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    Genetic Algorithm

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    January 2010 A Secure Steganography Method based on Genetic Algorithm Shen Wang‚ Bian Yang and Xiamu Niu School of Computer Science and Technology Harbin Institute of Technology 150080‚ Harbin‚ China shen.wang@ict.hit.edu.cn; bian.yang@ict.hit.edu.cn; xiamu.niu@hit.edu.cn Received April 2009; revised August 2009 Abstract. With the extensive application of steganography‚ it is challenged by steganalysis. The most notable steganalysis algorithm is the RS attack which detects the steg-message by

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    al.1997 describes a combined genetic algorithm and slicing approach for floorplan area optimization during the early stage of integrated circuit design. It applies a partition procedure to reduce the complexity routing problem. Genetic Algorithm (GA) is wide applied in almost any field‚ including solving FLP. Tam 1992 introduced the coding of layouts as a string of characters of finite length and used a fixed slicing tree structure defined by a clustering algorithm to represent a layout as a chromosome

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    Dynamic Timetabling using Reactive Resource. Malaysia. Norberciak‚ M. (2006). Universal Method for Timetable Construction based on Evolutionary Approach. World Academy of Science. Soolmaz Massoodian‚ A. E. (February 2008). Timetabling‚ A Hybrid Genetic Algorithm for Curriculum Based Course.

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    Introduction to Genetic Algorithms S.N.Sivanandam · S.N.Deepa Introduction to Genetic Algorithms With 193 Figures and 13 Tables Authors S.N.Sivanandam Professor and Head Dept. of Computer Science and Engineering PSG College of Technology Coimbatore - 641 004 TN‚ India S.N.Deepa Ph.D Scholar Dept. of Computer Science and Engineering PSG College of Technology Coimbatore - 641 004 TN‚ India Library of Congress Control Number: 2007930221 ISBN 978-3-540-73189-4 Springer Berlin Heidelberg

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    learning methods‚ and etc. In this project‚ genetic algorithm will be used to solve this problem by using GAlib package. Genetic Algorithms are adaptive methods which may be used to solve search and optimization problems. They are based on the genetic processes of biological organisms. Over many generations‚ natural populations evolve according to the principles of natural selection and "survival of the fittest". By mimicking this process‚ genetic algorithms are able to "evolve" solutions to real world

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    efficient operation of both primary and cognitive users. In this paper‚ an algorithm is used to dynamically control transmission power‚ which is capable of achieving reasonably good solutions fast enough in order to guarantee an acceptable level of performance for CU without degrading the performance of primary user(s). Genetic Algorithm is used to enhance the convergence time. Keywords: Cognitive radio‚ Genetic Algorithm‚ Power allocation‚ Quality of Service. I. INTRODUCTION The recent rapid

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    Algorithm

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    INFORMATION TECHNOLOGY ASSIGNMENT ON ALGORITHM Done by Densil Hamilton INTRODUCTION This Assignment was done to show the methods of algorithm. It outlines the meaning of algorithm and steps to be carried out to complete a give problem. Examples were also shown for the methods of representing algorithm. What is an Algorithm? An algorithm consists of a set of explicit and unambiguous finite steps which‚ when carried out for a given set of initial conditions‚ produce the corresponding

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    Algorithm

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    Algorithm is a list of instructions for carrying out some process step by step Flowchart is a diagram representing the logical sequence in which a combination of steps or operations is to be performed Types of Flowcharts Program Flowchart – describes graphically in detail the logical operations and steps within a program and sequence in which these steps are to be executed for the transformation of data to produce the needed output System Flowchart – is a graphic representation of the

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    the papers studied 3 3.1. Minutiae recognition system based on genetic algorithms 3 3.2. Fingerprint matching algorithms for integrated circuit cards 4 3.3. Algorithm based on tree comparisons using ratio of relational distances. 5 3. Comparative account of the papers studied 6 4. Conclusion 6 5. References 7 A SURVEY ON FINGERPRINT VERIFICATION ALGORITHMS Ms. Tasleem Fathima J ABSTRACT Fingerprints are the most widely used

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    Genetic Programming

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    GENETIC PROGRAMMING: AN INTRODUCTION AND SURVEY OF APPLICATIONS M.J. Willis*‚ H.G Hiden*‚ P. Marenbach+‚ B. McKay* and G.A. Montague* * Symbolic Optimisation Research Group (SORG) Dept. of Chemical and Process Engineering University of Newcastle upon Tyne NE1 7RU‚ UK + Institute of Control Engineering Darmstadt University of Technology Landgraf-Georg-Strasse 4 D-64283 Darmstadt‚ Germany {Mark.Willis‚ H.G.Hiden‚ Ben.McKay‚ Gary.Montague} @ncl.ac.uk http://lorien.ncl.ac.uk/sorg mali@rt.e-technik

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