` 50/ISSN 0970-647X | Volume No. 38 | Issue No. 8 | November 2014
www.csi-india.org
Cover Story
Visualization-Techniques,
Methods and Tools 7
Article
Information Technology to
Curb Piracy in Bollywood 23
Technical Trends
Big Data Visualization using
Cassandra and R 15
IT Industry Perspective
Future of Medical Transcription Jobs in
India - Need to Extend it beyond Record
Generating Process 29
Research Front
A Walkthrough & Pathfinder for Research
Novitiates: Google Scholar Vs Microsoft
Academic Search 18
Security Corner
A Case Study of Netrapur Police 39
CSI Communications | November 2014 | 1
CSI Job Specific Certifications
Computer Society of India enters into Knowledge Partnership with
InfoComm International, USA
In its drive towards empowering IT students beyond regular diplomas and degrees, CSI has launched professional certification programme
to certify them for direct employment in niche domains. As the members are aware, CSI has already entered into collaboration with the Open
Group for TOGAF Foundations Certificate to students in the graduate engineering stream. InfoComm certification is the second in line.
InfoComm International of USA is a nonprofit association serving the professional audio video communication industry worldwide.
InfoComm University education supported by CSI would offer those Indian students from the IT stream, pursuing diplomas as well as
degree, the opportunity to qualify as “AV Essential Technology Specialist”.
Initially, a pilot programme that would open around 200 vacancies for successful certified students will be made available by InfoComm.
The course would consist of:
•
Quick start to the AV Industry,
•
The essentials of audio visual technology,
•
Certification preparation, and,
•
Recognized Audio Visual Technologist Certificate.
The delivery of the pilot programme will be via the InfoComm University online learning platform supported by CSI and their partner
Institutions.
Each year, InfoComm International will consolidate the vacancies arising among its member organizations in India and will recruit competent
certified students through the CSI Educational Directorate.
All CSI member educational institutions are invited to be part of the partnership programme, which offers placement opportunities
to the young professionals. Interested institutions may please contact the Director (Education), Computer Society of India, Education
Directorate, CIT Campus, 4th Cross Road, Taramani, Chennai - 600 113.
Phone : +91-44-2254 1102/1103/2874
Email : director.edu@csi-india.org
Institutions in the Mumbai Region may also contact Computer Society of India, Headquarters, Samruddhi Venture Park, Unit No.3, 4th Floor,
MIDC, Andheri (E). Mumbai-400093 Maharashtra,
India. Phone: 91-22-29261700, Fax: 91-22-28302133
Email: hq@csi-india.org
www.csi-india.org
CSI Communications
Contents
Volume No. 38 • Issue No. 8 • November 2014
Editorial Board
Chief Editor
Dr. R M Sonar
Editors
Dr. Debasish Jana
Dr. Achuthsankar Nair
Resident Editor
Mrs. Jayshree Dhere
Published by
Executive Secretary
Mr. Suchit Gogwekar
For Computer Society of India
Design, Print and
Dispatch by
CyberMedia Services Limited
7
10
Cover Story
Visualization-Techniques, Methods and
Tools
Dr. KVSN Rama Rao, Mr. Surya Putchala and
Midhun Thaduru
Visualization for STEM Subjects
A.B. Karthick Anand Babu, D. Maghesh Kumar
and G. RajaRaja Cholan
Technical Trends
11
12
Visualization Tool for Data Mining
15
Big Data Visualization using Cassandra
and R
16
Visualization Methods for Vector Fields:
An Insight
18
A Walkthrough & Pathfinder for Research
Novitiates: Google Scholar Vs Microsoft
Academic Search
Dr. B. Eswara Reddy and Mr. K. Rajendra Prasad
Information Visualization in Gene
Expression Data
Sreeja Ashok, Dr. M. V. Judy and N. Thushara
Vijayakumar
Rishav Singh and Dr. Sanjay Kumar Singh
22
27
Dilip Kumar Dalei, B. V. Hari Krishna Nanda
and N. Venkataramanan
28
29
Amol Dhumane and Dr. Rajesh Prasad
PLUS
Protection of Software as Intellectual
Property
Dr. M Hanumanthappa, Mrs. S Regina
Lourdhu Suganthi and Mrs. Rashmi S
Practitioner Workbench
Programming.Tips() »
Fun with ‘C’ Programs – Reversing a
String using a Bitwise Operator
Programming.Learn(“R”) »
RStudio- Studio of R
Umesh P and Silpa Bhaskaran
IT Industry Perspective
Future of Medical Transcription Jobs
in India - Need to Extend it beyond
Record Generating Process
Prof (Dr.) D G Jha
36
37
Articles
Active Queue Management
Sumith Kumar Puri and Dr. H K Anasuya Devi
Wallace Jacob
Research Front
Anchal Garg, Madhurima, Madhulika and Saru Dhir
Please note:
CSI Communications is published by Computer
Society of India, a non-profit organization.
Views and opinions expressed in the CSI
Communications are those of individual authors,
contributors and advertisers and they may
differ from policies and official statements of
CSI. These should not be construed as legal or
professional advice. The CSI, the publisher, the
editors and the contributors are not responsible
for any decisions taken by readers on the basis of
these views and opinions.
Although every care is being taken to ensure
genuineness of the writings in this publication,
CSI Communications does not attest to the
originality of the respective authors’ content.
© 2012 CSI. All rights reserved.
Instructors are permitted to photocopy isolated
articles for non-commercial classroom use
without fee. For any other copying, reprint or
republication, permission must be obtained
in writing from the Society. Copying for other
than personal use or internal reference, or of
articles or columns not owned by the Society
without explicit permission of the Society or the
copyright owner is strictly prohibited.
23
25
Information Technology to Curb
Piracy in Bollywood
Innovations in India
Software User Experience Maturity
Model
Rajiv Thanawala and Prachi Sakhardande
Security Corner
Information Security »
A Quick Look at Virtual Private
Database Security
Jignesh Doshi and Bhushan Trivedi
39
Case Studies in IT Governance, IT Risk
and Information Security »
A Case Study of Netrapur Police
Dr. Vishnu Kanhere
Brain Teaser
42
Dr. Debasish Jana
Ask an Expert
43
Dr. Debasish Jana
Happenings@ICT
44
H R Mohan
On the Shelf!
Peeyush Chomal
45
CSI Report
46
CSI News
48
Published by Suchit Gogwekar for Computer Society of India at Unit No. 3, 4th Floor, Samruddhi Venture Park, MIDC, Andheri (E), Mumbai-400 093.
Tel. : 022-2926 1700 • Fax : 022-2830 2133 • Email : hq@csi-india.org Printed at GP Offset Pvt. Ltd., Mumbai 400 059.
CSI Communications | November 2014 | 3
Know Your CSI
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Mr. H R Mohan
president@csi-india.org
»
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CSI Communications | November 2014 | 4
www.csi-india.org
President’s Message
H R Mohan
From
: President’s Desk:: president@csi-india.org
Subject : President's Message
Date
: 1st November, 2014
Dear Members
On behalf of the CSI Execom 2014-15, I am pleased to invite you to
CSI-2014, the 49th Annual Convention on the theme “Emerging ICT for
Bridging Future”. It will be held as a part of CSI@50 during 12-14, Dec 2014
at Jawaharlal Nehru Technological University (JNTU), Hyderabad. CSI2014 is hosted by CSI Hyderabad chapter in association with JNTU and
Defense Research Development Organization (DRDO). The Convention
is spearheaded by Mr. JA Chowdary (OC), Dr. A Govardhan (PC) and
Mr. Gautam Mahapatra (FC) and a dedicated team of CSI members,
academic and industry professionals from Hyderabad. The arrangements for
CSI-2014 are in full swing. The team is putting up an excellent programme
which is under its final stage and will soon be available at the convention
website www.csi-2014.org. I am sure that the sessions by a wide range of
eminent speakers on a variety of topics will be a feast to all participants. Prior
to the CSI-2014, the Annual Students Convention will be held on 10-11, Dec
2014 at GNIT campus. Under the theme “Campus to Corporate and Beyond”,
the programme will focus on career opportunities and enhancements. It is
hosted by Guru Nanak Institutions under the chairmanship of Dr. HS Saini.
I look forward to active participation by the members in CSI-2014 and
student members in the student convention. As a heritage city, Hyderabad
has a lot to offer first-time visitors. Please plan your trip well in advance and
have a great time at CSI-2014. We will be delighted to see you at Hyderabad.
I was happy to be among the CSI veterans at Pune who had organized
a meet as part of CSI@50 events along with the International Conference
on Advances in Cloud Computing (ACC-2014) on 10th Oct 2014. Launched
in 1972, CSI Pune has gained prominence by organizing a number of
national and international events including two annual conventions.
Incidentally, CSI-77 at Pune was my first convention as a regular member
after I graduated in 1976. In the CSI@50 meet, after a briefing on chapter
activities by Mr. Anand Joglekar, I shared my views on CSI and the way
to move forward in the current context of capacity building and creating
intellectual property. In a special talk, Dr. Mathai Joseph, a seasoned
computer scientist, academic, researcher and one of the most respected
members of the Pune’s software industry took us down the memory lane
on computing in India from 1960s till now. He highlighted the growth as
well the opportunities we had missed. Mr. Shekhar Sahasrabudhe, a former
RVP-VI and past chairman of CSI Pune, made a lively presentation on
past chairpersons of CSI Pune and their contributions to the growth of the
chapter. A few other former chair persons and Dr. Deepak Shikarpur, former
chairman of CSI Pune, and fellow of CSI, shared their experiences. The conf.
ACC-2014, held under the Div V on “Education & Research” headed by
Dr. Anirban Basu, was well attended with over 100 enthusiastic participants
who had interacted actively with the speakers. The panel on “IoT – the
present and the future” was the highpoint of ACC-2014. Dr. Rajesh Ingle
and his team brought out an excellent proceeding with 13 papers, which
will be available in the CSI Digital Library soon. The CSI Pune deserves a
hearty congratulation for showcasing their organizing capacity once again.
Formal Methods (FM), a discipline in theoretical computing,
plays an important role by applying mathematical techniques in the
specification, development and verification of software and hardware
systems. NCFM - the National workshop-cum-Conference on Formal
Methods - recently held during 15-17, Oct 2014 in Bangalore was the
first of its kind that brought together scientists and engineers who
are active in the area of FM and are interested in exchanging their
experiences in the industrial usage of these methods. The NCFM was
organized by the new CSI SIG on Formal Methods whose convener is
Ms. Bhanumathi Shekhar, along with CSI Bangalore and hosted by IISc.
Dr. Ramaswamy Srinivasan, Global R&D Project Manager of ABB Global
Industries, Bangalore in his inaugural address highlighted the growing
needs in FM. In view of the fact that 400 out of 600 talent-starved R&D
centers of international companies are now located in India and the role
of CSI SIG-FM in creating awareness and motivating students to work
in FM, the need to educate our students and working professionals in
FM were the highlights of the special address by the President. The CSI
BC Chairman Chander Mannar and his team have spared no efforts in
making this conf. a technically rich one with a lot of interactions and
learning by the participants. While speaking to Prof. N. Balakrishnan,
of the Supercomputer Education and Research Centre at IISc, it was
given to understand that funding is available for research in the Formal
Methods in Cyber Security and related areas, and that SIG-FM can work
with them in popularizing Formal Methods among researchers.
While we at CSI are taking advantage of our association with IEEE
& IEEE Computer Society in organizing a number of Distinguished Visitor
Programme talks and tutorials at various CSI Student Branches, our own
home grown Distinguished Speaker Programme (DSP) requires attention
for its effective implementation. The growth in the number of engineering
institutions has created a shortage of qualified teachers; DSP was initiated to
rope in both experienced academic and industry professionals to supply an
alternative stream of teachers who will help our students become industry
ready. While it is quite easy to organize programmes with speakers from
abroad, my personal experience in getting our senior members of academia
and industry for talks is quite a mixed one. Some have been overwhelmingly
responsive to our request but a few do not even acknowledge the request,
left alone coming forward to speak at conferences organized by CSI.
I am happy to share some of the activities of our Education
Directorate in their continued effort in service to our members which
include: Signing of MoU with Telecom Sector Skill Council (TSSC)
for skill development initiatives in the Telecommunications domain;
Conducting the SEARCC International School Software Competition
ISSC-2014 at Rajalakshmi Engineering College, Chennai in which ROC
Taiwan came first, followed by India (Team-B) and Sri Lanka (Team-A) in
the second and third places respectively. The prizes were presented by
Mr. HR Mohan, President, CSI, Dr. Thangam Meganathan, Chairperson,
Rajalakshmi Group of Institutions, Prof. P Thrimurthy, Past President,
CSI, Mr. S Ramanathan, Past Hony. Secretary and Mr. Bhaskaran, Vice
Chairman, CSI Chennai; and Continuing its campaign on Open Source
Technology, by organizing a free workshop for faculty members on BOSS
MOOL at JNTU, Anantapur, Andhra, jointly with CDAC, IIT Madras. The
workshop, attended by over 100 was inaugurated by Prof. Lal Kishore,
Vice Chancellor, JNTU-A and facilitated by Prof. Ananda Rao.
I am happy to note that CSI Chennai in association with IEEE Computer
Society and IEEE Professional Communication Society is organizing an Essay
Contest for the school and college students on the topics “ICT for Digital
India”, “ICT for Make in India” and “ICT for Clean India” which are the
important initiatives of the Government of India. I wish all the best for their
efforts and request them to share the views of the young minds to the PMO
and DeitY.
Due to space constraints, I will discuss some of the recent
developments in the country such as eCommerce, ICT in manufacturing
and other initiatives in the next month. While I conclude my message, let
me once again remind you to enroll new members in CSI by letting them
know about the 15% discount on Life Membership being offered for a limited
period. This will end by Dec 2014.
Once again I extend my personal invitation to all for your participation
in CSI-2014, the flagship event of CSI at Hyderabad. I eagerly look forward
to seeing you at Hyderabad in Dec 2014.
With best regards
H R Mohan
President
Computer Society of India
CSI Communications | November 2014 | 5
Editorial
Rajendra M Sonar, Achuthsankar S Nair, Debasish Jana and Jayshree Dhere
Editors
Dear Fellow CSI Members,
We have come a long way since the time when data was displayed
only in text form. With increasing computing power over the years,
and deluge of data from a variety of fields from e-business to gene
sequencing, the visual representation of data has assumed greater
and greater importance. Techniques and technologies for visualisation
have emerged over the years making it possible and feasible to make
sense out of the overwhelming amount of data. Information today can
be represented in various formats which makes computing more and
more interesting with a variety of applications in different fields. The
advent of Google glass which displays information in a smartphonelike hands-free format, is a pointer to the future. The theme of CSI
Communications this month is related to the vast field of Visualization
Technologies. The articles of course are not covering the breadth of
the field, but as with other such fields, the theme would be taken up
again in future to do justice to the coverage.
We start our cover story section with an article titled “Visualization
– Techniques, Methods and Tools” by Dr. KVSN Rama Rao, Mr.
Surya Putchala and Midhun Thaduru. The article talks about how
visualization adds value to the data that needs to be analyzed. After
explaining the process of visualization the article provides information
about various open source tools available for visualization. The
second article is by A.B. Karthick Anand Babu, D. Maghesh Kumar
and G. RajaRaja Cholan and is titled “Visualization for STEM Subjects”.
The article discusses how visualization enhances learning experience
for students of subjects such as Science, Technology, Engineering and
Mathematics. It also gives information about visualization tools that
can be used and concludes saying that domain knowledge is required
for customizing and designing effective visualization using readily
available open source tools.
With increasing computing power over the years, and deluge of
data from a variety of fields from e-business to gene sequencing,
the visual representation of data has assumed greater and greater
importance. Techniques and technologies for visualisation have
emerged over the years making it possible and feasible to make
sense out of the overwhelming amount of data.
Our Technical Trends section is enriched with three articles. The first
article is written by Dr. B. Eswara Reddy and Mr. K. Rajendra Prasad on
“Visualization Tool for Data Mining”. This article provides information
about a tool called Visual Access Tendency (VAT) which is useful
for detecting information of number of data clusters (or classes) in
visual form. The second article is by Sreeja Ashok, Dr. M. V. Judy
and N. Thushara Vijayakumar n on “Information Visualization in Gene
Expression Data”. The article talks about significance of visualization
in the context of gene expression data and then goes about explaining
the process of visualization. The third article is by Rishav Singh and
Dr. Sanjay Kumar Singh and is titled “Big Data Visualization Using
Cassandra and R” which discusses the use of distributed database
system Cassandra and compares it with SQL database.
Research Front section has two articles. First one is by Dilip Kumar
Dalei, B. V. Hari Krishna Nanda and N. Venkataramanan titled
“Visualization Methods for Vector Fields: An Insight”. The article
provides introduction to scientific data visualization and provides
overview of fundamental flow visualization technique. The second
article is by Anchal Garg, Madhurima, Madhulika and Saru Dhir titled
“A Walkthrough & Pathfinder for Research Novitiates: Google Scholar Vs
Microsoft Academic Search”. The article explains how searching can be
done while researching.
In regular article section, we have three articles on different topics.
The first article titled “Active Queue Management” is written by
Amol Dhumane and Dr. Rajesh Prasad who write about new queue
management technique used for handling congestion in networks.
The second article is on an interesting topic of “Information Technology
CSI Communications | November 2014 | 6
to Curb Piracy in Bollywood” written by Sumith Kumar Puri and Dr. H K
Anasuya Devi. This article makes us aware about CineCat, a software
application idea. The third article titled “Protection of Software as
Intellectual Property” is sent by Dr. M Hanumanthappa, Mrs. S Regina
Lourdhu Suganthi and Mrs. Rashmi S. The article explains the meaning
of intellectual property and discusses the protection provided by law
for such intangible property in the form of patents and copyrights. It
compares the two and concludes saying that for software adequate
protection in the form of patent right is highly desirable and dual IP
protection in the form of Patents and Copyrights can also be explored
to cover both functional and non-functional aspects of software.
... for software adequate protection in the form of patent right is
highly desirable and dual IP protection in the form of Patents and
Copyrights can also be explored to cover both functional and nonfunctional aspects of software.
In Practitioner workbench section we have two articles from our
regular contributors. The first one: “Fun with ‘C’ Programs: Reversing
a String using a Bitwise Operator” under Programming.Tips() section
is written by Prof. Wallace Jacob of Tolani Maritime Institute and
second one: “RStudio – Studio of R” under Programming.Learn(“R”)
section is written by Umesh P and Silpa Bhaskaran, Department of
Computational Biology and Bioinformatics.
Under IT industry perspective we have an article titled “Future of
Medical Transcription Jobs in India – Need to Extend it Beyond Record
Generating Process?” by Prof (Dr.) DG Jha. This article discusses
various points such as importance of medical transcriptions (MT),
why the MT work is outsourced, quality standards applicable to MT,
stages in the process of MT, technological innovations which are
creating a doubt whether it is dead end for smaller Indian companies
doing MT jobs, factors obstructing outsourcing MT work to India and
finally talks about revival strategy that can make India a preferred
destination once again for MT work.
Under Innovations in India column, which we recently started from
July 2014 issue, we have a brief article titled “Software User Experience
Maturity Model” by Rajiv Thanawala and Prachi Sakhardande of TCS.
In this article they explain how metrics can be used for measuring
quality of software products in terms of user experience.
Under information security section of Security Corner column, this
time we have an article on “A Quick Look at Virtual Private Database
Security” by Jignesh Doshi and Bhushan Trivedi, where they explain
how Oracle’s virtual private database technology can be used for
prevention of theft of sensitive data. In the second section of Security
Corner column, we have a case study in IT Governance, IT Risk and
Information Security by Dr. Vishnu Kanhere, who writes about case
of Netrapur Police who plan to implement new surveillance system
called San-nirikshan and the kind of disruption it is expected to create.
In our regular section called Brain Teaser we have a cross-word by Dr.
Debasish Jana, Editor on Visualization Technologies. He also answers
readers’ questions under the column Ask an Expert: Your question,
Our answer. Briefs of various ICT news of October 2014 are compiled
and brought to us by H R Mohan, ICT Consultant, President, CSI and
former AVP (Systems), The Hindu, Chennai under Happenings@ICT.
We have other regular features like CSI Announcements, CSI Reports,
Chapter and Student Branch news etc. Please remember we welcome
your suggestions and feedback at csic@csi-india.org. Please do write
and help us serve you better. Wish you happy reading and learning.
With warm regards,
Rajendra M Sonar, Achuthsankar S Nair,
Debasish Jana and Jayshree Dhere
Editors
www.csi-india.org
Cover
Story
Dr. KVSN Rama Rao*, Mr. Surya Putchala** and Midhun Thaduru***
*Prof., Dept. of CSE, MLR Institute of Technology,Hyderabad
**CEO and Chairman, Zettamine Technologies
***Associate Consultant, Zettamine Technologies
Visualization-Techniques, Methods and Tools
Why Visualization?
It is a well known fact that “A picture
is worth a thousand words.“ To extract
and analyze the massive amount of
generated data, visualization plays an
incredible role. Further it amplifies the
cognition by helping in pattern detection
and enhancing visual insight of a large
quantity of data. It helps us to see data in
context, analyze and discover knowledge.
For companies across different industries
– retail, logistics, banking and Finance,
Insurance, energy etc., data visualization
offer terrific opportunities to identify
new products or uncover customer
propensities that can provide insights
of tremendous value to Businesses. For
example, in a retail industry, increased use
of geo-spatial visualization and analysis,
the location of store, the difference in
market size according to region, price and
compensation studies in regard to specific
regions, etc. reflect more clearly their
potential advantage.
Data Visualization techniques often
comes handy while representing large
quantities of data and help making sense
of big data and thus provide an exploratory
platform for gaining deeper and clear
insights. Some of the key functions of
visualization are highlighted below.
•
To present large volumes of data
(structured
or
unstructured)
effectively and elegantly.
•
Provide a platform for exploring
various facets of information
aesthetically and interactively.
•
Promote a deeper level of
understanding of the data under
investigation and assists us in
drawing conclusions.
•
Share information effectively to
persuade, collaborate and emphasize
important aspects of data.
A Simple Process for Visualization
As the data and the number of sources of
information keeps growing, extraction of
suitable information and presenting in a
human consumable form becomes a great
challenge. However, a data analyst can
systemically increase the value of data
through two major processes – one, Data
Cleansing/Pre Processing and the second,
Visualization process. Visualization is a six
step process.
•
•
•
•
•
•
Mapping : is encoding of data into
visual form. It is used for achieving
accurate relationship between data
points and visual objects that are to
be described.
Selection : of attributes from the
data which aims for right pictorial
representation.
Presentation : is effective management
and organization of information in
the available screen space.
Interactivity : is providing facilities to
organize explore and rearrange the
visualization.
Human factors : are easy readability
and accessibility of information for
end user.
Evaluation: is finding out effectiveness
in the created visual, if we have
succeeded in reaching our goal in
creating lucid and easy to understand
graphics.
A Brief Survey of Graphical Techniques
Charting or Graphing is small subset of
visualization where the data in question is
explained with the help of bar charts, line
charts or pie charts.
Information graphics or infographics
are graphic visual representations of
information, data or knowledge intended
to present complex information quickly
and clearly. They can improve cognition
by utilizing graphics to enhance the
human visual system’s ability to see
patterns and trends. Infographics are
used to communicate a message, to
simplify presentation of large amount of
data, often different facets arranged in a
thematic way.
A Scorecard is a tabular visualization
of measures and their respective targets
with visual indicators to see how each
measure is performing against their
targets at a glance. Scorecards may
contain columns that show trends in spark
lines. It measures performance against
goals. It displays the graphic indicators
that visually convey the overall success or
failure of an organization in its efforts to
achieve a particular goal.
A report is the presentation of
data transformed into formatted and
organized according to specific business
requirement. Reports contain detailed
data in a tabular format and typically
display numbers and text only, but
they can use visualization to highlight
key data.
Dashboarding takes visualization
a step further by aggregating several
different pieces of visual information in
a single location. As quoted by Stephen
Few, “dashboarding is a visual display of
the most information needed to achieve
one or more objectives which fits entirely
on a single computer screen so that it
can be monitored at a glance.” A typical
dashboard might contain a scorecard,
an analytical report and an analytical
chart. Digital dashboards are laid out to
track the flow inherent in the business
process that they monitor. Dashboard is
a user interface that is used to organize
and present information in a way that is
easy to read. A good dashboard presents
information about important data, with
fewer graphs and time overview.
To generate visualization, data plays
a major role. In order to visualize, data
need to be in one of the format.
Following are various data formats
that are available.
•
Spreadsheets
are
electronic
document in which the attributes are
stored in columns and the objects are
stored in rows.
•
JSON (Java Script Object Notation) is
a simple human readable file format
with data objects consisting of key
value pairs.
•
XML (extensible Markup language)
is a flexible way to create common
information formats and share both
the format and the data on the world
wide web
•
Delimited Separated Values is format
of data that is used to store various
two dimensional arrays of data by
separating the values in each row
with specific delimiter characters.
Various types of delimiters are
comma, space, tab, and semi-colon.
•
RDF
(Resource
Description
Framework) is a general framework
for describing website metadata, or
information about information.
•
HTML (Hyper Text Mark-up Language)
is a language used for describing webpages using ordinary text.
In many cases, there will be a need
to use more than one data format (variety
CSI Communications | November 2014 | 7
of data). In such situations, we need to
integrate different varieties of data. To
create visualizations for such complex
data, there are several popular approaches
and methods which are discussed below.
Popular Approaches/Methods for Data
Visualizations
There have been some conventional
ways to visualize data in the form of
tables, histograms, pie charts and bar
graphs. However to convey a message
effectively there are some exciting
visual techniques that are available.
In addition to the above methods, there
are certain popular open source tools.
Technique
Description
Choropleth
Thematic map where each spatial unit is filled with pattern or color which are scaled and normalized.
Choropleth used to show spatial variation of one or two variables at time by using color, shades
and/or patterns. E.g. population density of each state in a country.
Contour Heat Map
Chord Diagram
Collapsible Tree
Tree Map
Calendar Heat Map
used to display density from the vector point of data. Contour heat maps are used to plot when there are
large number of clustered and continuous data points which can also take categorical variables. These
maps do not actually plot the data but designs a surface fit to the data. E.g. density of population.
used to display inter-relationship between group of entities. The data is arranged around the circle
and the relationships are displayed by arcs.
Used for hierarchical data of long nested lists on the web pages can be difficult to understand.
The tree view, a user interface widget that displays hierarchical data as nested lists, solves this
problem by making lists collapsible and expandable; a list can be opened by or closed by clicking
on its parent list item. where the parent node and children nodes are are joined by arcs or line. E.g.
government divisions and sub-divisions.
Used for hierarchical data that shows attributes of leaf nodes using size and color coding. Tree
maps enable users to compare nodes and sub-trees even at varying depth in the tree and help them
spot the pattern. E.g. visualization of continents, countries, population and area
Chart time series onto vector of dates. E.g. Twitter activity of a celebrity on each day.
Method
Word cloud
Description
is a method of visualizing unstructured text data. Word cloud expresses the occurrence of words in
the text form with size of word or phrase directly related to the frequency of occurrence with which
the word has occurred in the text document. Word cloud helps quickly analyze the main focus or
topics of discussion and can also help us in sentiment analysis.
Association Trees
are used for understanding word association in large quantities of text. Association is most
commonly used in social media text, News analysis or customer feedback. Latent Semantic
Analysis (LSA) is a statistical computation used to identify relationships between a set of
documents and the terms contain by producing a set of concepts related to the documents and
terms. The main idea behind LSA is that all the word combinations in which a given word and
word does not appear can determine the similarity of word meanings. Association trees are a
way defining such similarities.
Cubism Horizon graphs
is used to analyze time series, or streaming content. Cubism Horizon graphs is an intuitive way of
project real-time time series plot. Horizon charts reduce vertical space without losing resolution.
is used for relationships and gaining insights from multidimensional data from multiple sources. A
topological network represents the data by grouping similar data points into nodes and connecting
Self-Organizing maps or Topological those nodes by an edge if the corresponding collections have data points in common. The
visualization techniques comes under the heading of scatter plot methods, where the data points
Analysis
are projected on to 2D or 3D dimensional space, then plotting projections on the coordinates in
usual way.
Network Graphs
is used to study meaning and relationships between large contextual data. These graphs are used
to quantify relationships between different vertices of data. These graphs can be directional or
non-directional based on requirement. A network is a collection of points; called vertices with lines
connection these points are called arcs.
CSI Communications | November 2014 | 8
www.csi-india.org
Open Source Visualization Tools
R is a programming language used for
Statistical Analysis, Data Visualization and
Predictive Modelling. R is an implementation
of S language combined with lexical scoping
semantics. R is a scripting and an interpreted
language i.e. a programming language for
which most of the implementations execute
instructions directly without compiling the
program into machine language. R is an open
source software with great contribution
from R-community towards R-programming
in the form of packages which are available
on Comprehensive R Archive Network
(CRAN).
The base graphs in R are used most
commonly and are a very powerful system
for creating 2-D graphics. The main
function for base graphic is plot(). The
base graphs are loaded by default into R.
Grid is an alternative graphics system
added to R that allows for the creation of
multiple regions on a single graphics page.
The grid package needs to be loaded before
it can be used by using library function.
lattice graphics is a powerful
Implementation
and elegant highlevel data visualization system with an
emphasis on multivariate data. The lattice
package is an implementation of Trellis
graphics for R originally developed for the
S-Language. The lattice consists of highlevel generic functions each designed
to create a particular type of display by
default. Lattice gives advantage of high
user controllable settings.
ggplot2 is a plotting system which
takes the best from the base and lattice
graphics. The plot can be split into
scales and layers which gives the added
advantage over base plot.
rShiny is an interactive web application
framework for r which helps us do our
analysis in dynamic fashion. Shiny combines
the computational power of R with
interactivity of modern web. rShiny has
its own capabilities which doesn’t require
HTML, CSS or JavaScript Knowledge.
D3.js is a Java Script Library which helps
build data visualization framework. D3
stands for Data Driven Documentations.
D3.js is a powerful tool for creating dynamic
and interactive data visualizations. D3.js
uses Scalable Vector Graphics, JavaScript,
HTML5, and Cascading Style Sheets
(CSS3) standards.
google charts is a simple and powerful
open source which can be used to visualize
simple line charts to complex hierarchical
tree maps. Google charts are a specialist
for geocharts. Google charts can easily
connect charts and controls into interactive
dashboards. It can also be used to connect
to data in real time using variety of data
connection tools and protocols.
Gephi is an interactive visualization
and exploration platform for all kinds of
network and complex systems, dynamic
and hierarchical graphs. Gephi is used for
exploratory data analysis, link analysis,
social network analysis, and biological
network analysis and poster creation.
Lumify is a open source big data analysis
and visualization platform. Its intuitive
web-based interface helps users discover
connections and explore relationships in
their data via a suite of analytic options,
including 2D and 3D graph visualizations,
full-text
faceted
search,
dynamic
histograms, interactive geographic maps,
and collaborative workspaces shared in
real-time.
Conclusion
Visualization provides great value addition
for the data that is to be analyzed. There
are several techniques, methods and open
source tools for visualization. Once the data
is ready in a particular format, visualization
can be generated by using these techniques.
References
[1] M Khan and S S Khan, (2011). “Data
and
Information
Visualization
Methods,
and
Interactive
Mechanisms:
A
Survey”,
International Journal of Computer
Application (0975-8887), vol. 34 –
No.1, November 2011
[2] https://www.dashingd3js.com/whybuild-with-d3js
[3] S Card, J MacKinlay, and
B Shneiderman, (1998). “Readings
in
Information
Visualization:
Using Vision to Think”. Morgan
Kaufmann.
[4] Alfredo R Teyseyre and Marcelo
R Campo, (2009). “An Overview
of 3D Software Visualization”, IEEE
Transactions on Visualization and
Computer Graphics, vol.15, No.1.
[5] L Chittaro, (2006). “Visualizing
Information on Mobile Devices”,
ACM Computer, v.39 n.3, p.40-45.
[6] Edward R Tufte, (2007). “The Visual
Display of Quantitative Inforamtion”,
Second Edition, Graphics Press.
[7] h t t p : //w h a t i s .t e c h t a rge t .co m /
definition/infographics
[8] h t t p : // t h e n e x t w e b . c o m /
d d /2 0 1 3/ 1 0/ 1 6 / 1 0 - ways - u s e infographics/
[9] h t t p : / / b l o g s . w s j . c o m /
cmo/2014/06/24/outside-voicesthe-visual-web-is-changingeverything-in-media-andadvertising/
[10] h t t p : //s p o t f i r e . t i b c o . c o m /
blog/?cat=34
[11] http://www.computer.org/portal/
w e b /c o m p u t i n g n o w/a r c h i v e /
january2014
[12] http://smartdatacollective.com/
jgptec/140486/3-big-trends-datavisualization
[13] http://code.stephenmorley.org /
javascript/collapsible-lists/
n
About the Authors
Dr. KVSN Rama Rao is a Professor,Dept of CSE at MLR Institute of Technology,Hyderabad.He is a Doctrate in Computer Science
with over two decades of academic experience. He has published several papers in reputed International and National journals and
conferences. His research interests are Cyber Security and Big data.
Surya Putchala is CEO and Chairman for ZettaMine Technologies, a firm focuses on providing high end educational and Management
consulting services to Business around the world. It also aims to become the first think tank in “Big Data” space in India. Over the last 2
decades, he provided thought leading consulting solutions in the areas of Business Intelligence, Data Warehousing, Data Management
and Analytics to Fortune 500 Clients. He has architected commercial Analytical Applications such as Product MDM and Procurement
Optimization. He has held senior leadership roles with firms such as GE capital, Cognizant, Accenture and HCL.
Midhun Thaduru is an Associate Consultant at ZettaMine Technologies. He is with the Data Science team and focusses on Statistical
Analysis, Exploratory Data Analysis, machine learning and Visualization. He extensively uses R, python, D3.js for his day to day
programming. His area of focus is in Life Sciences (Pharma) and Insurance, particularly, Payer and Provider analytics. His interests are
in developing high performance algorithms for Predictive modelling. Midhun graduated from BITS, Pilani.
CSI Communications | November 2014 | 9
Cover
Story
A.B. Karthick Anand Babu*, D. Maghesh Kumar** and G. RajaRaja Cholan***
*Managing Director, KK Infotech, Thanjavur
**Assistant Professor, Department of Software Engineering, Periyar Maniammai University, Vallam, Thanjavur
***PRIST Univerity, Thanjavur
Visualization for STEM Subjects
The process of learning in Science,
Technology, Engineering, and Mathematics
(STEM) fields using visualization will be
more interesting and can surely improve
the effectiveness in the learning and
teaching process. Besides making it easier
for students to understand the STEM
subjects, facilitates teachers in teaching
STEM lessons material in the classroom.
Visualization
Visual means of processed information
is referred as Visualization. The foremost
objectives
of
any
visualization
techniques
are
data
exploration
and
communicating
information
effectively to the intended audience.
Data Exploration is the practice of
using visualization techniques to find
unforeseen
relationships
between
data points or sets of points from huge
databases. Once a relationship has been
found, a similar visualisation will be used
to communicate that will be a reference
to others. Visualization techniques can
also be applied to information that is
already known and it has the potential
to organize large amounts of data in
meaningful ways. Visualizations are
often static, dynamic and interactive,
allowing users to manipulate the data
that they observe. Static visualizations
are the one that do not change with
time. Dynamic visualizations are
those in which the graphical elements
being displayed can change with time.
Interactive
visualisation
involves
humans’ interaction with computers
to create graphic illustrations of
information.
Visualization in Education
The application areas of Visualization
are many, one such area is Education.
Thomas Carpenter and James Hiebert
in[1] address the role of visualization in
education and also represent a framework
for knowledge representation in the
domain of education way back in early
1990s. The purpose of any visualization
to be used in an educational context
is to facilitate the learning of some
knowledge in the form of algorithm,
concept, idea, relationship, fact, decision
making and application. In order to
accomplish this visualization must make
connections between knowledge of the
learner has and the knowledge being
taught. Knowledge of a learner might
be of Fragmented and knowledge being
taught might be Coherent. Fragmented
knowledge results in domains in
which the learner has had little or no
experience. Coherent knowledge refers
to a wealth of information to draw upon
from a domain.
STEM Education
Education in any domain can be viewed
as the externally facilitated development
and representation of knowledge.
Education particularly in the field of
Science, Technology, Engineering, and
Mathematics (STEM) subjects is quite
difficult for the students to understand.
This is because the STEM subjects are
not simple and it requires high levels
of thinking and reasoning from the
students, especially in the areas of
Concepts and Logics. In addition, the
subject material is also quite difficult to
teach. Teachers, as educators, need a
S.No Tools
Science Tools
1.
ChemSketch
2.
Step
Technology Tools
3.
gEDA
4.
Player Project
specific way to teach in order to make the
material easily understood by students.
To make teaching more attractive and
effective, it needs a learning model or
a medium which can provide a concrete
conceptual, illustration, and definitive,
in order to improve the effectiveness of
the learning process and to achieve the
learning objectives.
Visualization tools in STEM Education
Teachers and students have long been
using charts and graphs to analyze and
make sense of data. The effective use
of any technology in teaching requires
thoughtful consideration and planning.
Technology has brought these tools to
a new level. In order to design effective
visualizations in STEM subjects it is
necessary to know the level of audience.
Table 1, list some of the open source
visualization tools used by educators to
provide STEM lessons’ material in the
classroom. This visualization tools acts
either as a primary medium or as an
alternative tool in the teaching learning
environment.
Features
•
•
•
•
Tool for learning Chemistry
Includes comprehensive chemical drawing package,
Offers drawing of polymers, organic elements and structures
h t t p : //w w w. a c d l a b s . c o m /r e s o u r c e s /f r e e w a r e /
chemsketch/
• Tool for learning physics
• Simulator supports classical mechanics, particles, springs,
gravitational and coulomb forces, collisions, molecular
dynamics, and much more.
• https://edu.kde.org/applications/all/step
• Refers to GPL'd Electronic Design Automation tools,
• Supports the teaching of electronics to the students of
technical institutions.
• offers various analog, digital simulation and printed circuit
board (PCB) layout capabilities.
• http://git.geda-project.org/
• Supports teaching of robotics in technical institutions
• Provides a simulated network interface for sensors and to
control robots
• Simulates the 2D and 3D robotic interaction in environment.
• http://playerstage.sourceforge.net/index.php?src=index
Continued on Page 41
CSI Communications | November 2014 | 10
www.csi-india.org
Engineering Tools
5.
OpenModelica • Tool for modelling and simulating industrial applications
such as control system design, embedded system modelling
and numerical algorithms
• https://www.openmodelica.org/download/download-linux
6.
OpenSCAD
• Provides a software for creating solid 3D Computer Aided
Design models
• offers two modeling techniques such as constructive solid
geometry and extrusion of 2D outlines
• http://www.openscad.org/about.html
Mathematical Tools
7.
About the Authors
8.
Maxima
GeoGebra
• Tool for Algebra and calculus teaching
• Manipulates and provides good numerical results
• http://www.gnu.org/software/maxima/
Conclusion
Visualization technology will provide
a detailed representation and creates
interesting definitions of Concepts,
Theories, Formulas, and the Principles
that are contained in the STEM materials.
Visualization tools can also be useful for
bridging the gap between domains of
knowledge and applications. Knowledge
base of the audience is much needed
for customizing and designing effective
visualizations. There are visualization tools
that are available as open source products,
which allow students and educators to
customize the tool and to learn the domain
of education.
References
• The award-winning math app combines tools for, arithmetic
algebra, calculus and geometry.
• Supports instructors to create worksheets and suitable
teaching aids for teaching maths to the students of schools,
colleges and university.
• http://www.geogebra.org/cms/
[1] Hiebert, James & Carpenter, Thomas
P. "Learning and Teaching with
Understanding"
Handbook
on
Mathematics Teaching and Learning1992.
[2] h t t p : //e n . w i k i p e d i a . o r g /w i k i /
Interactive_visualization
[3] h ttp://w w w. dpi . s t at e . nc . us /c t e /
n
program-areas/technology/
A.B. Karthick Anand Babu is member of CSI and Managing Director, KK Infotech, Thanjavur, Tamilnadu. He has rich experience in teaching and
software development. He can be contacted through karthickanandbabu.ab@gmail.com.
D. Maghesh Kumar is devoted Assistant Professor of Faculty of Software Engineering, Periyar Maniammai University,Tamilnadu. He has more
than 20 years of teaching experience. His research area includes “Big Data” , “Cloud Computing” and “Internet of Things”. Reach him through
maghesh.d@gmail.com
G. Raja Raja Cholan, Assistant Professor,Department of Computer Science and Engineering, PRIST University. He has also served as a Coordinator
for Centre for Knowledge Management. His primary research area includes Network Security, Internet of Things and Data Science. He can be
reached at gsrajarajacholan@gmail.com
CSI Communications | November 2014 | 11
Technical
Trends
Dr. B. Eswara Reddy* and Mr. K. Rajendra Prasad**
*Professor, Dept. of CSE, JNTUA, Ananthapur
**Associate Professor, Dept. of IT, RGM College of Engg. & Tech.,Nandyal
Visualization Tool for Data Mining
Introduction
Characterizing and classifying the data
is an emerging need for data mining
functionality. The aim of data mining is
to extract and classify the data based on
the data characteristics. We may have
pre-requisite to prior knowledge about
the number of distinct data classes for
any data mining functionality. For this
valuable determination, we introduce the
visualization tool called as Visual Access
Tendency (VAT), which is used to detect the
information of number of data clusters (or
classes) in visual form. The VAT has been
introduced by author Bezdek. The visual
pattern apparent will presents with the more
clarity of visual results for data classes (or
clusters). A very beginner of data clustering
can makes use of this tool for accessing of
data clusters from the organized data.
Motivation
Many algorithms of data clustering such
as k-means, hierarchical, density based
clustering algorithm etc have to produce
the clustering results without knowing
any prior knowledge about number of
clusters. Suppose the user has trying the
clustering results with incorrect k value in
the k-means, then the k-means procedure
may also produce the inaccurate clustering
results. This is the key motivation for
choosing of visualization tool (VAT) and
it has capable for detecting the number of
clusters (k value) as correctly. Thus, this
visualization tool helps for achieving the
best clustering results.
History
Initially, the author Bezdek has developed
the algorithm of VAT tool for classifying
of clusters. Later he has modified with the
spectral approach called as SpecVAT which
works better than VAT where in the cases of
tough data such as it may be huge, higher
dimensionality etc. He has also developed
another version iVAT (Improved VAT) for
the cases of path based data. Therefore,
we can use any one of the visualization tool
among the three based on our degree of the
complexity of the data.
Visual Access Tendency (VAT)
The following key diagram introduces
the processing steps of VAT tool.
Data Objects
The organization of data consists of a set
of data objects which is further clustered
based on the similarity features for
Fig. 2a: Dissimilarity matrix ‘R’ and its dissimilarity image ‘I’ (before applying the VAT tool)
Fig. 1: Processing steps of VAT
every two-element subset data objects.
Initially, the data is organized as data
matrix (n x m) form which can be shown
as follows with n number of objects and
m number of properties
O\P
P1
P2
...............
Pm
O1
X11
X12
..................
X1m
O2
.
.
.
On
Xn1
4.
Xn2
..................
Xnm
These n data objects are compared
using the distance measures such as
Euclidean, Mhanttan, and Minkowski etc
for obtaining the dissimilarity matrix R.
The following matrix is represents the
dissimilarity matrix R (with size n x n)
O\P
O1
O2
...............
On
O1
0
D12
..................
D1n
O2
.
0
.
.
On
Dn1
..................
0
Dn2
Dissimilarity Matrix and its VAT Image
The dissimilarity matrix R is the input of VAT,
and the VAT tool outputs the VAT Image
with finite number of visual squared shaped
dark blocks. Thus, we detect the number of
clusters by counting of square shaped dark
blocks along the diagonal of VAT Image. The
accessing of number of data clusters by VAT
tool is depicted by the following results
Advantages of VAT Tool
1. It presents the information in visual
so that even normal user also can
able the number of clusters
2. The VAT tool is uses only the Prim’s
logic, so there is no complexity about
understanding of how it works
3. We use this visualization to any kind
of data such as text, image, audio,
CSI Communications | November 2014 | 12
Fig. 2b: After applying VAT tool
and video etc for defining of clusters
or classes
It is possible to extract the correct
k value; so that it is useful for the
k-means
Limitations
1. It takes much time for solving of k
value where in the cases of big data
2. We have less clarity of visual results
if the data clusters are overlapped
3. The visualization results will depends
on distance measures
Designing of VAT Tool
The VAT uses the logic of Prim’s
algorithm for the major purpose of
changing the current indices of the data
objects. In this way, the indices of data
objects are reordered by the VAT tool.
Reordering the indices of data objects
would shown the number of clusters by
squared shaped dark blocks along the
diagonal in the VAT Image, this is clearly
shown in Fig. 2a. The main aspect of VAT
tool is to display the hidden clustering
structure for a set of data objects. The
logical steps of VAT tool are described
as follows
1. Choose the longest edge weight
e(vi,vj) from the dissimilarity matrix R
Index=1;P(index)=vj; Set I = { };
J = {1,2,…,n};
I = I ∪ {j} and J = J – {j}
2. Use Prim’s Logic
For the interactions t = 2,…, n
Select (i,j)∈ arg minp∈I,q∈J {Rpq} ;
P(t) = j;
I = I ∪ {j} , and J = J – {j}
3. Reordered dissimilarity matrix
[RRi,j] =[RP(i),P(j)]
www.csi-india.org
4.
Display the VAT Image of RR
Let R=[0.00 0.73 0.19 0.71 0.16;
0.73 0.00 0.59 0.12 0.78;
0.19 0.59 0.00 0.55 0.19;
0.71 0.12 0.55 0.00 0.74;
0.16 0.78 0.19 0.74 0.00];
Tracing steps for VAT Tool Algorithm for
the Input R(Dissimilarity Matrix)
Finally, we display the VAT image
in MATLAB by executing the command
of imshow(RR), then it displays image of
Fig. 2b. Hence, we can extract the number
of clusters information from this visualized
image.
Conclusion
We make use of visualization tool as VAT
Step No.
Iter. No.
especially in the data mining. The VAT
tool visualizes and reveals the similarity
structure of data objects. Hence we have
a prior knowledge about the number of
data classes (or clusters) which helps
the further processing of data mining
functionality. Specifically this visualization
tool has been used for the purpose of
unsupervised learning. In the k-means,
we can attempt the good clustering
results by this prior k value. Other
clustering algorithms are also required the
knowledge about number of clusters.
[3]
[4]
[5]
References
[1] Liang Wang, James Bezdek, Enhanced
Visual Analysis for cluster tendency
Choose the Max edge P
from R (In Step1) or
Choosing of Min Edge
from the vertices I to J
(In Step 2)
I
[6]
J
[7]
1
-
(2,5)-Max Edge
P(1)=5
{5}
{1,2,3,4}
2
3
t=2
t=3
(5,1)-Min Edge
(1,3)-Min Edge
P(2)=1
P(3)=3
{1,5}
{1,3,5}
{2,3,4}
{2,4}
4
t=4
(3,4)-Min Edge
P(4)=4
{1,3,4,5}
{2}
5
t=5
(4,2)-Min Edge
P(5)=2
{1,2,3,4,5}
{ }
About the Authors
[2]
[8]
assessment and data partitioning,
EEE Trans. on Knowledge and Data
Engineering, 22(10), 1401-1413(2010).
http://www.ece.mtu.edu/~thavens/
pubs.html
http://www.ece.mtu.edu/~thavens/
code/VAT.m
http://www.ece.mtu.edu/~thavens/
code/iVAT.m
Timothy C Havens ,and James
C Bezdek, An Efficient Formulation
of the Improved Visual Assessment
of Cluster Tendency (iVAT) Algorthm,
IEEE Trans. on Knowledge and Data
Engineering. 22( 10), 1401-1413(2010).
Liang
Wang,
James
Bezdek,
Automatically
Determining
the
Number of Clusters in Unlabeled
Datasets, IEEE Trans. on Knowledge
and Data Engineering, 21(3), 335349.(2009).
B Eswara Reddy, K Rajendra Prasad,
Reducing runtime values in minimum
spanning tree based clustering by
visual access tendency, International
Journal of Data Mining & Knowledge
Management Process, 2(3), 11-22
(2012).
James Bezdek, VAT: A Tool for Visual
Assessment of Cluster Tendency, Proc.
Int’l Joint Conf. Neural Networks. 22252230 (2002).
n
Dr. B. Eswara Reddy Graduated in B.Tech.(CSE) from Sri Krishna Devaraya University in 1995. He received Masters Degree in M.Tech.
(Software Engineering), from JNT University, Hyderabad, in 1999. He received Ph.D in Computer Science & Engineering from JNT University,
Hyderabad, in 2008. Currently he is working as professor in the Dept. of CSE, JNTUACE, Anantapur. His research interests include Pattern
Recognition & Image Analysis, Data Warehousing & Mining and Software Engineering. He is a life member of CSI, ISTE, IE, ISCA and
member IEEE.
Mr. K. Rajendra Prasad has a research scholar at JNTUA, Anantapur. He has completed B.Tech(CSE) at RGM Engg College, Nandyal and
M.Tech(CSE) at KBN College of Engg, Gulbarga. Currently, he is pursuing PhD (CSE) at JNTUACE, Ananthapur. He is life member of CSI and
a member of IEEE.
CSI Communications | November 2014 | 13
Technical
Trends
Sreeja Ashok*, Dr. M. V. Judy** and N. Thushara Vijayakumar***
*JRF, DST Funded Research Project, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham University, Kochi
**Associate Professor, HOD, CS and IT, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham University, Kochi
***JRF, DST Funded Research Project, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham University, Kochi
Information Visualization in Gene
Expression Data
Significance of Visualization in Gene
Expression Data
Bioinformatics is an exploration area
that manages huge amount of data.
Gene expression analysis is a significant
instance of Bioinformatics which tries to
identify expression levels of genes through
microarray experiments. Gene expression
data generated through this process
typically represents thousands of gene
expressions across multiple experiments.
Mostly, gene expression data are noisy
and of high dimensionality which makes
the analysis process difficult. They
have to be transformed into a reduced
set of genes for subsequent analysis.
Transforming large-scale gene expression
data into a meaningful set of data can be
done through preprocessing techniques
and through feature reduction methods.
The primary objective of analysis could
be to find functional groupings of genes
by discovering similarity or dissimilarity
among gene expression profiles, or
predicting the pathways of previously
uncharacterized genes. This can be
done through different supervised and
unsupervised methods. The challenge
is to interpret and to make sense out of
this processed information. Representing
the analysis output through a suitable
visualization framework simplifies the
reasoning process and allows users to
easily explore the relationships among
genes and conditions.
Visualization Process
Data mining and Visualization techniques
work hand in hand to enable complete
elucidation and user interpretation of
large datasets. The sandwich technology
that combines both techniques is
useful in molecular biology where large
volumes of sequences and gene arrays
can be efficiently mined and represented
in graphs, trees and chains to extract
meaningful information. Visualization
process of gene expression data focuses
on data preprocessing, data reduction,
clustering/classification,
visualization
technique and Analysis & Knowledge
discovery. The visualization process flow
is shown in below Fig. 1.
Genes that contribute noise will
lead to wrong analysis and results.
Preprocessing techniques helps in
converting raw data to meaningful
biological data by removing noise, low
intensity, bad quality and empty spots from
gene expression data using Normalization,
Filtration, Sampling, Extraction, Labeling,
Scanning etc. Feature reduction procedure
is an effective approach to downsize the
data. For example, when the dataset has
thousands of genes and few samples and
the objective is to classify novel samples
into known disease type, dimensionality
Fig. 1: Visualization process flow
reduction methods helps in finding
a subset of informative genes which
can be processed for further analysis.
Classification helps in understanding the
complex relationship/interaction among
the various conditions and features of a
biological object. For example, a training
dataset has diseased and normal cells and
when a new cell is obtained, classification
process has to automatically determine
whether it is normal or a diseased
cell. Cluster analysis helps in grouping
genes with similar function or grouping
samples with similar expression profiles.
Visualization techniques help in visually
inspecting and interacting with two/
three dimensional view of processed data
set. Following table shows the available
visualization techniques.
Available Visualization Techniques
Visualization
techniques
Objective
Methods
Geometric
techniques
Visualization of geometric transformations and
projections of the data
Scatterplots Matrices , Hyperslice, Parallel Coordinates, Projection
Pursuit Techniques, Prosection Views, Landscapes
Icon- based
techniques
Visualization of the data values as features of icons
Chernoff-Faces , Stick Figures ,Shape Coding, Color icons, Tile Bars
Pixel-oriented
techniques
The basic idea of pixel-oriented techniques is to map
each data value to a colored pixel. Each attribute value
is represented by a pixel with a color tone proportional
to a relevance factor in a separate window
Query-Independent Techniques
-Simple Techniques
-Recursive Pattern Technique
-Space-Filling Curves
Query-Dependent Techniques
-Spiral Technique
-Circle Techniques
-Axes Technique
Hierarchical
techniques
Visualization of the data using a hierarchical
partitioning into two- or three-dimensional subspaces
Treemap , Cone trees , Dimensional Stacking , InfoCube ,Worldswithin-Worlds , Box plots
CSI Communications | November 2014 | 14
www.csi-india.org
Graph-based
visualization
Graphs (edges + nodes) with labels and attributes
are used where emphasis is on data relationship
(databases, telecom)
Useful for discovering patterns
2D and 3D graph
Basic Graphs (e.g., Straight-Line, Polyline, Curved-Line, Orthogonal
Graphs)
Enrichment Map
Distortion
techniques
Global context/view of the information content.
Hyperbolic tree , Graphical Fisheye view, Perspective wall , Polyfocal
Display , 2D Bifocal Display
Dynamic/
Interaction
techniques
Providing interaction mechanism that make it possible
to manipulate visualization effectively and effortlessly
Brushing , Linking , Zooming & Panning,
Detail on Demand , Filtering (Selection, Querying), Data-toVisualization Mapping, Projections
Matrix
Techniques
To simultaneously explore the associations of up to
thousands of subjects, variables, and their interactions,
without first reducing dimension
Heat map
Hybrid
Techniques
Integrated use of multiple techniques in one or
multiple windows to enhance the expressiveness of
the visualizations
Scatter plot of icons with dynamic zooming and mapping
Dynamically link and brush scatterplot matrices, star icons, parallel
coordinates.
Graph Matrix Visualization.
Brief summary of some of the prominently
used visualization techniques for gene
expression data are given below
•
Heat map: Provides an overview of
the data. A colored matrix display
will represent the matrix of values
as a grid, number of rows equal to
the number of genes being analyzed,
and the number of columns equal
to expression levels (Fig. 2a). A big
challenge for interpreting patterns in
a colored matrix is that the rows and
columns need to be re-ordered in a
meaningful way.
•
Scatter plots : Scatter plots are
useful for pair wise comparisons,
finding which genes are excessively
expressed, they provide an overview
of the multivariate distribution of
expression values (Fig. 2b)
•
Parallel
coordinates:
Parallel
coordinates are a common information
visualization technique for highdimensional data sets. Expression
data for each gene corresponds to a
dimension in the data set, with data for
each gene being represented by one of
a series of parallel vertical axes. Colorcoding of expression profiles are very
efficient (Fig. 2c)
•
Dendrogram:
The
dendrogram
method plots the hierarchical
tree information obtained as a
graph from the cluster pane. The
numbers along the horizontal axis
represent genes and the height of
the diagram indicates the distance
between the genes. Different color
codes can be assigned to represent
null values or zero values. Shades
represent intensity or magnitude of
expression(Fig. 2d)
Conclusion
Every day new discoveries are made in the
field of molecular biology & genetics and
sheer volume of data comes out from studies.
These vast quantities of heterogeneous,
2008.
[2] Tangirala Venkateswara Prasad and
Syed Ismail Ahson , “Visualization
of microarray gene expression
data”, Bioinformation by Biomedical
Fig. 2: Visualization techniques for gene expression data
dynamic
and
largely
unprocessed
information have to be transformed into
a coherent and user friendly format easily
accessible to all. Analytical methods
together with visualization techniques play
a major role in exploring, analyzing and
presenting meaningful inferences.
References
[1] Ashraf S Hussein “Analysis and
Visualization of Gene Expressions
and Protein Structures”, Journal of
Software , Vol. 3, No. 7, October
Informatics Publishing Group, May
03, 2006.
[3] Wegman, E “ Hyperdimensional data
analysis using parallel coordinates.”
Journal of American Statistics
Association 85, 664-675.
[4] Pavlopoulos, G A, Wegener, A L,
& Schneider, R “A survey of
visualization tools for biological
network analysis. Biodata mining”,
1(1), 1-11.
[5] Chun Tang, Li Zhang and Aidong
CSI Communications | November 2014 | 15
About the Authors
Zhang , “Interactive Visualization and
Analysis for Gene Expression Data” ,
HICSS-35: 35th Hawaii International
Conference on System Sciences.
[6] Poornima. S, Dr. J Jeba Emilyn,”
A
Comparative
Analysis
on
Visualization of Microarray Gene
Expression Data”, ISSN: 1694-2108 |
Vol. 12, No. 1. APRIL 2014.
[7] Purvi Saraiya, Chris North, Karen
Duca, “An Evaluation of Microarray
Visualization Tools for Biological
Insight”, IEEE Symposium on
Information Visualization 2004,
October 10-12, Austin, Texas, USA.
[8] Janne Nikkila, Petri Toronenb,
Samuel Kaskia, Jarkko Vennaa, Eero
Castrenb, Garry Wongb,” Analysis and
visualization of gene expression data
using Self-Organizing Maps”, Neural
Networks 15 (2002) 953–966.
n
Sreeja Ashok is currently working as JRF for a DST Funded Research project at Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham
University, Kochi. She has completed MCA, has 14 years of experience in IT industry (Avenir & Wipro Technologies) with expertise in Software
Engineering, Project Management, Quality Management & Data Analysis, 2 years of teaching experience.
Dr. M. V. Judy is Associate Professor, Head of the Department of CS and IT at Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham
University, Kochi and also principle Investigator for DST Funded Research Project under Cognitive Science Research Initiative. She has
completed MCA, Mphil and Ph.D in Computer Science from reputed universities/institutes and has 12 years of teaching experience.
N.Thushara Vijayakumar is a former lecturer at NIT Calicut, completed M-Tech in Genetic Engineering from SRM University, Chennai and
B-tech from Anna university, Chennai. Currently working as JRF for a DST Funded Research project at Amrita School of Arts and Sciences,
Amrita Vishwa Vidyapeetham University, Kochi.
CSI Communications | November 2014 | 16
www.csi-india.org
Technical
Trends
Rishav Singh* and Dr. Sanjay Kumar Singh**
*Working in Infosys
**Associate professor, IIT-BHU, Department of Computer Science and Engineering
Big Data Visualization using Cassandra and R
In the current world each organization
is moving towards big data. Big data
basically consist of data storage and data
analysis. Earlier people used to store
only important data, since there was
no cost effective way of storing all the
data. But most of the organisations and
researchers felt the need of huge volume
of data for building up mathematical
models, so that complex problems can
be solved. However, in the last few years
many frameworks and databases have
been designed to store huge volume
of data using commodity hardware.
Whenever we talk about big data there
are 3 V’s that come to our mind Velocity
(the rate at which the data is growing),
Variety (structured, semi-structured and
unstructured) and Volume (Size of the
data in terms of petabytes or xetabytes).
There are many solutions which have
been proposed for the same, but most of
the time people are not aware of which
framework or database to choose. While
creating a database for any particular
application, the architect should
consider three features: consistency,
availability and partition tolerance.
Consistency means even if concurrent
updates are happening, users will get
the updated result irrespective of the
place from where they are accessing the
data. Availability means data should be
available to the users 24*7 irrespective
of the load on the server. Partition
tolerance means even in the case of
the partial failure the system should
be functional. Brewer suggested a CAP
theorem, which is applicable for all the
databases. According to him a database
cannot have all the three features, i.e
consistency, availability and partition
tolerance. They can have only two
features out of the three, for Example:
Consistent & Available: postgres
My SQL, SQL server.
Available & Partition Tolerance:
Cassandra, RIAK, Voldemort, CouchDB.
Consistent & partition tolerance: Neo4J,
MongoDB, HBase, Hypertable, Redis.
Cassandra
There are many distributed database
systems available but they have only
two features out of the three desired
features. Cassandra is a distributed and
decentralized database, which has high
availability and partition tolerance, but at
the same time it is eventually consistent
which means that its consistency level
can be increased by sacrificing the
availability. It is capable of storing all the
forms of digital data i.e structured, semi –
structured and unstructured data.
Cassandra[1] was designed with
a motive to have a database that
should be able to write at a very high
speed irrespective of the load on the
server or even if most of the nodes in
the cluster are dead or unavailable. In
Cassandra[2] the write operation is very
fast as compared to the read operation.
During the write operation, data is first
written to the commit log along with the
instructions for the durability purpose
and the flag bit is set to one,
then the data is moved to the
memtable which resides in RAM,
when the memtable exceeds a
given threshold value the data
is flushed into the SStable which
is present in the secondary
memory. Once the data is written
in the SStable, flag bit is again set
to zero or if anything goes wrong
the data will again be sent to the
memtable from the commit log.
But the user gets the confirmation that
the data is written successfully, when the
data is first written inside the commit log
file, and he does not have to wait for all
this process to complete.
Cassandra is a distributed system
and all of us know that the distributed
system works on network, which is one
of the highly unreliable resource in this
world, we don’t know when the traffic on
the network is going to increase/decrease
or it will get disconnected. Keeping this
thing in mind Cassandra was provided
with a mechanism known as HintedHandoff, which means that if a user wants
to write any data on a particular node(A)
which is unavailable, then a hint will be
written on its neighbor node(B), stating
that whenever node(A) comes back
node(B) will pass this hint.
R
Many organizations are moving towards
big data analysis and visualization. R
is an open source tool which is being
used by most of the analysts for building
up a mathematical model such as
recommendation system and predictive
system. To build up such models many
optimized algorithms packages[3] are
present in R such as SVM, kNN, Decision
Trees, outliers, Naïve Bayes, adaboost ,
JRip and many more.
R has a Cassandra package
(RCassandra[4]) to access the functionality
of apache cassandra cluster such as login,
updates, queries and read/write operation
without using java.
Following plot shows the iris data in 4
dimensions which has been first inserted
into Cassandra database using R and then
read the same data for analysis. Plot()
function is used for the representation of
data.
Cassandra Vs SQL:
The SQL was designed with a motive to
have database that can store only the
normalized form of data because at that
time the hardware cost was very high, but
due to normalization the query needs to
refer multiple tables for fetching a particular
record, due to this the latency time of the
query is very high and which affects the
overall performance of the application.
SQL was designed to handle data
in terms of Gigabytes and up to some
extent Terabytes. But the Cassandra can
handle the data in terms of petabytes and
xetabytes.
In SQL the table schemas are defined
upfront and the users are forced to insert
data for each column or else they have to
use the NULL value.
Scaling up and scaling down depending
upon the load is very expensive in SQL, but
in Cassandra you just have to plug in a new
node or remove the node. No configuration
needs to be done on the cluster side.
CSI Communications | November 2014 | 17
About the Authors
In SQL first the database is designed,
then the queries are identified to solve the
problem. But in Cassandra first the queries
are identified and then the data is organized
around the queries. There are no unions and
joins. Each query will refer to a single table.
Since SQL is a 100% consistent
database they need to use locks on
each transaction and if in a distributed
system the locks are not used properly
it will either lead it to starvation or
deadlock. Most of the time people say
that my data is important and it needs
to be consistent, but there are many
organizations such as Google, Facebook,
Amazon which have an inconsistent
database although there data is very
important.
References:
[1] http://cassandra.apache.org/
[2] http://www.datastax.com/
[3] http://en.wikibooks.org/wiki/Data_
Mining_Algorithms_In_R
n
[4] http://cran.r-project.org/
Rishav Singh is currently working in Infosys and also pursuing his Ph.D (part time) from Indian School of Mines, Dhanbad.
Dr. Sanjay Kumar Singh is an Associate professor in IIT-BHU in the department of Computer Science and Engineering.
His main area of interest are Biometrics, Computer Vision, Image Processing, Video Processing, Pattern Recognition and
Artificial Intelligence.
CSI Communications | November 2014 | 18
www.csi-india.org
Research
Front
Dilip Kumar Dalei*, B. V. Hari Krishna Nanda** and N. Venkataramanan***
*Scientist (ANURAG), Defence R & D Organization (DRDO), Hyderabad
** Scientist (ANURAG), Defence R & D Organization (DRDO), Hyderabad
*** Scientist (ANURAG), Defence R & D Organization (DRDO), Hyderabad
Visualization Methods for Vector Fields:
An Insight
Introduction
Scientific Data Visualization is the branch
of science which deals with transformation
of scientific data into meaningful visuals
to comprehend and gain insight into the
underlying scientific phenomena. The
output data from scientific experiments
and simulations are normally sampled
in 2D or 3D grids. The grids provide
an efficient data structure for data
storage and retrieval. A variety of grids
with different topology and geometry
are constantly used for numerous
applications. The choice of a right kind
of grid depends solely on the application
domain. These grid-based data are then
processed by different visualization
methods to generate visuals suitable for
human interpretation.
Over the years, researchers have
devised various methods, which form the
core part of any scientific visualization
system. There are various schemes of
classification for visualization methods.
Based on type of input data, these
can be broadly put into three major
categories, viz. Scalar, Vector and Tensor
visualization methods.
Scalar methods operate on the
data that represents scalar quantity viz.
temperature, pressure, density etc. In
vector field visualization, we deal with
vector quantity based data (like velocities).
The Tensor data type is more complex
than other ones. They generally arise
from applications such as engineering
analysis (Stress-Strain tensors), molecular
diffusion measurements etc.
What are Vector Fields
Vector fields are defined as the collection
of vectors over a region of space in
the domain. Mathematically, they are
represented as a vector-valued function
that assigns a vector at each point of the
field. The examples of vector fields are
gravitational field, electrical field that
surrounds charges, magnetic fields and
velocity fields (Fig. 1).
Fig. 1: Vector field with equation
Vx = x, Vy = -y in Matlab
In a vector field the vector
quantities can vary over space and time.
A static vector field represents vectorvalues that change over space, while a
time-dependent one changes over both
space and time. One of the important
applications of vector field visualization
is study of flow (velocity). In case of
flow, the field is termed as velocity
field, which is frequently encountered
in vector visualization arena. We have
assumed a flow vector field for the study
of visualization methods. The concepts
are still applicable to other vector fields.
The flow field is further divided into two
categories: steady (time-independent)
and unsteady (time-dependent).
Visualization Methods
The vector field needs to be visualized
effectively
by
considering
both
magnitude and direction simultaneously.
The problem gets challenging if the data
size is large and time-variant. In recent
times, vector visualization techniques
have received widespread attention.
This is due to extensive research in
areas such as Metrological simulation,
Medical blood flow, Computational
simulation of air flow around aircrafts,
ships and differential equation systems.
The vector fields representing fluids
are transparent in nature, thus making
the flow pattern invisible to us. The
visualization discerns the flow patterns
to convey its qualitative and quantitative
information. To get an insight of vector
field it is necessary to explore the flow
both locally and globally. Based on the
density of representation[1], the vector
based methods can be classified as local
and global techniques. A local technique
visualizes only a portion of domain, while
the complete flow is considered in global
techniques.
The local techniques create a
representation based on flow lines –
streamlines, streaklines and pathlines
etc. The flow lines are trajectory of
mass-less particles through the vector
field. They describe flow path with start
(come from) and end (will go). On the
other hand, global techniques visualize
the entire flow in single picture with
minimal user intervention. Examples
are line plots (hedgehogs), arrow plots,
glyphs, texture based methods (LIC
& Texture Splats). They give a sense
of vector magnitude and direction at
a point. E.g. at any point what is the
strength of flow and direction.
Lines, Arrows & Glyphs
These are the elementary visualization
techniques to make an overall picture of
the vector field. They put icons such as
lines, arrows or 3D objects to highlight
local features (magnitude, direction,
time dependency) of the field. The icons
are drawn directly at each data point.
Their scaling is controlled according to
magnitude and orientation of vectors.
Fig. 2: Arrowplot for Air flow over a city model
These methods are quite suitable
for 2D vector fields. In 3D, they
pose the problem of cluttering and
overlapping. As the number increases,
it is difficult to understand the
position and orientation of the field.
CSI Communications | November 2014 | 19
There is also no satisfactory scaling
mechanism exists. With large scaling,
they occlude each other. If the scaling
is fixed to study directions only, then
the magnitude information is lost.
Spot Noise & Line Integral Convolution
Spot noise and Line Integral
Convolutions (LIC) are texture synthesis
methods to visualize flow. Both employ
same
mathematical
principle
of
convolution to create the visual effect.
Spot Noise distributes a large number of
small intensity functions – called spots
– over the vector field. The shape of the
intensity functions is deformed by the
vector field. In LIC, a random noise is
convoluted with a piece of streamline. The
final result is a smeared image, which can
give the idea of fluid motion.
Flowlines: Streamline, Streakline,
Pathline
The flow lines visualize the flow starting
from a particular location. They are
calculated as integral lines that simply
assume the path traversed by a particle if
dropped in the vector field. The examples
of flow lines are Streamlines, Streaklines
and Pathlines. The lines are identical in
a steady flow, where the velocity field
remains constant over time. But, in
unsteady flow they are different. They
are displayed using standard graphical
primitives (points, lines, arrows).
Mathematically, the flowlines are the
solution of simple ordinary differential
equations (ODE) as given below for a 2D
vector field.
dx = vx(x(t), yt) dy = vy(x(t), y(t),t)
dt
dt
Intial Conditon: At t=0 x(0),
Fig. 3: 2D Line Integral convolution texture
applied to space shuttle[4]
Textured Splats
It is an extension of a popular volume
rendering technique, called splatting to
visualize vector data. It also uses texture
as a medium of visualization. Spaltting
is the projection of data volumes on a
2D viewing plane. The splats are finally
composited on top of each other to
produce the final image. Texture splatting
combines multiple textures and blend
them accordingly.
y(0)
The clear advantage with flow line
methods is the ease of implementation
and rendering. But the technique heavily
relies on seed point (start point of flow)
placement, which becomes a major
drawback. The efficient seed generation
is still an active area of research. A
significant amount of user’s involvement
and prior knowledge of vector field is
required to generate effective flow lines.
The other issue is related to number of
flowlines to be generated. With large
number, the computation becomes
expensive.
Streamlines represents a family
of curves that are tangential to fluid
flow everywhere. At any instant of time
streamlines provide a snapshot of a region
of the field. A streamline start from a given
initial position (seed point) and move
along the lines tangential to the vectors.
In an unsteady flow, streamlines keep
changing as the vector at each point varies
with time.
The streamlines mostly don’t
intersect each other, as there cannot
be two velocities at the same point.
The streamlines are easier to compute
compared to others, because they have
no temporal Interpolation. The technique
is better suited for static visualization.
The streamlines are further extended to
encode more spatial information in 3D
through the use of geometrical objects.
Some of the extensions are streamtubes,
streamribbons, streamsurfaces, streamballs and streamarrows.
The path lines are the curves
describing the traversals of all the
particles. They are identical to streamlines
in a steady vector field. The path lines are
drawn only in forward direction. But an
unsteady field has different pathlines and
streamlines. At every moment the vector
field changes, so the streamlines. This
makes the paths traversed by particles
different. The paths are determined by the
streamline at that time stamp.
The streak line is the locus of all the
particles passed through a certain position.
It is also similar to streamlines when the
flow is steady. In unsteady flow, when
particles are released from a fixed point
they travel along different paths because
of continuous change of vector field with
time. The collection of such points at later
instant of time gives a streakline.
Conclusion
Vector field visualization is an active topic
for research and analysis. An overview of
fundamental flow visualization techniques
are discussed in the current paper. The
aforementioned techniques are applicable
to both 2D and 3D vector fields. In 3D
Vector fields they generally pose issues
such as occlusion, Visual data density,
depth perception. People have come
up with suitable modifications - sparse
representations, color differences, semitransparency and many more to overcome
these issues.
Acknowledgement
We would like to thank members of
visualization wing and Director, ANURAG
for constant support and encouragement.
Fig. 4: Test tornado data rendered using the
textured splat[5]
Fig. 5: Streamlines of air flow over city model
CSI Communications | November 2014 | 20
References
[1] Charles D Hansen, Chris R Johnson
“The
Visualization
Handbook”,
Elsevier Academic Press, pp. 261-277,
2005.
[2] J
van
Wijk,
Spot
Noise,
www.csi-india.org
TextureSynthesis
for
Data
Visualization, ACM SIGGRAPH ‘91.
[3] B Cabral, C Leedom, Imaging Vector
Fields Using Line Integral Convolution
ACM SIGGRAPH ‘93.
[4] Roger A Crawfis, Han-Wei Shen, Nelson
Max, Flow visualization techniques
for CFD using Volume rendering, 9th
International symposium on flow
visualization, 2000.
[5] Roger A Crawfis, Nelson Max, Texture
Splats for 3D Vector and Scalar
Field Visualization, Proceedings
Visualization ‘93 IEEE CS Press.
n
About the Authors
Shri Dilip Kumar Dalei is Scientist at ANURAG, Defence Research & Development Organization (DRDO), Hyderabad. He received his Bachelor
degree in 2004 from NIT, Rourkela, India. He obtained his master degree in the field of Computer Science and Engineering in 2010 from
IIT, Kharagpur, India. His areas of interest are Scientific Data Visualization, Computer Graphics, 3D Displays and GPU programming. He has
publications in International and National Conferences.
Shri B. V. Hari Krishna Nanda received his M.Sc degree in Computer Science from Andhra University in 1992 and M.Tech in Computer Science
& Engineering from Acharya Nagarjuna University in 2010. He is presently working as scientist at ANURAG, Defence Research & Development
Organization (DRDO), Hyderabad. He has more than 20 years of experience in the area of Scientific Data Visualization, Computer Graphics
and Database Management.
Shri N. Venkataramanan received his M. Sc. in Computer Science from University of Mysore. He is presently working as Scientist at ANURAG,
Defence Research & Development Organization (DRDO), Hyderabad. He has more than 20 years of experience in the area of Scientific Data
Visualization and Computer Graphics. He has published research papers in various International and National Conferences.
CSI Communications | November 2014 | 21
Research
Front
Anchal Garg*, Madhurima**, Madhulika*** and Saru Dhir ****
*Assistant Professor, Department of CSE, Amity University Uttar Pradesh, Noida, India
**Assistant Professor, Department of Information Technology, Amity University Uttar Pradesh, Noida, India
***Assistant Professor, Department of CSE, Amity University Uttar Pradesh, Noida, India
****Assistant Professor, Department of Information Technology, Amity University Uttar Pradesh, Noida, India
A Walkthrough & Pathfinder for Research
Novitiates: Google Scholar Vs Microsoft
Academic Search
What Exactly Research is?
In our day to day life we are surrounded
by data, information, knowledge, opinions,
ideas etc. Initially we study, learn and use
them for our own advantage and later,
this information is disseminated for the
benefit of the society and the mankind.
Research is search for new knowledge.
When we extend the knowledge by
digging the unveiled information, we are
doing research. We often come across
this term through peers and while working
on it. Beginners in formal research often
encounter problems searching for relevant
scholarly papers[1]. They generally tend to
waste their enormous time in searching
and very often get baffled and frustrated.
2.
3.
Fig. 1: Showing the scholar.google.com page in the Google
Chrome Web Browser
Tutorial Insight
This short tutorial explains very precisely
and clearly how to begin and understand
the
searching
mechanism
while
researching in very simple steps. We
have explained the steps using Google
Scholar and Microsoft Academic Search.
Searching results are explained below
with the help of snapshots.
The steps below are showing the
searching tricks in Google Scholar.
Step 1- Go to Google Scholar by typing www.
scholar.google.com on the Web Browser
The Google Scholar is an excellent aid
for searching when we have to search for
different articles, thesis, books, abstracts
and research papers across different
disciplines[2]. The Fig. 1 below shows a
snapshot when you type www.scholar.
google.com in the Web Browser’s address
bar.
Step 2- Enter the topic to be searched (For
example artificial intelligence)
Then in the search field provided,
enter the topic for which you want to
fetch information. For example, in the
Fig. 2 below we have typed “artificial
intelligence” to get all the scholarly
articles related to it.
Fig. 2: Showing the topic “artificial intelligence” for searching
Step 3- Click on the
Search button. You will
get the list of scholarly
articles.
Further click on the
search button. This
will give access to a
list of scholarly articles
related to “artificial
intelligence” as shown
in the Fig. 3 below.
The scholarly articles
may include research
papers, thesis, books,
abstracts, etc.
Fig. 3: Showing the results or list of scholarly articles generated after
clicking on the search button.
The boxes represented in the figure are
explained below:
1.
CSI Communications | November 2014 | 22
4.
You can view the
paper by clicking on
this link.
Citations
for
a
particular paper can
be
seen
through
the “Cited by” link.
Here
“Cited
by
1903”indicates that
this paper has been
referred by 1903
paper [3].
People generally have
problems
writing
references. Click on
“Cite” in order to cite/
refer this paper in
your research paper.
You can find MLA,
APA and Chicago
referencing
styles
here. You can change
the referencing style
as required. Each
journal has its own
referencing style.
Clicking on “Since 2010”, you can
view papers published from the year
2010.
5.
6.
7.
It shows the Academic Publisher.
Here the Publisher is Elsevier.
It shows the name of the Journal.
Here the name of the Journal is
“Artificial Intelligence”.
It shows the year of publication. Here
www.csi-india.org
Fig. 7: Showing the topic “artificial intelligence” for searching
Fig. 4: Showing the results after clicking on “Cited by”
year in which the research paper was
published is “1987”.
Step 4- Click on “Cited by” to view papers
that have referred this paper in their research
papers.
For instance, if you click on “Cited by
1903” of the article titled “On agent based
software engineering”, then you will be
navigated to the webpage containing all
Step 5-Click on
“Cite” to refer this
article in your paper.
It
has
several
formats; you can use
any one of them to
add it as a reference
in your paper. Fig.
5 below shows the
Fig. 8: Showing various options for selection after clicking the search
button
Fig. 5: Snapshot of the web page when the user clicks on “cite”.
the scholarly articles that have referred
the above article. This new webpage will
help you find further work on the research
paper titled “On agent based software
engineering”.
Fig. 9: Search Result showing list of publications
snapshot when we
click on “Cite”.
Searching through Microsoft Academic
Search
Similarly, we can search the scholarly
articles on Microsoft Academic Search. The
Microsoft
Academic
Search
searches
research
papers
from various sources
based on the selected
conferences
and
journals.
Fig. 6: Showing the academic.research.microsoft.com page in the
Google Chrome Web Browser
The steps below are
showing the searching
tricks in Microsoft
Academic Search.
Step 1: To search
a
research
paper
on Microsoft Academic search, type
“academic.research.microsoft.com” on the
address bar.
Step 2: Next enter the topic to be
searched. As in previous case, type
“artificial intelligence”.
Step 3: Next, select the “Field of
Study”. For instance, select “Computer
Science” and click on search button as
shown in Fig. 8.
On clicking the search button, you
will be navigated to a new webpage
containing the following information as
shown in Fig. 9.
1. List of renowned authors in your
research area as shown in Fig. 9.
2. List of best rated conferences in your
research area as shown in Fig. 9.
3. List of Publications as shown in Fig. 9.
CSI Communications | November 2014 | 23
information on “International Joint
Conference on Artificial Intelligence”.
The famous authors, keywords and the
list of research papers published in IJCAI
(shown in Fig. 12).
Closing remarks
Fig. 10: Search Result showing list of publications
Fig. 11: Showing the information related to “Journal on Artificial Intelligence”. The most cited
authors, the keywords and list of research papers.
4.
List of best journals in your field of
study (Shown in Fig. 10.)
Scrolling down, we can see the list of
journals relevant to our research field.
Step 4: Clicking on the “AI” shown
in Fig. 10 (extreme left), we will be
navigated to new webpage. The Fig.
11 shows the information related to
“Journal on Artificial Intelligence”. The
most cited authors, the keywords and
list of research papers.
Similarly, clicking on “IJCAI” shown
in Fig. 9 (extreme left), we will be
navigated to the new webpage displaying
This article gives an overview for
effectively searching scholarly articles
using Google Scholar and Microsoft
Academic Search. This tutorial has
provided a step by step procedure for
efficiently searching the relevant articles
related to your research. Google scholar
offers a more user friendly interface as
compared to its counterpart Microsoft
Academic Search. Also, it is more
popular and up to date. Google scholar
has rich repository of academic materials
and citations than Microsoft Academic
Search. The main advantage of Microsoft
Academic Search over Google Scholar
is that more parochial proportionate
service. Also, the data processing in
Google Scholar is more time expensive.
Furthermore, Microsoft Academic Search
is more suitable search for retrieving
results from multidisciplinary fields[4] [5].
We sincerely hope the above
information will prove to be a useful aid to
your research navigation. We expect that
the information shared above facilitates
enough explanation to your unanswered
questions. We also hope that this concise
article will make your search for research
much trivial.
Acknowledgements
Authors are very thankful to Dept. of
Information Technology and Computer
Science & Engineering, Amity School
of Engineering and Technology, Amity
University Uttar Pradesh, Noida, India for
their support to carry out this study.
End Notes
[1]
[2]
[3]
[4]
Fig. 12: Showing information on “International Joint Conference on Artificial Intelligence”
CSI Communications | November 2014 | 24
http://scholar.google.co. in
www.researchgate.net/
http://en.wikipedia.org/wiki/Citation
Orduna-Malea, E, Ayllon, J M,
Martin-Martin, A, & López-Cózar,
E D (2014). Empirical Evidences
in Citation-Based Search Engines:
Is Microsoft Academic Search
dead?. arXiv preprint arXiv:1404.7045.
[5] Ortega, JL, & Aguillo, I F (in
press). Microsoft academic search
and Google scholar citations:
Comparative analysis of author
profiles. Journal of the Association for
Information Science and Technology.
n
www.csi-india.org
Anchal Garg has more than twelve years of teaching experience. She is working as Assistant Professor in Department of Computer Science
and Engineering at Amity University, Noida. Her major research areas are information systems, business process management, data mining,
process mining and higher education and research. She is a member of ACM and IET (UK). She has number of international and national
publications to her credit.
About the Authors
Madhurima did her Master’s Degree in Information Technology from Guru Gobind Singh Indraprastha University, New Delhi. She is at
presently doing her Ph.D in Information Technology from Sri Venkateshwara University. She has 7.6 years of working experience in academic
field. She has number of international and national publications to her credit. She has published one book with the title “Computer Networks”
with Laxmi Publications. Her M.Tech work has been published as a book titled “Video Object Tracking” by LAP LAMBERT Academic
Publishing GmbH & Co. KG, Germany. She is a member of CSI and ACM. Her primary research area includes image segmentation, object
tracking and object oriented testing, ajax and databases.
Madhulika is working as Assistant Professor in Department of Computer Science and Engineering at Amity University, Noida. She holds
diploma in Computer Science Engineering, B.E in Computer Science Engineering, MBA in Information Technology, M.Tech in Computer
Science & Pursuing Ph.D from Amity University, Noida. She has total 8 years of teaching experience. She published almost 15 Research
Papers in National, International conferences and journals. Her primary research area includes video object tracking and soft computing
techniques.
Saru Dhir did her Master's Degree in Computer Science and Technology from Amity University Uttar Pradesh, Noida. She is at presently
doing her Ph.D in Engineering. She has 5 years of working experience in academic field. She has number of international and national
publications to her credit. She is a member of IEEE. Her primary research area includes Software Engineering, Software Testing, Agile
Methodology and databases.
CSI Communications | November 2014 | 25
Article
Amol Dhumane* and Dr. Rajesh Prasad**
*Assistant Professor, Department of Computer Engineering, NBN Sinhgad School of Engineering, Ambegaon (Bk), Pune
**Professor & Head, Department of Computer Engineering, NBN Sinhgad School of Engineering, Ambegaon (Bk), Pune
Active Queue Management
Congestion is a complex process. It
is really a hard task to define congestion
but it can be easily sensed through the
tainted performance of the network.
Sometimes, user experiences long delays
in the delivery of messages, perhaps
significant losses due to buffer overflows.
One of the reasons of high packet loss rate
is the disappointment from the network
to provide early congestion notification
to the sources of traffic. It is essential
to avoid high packet loss rates in the
internet. Packet loss means the wastage
of the resources that have been used by
the packet. Normally network congestion
occurs when a link or node is carries
huge amount of data which deteriorates
networks quality of service.
In the traditional Droptail queuing
algorithm a mechanism of simple queue is
used but the problem with the algorithm
was, it was not able to handle the bursty
traffic.
To sort out the issue of bursty traffic
large buffers at the routers were used, but
it introduced the problem of high queuing
delays in the network especially during
the congestion. Small buffers reduced the
problem of large queuing delays but added
a problem of high packet loss, which will
further result into underuse of the link in
Droptail queues.
So we want a fair and sensible
tradeoff between high link utilization and
low queuing delays.
These limitations of endpoint
congestion are highlighted by peer to peer,
multimedia and short lived web traffic.
These applications mainly required less
delay and jitter, high bandwidth and less
packet drop. This created a need of new
queue management technique against
traditional Droptail queues, which becomes
the point of origin for the development of
new queue management technique known
as “Active Queue Management”.
Since the introduction to IP networks
in 1993 there has been a steady stream
of research output with respect to Active
Queue Management (AQM).
Congestion occurs when the total
requirement of a resource, (e.g. link
bandwidth) go beyond the capacity of the
available resource. Congestion results
into: high latencies in data transfers;
wasted resources due to packet losses;
and network failure in extreme case for
which there is essentially no data transfer
through the network: the throughput
drops to zero and the response time
goes to infinity. The aim would then to
be control congestion or more preferably
avoid congestion. Initial work is done in
the area of congestion control primarily
focused around the responsive flow
(TCP) traffic.
Endpoint
congestion
control
mechanism was employed at end points of
the network by keeping the core network
simple. In contrast AQM mechanism had
taken the advantage of powerful hardware
technology and tried to implement it
in the core network components (such
as routers).
Unlike Droptail, AQM is a proactive
congestion control scheme by which the
network informs the sources when the
incipient congestion is detected. The
network can inform the sources by means
of packet drops or with the help of Explicit
Congestion Notification (ECN) marks
inside the packet headers.
AQM marks the packets according
to the severity of the congestion. When
congestion increases the probability of
packet dropping (or marking) will also
increase.
Increase in the packet marking
reduces the transmission rate of the
sources which results into decreasing
the queue length and reducing the packet
losses by preventing the queue overflow.
As AQM algorithm used to drop
the packets randomly before buffer
overflow, it avoids the problem of
“global synchronization” that was
present in the Droptail algorithms
AQM Components are shown in the
diagram below:
Congestion indicator gives signal
of the occurrence of congestion, control
CSI Communications | November 2014 | 26
function proposes the strategies to
deal with the congestion and feedback
mechanism makes the sources aware
of it and asks them to adjust their pace
of transmission to bring the congestion
under control.
At earlier stages AQM algorithms
were entirely based on the queue length
as a congestion indicator, but as the
research progressed it has been found
that there are harms in using only queue
length as a congestion indicator. So for
detecting link congestion, AQM may
utilize any combination of the following
parameters: queue length (average
or instantaneous), input rate (packet
arrival rate or queue drain rate), queuing
delay and events of buffer overflow and
emptiness.
Congestion
control
function
calculates the probability of packet
marking (or dropping) based on the
level of congestion shown by the various
congestion indicating parameters and
decides which packets to drop (or mark).
Congestion control function can use
different parameters or blend of different
parameters. For getting better results, it
is essential to tune the congestion control
parameters according to the current traffic
condition in the network.
One important point here to note that,
in current AQM mechanisms, different
control function types are suited for
different traffic environments.
There is not a unique control function
that is suitable in all network conditions.
There are two major approaches to
in designing the control function: heuristic
approach and control theoretic approach.
Heuristic approach is completely
based on intuition of the algorithm
developer. There is always simplicity in
design and implementation to certain
extent. Mathematical modeling is generally
not present in this approach and the control
parameters are tuned manually depending
on the network traffic conditions.
Sometimes this approach may lead the
system into unstable state. As heuristic
approach is not always trustworthy, control
theoretic approach came into. It is based
on mathematical modeling where there
is always a explanation exists for the
www.csi-india.org
About the Authors
selection of the parameter values. Most
of the control theoretic approaches are
responsive flows centric.
Finally Feedback Mechanism informs
the sources about the incipient or transient
congestion in the network with the help of
ECN notification or packet drops (using
TCP’s triple duplicate acknowledgement
policy or retransmission policy).
Issues upsetting AQM performance:
a) Buffer size and link capacity
b) Traffic load and RTT
c) The manner in which flows enter
into the queue i.e. in-synch or out-ofphase way.
d) Routing matrix gain (it is used
to
represent
the
topologies
mathematically).
Network
robustness is inversely proportional
to this routing matrix gain.
e) The presence of short lived flows and
unresponsive flows.
f) Reverse path asymmetry.
Some of the existing AQM algorithms
are listed below:
Heuristic
Approach
Control-Theoretic
Approach
Random Early
Detection
Proportional Integral
(PI) controller
Adaptive
Random Early
Detection
Proportional
Derivative (PD)
controller
BLUE
Proportional
Integral-Derivative
controller
BLACK
Gain adaptive smith
predictor
Hyperbola RED
PI-PD
Load/Delay
Controller
Various fuzzy logic
controllers.
LUBA
And many more
And many more
Acknowledgements
We are thankful to our Principal Dr. S
D Markande, Prof. S P Patil, Head, IT
department and entire NBN Sinhgad
School of Engineering for their support in
our work.
References
[1] Richelle Adams, “Active Queue
Management: A Survey”, IEEE
Communications Surveys & Tutorials,
Vol. 15, No. 3, Third Quarter 2013, pp
1425-1476.
[2] S Floyd and V Jacobson, “Random
Early Detection Gate-ways for
Congestion
Avoidance”,
IEEE/
ACM Transactions on Networking,
1(4):397-413, Aug. 1993.
[3] W Feng, D Kandlur, D Saha and
K Shin, “A Self Configuring RED
Gateway,” in Proc.IEEEINFOCOM’99,
March (1999), pp.1320-1328.
n
Amol Dhumane has received his masters (M.E. Computer Engg.) from Bharati Vidyapeeth University, Pune. He is having 10 years of teaching
experience. His area of interest includes congestion control and IoT. He has published more than 10 papers in national and international
conferences. He is a life member of ISTE.
Dr. Rajesh Prasad has received masters (M.E. Computer Engg.) from College of Engineering, Pune and his doctorate from Swami Ramanand
Tirth Marathwada University, Nanded. He is having 18 years of experience. His area of interest is Soft computing, Text Analytic and
Information management. He has published more than 40 papers in national and international journals. He is a life member of IAENG, CSI
and ISTE.
CSI Communications | November 2014 | 27
Article
Sumith Kumar Puri* and Dr. H K Anasuya Devi**
*Bachelor of Engineering [Information Science and Engineering], Sri Revana Siddeshwara Institute of Technology, Bengaluru
**Researcher & Professor, Artificial Intelligence, CCE, Indian Institute of Science, Bengaluru
Information Technology to Curb Piracy
in Bollywood
This was it! The huge 1.5 GB download
was done. He observed that he was the
fastest seed, as he had close to a 60Mbps
connection. Albert now opened his
facebook friends' list and shot across a
message, announcing the link to all. By the
way, this was the latest in the series of scifi superhero movies that he and majority
of his peer group were awaiting. This
being the third day of the official release.
All set to watch the movie now, Albert
opened up his favorite video player on the
computer. But his joy was shortlived... The
movie quality did not live up to what was
mentioned on the site. It had promised
'HD 1080p video and DVD 384kbps
audio' as part of its title and description.
In spite of wanting to tear his hair apart at
the jumping of scenes, he plans to watch
the entire movie. The audio being hardly
audible, the video jittery and sometimes
tilted, the only pleasure he seemed to
have was his favorite cheese popcorn
and a glass of cola. Interestingly, the last
time Albert had ever paid for a movie or
music clip online was about three years
ago. That too, was actually an accidentally
downloaded clip, through auto-pay, as he
had his credit card registered on one of the
sites.
This is a normal daily or weekly
scenario of almost all of the netizens
who are within the teenage, graduate or
starting professional levels. Given the
same situation a few years earlier, we
would have seen the likes of Albert along
with his friends queuing up at a movie
theatre or waiting eagerly for the video
tape or compact disc release of the movie.
As per one of the reports the total
loss to Bollywood alone, in the year 2010,
was close to a billion dollars. This loss
was also attributed to camcorders' being
used in theatres to create pirated compact
discs and digital video discs. So, Hasn't
any one taken any steps to get back what
should be rightfully theirs? Though there
are many options including enhancing
the already available digital watermarking
techniques, policing and governance. But
in the reality of things, How much of this is
actually enforced and How much does the
film creator actually bother about? As per
a study by the Harvard Business School in
2011, the implementation of some of the
steps could actually outdo the financial
benefits associated with it. Hence,
sometimes even the creators overlook
these measures.
So, How about implementing a pure
information technology solution or system
that is not only helpful for the creators, but
also a fun and legal way for the users. My
proposal is not only to create a software
mechanism that promotes a legal way, but
one that also that is cost effective, cheaper
to implement, generates user interest,
direct business to customer, promotes
legality and is enjoyable. What's more,
it promises to even re-employ pirates as
legal vendors of the same media, albeit at
a lesser profit to them.
CineCat is what I call this software
idea, which will allow people of all ages
to easily and legally access any media,
primarily related to Bollywood. CineCat
acts not only as a directory or database
of movie information but as an online
distributor of, primarily, movies and music.
Unlike the YouTube's of our era, it works in
a mode that is even more closely tied to
Commerce, Anti-Piracy and Bollywood.
The simple driving process is that when
the movie is ready to release and it hits off
a calculated cooling period, the software
allows the creator to provide an online
release.
With
proprietary
security
mechanisms that are tied to the hardware,
it aims to distribute the release at equal or
lesser the cost to download or purchase
a pirated movie disc. The delivery can be
either digital or on an actual disc, through
post. Since the security mechanisms
are tied to hardware or the registered
player and to a specific user, they
cannot be duplicated or cracked easily.
The calculation of a cooling period is
done based on history, at times being a
calculated risk. It also aims to generate
further interest in the users who await
that ultimate digital experience and
would outright deny any pirated media. It
will create further avenues for revenues,
CSI Communications | November 2014 | 28
a legal approach which is attractive to
educated users and curb piracy effectively.
All of these can be combined with many
other digital and traditional marketing
techniques, to maintain users' interest.
The difference in the solution that we
are proposing is that an online release
would not only use CineCat as a form
of distribution but also as a player and
security control mechanism. It is not only
in India, but in even bigger countries such
as the United States, tying movies with
ordinary post or digital delivery is a tried
mechanism that has got good response.
So, the loose ends that remain in
such a proposal is what is that appropriate
time when the online release would outdo
or curb piracy to abysmal levels. Also, it
should allow the creator to gain revenues
that is rightfully theirs. Then there is the
issue of periodic or perpetual rights on
the creation itself. These are only minor
issues or calculated risks, that would
never take away the normal theatre,
multiplex or big screen watchers. Since
CineCat would allow a digital database,
which is equivalent of a movie wikipedia
and a lifelong availability of the original
or high quality creation itself – the issue
of rights is a decision to make that would
only eventually give benefits, now starting
from an earlier period.
But why would one chose a tedious
process as an user? What would appeal to
him, like our own Albert?
Albert is one of the normal graduate
or undergraduate that you would come
across, who has a group of geeky friends.
Albert is not the only one who prefers the
highest quality of video, audio or even
a trailer – his entire peer group does. At
the same time, they all vie to create the
best repository or collection of music or
movies. They are also the ones who don't
bother to spend a very small amount
of money, not only because it provides
quality – but also because it is now cool to
pay for this form of viewing. Also, being an
avid fan of sci-fi superhero movies, he is
even more enthusiastic of using CineCat.
He expects an autographed compact
disc to be delivered to him, and doesn't
www.csi-india.org
lose hope that he may win the contest on
CineCat to meet the superhero (actor)
himself. Even other buyers off the road
of a pirated compact disc, have now an
option – even if they do not use a personal
computer. This will mostly be tied to
the serial number of the playing device.
Since most household's may own a single
device (or at the most two) – a suitable
serial number can be provided to encode
it for playing with CineCat loaded onto the
movie disc itself.
What about the other side, that of
the creator? Does he see anything that
is different or lucrative from what he was
doing till now?
This could lead to a cheaper form of
distribution, that may infact itself pay for
itself in many ways, because of including
advertising to one extent – with CineCat
taking care of almost all processes which
include online security, distribution,
proprietary mechanisms, it would keep a
constant check (and update) on crackers
and any form of threats to its reliability.
We, in this article, are not covering
or studying any other application or
software system that is already in place
that is close to what CineCat does or is
intended to do.
But then there is a common sense
that may prevail in many minds. Why
curtail some piracy, When it is actually
good? There maybe positive vibes due to
the piracy. Well, there are steps to actually
take that too into account, as is done to one
extent even today. CineCat can be used as
an extended trailer, an extended promo to
ascertain not only the content, interest of
the user but also the quality, security and
reliability processes. Most of the times for
an user a very short wait is mostly worth
the watch (beyond the trailers).
All of the mentioned policies and
compared to the prevalent usage, and
of that do exist a small percentage are
enforced. One aspect of CineCat is also a
stronger enforcement of cyber laws related
to media and information technology. It
could lead to a combination of banning of
certain sites, internet service providers,
torrent sites, peer-to-peer sharing, file
sharing sites and even sale of pirated cd's.
CineCat can curb or provide alerts for
many of the online piracy methods and
also provide a way to tackle the offline
menace (out of this discussion).
Albert is back to watching the movie,
which is almost at the end. No, He isn't
the one who has lost hope... All this while,
with the movie quality not capturing his
interest - he spent some time reading
this article about CineCat. He is the one
eagerly awaiting the first time he gets to
see an online movie release on CineCat!
Glossary of Terms
CineCat was a Software Application
Idea based on the concepts mentioned
in this article. This was to be built by the
now closed startup, named TechArmy,
of one of the authors.
About the Authors
advertising, marketing, delivery and even
policing. Some of these ideas can be difficult
in implementing because of curtailed
internet speeds, but then there always is the
option of delivery of discs by post.
Also, since CineCat relies on
ideas are also applicable to music,
events, short films and any other form
of distribution that may need exclusive
rights, or are subject to piracy.
We are evolving into a society
where the cyber laws are too loose when
Interesting Read (Google Search Terms)
Hollywood and Bollywood Join Arms...
Protecting against the Pirates of Bollywood
Bollywood & Rights, Piracy Is Mostly Via
Torrents
Bollywood No Longer Worrying About
Piracy...
ETC Fights against Movie Piracy...
Film Piracy Funding Terror in India...
Piracy cost Bollywood $959m: Report
YRF digitizes Dhoom 3 to combat piracy
n
Sumith Kumar Puri holds a Bachelor of Engineering [Information Science and Engineering] from Sri Revana Siddeshwara Institute
of Technology, Bengaluru. He has also completed his Proficience [Cryptography & Network Security] and Proficience [Intelligent
Agents] from the Indian Institute of Science, Bengaluru. Sumith has recently completed a Part-Time Acting Course from Actor
Prepares, Mumbai. He has more than 9 years of experience in various facets of Software Development. You can reach him at sumith.
puri@sumithpuri.me
Dr. H K Anasuya Devi received her Ph D degree from the Indian Institute of Science, Bangalore in 1985. Her research interests include
– Computational Linguistics and Language Techonology, Artificial Intelligence and Expert Systems, Remote Sensing Applications
and Geographic Information Systems, Archaeology and Epigraphy, Sports. She possesses extensive research experience with over
25 years in inter-disciplinary areas, including 15 years of teaching experience at graduate and post-graduate levels. Over the last
decade and half, she has guided over 150 students in their research projects, published over 298 papers in all forms. You can reach
her at hkadevi@yahoo.com
CSI Communications | November 2014 | 29
Article
Dr. M Hanumanthappa*, Mrs. S Regina Lourdhu Suganthi** and Mrs. Rashmi S***
*Associate Professor, Department of Computer Science and Applications, Bangalore University, Bangalore
**Research Scholar, Department of Computer Science and Applications, Bangalore University, Bangalore
***Research Scholar, Department of Computer Science and Applications, Bangalore University, Bangalore
Protection of Software as Intellectual Property
Each system of Law has its own
definition of what can be bought and
sold, i.e., what is tangible property?
Therefore, by virtue of implication
of law, the ownership of property
such as tangible goods is defined and
apportioned. Whereas, the ownership
in Intellectual Property (IP), represents
a proprietary right in intangible products
of human minds, which are generally
referred to as “knowledge goods” and
the ownership of IP, is also defined by
law. However, as against the existence
of laws that define and protect the
ownership of tangible goods, a separate
form of legal protection is recognized
for the protection of knowledge goods,
since knowledge goods are intangible,
non-excludable
and
inexhaustible.
Accordingly, the laws that govern IP
define ownership rights in IP. Therefore,
the term “Intellectual Property Rights
(IPRs)”, is bundle of legal rights,
granted for knowledge goods, such
as inventions (Patent Right), brand
names (Trademark), artistic and literary
creations (Copyright), aesthetic designs
(Designs) and industrial secrets (Trade
secret).
Traditionally, computer software is
recognized as a literary work and hence
its legal protection is provided under
the law of Copyright (albeit statutory
registration is not mandatory). Prior to the
unbundling of computer software from
hardware and where there was no distinct
value for software, copyright protection
was deemed sufficient. It is important to
understand that Copyright Law provides
protection only to expression of ideas
(non-functional ideas) and not to ideas
(functional ideas) per se.
However, with the unbundling of
computer software from hardware in 1970s
and software assuming an independent
work of creation, the protection of
software, only under the law of Copyright
was found grossly inadequate.
In Lotus Development Corporation v.
Borland International, U.S. Supreme Court,
while deciding a copyright infringement
case, in a dispute between Borland and
Quattro Pro (Lotus 1-2-3), exposed the
limitation of legal protection of copyright
for software. In this case none of the source
code or machine code that generated the
menus was copied, but the names of the
commands and the organization of those
commands into a hierarchy were virtually
identical. The Court, while denying the
Copyright protection for the software,
where the functional aspects of software
are claimed, pronounced that copyright
was limited only to the protection of
non-functional aspects of software, as a
literary work.
Copyright law provides protection
for literary works, which are original
and non-functional in nature. With the
separation of software from hardware
and the greater value of realization for
software as an intellectual asset, a need
was felt to provide a comprehensive IP
protection for the functional aspects
of software and an effort was made to
seek protection of software as invention
(functional idea).
Accordingly, protection of software
in the form of Patents gained momentum,
in countries like US and Europe, by
considering them as inventions rather
than literary works.
Legal protection in the form of Patents
is granted by a State (Registration is
mandatory for exercising the legal rights),
for inventions, that are New, Inventive
and having Industrial Application. In
addition to the satisfaction of these legal
conditions, it is also imperative to ensure
that such inventions do not fall under the
category of ‘non-statutory inventions”. In
other words, patent statutes of countries,
do have negative list, with which they bar,
explicitly, certain categories of inventions,
irrespective of such inventions being
Novel and Inventive.
One such category of inventions,
which are often being considered as
“non-statutory” is software. For instance,
under US Patent Law (35 U.S.C. §101), the
subject matter of inventions relating to
laws of nature, natural phenomena, and
abstract ideas, are specifically excluded
from patentability. The rejection of
software as a patentable subject matter
is based on the premise that they are
abstract ideas and hence not patentable.
US Supreme Court in Gottschalk v.
Benson(409 U.S. 63 (1972)) ruled that a
process claim directed to a numerical
CSI Communications | November 2014 | 30
algorithm, as such, was not patentable
because the patent would wholly preempt the mathematical formula and in
practical effect would be a patent on
the algorithm itself and hence it would
amount to allowing a patent on an
abstract idea.
However, the US Supreme Court, in
the case Diamond v. Diehr, 450 U.S. 175
(1981), held that controlling the execution of
a physical process, by running a computer
program did not preclude patentability of
the invention as a whole. In other words,
the mere presence of a software element
did not make an otherwise patenteligible machine or process un-patentable.
This decision of US Supreme Court opened
up vistas for the protection of software as
patents in the USA.
Similarly, in Europe, in terms of
European Patent Convention (EPC), (Art
52 of EPC), "programs for computers" are
not regarded as inventions for the purpose
of granting European patents, but this
exclusion from patentability only applies
to the extent to which a European patent
application relates to a computer program
“as such”. In other words, inventions
relating to claiming of “mere algorithms”
fall foul of this provision of law. In
Europe, patents for software inventions
are granted, as long as they have new
“technical effect” and they do not relate to
the implementation of normal functioning
of computer hardware.
The term “technical effect” is
generally interpreted to include, solution
to a technical problem, higher speed,
reduced hard-disk access time, more
economical use of memory, more efficient
data base search strategy, more effective
data compression techniques, improved
user interface, better control of robotic
arm, improved reception/transmission of
a radio signal etc.
In India, the subject matter of the
inventions relating to “mathematical or
business methods or a computer program per
se or algorithms”, fall outside the purview of
patent protection. Nevertheless, software
can be protected as literary work under
Indian Copyright Law. In view, Indian
Patent Law governing software inventions
are similar to European Patent Law, Indian
Patent Law, also reckons “new technical
www.csi-india.org
effect” in considering the patentability of
inventions claiming computer software.
To conclude, Software as an IP, needs
to be framed as an invention and adequate
protection in the form of patent right is highly
desirable, since patents offer comprehensive
protection for functional ideas. If necessary,
dual IP protection for software in the form of
Patents and Copyrights can also be explored
to cover both functional and non-functional
aspects of software.
References
[1]
Manish Arora, “Guide to Patents Law”,
Universal Law Publishing Co. Pvt. Ltd, 2002.
[2] P Narayanan, “Law of Copyright and
Industrial Designs”, Eastern Law House,
2002.
[3] Frederick W. Mostert& Lawrence E
Aploson, “ From Edison to iPod”, Dorling
Kindersley Limited, 2007.
Web References
[1]
http://en.wikipedia.org/wiki/Lotus_Dev._
Corp._v._Borland_Int'l,_Inc.
[2] http://supreme.justia.com/cases/federal/
us/409/63/case.html
[3] http://www.invispress.com/law/patents/
diehr.html
[4] h t t p : //e n . w i k i p e d i a . o r g / w i k i /
Gottschalk_v._Benson
[5] h t t p : //e n . w i k i p e d i a . o r g / w i k i /
Diamond_v._Diehr
[6] http://en.wikipedia.org/wiki/Software_
patents_under_the_European_Patent_
Convention
n
About the Authors
Dr. M Hanumanthappa is currently working as Associate Professor in the Department of Computer Science and Applications, Bangalore
University, Bangalore, India. He has over 15 years of teaching (Post Graduate) as well as Industry experience. He is member of Board of
Studies/Board of Examiners for various Universities in Karnataka, India. He is actively involved in the funded research project and guiding
research scholars in the field of Data Mining and Network Security.
Mrs. S Regina Lourdhu Suganthi is a Research Scholar in the Department of Computer Science and Applications, Bangalore University,
Bangalore. She has two decades of rich teaching experience in the field of Computer Science. Areas of interest include Data Mining, Image
Processing, Algorithms and Problem solving. She also assists in computer related patent drafting work.
Mrs. Rashmi S is a Research Scholar in the Department of Computer Science and Applications, Bangalore University, Bangalore, India. She
also has over 3 years of teaching as well as Industry experience. Her specialization in research is Data Mining. She has published several
papers in various National and International conference and Journals.
CSI Communications | November 2014 | 31
Practitioner
Workbench
Wallace Jacob
Senior Assistant Professor, Tolani Maritime Institute
Programming.Tips() »
Fun with ‘C’ Programs – Reversing a String using a
Bitwise Operator
The program and its output below exemplify a novel method of
reversing a string using one of the bitwise operators:
Program listing one
#include<stdio.h>
#include<string.h>
main()
{
char str[80];
int i, len;
printf(“Enter a string (less than 80
characters): “);
scanf(“%[^\n]s”, str);
printf(“\nBefore reversal, str= %s”, str);
len=strlen(str)-1;
for(i=0;i<len;i++,len--)
{
str[i] ^= str[len];
str[len] ^= str[i];
str[i] ^= str[len];
}
printf(“\nAfter reversal, str= %s”, str);
return 0;
}
The underlying logic is explored below:
c
\0
str[0] str[1] str[2] str[3] . . .
str[79]
If we convert each character of str, into its corresponding ASCII
About the Author
98
99
0
str[0] str[1] str[2] str[3]
...
str[79]
The binary representation of the ASCII codes would be as follows:
01000001 01100010 01100011
str[0]
str[1]
str[2]
00000000
str[3]
...
str[79]
Now let us dissect the statements:
str[i] ^= str[len];
str[len] ^= str[i];
str[i] ^= str[len];
In the first run of the for loop, it would imply:
i.e. the contents of str[0] and str[2] have been interchanged.
The rest is simple iteration using the for loop.
The string (Abc) would be stored as follows:
b
65
str[0] ^= str[2]; /* str[0] = 01000001 ^
01100011; i.e. str[0] = 00100010 */
str[2] ^= str[0];
/* str[2] =
01100011 ^ 00100010; i.e. str[2] =
01000001 */
str[0] ^= str[2]; /* str[0] = 00100010 ^
01000001; i.e. str[0] = 01100011 */
Sample output:
Enter a string (less than 80 characters):
Before reversal, str= Abc
After reversal, str= cbA
A
code, then the storage can be visualised as follows:
[Why should we use bitwise operators? For the simple reason
that bitwise operations are faster and use less power because of
reduced resource usage.]
n
Wallace Jacob is a Senior Assistant Professor at Tolani Maritime Institute, Induri, Talegaon-Chakan Road,
Talegaon Dabhade, Pune, Maharashtra. He has contributed articles to CSI Communications especially in the
Programming.Tips section under Practitioner Workbench.
E-mail: wallace_jacob@yahoo.co.in
Office Contact No: 02114 242121
CSI Communications | November 2014 | 32
www.csi-india.org
Practitioner
Workbench
Umesh P and Silpa Bhaskaran
Department of Computational Biology and Bioinformatics, University of Kerala
Programming.Learn("R") »
RStudio- Studio of R
RStudio is one of the most popular open source Integrated
Development Environment (IDE) for R. Both Desktop version
for Windows, Linux and Mac and Server version of RStudio are
available. RStudio has both Open Source Edition and Commercial
License. The open source edition is supported by the Community
forums only, whereas commercial users will get email support for
eight hour response during business hours. RStudio is written in
the C++ programming language and the Qt framework was used
to develop its graphical user interface. RStudio makes the life of
data scientist easy by offering an open source and enterpriseready professional software.
Let us have a look at the RStudio IDE.
RStudio has mainly four windows –
1. Source Window (Data objects in Spreadsheet form).
2. Console Window, where you can type commands and see
output (as in the R environment )
3. Environment and History Window- Environment Tab shows
all the active objects and history tab shows a list of commands
used so far. By using the environment tab, you can
import/ load data into R.
4. File, Plot, Package, Help and Viewer area.
You can also make changes of the look and feel of
the environment by editing the Global Options (go to
tools> Global Options) of RStudio.
R studio provides syntax highlighting facility and
line numbering which help you in writing code in R.
Importing data from various resources including web
goes interactively in RStudio. You can add packages by
a single click on the IDE and load the package into the
environment by checking the box. Also you can view
plots and export figure into the format you wish to.
A new R script can be created by using
RStudio by either clicking the icon or from the file
menu. You can also create a new text file from the
Rstudio interface itself. RStudio also supports C++
programming.
One of the significant features of RStudio is that
you can make presentations and html documentation
using it. A particular block of code in R can be inserted in the html
code and you can run the block. In the documentation, you can
show the code and gives its plot/result.
In a similar way, you can also use RStudio as an editor to
produce documentation of your R experiment or tutorial and save
it in PDF.
RStudio has a number of packages like Packrat, Shiny, ggvis,
dplyr, knitr, R Markdown, which are actually assets of statisticians.
Packrat is one of such package which helps you to handle the
package dependencies. This makes the package installed in your
machine portable and thus you can move your project easily and
reproduce result in some other machine. Shiny helps to create
interactive web applications on R. We will discuss more on Shiny
in the next tutorial.
n
CSI Communications | November 2014 | 33
IT Industry
Perspective
Prof (Dr.) D G Jha
Professor & Area Chairperson – IT; Programme Coordinator-MCA
Future of Medical Transcription Jobs in
India - Need to Extend it beyond Record
Generating Process
The real India still lives in villages
and farming continues to be the main
occupation of the people of this nationa country among the largest agriculture
producers in the world, a nation that
survives necessarily because of the agro
sector; INDIA is and will continue to
be viewed globally as a giant granary.
However, this perception that India is
still only an agro-based nation is fast
changing and going by the recent policy
statements of Government of India, it
definitely reflects the determination that
it is ready to recognise that the services
sectors are slowly but surely occupying
the drivers’ seat in the economy. Indian
government official plan for 2020 says,
“Our vision of India in 2020 is of a nation
busting with energy, entrepreneurship and
innovation” (Yojana Aayog;-Planning
Commission.2000, p21). This is an
opportunity.
Given the kind of support the
government
provided
to
service
sector specially the ITES (Information
Technology Enabled Services) sector,
it certainly has managed to accelerate
India’s transformation from an agrarian
economy to a service economy to a
certain extent. For the sector to thrive
further, it should be understood that ITES
holds enormous promise for India but at
the same time it has to be handled with
utmost care. Having, a powerful revenue
generating model and support policy of the
government alone will not be the primary
success determining factor; the ability to
manage human resources and maintain
quality will be paramount. ITES is a global
industry – sourced locally – and India can
succeed only if it is globally competitive
(Dhar-Patel & Vishwanath eds. 2002, p1).
IT Enabled Services (ITES) is defined
as all those services which can be
delivered to the end user from a remote
location with the aid of information
technology (Dhar-Patel & Vishwanath
eds. 2002, p7). In simple terms, the set
of processes that can be outsourced
and (can be) enabled with the help of
Information Technology can be defined as
Information Technology Enabled Services
or more simply as ITES. The sectors
(indicative) that can be classified as the
part of ITES are: Call Centers; Back Office
Processing; Medical Transcription (MT);
Geographic Information System (GIS);
Knowledge Process Outsourcing (KPO).
The Economic survey of 2012-13 indicates
four major sub components of IT/ITeS
industry as: IT services, business process
outsourcing (BPO), engineering services
and R & D and software products. (http://
indiabudget.nic.in. Economic Survey 201213, p223)
Importance of Medical Transcription
“Health is one of the most informationintensive businesses you will find, and
that information can have a direct impact
on the quality of patient care” notes Prof
Michael Smith – editor of Healthcare
Informatics Journal (cited in Brady et al.
2001, p118).
Since, the entire healthcare industry
in the US revolves around insurance; the
detailed, comprehensive, accurate and
complete patient records are needed
for processing insurance claims making
medical transcription one of the most
challenging and fastest growing aspects
within healthcare.
Medical Transcription assumes
greater importance as it is concerned with
preserving each and every patient-related
document, including the doctor’s note.
•
A patient visiting a clinic may require
investigation by physicians with
different medical specialties, nurses,
therapists, and technicians, all of
whom will record observation or test
data in separate files
•
During examination the patients may
be asked about his/her condition or
lifestyle by all of the above involved
in diagnosis
•
A patient upon investigation may
be prescribed several drugs and
CSI Communications | November 2014 | 34
treatments by different physicians
Each of these responses can get recorded
in different ways and in different files.
(Nair (Dr) cited in www.chillibreeze.com).
Reasons for Outsourcing of Medical
Transcription Process
The processing of insurance claim
requires comprehensive documentation of
the patient’s medical consultation history
and records of the every interaction with
physicians. Most of such documents that
recorded the interaction of the patients
and the physicians were handwritten in
the past and that made at times difficult
for insurance auditors and lawyers to
decipher and interpret. They started
insisting on the typed medical records.
This gave birth to the concept of Medical
Transcription. An efficient record-keeping
system thus becomes important and
indispensable (especially in the US) since
insurance claims form an integral part of
the medical industry.
Transcribe (across + write in Latin)
means writing something out in full
from notes or shorthand. It also means
transferring of information from one way
of storing it on a computer to another,
or from computer to an external storage
device.
Medical records noted or dictated
by the doctor (or his assistants or nurses
or a clinician), physical therapists, health
professionals such as dietician or social
psychologist are loaded into the tape or
onto the digital voice processing system
precisely and aptly transcribed i.e.,
converted into the word document by MT
or MLS (Medical Language Specialist). All
the clinic notes, office notes, operative or
consultation notes, patient’s history and
physical reports, psychiatric evaluations,
laboratory reports, x-ray reports and
discharge summaries after transcription
are proofread up to 98% accuracy before
being uploaded back to the doctor’s office
or clinic (Dhar-Patel & Vishwanath eds.,
2002, p.100) .
www.csi-india.org
Since the US is the only country in
the world that has such stringent policies
on maintaining medical records, medical
transcription is largely the US based
industry. The need to reduce the cost of
administering these records pushed many
hospitals towards adopting electronic
formats for documentation. India, for its
excellence in interpretation and large
English-speaking population base, became
the preferred destination (till recently) for
the US medical practitioners.
The documents are expected to be
returned within the stipulated time frame
of 24 hours and time zone difference that
India has with US makes it quite easy.
Apart from need to cut cost, the other
apparent reason is increased reliance on
core competence that prompted hospital
administration to outsource this job. The
benefits of ordering out for the medical
practitioners are:
•
Concentration on core activity
•
Production based compensation
•
Minimized expenses on perks and
other employee benefits
•
Elimination of recruitment and
training expenses
•
Flexibility in choosing quality
manpower at reduced cost
•
Greater
accountability
and
transparency
in
production
standards.
(Dhar-Patel & Vishwanath eds.,
2002, p.101)
Quality Standards for Medical
Transcription
The healthcare industry in US needs
to adhere to stringent quality standards.
One such standard adopted by software
companies focused on healthcare domain
is HL7 (Health Level Seven) standards.
The HL7 standards (Shet 2005,
p.326-328) addresses the following
key processes as outlined in capability
Maturity Model or more simply CMM:
•
Requirements management
•
Software quality assurance
•
Organisation process focus
•
Training programmes
•
Software quality management
•
Technology change management
•
Defect prevention
It is one of the several ANSI
(American National Standard Institute)
-accredited
Standards
Developing
Organisation (SDO) operating in the
Healthcare domain. Members of the HL7
are collectively known as working group,
which is mainly organized into technical
committees (TC) and Special Interest
Groups (SIG).
The role of the Technical Committee
(TC) is to:
•
Identify the scope and range of data
elements
•
Work with other SIG, TCs, or any
other related organisation to identify
appropriate controlled vocabulary for
encoding those data elements
•
Identify or define messages (or
objects) required to support the
specific information exchange needs
of applications, both as input to the
application as well as output from the
application.
The Special Interest Groups (SIGs)
provides/certifies the standard for
electronic data interchange pertaining
to healthcare. It keeps on enhancing
the current standards and works in
conjunctions with technical committees
to advance the quality standards and
improve HL7 standards.
The goals of the HL7 standards are to
create flexible, cost effective approaches,
standards, guidelines, methodologies
and related services that help in the
interoperability of healthcare information
system with other dependent system
within the domain.
Another important and specific
standard that all healthcare organisations
Fig. 1: The entire medical transcription process
Fig. 2: The entire medical transcription process
[source: http://www. outsource2india.com]
[source: http:// www.slideshare.net/rohitpate l203/medical-transcription-industry]
CSI Communications | November 2014 | 35
are required to adhere to is the HIPAA
compliance. Health Insurance Portability
and Accountability Act of 1996 -or more
simple referred to as HIPAA complianceis the federal law amended to the
Internal Revenue Code of 1996. The
healthcare insurance industry to improve
portability and continuity for the groups
as well individuals rely heavily on the
HIPAA compliance standards. The main
objectives of HIPAA are:
•
To increase the efficiency and
effectiveness of health information
systems through improvements in
electronic health care transactions
recording and maintenance process
•
To maintain security and privacy
of individual identifiable health
information.
The processes and information
impacted by HIPAA are (but not limited
to):
•
Health claims and equivalent
encounter information
•
Enrolment in and disenrollment from
a health plan
•
Eligibility for health plan
•
Healthcare payment and remittance
advice
•
Health plan premium payments
•
Referral
certification
and
authorization
•
Coordination of benefits
•
Prescriptions
(www.call-centers-india.com/ites.
html)
Stages in Medical Transcription Process
The parameters that define a successful
medical transcription unit are efficient
receiving of voice files, allotting,
transcribing and sending of transcribed
files in cost-efficient manner and without
any error. Accuracy and quick delivery
is paramount in the field of medical
transcription. Figure 1 and 2 describes
the Standardized Medical Transcription
Process as stipulated by HIPAA.
Traditionally, Indian MT sector
followed:
• Dictation
The first step in MT begins with
physician dictating the observation
and diagnosis during examination
of the patient. The dictation is done
onto a device such as tape recorder,
Dictaphone, digital Dictaphone, a PC
or a normal telephone after dialling a
toll free telephone number provided by
the outsourced MT service provider.
First of such dictating machine was
engineered in the late 1880s and since
then it has progressed to several phases
of development from grooves cut on
a cylinder, to flexible belts of plastic,
magnetic media, digital dictation and
speech recognition.
Dictating through toll-free number
is currently the most used technique by
the physician. Since it is possible that a
physician may meet the same patient
at more than one hospital, the doctors
are allotted phone numbers where the
last digit indicates the hospital at which
the patient has been/is being examined.
The innovation like this helps the MT
service provider to locate the hospital
and accordingly decide upon the format
for recording, as different hospitals may
follow different formats.
To make the task of dictation easier
and efficient, voice recognition devices
that can record the message directly into
the PC are now being employed by the MT
service providers. Also, Personal Digital
Assistants or more popularly known
as PDA’s are now made available with
embedded voice recognition capacity or
dictation capture system.
• Storage and retrieval of audio files
The audio files are directed towards the
MT service provider’s voice capturing
server using the intelligent network.
The MT Company’s server host
application capable of digitizing the
voice on real time basis pushes these
voice data (files) to the production unit
through Internet.
• Encryption and transmission
The digitized data is then compressed
and properly encrypted for onward
transmission through satellite link
to MT service provider’s destination
(such as India) where the transcription
gets carried out. The files are then
allotted by the local unit of MT
Company or consultant to various
medical transcriptionist or franchisee.
• Allotment and actual transmission
Depending upon the familiarity with the
physician or based on specific stream
of medicine, the files are classified and
allotted to various transcriptionists
matching the required skill set and
needed turn-around time. The files
are then transcribed in the formats
as prescribed by the physicians or
hospitals. The completed files are
uploaded into the quality controllers
CSI Communications | November 2014 | 36
work area where these are checked for
quality before uploading it back. The
various types of error that may occur
while transcribing are:
• Medical terminology misunderstood (wrong disease attributed to
the patient)
• Omitted dictation (omission of
the laboratory finding as the value
dictated could not be heard or was
misunderstood)
• Medical terminology wrongly spelt
• English word misinterpreted and
hence wrongly spelt (entered
‘elicit’ instead of ‘illicit’ or ‘dissent’
instead of ‘descent’
• Grammatical errors
• Punctuation errors
• Inappropriate blanks
• Typographical errors (typos)
• Formatting errors
• Returning Completed Transcription
The quality checked transcripts
are generally uploaded to the MT’s
company server and are then sent
back to the individual doctors or the
hospitals where they are filled for
storage. Ideally, the medical records
are returned to the hospital servers
in real-time, ready to be accessed.
The encrypted transcribed files are
commonly known as EMR (Electronic
Medical Records).Transcribing/editing
all the hospital reports dictated by
hospital medical staff (physicians,
nurses and physician assistants)
is the responsibility of the Medical
Information
Transcriptionist/editor
also at times referred to as Medical
Language Specialists. The other tasks
include but not restricted to:
• Utilisation of sourcing hospital
information system in order to
place the transcribed report into
the patients account
• Based on sense of the report
and the patient types, selection
of apt report format and print
destinations
• Complete the required number
of transcription tasks within the
stipulated time frame without any
error as per the guidelines set by
the sourcing hospital
(Dhar-Patel & Vishwanath eds., 2002,
p.105-107)
www.csi-india.org
ITeS/MT Industry in India: Over the Years
“India controls 44 percent of the global
offshore outsourcing market for software
and back-office services, with revenues
of US $17.2 billion (euro14.07 billion) in
the year ended March 2005…” (Source:
Associated Press, June 2005. http://
www.medicaltranscription-olutions.com/
medical_transcription_statistics.html).
Over the years, the slowdown across
the globe has impacted the revenues of
this sector and this gets reflected in a
study by NASSCOM indicating that the
growth reduced from 15 percent in 201112 to an estimated 8.4 percent in 2012-13.
The estimated growth for 2013-14 are 1315 percent for total IT-BPM revenue (of
which MT is still a component perhaps to
reckon with), 12-14 percent for exports and
13-15 percent for domestic circuit. IT and
Business Process Management (however)
sector revenues have grown from
1.2 percent in 1997-98 to an estimated
8 percent in 2012-13. (http://indiabudget.
nic.in. Economic Survey 2012-13, p224)
When it comes to MT, starting from
1990, MT ranks amongst the first set of
ITeS-BPO activities to be sourced from
India. Currently MT segment in India
is estimated to earn annual revenue
aggregate of US$ 220-240 million.
(http://www.aiita.org /news/blogs/3322medical-transcription-the-way-to-getyour-bright-career.html)
In India, there are about 120-150 mid
to large size vendors offering medical
transcription services and 70% of the
revenues in the industry are generated
by the large players (mostly US medical
transcription service organizations MTSOs) with offshore centers in India.
Cbay is one the major vendors (www.
cbayscribe.com /cbay systems/ index.
htm) with aggressive growth plan having
headcount of over 3,500. Apart from
large-size and mid-size players there
are few small-size vendors offering MT
services with average employee strength
of about 50 competing for remaining 30%
market. (http://www .sourcingnotes.com/
content/ view/333/58/).
Technological Innovations in MT – Does
it mean Dead End for smaller Indian MT
Outsourcing Agencies…
To imagine that the industry will have
reliable speech recognition output without
human intervention was never envisaged,
and hence the elimination of medical
transcriptionist was completely ruled out
until the new disruptive voice recognition
(VR) technology got introduced. The
automated VR technology allows the data
to be fed directly by the doctors into the
system.
Nuance and Royal Philips Electronics
are the two key players in providing
technology that caters to speech-to-text
market for health care professionals.
The use of speech-to-text technology
by US military’s health system grew by
100% over the last year with about 6000
professional adopting Nuance’s software
across all branches of the military. (http://
w w w. s o u rc i n g n o t e s .co m /co n t e n t /
view/333/58/)
Role of Information as a Business
Resource (IaBR) in healthcare industry
and its impact on patients care, reputation
of the hospital, seamless archiving of
patients data, health tourism and ease
of retrieval has been well-established.
Some of the important terms (http://
w w w. c h i r o c a r e . c o m /w p - c o n t e n t /
Fig. 3: Electronic Medical Record [Source: Nuesoft XpressTM Electronic Medical Record accessed at
http://mtherald.com/how-emr-ehr-is-going-to-affect-medical-transcription-industry]
uploads/2013/03/HITTerms.pdf) related
to health information systems are:
•
EMR (Electronic Medical Record):
Capturing
patient
data
and
facilitating access of these details
to authorized clinical staff from any
specified location characterises a
computer-based medical recording
system popularly referred to as EMR.
Some of important deliverables
associated with EMR are: accurate
and complete claim processing as
required by insurance companies,
providing automated alerts for
drugs’ allergic reactions (and
interactions), generating clinical
notes, prescriptions and schedules,
allowing labs to communicate with
clinical staff etc. The advanced EMR
systems now include units which
keep track of all relevant (from
internal as well as external sources)
medical information and are now
often referred to PMS (practice
management system)
•
EHR (Electronic Health Record):
EHR comprises of processes such
as recording, storing, classifying,
retrieving, querying, generating
reports with respect to patients
physical
and
mental
health.
Past, progressive and predictive
information is then used for providing
primary-health care and healthrelated services. EHR also comprises
of decision-based tools that helps
clinical staff to access and take
decisions on the basis of evidences.
Apart, from clinical purpose EHR
also has modules that help collect
and manipulate data with regards
to billing, quality management,
outcome reporting and public-health
disease surveillance and reporting
modules. The primary contents of
a typical Electronic Health Record
would include: patient demographics,
progress notes, SOAP (Subjective,
Objective, Assessment and Plan)
notes, persisting problems, vital
signs, diagnosis details, medical
history, immunizations time-lines,
laboratory data and radiological data.
Also, using Discrete Reportable
Transcription (DRT) facility, clinical
documentation on EHRs can be further
improved. It not only directly populates
transcribed information into the EHR’s
fields and templates, but also facilitates
structured documentation (right format)
of information in EHR.
CSI Communications | November 2014 | 37
Fig. 4: Sample EHR [Source: http://www.assistmed.com/ blog/ bid/79204/Save-Physicians-90-Minutes-Per-Day-with-DRT-Transcription]
Fig. 5: Sample PHR [Source: http://mtherald.com/how-emr-ehr-is-going-to-affect-medicaltranscription-industry/]
•
PHR (Personal Health Record):
Electronically
maintaining
and
managing
individuals’
health
information requires a very secured
and
confidential
environment.
PHR provides an application that
provides access of the details only
to the authorized person. It controls
an keeps track of accesses made
(accountability), authorization (provide
access to right people in right format at
the right time), authentication (verify
the credentials before allowing the
access) and privacy.
Factors that Obstruct Outsourcing MT
Jobs to India
The healthcare industry in US brought in a
major change in the 1990’s by recognising
and adopting standards that would clearly
define medical terminologies which
was later referred to as standardized
transcription style.
In order to lay
emphasis on standardized documentation
and accuracy the American Association of
Medical Transcription (AAMT) published
Book of Style for Medical Transcription in
1995. The increased use of standards
made hospitals and clinics outsource
their work to medical transcription service
organizations (MTSOs) or home-based
US medical transcriptionists having their
own centers or at the most leased out
the task and services (sub-contract) to
smaller medical transcription companies
within the US. These MTSOs account
for 40% of the transcription job that are
outsourced in the US while only 5% of
these task are currently offshored to low
cost destinations such India, Philippines
and other Asian countries. (http://
w w w. s o u rc i n g n o t e s .co m /co n t e n t /
view/333/58/). This very clearly indicates
that several hospitals and physician
groups out in the US doesn’t favour the
off-shoring of medical records.
CSI Communications | November 2014 | 38
There have been widespread protests
by unions and employees of a hospital in
the east Midlands town of Leicester against
outsourcing of medical transcription work
to India as a part of plans to cut costs. For
the management, outsourcing of task such
as typing of letters by doctors would cut to
48 hours and save about 500,000 pounds
annually. The proposed changes when
implemented would cause loss of jobs for
the medical secretary’s - fears unions and
employees of the medical hospitals in UK.
(http://articles.economictimes.
indiatimes.com/2012-05-13/
news/31689733_1_outsourcing-movemedical-transcription-typing).
Use of technology has added another
dimension. The speech recognition
software is said to get upto 98%
accuracy in results. For the large player
in India adapting itself to the changes in
technology is seamless and in tandem
with the requirements of the industry. Also
these big players not only can afford to get
in new technology but also complement it
with apt training schedule which in turn can
tackle employee attrition/retention issues.
For the small India-based MT companies
bringing in the new technology is always
not affordable and hence it means lesser
flows of works to them which they could
bag either directly or via sub-contracting
earlier. Since smaller offshore vendors
are dependent on medical transcription
service organizations (MTSOs) for
subcontracted work, the non-compatible
obsolete technology makes it difficult to
change the task-giver perception that the
www.csi-india.org
capabilities of small offshore vendors are
found wanting on technology front. This
apparently means loss of opportunity
in MT offshoring job to smaller MT
companies.
For the small India based MT
industry facing stiff internal competition
and lack of stable and trained manpower;
advancements in speech recognition
and Electronic Health Records (EHR)
technology is adding new challenges
to their very existence. The technology
due to features such as easy to use is
gaining popularity and is expected to
be increasingly adopted by clinics in the
US.
(http://www.sourcingnotes.com/
content/ view/333/58/). This would
simply mean that a clinic on successful
implementation of EMR can stop
outsourcing transcription work and can
become self compliant to fulfil statutory
requirements of state/s altogether.
Availability of low cost technology
with low operational cost has definitely
boosted the confidence of physician to
acquire these applications in-house.
However, not all the EMR applications
follow the same methodology for creating
patient records. While some are strictly
non-customizable
but
standardized
template-driven point and click technique
others are DRT enabled, which allows
physicians to use traditional dictation
technique for feeding the data into the
system. Needless to say if the former
becomes more prevalent, need for
transcription will further decrease. (http://
mtherald.com/how-emr-ehr-is-going-toaffect-medical-transcription-industry/)
Currently one of the major concerns
for the medical practitioners is medical
accuracy of the patients’ data and this
view is getting stronger that Indian MT
organisations are not fully equipped to
handle this. But still India continues to
get the job outsourced to its shore. But,
what if the law makes it compulsory for
the physicians do it on their own to avoid
medical errors?
Revival Strategy that can Make India
Once Again the Preferred Destination
Though technology is a threat for Indian
MT industry but then it is and will not be
possible for all the doctors’ to switchover
instantly, physicians with less volume
of practice may not be able to afford to
automate and implement EMR solution
into their clinics. And these are the
targets for Indian MT industry. However,
once it becomes affordable - the word of
caution is, EMR in not too tough a task to
perform on a PC or a tablet, the easy to
use interface and training (as part of their
academics) is enough for the doctors to
fill in the prescription with few clicks. It’s
time clicking fast for Indian MT industry
to change and think fast to take advantage
of brand that India has created in the
outsourcing business over the years.
According to the Bureau of Labor
Statistics (US):
"Employment
of
medical
transcriptionists is projected to grow
faster than the average; job opportunities
should be good, especially for those who
are certified. Employment of medical
transcriptionists is projected to grow 14
percent from 2006 to 2016, faster than
the average for all occupations." (Source:
http://www.bls.gov/oco/ocos271.htm and
http:// mteducationonline.com)
About 80 medical transcriptionist
(MT) firms in Philippines have formed
the Medical Transcription Industry
Association of the Philippines Inc.
(MTIAPI), in order to provide standardized
training in various functions. It aims
at providing standardised training and
increasing the workforce three times as
that of present. The vision states “The
Organization envisions the Philippines to be
the offshore destination of choice for Medical
Transcription services.”(http:// www.ncc.
gov.ph/default.php).
In India too, efforts are being
made towards launching the training
programmes in medical transcription
especially for the rural youth. The 4-6
months program covering the subjects
like Science, US accent training, English
typing and grammar aims at improving
the quality of MT jobs and deliverables in
India. This would then help India spruce
up MT industry and make it ready to
tackle the threat from the countries such
as Philippines which are churning out
adequate numbers of trained manpower.
(http://www.sourcingnotes.com/content/
view/333/58/)
In
August
2004,
Medical
Transcription firms in the country formed
the Indian Medical Transcription Industry
Association with the aim of boosting the
growth to US$ 100 million (www.imtia.
net). Accessing the website, however,
gives the feeling that the association is
defunct with web links of some of the
founder members leading to load page
error. In the news and event section it
still shows the latest news pertaining
to August 6, 2004. One of the revival
strategies could be to have IMTIA as more
visible association representing India in
the field of MT globally. Consortiums
always help. Another key factor is the
wage. Currently, the wages for the medical
transcriptionist in India is:
National Salary Data
Salary
Rs 72,650 - Rs 348,068
per year ($1207.51 $5785.22 per year)
Bonus
Rs 0.00 – Rs 39,732 per
year
Certified
Professional
Coder
Employees
Rs 180,000 – Rs 3,60,000
per year ($2991.71
-$5983.55 per year)
(Country: India | Currency: INR | Updated:
9 Jun 2014 | Individuals Reporting: 336;
http://www.payscale.com/research/IN/
Job=Medical_Transcriptionist/Salary)
The above figures don’t inspire the
current generation youth to join the MT
industry as they perceive this to be the
dead end to their careers. Not only have
wages remained stagnant since the new
millennium, but the introduction of voice
recognition has actually reduced wages
by nearly one-half. Moreover even after
acquiring the certified profession coder
credential the salary ranges to about Rs
15,000 – Rs 30,000 per month which does
not meet the GenNext aspiration. With
perception that MT industry in India is not
doing enough to stand the competition,
the sector is moving towards the dead
end opines several of the MT professional
interacting on social network? Wage
correction and defining the standards can
help regain the past glory of MT industry
in India. Compare this to the wages in US:
US Data
$34,020 per year
$16.36 per hour
Entry-Level
Postsecondary
Education
non-degree award
Work experience in None
a related occupation
On-the-Job-Training None
Number of Jobs
84,100
2012
Job Outlook, 2012-22 8% (As fast as
average)
Employment
6,400
Change 2012-22
Quick Facts: Medical Transcription in
US (Source: http://www.bls.gov/ooh/
healthcare/ medical- transcriptionists.
htm)
2012 Median Pay
CSI Communications | November 2014 | 39
Inaccuracies in medical records
can put patients’ lives to risk. Once the
records are generated by transcriptionist,
the outsourced agency should make their
process of checking more rigorous and
ensure that records are accurate. This
would help rebuild the confidence of the
hospitals and doctors outsourcing their
task to India as they don’t have to recheck
the records before replacing the patient
information into the shelf.
Hacking, breach of security and
leakage of sensitive patient data are cited
as other reasons by hospitals and clinics
for not sourcing the MT tasks to India. It is
important for MT industry in India to build
the robust and protective security system
that will prevent the hacking as technology
advances, merely stating that hacking
happens day in and day out and even
military or banking data are not immune
to these kind of attempt will not suffice
and further alienate the MT outsourcing
task from India. (http://mtherald.com/
how-emr-ehr-is-going-to-affect-medicaltranscription-industry/)
or palm tops, connected to internet at ever
increasing speed, the internet of things
(IOT) is increasingly becoming a reality. The
practising doctor in U.S. is not an exception
to the bevy of users getting smarter in use
of these devices and technologies. In such a
condition the absence of even a functional
industry association may seem like the last
nail on the coffin- specially when a country
like Philippines is trying to catch up to give
a tough competition to established player
like India.
Will the Indian MT industry sit up and
notice? Will it use the same technology
disruption to its advantage? Quality is the
mantra. Can we take it to six sigma level
which can instil confidence in the hearts of
the users? Can we make it secure enough to
pass laws like HIPPA and standards like HL7.
Can we make it more productive so that we
can attract better talent who are in search of
better salaries? That is the need of the hour.
It remains to be seen how the Indian MT
industry copes with this challenge brought
about by new wave of technology.
References
Conclusion
For whom the bell tolls? The answer may
seem obvious to many given the rate of
change of technology. The same technology
which brought the MT work from the
faraway shores of U.S.A many years back
today seems to be a hindrance to the health
of the Medical Transcription job in general.
Technologies like speech to text and
handwriting recognition are terms which
we are becoming aware more and more in
everyday life. With the proliferation of hand
held devices, be it smart phones or tablets
[1]
[2]
[3]
[4]
[5]
[6]
[7]
Associated Press, June 2005. http://
www.medicaltranscription-solutions.
com/medical_
transcription_statistics.
html
Brady, JA Monk, EF & Wagner, BJ, 2001.
Concepts in Enterprise Resource Planning.
Bangalore: Thomson Course Technology.
Dhar-Patel, M & Vishwanath, CV eds.,
2002. The Economic Times: IT enabled
services – An ETIG report. Mumbai: The ET
knowledge series.
en.wikipedia.org
http:// mteducationonline.com
http:// www.ncc.gov.ph/default.php
http://articles.economictimes.indiatimes.
com/2012-05-13/news/31689733_1_
outsourcing-move-medical-transcriptiontyping
[8] http://indiabudget.nic.in.
Economic
Survey 2012-13
[9] http://mtherald.com/how-emr-ehr-isgoing-to-affect-medical-transcriptionindustry/
[10] http://www .sourcingnotes.com/content/
view/333/58/
[11] http://www. outsource2india.com
[12] http://www.aiita.org /news/blogs/3322medical-transcription-the-way-to-getyour-bright-career.html
[13] http://www.assistmed.com/
blog/
bid/79204/Save-Physicians-90Minutes-Per-Day-with-DRT-Transcription
[14] http://www.bls.gov/oco/ocos271.htm
[15] http://www.bls.gov/ooh/healthcare/
medical- transcriptionists.htm)
[16] http://www.chirocare.com/wp-content/
uploads/2013/03/HITTerms.pdf
[17] http://www.payscale.com/research/IN/
Job=Medical_Transcriptionist/Salary)
[18] http://www.slideshare.net/rohitpate
l203/medical-transcription-industry
[19] http://www.sourcingnotes.com/content/
view/333/58
[20] Nair, K (Dr.)., 2008. Medical Transcription
and India: The current scenario and the future.
Available at http://chillibreeze.com/
articles/MedicaltranscriptionandIndia.
asp [accessed 16 December 2008].
[21] Nuesoft Xpress TM Electronic Medical
Record accessed at http://mtherald.com/
how-emr-ehr-is going-to-effect-medicaltranscription-industry/
[22] www.call-centers-india.com/ites.html
[23] www.cbayscribe.com/cbaysystems/
index.htm
[24] www.imtia.net
[25] Yojana Aayog;-Planning Commission.
2000. India Vision 2020 [pl_vsn2020.
pdf], Government of India. Available at
http://www.planningcommission.gov.
in/plnre/pl_vsn2020.pdf; pg21 of 108.
n
[accessed on 5 April 2008]
Some of the facts are taken from blogs and other social networks, where the Medical transcriptionist and others associated with industry have expressed their opinions. These are
represented here for the academic purpose only. Also, websites are liberally referred - to get the overview of the industry and the prevailing conditions, the inferences are based purely
on the availability of these secondary data. The trademarks used here belong to the respective organisations and have been used here for the academic purpose as well.
CSI Communications | November 2014 | 40
www.csi-india.org
Kind Attention: Prospective Contributors of CSI Communications
Please note that Cover Themes for forthcoming issues are planned as follows:
•
December 2014 – Algorithmic Computing
•
January 2015 – IT Infrastructure
•
February 2015 – Quantum Computing
•
March 2015 – Machine Translation
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CSI Communications | November 2014 | 41
Innovations
in India
Rajiv Thanawala* and Prachi Sakhardande**
Product Experience CoE, Component Engg. Group, TCS
Software User Experience Maturity Model
To improve software code quality, we use
quality metrics that are measurable. Defects
per Line of Code, Cyclometric Complexity,
and so on, are examples of measurable
metrics that enable this. User Experience
(UX) is a critical quality aspect for software.
How can we then measure UX quality?
We assessed the existing UX
assessment methods. They revealed
that though the current UX assessments
helped identify usability flaws, they
lacked quantifiable metrics for an
objective review of UX quality, and also
lacked increasing levels of UX maturity
using which one can strive for continuous
improvement of UX quality.
To objectively and quantitatively
assess UX quality, we then formulated
User Experience Maturity Model
(UXMM) – a system and framework built
based on established UX assessment
techniques. UXMM is applicable to
software products and applications,
irrespective of its domain or device.
Figure 1 shows diagrammatic representation of User Experience Maturity Model.
Main features of UXMM are as follows:
•
4 hierarchical levels of UX maturity—
Usable, Useful, Desirable and
Delightful—indicating progression in
user experience
•
14 Key UX Parameters (KUXP)] –
Ease of Use, Speed of Use and others
as shown in the figure
•
Each KUXP comprising of attributes.
E.g. “Ease of Use” KUXP has
attributes like Ease of access, Ease
of Data Input, Visibility of System
Status etc. (not shown in the figure)
•
Levels 1 and 2 based on first 10
KUXPs—from ‘Ease of Use’ to ‘Help’
•
Levels 3 and 4 based on additional
4 KUXPs—from ‘Brand Recall’ to
‘Greater Good’
‘Expert Review’ used as assessment
method for certifying software at Level 1
•
‘Usability Tests’, ‘Competitor Analysis’
and ‘Emotional Heuristics’ used for
certifying software at Levels 2, 3 and 4
•
Quantitative scores as result of
assessments
The approach for UXMM assessment is as
follows:
1. Capture context of use of a software
application or product through a preassessment questionnaire. Based
on the context, UXMM system
generates weightages for each KUXP.
2. Steps to Certify for each Level:
2.1 UXMM system generates a level
specific benchmark score.
2.2 A usability expert rates the
application across KUXPs with
a scorecard based on a specific
assessment technique (‘E.g.
Expert Review’ for Level 1).
2.3 If this score is lesser than
benchmark score, the expert
identifies improvement areas.
Else, the software is considered
certified for that specific Level.
2.4 Once a level is achieved, repeat
steps 2.1 to 2.3 for the next level,
all the way up to Level 4: Delightful
Over the last two and half years, more
than 100 UXMM assessments have been
used to certify UX quality of our software
products and applications. Use of a
standardised assessment mechanism has
helped improve our products’ UX quality
and institutionalised UX as a practice.
•
Reference
[1]
About the Authors
Fig. 1: User Experience Maturity Model
TCS Published Patent Application – US
20130254735 A1 – ‘User Experience
Maturity Level Assessment’ – Prachi
Sakhardande, Rajiv Thanawala
n
(© 2014, Tata Consultancy Services Limited, Printed
with permission)
Rajiv has 25 yrs of experience in IT consulting and product development. He leads Product Experience Center of
Excellence which provides User Experience, Information Visualization, User Assistance and Customer Experience
services to a products group at TCS.
Prachi Sakhardande has consulted with Fortune companies and leads User Experience and Customer Experience
within Product Experience Center of Excellence for a products group at TCS. Her team is responsible for UX design
and benchmarking.
Innovators interested in publishing about their work can send a brief write up in 150 words to Dr Anirban Basu, Chairman, CSI Div V, at div5@csi-india.org.
CSI Communications | November 2014 | 42
www.csi-india.org
Security Corner
Jignesh Doshi* and Bhushan Trivedi**
*Associate Professor, L J Institute of Management studies
**Ph.D.
Information Security »
A Quick Look at Virtual Private Database Security
Introduction
Internet users and usage have increased
drastically in past few years. Internet
is widely used for business. Millions of
transactions are taking place via web
applications. Cyber attacks are becoming
more sophisticated day by day with
evolution of technologies and increasing in
numbers. Security is a big challenge for IT.
As per Open World Application Security
Projects (2013), 5 out of 10 top attacks are
related to databases.
A new attack, “Sensitive Data
Exposure” is added into top 10 list.
After getting access, attacker can dump
sensitive data like credit card number,
social security number, financial data
etc. As a result it may impact data loss,
negative publicity and a loss of customer
confidence.
Oracle Virtual Private Database
(VPD) is one of the key technologies
powering sensitive data theft prevention.
In this article, some of the ways in which
sensitive data exposure can be prevented
using Oracle Virtual private Database is
discussed.
Limitations of Traditional Security Policies
There are two types of database
security available in oracle databases
are Discretionary access control using
grant and revoke (DAC) and Mandatory
Access Control (MAC).
Two level of access privileges can
be granted using DAC security policy, at
account level ( like create table, drop table
etc.) and table level (like insert, update,
select or delete). DAC is very flexible
policy and DBA must provide selective
access using Grant or Revoke statements.
In many applications, additional security
policy is needed for classifying data and
users based on security classes. This
approach is known as Mandatory Access
Control.
Most commercial DBMS provide
mechanisms only for Discretionary
Access Control.
Security Flaws in DAC and MAC is
summarized as below:
What is VPD?
Oracle Virtual Private Database (VPD)
enables you to create security policies to
control database access at the row and
column level. VPD can be enforced directly
on database tables, views, or synonyms.
We can apply VPD policies on SELECT,
INSERT, UPDATE, INDEX, and DELETE
statements. Oracle database engine
automatically applies security functions
whenever a user access data and there is no
way to bypass security i.e. adds a dynamic
WHERE clause to a SQL statement.
Security Policy Drawbacks
1) In this security
DAC
policy. users either
have or do not have
a certain privilege.
2) No method to Limit
propagation
e.g.
one can not restrict
GRANT
OPTION
privilege to at most
‘n’ other accounts.
3) Not suitable for high
security data.
MAC
1) Not flexible as a
result it can not
work with all types
of applications.
How Oracle Virtual Private Database
Works?
VPD execution flow is narrated in Fig. 1.
Whenever any statement is executed,
DBMS engine checks whether security
policy is configured on the objects found
in query or not. If security policy is
configured on the objects of query, it will
modify query and execute the query.
With DAC security policy, we can not
restrict data selection at horizontally
(row) or vertically (column) level. i.e. if
we want to restrict that AR user can see
only his department data or he can not see
salary of employees.
How to Configure?
Pre-requisites: Fine grained access
control must be enabled in database.
Check using query “select * from v$option
where parameter = 'Fine-grained access
control”, it should be TRUE.
ROW LEVEL VPD Security Policy
One can create multiple security policies
on different objects using same function.
We can apply row level security directly
on database tables, views, or synonyms.
Row Level VPD configuration is a two
step process.
i) In first step, we will create the stored
function.
ii) Second step comprise of creation
of security policy using DBMS_RLS
CREATE OR REPLACE FUNCTION
SEC_AUTH_ORDERS
(SCHEMA_VAR IN VARCHAR2,
TABLE_VAR IN VARCHAR2 )
RETURN VARCHAR2 IS RETURN_
VAL VARCHAR2 (400);
BEGIN
RETURN_VAL := 'SALESMAN_ID
= 101';
RETURN RETURN_VAL;
END AUTH_ORDERS;
Fig. 1: Oracle VPD processing flow
Table 1: Security Function
CSI Communications | November 2014 | 43
package for stored function created
in step 1.
Example: If you have configured policy
such that JOHN can view only his sales
orders and employee id of John is 101.
Step 1: Create Security Function
Create the stored function (refer to
Table 1), which will append the WHERE
SALESMAN_ID = 101 clause to any SELECT
statement on the OE.ORDERS table.
Step 2: Create the Oracle Virtual Private
Database Policy
BEGIN
DBMS_RLS.ADD_POLICY (
OBJECT_SCHEMA => ‘OE’,
OBJECT_NAME => ‘ORDERS’,
POLICY_NAME => ‘SEC_POLICY_
ORDERS’,
FUNCTION_SCHEMA => ‘SYS’,
POLICY_FUNCTION => ‘SEC_
AUTH_ORDERS’,
STATEMENT_TYPES => ‘SELECT,
INSERT, UPDATE, DELETE’ );
END;
Table 2: Security Function
using DBMS_RLS package.
Two ways to implement column level
security policies are as below:
•
Displaying Only the Column Rows
Relevant to the Query
•
Using Column Masking to Display
Sensitive Columns as NULL Values
We can apply column-level security
policies to tables and views, but not
to synonyms. Let us understand using
example.
Example: Security policy in which
Chicago sales users cannot see the salaries
a) Security Function
CREATE OR REPLACE FUNCTION
SEC_HIDE_SALES_DATA
(SCHEMA_VAR IN VARCHAR2,
TABLE_VAR IN VARCHAR2 )
RETURN VARCHAR2 IS RETURN_
VAL VARCHAR2 (400);
BEGIN
RETURN_VAL := 'LOCID=15';
RETURN RETURN_VAL;
END AUTH_ORDERS;
b) Configure security Policy
BEGIN
DBMS_RLS.ADD_POLICY (
OBJECT_SCHEMA => 'OE',
OBJECT_NAME => 'EMPLOYEE',
POLICY_NAME => 'SEC_POLICY_
HIDE_SAL',
POLICY_FUNCTION => 'SEC_
HIDE_SALES_DATA',
SEC_RELEVANT_COLS =>
'SAL,COMM');
END;
Next, create the policy (refer to Table 2)
using the ADD_POLICY procedure in the
DBMS_RLS package.
How security policy will work?
Query Executed
by JOHN
Converted Query
by VPD
SELECT* FROM
OE.ORDERS;
SELECT* FROM
OE.ORDERS
WHERE SALESMAN
_ID = 101;
About the Authors
COLUMN LEVEL VPD Security Policy
Column Level VPD configuration is a two
step process. In first step, we will create
the stored function. Using it we will define
row level access control Second step
comprise of creation of security policy
and commission details of people outside
the Chicago. (Location id is 15 for Chicago).
Above security policy will display salary
and commission details of Chicago sales
representatives only. However, super user
can view all details.
Conclusion
Key Benefits of Oracle Virtual Private
Database security policies are as below:
•
High Level of Security:
˚ As plemented at database level, it
provides consistent access control
on tables, views or synonyms, no
matter from where user access
data ( Front end, back end or third
party tools)
we
can mitigate Sensitive data
˚
exposure risk using VPD security
policies.
•
Simplicity;
˚ Adding security policy is very easy
and simple.
•
Flexibility.
˚ One can create different policies
for different operations (select,
insert, update or delete) on same
table.
Security policy functions run as it had
been declared with definer’s rights so
do not declare it with invoker’s rights.
We can extend user Role based access
control (RBAC) to fine grained row or
column level.
References
[1] OWASP:
https://www.owasp.org/
index.php/Top_10_2013-A1-Injection:
accessed 31st May 2014
[2] Internet hosting statistics : http://www.
netcraft.com/internet-data-mining:
accessed 31st May 2014
[3] Common Weakness Enumeration:
h t t p : //c w e . m i t r e . o r g /d a t a /
definitions/89.html : accessed 3rd June
2013
[4] Internet
users
:
http://www.
internetlivestats.com/internet-users:
accessed 14th June 2014
[5] Oracle documentation ; docs.oracle.
com
[6] DBMS_RLS :docs.oracle.com: visited on
25th july 2014.
n
Jignesh Doshi received the B.Sc (Maths) and M.C.A. degrees in 1989 and 1992, respectively. He is an Oracle Certified
Professional ( OCP 10g). He has nearly 22 years of experience. During 1992-2008, he worked in various IT firms like
Patni Computer Systems, Vodafone (Fascel), Gujarat Lease Financing Ltd., Erhardt + Leimer (I) Ltd.. Since 2008, he is
working as associate professor at L J Institute of Management studies. His areas of interest are Database, Database
security and Data warehousing and data mining.
Bhushan Trivedi received Ph.D. in 2008. He has nearly 25 years of teaching experience. His areas of interest are
Intrusion Detection with mobile agents, Sensor Networks, Using artificial intelligence techniques to solve real world
Problems. He had conducted workshops on Effective Teaching (20), "how to debug a network with TCPDUMP and
WireShark" (15) and “how to write an effective research paper” across India. He has written books are on ANSI
C++ and Computer Networks under Oxford publications. He is guiding 8 students in their doctorate degree.
CSI Communications | November 2014 | 44
www.csi-india.org
Security Corner
Dr. Vishnu Kanhere
Convener SIG – Humane Computing of CSI (Former Chairman of CSI Mumbai Chapter)
Case Studies in IT Governance, IT Risk and Information Security »
Visualization – to make visible: Visualization covers a wide range from mental and creative visualization to geo visualization, flow
visualization, computer graphics, data visualization and even network visualization. Visualization has been used by mankind since
its early days and is not a new concept. The early prehistoric cave paintings and the later Egyptian hieroglyphs are examples of the
use of visual symbols and pictures by humans to communicate, convey and interact meaningfully. Visualization has found growing
acceptance and extensive use in science, education, engineering, communication, multimedia and medicine to name a few. In the
field of computing the growth and emphasis on use of visualization was limited due to the lack of graphics power. However, since late
1990’s the field has seen an accelerated growth which has been further boosted with the use of computer animation. Moving forward
from the more familiar digital animations used for weather pictures and satellite photos and the complex scientific 2D & 3D imaging,
- visualization is now being used for educational animations, and dynamic representation of timelines.
Computer Visualization has two main aspects. The first is a major benefit in terms of providing a powerful tool for better and
smarter governance. Governance whether of nations, corporate, organizations, entities or individuals requires a robust measurement
and reporting system and efficient MIS for better control, monitoring, corrective action and delivery. Computer visualization has enabled
improved meaningful MIS which has provided a strong boost at a micro as well as macro level, for both IT and corporate governance.
In today’s information age an increasing amount of data is being created by the internet and social media and the various sensors
in and around us – be it the CCTV’s in offices, public places, housing societies or at traffic signals, which in turn does at times get
related or is relatable to data bases holding personally identifiable information like PAN data base, Aadhaar data base etc. This data is
often referred to as Big Data. Computer visualization includes Data visualization which enables and improves the processing, analyzing
and communicating of this Big Data. This is the second aspect. In this context visualization of Big Data presents a variety of ethical
and analytical challenges for visualization.
The potential threats to the data and from the use of such data are many – these primarily arise from the SMAC threats which
are ever present in mobile, social media, cloud environment and in analytics – since visualization does require and makes extensive
use of analytics.
Mobile devices are not always secured, are often mishandled, lost or stolen and used for almost all activities, both personal and
professional exposing data.
Social media has its own vulnerabilities with users, their friends and relations indiscriminately and accidentally posting and
exchanging sensitive information.
Analytics aggregates and analyzes such information making it even more critical, hence enlarging the threat.
Finally, the Cloud has removed the barriers between the entity dealing with the information and the outside world. Even if you are
not on the cloud your service providers, associates, users, are bound to be there and that is enough to increase the risk further.
In such situation the need has arisen for a specialized field in Governance – the field of data governance to improve data security
and to ensure accountability and ethics in use of data within a robust framework that promotes public confidence.
Given this background the current Case in Information Systems is being presented. The facts of the case are based on information
available in media reports, online information and some real life incidents. Although every case may cover multiple aspects it will have
a predominant focus on some aspect which it aims to highlight.
A case study cannot and does not have one right answer. In fact answer given with enough understanding and application of mind
can seldom be wrong. The case gives a situation, often a problem and seeks responses from the reader. The approach is to study the
case, develop the situation, fill in the facts and suggest a solution. Depending on the approach and perspective the solutions will differ
but they all lead to a likely feasible solution. Ideally a case study solution is left to the imagination of the reader, as the possibilities
are immense. Readers’ inputs and solutions on the case are invited and may be shared. A possible solution from the author’s personal
viewpoint is also presented.
A Case Study of Netrapur Police
Satyarthi the SP of Netrapur was newly
posted to this state. He is tech savvy and
wishes to go in for major initiatives to make
his policing better and more effective.
He has unveiled his policing plans and
initiatives. He has planned to introduce
state of the art surveillance system “Sannirikshan” initially in the urban and the
remote far flung areas followed up by
coverage of the semi urban and rural
parts of Netrapur. He is convinced that
adopting state of the art monitoring
technology with face recognition software
for CCTVs and cross referencing with
universal data base of Aadhaar and PAN
will enable quick identification of persons
from footage and help prevent, detect
and resolve crimes effectively. It will also
improve policing with rapid pinpointed
and effective action. Coupled with this
he also plans to introduce cyber-policing
of the internet, social media and mobile
messaging using network traffic analysis.
Combining these two in “san-nirikshan”
will enable compilation of Big Data and
computer visualization of all the activities
of the population helping in curbing of
criminal, anti social as well as socially and
morally reprehensible practices.
He calls a meeting of his top officials
and shares his viewpoint. He emphasizes
that adopting “san-nirikshan” and using
visualization will enable Netrapur police to •
Go beyond geo-political, cultural,
social and physical barriers
•
Deploy cost effective policing
CSI Communications | November 2014 | 45
solutions enabling comprehensive 24
by 7 coverage
•
Enhance operations and logistics
enabling rapid and effective response
•
Enable better data gathering and
analysis with visualization for crime
prevention and promoting moral and
ethical society
•
Promote inter-state and inter-agency
collaboration and exchange of data
•
Use real time data analytics and
advanced visualization techniques
thereby improving the policing
process
enabling
deterrence,
prediction and prevention of crimes
that are about to happen
•
Enable rapid scaling up and right
sizing of the Police force and support
internal and external security
His CP Varun Pal and Joint CP
Crime Vishal are apprehensive of the far
reaching changes and possible impact
especially given the fact that such a major
initiative is being adopted without taking
the people into confidence and virtually
being thrust on the public. Samar the DSP
is extremely bullish and is certain that this
would provide a definite edge to the police
force over criminals, terrorist networks,
anti-social elements and trouble makers
and keep the pseudo intellectuals who
generally foment trouble over human
rights as well as the media in check.
Anticipating some resistance to the
project – “san-nirikshan” from intellectuals
and vested interests Satyarthi emphasizes
that there are both privacy / human rights
concerns as well as deployment issues.
He selects a crack team consisting of
Samar, Varun and Vishal to overcome the
social resistance and nip it in the bud to
enable smooth deployment. They are
also tasked to put in place systems to
address the various issues and concerns
about deploying “san-nirikshan”. The
political set up is fully supportive of the
project and has already given a go ahead
using administrative powers. The project
involves sensitive internal security issues
and hence is outside the purview of
RTI, and is to be kept confidential with
complete media blackout.
The crack team develops a plan and
submits it. Varun is very uneasy with the
manner in which the whole project is
steamrolled. He seeks an appointment
with Satyarthi and voices his reservations
about privacy and human rights and
freedom of the press. He suggests that
the project be introduced in remote
areas first as a pilot and then extended
to metro cities in a transparent manner. If
implemented initially on a small scale and
then deployed in phases taking the people
into confidence it will be both acceptable
and successful.
Satyarthi rejects Varun’s approach,
points out the increasing criminal activities
and terrorist attacks and stresses the
need for a full deployment with utmost
secrecy. He advises Varun to go ahead and
implement the plan as it is.
After much persuasion Varun relents
and the project is implemented. The
project achieves quick and remarkable
success. A number of criminal gangs are
neutralized, terrorist activities are visibly
reduced. The backbone of the Naxalite
resistance in remote areas is broken and as
a result the law and order situation in the
state of Netrapur improves considerably.
The police are lauded for their good work
and Satyarthi is promoted. Varun is still
ill at ease and opts for a posting in the
police housing project where he remains
till retirement.
What are your views on project “san-nirikshan”?
Solution
The situation:
Visualization techniques using computer
graphics and imagery, analytics and
presentation using visualization techniques
relating to Big Data especially from Social,
Mobile, Analytics and Cloud technologies
have added a new dimension to surveillance.
The eyes and ears of the police – the Big
Brother are now omnipresent. Surveillance
and use of covert means and secret agents
including agencies like FBI, MI6 and KGB
are common in countries subscribing
to all shades of political, economic and
social viewpoints. The recent use of similar
techniques by the US, to tackle terror and
ensure ‘Homeland Security’, has been
accepted without question. It has had a
significant impact across the world and an
even more profound impact on privacy and
human rights.
There exists a case both for and
against the use of technology for such
means and the case both for and against
use of visualization techniques for internal
and external security is equally strong.
Information technology when combined
with technological advances like street
CSI Communications | November 2014 | 46
level view satellites and micro drones
carrying eavesdropping equipment and
remote CCTVs make the visualization and
analytical technology even more powerful.
The way forward therefore cannot
be either to pull the plug on use of Data
visualization for internal policing and / or
external defense or to wait and watch till
the technology is deployed, stabilizes and
is eventually safe and acceptable enough
to adopt.
The challenge:
Disruptive technology as has often been
said needs proper governance. In the same
fashion use of Data visualization has to be
understood, the risks appreciated and the
technology proactively adopted.
There are primarily four challenges
which need to be understood and
considered.
1. Preventing the potential abuse of the
technology and the power it provides
either for selective victimization,
oppression, political misuse, or moral
policing
2. Preventing the leakage, compromise
and misuse of the data resulting
in harm to the community or to
individuals
3. Preventing the loss of privacy and
fundamental human rights
4. Preventing the loss of freedom
of expression and preserving the
opportunity for reasonable dissent
and difference of opinion either
collective or individual.
The consequences:
Continuing in the existing fashion with
the project, given the lack of proper
governance and transparency may despite
initial encouraging results, ultimately lead
to a totalitarian situation where a handful
few control the multitude. It will pose a
clear threat to the democratic polity and
cultural ethos. Ethical values may not be
maintained and freedom of expression
and privacy may be lost.
The strategy:
The right strategy for the state of Netrapur
at this stage would be:
1. The four arms – the parliament, the
executive, the judiciary and the press
and public need to understand the
technology and the pressing need to
deploy it.
2. Understand and agree on the need
of using Big Data Visualization and
www.csi-india.org
3.
4.
About the Author
5.
analytics for internal and external
security and protection.
Understand potential threats of
abuse, leakage, and threats to privacy,
fundamental rights and freedom.
Develop a GRC (Governance, Risk,
and Compliance) framework with
proper safeguards and security built
in to protect integrity and ethical
values and prevent misuse.
Deploy framework and manage
Vulnerabilities and threats.
6.
Ensure appropriate controls to
protect the system from future abuse
or compromise.
It is evident from the reported
and unreported incidents till date that
aberrations are possible and misuse
cannot be entirely prevented. However
given the pressing need for adopting
emerging technologies the way forward is
to proactively adopt Data visualization and
analytics. The police in Netrapur cannot
afford to lag behind their counterparts in
other countries and states, nor fall short
of the criminal and terrorist networks.
The police have to be where the action
is and even where the action is going to
be in a proactive manner. Likewise the
governance and security framework and
its scope have to deal both with the threats
and the key issues identified above.
An effective solution is generally
expected to proceed on these lines.
n
Dr. Vishnu Kanhere Dr. Vishnu Kanhere is an expert in taxation, fraud examination, information systems security and system audit and has done
his PhD in Software Valuation. He is a practicing Chartered Accountant, a qualified Cost Accountant and a Certified Fraud Examiner. He has over
30 years of experience in consulting, assurance and taxation for listed companies, leading players from industry and authorities, multinational
and private organizations. A renowned faculty at several management institutes, government academies and corporate training programs, he has
been a key speaker at national and international conferences and seminars on a wide range of topics and has several books and publications to
his credit. He has also contributed to the National Standards Development on Software Systems as a member of the Sectional Committee LITD17
on Information Security and Biometrics of the Bureau of Indian Standards, GOI. He is former Chairman of CSI, Mumbai Chapter and has been a
member of Balanced Score Card focus group and CGEIT- QAT of ISACA, USA. He is currently Convener of SIG on Humane Computing of CSI and
Topic Leader – Cyber Crime of ISACA(USA). He can be contacted at email id vkanhere@gmail.com
CSI Communications | November 2014 | 47
Brain Teaser
Dr. Debasish Jana
Editor, CSI Communications
Crossword »
Test your Knowledge on Visualization Technologies
Solution to the crossword with name of first all correct solution provider(s) will appear in the next issue. Send your answers to CSI
Communications at email address csic@csi-india.org with subject: Crossword Solution - CSIC November 2014
CLUES
ACROSS
1.
5.
6.
7.
8.
9.
10.
11.
15.
16.
17.
19.
21.
22.
23.
24.
27.
28.
29.
Displays tree data structure in a way that expands outwards (9)
A property or characteristic of data (9)
A common data visualization method used in computational fluid
dynamics (10)
A data structure optimized to quickly answer multi-dimensional
analytical queries (4)
A schematic representation of a sequence of operations in a computer
program (9)
Used in project management to illustrate schedule of a project (5, 5)
Type of diagram used for data visualization (11)
Type of diagram showing the flow of data through an information system (4, 4)
A graphical representation of data (5)
Field lines resulting from this vector field description of the flow (11)
Type of fishbone shaped diagram that shows the causes of a specific event (8)
open source JavaScript charting library (8)
Type of dictionary that illustrates the meaning of words primarily
through pictures (6)
A sequence of related images viewed in rapid succession to show
apparent movement of objects (9)
Online analytical processing (4)
comma separated values (3)
Online transactional processing (4)
Displays a list of events in chronological order (8)
Microsoft Windows-based visual mapping software (10)
DOWN
2.
3.
4.
9.
12.
13.
14.
18.
20.
Did you know view of Hal Varian on how the Web challenges managers?
Hal Varian, Google’s chief economist commented in The
McKinsey Quarterly, Jan 2009:
The ability to take data—to be able to understand it, to process
it, to extract value from it, to visualize it, to communicate it—
that’s going to be a hugely important skill in the next decades,
… because now we really do have essentially free and ubiquitous
data. So the complimentary scarce factor is the ability to understand that data
and extract value from it.
25.
26.
Organic-looking n-dimensional objects used in computer graphics for
visualization (8)
An open-source Java based framework that allows the creation of a wide
variety of charts (10)
An assignment of a vector to each point in a subset of space used in vector
calculus (11)
Visualization technique supporting geospatial data analysis (16)
Describes the property that allows light to partially pass through and
partially reflect (12)
What you see is what you get (7)
A measure of spatial extent, especially width, height, or length (9)
an open-source network analysis and visualization software package
written in Java (5)
An effect that causes different signals to become indistinguishable when
sampled (8)
Type of diagram that shows all possible logical relations between a finite
collection of sets (4)
Symbol or icon used to represent data values (5)
Solution to October 2014 crossword
(More details can be found in
http://www.mckinsey.com/insights/innovation/hal_varian_on_how_the_web_challenges_managers)
We are overwhelmed by the responses and solutions received from our enthusiastic readers
Congratulations!
ALL correct answers to October 2014 month’s crossword received from the
following readers:
Prof. Suresh Kumar (Dept. of Computer Science and Engineering, Manav
Rachna International University, Faridabad)
CSI Communications | November 2014 | 48
www.csi-india.org
Ask an Expert
Dr. Debasish Jana
Editor, CSI Communications
Your Question, Our Answer
“There is a magic in graphs. The profile of a curve reveals in a flash a whole situation — the life history of an epidemic, a panic, or an era of
prosperity. The curve informs the mind, awakens the imagination, convinces.”
~ Henry D. Hubbard, 1939
On Object Oriented Programming
From: Himanshu Raghav, B.Sc. Final Year,
Dev Sanskriti Vishwavidyalaya, Haridwar,
Uttrakhand
I want to know the concepts of object oriented
programming with example that I can easily
understand them and not forget them in my whole
life time.
A
Object Oriented Programming (OOP) involves
a new paradigm of concepts to programmers
of traditional procedural languages such as Pascal,
C, FORTRAN, COBOL etc. These new ideas, such as,
data hiding, encapsulation and polymorphism lie at the
heart of OOP. In OO system, the system is based
on objects rather than on actions. Here, procedures
operate on abstract values called objects rather than
on stored representations. Objects interact with each
other through well-defined interfaces. Objects can be
created and destroyed dynamically. Commonality of
objects can be made explicit by using inheritance.
OO paradigm has two important philosophies:
data hiding and data abstraction. Data hiding philosophy
says to partition the program so that data is hidden
in modules such that users of the service shouldn't
know the underlying implementation. Internal
representation can be accessed from internal
implementation and not by the users of the modules.
Data abstraction philosophy says to decide which
types are needed, to provide full set of operations
for each type so that a new type of data if defined
can be used similar to built in type of data with all
sort of operations permissible. Data abstraction is
the decision to concentrate on properties, which are
shared by many objects or situations in the real world,
and to ignore the differences between them.
In contrast to procedural programming paradigm
to have a large single store where all procedures work,
in Object-Oriented paradigm, procedures operate
on abstract values called objects rather than on
stored representations. OO programming paradigm
is based on the idea of communicating between
objects to simulate the temporal evolution of a set
of real world phenomena. Data as well as operations
are encapsulated in objects. Information hiding is
used to protect internal properties of an object.
Objects interact by means of message passing or
function invocations. Objects are active entities that
communicate with each other. State of an object may
change in response to some interaction requested
from some other object. In object-oriented paradigm,
objects are grouped in classes. Objects in classes are
similar enough to allow programming of the classes,
as opposed to programming of the individual objects.
Let’s take an example of approach in
implementing say, a stack using procedural paradigm
through C and same implementation using object
oriented paradigm using C++, and let’s compare the
philosophy by discussing pro’s and con’s.
‘C’ implementaion of Stack
#include <stdio.h>
#define MAX_SZ 10
typedef struct {
int data[MAX_SZ];
int sp;
} STACK;
void Init(STACK *which) {
which->sp = -1; //initialize the
stack
}
bool Push(int d, STACK *which) {
if (which->sp == MAX_SZ-1) //
overflow
return false;
which->data[++which->sp]=d;
return true;
}
bool Pop(int *d, STACK *which) {
if (which->sp == 1) // underflow
return false;
*d = which->data[which->sp--];
return true;
}
int main() {
STACK s1, s2;
Init(&s1);
Init(&s2);
Push(3, &s1);
Push(4, &s2);
Push(5, &s2);
int d;
Pop(&d, &s1); // d becomes 3
Pop(&d, &s2); // d becomes 5
Pop(&d, &s2); // d becomes 4
return 0;
}
In the above approach, we find little strength and few
weaknesses, which are kind of risky.
int data[MAX_SZ];//by default,
private
int sp; // by default, private
public:
STACK() { this->sp = -1; }
bool Push(int d) {
if (this->sp == MAX_SZ-1) //
overflow
return false;
this->data[++this->sp]=d;
return true;
}
bool Pop(int &d) {
if (this->sp == 1) // underflow
return false;
d = this->data[this->sp--];
return true;
}
};
int main() {
STACK s1, s2; //constructor call
s1.Push(3);
s2.Push(4);
s2.Push(5);
int d;
s1.Pop(d); //d passed as reference,
//d becomes 3
s2.Pop(d); // d becomes 5
s2.Pop(d); // d becomes 4
return 0;
}
Strength, first
The effect?
1.
1.
2.
The program is structured, written in a
methodical way
Multiple stacks can be used, since stack pointer
is not kept as a global data. Keeping one global
data as stack pointer restricts the usage of
multiple stacks
2.
3.
Weaknesses
1.
2.
3.
4.
5.
#define has its own hazards, if we by mistake
put a semicolon after #define MAX_SZ 10; or a
line comment i.e. //, we fall into trap of macros.
#define does not ensure datatypes, which are
essence of any data
The implementation is well exposed, yet not
protected from wrong usage by the user. For
example, the person who writes main, may
start accessing s1.data[2] directly, absolutely no
control on that.
What happens if the user (who writes main)
forgets to initialize the stack by calling Init?
Push, Pop take d as a pointer, and the pointer is
passed by value (not reference) in C. Passing
pointer is kind of risky, as, we don’t know
whether the pointer is pointing to a valid content
or not, a pointer may be null or spurious having
uninitialized data, which is very risky.
Now, let’s see if we take a C++ route through
object-orientedness.
#include <stdio.h>
const int MAX_SZ = 10;//put ; at your
will
class STACK {
4.
5.
#define has its own hazards, we don’t fall into
trap of macros. Instead, we define an integer
constant.
const int ensures datatypes, which is the
essence of any data
The implementation is well exposed, yet
protected from wrong usage by the user.
For example, the person who writes main, is
prevented from accessing s1.data[2] directly, as
the data is private within a stack.
No chance of forgetting by the user (who writes
main) to initialize the stack. constructors are
called automatically when variables (objects)
are declared.
Push, Pop take d as a integer reference, saves
memory, also, no pointer is passed explicitly,
putting less risk and also looks elegant. No risk
of un-initialized data exists.
A class is a construct for implementing a userdefined type. Once defined, such types may be
conveniently used as the languages primitive types.
The instances of a class are called objects. A class
specifies the representation of objects and a set of
operations that are applicable to such objects. We
have already discussed two important philosophies
of object oriented programming as data hiding and
data abstraction. Ideally, a class is an implementation
of an abstract data type. This implies that the
implementation details of the class are private to
the class. The public interface of a class is exposed
externally.
n
Do you have something to ask? Send your questions to CSI Communications with subject line ‘Ask an Expert’ at email address csic@csi-india.org
CSI Communications | November 2014 | 49
Happenings@ICT
H R Mohan
ICT Consultant, Former AVP (Systems), The Hindu & President, CSI
Email: hrmohan.csi@gmail .com
ICT News Briefs in October 2014
The following are the ICT news and headlines
of interest in October 2014. They have been
compiled from various news & Internet sources
including the dailies - The Hindu, Business Line,
and Economic Times.
Voices & Views
•
Smartphones, data plans cheapest in
India, the Internet access remains beyond
the grasp of about 95 crore people. It is
predicted about 30 crore Internet users will
be added by 2018, taking the total number
to 50 crore users. Even the cheapest data
plans are simply too expensive, equal to
13% of the total spending of people in the
segment – McKinsey.
•
The demand for regular satellite capacity
in India has been growing at over 6%
between 2008 and 2013 and now
reached 214 transponder equivalents –
Euroconsult.
•
Better urban planning through telecom
networks – LIRNEasia.
•
The global semiconductor revenue is
on pace to reach $338 billion in 2014,
a 7.2% increase from 2013. In 2014,
unit production of smartphones and
ultramobiles to increase 27% and 18.9%
respectively – Gartner.
•
Smartphones, a tool for driving
productivity. Globally, one-third of
business smartphone users said their
devices save them more than 5 hours
during an average working week – survey.
•
The domestic demand of electronic goods
is projected to grow to $400 billion by
2020, of which domestic production can
cater to only $100 billion.
•
India is a test-bed to create tools, ideas
for the world. Internet growth in India will
have a big global impact – Zuckerberg.
•
India is destination of choice for
engineering R&D - BVR Mohan Reddy,
Vice-Chairman, Nasscom.
•
India today is a home to over 600 ER&D
companies, and over 400 global ER&D
organisations with 2,00,000 engineers
are employed by service providers and
engineering firms.
•
As e-commerce grows, protecting
consumers is a challenge – Paswan.
•
Cyclone Hudhud hits, 1000 crore revenue
generating IT industry at Vizag.
•
Online retailing - both direct and through
marketplaces - will become a Rs. 50,000
crore industry by 2016, growing at a
whopping 50-55% annually over the next
three years - Crisil Research.
•
Mobile messaging apps eating into telcos’
SMS revenue. Operators worldwide will
lose $14 billion to OTT services this year
- Juniper Research.
•
E-commerce sector, which is a little less
than one per cent (at $3.2 billion) of the
$700-billion retail industry, has attracted
several global investors in a short span of
time – Industry experts.
•
India is the third largest base for startups in the world with 3,100 of them after
the US (41,500) and the UK (4,000) Nasscom.
Govt, Policy, Telecom, Compliance
•
Vizag smart city to get US-funding.
•
DoT ropes in ISRO scientists to explore
use of satellite for broadband.
•
Four years after receiving 4G spectrum,
telecom operators - Airtel, Reliance Jio and
Aircel have approached the DoTseeking
another five years to complete their
rollout obligation.
•
Two electronic manufacturing clusters
(EMC) coming up in Madhya Pradesh
at Purva near Jabalpur and Badwai near
Bhopal. They will be the first greenfield
EMCs in the country.
•
Audit by CAG finds under-utilisation
(compared to a total collection of Rs.
58,579 crore, only Rs. 17,947 crore has
been disbursed), misuse of Universal
Services Obligation funds. In three circles
(Kerala, Tamil Nadu and Karnataka),
subsidy amount of Rs. 20.34 crore was
allowed for 32,759 multiple connections
in the name of one person/address and
for more than one member of a family at
the same address.
•
Centre to use Aadhaar-based system to
track staff attendance.
•
Zuckerberg meets PM and IT Minister to
discuss how Facebook can help with the
Digital India mission.
•
Govt to start reimbursing electronic firms
under special incentive scheme soon.
•
2G auction: TRAI for 10% hike in 1800
MHz base price at Rs. 2,138 crore per
MHz.
•
Karnataka drafts policy on rural BPOs;
Cabinet nod soon.
•
India may dilute stand on Net control.
Proposes backing for the popular view on
a multi-stakeholder approach to Internet
Governance.
•
US-based Iridium wants a piece of the
Indian satellite services play.
•
Green signal for entire SmartCity Kochi
project.
•
IT firms get domestic boost due to Govt.
IT spending.
•
Japan’s SoftBank to invest $10 billion in
India. Picks up stake in Snapdeal ($627m),
Ola ($210m)
IT Manpower, Staffing & Top Moves
•
EMC at Jabalpur will generate around
3,000 direct employment opportunities
and around 9,000 indirect employment
opportunities.
•
Kris Gopalakrishnan’s innings at Infosys
set to end on 10th Oct 2014. He recently
donated $35 million to IISc for brain
research and $1.8 million to CMU to fund
its research partnership with IISc.
•
Yahoo! India R&D Centre lays off 600 in
engineering & product development.
•
S. Ramadorai steps down from Tata
companies.
•
Out of Yahoo! into waiting arms of startups, e-commerce firms.
•
Pegasystems to tap varsities, Java, .NET
professionals.
•
TCS plans to hire 35,000 from campus
this year.
•
Software majors on hiring spree in Sept
quarter.
CSI Communications | November 2014 | 50
Company News: Tie-ups, Joint Ventures, New
Initiatives
•
The country’s, claimed to be the first
dedicated medical search engine - www.
braham.in to emerge as a one-stop-shop
information source for all medical and
healthcare-related information has been
lauched.
•
Online car rental companies - Meri Cabs,
Ola Cabs have launched digital wallets.
Others like Savaari, Taxiforsure, TabCab,
Uber and Mytaxiindia are also said to be
in talks with firms such as Citrus, PayU
and Paytm for creating a mobile or digital
wallet.
•
Microsoft to continue with the Nokia
brand continues in the entry and feature
phones for the next 10 years. In the
smartphones space, they will be branded
as Lumia.
•
Flipkart fumbles on the “Big Billion Day”
on 6th Oct 2014, as server fails. Flipkart
says sorry for mega snag. But claims to
a have received a billion hits with about
1.5 million people shopped and achieved
a 24-hour sales target of $100 million in
gross merchandise value in just 10 hours.
•
Hewlett-Packard spinoff likely to hit
Mphasis outsourcing biz.
•
Flipkart campaign leads retailers to
Amazon as www.bigbillionday.com were
redirected to rival online marketplace
www.amazon.in
•
Pre booking starts by Apple for its launch
of iPhone 6 and iPhone 6 Plus in India on
October 17.
•
Microsoft Devices will now import phones
from the Hanoi (Vietnam) factory instead
of the facility owned by Nokia in Chennai.
•
DigitSecure has launched online and
mobile social wallet platform – HotRemit
for money transfer and payments service.
•
Citi downgrades IT sector; shares of Infy,
TechM, Mindtree tank.
•
Facebook’s Zuckerberg in India to focus
on driving Internet access.
•
Infibeam.com’s model, ‘live online stores’
- buildabazaar.com, has gathered over
30,000 live stores, enabling merchants
or brand owners to set up their own
e-retailing portals and offer discounts as
they deem fit for their business.
•
Microsoft
Ventures
is
accepting
applications for the next batch of its
Accelerator programme aimed at
technology start-ups.
•
With Drones and 3D visuals, real-estate
players innovate to attract buyers.
•
Flipkart to unveil world’s first dual-screen
phone today .
•
Philips unveils handset, with large font
size keypad, a torch-cum-SOS button and
long lasting battery life targeting senior
citizens.
•
Google’s Inbox promises to act as your
personal secretary.
•
Zensar Tech sets up the first National
Digital Literacy Mission (NDLM) Centre
in Pune.
•
Dell offers cloud-based solution targeting
mid-size hospital chains.
n
www.csi-india.org
On the Shelf!
Peeyush Chomal
Sr. Technical Officer, C-DAC, Mumbai
Book Review »
Book Title
:
C++ and Object-Oriented Programming Paradigm, 3rd edition
Author
:
Dr. Debasish Jana
ISBN
:
978-81-203-5033-5
No. of Pages
:
551
Price
:
Rs. 495/-
Publisher
:
Prentice Hall India
About the Author
First I must congratulate Dr. Debasish Jana for successfully
bringing out 3rd edition of his book C++ and Object-Oriented
Programming
Paradigm,
which
reflects
upon
acceptance of his
textbook as a fine
academic material
amongst students,
professionals and
casual
readers’
community. I have
grown up reading
books
in
C++
dominated largely
by foreign authors
such as Stroustoup,
Lippman
with
few contributions
in that area by
Indian
Authors.
It
is
definitely
pleasant to see a quality material coming from one more author
with Indian origin who has painstakingly addressed almost each
aspect of C++ and OO paradigm together in roughly 500 pages.
In other words, the book is not voluminous which otherwise tends
to discourage students/casual readers in carrying a bulky load of
material to read through but at the same time is addressing all the
critical mass within the paradigm and C++ as a tool for attaining it.
What has further impressed me is that Dr. Jana has tried to
introduce all the relevant concepts surrounding a particular topic
while discussing it in his book. For example, most books limit their
talk to static
binding
and
dynamic binding
whereas Dr Jana
has introduced
his readers to
even
concept
of static typing
and dynamic typing and presented the matrix showcasing which
language/tool provides for all four in his very first chapter. But he
has done this without digressing too much into the nitty-gritties
which otherwise would tend to distract reader from main idea into
unnecessary detailing. He has basically given pointers to readers who
can at their will then decide to pursue the in-depth understanding
from alternative material subject to his/her interest in the area.
The book consists of 15 chapters with last two chapters
discussing on Object Oriented Design and Modelling, and
Unified Modelling Language. Each chapter is concluded with
questions challenging reader to assess his/her conceptual
understanding of the topic. The book also comprises of problems
(for laboratory workouts), glossary, bibliography and Index which
take up around 50 pages towards the end. I also appreciate him
for covering pre-processor directives, operator overloading and
advanced concepts in dedicated chapters of their own. He also
has placed emphasis on importance of program design through
chapters on Data abstraction through classes and user defined
data types, and Data Structures and Applications in C++. I have
found the textual material well-balanced and well-supported
with diagrams and numerous examples. I therefore recommend
this book to find place on your shelf, your collections and your
Institution’s library, if it has one.
n
Peeyush Chomal serves as Sr Technical Officer at C-DAC, Mumbai (Erstwhile NCST) in Research & Development
areas of Software Architectures, Middleware Computing and Sensor Technologies. Equipped with Postgraduation from
University of Madras, Graduation from University of Mumbai and MBA from JBIMS, he has 15 years of experience
spread across Turnkey Project deliveries for DeitY, IAEA, BARC, DGoV and NPCIL. In his free time, he enjoys fiddling
with open source tools, trying out new gadgets and messing with ROMs on Android/Window platform.
CSI Communications | November 2014 | 51
CSI Report
From CSI SIG and Divisions »
Please check detailed news at:
http://www.csi-india.org/web/guest/csic-reports
SPEAKER(S)
TOPIC AND GIST
Information Retrieval Society of India, IEEE Uttar Pradesh Section, IEEE Computer Society GLA University SB and CSI Region-1, Division-1 &
Mathura Chapter, Department of Computer Engineering & Applications, GLA University, Mathura, India
Prof. DS Chauhan, Prof. Naresh Chauhan, Dr. Sujoy Das, 27 September 2014: One day National Workshop on “Emerging Trends in
Prof. MM Sufyan Beg, Prof. Krishna Kant, Prof. Anand Singh Information Retrieval (ETIR – 2014)”
Jalal, Prof. Charul Bhatnagar, Dr. Dilip Kumar Sharma
L-R: Dr. Dilip Kr Sharma, Prof. Krishna Kant, Prof. DS Chauhan,
Dr. Sujoy Das, Prof. Naresh Chauhan & Prof. AS Jalal
CSI Communications | November 2014 | 52
Dr. Dilip introduced workshop theme & focused on need of Information Retrieval
in day to day life. He discussed about how other Computer Science domains
are contributing to Information Retrieval (IR) research area. Emerging trends of
Information Retrieval include cross linguistic IR systems, recommender systems,
social network analysis & temporal Information Retrieval. He explained how
music IR system can play song(s) based on our mood. Dr. Sujoy discussed basic
concepts of IR, IR models & evolution and explained how to search faster. He
gave emphasis on how to index data, phases of indexing & its applications while
assigning tokens. Prof Beg unveiled concept of Precisiating natural language for
question answer system. He explained how natural language processes English
language as well as functioning of computer system to understand English
language through Stenford POS tagger. Dr. Sujoy Das along with Ms. Aarti
Kumar, Ms. Anubha Jain, Avinash Samuel & Mohd. Amir Khan gave hands on
experience on Terrier IR tool to participants.
www.csi-india.org
A.V. Ramachandra Rao Memorial Award for Best Papers in Hardware Area
We are pleased to announce a new award - A.V. Ramachandra Rao Memorial Award for Best Papers in Hardware Area, named after
the late husband of one of our Fellows, Dr Swarnalatha Rao.
Two cash awards of Rs. 10,000/= and Rs. 5,000/= each will be presented to the Best Papers presented in the area of Hardware in the
conferences organized by the CSI Units – Chapters, Divisions, Regions during the year and ranked First & Second.
These awards will be presented for the first time in the Annual Convention CSI-2015 to be held at New Delhi in 2015.
The Programme Committee chairs of conferences being held from Apr 2014 till Mar 2015 are requested to nominate and forward
three shortlisted papers in the area of Hardware to awards@csi-india.org for review and final selection. For more details on the award,
pl. visit www.csi-india.org
Brief profile of
Late Shri. A. V. Ramachandra Rao
(1-2-1934 to 2-5-2014)
Late Shri. A. V. Ramachandra Rao was an eminent technologist and entrepreneur in electronic devices and equipment. Over a period
of two decades, in the 1960’s and 1970’s, in the formative years of Bharat Electronics Ltd (BEL), he lead teams in the development
and manufacturing of X-Ray tubes and systems, electronic tubes of various kinds for civilian and military communication and radar
applications, black and white CRTs for use in medical diagnostic systems and in televisions etc. He had aslo contributed to the
development of germanium semiconductor devices.
On leaving BEL, Shri Ramachandra Rao became an entrepreneur, and concentrated in developing and manufacturing components and
subsystems for import substitution in important electronic equipment, such as deflection components in TVs, pulse transformers
especially for high end power electronic equipment etc.
Shri Ramachandra Rao on invitation by the West Bengal Electronics Corporation, involved in the setting up their TV Picture Tube
manufacturing plant – Webel Video Devices in late 1970’s and served as its Managing Director.
He had also set up successful companies in Chennai and Bangalore, concentrating on import substitutions in areas which were
important at that time, thus enabling the country to save precious foreign exchange.
Shri. Ramachandra Rao was a keen follower of technological developments taking place across the world. He admired the culture
and achievements of western societies. He was deeply interested in education and training of the younger generation in India to do
innovative contributions at the level of the advanced industrialized countries.
CSI Communications | November 2014 | 53
DETAILS OF CSI GRANTS AVAILABLE FOR CHAPTERS/STUDENT
BRANCHES/MEMBERS
(Presented by Mr. Ranga Rajagopal. Hon. Treasurer – CSI)
CSI has made available several new categories of grants for the benefit of members during the last few years. Following are the
categories of grants available to CSI chapters, student branches and members (as applicable). Members/chapters are requested
to avail the grants provided for the fiscal year before 31st March 2015. Members may share any feedback/suggestions in this
regard with treasurer@csi-india.org.
- Tech Bridge - Grant of 5k per event of the chapter (upto 2 events per year) to be availed before 31st March 2015.
Refer http://www.csi-india.org/grant-to-csi-chapters for details
Total Grant budget for 2014-15 Rs. 5.0 Lacs
- Golden Jubilee Chapter Grant (50k for Cat A, 25K for Cat B and 15K for Cat C) - a one
time grant to chapters for a Golden Jubilee event to be conducted before March 31st 2015 to enable all chapter members/Past OBs/
Patrons/Fellows to participate. Refer http://www.csi-india.org/grant-to-csi-chapters for details
Total Grant budget for 2014-15 Rs. 10. Lacs
- Divisional Grant - 25 K available for any chapter level technical event conducted in association with any Division. Event should be
planned and announced well in advance. Refer http://www.csi-india.org/divisions for details
Total Grant budget for 2014-15 Rs. 5.0 Lacs
- Tech Bridge (for Student chapters) - 5k for 1 event during the year for the 100
proposals received during the year 2014-15.
Refer http://www.csi-india.org/web/education-directorate/grant-to-student-branch
Total Grant budget for 2014-15 Rs. 5.0 Lacs
- Travel grant for Research scholars/students for participation in International Conferences upto Rs. 25K. (Available for first 12
proposals received during the year).
Refer http://www.csi-india.org/c/document_library/get_file?uuid=944dd521-20c9-4541-aaf5-a2a6de694be0&groupId=10157
Total Grant budget available for 2014-15 Rs. 3.0 Lacs
- Student Convention grant for Student Branches (25k for State Student convention, 35k for Regional Student Convention and 70k
for National Student Convention). Claim format available with Education Directorate. Convention proposal to be submitted to ED/
NSC for approval as per guidelines in advance
Total Grant budget for 2014-15 Rs. 6.0 Lacs
-Support grant to chapters for conducting Chapter level/Regional level/National level rounds of Discover Thinking School Quiz,
Discover Thinking Project Contest. Alan Turing Programming Contest, Discover Thinking Online Quiz for Student members. Refer
notification in CSIC or contact csiprograms@csi-india.org
Total Grant budget for 2014-15 Rs. 5.0 Lacs
CSI Communications | November 2014 | 54
www.csi-india.org
Application for Travel Grants for Researchers
Research Committee of Computer Society of India has decided to partly fund CSI Life Members to the extent of Rs. 25000/ for
travelling abroad to present research papers at conferences.
CSI Life Members who have been invited to present papers abroad and have received partial or no funding are eligible to apply for the
same. They have to apply within December 31, 2014 to div5@csi-india.org and furnish:
1.
2.
3.
4.
5.
6.
7.
8.
9.
Name of the Applicant, Organization Details and Bio Data of Applicant
CSI Life Membership Number
Name of the International Conference with details of the organizers
Conference Venue and Date
Copy of the Research Paper
Copy of the Invitation Letter received from the organizers
Details of funding received from/applied to for funding to any other agency
Justification for requesting support (in 100 words).
Two References (including one from head of the organization)
Dr Anirban Basu
Chairman,
CSI Division V (Education and Research)
CSI Communications | November 2014 | 55
CSI News
From CSI Chapters »
Please check detailed news at:
http://www.csi-india.org/web/guest/csic-chapters-sbs-news
SPEAKER(S)
TOPIC AND GIST
DELHI (REGION I)
Dr. Roop N Bharadwaj, VK Gupta, Dr. AK Bansal
and SD Sharma
13 September 2014: Technical talk on “Innovation Means of IT &
Telecommunication of Education”
Mr. Sharma explained how new ideas and innovations in IT are impacting our
day to day life. Dr. Bhardwaj covered the topic on e-learning - education with
innovative means, how it was 30 years before with limited technical support
and how it is as on date with latest technologies. He spoke about how IT is
playing useful role in imparting education to masses living in remote areas.
Speaker and participants during technical talk
HARIDWAR (REGION I)
Dr. Satish K. Peddoju, Lt.Col. (Rtd.) PK Jain,
Prof. VK Sharma, Dr. Mayank Aggrawal and
Dr. Mahendra Singh Aswal
11 October 2014: Expert Session on “Cloud Computing”
Dr. Satish delivered lecture on very current and popular issue of “Cloud
Computing”. He covered all aspects of cloud computing including
Introduction, tools knowledge, practical view of cloud, simulators required
for research and how it works. The session was full of information for all
students, researchers, teachers etc.
Faculty members and participants
CHENNAI (REGION VII)
HR Mohan, Judges-Prof. P Thrimurthy, S Ramanathan
and Bhaskaran assisted by Prof. P Kumar and
Bhuvaneswaran
9 & 12 October 2014: SEARCC – International Schools’ Software Competition
(ISSC) 2014
Participating team had 3 students each. 2 teams from India, 2 from
Sri Lanka, 1 from ROC Taiwan and 1 from Papua New Guinea participated.
Trial competition was held on 11th Oct 2014 and all teams participated in
it for getting experience. Software displaying minute to minute position
was very handy. Result: First- ROC Taiwan, Second-India (Team-B) and
Third- Sri Lanka (Team-A). Mr. Mohan gave away prizes and addressed
the gathering. SEARCC Rolling Trophy was given away to the Taiwan team.
Prize winners with CSI President HR Mohan, Dr. Thangam Meganathan and
other dignitaries of CSI
TRIVANDRUM (REGION VII)
Mr. Vinod Purushothaman
6 August 2014: Technical talk on “Connecting with Agile Principles and
Practices”
CSI Trivandrum Chapter organized a technical talk on ‘Connecting with
Agile Principles and Practices’ by Mr. Vinod Purushothaman, Technical
Architect, Envestnet Inc. (NYSE: ENV) at Institution of Engineers Hall,
Thiruvananthapuram.
Mr. Vinod Purushothman delivering the lecture
CSI Communications | November 2014 | 56
www.csi-india.org
TRIVANDRUM (REGION VII)
24 September 2014: Technical talk on the topic “Time
Management Using A Tomato”
Mr. Ramnath Jayakumar
CSI Trivandrum Chapter organized a Technical talk on the
topic ‘Time Management Using A Tomato’ by Mr. Ramnath
Jayakumar, Lead Engineer, Envestnet Inc. (NYSE: ENV),
Thiruvananthapuram at The Institution of Engineers Hall,
Thiruvananthapuram.
Mr. Ramnath Jayakumar delivering the lecture
From Student Branches »
(REGION-V)
CMR TECHNICAL CAMPUS, HYDERABAD
16th Oct 14: Mr. Somagiri delivered a lecture on “Big Data Analytics"
(REGION-V)
(REGION-V)
ANURAG GROUP OF INSTITUTIONS, HYDERABAD
9th Oct, 2014 : Conducted an one day “TECHNICAL QUIZ CONTEST”
to bring out the talent of the students in Computer programming skills
and winners with certificates awarded by the Principal
(REGION-V)
SREE VIDYANIKETHAN INSTITUTE OF MANAGEMENT, TIRUPATI
LAKIREDDY BALI REDDY COLLEGE OF ENGINEERING, MYLAVARAM
14th Oct, 2014: New student branch was inaugurated by Consultant
Mr. S. Ramasamy and Mr. Y. Kathiresan, Dr. Mohan, Dean, Mr. Prabhakar,
Guest speaker are during the inauguration
20th and 21st of Sep, 2014: Two day workshop on “ASP.NET MVC4.0”
was conducted by Mr. V. Phani Sekhar, Senior Software Engineering from
HPS, Bangalore
(REGION-V)
(REGION-V)
KLE DR M S SHESHGIRI COLLEGE OF ENGINEERING AND TECHNOLOGY,
BELGAUM
SWARNANDHRA INSTITUTE OF ENGINEERING AND TECHNOLOGY (SIET),
NARASAPUR
27th Aug, 2014: Mr. Prasad Inchal, Senior Consultant, HP, Bangalore
inaugurated the CSI activities for the year 2014-15
15th Sep, 2014: Activities for 2014-15 inaugurated Prof, J V R Murthy,
JNTUK – Kakinada. Prof. Rajesh C Jampala, Chairman - CSI Vijayawada
chapter and Principal, Dr. T Madhu with the Student branch Plaque
CSI Communications | November 2014 | 57
(REGION-VI)
(REGION-VII)
P.E.S COLLEGE OF ENGINEERING, AURANGABAD
DE PAUL INSTITUTE OF SCIENCE AND TECHNOLOGY, ANGAMALY
12th Oct, 2014: Orphan children and Students of the college along with
Prof. V.A.Losarwar, HOD & Prof. A.U.Jadhav
7th Oct, 2014: Workshop on Ethical Hacking and Web Application
Security by Mr. Manu Zacharia, Information Security Evangelist
(REGION-VII)
(REGION-VII)
SRINIVASA RAMANUJAN CENTRE, SASTRA UNIVERSITY, KUMBAKONAM
SENGAMALA THAYAR EDUCATIONAL TRUST STUDENT BRANCH
9th Oct 14: Event INNOVATE-AD based on advertisement for enriching
student’s creativity and innovative ideas organized wherein 26 teams
from various streams of Engineering, Arts and Science participated.
26th Sep, 2014: National Seminar on Cloud computing was conducted.
Correspondent , Principal, Tamilnadu State student Coordinator
Dr. Srinath and Mr. S. Ramasamy, Consultant are on the dais
(REGION-VII)
(REGION-VII)
JYOTHI ENGINEERING COLLEGE, THRISSUR
MCA DEPARTMENT OF COMPUTING SCIENCE, VELS UNIVERSITY, CHENNAI
22nd Sep, 2014: Computer Awareness Programme for plus students was
conducted by CSI Student Volunteers Mr. Gijo Vargese, Mr. Joe Mathew
and Mr. Sanjo Simon under the guidance of Mr. Viju Shankar, SBC
1st Oct, 2014: Mr. Rajan T.Joseph Director-Education, CSI was the Chief
Guest and delivered the Inaugural address in the National level Technical
symposium CIPHERMIX 2014
(REGION-VII)
(REGION-VII)
JEPPIAAR ENGINEERING COLLEGE , CHENNAI
ST. PETER’S UNIVERSITY, CHENNAI
25th & 26th Sep, 14: Workshop On NS2 Simulations by Mr. Pradeep Kumar Inauguration of New student branch by Mr. Rajan Joseph, Director
along with Principal Dr. Sushil Lal Das , Director Mrs. M. Regeena Jeppiaar, Education with Vice Chancellor
CSE HOD Dr. V. L. Jyothi, IT HOD Dr. R. Sabeetha
Please send your student branch news to Education Director at director.edu@csi-india.org. News sent to any other email id will not be considered.
Low-resolution photos and news without gist will not be published. Please send only 1 photo per event, not more.
CSI Communications | November 2014 | 58
www.csi-india.org
CSI Calendar
2014
Date
Prof. Bipin V Mehta
Vice President, CSI & Chairman, Conf. Committee
Email: bvmehta@aesics.ac.in
Event Details & Organizers
Contact Information
November 2014 events
14–16 Nov 2014
International Conference on Emerging Computing Technologies-2014
(ICECT-2014) Organized by Dept. of Computer Science and Applications, M.
D. University, Rohtak in association with CSI Region – I and CS Division – I.
Prof. R S Chhillar
chhillar02@gmail.com
14–16 Nov 2014
International Conference on Information and Communication Technology
for Competitive strategies (ICTCS-2014) Organized by: Computer Society of
India, Udaipur Chapter, Division IV, I, SIG-WNs, Hosted by: Sunrise Group of
Institutions, Udaipur. http://www.csi-udaipur.org/ictcs-2014
Prof. Amit Joshi
Organizing Secretary
amitjoshiudr@gmail.com
28-30 Nov 2014
International Conference on Advance in Computing Communication and
Informatics at COER School of Management, Roorkee , Uttrakhand
http://coer.ac.in/ICACCI2014/index.html
Dr. Vishal Singhal, Convener
fdpcoersm@coer.ac.in
December 2014 events
10-11 Dec 2014
49th Annual Student Convention, Organized by Computer Society of India,
Hyderabad Chapter In association with GNIT, Hyderabad. Theme: “ Campus to
Corporate” Venue: GNIT, Ibrahimpatnam, Rangareddy District Telangana.
http://www.csihyderabad.org/csi-2014
Dr. DD Sarma,
Shri Raju Kanchibhotla
Shri Chandra Sekhar Dasaka.
http://www.csihyderabad.
org/csi-2014
12-14 Dec 2014
49th Annual Convention ,Organized by Computer Society of India,
Hyderabad Chapter In association with JNTU-Hyderabad & DRDO. Theme:
Emerging ICT for Bridging Future Venue: JNTUH, Kukatpally, Hyderabad
http://www.csihyderabad.org/csi-2014
Sri. J A Chowdary
Sri. GautamMahapatra
csi2014@csihyderabad.org
12-14 Dec 2014
Special session on “Cyber Security and Digital Forensics” during Computer Society
of India Annual Convention - 2014 by CSI Special Interest Group on Cyber Forensics,
JNTU Hyderabad
Dr. Vipin Tyagi
dr.vipin.tyagi@gmail.com
16-20 Dec 2014
ICISS-2014: International Conference on Information Systems Security. At
Institute for Development & Research in Banking Technology (IDRBT), Hyderabad,
India. Co-sponsored by CSI Division IV and CSI SIG-IS.
http://www.idrbt.ac.in/ICISS_2014/
iciss2014@idrbt.ac.in
19-21 Dec 2014
EAIT-2014: Fourth International Conference on Emerging Applications of
Information Technology at Kolkata. Organized by CSI Kolkata at Indian Statistical
Institute, Kolkata https://sites.google.com/site/csieait/ For paper ssubmission :
https://cmt.research.microsoft.com/EAIT2014
Prof. Aditya Bagchi
Dr. Debasish Jana
Prof. Pinakpani Pal
Prof. R T Goswami
csieait@gmail.com
22-24 Dec 2014
ICHPCA-2014: International Conference on High Performance Computing and
Applications Organized by: CV Raman College of Engg. in association with CSI
Div-V and IEEE Kolkata Section http://www.ichpca-2014.in/
Prof. (Dr.) Rachita Misra
ichpca2014@gmail.com
9th INDIACom; 2015 2nd International Conference on “Computing for Sustainable
Global Development” Organized by Bharati Vidyapeeth’s Institute of Computer
Applications and Management (BVICAM), New Delhi
Prof. MN Hoda
conference@bvicam.ac.in,
indiacom2015@gmail.com
March 2015
11–13 Mar 2015
CSI Communications | November 2014 | 59
Registered with Registrar of News Papers for India - RNI 31668/78
Regd. No. MH/MR/N/222/MBI/12-14
Posting Date: 10 & 11 every month. Posted at Patrika Channel Mumbai-I
Date of Publication: 10 & 11 every month
If undelivered return to :
Samruddhi Venture Park, Unit No.3,
4th floor, MIDC, Andheri (E). Mumbai-400 093
CSI-2014
Annual Convention and
International Conference on Emerging ICT for Bridging Future
Hosted by: CSI Hyderabad Chapter
In Association with JNTU Hyderabad & DRDO
Dates: 12th- 14th December 2014, Venue: JNTU Hyderabad
www.csihyderabad.org/csi-2014, www.csi-2014.org
Call for Sponsors/ Participation
Introduction: CSI-2014, the 49th Annual Convention of Computer Society of India (CSI) is being organized as a part of CSI@50, the Golden
Jubilee celebrations of CSI by CSI Hyderabad Chapter, in association with Jawaharlal Nehru Technological University, Hyderabad and DRDO.
The Golden Jubilee Celebration along with International Conference will be held at JNTU Hyderabad on 12th ,13th and 14th December 2014. The
theme of the convention is “Emerging ICT for Bridging Future”. The objective of this convention is to bring together researchers, engineers,
developers, practitioners, IT professionals from academia, industry, government establishments, SME, Public Sectors and multi-national
companies and share their experience, exchange ideas and update their knowledge on the latest developments in emerging areas. As part
of this convention Knowledge sharing sessions on e-governance have been organized where the implementers, policy makers, users and
developers from various agencies will be deliberating regarding successful implementation of E-Governance for achieving the vision of Digital
India. In this convention many IT luminaries, famous personalities from industries, Govt and Public sectors are participating and deliberating
from various aspects of ICT’s for IT enabling of India. Number of Keynote sessions, CIO’s panel discussions is also part of this convention. Large
scale exhibition from various IT firms is one of the main attractions. We have already received more than 160 high quality research papers on
all aspects of the ICT’s and same will be presented in this convention in various parallel tracks.
National Student convention is also being organized at Gurunanak Group of Institutions, Ibrahimpatnam, Hyderabad to make the student
community glide through “Campus to Corporate and Beyond” on 10th and 11th December 2014.
Invitation: Govt, Public sectors, Educational Institutes, Software firms, industries and business houses are invited to participate in the
convention and present and exhibit their products and services. Online registrations facilities are provided in the website: www.csi-2014.org.
We also invites proposals for workshops, pre-conference tutorials and doctoral consortium.
Registration fee and Sponsorship plan is given below:
Souvenir
Registrations
Delegate Type
CSI Ins(Rs)
Others(Rs)
Regular
3000
4000
150
Paper Presenter
Springer
5000
6000
250
Student For Stu.
Convention
400
500
25
Amount (Rs)
Full Page
50000
Half Page
25000
Qtr. Page
15000
Exhibition Stall 9x6ft:Rs 30000
Sponsorship Plans
Facilities Given
Amount
(Rs)
Registrations
Exhibition Stall
Ad Pages
Crown
700000
10
2
2
Platinum
500000
5
2
1
Diamond
300000
3
1
1
Gold
200000
2
1
1
Silver
100000
1
Shared
Half Page
Bronze
50000
1
None
Half Page
Plan
Page
Overseas($)
Delegates will be provided accommodation on first come
first serve basis.Transport to venue will be provided by the
convention team.
*12.36% service tax extra.
Address for Communication:
CSI-Hyderabad Chapter,
#302,Archana Aracde,10-3-190,
Opp: Railway Reservation Complex,
Secunderabad,Telangana-500025
Email:csi2014@csihyderabad.org
contact@csihyderabad.org
Payments to be made by DD/Cheque drawn in favour of:
“CSI Annual Convention” Payable at MUMBAI or by RTGS/NEFT at A/c no: 34242332507
IFSC Code: SBIN0007074, Service Tax Registration No: AAATC1710FSD001
Sri. J A Chowdary
Dr. A Govardhan, JNTU Hyderabad
Organizing Committee
Programme Committee
Sri. Gautam Mahapatra, RCI, DRDO
Finance Committee