
312
794
606
215
516
184
689
25
349
360
51
2556
1
86
163
581
322
143
93
46
83
74
110
987
400
0
25
672
ip address of player
3571
lpazl04c.life.Arizona.EIJ/150.135.70.245
3572
ad113-202.nngix.can.sg/165.21.113.202
3573
o.can/208.19.155.46
s36.pnl.cybrt
26
9 22 7
3574
. 7 .148.1
tsftll-126.gate.net/19
48
3575
.1 .126
tsftll-126.gate.net/199.22
3576
s36.pn1. cybrtown.can/208.19.155.46
8 26
7
3577
.14.1
tsftll-126.gate.net/199.22
3578
pp300.rtp.intrex.net/209.42.198.45
4
3579
5
pp300.rtp.intrex.net/209.42.198.
7
3580
4
tsOO3dl4.ind-in.concentric.net/206.173.97.
3581
tc2-20.utah-inter.net/208.14.200.150
3582
ts50ip36.cadvisicn.mcn207.228.73.36
3583
pool048-mn2.ds13-ca--us.dialup.earthlink.net/209.178.15.248
3584
pool048-nux2.ds13-ca-us.dialup.earthlink.net/209.178.15.248
3585
bds-ptblic.ib.ci.phoenix.az.us/207.246.36.153
3586
pool048-nsx2.ds13-ca-us.dialup.earthlink.net/209.178.15.248
78
24 8
2 9
3587
poo048-nnx2.ds13-ca-us.dialup.earthlink.net/ 0 .1 78 .15. 24 8
3588
pool048-rnw2.ds13--c-us.dialup.earthlink.net/209.1 .15.
3589
74.cleveland-06.oh.dial-access.att.net/12.67.197.74
3590
pool048-nex2.ds13-ca-us.dialup.earthlink.net/209.178.15.248
7
3591
ppp067-hnvrpa.netrax.net/208.192.148.6
6
3592
user95.netcarrier.<orn198.136.22
6 26 .95
1
3593
.2
.95
98.13
user95.netcarrier.cnm
3594
EIJ/18.223.0.26
BALIRICK.MIT.
3595
lCust88.tntl.beaverton.or.da.uu.net/153.35.201.88
88
3596
1Cust88.tntl.beaverton.or.da.uu.net/153.35.201.
8
3597
1Cust88.tntl.beaverton.or.da.uu.net/153.35.201.8
3598
206.48.60.116/206.48.60.116
3599
se-pub23.library.Arizona.KJ/128.196.102.123
3600
ppp018.n±ax4.las-vegas.rv.skylink.net/207.49.176.18
3601
EVAIGER.hayboonet.can/165.97.13.64
3602
EVAIGER.hayboet.can/165.97.13.64
7
3603
paris4-2.isdnet.net/194.149.1 5.129
3604
scc41959.dscc.dla.mnil/131.74.195.9
3605
su5-3.ida.liu.se/130.236.186.74
3606
so22.boh.busd.k12.co.us/161.97.203.22
3607
209.66.196.254/209.66.196.254
3608
TJBohan.unenfa.nnine.edu/130.111.116.59
3 7 99
3609
.1 .5
lcust5.tnt2.reoond.wa.da.uu.net/153.
3610
1cust5.tnt2.rehoind.va.da.uu.net/153.37.199.5
3 7 99
3611
.1 .5
1Cust5.tnt2.recodnd.a.da.uu.net/153.
3612
168.37.224.65/168.37.224.65
3613
168.37.224.65/168.37.224.65
3614
168.37.224.65/168.37.224.65
3615
168.37.224.65/168.37.224.65
3616
168.37.224.65/168.37.224.65
9
3617
0
jasper.w1u.ca/192.219.240.
3618
204.234.75.181/204.234.75.181
3619
168.37.224.65/168.37.224.65
3620
205.234.22.160/205.234.22.160
3621
K9 M103-14.splitrock.net/209.156.154.60
3622
client-125-14.bellatlantic.net/151.198.125.14
6
6
3623
0
.154.
K9cyB103-14.splitrock.net/209.15
3624
KScyB103-14.splitrock.net/209.156.154.60
3625
2cust6O.tntl.phx1.da.uu.net/153.34.27.60
3626
209.76.80.243/209.76.80.243
3627
204.49.240.51/204.49.240.51
8
3628
.24
rncl4.ia.utexas.elu/128.83.8
3629
198.30.208.99/198.30.208.99
3630
hag2.infocn.ccm/208.196.32.104
3631
hag2.infoccm.canr/208.196.32.104
3632
hag2.infocan.ccm/208.196.32.104
3633
hag2.infoccu.ccW/208.196.32.104
3634
hag2.infocan.can/208.196.32.104
3635
hag2.infocca. ccrL/208.196.32.104
3636
hag2.infocan.ccW/208.196.32.104
3637
nedncableO066.98.iimi.videotran.net/207.253.98.66
3638
B02.reach.net/204.50.58.97
9
3639
dt043ndc.nnine=.rr.ccV204.210. 1.220
3640
dt043ndc.nine. rr. cc/204.210.91.220
3641
dt043ndc.naine.rr.caV204.210.91.220
3642
dt043ndc.rnaine.rr.ccm/V204.210.91.220
9 22
3643
1. 0
dt043ndc.nnjine.rr.canV204.210.
3644
199.106.87.155/199.106.87.155
23
3645
1Cot123.tnt3.seal.da.uu.net/208.253.65.1
3646
165.97.13.100/165.97.13.100
3647
207.194.178.141/207.194.178.141
38
66
8
8
3648
166-1 5-13 . ipt.ol.can/152.1 .185.1
3649
166-185-138.ipt.aol.can/±152.166.185.138
3650
spc-isp-no-uas-01-27.sprint.ca/209.103.24.28
3651
spc-isp-non-uao-01-27.sprint.ca/209.103.24.28
3652
g-1nsl-40.c2i2.can/207.98.161.105
3653
pool012-nox4.ds19-ca-us.dialup.earthlink.net/209.179.14.12
79 4 2
3654
.1 .1
pool012-nx4.ds19-ca-us.dialup.earthlink.net/209.1
3655
agns1-40.c2i2.can/207.98.161.105
4
7
3656
9.1 .12
pool012-nex4.ds19-ca-us.dialup.earthlink.net/209.1
3657
207.10.168.52/207.10.168.52
2 9 79 4 2
3658
pool12-onx4.ds19-ca-u.dialup.earthlink.onet/ 0 .1 .1 .1
3659
pn14-15.nidlink.canV206.96.75.56
3660
pn14-15.nidlink.can/206.96.75.56
3661
pn14-15.nidlink.on/V206.96.75.56
3662
ls.can/207.172.191.86
207-172-191-86.s22.al.nkt.o
86
3663
207-172-191-86.s22.as1.mkt.erols.can/207.172.191.
3664
12.6.167.177/12.6.167.177
3665
12.6.167.177/12.6.167.177
3666
12.6.167.177/12.6.167.177
3667
12.6.167.177/12.6.167.177
3668
12.6.167.177/12.6.167.177
6 7 69 22
3669
4
. 98
. 66
224.denver-02.co.dial-access.att.net/12.
3670
.
nodeucable066.98.ntimi.videotron.net/207.253.
3671
nodatrable66.98.timi.videotron.net/207.253.98.66
3672
net15-cust140.den.wantweb.net/24.236.15.140
3 37 6 9
3
3673
. . .25
.da.uu.net/15
1Cust25.tnt6.lax
3674
204.222.143.156/204.222.143.156
130
data
980506
980506
980506
980506
980506
980506
980506
980506
980506
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
time
10:37:53 0M
10:39:192M
10:43:17
10:43:53PM
10:48:262M
10:57:052M
10:59:442M
11:02:012M
11:09:362M
2:10:36AM
2:12:35AM
6:41:21AM
8:22:26AM
11:36:34A24
11:36:35AM
11:36:36AM
11:36:37AM
11:36:37
11:36:38AM
11:36:39AM
11:36:39AM
11:36:40AM
11:36:41AM
11:36:42AM
11:36:42AM
AM
11:36:43
11:36:44
AM
AM
11:50:40
AM
11:50:41
AM
11:50:42
2M
12:20:12
EM
12:23:09
12:38:042M
FM
12:39:15
12:41:10
12:49:44
R4
R4
12:54:52
12:56:0224
1:03:172M
1:23:542M
1:39:2624
1:46:46PM
1:50:33EM
1:53:16PM
1:58:39PM
2:08:46EM
2:10:462M
2:10:472M
2:34:082M
2:36:26PM
2:42:18PM
3:16:26PM
3:19:42PM
3:22:06
3:39:042M
3:45:02R4
3:58:0524
4:05:572M
4:18:442M
4:20:0824
4:20:092M
5:13:02R4
5:14:3524
5:24:2124
5:43:37
5:54:55PM
5:55:54FM
6:01:26
6:01:28R4
6:01:3324
6:06:36R4
6:09:58PM
6:10:132M
6:13:082M
6:15:322M
6:16:26PM
6:17:09
6:19:14
6:20:2124
6:21:4024
6:25:01R4
6:26:33 4
6:33:592M
6:37:492M
6:42:592M
6:47:142M
6:47:382M
6:50:26R4
6:52:0924
7:00:02PM
7:10:402M
7:12:552M
7:16:17
7:22:534
7:29:2124
7:31:592M
7:54:48
8:00:2024
8:02:36R4
8:14:472M
8:16:51EM
8:19:59FM
8:22:02R4
8:22:03
M
M
M
M
M
M
M
M
M
M
M
score
duration
baddies
hits
shots
ip address of player
id#
2350
2950
0
5800
6200
1200
350
1650
1150
3350
2900
2400
1800
0
10300
4550
2800
0
4350
6250
900
600
6250
8300
0
11950
50
4300
3600
8800
4250
4650
100
0
50
1050
3050
50
0
850
4500
10100
10500
2000
7500
16100
4050
1050
2950
4450
1200
6250
4500
4100
0
1600
0
1300
0
3250
350
4100
0
3550
10650
23100
5100
0
9900
8700
600
4700
11500
4900
2900
3700
1750
2750
1350
950
6450
2600
1850
5350
4100
3000
3200
12600
8350
2650
3850
3550
0
3000
650
2250
250
3550
4050
0
2450
700
2750
6650
64
69
124
213
226
206
107
120
93
109
105
120
138
167
192
231
117
19
201
484
118
41
291
304
71
334
25
168
177
239
145
156
62
58
96
78
119
50
139
72
162
276
297
118
235
470
274
72
114
117
800
187
130
128
105
252
64
114
135
435
111
211
1
165
421
658
139
4
318
378
109
184
277
175
179
183
82
107
50
62
185
75
97
199
112
98
303
403
198
290
156
119
95
78
46
131
56
217
547
36
107
219
108
297
5
9
0
13
15
2
0
5
3
5
6
4
4
0
23
18
8
0
14
18
1
1
18
26
0
31
0
10
6
18
11
13
0
0
0
4
5
0
0
3
11
25
18
6
21
31
9
3
6
9
2
14
8
12
0
3
0
1
0
13
0
8
0
5
25
55
13
0
22
26
2
9
27
11
9
7
7
11
5
3
11
4
4
13
8
5
7
35
16
5
6
7
0
6
2
4
1
7
11
0
4
2
11
14
85
125
0
118
122
15
7
101
75
41
34
25
85
3
225
153
82
0
143
106
13
6
129
204
0
269
1
91
44
209
98
86
7
4
5
38
36
1
2
44
64
239
272
109
223
416
91
57
35
54
12
111
56
91
3
29
0
20
2
133
7
58
0
92
328
689
140
0
188
241
15
77
279
88
117
46
73
72
61
70
109
28
25
95
64
50
66
337
161
68
42
41
10
46
31
34
22
41
115
37
27
82
108
123
162
362
4
777
533
52
68
581
137
154
159
79
110
11
416
540
248
1
519
711
57
7
1239
1955
20
1609
18
375
326
724
187
211
12
5
25
122
161
10
47
69
135
896
774
244
561
1227
178
104
76
179
54
300
385
316
66
92
1
108
20
2220
56
228
0
168
1302
2118
296
0
771
1411
54
279
717
285
481
370
328
565
203
134
529
239
151
430
119
116
357
1406
270
242
149
144
16
92
42
198
64
243
878
45
106
146
198
543
204.222.143.156/204.222.143.156
204.222.143.156/204.222.143.156
checkers-fddi.cray.o-no/137.38.235.5
204.222.143.156/204.222.143.156
ts7-16.frd.cyberidghoy.net/209.161.34.180
30ast134.tntl.phxl.da.uu.net/153.34.215.134
34
3 34 2
. . 15.1
3Cust134.tntl.phxl.da.uu.net/15
3Cut134.tnt1.phx1.da.uu.net/153.34.215.134
7
2
ck47-172.doub.ccpuserve.cun/199.174.179.1
193.14.53.10/193.14.53.10
193.14.53.10/193.14.53.10
dhcp-892195149.qualcmn.cun/129.46.238.194
ws103.ini.cz/195.212.195.103
198.234.86.182/198.234.86.182
207.157.48.194/207.157.48.194
168.221.114.154/168.221.114.154
169.244.152.67/169.244.152.67
7
.142.136.102
bodine.cobite.com/20
168.221.114.154/168.221.114.154
cx11539-a.cv1.adca.hron.cn/24.0.137.107
vikings.tte.lv/159.148.220.11
206.30.9.204/206.30.9.204
152.111.35.141/152.111.35.141
152.111.35.141/152.111.35.141
white2.nada.kth.se/130.237.226.124
152.111.35.141/152.111.35.141
42
9 3 44
. .l60.
dhcp12.dacapo.se/1
207.232.193.154/207.232.193.154
6
gorgon.cs.tu-berlin.de/130.149.31.10
207.232.193.154/207.232.193.154
159.164.201.74/159.164.201.74
159.164.201.74/159.164.201.74
208.224.45.50/208.224.45.50
208.224.45.50/208.224.45.50
208.224.45.50/208.224.45.50
9
6
5.l1
spk2-13.ipeg.conV206.96.
169.244.152.67/169.244.152.67
4
9 48
.24 . .18
franklinl8.franklin.cc±/20
calzone.stardiv.de/62.156.160.60
208.198.210.126/208.198.210.126
will-25s.citynet.net/207.0.254.85
208.144.248.13/208.144.248.13
205.152.23.2/205.152.23.2
205.152.23.2/205.152.23.2
205.152.23.2/205.152.23.2
205.152.23.2/205.152.23.2
3
7
.19.1.185
205.152.23.2/205.152.23.2
ts1-16.she.cyberhighwy.net/209.161.50.22
ts1-16.she.cyberhighway.net/209.161.50.22
unknown-35-6.nuhse.cc/206.189.35.6
198.163.125.224/198.163.125.224
198.163.125.223/198.163.125.223
198.163.125.223/198.163.125.223
207.203.196.86/207.203.196.86
166.34.97.123/166.34.97.123
nrjava.miedia.nit.edu/18.85.1.12
3675
3676
3677
3678
3679
3680
3681
3682
3683
3684
3685
3686
3687
3688
3689
3690
3691
3692
3693
3694
3695
3696
3697
3698
3699
3700
3701
3702
3703
3704
3705
3706
3707
3708
3709
3710
3711
3712
3713
3714
3715
3716
3717
3718
3719
3720
3721
3722
3723
3724
3725
3726
3727
3728
3729
3730
3731
3732
3733
3734
3735
3736
3737
3738
3739
3740
3741
3742
3743
3744
3745
3746
3747
3748
3749
3750
3751
3752
3753
3754
3755
3756
3757
3758
3759
3760
3761
3762
3763
3764
3765
3766
3767
3768
3769
3770
3771
3772
3773
3774
3775
3776
3777
3778
GLOM:Information Agglomerates
ppp-207-193-1-185.kscyno.swbell.net/20
pp114.uio.no/129.240.240.119
205.213.93.2/205.213.93.2
9
49.new-york-26.ny.dial-access.att.net/12.68.191.4
147.133.43.120/147.133.43.120
tcl-73.utah-inter.net/208.14.200.83
6
36
1.1
rc-136.netanecan.net/207.142.1
149.127.131.243/149.127.131.243
ntrs-244ppp219.epix.net/205.238.244.219
24 4 2 9
2
23
05. 8. . 1
ntrs-244ppp219.epix.net/
jtrobinon.ne.medione.net/24.128.64.245
199.79.138.175/199.79.138.175 24
jtrobinono.ne.nedione.net/24.128.64.
2 38 2 4 2 9 5
.4 .1
ntrs-244ppp2l9.epix.net/205.
ocal-pn3-19.mfi.net/205.161.238.96
6 2 38 96
.
ocal-pn3-19.afi.net/205.1 1.
jtrobinson.ne.mediaone.net/24.128.64.245
ol-pn3-19.mfi.net/205.161.238.96
33
4
6 42
.2 .11 .1
nedn7-73.no-net.canV20
sol-gn3-19.mfi.net/205.161.238.96
n±den7-73.no-net.cam/206.242.114.13333
noden7-73.no-net.om/206.242.114.1
nmden7-73.ro-net.can/206.242.114.133
neden7-73.no-net.can/206.242.114.133
4 33
.1
noden7-73.no-net.canV206.242.11
neden7-73.no-net.can/206.242.114.133
208.204.46.20/208.204.46.20
208.204.46.20/208.204.46.20
ca-lde.unnu.umich.edu/141.213.34.105
calder.unnu.umich.edu/141.213.34.105
206.14.7.105/206.14.7.105
2
44 21 1
.
171-144-211.ipt.aol.cnVl5
2 .171.1
3 34
4
.um±ich.ed/1 1. 1 . .105
calder.u
.umi±ch.edu/141.213.34.105
calder.u
pc612.shor.kcls.org/198.104.21.22
22
4 2
9
8.10 . 1.
pc612.shor.kc1s.org/1
ppp78.wingsisp.can207.142.108.7867 6
. 8.10
10.denver-01.co.dial-access.att.net/12.
slip166-72-219-153.ny.us.ihn.net/166.72.219.153
slip166-72-219-153.ry.us.ihn.net/166.72.219.153
gv1237195.colunb.r.can/204.210.237.195
dabc-03p88.NKsU.Fldu/128.123.41.198
7
166-156-227.ipt.aol.can/12.166.156.22
atl-ga57-34.ix.netcan.amn/207.223.188.98
98
7 2 23
. .188.
atl-ga57-34.ix.netcan.can/20
rvl-ndl-01.ix.netcan.can/V205.187.208.33
rvl-nd1-01.ix.netcan.caV205.187.208.33
88 98
7
.223.1 .
atl-ga57-34.ix.netcan.can/20
131
date
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980507
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
time
8:24:14 2M
8:24:16 0M
8:26:07 FM
8:26:230M
8:26:450M
8:27:390M
8:29:240M
8:41:240M
8:42:310M
9:03:300M
9:05:522M
9:07:310M
9:13:128M
9:33:43R4
9:36:05EM
9:46:33EM
9:50:13EM
9:51:430M
9:52:280M
10:21:0504
10:34:07EM
11:03:558M
11:59:128M
12:32:570M
8:43:54A14
8:43:55AM
8:43:56A14
8:43:57A14
8:44:38AM
9:41:53AM
9:59:37 AM
10:04:55AM
10:06:00AM
10:06:28AM
AM
10:10:16
8M
10:31:48
AM
10:39:01
10:43:21
A14
10:56:46
AM
10:58:11
AM
10:58:24
10:59:21 AM
10:59:35 AM
11:16:52 9M
11:17:35 AM
11:21:03 AM
AM
11:24:32
11:26:20 AM
AM
11:28:42
11:43:00
A14
11:49:36
11:53:04 A81
EM
12:34:26
EM
12:39:23
12:44:11 0M
12:47:05 PM
12:49:03 0M
1:01:23 P4
1:03:43PM
1:17:14 PM
1:23:4924
1:26:50PM
1:30:22 2M
1:35:17 R4
1:42:14
1:42:4524
1:47:562M
1:51:540M
1:53:020M
2:17:37
2:20:06
2:22:052M
2:35:532M
2:45:0524
2:46:1824
2:55:0524
2:55:062M
3:06:58 24
3:09:11 24
3:11:3024
3:17:352M
3:22:27 2M
3:34:11
3:48:5924
3:57:51
4:07:2124
4:26:0224
4:43:14
4:48:27PM
4:54:51 2M
5:01:05 2M
5:01:5524
5:14:29 PM
5:15:23R4
5:17:44 24
5:18:33 2M
5:19:08 054
5:20:11 0M
5:21:48
5:22:58
5:23:15
5:25:2324
5:27:2524
5:30:40
M
M
M
M
M
M
M
M
M
M
M
M
score
3600
1200
1700
3500
4750
0
6950
8400
0
2400
13300
2500
9350
4250
650
3250
4450
8700
5650
1000
8900
2500
2500
6850
3300
0
2500
500
8650
10250
650
4400
5200
2150
8000
10050
5850
5050
950
2650
0
1250
0
0
5200
8150
8600
2100
5050
0
4200
0
6350
1700
3400
2050
4700
15950
8700
450
6200
9250
3050
8450
0
50
3900
2650
0
750
5350
7350
3600
650
7750
19400
7550
2650
49650
1800
8150
6000
0
1800
100
13500
2650
3900
1300
2700
5050
250
3950
5700
2900
9850
2100
3550
1200
1100
3650
4350
5150
5400
duration
111
120
87
128
136
44
141
141
93
346
473
84
324
465
130
113
126
293
119
138
697
134
140
338
234
4
94
20
77
207
95
310
135
73
377
403
277
210
61
94
4
41
4
21
167
191
193
92
123
83
381
118
359
126
271
67
103
590
391
366
2059
165
145
277
152
45
294
217
46
44
134
161
106
177
294
509
446
150
1433
225
480
270
8
493
93
372
127
200
47
296
341
141
253
325
121
407
263
132
78
88
155
101
106
144
GLOM:Information Agglomerates
haddies
hits
6
4
4
14
9
0
12
13
0
6
34
10
22
10
1
7
8
14
10
1
34
10
7
11
7
0
10
2
14
27
1
9
12
8
17
26
14
11
3
4
0
5
0
0
11
15
17
7
12
0
11
0
24
5
6
3
10
38
16
1
16
20
8
19
0
0
11
5
0
3
17
14
7
2
19
31
15
7
197
3
22
11
0
5
0
33
6
8
5
5
14
0
8
13
6
25
4
8
2
3
9
9
12
15
53
77
24
110
76
0
112
220
0
107
401
118
241
96
14
45
91
231
97
14
240
72
89
170
42
0
116
71
255
226
7
52
76
71
158
214
94
82
42
30
0
67
0
0
107
137
157
110
89
3
96
0
178
95
100
24
58
460
360
33
170
222
69
183
0
23
86
36
0
48
157
159
47
48
204
456
136
100
1038
20
152
103
0
73
3
498
88
50
68
54
103
5
65
208
37
211
24
48
12
52
51
81
86
242
shots
155
136
59
410
345
2
267
474
0
779
1384
449
1128
676
304
113
131
459
163
62
3950
155
232
294
556
5
295
106
600
709
30
309
244
136
488
1338
452
392
77
103
1
125
14
1
439
465
519
366
534
122
661
18
929
201
437
60
124
1429
790
1230
529
418
247
541
5
57
796
675
4
61
416
352
190
78
588
954
507
261
4006
228
622
403
0
156
11
1646
232
356
123
231
337
247
344
640
140
813
277
238
77
105
320
256
235
491
id#
ip address of player
3779
Extensio--131B.CSS.CPSr.EW/128.193.102.154
3780
rvl-ndl-01.ix.netcam.cmo/205.187.208.33
7
3
3781
rvl-nd1-0l.ix.netecm.ccmV205.18
2 .208.3
8 8
3782
mrjava.nedia.mit.edu/1 . 5.1.1
3
4
3783
.102.15
Extosion-131B.C0.CSr.EDU/128.19
3784
nrjava.media.nt.edu/18.85.1.12
3785
Extnsion-131B.CSS.CPSr.E[U/128.193.102.154
8
3786
1
1Custl8l.tnt3.nunassas.va.da.uu.net/208.252.85.1
3787
et7-15.qtm.net/206.53.233.107
8
3788
118.philadelphia-05.pa.dial-acess.att.net/12.68.111.11
7 2 3 98
3789
noderable066.98.ntimni.vidotron.net/20
6
7 . 53 . .66
3790
nudecable066.98.ntimi.vidotrn. net/20 .25 .98. 6
3791
nodenrableO66.98.ntimi.videotron.net/207.253.98.66
3792
sc6.vico.net/208.223.80.15
3793
sc6.vico.net/208.223.80.15
3794
ppp208.oscow.<xn/207.141.26.208
3795
12.6.167.172/12.6.167.172
3796
pp208.nscow.a-n/207.l41.26.208
3797
12.6.167.172/12.6.167.172
3798
12.4.248.230/12.4.248.230
3799
bobll.olywa.net/205.163.58.211
3800
van-bc8-08.netcm.ca/207.181.73.136
3801
205.152.23.2/205.152.23.2
3802
205.152.23.2/205.152.23.2
3803
207.125.48.234/207.125.48.234
3804
207.125.48.234/207.125.48.234
3805
207.125.48.234/207.125.48.234
3806
209.160.99.16/209.160.99.16
3807
209.160.99.16/209.160.99.16
3808
199.252.50.239/199.252.50.239
3809
dfbfl4-10.gate.net/199.227.117.10
3810
dfbfl4-10.gate.net/199.227.117.10
3811
jazz.evc.kl2.nf.ca/205.251.11.14
3812
dfbfl4-10.gate.net/199.227.117.10
3813
160.7.64.167/160.7.64.167
3814
rtv-40.nndera-01.nadnet.net/206.190.157.140
3815
dialup02O.intertek.net/209.83.158.264 3 47
3816
1oust147.tnt1.reoind2.wa.da. uu.net/208.250.2 .1
3817
st06.tetranetsoftware.ccn206.248.25.23
3818
209.1.11.34/209.1.11.34
3819
209.1.11.34/209.1.11.34
3820
209.1.11.34/209.1.11.34
3821
209.1.11.34/209.1.11.34
3822
93. freemarket. cc/206.210.69.93
3823
207.232.193.204/207.232.193.204
3824
207.232.193.204/207.232.193.204
3825
207.232.193.204/207.232.193.204
3826
207.232.193.204/207.232.193.204
3827
207.232.193.204/207.232.193.204
3828
168.37.224.71/168.37.224.71
3829
168.37.224.71/168.37.224.71
3830
209.49.193.129/209.49.193.129
7
3831
4.226.45
sco22645.dsecdla.mil/131.
3832
198.234.86.135/198.234.86.135
3833
198.234.86.135/198.234.86.135
3834
207.127.134.90/207.127.134.90
3835
207.127.134.90/207.127.134.90
3836
198.234.86.135/198.234.86.135
3837
198.234.86.189/198.234.86.189
3838
du66-6.pp.algonet./195.100.6.66
3839
207.248.185.80/207.248.185.80
3840
207.248.185.80/207.248.185.80
3841
166-232-172.ipt.aol.ca1c52.166.232.172
3842
166-232-172.ipt.ol.can/152.166.232.172
3843
140.189.127.43/140.189.127.43
3844
aphrodite-137.dialin.gremepa.net/206.205.118.137
7
3845
aphrodite-137.dialin.gremnepa.net/206.205.118.13
8 37
3846
.1
aphrodite-137.dialin.greenepa.net/206.205.11
3847
aphrodite-137.dialin.greenepa.net/206.205.118.137
6 97
3848
. 7
kipa3pp32.alltel.net/166.102.11
3849
kipa3rp32.alltel.net/166.102.116.9
0 83
3850
.1
pg05.mic.ul.ie/136.201.11
3851
pc248-037.ich.ucl.ac.uk/194.82.248.37 7
3852
host-209-214-2-97.mia.bellsouth.net/209.214.2.9
3853
205.152.23.2/205.152.23.2
3854
205.152.23.2/205.152.23.2
3855
tc2-117.utah-inter.net/208.14.200.247
3856
170.181.182.130/170.181.182.130
3857
host-209-214-2-97.mia.bellsouth.net/209.214.2.97
3858
h212.s245.ts.hinet.net/168.95.245.212
2 9 2 4 2 97
3859
0 . 14 .2 .97
host-209-214-2-97.mnia.bellsouth.net/
3860
. .
hxst-209-214-2-97.mia.bellsouth.net/209.21
7
3861
vocstu09.narissa40.org/205.216.223.1
70
3862
8
votul7.mrissa40.org/205.216.223.1
3863
sgva-23.ucsd.edu/132.239.126.229
3864
172-171-168.ipt.aol.can/152.172.171.168
3865
207.96.161.196/207.96.161.196
3866
204.216.87.202/204.216.87.202
7
3867
ip137.rutland2.vt.pib-ip.psi.net/38.26.145.13
4 78 2
3868
.78 .
host-209-214-78-2.atl-n.bellsouth.net/209.21
3869
.2
host-209-214-78-2.atl-n.bellouth.net/209.214.
3870
207.113.243.102/207.113.243.102
3871
host-209-214-78-2.atl-n.bellsouth.net/209.214.78.2
3872
vet-aff.cub.wu.edu/134.121.188.50
3873
207.203.171.29/207.203.171.29
3874
cx53227-a.elejnl.sdca.hlm.can/24.4.69.34
9 2 4 78 2
78
3875
host-209-214- -2.atl-n.bellouth.net/20 . 1 . .
3876
207.203.171.29/207.203.171.29
3877
207.203.171.29/207.203.171.29
3878
206.210.132.68/206.210.132.68
3879
pn3a26.bn.sover.net/206.25.65.216
6
6
3880
pn3a26.ben.sover.net/206.25. 5.21
3881
pn3a26.ben.sover.net/206.25.65.216
3882
206.232.107.94/206.232.107.94
132
date
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
time
5:32:2324
5:41:28EM
5:47:58EM
5:52:32PM
5:53:30EM
5:57:19PM
5:58:092M
5:59:232M
6:02:10PM
6:03:042M
6:06:14
6:07:07
6:39:40
7:04:46
7:06:41
7:09:47
7:12:052M
7:12:232M
7:12:3524
7:17:492M
7:19:24FM
7:30:19M
7:30:462M
7:32:4124
7:33:16FM
7:34:10 4
7:35:38
7:41:4424
7:44:3724
7:46:2124
7:52:422M
7:54:5824
8:06:3924
8:13:26
8:14:49
8:17:52
8:18:4524
8:21:49M
8:21:5124
8:23:1824
8:24:362M
8:25:312M
8:25:5624
8:27:5024
8:35:0824
8:35:172M
8:39:0524
8:46:2024
8:48:48
8:49:5124
8:50:4024
8:50:492M
8:50:59
8:52:122M
8:52:39
8:54:02
8:54:542M
8:56:10
8:56:362M
8:58:152M
9:00:242M
9:01:40
9:02:22R4
9:03:0324
9:05:1124
9:06:13
9:12:282M
9:13:02 4
9:16:1724
9:17:0424
9:17:4724
9:22:472M
9:28:12FM
9:28:2524
9:37:402M
9:40:242M
9:42:372M
9:50:48
9:52:56
9:55:3924
9:59:51
10:02:2324
10:03:08
10:04:54
10:04:5524
FM
10:08:14
10:08:18
FM
R4
10:08:41
10:09:29
24
2M
10:10:03
10:10:2224
10:11:462M
10:13:502M
10:14:3824
10:15:282M
10:19:3824
10:20:282M
10:21:42PM
10:23:38PM
10:24:4924
10:25:0324
10:26:33
10:27:1024
10:32:4924
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
score
3500
0
10050
0
8950
13500
8000
5350
9200
9700
11350
1450
7750
3750
3850
6200
3950
5200
3150
0
3050
6600
4200
2400
1750
5550
10250
0
3500
25000
750
850
1800
750
1350
10650
3750
9450
4250
2900
0
10850
5900
8950
25300
1050
4750
5250
2800
4150
50
3600
2500
1900
0
200
50
2400
0
3800
4350
38150
3050
6050
2500
1800
9400
6100
6700
250
10200
8650
3500
15750
2950
1800
3750
450
1200
9200
9950
3850
4200
4050
2600
4200
4500
1850
3200
2800
3750
5200
5650
7150
18550
20250
11700
4050
3850
850
0
6000
2550
900
duration
66
59
1322
50
213
214
323
109
152
895
229
38
181
143
106
169
225
139
101
135
94
257
175
153
141
188
304
91
91
628
159
100
451
199
75
167
36
167
246
848
90
417
140
102
234
48
205
226
89
59
39
41
116
58
9
90
35
198
72
421
247
526
99
273
109
136
422
392
190
56
471
284
125
320
105
110
116
54
111
248
187
177
164
132
84
157
142
227
59
136
107
123
289
156
261
238
354
163
801
75
4
141
110
150
GLOM:Information Agglomerates
baddies
6
0
33
0
19
22
32
11
15
33
19
3
15
8
7
12
9
11
7
0
6
18
9
4
7
11
25
0
7
56
1
2
3
3
4
22
5
17
13
6
0
23
7
15
48
2
13
12
5
7
0
4
4
2
0
0
0
4
0
7
9
61
5
16
4
3
22
16
10
0
24
19
9
27
9
3
6
1
2
22
20
7
9
10
8
7
9
6
5
5
7
12
17
13
33
32
27
10
14
3
0
24
4
1
hits
154
0
219
0
226
407
222
96
273
239
359
34
150
57
50
121
73
162
67
0
71
144
107
27
81
94
285
0
58
774
18
45
42
105
89
297
86
309
123
34
0
401
128
164
596
15
88
126
32
98
3
76
26
61
20
50
38
26
0
47
58
582
31
111
26
25
202
194
232
5
265
219
71
586
95
20
49
45
49
210
291
44
99
61
100
91
66
52
35
43
49
93
145
187
316
329
380
117
122
44
0
169
45
12
shots
244
4
884
1
1312
1306
1299
501
838
1116
1212
153
429
88
115
271
189
308
115
17
185
1593
600
51
208
650
1452
1
314
3475
83
178
462
124
305
861
129
694
505
605
31
1716
497
389
1446
48
267
399
80
153
13
105
83
123
22
64
38
55
2
1268
349
1352
164
894
122
64
1022
687
289
8
1071
855
129
1184
203
44
102
99
230
601
518
140
340
173
234
255
258
244
174
108
206
271
398
328
742
622
1928
248
1229
68
4
315
235
81
id#
ip address of player
3883
206.232.107.94/206.232.107.94
3884
dicb-21.nd.eau.execpc.ocn/l69.207.98.150
3885
usr-401-5-39.ISD.net/208.238.143.39
3886
cle1port1.pon.on/206.229.114.11
3887
sp8.nnth.unn.ed/160.94.6.136
3888
sp8.nnth.un.edu/160.94.6.136
3889
clelportl.pem.omnV206.229.114.11
3890
op8.nmth.unn.edu/160.94.6.136
36
3891
sp8.nmth.u.edu/160.94.6.1
3892
usr-401-5-39.ISD.net/208.238.143.39
3893
sp8.nnth.un.edu/160.94.6.136
6 94
36
3894
0. .6.1
sp8.nath.unn.edu/1
3895
ad50-126.ar1. ccpuserve.cr/ 199.174.167.126
3896
aus-tx25-17.ix.netcc.ocn/207.221.69.81
3897
au-tx25-17.ix.netcan.oano207.221.69.81
3898
aus-tx25-17.ix.netan.can/207.221.69.81
3899
calliandra.spry.cnV198.185.1.170
3900
aus-tx25-17.ix.netcan.caV207.221.69.81
3901
spc-isp-tor-uas-03-12.sprint.ca/209.5.16.113
3902
198.30.208.19/198.30.208.19
3903
208.11.193.161/208.11.193.161
3904
185.san-francisco-13.ca.dial-access.att.net/12.64.160.185
3905
nmch-21.truelink.net/207.155.71.135
3906
h-207-1-145-42.netscape.can/207.1.145.42
3907
166.41.204.252/166.41.204.252
7
7
3
3908
.155.1.1 5
nach-21.truelink.net/20
3909
185.oan-francisco-13.ca.dial-acoss.att.net/12.64.160.185
3910
brost.lib.buffalo.edu/128.205.191.27
3911
ad36-229.arl.ccruserve.cam/199.174.139.229
3912
185.san-franciso-13.ca.dial-access.att.net/12.64.160.185
3913
d12.5200-1.plantnet.com/208.141.196.112
3914
ingrid.schrodinger. can/206.231.140.228
6 3
4 2 28
3915
.2 1.10.
ingrid.schrodinger.can/20
3916
Rivervie41.tbayte1.net/204.101.55.105
3917
Riverview4l.tbaytel.net/204.101.55.105
3918
Riverview41.tbaytel.net/204.101.55.105
3919
Rivervie41.tbaytel.net/204.101.55.105
3920
Riverview41.tbaytel.net/204.101.55.105
3
3921
3.211
pnl-01.od22.bc.ca/206.12.
3922
ingrid.schrodinger.can/206.231.140.228
3923
usr30-dialupl9.mix2.Atlanta.nri.net/166.55.58.83
3924
opc-isp-van-uas-26-44.sprint.ca/209.103.5.45
3925
nn-pq6-26.netcan.ca/207.181.92.218
3926
non-pq6-26.netcan.ca/207.181.92.218
3927
spc-isp-vm-uas-26-44.sprint.ca/209.103.5.45
3928
ti21a31-0011.dialup.online.no/130.67.193.203
3929
ti2la3l-0011.dialup.online.no/130.67.193.203
3930
dd06-080.dub.carguserve.can/199.174.148.80
3931
ip26.vanl.pacifier.cc-n206.163.4.26
3932
ci85061-a.nashl.tn.hane.cam24.2.97.219
3933
usm-37-97.wans.net/208.205.37.113
3934
tn.hxnm.aon/24.2.97.219
ci85061-a.nash1
3935
ip26.vanl.pacifier.coa/206.163.4.26
3936
ci85061-a.nashl.tn.hxmn.can/24.2.97.219
3937
ci85061-a.nashl.tn.hn.±con/24.2.97.219
3938
usm-37-97.wans.net/208.205.37.113
3939
usm-37-97.wms.net/208.205.37.113
3940
dia1217.abacan.axn/207.253.161.77
3
3941
0
to.nci.net/166.55.8.1
usr23-dialup2.rnix1.Sacra
3942
ip26.vanl.pacifier.can/206.163.4.26
3943
dia1217.abaom.can/207.253.161.77
3944
ci85061-a.nashl.tn.hano.canV24.2.97.219
6 77
3945
1.
dial217.abacn.caV207.253.1
3946
ip26.van1.pacifier.can206.163.4.26
3947
ip26.vanl.pacifier.can/206.163.4.26
3948
74.sa-frciso-11.ca.dial-access.att.net/12.64.125.74
3949
ip26.vanl.pacifier.ccrn/206.163.4.26
74.san-francio-11.ca.dial-access.att.net/12.64.125.74 3950
3951
adu69.otr.ptd.net/204.186.6.69
3952
p3oa26.ben.sover.net/206.25.65.216
221.an-francio-13.ca.dial-access.att.net/12.64.160.2213953
3954
221.san-franciso-13.ca.dial-access.att.net/12.64.160.221
3955
sac-ca6-13.ix.neto.ca/V198.211.110.205
3956
221. n-francisoo-13.ca.dial-access.att.net/12.64.160.221
76
3 3
3957
. 4.51.1
1Cust48.nax6.washingtmo..nm.uu.net/15
3958
van-bc12-25.netcan.ca/207.181.74.153
3
7 8 74
3959
.1 1. .15
a-bc12-25.netcan.ca/20
3960
us-43-28.wans.net/208.205.43.44
3961
uso43-28.wans.net/208.205.43.447
3962
1Cust199.tntl.orll.da.uu.net/208.250.7
8
7 7 .199
3963
.250. .199
1Csot199.tt1.r11.oda.uu.net/20
3964
user-381d0gk.dialup.mindsprig.omn/209.86.130.20
3965
wnstO-sh2-portll3.snet.net/204.60.37.113
3966
user-381d0gk.dialup.mindspring.can/V209.86.130.20
7
3967
.113
wnstOO-sh2-portl13.snet.net/204.60.3
3968
wnstOO-sh2-portll3.snet.net/204.60.37.113
3969
128.ledngton-Ol.ky.dial-acces.att.net/12.66.70.128
66
3970
66.louston-03.tx.dial-access.att.net/12.65.130.
7
3
3971
.11
wnstOO-sh2-portll3.mnet.net/204.60.3
3972
kit-cnl-39.netcan.ca/207.181.77.103
3973
128.lexington-01.ky.dial-access.att.net/12.66.70.128
3974
vnstOO-sh2-port113.snet.net/204.60.37.113
3975
66.houston-03.tx.dial-access.att.net/12.65.130.66
3976
3977
ci85061-a.nashl1.tn.hnme.can/24.2.97.219
7
3978
.219
ci85061-a.nashl.tn.8xne.<xrn24.2.9
3979
eknapp.housing.res.keot.edu/131.123.48.233
7
3980
user-381d44j.dialup.rmindspring.c-±n/209.86.144.14
3
7 8 77
3981
.1
1.
.10
kit-on1-39.netcan.ca/20
3982
nic-c09-041.rw.mediaone.net/24.131.9.41
3983
nic-c09-041.nw.ndiaone.net/24.131.9.41
3984
kit-on1-39.netcain.ca/207.181.77.103
3985
nic-c09-041.nw.nediaone.net/24.131.9.41
3986
doyl222-pri.voiceet.aom207.103.116.152
wnst0o-sh2-portll3.snet.net/204.60.37
133
date
time
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980508
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
10:32:57
10:34:2824
10:36:0524
10:36:15
10:38:22
10:41:1124
10:45:402M
10:48:412M
10:49:492M
10:51:442M
10:52:232M
10:52:582M
11:05:162M
11:10:372M
11:12:5724
11:20:0324
11:21:4524
11:31:562M
11:42:12
12:02:02AM
12:04:52AM
12:09:08AM
12:09:12AM
12:11:20AM
12:13:54AM
12:16:29AM
12:20:572M
12:21:222M
12:22:392M
12:24:11
12:31:072M
24
12:40:30
2M
12:40:39
12:41:27
2M
2M
12:43:28
12:45:24
12:45:28
24
2M
12:57:54
2M
12:58:07
2M
12:59:57
1:05:022M
108:56
1:11:1424
1:14:222M
1:14:252M
1:18:142M
1:23:1024
1:25:222M
1:25:5124
1:30,06
1:31:32
1:53:3024
1:55:522M
1:57:122M
1:59:352M
2:00:272M
2:00:492M
2:07:132M
2:07,272M
2:34:132M
2,36:342M
2:38:2924
2:39:3624
2:46:0124
2:46:15
2:47:372M
2:49:59
2:54:05
2:58:2624
2:58:3524
3:04:252M
3:38:312M
3:40:4124
3:42:512M
4:12:422M
4:20:392M
4:45:2924
5:39:4224
5:42:28
5:42:39
5:45:002M
5:46:31
6:08:08
6:21:42
6:43:462M
6:45:442M
6:46:58AM
6:48:56
7:28:0924
7:28:36AM
7:32:152M
7:32:322M
7:43:452M
7:50:12AM
7:53:29AM
8:07:0824
8:09:56
8:20:46
8:24:08AM
8:30:36M
8:30:56AM
8:32:18A4
8:32:34AM
8:35:362M
M
M
M
M
M4
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
id#
score
duration
baddies
hits
shots
ip address of player
0
0
0
12300
3250
6600
0
4400
2450
2000
3250
8050
2300
4050
3900
4000
3150
3950
4050
2150
9300
9650
1600
5950
1900
1800
15450
0
0
2650
0
8250
5700
2000
4550
1550
6150
4250
750
3300
9000
1450
4950
7850
2550
7350
11300
6500
1500
3550
5450
2850
2650
4200
6050
600
4100
3600
2050
6700
5000
0
4850
5600
13150
4250
7900
12750
5600
6750
32150
4350
2100
6800
22700
3350
4600
4300
3000
3900
6250
4050
10350
3100
650
0
200
5750
4350
8500
3450
9650
43550
950
4800
7600
5650
0
200
6050
400
2600
3350
7350
46
66
79
838
155
134
181
124
187
93
131
231
78
65
89
166
86
96
215
169
292
495
74
107
278
140
692
1
70
174
96
249
386
94
162
85
225
258
41
94
286
80
142
170
67
207
277
116
107
195
262
234
133
175
214
36
197
121
208
165
125
168
165
259
375
69
207
372
245
228
849
144
114
128
633
152
267
212
147
68
124
225
232
63
186
99
52
293
224
186
227
220
661
86
181
290
132
59
142
125
35
128
98
160
0
0
0
41
11
18
0
9
4
4
7
15
9
7
7
7
6
7
7
8
19
20
6
13
3
3
29
0
0
5
0
19
14
6
9
6
19
10
1
7
20
3
10
14
10
14
20
12
4
7
12
5
10
16
13
2
9
7
3
21
14
0
12
11
30
7
17
40
12
15
66
9
8
13
90
13
10
17
12
7
15
7
25
5
0
0
0
16
8
15
8
18
74
3
12
19
13
0
0
17
1
10
6
15
0
0
0
290
127
147
0
63
32
33
41
281
88
60
46
62
40
51
110
83
188
244
91
153
37
18
395
0
0
29
13
139
92
94
91
82
167
132
13
94
251
24
83
163
77
236
327
144
67
45
132
39
87
130
197
80
52
42
47
158
94
7
67
135
326
78
152
399
131
223
665
59
99
136
492
125
59
127
92
50
185
47
242
51
14
20
25
116
60
352
46
294
786
66
83
208
151
0
4
91
15
79
62
132
0
0
3
1543
764
423
12
182
79
89
128
574
131
156
91
360
120
149
254
292
451
609
180
290
132
137
1066
0
1
67
72
408
197
224
207
190
472
345
42
290
1224
72
251
330
237
540
615
214
251
160
268
227
460
349
782
124
317
137
68
400
252
16
364
244
1157
197
454
1177
464
647
2147
223
570
240
1698
296
422
484
224
139
509
267
681
114
45
38
35
402
164
486
243
598
2047
301
878
739
391
0
33
277
17
530
138
422
3987
246.salt-lake-city-02.ut.dial-access.att.net/12.64.69.246
3988
246.oalt-lake-city-02.ut.dial-access.att.net/12.64.69.246
64 69 24 6
3989
. .
246.salt-lake-city-02.ut.dial-access.att.net/12.
3990
ls.ca/207.172.52.117
207-172-52-117.s117.tnt1.hrd.eo
3991
auasc6-19.flash.net/208.194.194.19
3992
auasc6-19.flash.net/208.194.194.19
3993
3994
lCust97.tnt6.seal.da.uu.net/208.253.73.97
3995
16.los-angeles-22.ca.dial-access.att.net/12.64.180.16
7
3996
9
borge-179.infinitytx.net/204.254.148.1
3997
16.los-angeles-22.c.dial-access.att.net/12.64.180.16
7
3998
1Cust97.tnt6.seal.da.uu.net/208.253.73.9
3999
yckan019039.netvigator.cxW205.252.149.167
4000
ip126.chicagolo.il.p.ib-ip.psi.net/38.27.45.126
4001
pn144-22.dialip.mich.net/198.110.144.62
7
7
4002
.47.9
dip-80.nex-02.Clarion.csonline.net/209.13
7
4003
dip-80.nex-02.Clarion.csonline.net/209.137.47.9
4004
166-2-75.ipt.ol.ccV152.166.2.75
4005
d119-1002.rh.rit.edu/129.21.119.2
4006
dial1-6.tctc.<xan/205.243.39.6
4007
ttyCOf.kw.igs.net/206.248.55.143
4008
cor02-23.ppp.iadfw.net/206.66.7.88
4009
pn1a-65.richolnd.infi.net/205.219.233.65
4010
pn1-65.richTmnd.infi.net/205.219.233.65
4011
sasc5-231.tlash.net/209.30.90.231
4012
oaoc5-231.flash.net/209.30.90.231
7 88
4013
.
oor02-23.ppp.iadfw.net/206.66.
4014
207.175.173.78/207.175.173.78
4015
207.175.173.78/207.175.173.78
4016
sasc5-231.flash.net/209.30.90.231
4017
ts4-07.rpt.cyberhighay.net/209.161.38.97
4018
p36-nex25.auck.ihug.co.nz/207.212.238.100
4019
dial-115-30.ots.utexas.edu/128.83.168.126
4020
lgdp167.eoni.a-n192.216.239.167
4021
p36-nox25.auck.ihug.3o.nz/207.212.238.100
4022
223.dallas-10.tx.dial-access.att.net/12.67.3.223
4023
lgdpop167.eoni.ccn/192.216.239.167
4024
pppO88.216.msherb.vidootron.net/207.96.216.88
4025
barrn6-23.caribsurf.com/205.214.193.23
4026
barp5-23.caribsurf.co/205.214.193.23
4027
barpn5--23.cariburf.crnV205.214.193.23
4028
dialup83-2-56.swipiet.se/130.244.83.120
4029
slip166-72-161-90.tx.us.in.net/166.72.161.90
4030
slipl66-72-161-90.tx.us.ihn.net/166.72.161.90
4
4031
24.charlotte-06.nc.dial-access.att.net/12.69.125.2
4032
olipl66-72-161-90.tx.us.ihn.net/166.72.161.90
6
4033
1-90.tx.u.iln.net/166.72.161.90
slip166-72-1
16 6
4034
slip -72-161-90.tx.us.ihn.net/166.72.161.90
4035
1ELO0f219201.rev.telstra-m.net.au/24.192.19.201
4036
4037
tsOO5dOl.pro-ri.concentric.net/206.83.81.109
4038
prp114.citi1ink.wV209.98.9.145
4039
ndhtpx03-port-17.agt.net/204.209.206.126
4040
rpn114.citilink.can/209.98.9.145
4041
ndhtpx03-port-17.agt.net/204.209.206.126
4042
ndhtpx03-port-17.agt.net/204.209.206.126
4043
7
4044
liv24-23.tor.idirect.canV207.136.93.8
4045
p31-nex6.well.ihug.co.nz/209.76.103.31
4046
port-27.IN3-1.globeca.net/195.100.210.217
4047
port-27.2I3-1.globea-an.net/195.100.210.217
3
7
3
4048
0.14.5
lfkn-&1as2-a7.lcc.net/207.
4049
port-27.EM3-1.globca.net/195.100.210.217
4050
zzecraig.dialin.uq.net.au/203.101.251.11
4051
port-27.m3-1.globecan.net/195.100.210.217
4052
zzecraig.dialin.uq.net.au/203.101.251.11
4053
port-27.I0-1.globecan.net/195.100.210.217
4054
zzecraig.dialin.uq.net.au/203.101.251.11
4055
odn-ts-004casjosP1.dialsprint.net/206.133.193.68
4056
zzecraig.dialin.uq.net.au/203.101.251.11
4057
port-27.H63-1.globecan.net/195.100.210.217
3
4058
pn343-34.dialip.mich.net/207.74.188.9
4059
pn343-34.dialip.mich.net/207.74.188.93
4060
p29.ta5.actca.co.il/192.115.23.139
4061
btr-lal-13.ix.netcan.can/205.184.10.45
4062
od-ppp-248.abac.net/208.137.255.148
4063
194.17.250.206/194.17.250.206 6 4
4064
.22
spc-isp-tor-uas-05-41.sprint.ca/209.5.1
4065
spc-isp-tor-uas-05-41.sprint.ca/209.5.16.242
4066
lost5-99-50-79.btinternet.noVl95.99.50.79
4067
hst5-99-50-79.btinternet.crnVl95.99.50.79
4068
spc-isp-tor-uas-05-41.sprint.ca/209.5.16.242
7 39
4069
.1
dialup107-9-11.swipet.se/130.244.10
4070
a4-p23.syd.fl.net.au/202.181.2.87
4071
199.212.46.151/199.212.46.151
4072
mc1-14.ilhamii.net/206.127.241.110
4073
rocl-14.ilhaii.net/206.127.241.110
4074
199.212.46.151/199.212.46.151
4075
DIAUPl.7BL.USIT.NEr/199.1.58.32
4076
rig-129-91.riq.qc.ca/199.84.129.91
4077
DIALUl.7NBUL.USIT.NET/199.1.58.32
4078
riq-129-91.riq.qc.ca/199.84.129.91
4079
riq-129-91.riq.qc.ca/199.84.129.91
4080
user-tre-501-60.dial.inet.fi/195.165.2.60
4081
user-tro-501-60.dial.inet.fi/195.165.2.60
4082
nichael.clark.net/168.143.3.91
4083
mdchael.clark.net/168.143.3.91
7
7
4084
.17.22.120
dialup7O.viconet.can/20
4085
dialup7O.vionet.can/207.17.227.120
4086
linel06.net-conect.net/206.160.145.106
4087
crn±206b.stny.lrun.canV204.210.137.157
33
4088
p -nux11.well.ihug.co.nz/209.78.48.33
4089
linelO6.net-coect.net/206.160.145.106
6
4090
line106.net-conect.net/206.160.145.10
GLOM:Information Agglomerates
mp8578.on.bellglobal.ccm/207.236.125.2
arf-ca3-04.ix.netcan.cn/199.182.131.100
I114.citilink.caV209.98.9.145
134
date
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
time
8:37:17 AM
8:39:01AM
8:40:39AM
8:43:52AM
8:44:06AM
8:46:19AM
9:23:22AM
9:45:40AM
9:46:00AM
9:47:45AM
9:47:47AM
9:49:53AM
9:51:03AM
9:51:19AM
9:52:43AM
9:53:26AM
9:54:21AM
9:54:28AM
9:54:35AM
9:54:40AM
9:55:41AM
9:57:30AM
9:57:42AM
9:59:41AM
9:59:42AM
9:59:49AM
10:01:03AM
10:02:07AM
10:02:37AM
10:03:16AM
10:05:24AM
10:37:10
AM
10:40:51
AM
AM
10:43:31
10:46:05
AM
10:50:30 AM
10:54:52 AM
11:04:00 AM
AM
11:04:44
AM
11:08:35
AM
11:08:49
11:14:28
AM
11:17:53AM
11:18:02AM
11:18:53AM
11:20:04AM
11:21:12AM
11:21:25AM
11:22:25AM
11:24:01AM
11:24:51AM
11:33:55AM
11:44:14AM
11:45:58AM
11:57:36AM
12:00:03
12:08:4504
12:14:02
12:18:180M
12:25:260M
12:28:15
12:38:43R4
12:50:0024
12:53:302M
12:54:472M
2M
12:55:03
12:57:37
2M
1:03:352M
1:05:592M
1:06:222M
1:08:022M
1:08:552M
1:10:2324
1:12:49
1:16:442M
1:16:552M
1:21:3324
1:32:032M
1:34:0124
1:38:13EM
1:38:17
1:38:41
1:39:482M
1:41:022M
1:41:192M
1:42:022M
1:42:092M
1:42:49 EM
1:43:332M
1:44:242M
1:44:5824
1:45:562M
1:46:262M
1:49:582M
2:08:122M
2:09:142M
2:15:042M
2:17:022M
2:18:382M
2:20:212M
2:21:39
2:23:26
2:23:542M
2:29:51
M
M
M
M
M
M
M
M
M
duration
84
385
186
176
156
129
102
138
81
89
95
111
129
57
68
79
80
45
194
88
162
172
100
22
93
114
185
40
160
117
149
258
90
81
295
174
218
46
135
186
3
159
72
41
45
57
385
345
127
98
204
395
126
86
223
94
109
443
556
98
155
168
289
123
271
357
85
148
38
161
107
274
225
370
200
111
221
113
221
141
132
100
50
149
9
28
43
baddies
7
43
0
8
14
4
5
14
3
7
9
10
5
4
8
1
7
0
7
0
15
18
0
1
9
8
2
0
5
15
14
22
0
13
7
10
9
0
1
19
0
10
1
0
1
1
27
27
4
6
12
34
6
9
15
1
11
23
28
7
11
12
28
0
25
21
8
9
0
9
6
16
20
5
11
12
19
4
6
8
11
8
6
12
0
6
6
500
32
0
500
150
12050
8600
4700
9700
7150
3850
5200
3100
4000
750
8800
8900
5550
0
62
42
113
212
156
226
737
127
161
109
80
45
301
169
145
79
2
0
15
19
10
19
13
7
12
6
9
1
17
15
15
0
score
4200
19150
250
3500
5950
2550
2350
5250
1550
3500
4050
4650
3000
1900
3750
450
3750
500
4000
0
7650
8000
100
600
4350
4700
700
0
2850
5600
8550
7500
100
3300
1950
4400
5200
0
400
5600
0
4750
650
150
750
650
10250
10750
2550
2900
5750
20250
3100
4100
7250
800
5200
10200
12250
3700
5000
4400
9200
250
8600
9200
4100
4550
0
3700
4950
4600
9550
1700
4500
6600
9900
1250
2750
4100
5050
2350
3450
4050
50
3900
1800
GLOM:Information Agglomerates
hits
83
697
9
46
127
27
70
85
62
46
68
119
32
26
45
31
45
11
132
0
149
126
2
26
76
96
58
0
111
133
363
188
40
117
107
330
315
0
76
141
0
100
8
4
9
7
220
248
29
34
121
548
47
52
146
36
105
242
418
89
168
98
166
7
207
228
55
78
5
100
131
154
213
62
77
160
221
51
52
55
84
96
40
118
25
98
90
66
46
4
186
203
91
345
131
46
82
47
50
34
207
249
99
55
shots
186
1874
27
141
280
143
125
325
135
207
244
334
77
65
123
105
193
67
258
1
267
325
102
29
199
195
333
102
133
318
485
556
199
285
1290
731
1060
41
454
648
0
330
61
22
33
29
1794
1471
110
166
671
1730
142
155
358
52
213
784
816
291
835
847
1081
19
1055
530
133
131
18
205
203
375
604
193
232
665
453
215
107
144
228
339
179
495
32
126
142
105
54
12
468
566
213
706
758
141
302
146
132
90
383
584
587
62
ip address of player
line106.net-onnect.net/206.160.145.106
p33-nax11.well.ihug.co.nz/209.78.48.33
net/208.205.39.55
usm-39-39.ano.
8 2
39
. 05. .55
usw39-39.wans.net/20
fctnts13c70.nlnet.nb.ca/207.179.148.172
usm-39-39.wans.net/208.205.39.55
dig01-19.i40.sotaoh.on/209.190.80.22
slip-32-100-115-112.ny.us.ihn.net/32.100.115.112
56K-100.MaxINrl.p&.net/209.144.226.100
56K-100.Max'I14l.pdq.net/209.144.226.100
slip-32-100-115-112.ny.us.ihn.net/32.100.115.112
slip-32-100-115-112.ny.us.ihn.net/32.100.115.112
ici-123-133.vsat.net/208.12.123.133
olip-32-100-18-223.ky.us.ih±n.net/32.100.18.223
slip-32-100-18-223.ky.us.ihn.net/32.100.18.223
intrepid-121.fuse.net/208.16.149.121
lineo106.net-connect.net/206.160.145.106
2
1.fuse.net/208.16.149.121
intrepid-1
ici-123-133.voat.net/208.12.123.133
128.113.70.95/128.113.70.95
8 23
.2
slip-32-100-18-223.ky.us.ihn.net/32.100.1
line106.net-onnect.net/206.160.145.106
slip-32-100-18-223.ky.us.ihn.net/32.100.18.223
ici-123-133.vsat.net/208.12.123.133
6
6
0.145.10
line106.net-connect.net/206.1
pn3-133.x31.infi.net/206.27.115.133
slip-32-100-18-223.ky.u.ihn.net/32.100.18.223
128.113.70.95/128.113.70.95
ici-123-133.vsat.net/208.12.123.133
slip-32-100-18-223.ky.u.ihm.net/32.100.18.223
33
ici-123-133.vsat.net/208.12.123.1
ip4.yorkr4.blazeet.net/24.104.7.4
nic-c08-149.nw.nediaone.net/24.131.8.149
slip-32-100-18-223.ky.us.ihn.net/32.100.18.223
nic-c08-149.nw.medione.net/24.131.8.149
nic-c08-149.nw.ediacne.net/24.131.8.149
nic-c08-149.nw.mediamne.net/24.131.8.149
128.113.70.95/128.113.70.95
nic-c8-149.nw.uediaone.net/24.131.8.149
128.113.70.95/128.113.70.95
128.113.70.95/128.113.70.95
7
.242
242.norristown-05.nj.dial-access.att.net/12.68.15
cliot9543.globalnet.co.uk/194.126.95.67
dia1097.netaccess.on.ca/199.243.225.225
client9543.globalnet.co.uk/194.126.95.67
client9543.globalnet.co.uk/194.126.95.677
.242
242.norristown-05.nj.dial-access.att.net/12.68.15
dialin-56.carmel.bestweb.net/209.94.104.90
cliot9543.globalnet.co.uk/194.126.95.67
cs2511-1-6.nds.nn.frontieet.net/209.130.165.212
7
242.norristo-05.nj.dial-access.att.net/12.68.15
242
68
7 .242
.15 .
242.orristown-05.nj.dial-access.att.net/12.
7
tctoriver689.adelphia.net/24.48.3.1
77
7
tcoriver689.adelphia.net/24.48.3.1
123.newark-03.nj.dial-access.att.net/12.68.34.123
2
203-32-152.ipt.aol.amn/152.203.32.15
204-45-117.ipt.aol.canul52.204.45.117
ts002d14.jac-nm.concnmtric.net/206.173.74.50
204-45-117.ipt.aol.can/'152.204.45.117
dialup2ll-2-5.swipiet.se/130.244.211.69
69
dialup211-2-5.swi;net.se/130.244.211.
id#
4091
4092
4093
4094
4095
4096
4097
4098
4099
4100
4101
4102
4103
4104
4105
4106
4107
4108
4109
4110
4111
4112
4113
4114
4115
4116
4117
4118
4119
4120
4121
4122
4123
4124
4125
4126
4127
4128
4129
4130
4131
4132
4133
4134
4135
4136
4137
4138
4139
4140
4141
4142
4143
4144
4145
4146
4147
4148
4149
4150
4151
4152
4153
4154
4155
4156
4157
4158
4159
4160
4161
4162
4163
4164
4165
4166
4167
4168
4169
4170
4171
4172
4173
4174
4175
4176
4177
4178
4179
4180
4181
4182
4183
4184
4185
4186
4187
4188
4189
4190
4191
4192
4193
4194
srh0084.urh.uiuc.edu/130.126.208.93
198.99.179.2/198.99.179.2
windchiun-08.synapse.net/199.84.52.104
198.99.179.2/198.99.179.2
206.14.7.115/206.14.7.115
209.150.79.67/209.150.79.67
pn2-29.voil.cnV206.230.70.49
texsipd07.texhm.net/209.48.241.136
dial-241.hay.net/207.81.39.241
pn2-29. woil.cnr/206.230.70.49
usr35-dialup44.mix2.Atlanta.nci.net/166.55.59.172
dial-241.hay.net/207.81.39.241
tcrl-43.keee.nond.net/206.231.110.43
afon-dyn39.afcn.net/209.26.60.39
sergei-eisenstein.nedia.mit.edu/18.85.25.36
7
0.49
pn2-29.woil.ca206.230.
188.hartford-02.ct.dial-access.att.net/12.68.148.188
130.184.111.33/130.184.111.33
hlfxl5-11.ns. synpatio.ca/142.177.14.20
1Cust176.tntl.por2.da.uu.net/153.34.14.176
pc82.vash.kcls.org/198.104.18.22
pc82.vash.kcls.org/198.104.18.22
unet/153.34.14.176
1Custl76.tntl.por2.da.u
pc82.vash.kcls.org/198.104.18.22
pc82.vash.kcls.org/198.104.18.22
1Cust176.tntl.por2.da.uu.net/153.34.14.176
8
.22
pc82.vash.kcls.org/198.104.1
:C001684.greek.uidaol.edu/129.101.136.184
bing7O2y.stny.1run.cun/204.210.143.76
pc82.vash.kcls.org/198.104.18.22
1Cust176.tnt1.por2.da.uu.net/153.34.14.176
PC001684.greek.uidaho.edu/129.101.136.184
7
6
1Cuist176.tntl.por2.da.uu.net/153.34.14.1
198.99.179.2/198.99.179.2
207.194.179.67/207.194.179.67
3
2 6 66 7
6
0 . . .11
crOl-1 .ppp.iadfw.net/
pool-207-205-151-72.dlls.grid.net/207.205.151.72
pool-207-205-151-72.dlls.grid.net/207.205.151.72
sdn-ts-002ilbellP10.dialsprint.net/206.133.107.45
cru01-16.gp.iadfw.net/206.66.7.113 7
Bdn-ts-002il1ellP10.dialsprint.net/206.133.10
7.45
2
pool-207-205-151-72.dlls.grid.net/207.205.151.
pn3-31.boone.net/206.154.8.40
135
date
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
time
2:30:40 EM
2:31:08EM
2:32:20R4
2:33:49EM
2:35:51RM
2:37:46RM
2:42:03PM
2:42:25RM
2:43:49RM
2:45:41EM
2:50:35
2:51:47RI
2:53:36RM
2:53:52RM
2:56:52RM
2:57:22RI
2:58:09RM
2:59:01RM
2:59:21RM
3:02:23PM
3:02:34
3:03:04
3:04:22RM
3:08:02
3:10:06RM
3:10:54RM
3:11:42RM
3:12:50RM
3:13:33RM
3:15:21RI
3:16:03
3:17:28
3:17:34M
3:17:54
3:19:00RI
3:20:28RM
3:20:42RM
3:21:22RM
3:24:19R
3:24:33RM
3:28:14RI
3:28:30RI
3:33:04RM
3:33:52RM
3:35:05RM
3:39:09RI
3:39:18
3:43:25
3:46:31
3:48:05RM
3:48:22RI
3:49:36RM
3:51:47RM
3:54:43RM
3:54:46RM
3:57:09
3:57:41RM
3:59:49RM
4:07:04RM
4:12:58 FM
4:15:39
4:18:12
4:27:51RM
4:36:37RM
4:38:32RM
4:45:58
4:46:28RI
4:50:57RM
4:53:41RM
4:54:40RM
4:58:03RM
5:02:42RI
5:03:49RI
5:04:42RI
5:04:53RM
5:07:02RM
5:09:34RM
5:12:21RM
5:18:58RI
5:21:04RM
5:21:34RM
5:23:06RM
5:28:19RI
5:30±51RI
5:33:36RI
5:35:02
5:35:19RM
5:38:31RM
5:42:57RM
5:45:00RM
5:46:46RI
5:46:52RI
5:50:08RM
5:51:41
5:56:20RI
5:56:49RI
5:59:14RM
6:00:04RI
6:10:22
6:11:09RM
6:11:53RM
6:16:45RM
6:19:22RM
6:20:18RM
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
score
3750
3450
5500
750
21700
4900
5000
1300
1150
3250
6350
1550
4650
4350
2400
3450
5150
3300
3100
14250
4100
3500
3750
5150
7000
350
4950
650
4450
3350
4700
9850
5000
5200
5550
6750
6300
6400
0
9100
9150
250
9400
2700
9550
2750
1750
6850
4500
100
2950
4400
7950
7000
7150
0
1950
3000
10100
5150
5000
800
1350
3800
4100
4400
14250
2650
5800
0
4500
1300
4750
8850
5650
4550
5750
7400
4500
4900
0
6950
0
0
900
2800
5250
7500
0
1200
3500
2900
5750
7250
4200
0
2750
5950
0
50
100
2050
1250
2950
duration
111
61
84
95
265
99
117
74
93
98
325
57
151
177
83
147
363
209
133
494
229
226
167
283
151
50
80
48
94
130
134
377
126
95
69
139
87
146
132
229
204
87
195
115
185
142
209
240
105
13
48
75
185
128
587
222
105
112
293
266
148
118
75
79
89
153
335
113
249
36
102
270
162
220
138
176
130
97
226
370
48
226
102
38
146
215
181
175
11
96
91
162
175
269
161
14
128
236
4
22
16
77
50
195
GLOM:Information Agglomerates
baddies
5
4
12
3
41
8
10
5
3
7
15
6
10
9
5
6
15
10
6
43
8
8
8
12
14
0
8
1
9
7
10
21
13
10
12
13
14
11
0
21
22
0
21
5
20
5
5
20
9
0
3
8
16
12
14
0
4
8
25
18
11
0
4
8
8
9
50
6
14
0
11
2
11
24
15
13
14
14
12
11
0
22
0
0
2
9
12
16
0
2
7
6
14
15
5
0
3
21
0
0
0
8
3
6
hits
94
90
130
45
449
187
86
46
47
61
138
56
87
51
46
41
130
105
43
356
59
46
46
68
115
8
72
19
53
48
78
228
160
68
184
101
199
259
0
170
174
10
159
30
190
42
57
147
58
29
211
121
338
361
151
0
195
269
244
149
87
21
48
46
46
65
289
35
111
0
123
22
117
163
98
141
152
144
114
69
0
183
0
5
18
118
94
126
0
17
40
117
150
168
125
17
80
181
0
25
31
86
21
35
shots
253
119
275
121
817
221
201
102
87
167
509
140
229
516
117
130
780
345
225
2006
303
603
143
396
216
14
144
43
158
392
217
574
817
199
404
191
562
413
5
454
385
55
364
116
355
205
200
891
175
33
257
178
931
689
425
9
426
430
681
1202
300
47
137
183
230
179
2109
233
300
1
228
249
571
678
325
734
397
249
1170
257
1
756
32
23
58
731
292
291
11
42
79
358
376
583
166
22
112
701
1
33
39
146
65
233
id#
ip address of player
4195
207.106.138.2/207.106.138.2
4196
pn3-31.boone.net/206.154.8.40
4197
207.106.138.2/207.106.138.2
8
82
4198
.101.
anilane.ne.nediaoe.net/24.12
6
4 8 4
4199
.15 . . 0
pn3--31.boone.net/20
4200
pn3-31.boone.net/206.154.8.40
4201
ncx3-156.netcologne.de/194.8.196.156
4202
207.106.138.2/207.106.138.2
3 37
4203
4.
cs3-5.pot.ptd.net/204.186.
4204
cs3-5.pot.ptd.net/204.186.34.37
8
4205
4
pn±3-3-084.wizard.co/208.211.54.
4 84
8
4206
.
.211.5
pn3-3-084.wizard.o-n/20
4207
ci.net/166.55.19.123
usr2-dia1up59.mix1.B1oaninton±
4208
ip185.van6.pacifier.can/206.163.4.185
4209
user-37kiEnc.dialup.mindspring.cCm207.69.222.196
4210
169-71-78.ipt.aol.cxrn/152.169.71.78
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4211
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pn3-3-084.wizard.ccanV208.211.5
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dia145.stu.adelphia.net/24.48.26.45
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4213
user-37khct.dialup.mindspring.canV207.69.222.19
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4214
5
ip185.van6.pacifier.ccm/206.163.4.1
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pn3-3-084.wizard.can/208.211.54.84
4216
dial45.stu.adelphia.net/24.48.26.45
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GA-g5.resnet.erory.edu/170.140.88.5
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4218
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ucpppl9.buffnet.net/207.41.194.124
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15pck9.Risn.O:xn/198.93.14
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171-183-186.ipt.aol.ccan/152.171.183.186
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4224
1epck9.Rion.2/198.93.14 .50
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4225
171-183-186.ipt.aol.can±/152.171.183.1
24
7
94
4226
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ucprp19.buffnet.net/20
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1kpck9.Rien.02n/19 . .1 .50
4228
171-183-186.ipt.aol.can/152.171.183.186
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15pck9.Rien.c2n/198.93.148.50
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171-183-186.ipt.aol.caV152.171.183.186
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krpck9.Rien.c2n/198.93.148.50
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ucppl9.btuffnet.net/207.41.194.124
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hd50-023.hil.carpuserve.can199.174.230.23
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1.183.1
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171-183-186.ipt.aol.canV152.171.183.186
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209.73.220.45/209.73.220.45
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205.152.23.2/205.152.23.2
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171-183-186.ipt.aol.can/152.171.183.186
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ts3l-02.tor.istar.ca/204.191.149.193
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dlp219.spring.eri.net/20
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ts31-02.tor.istar.c/204.191.149.193
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nic-c08-149.nw.cnmdiaone.net/24.131.8.149
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anc-p23-117.alaska.net/209.112.140.117
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nic-c08-149.nw.mediaone.net/2
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usrt1n48.ipo1ine.<cxmn209.5.74.106
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210.seattle-04.m.dial-access.att.net/12.65.1
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4266
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ok3-11.ncmphis.edu/1 1. 225.2
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128.113.70.95/128.113.70.95
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lgdgpp4 .eoni.can/V. 1 .239.1
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1
ip-100-181.c1d.prinet.ca/207.218.100.1
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4
6
4274
pppl.poa1.presys.can/20 .100.16 .11
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167-137-171.ipt.aol.can/152.167.137.171
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p07-tcl.act.net/167.114.24.232
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4282
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pp07-tcl.acnet.net/167.114.24.2
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pppwl9.htc.net/208.165.192.19
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pppwl9.htc.net/208.165.192.19
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8
8
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PPP46.oonet.ca/20
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PPP46.oonet.ca/208.12
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PPP46.socnet.ca/208.128.159.
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208.new-york-28-29rs.ny.dial-accss.att.net/12.79.5.208
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P-198.83.Elhet.yu/194.2
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206.65.254.232/206.65.254.232
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4297
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wieladl-103.up.net/20
24 7 3 8 2 22
4298
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usr-22.syr.axess.net/205.
136
id#
date
time
score
duration
baddies
hits
shots
ip address of player
980509
980509
980509
980509
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980509
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6:20:34 EM
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4299
206.65.254.232/206.65.254.232
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wicladl-103.up.net/208.4.95.103
client-151-197-111-46.bellatlantic.net/151.197.111.46 4301
4302
user-381d21a.dialup.mindspring.ccrn/209.86.136.42
4303
user-381d21a.dialup.mindspring.ccen/209.86.136.42
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169-254-131.ipt.aol.cczn/152.169.254.131
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169-254-131.ipt.aol.caVl52.169.254.131
4306
tuctcl-28.flash.net/209.30.43.28
4307
169-254-131.ipt.aol.ccn/V152.169.254.131
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169-254-131.ipt.aol.can/152.169.254.131
9 2 4
4309
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169-254-131.ipt.aol.ccuVl52.16
4310
cx208265-a.mesal.az.hcne.ccan/24.1.200.93
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user-381d21a.dialup.mindspring.can/209.86.136.42
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mr63.oregcoast.crn/204.176.109.53
4313
206.74.5.251/206.74.5.251
4314
=s63.oregoncoast.can/204.176.109.53
4315
yam.unnu.udch.edu/141.213.34.95
4316
95
yam.usnu.umich.edu/141.213.34.
4317
209.44.36.36/209.44.36.36
2
4318
user-381&dmk.dialup.mindspring.cxns/209.86.162.21
4319
149.nations.net/209.194.92.149
4320
nic-c08-149.nw.mediaoe.net/24.131.8.149
4321
R0G106.rh.psu.edu/128.118.51.4
4322
user-381d&mk.dialup.mindspring.can/209.86.162.212
4323
nic-c08-149.nw.rediaone.net/24.131.8.149
4324
pc-12634.on.rogero.wave.ca/24.112.38.157
4325
noden-199.peterboro.net/205.206.219.199
4326
pc-12634.on.rogers.wave.ca/24.112.38.157
4327
171-41-185.ipt.aol.can/152.171.41.185
4328
pc-12634.on.rogers.wave.ca/24.112.38.157
4329
cc1009683-a.vronl.nj.hcme.can/24.3.145.77
4330
168-142-15.ipt.aol.cc/152.168.142.15
4331
ppp6440.on.bellglobal.ccm/206.172.208.32
4332
fre-76-121.Reshall.Berkeley.EDD/169.229.76.121
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4333
port59.lightlink.ccm/205.232.34.15
4334
nexX15217.servers.unsw.EIf.AU/129.94.15.217
4335
hannptl-port-3.agt.net/198.161.155.141
4336
hannptl-port-3.agt.net/198.161.155.141
5 92
7
4337
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2 7 2 14 2
4338
ppp-0 - - 52-92.psdn11.pacbell.net/207.214.252.92
2
4339
usr27-dialup1.mix1.Blocmington.ni.net/166.55. 5.129
4340
ascend-statewide-dialin350.esslink.ccm/204.252.96.166
7
2 2
2
2 07 2 14 25 2
4341
.214.5 .9
- - -92.pednll.pacbell.net/20
usr27-dialupl.mix1.Blocmington.mni.net/166.55.25.129 4342
4343
nexX15217.servrs.unsw.EJ.AU/129.94.15.217
4344
lust.oug.uyne.edu/141.217.24.246
4345
usr27-dialupl.mix1.Blocington.nci.net/166.55.25.129
4346
usr27-dialupl.mix1.Bloaington.nci.net/166.55.25.129
4347
sil-wa4-35.ix. netccmn.ccnV207.93.136.99
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nic-c08-149.nw.mediaone.net/24.131.8.149
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sil-±.a4-35.ix.netcn.ccm/207.93.136.99
4350
cgoave-26-204.ajocable.net/24.226.26.204
4351
nic-c08-149.nw.muediaone.net/24.131.8.149
4352
victoria.pe.net/207.49.166.2
4353
FUIDS15.MIT.EI/18.80.3.119
4354
FWIDS15.MIT.EIU/18.80.3.119
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207.98.63.38/207.98.63.38
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lCustl59.tnt13.det3.da.uu.net/208.254.241.159
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ci8506l-a.nashl.tn.hare.canV24.2.97.219
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4358
29
nexx15229.servers.unsw.EIU.AU/129.94.15.
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208.13.22.202/208.13.22.202
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usr36-dialup3.mix2.Atlanta.nci.net/166.55.59.195
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ip42.van2.pacifier.can/206.163.4.42
4362
user-381cp7e.dlialup.mindspring.cam/209.86.100.238
4363
ip42.van2.pacifier.ccn/206.163.4.42
4364
rabit.greme.xtn.net/206.30.189.10
4365
dsle00398.adsl.telusplanet.net/209.115.144.142
7
4366
9.8.145
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4367
bay1-94.quincy.ziplink.net/206.15.142.108
4368
bay1-94.quincy.ziplink.net/206.15.142.108
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202-176-93.ipt.aol.ccn/152.202.176.93
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3
4370
6.9
202-176-93.ipt.ol.can/152.202.1
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144.baltior-02.nd.dial-access.att.net/12.68.115.144
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cdial-108.suite224.net/209.176.65.108
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utbp-245-015.p-net.buffalo.edu/128.205.245.15
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95.dallas-25.tx.dial-access.att.net/12.67.82.95
4375
95.dallas-25.tx.dial-acss.att.net/12.67.82.95
4376
116.san-frncisco-13.ca.dial-access.att.net/12.64.160.116
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95.dallas-25.tx.dial-acsos.att.net/12.67.82.95
61.san-francic-13.ca.dial-access.att.net/12.64.160.61 4378
4379
207.49.41.161/207.49.41.161
4380
116.san-francisoo-13.ca.dial-access.att.net/12.64.160.116
4381
4382
cybers144d45.nt.wave.shaw.ca/24.64.144.45
4383
tc22-249.
4384
198.189.70.224/198.189.70.224
4385
198.189.70.224/198.189.70.224
4386
cyber32d176.cg.wve.shaw.ca/24.64.32.176
4387
cybers32dl76.og.wave.shaw.ca/24.64.32.176
4388
slipl66-72-150-84.ca.us.ib±n.net/166.72.150.84
4389
world-f.std.ccm/199.172.62.5
4390
phx-ts18-22.goodnet.cxn/207.98.133.55
4391
SA5399-11-10.stic.net/207.71.50.240
4392
phx--tsl8-22.goodnet.ccia/207.98.133.55
4393
AS52-25-232.cso-kit.goldo±.net/209.183.132.232
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tor7-16.yesic.axn/209.167.2.136
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anc-p50-16.alaska.net/209.112.138.16
4396
anc-p50-16.alska.net/209.112.138.16
4397
anc-p5O-l6.alska.net/209.112.138.16
4398
207.150.39.132/207.150.39.132
4399
gen2-112ip163.cadvision.ccn/209.91.112.163
4400
SA5399-11-10.stic.net/207.71.50.240
4401
dyn120pp94.pacific.net.sg/210.24.120.94
4402
gen2-112ip163.cadvision.ccV209.91.112.163
M
GLOM:Information Agglomerates
gp-207-214-252-92.psdnll.pacbell.net/20
pM-
mpp-5200-3539.nt1.total.net/207.139.1
mtelchile.net/206.84.69.249
137
date
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980509
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
time
10:51:01 2M
2M
10:51:12
R4
10:53:23
FM
10:55:23
11:01:06
11:04:54
R4
11:19:48
PM
11:23:02
R4
11:27:55
11:34:06 FM
11:36:25
11:37:42
11:39:16
11:48:562M
11:53:242M
11:54:042M
11:54:2724
11:56:482M
11:56:502M
11:59:16
11:59:17
11:59:402M
11:59:442M
12:02:24
AM
12:05:11
AM
12:08:37
12:09:06AM
12:22:21A14
12:22:50AM
12:24:42AM
12:27:41AM
12:27:580M
12:28:43814
12:32:23AM
12:33:45AM
12:36:36 AM
AM
12:37:28
AM
12:37:54
014
12:40:04
AM
12:40:58
12:42:00
0M
AM
12:43:24
12:44:000M
12:45:070M
12:47:27AM
12:47:57AM
12:50:21AM
12:50:258M
12:52:100M
12:52:280M
12:53:08AM
12:54:06AM
12:54:19AM
12:54:330M
12:55:44AM
12:57:32AM
12:58:47
1:00:360M
1:01:040M
1:08:38AM
1:22:0101
1:24:32014
1:24:54AM
1:27:00AM
1:28:35AM
1:29:42AM
1:31:1814
1:35:480M
1:39:10014
1:43:04AM
1:44:010M
2:10:19 AM
2:12:16 4
2:38:58014
2:44:440M
2:48:17AM
2:52:43AM
2:57:160M
3:18:24AM
3:20:45AM
3:25:100M
3:45:13AM
3:48:200M
3:50:290M
3:53:180M
3:55:150M
3:57:02A14
3:59:240M
4:28:430M
4:32:470M
4:34:45AM
4:37:430M
4:53:35AM
4:55:22AM
5:15:01014
5:15:290M
AM
5:17:07
5:36:26 AM
5:41:50014
7:42:360M
7:45:45014
7:46:26 014
8:08:400M
8:12:23
M
M
M
M
M
M
M
M
M
M
score
4750
11450
150
8000
4850
7850
4900
4450
14300
7750
1250
0
2700
950
200
5850
800
3400
6650
9900
5650
1050
3650
8800
4050
4150
2600
0
5300
4600
1750
3400
950
5100
1400
12100
50
0
1750
13100
4000
7900
5600
7250
14100
5800
4750
1650
2500
3500
8250
1450
1050
2600
3200
6800
1450
11200
3500
16100
3200
0
0
9100
4100
6300
9850
12700
9550
4850
14250
6250
150
1150
5050
6100
3600
3050
2800
8250
3150
950
5350
3400
3600
4000
1800
4100
3300
6500
3150
7200
5000
3600
0
0
3350
11300
13450
3750
7450
7700
200
7950
duration
97
194
61
238
225
213
145
128
279
107
140
68
138
674
50
349
46
127
457
274
133
84
94
149
133
155
219
80
131
96
57
166
42
201
32
520
48
11
57
168
59
65
20
51
124
171
170
94
87
108
283
83
51
130
129
164
59
360
121
466
77
44
3
132
79
52
142
255
183
133
272
116
141
48
257
197
138
117
62
127
142
83
169
111
153
102
91
125
120
227
99
162
107
87
50
12
81
325
311
100
158
188
39
205
GLOM:Information Agglomerates
baddies
9
19
0
17
11
16
10
10
30
12
5
0
8
3
0
13
1
5
19
20
11
1
7
14
9
9
10
0
10
10
6
13
2
13
2
21
0
0
2
24
5
11
8
12
26
17
10
4
4
7
20
5
3
4
10
21
3
24
7
39
5
0
0
15
5
9
18
26
15
9
19
12
0
2
14
17
8
5
5
19
8
1
13
7
8
7
3
8
6
12
7
13
8
6
0
0
4
21
26
8
15
15
0
17
player
id#
hits
shots
ip address of
71
306
27
176
118
187
155
95
349
186
62
0
60
47
5
126
24
83
216
281
138
55
102
204
57
61
89
6
88
85
63
117
14
94
18
355
29
22
42
349
138
249
125
275
415
123
60
95
26
43
317
87
110
47
126
180
69
431
40
582
38
44
0
291
109
162
261
357
255
91
464
111
25
17
145
127
95
40
37
152
86
20
75
60
48
50
18
57
52
138
73
135
94
37
55
17
139
296
358
50
151
168
11
173
115
898
94
1169
473
523
200
172
663
268
99
0
342
145
148
802
30
155
547
601
243
77
144
647
167
379
264
13
261
194
103
321
31
266
38
1419
34
30
60
684
270
507
155
400
777
668
228
339
375
166
657
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197
616
526
1414
197
988
498
1870
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0
488
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645
1204
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830
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878
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200
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176
300
228
102
254
177
155
125
45
157
181
446
236
300
233
418
59
20
163
649
861
375
304
872
56
455
4403
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4404
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sA5399-11-10.stic.net/20
4405
p124.rcia.cc/209.20.190.185
7 7
4
4406
. 1.50.20
SA5399-11-10.stic.net/20
4407
tntOl-96.n-link.o-/208.135.246.96
4408
tntOl-96.n-link.ccmV208.135.246.96
4409
dia112.eidnet.org/207.34.60.12
0 82
4410
. .152
s65.coslink.net/199.19
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4411
o65.coslink.net/199.190.82.15
4412
rdialup12.tcinc.net/207.49.41.162
4413
c6p>172.ocaon.net/207.155.74.172
7 4 72
2 7
7
4414
c6pmp1 2.eccm.net/ 0 .155. .1
4415
207.245.249.63/207.245.249.63
4416
arh0378.urh.uiuc.edu/130.126.72.88
78
4417
168-109-78.ipt.ol.can/152.168.109.
8
4418
.206
d206.focal3.interaccess.can/207.208.13
4419
168-109-78.ipt.aol.ccm/152.168.109.78
4420
168-109-78.ipt.aol.ocrVl52.168.109.78
8
7
4421
arh0378.urh.uiuc.edu/130.126.
8 3
2 2. 8
2 7
4422
0 .16 . 1.9
ccc92.dclink.ca/
78
4423
168-109-78.ipt.ol.o/152.168.109.
4424
dial-35-056.easystreet.crn206.103.35.56
4425
pn2-5-03.cyberspc.mb.ca/198.163.240.152
4426
dial-35-056.easystreet.co206.103.35.56
4427
cbv-43.c&v.ccs/207.124.188.143
4428
narket.pe.net/205.219.116.52
4429
1Cust164.tntl5.dfw5.da.uu.net/153.36.247.164
4430
200-106-157.ipt.ol.occ/152.200.106.157
2 3 23 8
4431
5. 3 8
logan238.blue.net/208.194.
4432
logan238.blue.net/208.194.235.2
2 3
4433
17
ts2l.rworld.ccn/206.230.95.
4434
167-120-45.ipt.ol.ccm/152.16 .120.45
4435
sea-ts4-p07.wolfenet.ccr/207.178.59.57
7
4436
sea-ts4-p07.wolfeet.xm/207.178.59.5 7
4437
ocntric.net/207.155.211.1
tsOOldO5.sag-mi.
2 3
3
4438
0.95.1
ts2l.orld.ccoV206.2
4439
lgvdiall5.tyler.net/208.134.148.15
4
4440
8.15
lgvdiall5.tyler.net/208.134.1
4441
24.128.50.18/24.128.50.18
4442
lgvdiall5.tyler.net/208.134.148.15
7
4443
hlst-209-214-72-121.atl-n.bellouth.net/209.214.
2
7 2.121
2
4444
14. .121
host-209-214-72-121.atl-n.bellsouth.net/209.
4445
host-209-214-72-121.atl-n.bellsouth.net/209.214.72.121
72
4446
7 .121
4447
2.121
host-209-214-72-121.atl-n.bellouth.net/209.214.
77
4448
alex-va-n008c167.noon.jic.ccm/206.156.18.1
4449
208.147.62.90/208.147.62.90
4
28
7
4450
.6.
.ca.dial-acces.att.net/12.6
28.san-francisco-0
28.san-francisco-07.ca.dial-access.att.net/12.64.6.28 4451
4452
208.147.62.90/208.147.62.90 2 5
4453
1.11
zzecraig.dialin.uq.net.au/203.101.
4454
208.147.62.90/208.147.62.90
4455
zzecraig.dialin.uq.net.au/203.101.251.11
4
8
7
4456
28.san-franciso-0 .ca.dial-access.att.net/12.6 .6.2
4457
d206.focal3.interaccess.ccn/207.208.138.206
28
4458
-07.ca.dial-acces.att.net/12.64.6.
28.san-franciso
8
4459
28.oo-francisco-07.ca.dial-access.att.net/12.64.6.2
4460
zzecraig.dialin.uq.net.au/203.101.251.11
4461
28.san-francisco-07.ca.dial-acces.att.net/12.64.6.28
2
3
4462
.101.51.11
zzecraig.dialin.uq.net.au/20
7
00
4463
4.2
host47.analog.xroadstx.ccmV208.220.
4464
ad24-118.ar1.copuserve.cc/199.174.166.118 8
4465
207-172-62-118.s118.tnt2.mn.erols.cm/207.172.62.11
4466
ad24-118.ar1. cpuserve.om/V199.174.166.118
8
74
4467
ad24-118.arl.cxxpuere.can/199.1 7 .166.11 8
4468
4.166.11
ad24-118.arl.ccupuserve.cxn/l99.1
4469
zzecraig.dialin.uq.net.au/203.101.251.11
2 3
4470
0 .101.251.11
zzecraig.dialin.uq.net.au/
4471
zzecraig.dialin.uq.net.au/203.101.251.11
4472
p25.pnl.van.integrityonline.ccn/205.238.28.25
3
4473
zzecraig.dialin.uq.net.au/20 .101.251.11
4474
ppp032.anet-st1.ccm/209.83.129.32
8
2 72
4475
.1 .20.195
172-208-195.ipt.aol.can/15
4476
sdcoe-ibl4.sdcoe.k12.ca.us/209.66.194.14
4477
user-381clsr.dialup.nindspring.ccs/209.86.87.155
8
7
4478
6.8
.155
user-381clsr.dialup.mindspring.caV209.7
2 4
4479
user-37kbo84.dialup.mnindspring.ccV20 .69.2 5.
4480
209.84.132.245/209.84.132.245
42 2 47
4481
tcnet00-58.austin.texas.net/209.99.
2 .2 47
4482
.
tcnetOO-58.austin.texas.net/209.99.4
93
44
3
4483
.89.
.swirnet.se/130.2
dialup89-6-1
97
2
89
4484
1.1 .
nO001027.singnet.can.sg/165.
4485
no001027.singnet.ccm.sg/165.21.189.97
97
4486
nsO001027.singnet.cxx.sg/165.21.189.
97
2
4487
1.189.7
nsO001027.singnet.ccmn.sg/165.
4488
nsO001027.singnet.can.sg/165.21.189.9
4489
OO001027.singnet.cxx.sg/165.21.189.97
4490
OO001027.singnet.ccm.sg/165.21.189.97
4491
175.229.163
3
9
4492
.16
afdn12-163.sf.ccnpuserve.cxn/206.175.22
3
4493
sfdn12-163.sf.conpuserve.cc/206.175.229.16
22 9
3
4494
.16 7
sfdnl2-163.sf.cpapuserve.ccs/206.175.
4495
.38
a5-04-asy33.bey-ro-02.superonline.can/s195.33.21
4496
a5-04-asy33.bey-ro-02.superonline.cc/195.33.217.38
3
4497
.25.160.26
user23.argo.net.au/20 3
2
4498
user23.argo.net.au/20 .25.160. 6
4499
user23.argo.net.au/203.25.160.26
7
4500
sjoback.medkEn.gu.se/130.241. 6.95
4501
sjoback.oedkon.gu.se/130.241.76.95
7
4502
dlialup201-2-53.swiinet.se/130.244.201.11
4
2
4503
9
.139.25.
diall8.hotline.net.au/20
7
4504
dialup201-2-53.swinet.se/130.244.201.11
7
4
4505
6.9
clam-246ppp97.epix.net/205.238.2
7
2
24
4506
05.238. 6.9
clam-246ppp97.epix.net/
ost-209-214-72-121.atl-n.bellsouth.net/209.214.
sfdn12-163.sf.ocpnserve.cc/206.
138
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
980510
8:20:58 AM
8:21:13AM
8:59:38AM
9:02:16AM
9:15:15M
9:27:03AM
9:39:20AM
9:39:39AM
9:41:43AM
9:43:33AM
9:53:02AM
9:57:37AM
10:01:53 AM
10:04:22 AM
4650
5300
9050
2750
7650
2300
7550
14100
450
6000
11150
8900
1250
17600
164
146
241
162
338
121
980
459
19
94
303
260
64
389
GLOM:Information Agglomerates
7
10
22
5
23
3
17
25
0
13
24
20
2
33
258
100
209
41
174
158
144
406
33
121
388
200
14
489
949
255
416
207
928
366
407
863
39
343
938
510
28
1041
nic-c08-149.n.nediae.net/24.131.8.149
rpp13287.on.be11global.can/206.172.165.6
prn180-14.dialip.mich.net/198.108.246.24
43-pn-cltx.hinc.can/206. 54.161.243
dia116.hotline.net.au/202.139.25.47
nic-c08-149.nw.nediane.net/24.131.8.149
rdg-52t2-68.nveb.co.za/196.2.33.68
204.183.206.50/204.183.206.50
ns000925.singnet.ca.sg/165.21.189.35
ns00925.singnet.can.sg/165.21.189.35
2
3
6
5. 1.189.5
ns000925.singnet.a-m.sg/1
ns000925.singnet.om.sg/165.21.189.35
nbte13-166.nbtel.net/207.179.142.1663
5
ns000925.singnet.ca.sg/165.21.189.
4507
4508
4509
4510
4511
4512
4513
4514
4515
4516
4517
4518
4519
4520
139
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