Computer Systems Lab TJHSST Philosophy • Creativity • Opensource accessibility to knowledge, information and resources • Research and development • Writing and documentation of your research 2 Project Opportunities in CS • Artificial intelligence and machine learning • Opensource software development • Game simulation and design • Web development • Database design • Security and Cryptography • Operating system, language design • Networking and ISP 3 Computer Science Applications • • • • • • • Computer graphics and vision Artificial intelligence, robotics Distributed and Multiagent systems Software engineering Computer languages and compilers Operating systems and networking Database design 4 TJ Techlabs • Astronomy – Co-req: Astronomy - The Universe or Solar System • Automation and Robotics – Recom: Princ. of Robotics I, II, Analog/Digital Elec., Pre-engineering, Prototype Dev. • Chemical Analysis – Pre-req: AP Chemistry • Computer Assisted Design – Pre-req: CAD, Recom: Arch. Drawing, Engineering Drawing, Pre-engineering 5 TJ Techlabs • Computer Systems – Pre-req: AP Computer Science – Recom: Intro. to AI, Comp. Arch, Supercomputer Apps • Energy Systems – Recom: Pre-engineering, Analog Elec., Nature of Materials, CAD • Biotechnology – Pre-req: Bio elective, Bio-tech elective, or Chem. elective, Recom: DNA Science 1 • Microelectronics – Recom: Analog, Digital, or Audio Electronics, or Microprocessor Design 6 TJ Techlabs • Oceanography and Geophysics – Recom: Marine Biology • Optics and Modern Physics – Recom: Advanced Optics Apps or Quantum Mechanics and Dev. in Modern Physics • Prototyping and Engineering Materials – Recom: Prototype Dev. and Processing or Nature of Materials • Video Technology – Pre-req: Videotech and Communications – Recom: Analog Electronics, Audio Electronics, or 7 Photography TJ Techlabs - Portfolio Skills We Stress • • • • • • • • Writing – Technical Research Paper Visual presentation – Digital poster Oral presentation – PPT slides of the research Research Long term project development – iterative models Working individually and in teams Record keeping Peer evaluation 8 Electives – Computer Systems Lab • Artificial Intelligence • High Performance Computing and Supercomputer Applications • Computer Architecture • Comparative Languages 9 Computer Science at TJHSST http://www.tjhsst.edu/compsci • Full four-year sequence in Computer Science. • The Computer Science Team is part of the Math/CS Division and the Computer Systems Lab is part of the Science and Technology Division. • Our collective goal is to provide a world class Computer Science education to our students and to disseminate curriculum materials to other academic institutions. 10 Computer Science at TJHSST http://www.tjhsst.edu/compsci • Introduction to Computer Science – A mandatory course for all TJ students, the intro. course assumes no prior programming experience. Students study object-oriented programming and develop fundamental programming skill. In preparation for the AP course, Java is the language of instruction. 11 Computer Science at TJHSST http://www.tjhsst.edu/compsci • AP Computer Science – An elective course available to all students who have completed Introduction to Computer Science, APCS follows the College Board topic outline. This course carries an additional 0.5 quality point in GPA calculation and pepares students to take the APCS Exam given each May. 12 Computer Science at TJHSST http://www.tjhsst.edu/compsci • Accelerated Computer Science – A non-traditional route designed for experienced programmers only, this course requires exceptional problem solving skills (by TJ standards). 13 Computer Science at TJHSST http://www.tjhsst.edu/compsci • Summer School – How better to spend five weeks of summer than learning Computer Science with 140 of your closest TJ friends. A great way to fit more into your cramped schedule, the summer school program thrives because of students aides (upperclassmen, apply early). An accelerated class is usually formed during the second week. Not only is there an ice cream social and a pizza party, but you may even get to work with teachers from outside TJ. 14 Computer Science at TJHSST http://www.tjhsst.edu/compsci • Artifical Intelligence – A half-credit semester course requiring APCS as a prerequisite, students program in Python in a Linux environment. This class carries the same extra grade point value as an AP course. • Computer Architecture – A half-credit semester course requiring APCS as a prerequisite, students program in C in a Linux environment. This class carries the same extra grade point value as an AP course. 15 Computer Science at TJHSST http://www.tjhsst.edu/compsci • Supercomputer Applications – A half-credit semester course with a suggested APCS prerequisite, students program in C and Fortran in multiple UNIX environments. This class will get you an account on our Cray SV1 supercomputer. • Comparative Languages – A half-credit semester course with a suggested APCS prerequisite, students program in Python, LISP, C++, Prolog, Smalltalk, ML and other exotic tongues in a Linux environment. Veni, vidi, vici. 16 Computer Science at TJHSST http://www.tjhsst.edu/compsci • Senior Tech Lab – One credit in Technology Independent Research, such as this course in Computer Systems Research, is required for graduation from TJ. 17 Artificial Intelligence • Search techniques for problem solving – Uninformed: depth first, breadth first – Heuristic: hill climbing, best first, A Star • Game playing and adversarial search – Minimax trees – Alpha-beta pruning • Machine Learning – Evolutionary computation, genetic algorithms 18 Supercomputer and High Performance Computing • Parallel Computing – Speedup of processing: Time/# of processors – Sorts, searches, image processing across matrices, fractal images • MPI – Message Passing Interface – Message sending topologies, ring/broadcast – Time vs number of processors • Computer Graphics in OpenGL – 3D transformations, lighting for realism 19 Computer Architecture • Organization of Computer Systems • High level language implementations down to the digital logic level • SPIM simulator for assembly language • History of the development of computing machines – Evaluate current platforms – Analyze future forecasts 20 Comparative Languages • Evolution of programming languages • Syntax and semantics representation • Machine parsing of grammars, building a compiler • Some issues: Exception handling, Concurrency, Garbage collection • Language approaches: imperative, object oriented, functional, logic based 21 Comparative Languages • Scheme – functional programming language and a dialect of Lisp. It was developed in the 1970s, MIT. Lisp, 1958, is the second-oldest high-level programming language in widespread use today; only Fortran is older. • Smalltalk – object oriented programming language designed at Xerox PARC (Xerox Palo Alto Research Center) by Alan Kay and others during the 1970s...great influence on the development of many other computer languages 22 Comparative Languages • Prolog – Programmation en logique (French for "logic programming"), created by Alain Colmerauer around 1972 to make a programming language enabling the expression of logic instead of specified instructions on the computer. • ML – functional programming language developed by Robin Milner and others in the late 1970s at Edinburgh University. CMU 23 Comparative Languages • C programming language – low-level standardized programming language developed in the early 1970s by Ken Thompson and Dennis Ritchie for use on the UNIX operating system. • Fortran – compiled, programming language originally developed in the 1950s and still heavily used for scientific computing and numerical computation half a century later. 24 Comparative Languages • Python – interpreted, interactive programming language created by Guido van Rossum in 1990. Used in our AI course. • Ruby – object-oriented language, combines syntax inspired by Ada and Perl with Smalltalk-like features, also shares some features with Python, Lisp. Ruby's an interpreted language created by Yukihiro "Matz" Matsumoto, began working on Ruby on February 24, 1993 and released to the 25 public in 1995. GMU Collaborations • CS 635 Foundations of Parallel Computing – Fall 2004, Dr. Pearl Wang • CS 363 Comparative Programming Languages – Spring 2005, Dr. Elizabeth White • CS 499 Autonomous Robotics – Spring 2005, Dr. Sean Luke • MASON Multiagent Simulation Toolkit – Evolutionary Computation, Dr. Sean Luke 26 GMU Collaborations • Center for Social Complexity – Dr. Claudio Cioffi-Revilla – CSS 600 Introduction to Computational Social Science – CSS 610 Computational Analysis of Social Complexity – CSS 640 Human and Social Evolutionary Complexity – CSS 643 Land-Use Modeling Techniques and Applications 27 GMU Collaborations • Center for Social Complexity – – – – – Dr. Claudio Cioffi-Revilla, Dr. Ann Palkovich CSS 600 Introduction to Computational Social Science CSS 610 Computational Analysis of Social Complexity CSS 640 Human and Social Evolutionary Complexity CSS 643 Land-Use Modeling Techniques and Applications – CSS 645 Spatial Agent-based Models of HumanEnvironment Interactions – CSS 650 Physics Methods for Analyzing Social Complexity – CSS 660 Computational Social Science of Spacefaring Civilization 28 Computer Systems Research Goals for Students • Pursue an individual or group research project in computer science • Write a formal research paper in support of the project • Develop presentation skills in support of the project • Maintain records of individual effort and progress 29 Computer Systems Research Lab Requirements • • • • • • Project proposal Formal research paper Oral presenations Poster display Project website/notebook folder Logs 30 Computer Systems Research 1st Quarter • Gather preliminary background materials, references • Develop formal project proposal – Feasability of subject matter, scope – Algorithms, language(s), software tools – Open ended, what can be accomplished this year • Begin writing programs experimenting with algorithms 31 • Oral report on your proposal Computer Systems Research 2nd Quarter • Expanding upon research, reference materials • Expand program in support of research goals • Develop digital poster display • Research paper preliminary: Title, Abstract, Introduction/Background • Oral presentation on your poster 32 Computer Systems Research 3rd Quarter • Begin finalizing computer programs, models • Summarization of data collected, tests, results • Draft of your research paper – Title, Abstract, Introduction, Background – Development sections, what you've actually done – Preliminary results, conclusions 33 Computer Systems Research 4th Quarter • Final version of your research paper – LaTeX, PDF, PS, HTML • Final version of your digital poster • Visuals – graphs, charts, screenshots • Oral presentation of project 34 Computer Systems Research Resources • Research Resources – Research examples from universities – Computer Science research areas – Writing a research paper • Mayfield Publications – LaTeX, PDF – Writing a proposal – Intel and Westinghouse example projects – Gantt charts/Time lines 35 Computer Systems Research Iterative Development Model • Periodic Iteration Progress reports – See extremeprogramming.org • • • • • • Plan, design, goal of this iteration Pseudo code versions, sketches Commented code Testing, validation of this iteration's code What to change, develop for next iteration Any users for feedback? 36 Computer Systems Research Peer/Faculty Review • Peer assessments of research progress, poster and paper feedback • Appropriate title, abstract? • Introduction, does it lead the reader into the body of the paper, define the research being presented, provide background? • Research theory, code content, testing and validation – how clearly are the algorithms and theory stated, thorough testing, 37 analysis? Computer Systems Research Peer/Faculty Review • Student Posters and Papers 2005 – http://www.tjhsst.edu/~rlatimer/assignments200 4/posters05.html – or see top of www.tjhsst.edu/~rlatimer 38 Computer Systems Research Research Writing Resources • Mayfield Handbook for Technical and Scientific Writing • Detailed online resource • Elements of Technical Documents • Front matter, Body, End matter 39 Intel Science Talent Search Sieman's Westinghouse Comp. • Review of Abstracts, Titles from recent years • Which are applicable to computer science? 40 Linux Resources and Software Tools – Opensource availability • Programming – C/C++, Java, Fortran, Python, Lisp – PHP, Perl, HTML for WWW – OpenGL – computer graphics • • • • • Image processing – Gimp 2D/3D analysis - Gnuplot Openoffice for ppt, publishing LaTex, PDF, PS for scientific writing “planner” - Gantt charts, “dia” - flow charts, network diagrams, UML – objects, electronic diagrams... 41 Computer Systems Lab Hardware • Linux workstations • Mosix Cluster (being constructed) • Cray SV1, 16 processors – C, Fortran, vector processing – Parallel programming, MPI, PVM 42 Computer Systems Lab Accessing from Home • WinSCP – Transfer files from Windows to the Lab • Putty.exe – work from home, connected from Windows/Macs to Linux here • “Compatable” software with Windows/Macs 43 Computer Systems Lab Project Areas 2004-05 • Algorithms – Variants of Red-Black Trees • Agent-based modeling of complex systems – A Study of Microevolution – Modeling of Evolutionary Systems – Modeling of Evacuation Centers – Traffic Modeling – Model of the Decomposition of the Atmosphere 44 Computer Systems Lab Project Areas 2004-05 • Modeling of Complex Systems (cont.) – – – – Saturnian Moon System Robot Swarms Sabermetrics: Statistical Modeling in Baseball A Bowling Ball in Action • Machine Learning, Evolutionary Computation – Machine Learning to Develop a Game Playing Strategy – Can a Robot Learn to Walk – Assessment of Sorting Parts by Variable Slot Width 45 Computer Systems Lab Project Areas 2004-05 • Natural Language Processing, Computational Linguistics – Part of Speech Tagging with Training Corpora • Example: “Hospitality NN is BEZ an AT excellent JJ virtue NN” • NN: singular common noun, BEZ: is, AT: article, JJ: general adjective – Computational Comparative Diachronic Historical Linguistics • Systems Programming, Development – Kernel Debugging API Library 46 Computer Systems Lab Project Areas 2004-05 • Computational Biology – Investigation of Implementations of DNA Sequence Pattern Matching Algorithms (BLAST) • Computer Architecture – Construction and Application of a Beowulf Cluster 47 Computer Systems Lab Project Areas 2004-05 • Computer Graphics – Polygon Mesh Rendering (03-04) – Creating a 3D Game with Textures and Lighting – Car Simulation and Modeling • Computer Music – Genetic Algorithm Music Composer • Software Development – Software Development Team 48 Computer Systems Lab Mentorship Opportunities • Naval Research Lab – Artificial Intelligence – Robotics Labs – Computer Vision, Image Processing • Virtual Technologies – Software Development • GMU – Center for Social Complexity – Agent based modeling 49 Computer Systems Lab Mentorship Opportunities • UUnet – Internet, Network programming – 7 layers of Internet protocol • GMU – Computer Science Department – Artificial Intelligence, Robotics Labs – Computer Vision, Image Processing • Walter Reed Army Intstitute • NIH – Biotech, image processing programming 50 Computer Systems Lab Mentorship Opportunities • Semi-Autonomous Control of a Segway Robotic Mobile Platform - NRL • The Effect of Sound Distortion on Hearing Perception - NRL • Development of a Web Interface for Accessing Chemical Information in Thor and Informix Databases – Walter Reed Army Institute • Development of a Data Measuring Application for Federates Used in Simulations – Virtual Technologies 51 Software Systems Development The primary purpose of our Computer Systems Research project is to investigate the feasibility and consequences of establishing a student workgroup based on a classical development lifecycle model. We modeled our project on the Waterfall Development Model, otherwise known as the Systems Development Lifecycle Model (SDLC). 52 Computational Models of Traffic The goal of my project is to make an accurate simulation of traffic in an multi-lane intersection world that will be easily mutable for work in studies on the effects of construction work and accidents on traffic flow. Traffic Simulations are used in a variety of ways. One of the most prominent and original uses was to use traffic simulations to evaluate alternate treatments. 53 Genetic Algorithms and Music Genetic algorithms use feedback resulting from evaluating data sets to optimize these data sets for the best performance as defined by the user. The main data processing is done in LISP. The creation of audio files is done using Csound. 54 Car Simulation This project will be used to simulate carrelated incidents from the real world. By working with this program, users will be able to benefit from responses to scenarios that may have hazardous consequences in real life. By showing real people the decisions of robots, human drivers will attempt to replicate the robots' acceptable actions. 55 Sorting Parts of Variable Width Problem Statement. To analyze the efficacy of sort parts by using slots and utilizing the variable angular velocities that result when parts of distinct physical dimensions move off of a relatively flat inclined surface. Purpose. The final goal is to assess the feasibility of quality control based on taking advantage of the different orientations at various time after release that are caused by deviations from the original product. 56 Robot Swarms My project is an agent based simulation, posing robots in a “game of life”, with each new generation of robot comes new genes using a random number selection process creating the mutations and evolutions that in real life we experience for DNA cross over and such. 57 Modeling Evolutionary Behavior The purpose of this project is to attempt to model evolutionary behavior in agents in an environment by introducing traits and characteristics that change with the different generations of agents. I hope to create an environment where certain agents will prosper and reproduce while others will have traits that negatively affect their performance. In the end, a single basic agent will evolve into numerous subspecies of the original agent and demonstrate evolutionary behavior. 58 Developing a Learning Agent The goal of this project was to create a learning agent for the game of bridge. I think my current agent, which knows the rules, plays legally, and finds some basic good plays, is a step in the right direction. This agent could and will be improved upon over the course of the year and will become smarter and learn faster throughout the year 59 Modeling a Bowling Ball The idea behind this project is to create a model of the dynamical bowling game system. By analyzing sets of physics equations and applying them to this system, a program can be created to calculate and output the path and other characteristics of a bowling ball's traversal across a bowling lane. This ouput is based on a set of initial conditions, including speed, angle, lane conditions, and starting rotation. 60 Optimization of a Traffic Signal The purpose of this project is to produce an intelligent transport system (ITS) that controls a traffic signal in order to achieve maximum traffic throughput at the intersection. To produce an accurate model of the traffic flow, it is necessary to have each car be an autonomous agent with its own driving behavior. A learning agent will be used to optimize a traffic signal for the traffic of the autonomous cars. 61 Modeling a Saturnian Moon This project hopes to add to our understanding of space systems by providing a comprehensive simulation of the Saturnian moon system. By doing this, this project attempts to expose what phenomena can't be explained with modern models and perhaps suggest theories to explain the unexplained. 62 Modeling Atmosperic Change My goal is to create a model of the atmosphere over time, predicting its strength given the increasing amount of pollution as well as the controversial but effective Montreal Protocol. Many projects are in place to save the ozone, and this model will assist in assessing the impact of anti-pollution movements and determine the longterm possible outcome given many parameters. This model features usercontrolled variables, allowing the user to manipulate the year, solar flux, and existence of anti-pollution projects. 63 An Investigation into Implementations of DNA Sequence Pattern Matching Algorithms There is an immense amount of genetic data generated by government efforts such as the human genome project and by organization efforts such as The Institute for Genomic Research (TIGR). there exist large amounts of unused processing power in schools and labs across the country. Harnessing some of this power is a useful problem not just for the specific application in Bioinformatics of DNA sequence pattern matching. 64 Modeling of Evacuation Centers Using NetLogo Modeling is a powerful tool that allows a programmer or social engineer to observe cause-andeffect relationships in occurences that a) happen too slowly or quickly to see, b) involve danger or safety concerns, c) occur on a scale too large or too small for study, d) is not a common occurrence. Using NetLogo, a multi-agent programmable modeling environment, the socio- and psychological factors affecting decision-making in these situations can be effectively simulated. 65 Construction and Application of a Pentium II Beowulf Cluster I plan to construct a super computing cluster of about 15-20 or more Pentium II computers with the OpenMosix kernel patch. Once constructed, the cluster could be configured to transparently aid workstations with computationally expensive jobs run in the lab. This project would not only increase the computing power of the lab, but it would also be an experiment in building a lowlevel, lowcost cluster with a stripped down version of Linux, useful to any facility with old computers they would otherwise deem outdated. 66 Study of Microevolution Using Agent-Based Modeling in C++ Agent Class class Organism { public: Organism(); Organism(int ident, int row2, int col2); Organism(Nucleotide* mDNA,Nucleotide* dDNA, int ident, bool malefemale, int row2, int col2); ~Organism(); void printGenome(); void meiosis(Nucleotide* gamete); Organism* reproduce(Organism* mate, int ident, int r, int c); int Interact(Organism* neighbors, int nlen); int GeneValue(bool parent, int chromnum, int gennum); 67 Creating a 3D Game With a Study of OpenGL Textures and Lighting Techniques To create a first person 3D game using OpenGL. The program consists of using models, textures, lighting, and polygons to create a 3D world in OpenGL. Various equations are used to calculate camera angles, movement, and physics. For example, to move the camera, “eye movements” are controlled by glLookAt, which takes an eye position with 3 points (x,y,z) and 2 vectors. One vectors is the up direction and the other is the forward direction. 68 Paintball Frenzy! Optimized Minimax Agent AI The purpose of this project is to create an innovative and enjoyable graphical game and program a minimax AI agent that performs optimally. 69 Using Machine Translation in a German – English Translator This project attempts to take the beginning steps towards the goal of creating a translator program that operates within the scope of translating between English and German. 70 A Study of Balanced Search Trees This project investigates four different balanced search trees for their advantages and disadvantages, thus ultimately their efficiency. Runtime and memory space management are two main aspects under the study. Statistical analysis is provided to distinguish subtle difference if there is any. A new balanced search tree is suggested and compared with the four balanced search trees. 71 Linux Kernel Debugging API The purpose of this project is to create an implementation of much of the kernel API that functions in user space, the normal environment that processes run in. The issue with testing kernel code is that the live kernel runs in kernel space, a separate area that deals with hardware interaction and management of all the other processes. Kernel space debuggers are unreliable and very limited in scope; a kernel failure can hardly dump useful error information because there's no operating system left to write that information to disk. 72 Machine Learning Techniques for Game Playing Machine learning allows the computer to create its own logical rules, and learn from its past experiences. Machine Learning allows an AI to increase its abilities over time, even without additional direct programmer input. My project hopes to develop a proficiency at Tic-Tac-Toe. My project hopes to create a new algorithm for a relatively simple game, Tic-Tac-Toe. Ideally, this algorithm will be modified according to its results to create better algorithms. 73 Part-of Speech Tagging with Corpora The aim of this project is to create and analyze various methods of part-ofspeech tagging. The corpora used are of extremely limited size thus offering less occasion to rely entirely upon tagging patterns gleamed from predigested data. Methods used to analyze the data and resolve tagging ambiguities include Hidden Markov Models and Bayesian Networks. Results are analyzed by comparing the system-tagged corpus with a professionally tagged one. 74 Benchmarking of Cryptographic Algorithms The author intends to validate theoretical numbers by constructing empirical sets of data on cryptographic algorithms. This data will then be used to give factual predictions on the security and efficiency of cryptography as it applies to modern day applications. 75 Resource Locking and Synchronization in the Linux Kernel The goal of the KDUAL project is to create a C library which implements the kernel Application Programming Interface (API) in user-space and performs automatic debugging. Sections of kernel code can then be compiled against this library and run as ordinary programs for convenient testing. This particular section of the project aims to implement the kernel's resource locking API with automatic detection of deadlock situations. Locking will be implemented in two parts-the core algorithms, with their ownAPI designed to be convenient for the developers, and simple glue code bridging that API to the kernel API. 76 Algorithms for Computational Comparative Historical Linguistics Over time, languages change by regular, systematic processes. It is possible, by looking at the state of a language now and in the past, to deduce the exact changes that occurred, and the order in which they occurred. These changes also split languages, therefore it is also possible to, by using modern languages as input, induce the probable structure of their parent language. My goal is to develop algorithms by which computers may efficiently analyze the historical structure of languages and language families. 77 Optimizing Genetic Algorithms for Cypher Decoding Over the past several years, genetic algorithms have come into wide use because of their ability to find good solutions to computing problems very quickly. They imitate nature by crossing over strings of information represented as chromosomes, with preference given to the more fit solutions produced. They hold great promise in the field of cryptology, where they may be used to quickly find good partial solutions, thus eliminating much of the intense manual labor that goes into identifying initial coding schemes. 78 Decision Trees for Career Guidance This research project will be an investigation into the design and implementation of various decision trees for career guidance. A decision tree takes into account some sort of situation outlined by a group of parameters and outputs a Boolean decision to the situation. This project will take into account many aspects associated with decision trees including database building, searching and sorting, and algorithms for accessing data. My project utilizes numerous decision trees in an effort to serve as a tool for career guidance for young adults. A user will fill out a form of specified fields that will then be analyzed by the group of decision trees until a field of study/occupation is given to the user as the outcome. This group of decision trees will be built through database building techniques. 79 Archival of Articles via RSS and Datamining Performed on Stored Articles RSS (Really Simple Syndication, encompassing Rich Site Summary and RDF Site Summary) is a web syndication protocol used by many blogs and news websites to distribute information it saves people having to visit several sites repeatedly to check for new content. At this point in time there are many RSS newsfeed aggregators available to the public, but none of them perform any sort of archival of information beyond the RSS metadata. The purpose of this project is to create an RSS aggregator that will archive the text of the actual articles linked to in the RSS feeds in some kind of linkable, searchable database, and, if all goes well, implement some sort of datamining capability as well. 80 An Analysis of Sabermetric Statistics in Baseball For years, baseball theorists have pondered the most basic question of baseball statistics: which statistic most accurately predicts which team will win a baseball game. With this information, baseball teams can rely on technological, statistical-based scouting organizations. The book, Moneyball addresses the advent of sabermetric statistics in the 1980s and 1990s and shows how radical baseball thinkers instituted a new era of baseball scouting and player analyzation. This project analyzes which baseball statistic is the single most important. It has been found that new formulas, such as OBP, OPS, and Runs Created correlate better with the number of runs a team scores than traditional statistics such as batting average. 81 A Comparison of AI Types of Various Strengths Many different methods of Artificial Intelligence in games exist in todays world, such as a min-max search or goaldirected reasoning. By using a game that is less complex than chess, the standard game for testing AI's, I intend to compare various AI methods and their strengths in the game of Othello. 82 Developing an AI Player for Guess Who My project is to create a computerized version of the game "Guess Who?" complete with an AI player. This involves two research areas: Game AI and Data Mining. Data mining is the analysis of data and the use of software techniques for finding patterns and regularities in sets of data. My AI's strategy algorithm will formulate questions that eliminate 50% of the suspects, which is the optimal percentage. 83 Techniques of Asymmetric File Encryption Encryption programs have been created to protect privacy during a transfer of files and to make sure that sensitive files will be protected. My project is to create an asymmetric file encryption program. This means that encrypted files will need a pass-key to open that will be different from the key used to encrypt. This program could be applied practically to protect files during transfers. 84 Computer Vision: Edge Detections Vertical diff., Roberts, Sobels 85 Computer Vision: Edge Detections Sobels – Red, Green, Blue 86 Computer Vision: Edge Detections Sobels – No Red/Green/Blue 87 Projects from previous years • Computer Simulation and Modeling, Computational Computer Science – Evolution of Darwin's Finches: Simulation using Genetic Algorithms • This project uses genetic algorithms to simulate the process of the evolutionary changes that gave rise to the varying species of the finches. Factors including theabundance of food, probability of mutation, and size of the initial results of this project demonstrate the drastically different evolutionary paths the finches could have followed depending on varying environmental conditions. Projects from previous years • Computer Algorithms – The Use of Polynomial-time Reducibility to Improve Approximations to NP-complete Problems • NP-complete problems are thought, though not proven, to be intractable. Because they are commonly encountered by programmers in situations where an exponential -time solution will be too slow, efficient approximations based on greedy or random approximation algorithms are necessary. By reducing one NP-complete problem to another, some aspect of it that was not immediately obvious but that can be exploited to produce a superior greedy algorithm may be revealed. Projects from previous years • Computer Graphics – Implementation of Ray Tracing to Create a Virtual Underwater Environment • The realistic rendering of a scene beneath the water's surface allows users to experience and learn about the underwater surroundings. Students are able to "travel" underwater with this education tool. Projects from previous years • Encryption – Encryption and Decryption Using Character Manipulation, Twist and Flip, and RSA • The project will combine three methods of encryption already used in various levels of security. Character (bit) manipulation provides the least amount of security, but combined with a modified Twist and Flip algorithm and RSA, the most advanced encryption method in use, there is the possiblity of a nearly unbreakable code. Projects from previous years • Database, Expert Systems – Online Bleeding Logs for Hemophiliacs: Simplifying Data Collection and Analysis • The objective of this project is to simplify for doctors of hemophiliacs the process of collecting, compiling, searching, and viewing information contained in their patients' bleeding logs. Projects from previous years • Computer Music – The Stravinsky Project : Using Genetic Algorithms to Compose Music • This program will use artificial intelligence and user input to compose original music using midi output from the computer. The AI will use genetic algorithms based on music theory to determine the "quality" of any given phrase, and the type of music will gravitate towards the preference of the user. Projects from previous years • Computer Graphics, Grid Computing – SETI Visualizations: Development of Graphical Utilities for Explaining SETI • The SETI (Search for Extra-Terrestrial Intelligence) program has been active since 1960. It publicises itself well with many text-based sites. However, few graphical utilities exist to explain the program. The purpose of this project is to develop such utilities using OpenGL. Projects from previous years • AI, Cellular Automata – with GMUComputer Science Dept. – Solving the Majority Classification Problem and Cellular Automata • Creation of an algorithm that will solve the Majority Classification Problem in an efficient and successful manner. Projects from previous years • Linux Educational Applications – The Luminance Open Source Educational Desktop • The Luminance Desktop aims to be the premier open source educational desktop. It will be comprised of many other open source projects. The Luminance desktop does not aim to reinvent the wheel and rewrite every single application. Rather its goals is to create uniformity and ease of use to the a small subset of users, students and teachers. All software forming the luminance desktop will be Open Source, in order to promote the Open Source philosophy. Projects from previous years • Portal to the Past - a Virtual Museum Tour • Three-Dimensional Network Structure Visualization Using OpenGL Graphics and TCP/IP • Creation of an Intelligent Traffic Light System • Exploration of Software Defined Radio • Investigation of Methods of Computer Music Generation • Random Terrain and Non-fractal Urban Environment Generation Projects from previous years • Terrain Generation in OpenGL • Polak-Ribiere conjugate gradient method for function minimization, Quantum Computing • New Quantum Mechanical Model of Lossy Information Propagation and Transmission • Parameter Defined Polygon Modification • Artificial Intelligence Techniques in Dots and Boxes •Modular Tank Simulation Thanks and have fun computing!