...Genetic modification is natural selection on steroids. Plants can be breed to Embryos can receive genetically modifying injections throughout the pregnancy, or can be injected into the egg and placed in a surrogate mother. The goal of GMO’s is to enhance a particular feature e.g., size, taste, color, or immunity. Sometimes one change in the genome leads to unintentional side-effects. [1] I recommend the film, Genetic Roulette. It enlightens even the most skeptical viewer of the GMO’s environmental and health concerns. For example are bovine sent to slaughter are usually treated with growth hormones throughout their life. In some cases, the growth hormones immobilize the animal from its sheer weight. The main concern however is not indirect growth hormones, but side effects from herbicides. As ludicrous as it sounds, genetically modified plants have earned insecticidal properties. After an insect eats part of the plant, the insecticide will cause the rupture the insect’s stomach and effectively killing it. If people eat large amounts of insecticide treated plants, the big question is whether large dosages can also cause human health risks. The film notes a correction between leaky gut syndrome and GMOs with insecticides. [2] Unfortunately, this would come across as junk science or zealotry. [3] Thus, economic...
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... Xi’an Univ.of arch.﹠Tech., Xi’an 710055, China; a 15829690177@163.com, b631931577@qq.com Keywords: Building information modeling; Construction project; Time-cost-quality trade-off optimization; Genetic algorithm. Abstract. With the development of BIM technology, BIM provides a new direction for the project management of three objectives. Based on the current situation of the project time cost-optimized mass balance studies, pointing out the implementation mechanism of achieving the trade-off of time-cost-quality in construction project based on BIM mainly oriented components of the BIM model based; the use of Structured Query Language query statistics data information needs combined bill of quantities calculation method for the specification, preliminary engineering scale generation; establishment of Project relations system model. In the process duration is subject, for the construction of uncertainty factors such as interest rates and prices, through the establishment of quality, cost and schedule function, the establishment of quality balanced schedule cost optimization model, using genetic algorithm model of the optimal solution are obtained. With BIM case finally proves the rationality of the model and the effectiveness of the proposed genetic. 1. Introduction Balance between the three objectives of the optimization problem has also been a research scholar in the field of project management focus at home and abroad, as early as 2005 EI-Rays on...
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...Classification Using Genetic Algorithm N. Suguna1, and Dr. K. Thanushkodi2 1 Professor in Computer Science and Engg, Akshaya College of Engineering and Technology, Coimbatore, Tamil Nadu, India. 2 Director, Akshaya College of Engineering and Technology, Coimbatore, Tamil Nadu, India. Abstract k-Nearest Neighbor (KNN) is one of the most popular algorithms for pattern recognition. Many researchers have found that the KNN algorithm accomplishes very good performance in their experiments on different data sets. The traditional KNN text classification algorithm has three limitations: (i) calculation complexity due to the usage of all the training samples for classification, (ii) the performance is solely dependent on the training set, and (iii) there is no weight difference between samples. To overcome these limitations, an improved version of KNN is proposed in this paper. Genetic Algorithm (GA) is combined with KNN to improve its classification performance. Instead of considering all the training samples and taking k-neighbors, the GA is employed to take k-neighbors straightaway and then calculate the distance to classify the test samples. Before classification, initially the reduced feature set is received from a novel method based on Rough set theory hybrid with Bee Colony Optimization (BCO) as we have discussed in our earlier work. The performance is compared with the traditional KNN, CART and SVM classifiers. Keywords: k-Nearest Neighbor, Genetic Algorithm, Support...
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...Introduction TSP (Travelling salesman problem) is an optimization problem that it is difficult to solve using classical methods. Different Genetic Algorithm (GA) have been right to solve the TSP each with advantages and disadvantages (Davis, 2005) In this research paper, I highlight a new algorithm by merging different genetic Algorithm results to the better solution for TSP. In amalgam algorithm, appropriateness of algorithm and traveled distance for TSP has been considered. Results obtained suggest that it does not quickly establish in the local optimum and enjoys a good speed for an inclusive answer (Fogel, 2010). New methods such as GAs, refrigeration algorithms, Artificial Neural Networks, and ACO (Ant Colony Optimization) to solve TSP problem, in recent past have been suggested. Both ACO and GAs is centered on repetitive (Goldenberg, 2005) ACO system was unfilled for the first time by Dorigoat al. to solve TSP. In ACO algorithms, people work together to find the solution. In collective intelligence algorithms, it uses the real life of creatures without putting in consideration the complex mechanisms in run their day to day life in all aspects as best as possible. GA is an iterative procedure that contains a population of individuals or chromosomes. Coding of randomly or heuristic by a string of symbols as a gene in possible solution is done. All possible solution in this search space is examined. When search space is large, GAs usually are used. People can select an...
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...Chapter 1 Discrete Probability Distributions 1.1 Simulation of Discrete Probabilities Probability In this chapter, we shall first consider chance experiments with a finite number of possible outcomes ω1 , ω2 , . . . , ωn . For example, we roll a die and the possible outcomes are 1, 2, 3, 4, 5, 6 corresponding to the side that turns up. We toss a coin with possible outcomes H (heads) and T (tails). It is frequently useful to be able to refer to an outcome of an experiment. For example, we might want to write the mathematical expression which gives the sum of four rolls of a die. To do this, we could let Xi , i = 1, 2, 3, 4, represent the values of the outcomes of the four rolls, and then we could write the expression X 1 + X 2 + X 3 + X4 for the sum of the four rolls. The Xi ’s are called random variables. A random variable is simply an expression whose value is the outcome of a particular experiment. Just as in the case of other types of variables in mathematics, random variables can take on different values. Let X be the random variable which represents the roll of one die. We shall assign probabilities to the possible outcomes of this experiment. We do this by assigning to each outcome ωj a nonnegative number m(ωj ) in such a way that m(ω1 ) + m(ω2 ) + · · · + m(ω6 ) = 1 . The function m(ωj ) is called the distribution function of the random variable X. For the case of the roll of the die we would assign equal probabilities or probabilities 1/6 to each of the outcomes....
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...robinson@earthopensource.org June 2012 Disclaimer The views and opinions expressed in this paper, or otherwise published by EOS, are those of the authors and do not represent the official policy, position, or views of other organizations, universities, companies, or corporations that the authors may be affiliated with. GMO Myths and Truths 2 About the authors Michael Antoniou, PhD is reader in molecular genetics and head, Gene Expression and Therapy Group, King’s Cols: lege London School of Medicine, London, UK. He has 28 years’ experience in the use of genetic engineering technology investigating gene organisation and control, with over 40 peer reviewed publications of original work, and holds inventor status on a number of gene expression biotechnology patents. Dr Antoniou has a large network of collaborators in industry and academia who are making use of his discoveries in gene control mechanisms for the production of research, diagnostic and therapeutic products and safe and efficacious human somatic gene therapy for inherited and acquired genetic disorders. Claire Robinson, MPhil, is research director at Earth Open Source. She has a background in investigative reporting and the communication of topics relating to public health, science and policy, and the environment. She is an editor at GMWatch (www.gmwatch.org), a public information service...
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...Natural Computing Series Series Editors: G. Rozenberg Th. Bäck A.E. Eiben J.N. Kok H.P. Spaink Leiden Center for Natural Computing Advisory Board: S. Amari G. Brassard K.A. De Jong C.C.A.M. Gielen T. Head L. Kari L. Landweber T. Martinetz Z. Michalewicz M.C. Mozer E. Oja G. P˘ un J. Reif H. Rubin A. Salomaa M. Schoenauer H.-P. Schwefel C. Torras a D. Whitley E. Winfree J.M. Zurada For further volumes: www.springer.com/series/4190 Franz Rothlauf Design of Modern Heuristics Principles and Application Prof. Dr. Franz Rothlauf Chair of Information Systems and Business Administration Johannes Gutenberg Universität Mainz Gutenberg School of Management and Economics Jakob-Welder-Weg 9 55099 Mainz Germany rothlauf@uni-mainz.de Series Editors G. Rozenberg (Managing Editor) rozenber@liacs.nl Th. Bäck, J.N. Kok, H.P. Spaink Leiden Center for Natural Computing Leiden University Niels Bohrweg 1 2333 CA Leiden, The Netherlands A.E. Eiben Vrije Universiteit Amsterdam The Netherlands ISSN 1619-7127 Natural Computing Series ISBN 978-3-540-72961-7 e-ISBN 978-3-540-72962-4 DOI 10.1007/978-3-540-72962-4 Springer Heidelberg Dordrecht London New York Library of Congress Control Number: 2011934137 ACM Computing Classification (1998): I.2.8, G.1.6, H.4.2 © Springer-Verlag Berlin Heidelberg 2011 This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations...
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...No Paper Code 1. 2. 3. 4. 5. 6. CSE411 CSE461 CSE412 CSE462 CSE414 CSE464 Subject Title Scheme of Teaching L 3 0 3 0 3 0 T 1 0 1 0 1 0 P 0 3 0 3 0 3 Hours 4 3 4 3 4 3 Credit 4 2 4 2 4 2 University External Marks 50 50 50 CSE361 CSE313 CSE363 AS301 EC316 EC366 EC317 EC367 Data Structures (Practical) Peripheral Devices & Interfaces Hardware Lab (Practical) Engineering Mathematics – III Digital Electronics Digital Electronics (Practical) Microprocessors Microprocessors (Practical) 0 3 0 3 3 0 3 0 15 0 1 0 1 1 0 1 0 5 3 0 2 0 0 2 0 2 09 3 4 2 4 4 2 4 2 29 2 4 1 4 4 1 4 1 25 50 50 50 50 250 Internal Total Sessional Marks 50 50 50 50 50 50 50 50 50 450 100 50 100 50 100 100 50 100 50 700 7. 8. Total ASC405 CSE 415 Analysis & Design of Algorithms Analysis & Design of Algorithms (Practical) Database Management System Database Management System (Practical) Object Oriented Programming Object Oriented Programming (Practical) Cyber Law & IPR Computer Architecture & Organization Internal Total Sessional Marks 50 100 50 50 50 50 50 50 100 50 100 50 3 3 15 0 1 4 0 0 9 3 4 28 3 4 25 50 50 250 50 50 400 100 100 650 2 Scheme of Examination of B.E. in Computer Science & Engineering Third Year - Fifth Semester Sr. Paper Subject Title Scheme of Teaching Univesity Internal Sessional Code External L T P Hou Credit Marks Total Marks rs s 1. CSE511 Operating System 3 1 0 4 4 50 50...
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...[pic] Narcissistic And Psychopathic Leaders 1st EDITION Sam Vaknin, Ph.D. Τηε “υτηορ ισ ΝΟΤ α Μενταλ Ηεαλτη Προφεσσιοναλ. Τηε “υτηορ ισ χερτιφιεδ ιν Χουνσελλινγ Τεχηνιθυεσ. Εδιτινγ ανδ Δεσιγν: Λιδιϕα Ρανγελοϖσκα “ Ναρχισσυσ Πυβλιχατιονσ Ιμπριντ Πραγυε & Σκοπϕε 2009 ♥ 2009 Χοπψριγητ Λιδιϕα Ρανγελοϖσκα Ναρχισσυσ Πυβλιχατιονσ “λλ ριγητσ ρεσερϖεδ. Τηισ βοοκ, ορ ανψ παρτ τηερεοφ, μαψ νοτ βε υσεδ ορ ρεπροδυχεδ ιν ανψ μαννερ ωιτηουτ ωριττεν περμισσιον φρομ: Λιδιϕα Ρανγελοϖσκα ? ωριτε το: palma@unet.com.mk ορ το vaksam@mt.net.mk “λλ ριγητσ φορ τηισ βοοκ αρε φορ σαλε. Λιτεραρψ αγεντσ ανδ πυβλισηερσ, πλεασε χονταχτ Λιδιϕα Ρανγελοϖσκα. |Το γετ ΦΡΕΕ υπδατεσ οφ τηισ βοοκ ϑΟΙΝ τηε Ναρχισσισμ Στυδψ Λιστ. | |Το ϑΟΙΝ, ϖισιτ ουρ Ωεβ σιτεσ: | |http://www.geocities.com/vaksam/narclist.html ορ | |http://www.narcissistic-abuse.com/narclist.html ορ | |http://groups.yahoo.com/group/narcissisticabuse | ςισιτ τηε “υτηορ∍σ Ωεβ σιτε: http://samvak.tripod.com Βυψ οτηερ βοοκσ αβουτ πατηολογιχαλ ναρχισσισμ ανδ ρελατιονσηιπσ ωιτη αβυσιϖε ναρχισσιστσ ανδ πσψχηοπατησ ηερε: http://www.narcissistic-abuse.com/thebook.html Χρεατεδ βψ: Λιδιϕα Ρανγελοϖσκα, Σκοπϕε ΡΕΠΥΒΛΙΧ ΟΦ Μ“ΧΕΔΟΝΙ“ Χ Ο Ν Τ Ε Ν Τ Σ Pathological Narcissism – An Overview A Primer on Narcissism and the Narcissistic Personality Disorder...
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...Fuzzy Control Kevin M. Passino Department of Electrical Engineering The Ohio State University Stephen Yurkovich Department of Electrical Engineering The Ohio State University An Imprint of Addison-Wesley Longman, Inc. Menlo Park, California • Reading, Massachusetts Don Mills, Ontaria • Sydney • Bonn • Harlow, England • Berkeley, California • Amsterdam • Mexico City ii Assistant Editor: Laura Cheu Editorial Assistant: Royden Tonomura Senior Production Editor: Teri Hyde Marketing Manager: Rob Merino Manufacturing Supervisor: Janet Weaver Art and Design Manager: Kevin Berry Cover Design: Yvo Riezebos (technical drawing by K. Passino) Text Design: Peter Vacek Design Macro Writer: William Erik Baxter Copyeditor: Brian Jones Proofreader: Holly McLean-Aldis Copyright c 1998 Addison Wesley Longman, Inc. All rights reserved. No part of this publication may be reproduced, or stored in a database or retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America. Printed simultaneously in Canada. Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and AddisonWesley was aware of a trademark claim, the designations have been printed in initial caps or in all caps. MATLAB is a registered trademark of The MathWorks...
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...Chemistry/Physics Laboratory Workshop Physical Training-I NCC/NSO/NSS L 3 3 3 1 3 0 0 0 0 13 T 1 0 1 0 0 0 0 0 0 2 1 1 1 1 0 0 0 0 4 1 1 0 0 0 0 0 0 2 0 0 0 0 P 0 0 0 3 0 2 3 2 2 8 0 0 0 0 0 2 2 2 2 0 0 0 0 0 2 2 2 6 0 0 8 2 C 8 6 8 5 6 2 3 0 0 38 8 8 8 8 6 2 0 0 40 8 8 6 6 6 2 2 2 40 6 6 8 2 Course No EC-1101 CS-1101 MA-1102 ME-1101 PH-1101/ CH-1101 CS-1111 EE-1111 PH-1111/ CH-1111 Course Name Semester-2 Basic Electronics Introduction to Computing Mathematics-II Engineering Mechanics Physics/Chemistry Computing Laboratory Electrical Science Laboratory Physics/Chemistry Laboratory Physical Training –II NCC/NSO/NSS Semester-4 Structural Analysis-I Hydraulics Environmental Engg-I Structural Design-I Managerial Economics Engg. Geology Laboratory Hydraulics Laboratory Physical Training-IV NCC/NSO/NSS Semester-6 Structural Design-II Structural Analysis-III Foundation Engineering Transportation Engineering-II Hydrology &Flood Control Concrete Lab Structural Engineering Lab L 3 3 3 3 3 0 0 0 0 0 15 3 3 3 3 3 0 0 0 0 15 3 3 3 3 3 0 0 T 0 0 1 1 1 0 0 0 0 0 3 1 1 0 1 0 0 0 0 0 3 1 1 1 0 0 0 0 P 0 0 0 0 0 2 2 2 2 2 6 0 0 0 0 0 2 2 2 2 4 0 0 0 0 0 2 2 C 6 6 8 8 8 2 2 2 0 0 42 8 8 6 8 6 2 2 0 0 40 8 8 8 6 6 2 2 MA-1201 CE- 1201 CE -1202 CE -1203 CE-1204 CE-1211 Semester-3 Mathematics-III Building Materials and...
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...101 Option Trading Secrets Also by Kenneth R. Trester The Complete Option Player The Option Player’s Advanced Guidebook Secrets to Stock Option Success 101 Option Trading Secrets K E N N E T H R. TRESTER Institute for Options Research, Inc. Lake Tahoe, Nevada Copyright © Kenneth R. Trester 2004 All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without prior written permission of the publisher. Printed in the United States. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold with the understanding that the publisher is not engaged in rendering legal, accounting, or other professional service. If legal advice or other expert assistance is required, the services of a competent professional person should be sought. From a Declaration of Principles jointly adopted by a Committee of the American Bar Association and a Committee of Publishers. We advise all readers that it should not be assumed that present or future recommendations will be profitable or equal the performance of previous recommendations. The reader should recognize that risk is involved in any option or security investment, and they should not assume that any formula, method, chart, theory or philosophy will result in profitable results or equal past performances. This...
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...Contents Preface Acknowledgments Introduction 1 BRAIN POWER Myth #1 Most People Use Only 10% of Their Brain Power Myth #2 Some People Are Left-Brained, Others Are Right-Brained Myth #3 Extrasensory Perception (ESP) Is a Well-Established Scientific Phenomenon Myth #4 Visual Perceptions Are Accompanied by Tiny Emissions from the Eyes Myth #5 Subliminal Messages Can Persuade People to Purchase Products 2 FROM WOMB TO TOMB Myth #6 Playing Mozart’s Music to Infants Boosts Their Intelligence Myth #7 Adolescence Is Inevitably a Time of Psychological Turmoil Myth #8 Most People Experience a Midlife Crisis in | 8 Their 40s or Early 50s Myth #9 Old Age Is Typically Associated with Increased Dissatisfaction and Senility Myth #10 When Dying, People Pass through a Universal Series of Psychological Stages 3 A REMEMBRANCE OF THINGS PAST Myth #11 Human Memory Works like a Tape Recorder or Video Camera, and Accurate Events We’ve Experienced Myth #12 Hypnosis Is Useful for Retrieving Memories of Forgotten Events Myth #13 Individuals Commonly Repress the Memories of Traumatic Experiences Myth #14 Most People with Amnesia Forget All Details of Their Earlier Lives 4 TEACHING OLD DOGS NEW TRICKS Myth #15 Intelligence (IQ) Tests Are Biased against Certain Groups of People My th #16 If You’re Unsure of Your Answer When Taking a Test, It’s Best to Stick with Your Initial Hunch Myth #17 The Defining Feature of Dyslexia Is Reversing Letters Myth #18 Students Learn Best When Teaching Styles Are Matched to...
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...Chaotic Growth with the Logistic Model of P.-F. Verhulst Hugo Pastijn Department of Mathematics, Royal Military Academy B-1000 Brussels, Belgium Hugo.Pastijn@rma.ac.be Summary. Pierre-Fran¸ois Verhulst was born 200 years ago. After a short biograc phy of P.-F. Verhulst in which the link with the Royal Military Academy in Brussels is emphasized, the early history of the so-called “Logistic Model” is described. The relationship with older growth models is discussed, and the motivation of Verhulst to introduce different kinds of limited growth models is presented. The (re-)discovery of the chaotic behaviour of the discrete version of this logistic model in the late previous century is reminded. We conclude by referring to some generalizations of the logistic model, which were used to describe growth and diffusion processes in the context of technological innovation, and for which the author studied the chaotic behaviour by means of a series of computer experiments, performed in the eighties of last century by means of the then emerging “micro-computer” technology. 1 P.-F. Verhulst and the Royal Military Academy in Brussels In the year 1844, at the age of 40, when Pierre-Fran¸ois Verhulst on November c 30 presented his contribution to the “M´moires de l’Acad´mie” of the young e e Belgian nation, a paper which was published the next year in “tome XVIII” with the title: “Recherches math´matiques sur la loi d’accroissement de la e population” (mathematical investigations of the law of...
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...SAGE India website gets a makeover! Global Products Enhanced Succinct Intuitive THE Improved Interactive Smart Layout User-friendly Easy Eye-catching LEADING WORld’s LEADING Independent Professional Stay tuned in to upcoming Events and Conferences Search Navigation Feature-rich Get to know our Authors and Editors Why Publish with SAGE ? World’s LEADING Publisher and home and editors Societies authors Professional Academic LEADING Publisher Natural World’s Societies THE and LEADING Publisher Natural authors Societies Independent home editors THE Professional Natural Societies Independent authors Societies and Societies editors THE LEADING home editors Natural editors Professional Independent Academic and authors Academic Independent Publisher Academic Societies and authors Academic THE World’s THE editors Academic THE Natural LEADING THE Natural LEADING home Natural authors Natural editors authors home World’s authors THE editors authors LEADING Publisher World’s LEADING authors World’s Natural Academic editors World’s home Natural and Independent authors World’s Publisher authors World’s home Natural home LEADING Academic Academic LEADING editors Natural and Publisher editors World’s authors home Academic Professional authors Independent home LEADING Academic World’s and authors home and Academic Professionalauthors World’s editors THE LEADING Publisher authors Independent home editors Natural...
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