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/Home/Technology/Computer Science/Computer Programming/Computer Algorithms Journal of Graph Algorithms and Applications Votes:0 Journal of Graph Algorithms and Applications http://jgaa.info ISSN: 1526-1719 [ Home ] [ Electronic Edition ] [ Hardcopy Edition ] [ Scope ] [ Submission ] [ Mirrors ] Editors-in-Chief Roberto Tamassia Brown University Ioannis G. Tollis University of Crete and ICS-FORTH Advisory Board I. Chlamtac CREATE-NET G. N. Frederickson Purdue University T. C. Hu University of California at San Diego D. E. Knuth Stanford University C. L. Liu University of Illinois K. Mehlhorn Max-Planck Institut für Informatik T. Nishizeki Tohoku University F. P. Preparata Brown University I. H. Sudborough University of Texas at Dallas R. E. Tarjan Princeton University M. Yannakakis Columbia University In Memoriam S. Even Technion News October 2006. The Managing Editor and the Editors-in-Chief of JGAA are please Read More Go to Site Boolean Logic and Gates » PC Mechanic Votes:0 CLOSE You've Found Us! Now Stay Connected... Sign Up for PCMech.com's FREE weekly newsletter: Privacy Policy | More Information PCMech.com, a blog covering technology, computers and the Internet. Home | About | Newsletter | Forums | RSS | Shop.PCMech | Membership | Login Home News Wire Forums Comics Store How Do I Podcast Videos Ask Us Dave's Faves Helping Normal People Get Their Geek On Latest From The Wire Links to Reviews from Nov 19-21 Apples Continues to be Cocky Thanksgiving Wikipedia Stuff to Educate Your Brain Oprah Admits YouTube Comments Are a Problem 3 Quick Tips for Faster IMAP Gmail in Mozilla Thunderbird Subscribe to PC Mechanic Subscribe via RSS What is RSS? Or, via email. Follow PCMech on Twitter PCMech Sponsors Advertise on PCMech Sponsor Who Visits Boolean Logic and Gates Read More Go to Site CP2001 - Data Structures & Algorithms (3 units) Votes:0 CP2001 - Data Structures & Algorithms (3 units) Offered in : First Semester Availability : To all students on Townsville and Cairns campuses with appropriate prerequisites and corequisites. Prerequisite Subjects : CP1300 Prerequisite to Subjects : CP2002 , CP2003 , CP3050 , CP3060 , CP3070 , CP3100 , CP3110 , CP3210 Inadmissible Subject Combinations : CP2000, CP2010, CP2060, CP2101 Description Introduction to data structures; internal data structures, e.g., lists, queues, trees, and tables; external data structures, e.g., hashing and B-trees; analysis of algorithms; memory management. Object-oriented implementation. Staff Lecturer: TBA (Townsville) Lecturer: TBA (Cairns) Contact Hours Lectures: 39 Tutorials: 39 Assessment Assessment in this subject involves significant on-course assessment Read More Go to Site A Course of Distributed Algorithms Votes:0 A Course on Distributed Algorithms Prof. Seif Haridi, Computer Systems This is a web page including current information about the Ph.D. course on Distributed Algorithms, given by the Department of Teleinformatics at the Royal Institute of Technology. The course is based on the book: Introduction to Distributed Algorithms, by Gerard Tel, Cambridge University Press, ISBN 0 521 47069 2. The book will be augmented with material on three extra subjects namely, distributed garbage collection algorithms, mobile objects protocols, and distributed unification algorithms. Content Introduction, and overview of the course Distributed programming model Communication Protocols Routing Algorithms Deadlock-free packet switching Wave and traversal algorithms Election algorithms Termination detection Snapsh Read More Go to Site A Toolkit for the Simulation of Distributed Algorithms in Java Votes:0 A Toolkit for the Simulation of Distributed Algorithms in Java We describe a toolkit for designing, implementing, testing, simulating, and visualizing distributed algorithms in Java. The toolkit consists of a Java class library with a simple programming interface that allows to develop distributed algorithms based on a message passing model. The resulting programs may be executed in standalone mode using a Java interpreter or embedded as applets into HTML pages and executed by Web browsers. The goal of the toolkit is to provide an universally accessible platform for research and education in the area of distributed algorithms. The toolkit is freely available over the World Wide Web. Examples Execute distributed programs as applets in your Web browser. 3 Nodes in a Ring A trivial distribute Read More Go to Site Algorithm Animation Votes:0 Algorithm Animation I've written some Java code for animating algorithms. As time passed, the code developed into a general-purpose system. The latest version, which I call Gawain , is available online . Some earlier efforts An old applet that animates Graham's Scan , and here's the Java source code for the applet. An early version of Gawain . It runs on Java 1.0, suitable for older browsers. Author: Alejo Hausner email: ah@cs.princeton.edu CS Department , Princeton University Last Updated: May 9, 1996 Read More Go to Site Algorithm Tutorial Votes:0 Delite Algorithm Tutorial This help file covers how to invoke and understand the various design algorithms found in Delite. We could include an outline but it is far simpler to just go to the Navigate menu of this window and then select "Table of Contents". The outline of the following sections appears in a new dialog. Prim's Algorithm Prim-Dijkstra Algorithm Tours Esau-Williams Algorithm Sharma The Multi-speed Tree Design Algorithm The Nearest-Neighbor Esau-Williams Algorithm The Multiple Center Esau-Williams Algorithm The MENTOR Algorithm The MENTOR-II Algorithm The MENTour Algorithm The IncreMENTOR Algorithm Prim's Algorithm We begin the tutorial by looking at Prim's algorithm. This algorithm builds a minimum spanning tree. This is the cheapest tree which can be constructed which links Read More Go to Site Algorithms Votes:0 Dr. Gabriel Robins Professor of Computer Science Department of Computer Science School of Engineering and Applied Science University of Virginia 151 Engineer's Way, P.O. Box 400740 Charlottesville, VA 22904-4740, USA robins@cs.virginia.edu www.cs.virginia.edu/robins Phone: (434) 982-2207, Fax: (434) 982-2214 Office: 210 Olsson Hall Gabe's vitae / resume ( NIH Biosketch ) CS661 - Algorithms, University of Virginia The CS661 Midterm Exam (take-home & open book) pick-up period starts at noon on Tues Mar 20, and ends at 5pm the next day (Wed). You have 48 hours to work on it (so all midterms are due by 5pm on Fri March 23). All exams should be picked up and droped off with Brenda at the front CS office. --> The CS661 Final Exam (take-home & open book) pick-up period starts at noon on Wed May 2 Read More Go to Site Algorithms and Complexity Votes:0 Skip to content Skip to navigation Text only • Sign in Search: Department of Computer Science [n] Home About the Department Calendar of Events Admissions Teaching Research Algorithms and Complexity Members Seminar Activities Computational Biology Empirical Modelling Formal Methods High Performance Systems Intelligent and Adaptive Systems Medical Informatics and Medical Image Computing Signal and Image Processing People Directory Intranet Not signed in Sign in Powered by Sitebuilder © MMVII | Privacy Accessibility Algorithms and Computational Complexity Research Group [c] Research in the Algorithms and Computational Complexity Research Group is concerned with various topics of Theoretical Computer Science, Algorithms, and Complexity Theory. Our research aims at providing understanding Read More Go to Site Algorithms and Complexity Votes:0 Algorithms and Complexity by Herbert S. Wilf This is the first edition of my book Algorithms and Complexity , in the form of a single Acrobat file of about 1.1Mb. The book was in print from 1986 to 1994, and the copyright has now been returned to me. The second edition has just been published! See below. Terms and Conditions By downloading this file you are agreeing to the following conditions of use: Copyright 1994 by Herbert S. Wilf. This material may be reproduced for any educational purpose, multiple copies may be made for classes, etc. Charges, if any, for reproduced copies must be no more than enough to recover reasonable costs of reproduction. Reproduction for commercial purposes is prohibited. The cover page, which contains these terms and conditions, must be included in all distri Read More Go to Site Algorithms and Data Structures (CSE 2320) Fall 1999 Votes:0 Algorithms and Data Structures (CSE 2320) Fall 1999 Algorithms and Data Structures (CSE 2320) Fall 1999 CSE 2320 Section 501/571 105 Nedderman Hall, TuTh 5:30-6:50pm University of Texas at Arlington Department of Computer Science and Engineering Past semesters: Fall 98 , Spring 99 Other course materials: Dr. Holder's CSE 5311 Materials Dr. Cook's CSE 5311 Materials , Description: Design and analysis of algorithms with an emphasis on data structures. Approaches to analyzing lower bounds on problems and upper bounds on algorithms. Classical algorithm design techniques including algorithms for sorting, searching, and other operations on data structures such as hash tables, trees, graphs, strings, and advanced data structures, dynamic programming and greedy approaches. Prerequisites: C/C++ Pro Read More Go to Site Algorithms Project's Home Page Votes:0 Algorithms Project's Home Page Welcome! Research Topics People Publications Seminars Software On-Line Applications Jobs & Internships Welcome to the Algorithms Project! INRIA Rocquencourt Organizations Links Contacts Last modified: August 10, 2007. For problems or questions involving this site, please contact Virginie Collette . Read More Go to Site Arrays Votes:0 Arrays 7/31/97 Click here to start Table of Contents Arrays Iteration Through an Array Searching Through the Values PPT Slide Searching for a Value PPT Slide Binary Search Binary Search Algorithm Illustration of Binary Search PPT Slide PPT Slide PPT Slide PPT Slide PPT Slide PPT Slide PPT Slide PPT Slide PPT Slide PPT Slide Binary Search Alternative Implementation Selection Sort Example: of Selection Sort Example: of Selection Sort Example: of Selection Sort Example: of Selection Sort Example: of Selection Sort Example: of Selection Sort Example: of Selection Sort Example: of Selection Sort Example: of Selection Sort Example: of Selection Sort Example: of Selection Sort Example: of Selection Sort PPT Slide PPT Slide PPT Slide PPT Slide PPT Slide Selection Sort Algorithm Selection Sort Code Read More Go to Site BSP and CGM Algorithms Votes:0 This work was initiated by Prof. Frank K. H. A. Dehne with the purpose of providing a comprehensive archive of papers on algorithms in the Bulk Synchronous Parallel (BSP), the BSP* and the Coarse Grained Mulitcomputer (CGM) Model. The references herein were gathered and catalogued by Silvia Goetz . Note: Download the compressed ps-files with click of your right mouse button and "save link as"-field ! Overview on Algorithms Silvia Goetz , " Algorithms in CGM, BSP and BSP* Model: A Survey ", Term Paper for Graduate Course "Parallel Algorithms and VLSI Implementation", Carleton Unviversity, Ottawa, January 1997. on Parallel Computation Models B.M. Maggs, L.R. Matheson, R.E. Tarjan, " Models of Parallel Computation: A Survey and Synthesis , Proc. of the 28th Hawaii International Conference on Read More Go to Site Center for GIVE Votes:0 Center for GIVE Research information for the Center for Geometry, Imaging and Virtual Environments . Master Program GMT Information for (prospective) students of the master program Game and Media Technology . contact: G.J. Giezeman Read More Go to Site Character Recognition by Feature Point Extraction Votes:0 Character Recognition by Feature Point Extraction Eric W. Brown feneric@ccs.neu.edu Abstract The ability to identify machine printed characters in an automated or a semi-automated manner has obvious applications in numerous fields. Since creating an algorithm with a one hundred percent correct recognition rate is quite probably impossible in our world of noise and different font styles, it is important to design character recognition algorithms with these failures in mind so that when mistakes are inevitably made, they will at least be understandable and predictable to the person working with the program. This paper explores one such algorithm and tests it on two different fonts using a third font as a Read More Go to Site Classes | Department of Computer Science | University of Illinois at Urbana-Champaign Votes:0 Undergraduate Graduate Online Programs Research Directory About Us Awards Alumni Corporate Relations Outreach/Diversity Calendar In the News Search Classes for the Fall 2007 Semester For a list of course descriptions, see undergraduate courses and graduate courses . The university also maintains a Class Schedule for the current semester, and a Course Catalog . Information about Instructional Labs listed below can be found at: Computer Science Instructional Labs (CSIL) Engineering Workstations (EWS) Newsgroups exist for most courses, typically named 'class.cs###'. Complete information on how to access these newsgroups can be found at news.cs.uiuc.edu . See the Campus Class Schedule for the descriptions of sections of CS 196, CS 296, CS 591, CS 598 courses. Class Title (Link to Description) Read More Go to Site CMSC 427-Computer Graphics Votes:0 CMSC 427 Computer Graphics Dave Mount Spring 2004 Home Handouts Lectures OpenGL Syllabus Art-Gallery Announcements The course is over. I have combined all the lecture notes and handouts into one large pdf file. General Information Class Time Tue, Thu 2:00-3:15 Room CSIC 3117 Course Info Syllabus (also in PDF format ) Text Computer Graphics with OpenGL (3rd edition), D. Hearn and M. P. Baker, Prentice Hall, 2004. Personnel Instructor Teaching Assistant Name Dave Mount Pooja Nath Email mount@cs.umd.edu pooja@cs.umd.edu Office AVW 3373 AVW 1112 Office hours Mon 3:00-4:00, Wed 3:00-3:45. Tue 3:30-4:30pm, Thu 9:30-10:30am If you cannot make these office hours, please send email to arrange another time. Handouts The handouts and homeworks have been combined into a single pdf file. Some pages are Read More Go to Site Collected Algorithms of the ACM Votes:0 Collected Algorithms The Collected Algorithms ( CALGO ) is part of a family of publications produced by the ACM . Background Software associated with papers published in the Transactions on Mathematical Software , as well as other ACM journals are incorporated in CALGO. This software is refereed for originality, accuracy, robustness, completeness, portability, and lasting value. (See the ACM Algorithms Policy for details.) Readers may subscribe to CALGO. Subscribers receive quarterly notification of the appearance of new algorithms, as well as copies of research papers describing them in loose-leaf binder form. Back issues may also be ordered. Use of ACM Algorithms is subject to the ACM Software Copyright and License Agreement Contact For further information about CALGO contact its Editor- Read More Go to Site Computer Arithmetic Algorithms Simulator Votes:0 A companion website to the book " Computer Arithmetic Algorithms " by Israel Koren . About this site. THE ALGORITHMS: Addition Ripple-Carry Addition , Manchester Adder , Carry-Look-Ahead Adder , Ling's Adder , Conditional-Sum Adder , Carry-Select Adder , Carry-Skip Adder , Hybrid Adder (Lynch and Swartzlander) Multiplication Sequential , Booth's Algorithm , Modified Booth's Algorithm , Two's Complement Array Multiplier , Fused Multiplier-Adder Division Restoring , Non-Restoring , SRT Radix-2 , SRT Radix-4 , SRT Radix-8 , SRT with overalpping stages , By Convergence , By Convergence With Table Lookup , By Reciprocation Square Root Restoring , Non-Restoring , SRT Radix-2 , SRT Radix-4 , By convergence Floating-Point Arithmetic Addition and Subtraction , Far and Close Cases , Multiplication a Read More Go to Site Course Page -- Algorithms (CMSC 251) Votes:0 Home Page for CMSC 251 (Algorithms) Grades will be ready Tuesday afternoon (Dec 17). On my door. Instructor: Samir Khuller Office: AVW 3217. Office phone: 405--6765. E-mail: samir@cs.umd.edu. Office Hours: Monday: 3pm--4pm, Wednesday 5pm--6pm, Thursday: 11am--12am. If you cannot make these hours, please make an appointment to see me at a different time. Teaching Assistant: Sungjoon Ahn Office: AVW 4160. Office phone: 405--2724. E-mail: sjahn@cs.umd.edu. Office Hours: Monday: 1-2pm, Wednesday: 1-2pm, Friday: 11-12am. Office hours will be held in AVW 1109. Also by appointment. The BEST way to contact the TA is to send him email. I will update this page every week during the semester. I will place all homeworks as well as solutions to homeworks here. If you have any trouble accessing them, pl Read More Go to Site Crossroads Feature Articles Votes:0 Crossroads The ACM Student Magazine ACM / Crossroads / Doc / Indices / Crossroads Feature Articles Features Focus on Student Life: Career Graduate School Research Advice Themes of Feature Articles: Algorithms Artificial Intelligence Agents Artificial Life Computer Architecture Computer Games Computer Graphics Databases E-Commerce Information Technology Interdisciplinary Computer Science Markup Languages Mobile and Wireless Computing Multimedia Networking Operating Systems Linux Parallel Computing Programming Object Oriented Programming Windows Programming Programming Languages Java Robotics Security Social Issues Software Engineering Tutorials User Interfaces Algorithms An Error-Controlled Octree Data Structure for Large-Scale Visualization Image Compression - from DCT to Wavelets: A Revie Read More Go to Site CS 161: Design and Analysis of Algorithms Votes:0 CS 161 Design and Analysis of Algorithms Fall 2007 [Announcements] [Course Handouts] [Course Information] [Frequently Asked Questions] General Information Course Information Homework Sets Announcements FAQ --> Announcements If you decide to take a late day on Homework 4, you must turn in the homework by Tuesday, 11/20. You must submit either electronically or under Professor Plotkin's door. Jason's office hours will be cancelled the Monday after Thanksgiving week (11/26). Sorry for any inconvenience. Jason's office hours will be held from 1-3 this Monday (10/29). They will also be cancelled next Friday (11/2). Sorry for any inconvenience. The midterm will be on November 6th, in class. From now on, we will only grade homeworks submitted online and will not print them out to return with comm Read More Go to Site CS2604 Spring 1999 Votes:0 CS2604: Data Structures and File Processing Spring Semester 1999 Instructors Bill McQuain (MWF at 1:00 Section) Email: mcquain@cs.vt.edu Office: McBryde 631, 540-231-5605 Office Hours: TBA Dr. John Roach (MWF at 9:00 and 11:00 Sections) Email: roach@vtopus.cs.vt.edu Office: McBryde 622, 540-231-5368 Office Hours: Mon: 0800-0850, Wed: 1000-1050, Fri: 1300-1400 Dr. Cliff Shaffer (TuTh at 12:30 Section) Email: shaffer@cs.vt.edu Office: McBryde 331, 540-231-4354 Office Hours: Tu 11-12 and by appointment. GTAs: Farooq Ali, mfali@csgrad.cs.vt.edu Duxing Cai, dcai@vt.edu Vinil Cheeramuelil, vinil@csgrad.cs.vt.edu Jialin Xiang, jxiang@vt.edu Announcements The final exam will be on Tuesday, May 11 at 1:05-3:05. Listserv archive has been updated for the month of March Sample solutions to Homework As Read More Go to Site CSE 373 - Analysis of Algorithms Votes:0 CSE 373 - Analysis of Algorithms Course Time: 3:50 - 5:10PM Tuesday-Thursday Place: 103 Javits. Steven Skiena's office hours are 11:15AM-12:45PM Tuesday-Thursday, and after class in 1411 Computer Science, and by appointment. The course TA will be Yun Zeng. His email address is theory.of.computation@gmail.com He will have office hours Monday and Wednesday from 1PM to 2:30PM in 1207 CS. During finals week Girish will have office hours by appointment (send him email) and on: Wednesday 5/10, 4-5:30PM Friday 5/12, 12:30-2PM (NOTE CHANGE) Monday 5/15, 2-4PM (NOTE CHANGE) Graded homeworks will be available in a box outside my office. Good luck on your finals! --> Lecture Notes Lecture notes from the current semester are available here . Lecture notes from previous semesters are available in HTML Read More Go to Site Data Structures and Algorithms II Votes:0 What this Course is About The course introduces a range of standard data structures and algorithms that are important for practical programming tasks, focusing on graph, string, and geometric algorithms. This web page will be used simply to make available any handouts and slides that are not given in the lectures. It is not intended as a full web site describing the course. The module descriptor is available here . Notes and Handouts This year's lecture handouts are available in PDF form (below). They should be available a day or two before the lecture, for those who wish to go over the material in advance. This link also contains various other useful stuff. Lecture Handouts, Jan-Mar 2000 A full html version of the course from 97/98 is here . There will be some changes this year, but this Read More Go to Site Data Structures and Algorithms in Java (second edition) Votes:0 Your browser should now automatically switch you to http://java.datastructures.net Read More Go to Site Data structures and algorithms: A comparative slice and dice -- er, review -- of 5 Java DS&A books - Java World Votes:0 Advanced search Click Here Home Research Centers + Java Standard Edition APIs AWT / Swing Design Patterns User Interface Design Java Database Connectivity (JDBC) Java Virtual Machine (JVM) Java Q&A Java Tips + Java Enterprise Edition Enterprise JavaBeans (EJBs) Java Message Service JavaServer Pages Servlets Web Services and SOAs Java and XML Design Patterns Performance Tuning + Java Micro Edition + Development Tools Application Management Data Access Tools Gaming Tools Web Development Frameworks Security & Testing Java Application Servers Profiling and Monitoring Reporting Site Resources Featured Tutorials News & Reviews Forums Podcasts Newsletters White Paper Library Web resources RSS Feeds Careers Partner Sites Demo.com LinuxWorld.com NetworkWorld.com About Us sponsored links See your li Read More Go to Site David MacKay: Information Theory, Pattern Recognition and Neural Networks: The Book Votes:0 David MacKay Information Theory, Pattern Recognition and Neural Networks Prerequisites Summary Slides Supervisions The Book « · Errors Software Any questions? Search : Information Theory, Inference, and Learning Algorithms (Hardback, 640 pages, Published September 2003) Order your copy Price: £35.00 / $60.00 from | CUP UK / USA | | amazon.co.uk / .com / .ca / .co.jp | | Barnes and Noble USA | booksprice . | fetchbook.info | allbookstores | biggerbooks | blackwells | directtextbook | kalahari.net (South Africa) | Special Paperback edition for South Asia .| Download the book too You can browse and search the book on Google books . You may download The book in one file (640 pages): U.K. Canada South Africa PDF (A4) pdf (9M) (fourth printing, March 2005) pdf pdf Postscript (A4) postscript (fou Read More Go to Site Design and Evaluation of a Compiler Algorithm for Prefetching Votes:0 Next: Introduction Design and Evaluation of a Compiler Algorithm for Prefetching Todd C. Mowry, Monica S. Lam and Anoop Gupta Computer Systems Laboratory Stanford University, CA 94305 Abstract: Software-controlled data prefetching is a promising technique for improving the performance of the memory subsystem to match today's high-performance processors. While prefetching is useful in hiding the latency, issuing prefetches incurs an instruction overhead and can increase the load on the memory subsystem. As a result, care must be taken to ensure that such overheads do not exceed the benefits. This paper proposes a compiler algorithm to insert prefetch instructions into code that operates on dense matrices. Our algorithm identifies those references that are likely to be cache misses, and issu Read More Go to Site Elementary Algorithms Using Discrete Loops Votes:0 Elementary Algorithms Using Discrete Loops The following examples of classic algorithms show the effective use of the 'discrete loop'-construct developped under the WOOP project defined in the paper Discrete Loops And Worst Case Performance (J. Blieberger, Department of Automation at the Technical University of Vienna). Algorithms Mathematical algorithms Euclid's Algorithm Fast Fourier Transformation Fibonacci numbers Josephus algorithm Tree algorithms Binary tree traversal AVL tree traversal BB[alpha] tree traversal Search algorithms Binary search Fibonacci search Interpolation search Sorting algorithms Heap sort Merge sort Shell sort Note: To compile and use the examples from this pages, you have to install the precompiler for the discrete loops (WPP). For further information concerning Read More Go to Site Evolvica - Table of Contents Votes:0 Evolutionary Algorithms in Action An Interactive Tutorial based on Java Applets and Mathematica Notebooks Christian Jacob Dept. of Computer Science , Programming Languages University of Erlangen and Dept. of Computer Science , The University of Calgary, Canada Table of Contents Introduction About Evolvica ... This section gives a brief overview of the ideas behind Evolvica as a web and notebook based tutorial on evolutionary algorithms. The following two examples serve as a first glimpse on the fundamental evolution principles of selection and mutation. The selection-mutation principle: A simple demonstration with Mathematica Selection and mutation: A Java example Evolutionary algorithms in Java About Java ... Exploring evolution with Java An illustrative way to find out about evolutionary Read More Go to Site flipCode - Harmless Algorithms Votes:0 Please update your bookmarks. This column interface is outdated. These articles have been reformatted and placed within our article archive . This page is here to avoid broken links, but please update your bookmarks to reflect the new URLs in the article archive. Harmless Algorithms is an exciting trip through some of the most interesting 3D algorithms and techniques currently in use by video games (amongst other fields). Harmless (Edward Kmett) offers valuable insight into how different algorithms and data structures work ranging from various bsp tree implementations to octrees and plenty more! This column is updated at random depending on Harmless' schedule, but even if it takes a while, its well worth the wait! Note that this column is not neccesarily for beginners :) 04/09/1999 - Issue Read More Go to Site GA Playground - Java Genetic Algorithms Toolkit Votes:0 A general GA toolkit implemented in Java, for experimenting with genetic algorithms and handling optimization problems Contents The GAA Applet/Application Overview Browser Requirements and Loading Times General Notes Alphabet Problem Definition - Definition Files Problem Definition - Source Modifications Special GA Mechanisms Automatic 'Kick' Kin-competition compensating factor Memory Pre &amp Post Breed Functions Interactively (on-the-fly) defined functions Continuous Reporting Graphic Display User-Initiated Logging File Input/Output Application Mode IO Applet Mode IO Online Help Documentation Download and Installation Applet Mode Application Mode Classpath (Application mode) Application Batch File Javadoc Files Source Code Limitations and Request for feedback Examples and Test Problems G Read More Go to Site GAlib: Matthew's Genetic Algorithms Library Votes:0 GAlib A C++ Library of Genetic Algorithm Components the current release is version 2.4.7 GAlib contains a set of C++ genetic algorithm objects. The library includes tools for using genetic algorithms to do optimization in any C++ program using any representation and genetic operators. The documentation includes an extensive overview of how to implement a genetic algorithm as well as examples illustrating customizations to the GAlib classes. Licensing GAlib is free. Licensing and copyright details are available. Documentation Answers to frequently asked questions Mailing list and mailing list archive Complete documentation in HTML or PDF format Screen Shots of GAlib examples Where to get the current version... http://lancet.mit.edu/ga/dist/ System Requirements GAlib has been built on variou Read More Go to Site GEATbx: Documentation - Genetic and Evolutionary Algorithm Toolbox for MATLAB Votes:0 GEATbx: Main page Tutorial Algorithms M-functions Parameter/Options Example functions www.geatbx.com GEATbx: Genetic and Evolutionary Algorithm Toolbox for use with MATLAB Documentation Version 3.70 (released November 2005) Author: Hartmut Pohlheim The Genetic and Evolutionary Algorithm Toolbox (GEATbx) implements a wide range of genetic and evolutionary algorithms to solve large and complex real-world problems. Many ready-to-run demos and examples are included. The documentation of the GEA Toolbox contains a 1 Tutorial , an 2 Introduction to Evolutionary Algorithms and a large 3 Reference section. A first overview can be found in 4 Features of the GEATbx and 5 Implementation of the GEATbx . The 6 Installation of the GEATbx is simple and can be done in a minute. 1 Tutorial Tutorial - expla Read More Go to Site Generation 5: Artificial Intelligence Repository - Introduction to Genetic Algorithms Votes:0 Please use a JavaScript-enabled browser! Get Microsoft Internet Explorer 4.0 for the best out of this site. For the meanwhile, you will have to use the text-based index to navigate the site. Sorry, JavaScript required for this. Introduction to Genetic Algorithms and Genetic Programming After scientists became disillusioned with classical and neo-classical attempts at modelling intelligence, they looked in other directions. Two prominent fields arose, connectionism (neural networking, parallel processing) and evolutionary computing. It is the latter that this essay deals with - genetic algorithms and genetic programming. Symbolic AI vs Genetic Algorithms Most symbolic AI systems are very static. Most of them can usually only solve one given specific problem, since their architecture was des Read More Go to Site Genetic Algorithms FAQ Votes:0 AI-related FAQs Genetic Algorithms FAQ FAQ: comp.ai.genetic part 1/6 (A Guide to Frequently Asked Questions) FAQ: comp.ai.genetic part 2/6 (A Guide to Frequently Asked Questions) FAQ: comp.ai.genetic part 3/6 (A Guide to Frequently Asked Questions) FAQ: comp.ai.genetic part 4/6 (A Guide to Frequently Asked Questions) FAQ: comp.ai.genetic part 5/6 (A Guide to Frequently Asked Questions) FAQ: comp.ai.genetic part 6/6 (A Guide to Frequently Asked Questions) Last Web Update on August 10, 1997 by Mark Kantrowitz AI.Repository@cs.cmu.edu Read More Go to Site Genetic Algorithms on Proteins Votes:0 Genetic Algorithms and Protein Folding by Dr. Steffen Schulze-Kremer WestfÄlische Strasse 56, D-10711 Berlin, FRG E-mail: steffen@chemie.fu-berlin.de All-in-one Html file (THIS FILE IS BIG !) Postscript Version. Revised Tue Jun 25 17:30:20 MET DST 1996 Table of Contents 1 Evolutionary Computation (introduction) 1.1 Methodology 1.1.1 Genetic Algorithms 1.1.2 Evolution Strategy 1.2 Applications 1.2.1 Protein Folding Simulation by Force Field Optimisation 1.2.1.1 Representation Formalism 1.2.1.2 Fitness Function 1.2.1.3 Conformational Energy 1.2.1.4 Genetic Operators 1.2.1.5 Ab initio Prediction Results 1.2.1.6 Side Chain Placement 1.2.2 Multi-Criteria Optimisation of Protein Conformations 1.2.2.1 Vector Fitness Function 1.2.2.2 Specialised Genetic Operators 1.2.2.3 Results Exercises Referenc Read More Go to Site Handbook of Algorithms and Data Structures Votes:0 Handbook of Algorithms and Data Structures Gaston H. Gonnet Informatik, ETH ZÜrich Ricardo Baeza-Yates Dept. of Computer Science, Univ. of Chile Warning: This Beta version needs a browser capable of handling tables. The contents is still under revision, please send comments as indicated below if you find any problem. These WWW pages are not a digital version of the book, nor the complete contents of it. Here you will find the preface, table of contents, index and all source code of the handbook. The main goal is to make available through Internet the source code of many algorithms (in C and/or Pascal) that have been already tested. The printed version of the Handbook includes over a thousand references and details many of the algorithms presented here. It should be ordered directly to Addi Read More Go to Site Hands On C++ Algorithms Library Quick Reference Votes:0 C++ algorithms Library Quick Reference In each of the following descriptions, start is an iterator pointing to the beginning of a sequence (usually container .begin() ), and stop is an iterator pointing to the end of a sequence (usually container .end() ). Most of these require that the header file algorithm be included ( accumulate() requires numeric instead). This is not an exhaustive listing of the C++ standard algorithms library. For an exhaustive list, see the latest on the ANSI C++ standard at Cygnus.com . algorithm Description accumulate( start , stop , value ); Return the sum of the values in the sequence plus value find( start , stop , value ); Return an iterator to value in the sequence, or stop if it is not present count( start , stop , value ); Return the number of times value Read More Go to Site IBM Research | Almaden Research Center | Computer Science Votes:0 United States [ change ] Terms of use All of IBM Home Products Services & solutions Support & downloads My account IBM Research Almaden Research Center IBM CS Research Computer Science Research Areas Projects People Work with Universities Work with Clients Achievements Publications Events News Career Opportunities Feedback Sixth A Link Sixth B Link --> Related Links Almaden CS Storage Systems Worldwide Labs Computer Science Principles and Methodologies Overview A tribute to John Backus , one of the first members of our Theory Group, written by Alex Aiken . The IBM Computer Science Principles and Methodologies Group (aka the Theory Group) explores foundational issues that confront the computing industry today. Because theory cuts across every aspect of computer science, we tend to interact Read More Go to Site Intro to Genetic Algorithms Votes:0 Introduction to Genetic Algorithms This is an introduction to genetic algorithm methods for optimization. Genetic algorithms were formally introduced in the United States in the 1970s by John Holland at University of Michigan. The continuing price/performance improvements of computational systems has made them attractive for some types of optimization. In particular, genetic algorithms work very well on mixed (continuous and discrete), combinatorial problems. They are less susceptible to getting 'stuck' at local optima than gradient search methods. But they tend to be computationally expensive. To use a genetic algorithm, you must represent a solution to your problem as a genome (or chromosome ). The genetic algorithm then creates a population of solutions and applies genetic operators suc Read More Go to Site Introduction to genetic algorithms with Java applets Votes:0 GENETIC ALGORITHMS These pages introduce some fundamentals of genetics algorithms. Pages are intended to be used for learning about genetics algorithms without any previous knowledge from this area. Only some knowledge of computer programming is assumed. You can find here several interactive Java applets demonstrating work of genetic algorithms. This page uses frames, but your browser doesn't support them. Please check requirements for the browser at the about page . You can access all documents from page with contents . We recommend you to start from the main page . Sorry for any inconvenience. (c) Marek Obitko, 1998 Read More Go to Site Kirk Pruhs' Home Page Votes:0 Professor Kirk Pruhs Dept. of Computer Science 210 South Bouquet Street Sennott Square Building, Room 6415 University of Pittsburgh Pittsburgh , PA 15260 Email: kirk@cs.pitt.edu Phone : 412-624-8844 Fax : 412-624-8854 Research My research interests are in algorithmic problems that arise in computer systems and computer networks. My current research focuses on algorithmic problems in temperature and energy aware computing, algorithmic problems in scalable multicast-based data dissemination methods, server scheduling algorithms, online algorithmic problems, and algorithms for dynamic spectrum allocation. A reasonably accurate list of publications from DBLP and some papers available online A slightly dated Vita Teaching and Education Current Post-Doc Ho-Leung Chan Current PhD Students: Mohame Read More Go to Site Lesson: Concurrency (The Java™ Tutorials > Essential Classes) Votes:0 Download the JDK Search the Tutorials Hide the TOC Concurrency Processes and Threads Thread Objects Defining and Starting a Thread Pausing Execution with Sleep Interrupts Joins The SimpleThreads Example Synchronization Thread Interference Memory Consistency Errors Synchronized Methods Intrinsic Locks and Synchronization Atomic Access Liveness Deadlock Starvation and Livelock Guarded Blocks Immutable Objects A Synchronized Class Example A Strategy for Defining Immutable Objects High Level Concurrency Objects Lock Objects Executors Executor Interfaces Thread Pools Concurrent Collections Atomic Variables For Further Reading Questions and Exercises Trail: Essential Classes Home Page > Essential Classes « Previous • Trail • Next » Lesson: Concurrency Computer users take it for gran Read More Go to Site LYDIAN:An Extensible Educational AnimationEnvironment for Learning Distributed Algorithms Votes:0 Main Page Description FAQ Courses that Use(d) LYDIAN Download Installation Manual html pdf ps.gz Updates & Changes Forums A VR Extention EXJOBBS People Related Publications One area in which visualization techniques may be applied to enhance understanding of computer systems is the field of distributed algorithms. Lydian is a simulation and visualization environment for distributed algorithms that provides to the students an experimental environment to test and visualize the behaviour of distributed algorithms. It gives to the students the ability to create easily their own experiments and visualize the behaviour of the algorithms on their experiments. Lydian is easy to use and can also be extended. Last modified: Thu May 26 15:19:59 CEST 2005 Read More Go to Site Materials Algorithms Project Votes:0 Materials Algorithms Project Welcome to MAP A centre for the "validation" and distribution of algorithms useful in the modelling of materials. MAP is a library which can be used to build on existing knowledge. Enter Library Purpose Participation Organisation Downloading Publications Contributors Links Statistics Online calculations Mirror site in North America (Northwestern University) Mirror site in Japan (JWRI, Osaka University) MAP owes its origins to the Phase Transformations Group of the University of Cambridge and the National Physical Laboratory . It is a non-profitmaking venture, sponsored originally by the Engineering and Physical Sciences Research Council of the United Kingdom. Superalloys Titanium Bainite Martensite WidmanstÄtten ferrite Cast iron Welding Allotriomorphic ferrite Read More Go to Site Minimum Genetic Tree Finder Using Kruskal Algorithm Votes:0 Minimum Genetic Tree Finder Using Kruskal Algorithm More info about this applet you can find in : Algorithms Tutoring Web Page Or you can go to : my Homepage ? Read More Go to Site Montreal Machine Learning Workshop 2000 Votes:0 CRM / MITACS / IRIS Workshop on Selecting and Combining Models with Machine Learning Algorithms Montreal, QuÉbec, Canada, April 11-14, 2000 April 11-14, 2000 Centre de Recherches MathÉmatiques , MontrÉal Organizers: Yoshua Bengio (UniversitÉ de MontrÉal) and Dale Schuurmans (University of Waterloo) Workshop Program and Pointers to Workshop Material Location of the conferences: Room 1140 (1st floor), Pavillon Andr?-Aisenstadt, Universit? de Montr?al, 2920 Chemin de la Tour, Montr?al Workshop Objectives A central objective of machine learning research is to develop algorithms that learn predictive relationships from data. This is a central component of data mining and knowledge discovery tasks, which are becoming commonplace applications in the realm of e-commerce. This is a difficult task, Read More Go to Site Moshe Sipper's Site Votes:0 Call for Papers: Evolutionary Computation in Games --> Read More Go to Site NNUGA - Neural Network Using Genetic Algorithms Votes:0 NNUGA Neural Network Using Genetic Algorithms By Omri Weisman and Ziv Pollack A final project in the course Robotics 95 Using Genetic Algorithms in Computer Learning Essentially, Genetic Algorithms (GA) are a method of "breeding" computer programs and solutions to optimization or search problems by means of simulated evolution . Processes loosely based on natural selection, crossover, and mutation are repeatedly applied to a population of binary strings which represent potential solutions. Over time, the number of above-average individuals increases, and better fit individuals are created, until a good solution to the problem at hand is found. In NNUGA, we are using GA to find the solution to a classification problem with a neural network (NN). The neural network is a structure which is ab Read More Go to Site Out of order Votes:0 Out of order The Algorithm Archive is Dead I 've never been satisfied with the archive both because it was always incomplete and because the code included had many bugs. In a moment of clarity I admitted to myself that I had no time anymore to maintain it. So that left me with two choices: leave it up in its ragged, buggy state or take it down. I chose to take it down. If you are interested you may download the archive in tar.gz format for your own use. --Scott, August 2001 Read More Go to Site Penn State Univ. Berks CMPSC 101 with Mr. Minich Votes:0 CMPSC 101 - C++ Programming Penn State University - Berks Campus Instructor - Mr. Minich General Resources Lecture Notes More Demo Programs Tuesday Thursday Class Schedule variables variables Aug 28 Aug 30 Syllabus if's & loops if's & loops Sep 4 asst #1 is due Sep 6 asst #1 is due Assignments functions functions Sep 11 Sep 13 Exam Info files files Sep 18 Sep 20 Grades arrays arrays Sep 25 asst #2 is due Sep 27 asst #2 is due Worksheets strings strings Oct 2 Oct 4 Demo Programs Oct 9 Exam #1 Oct 11 Exam #1 Coding Standards Oct 16 Oct 18 Angel Oct 23 Oct 25 Visual C++ Software Oct 30 asst #3 is due Nov 1 asst #3 is due Visual C++ Online Help Nov 6 Nov 8 Miscellaneous Links Nov 13 Exam #2 Nov 15 Exam #2 Nov 27 Nov 29 Dec 4 Dec 6 Dec 11 Dec 13 Thur Dec 20 3:25 - 5:15 pm in Luerssen Room 005 a Read More Go to Site PERFORMANCE' 96 TUTORIALS Votes:0 PERFORMANCE '96 Lausanne, October 7-11, 1996 International Conference on Performance Theory, Measurement and Evaluation of Computer and Communication Systems (Organised by IFIP WG7.3) Tutorials Click on the following links to get an abstract of the tutorial and links for downloading the Postscript files (if available) of the Tutorial slides. Issues in Trace-Driven Simulation Error Bound Analysis for Queueing Networks Queueing Networks with Finite Capacity Queues and Blocking Parallel Simulation Algorithms and Software Discrete Time Queueing Networks: Recent Developments Structured Analysis Approaches for Large Markov Chains Benchmarking An Introduction to Large Deviations and its Applications to Teletraffic Engineering Back to Performance '96 home page. Read More Go to Site Predicting Algorithm Performance Votes:0 In Computing Science and Statistics 30 (1998), pp. 309-314. Predicting Algorithm Performance Joshua Landrum EECS Department, University of Michigan Janis Hardwick Statistics Department, Purdue University Quentin F. Stout EECS Department, University of Michigan Abstract: We have developed a sequential approach which predicts the time that a computer algorithm will take to solve a large problem of specified size on a given system. We use regression techniques to extrapolate observations of the time needed to solve smaller problems. The past observations and current predictions are used to adaptively decide the size of problem to be observed next. While based on classic ideas, some unique aspects occur in this setting. One is that observations of small inputs can be accomplished more quickly Read More Go to Site Programming Parallel Algorithms Votes:0 Programming Parallel Algorithms Guy E. Blelloch Computer Science Department Carnegie Mellon University This page is an online version of an article that appears in the --> March 1996 issues of the Communications of the ACM , 39(3). The examples that appear in the paper can be run interactively. Table of contents Introduction Work and Depth Why Work and Depth? Relationship of Work and Depth to Running Time Nested Data-Parallelism and NESL NESL The Performance Model Examples of Parallel Algorithms Primes Sparse Matrix Multiplication Planar Convex-Hull Three Other Algorithms Summary Acknowledgements References Related information The NESL page includes Documentation and papers on NESL A description of how to install NESL Other algorithms . An online tutorial . Some animations of parallel algo Read More Go to Site SC97 Tutorial on Linear Algebra Algorithms and Software for Large Scientific Problems Votes:0 Slide 1 of 51 SC97 Tutorial on Linear Algebra Algorithms and Software for Large Scientific Problems Jack Dongarra, U of Tennessee and ORNL Iain Duff, Rutherford-Appleton Lab Danny Sorensen, Rice University Henk van der Vorst, Utrecht University --> Read More Go to Site services Votes:0 Services References News Contacts and CVs About us Key markets Pulp and Paper Panelboard Energy Automation and Process control Products Controller Series Predictor Series Multisimplex -Pricing information Unscrambler Download LubeRight Key application fields Process Optimization Environment Laboratories Support FAQ Ordering Distributors Partners Links Search Sponsor children A live demonstration of the basic and modified simplex algorithms Below is a live demonstration of the basic and modified simplex algorithms in two dimensions. Click with the mouse pointer somewhere on the Java applet area and watch how the simplex, a triangle in two dimensions, moves to the target (optimum) step-by-step. Your browswer is without Java support. Please upgrade your browser, and/or enable Java support! Fu Read More Go to Site SGI - MLC++: Home Page Votes:0 SGI Home How to Buy About SGI Worldwide Products & Services | Industry Solutions | Support & Downloads | Developers Home Products & Services High-Performance Computing MLC++ Legal Issues Documentation Utilities Tree Visualizer History Source Code Environment/ Standards MLC++ MLC++ is a library of C++ classes for supervised machine learning. The MLC++ utilities were created using the library. MLC++ (up to version 1.3.X) was developed at Stanford University and was public domain; that version is still distributed as such by SGI. SGI MLC++ (V2.0 and higher) includes improvements to MLC++. These improvements are research domain only and are available in both source and object code formats through this web site. SGI MLC++ is used in SGI's MineSet product as the main engine for the s Read More Go to Site Solving Rubik's Cube Using the Bestfast Algorithm and Profile tables Votes:0 Solving R U B I K ' S C U B E USING THE "BESTFAST" SEARCH ALGORITHM AND "PROFILE" TABLES A Prolog program and demonstration of an efficient heuristic search method by David Lee Winston Miller Selected as the Geek Site of the Day . (Reviewed in the Ziff-Davis magazine and received "Four Stars", Voume 2, Issue 4, April 1997. Also reviewed online at http://www.underground-online.com/webguide/ ) -- Please don't miss the last half of my home page or CLICK HERE for one of my favorite unrelated pages! " . . . efficient programs can be developed that automatically generate profile tables (and solutions) when given most any problem involving a definable goal and state space." Note: This project was originally completed for Dr. Jorge Novillo 's graduate level Read More Go to Site Sorting Algorithms Demo Votes:0 Sorting Algorithms We all know that Quicksort is one of the fastest algorithms for sorting. It's not often, however, that we get a chance to see exactly how fast Quicksort really is. The following applets chart the progress of several common sorting algorithms while sorting an array of data using in-place algorithms. This means that the algorithms do not allocate additional storage to hold temporary results: they sort the data in place. (This is inspired by the algorithm animation work at Brown University and the video Sorting out Sorting By Ronald Baecker from the University of Toronto (circa 1970!).) Some of these sorts are very stupid or very slow and should not be used in code. The use of Bubblesort is deprecated. So don't use Bubblesort! Also, don't use Swapsort! It is only a demonstr Read More Go to Site Sorting Algorithms Demo Votes:0 Bubble Sort (by James Gosling and Jason Harrison) Insertion Sort (by Jason Harrison) Quick Sort (by James Gosling) Fast Quick Sort (by Denis Ahrens) Read More Go to Site Sorting and Searching Algorithms Votes:0 Sorting and Searching Algorithms Read More Go to Site Systems Biophysics - Research - Self-Organizing Networks - DemoGNG Votes:0 DemoGNG (Version 1.5) Home "> SysBio "> Research "> Networks "> DemoGNG The Institute ¤ People ¤ Courses ¤ Graduate study ¤ Events ¤ Directions ¤ Search ¤ FTP Server Theoretical Biology Systems Biophysics ¤ People ¤ Publications ¤ Research ¤ Diploma Theses ¤ Contact (Please wait while loading ca. 122 KByte class-code.) DemoGNG , a Java applet, implements several methods related to competitive learning. It is possible to experiment with the methods using various data distributions and observe the learning process. A common terminology is used to make it easy to compare one method to the other. Your browser does not support Java applets. Authors: Hartmut S. Loos Bernd Fritzke Java Code Model Description Manual Hopefully, the experimentation with the models will increase the intuitive underst Read More Go to Site The ADATE System Votes:0 Automatic Design of Algorithms Through Evolution Automatic Design of Algorithms Through Evolution (ADATE) is a system for automatic programming i.e., inductive inference of algorithms. ADATE can automatically generate non-trivial and novel algorithms. Algorithms are generated through large scale combinatorial search that employs sophisticated program transformations. Some Selected ADATE Publications Reference [2] in the list below gives an overview of ADATE. For the time being, the best source of information about the internal details of the ADATE system is [1] which is an edited version of my Dr. Scient. thesis. J. R. Olsson, Inductive functional programming using incremental program transformation and Execution of logic programs by iterative-deepening A* SLD-tree search , Research report Read More Go to Site The Condensation Algorithm Home Page Votes:0 The Condensation Algorithm Background Tracking objects through highly cluttered scenes is difficult. We believe that for tracking to be robust when following agile moving objects, in the presence of dense background clutter, probabilistic algorithms are essential. Previous algorithms, for example the Kalman filter, have been limited in the range of probability distributions they represent. We have developed a new algorithm, the Condensation algorithm ( Con ditional Dens ity Propag ation ) which allows quite general representations of probability. Experimental results show that this increased generality does indeed lead to a marked improvement in tracking performance. In addition to permitting high-quality tracking in clutter, the simplicity of the Condensation algorithm also allows the use Read More Go to Site The NN learning algorithm benchmarking page Votes:0 Benchmarking of learning algorithms information repository page Abstract: Proper benchmarking of (neural network and other) learning architectures is a prerequisite for orderly progress in this field. In many published papers deficiencies can be observed in the benchmarking that is performed. A workshop about NN benchmarking at NIPS*95 addressed the status quo of benchmarking, common errors and how to avoid them, currently existing benchmark collections, and, most prominently, a new benchmarking facility including a results database. This page contains pointers to written versions or slides of most of the talks given at the workshop plus some related material. The page is intended to be a repository for such information to be used as a reference by researchers in the field. Note that most Read More Go to Site The Stony Brook Algorithm Repository Votes:0 The Stony Brook Algorithm Repository The Stony Brook Algorithm Repository Steven S. Skiena Department of Computer Science State University of New York Stony Brook, NY 11794-4400 This WWW page is intended to serve as a comprehensive collection of algorithm implementations for over seventy of the most fundamental problems in combinatorial algorithms. The problem taxonomy, implementations, and supporting material are all drawn from my book The Algorithm Design Manual . Since the practical person is more often looking for a program than an algorithm, we provide pointers to solid implementations of useful algorithms, when they are available. Because of the volatility of the WWW, we provide local copies for many of the implementations. We encourage you to get them from the original sites instead Read More Go to Site Understanding and Implementing Votes:0 the Technology Interface / Spring98 Understanding and Implementing the Algorithm Used for Adding BCD Numbers By &copy Jerome Tapper, 1998 jtapper@coe.neu.edu Northeastern University School of Engineering Technology Boston, Massachusetts ABSTRACT Real numbering systems are characterized by the fact that they can be manipulated by the four basic arithmetic operations of addition, subtraction, multiplication, and division. Coded numbers on the other hand are codes of some form that represent other elements. For example, a secret coded message is simply gibberish until it is "decoded" which would then make sense to the reader. Since codes, in this case numerical codes, are not numbering systems themselves, they do not exhibit the ability to perform arithmetic operations. Decimal numb Read More Go to Site Visualizing Geometric Algorithms Votes:0 This is an award winning page StudyWeb Visualizing Geometric Algorithms - State of the Art David Dobkin Department of Computer Science Princeton University Princeton, NJ 08540 dpd@cs.princeton.edu Abstract: The visual nature of geometry makes it a natural area where visualization can be an effective tool in communicating ideas. This is enhanced by the observation that much of the action in computational geometry occurs in 2 and 3 dimensions, where visualization is highly plausible. Given these observations, it is not surprising that there has been noticeable progress during the past few years in the production of visualizations of geometric algorithms and concepts. There is every reason to believe that this will continue and even accelerate in the future. In this note, I briefly survey the Read More Go to Site Workshop on Scheme: Some familiar algorithms Votes:0 Summing a collection of numbers Computing factorials Generating the Fibonacci sequence Finding the greatest common divisor by Euclid's algorithm Raising a number to a large integer power Factoring integers The fast Fourier transform Merging sorted lists Merge sorting Evaluating unsigned integer numerals Selective tallying Computing sines Computing square roots by Newton's method Swapping values Reversing the elements of a vector Tallying by category Removing duplicates from a list Partitioning a vector Finding the k th least element of a vector Finding the longest monotone subsequence of a sequence Gaussian elimination Stacks Insertion sorting Selection sorting Sorting by Shell's algorithm Quicksort Binary search Hash searching Projects String matching Huffman coding Sets and relations Red Read More Go to Site

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