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Books on the topic 'Major Computer Science'

Author: Grafiati

Published: 4 June 2021

Last updated: 2 February 2022

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1

Anderson, Alastair A. The effects of microcomputer anxiety, knowledge, experience, gender and course major on performance in information systems: A study of business undergraduates in Australia. Burwood, Australia: Graduate School of Management, Deakin University, 1994.

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2

America's top computer and technical jobs: Detailed information on 112 major jobs at all levels of education and training. Indianapolis, IN: JIST Works, 2003.

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Top 100 computer and technical careers: Your complete guidebook to major jobs in many fields at all training levels. 4th ed. Indianapolis, IN: JIST Pub., 2009.

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4

Mark, Rowh, ed. Great jobs for computer science majors. 2nd ed. Chicago: VGM Career Books, 2003.

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Great jobs for computer science majors. Lincolnwood, Ill: VGM Career Horizons, 1998.

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6

Office, General Accounting. Software reuse: Major issues need to be resolved before benefits can be achieved : report to the Chairman, Subcommittee on Defense, Committee on Appropriations, House of Representatives. Washington, D.C: The Office, 1993.

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Nasdaq Market Simulation: Insights on a Major Market from the Science of Complex Adaptive Systems (Complex Systems and Interdisciplinary Science) (Complex Systems and Interdisciplinary Science). World Scientific Publishing Company, 2007.

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8

Graduate S/E enrollment rose 4% in 1983, with major gains in computer science and engineering. Washington, D.C: National Science Foundation, 1985.

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9

Abramsky, S., Dov M. Gabbay, and T. S. E. Maibaum, eds. Handbook of Logic in Computer Science: Volume 5. Algebraic and Logical Structures. Oxford University Press, 2001. http://dx.doi.org/10.1093/oso/9780198537816.001.0001.

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Logic is now widely recognized as one of the foundational disciplines of computing, and its applications reach almost every aspect of the subject, from software engineering and hardware to programming languages and AI. The Handbook of Logic in Computer Science is a multi-volume work covering all the major areas of application of logic to theoretical computer science. The handbook comprises six volumes, each containing five or six chapters giving an in-depth overview of one of the major topics in field. It is the result of many years of cooperative effort by some of the most eminent frontline researchers in the field, and will no doubt be the standard reference work in logic and theoretical computer science for years to come. Volume 5: Algebraic and Logical Structures covers all the fundamental topics of semantics in logic and computation. The extensive chapters are the result of several years of coordinated research, and each have thematic perspective. Together, they offer the reader the latest in research work, and the book will be indispensable

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10

Farr, Michael. Top 100 Computer and Technical Careers: Your Complete Guidebook to Major Jobs in Many Fields at All Training Levels (Top 100 Computer and Technical Careers). 3rd ed. JIST Works, 2006.

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11

Farr, J. Michael. America's Top 101 Computer and Technical Jobs: Detailed Information on Major Jobs at All Levels of Education and Training (America's Top 101 Computer and Technical Jobs). 2nd ed. Jist Publishing, 2004.

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12

Digital Document Processing: Major Directions and Recent Advances (Advances in Pattern Recognition). Springer, 2006.

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13

Bokstein, Boris S., Mikhail I. Mendelev, and David J. Srolovitz. Thermodynamics and Kinetics in Materials Science. Oxford University Press, 2005. http://dx.doi.org/10.1093/oso/9780198528036.001.0001.

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This text presents a concise and thorough introduction to the main concepts and practical applications of thermodynamics and kinetics in materials science. It is designed with two types of uses in mind: firstly for one or two semester university course for mid- to - upper level undergraduate or first year graduate students in a materials-science-oriented discipline and secondly for individuals who want to study the materials on their own. The following major topics are discussed: basic laws of classical and irreversible thermodynamics, phase equilibria, theory of solutions, chemical reaction thermodynamics and kinetics, surface phenomena, stressed systems, diffusion and statistical thermodynamics. A large number of example problems with detailed solutions are included as well as accompanying computer-based self-tests, consisting of over 400 questions and 2000 answers with hints for students. Computer-based laboratories are provided, in which a laboratory problem is posed and the experiment described. The student can "perform" the experiments and change the laboratory conditions to obtain the data required for meeting the laboratory objective. Each "laboratory" is augmented with background material to aid analysis of the experimental results.

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14

(Japan), Sangyō Kōzō Shingikai, ed. Unfair trade, the complete report on unfair trade policies by Japan's major trading partners. Commack, N.Y: Nova Science Publishers, Inc., 1993.

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15

Great Jobs for Computer Science Majors. New York: McGraw-Hill, 2002.

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16

Steane, Andrew. The Structure of Science, Part 1. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198824589.003.0003.

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The first major theme of the book is introduced. This is that science does not present a ladder or tower of explanation, but a network of mutually interacting and informing ideas. The digital computer is invoked to introduce the concept of low-level and high-level language. The role of symmetry and symmetry principles in physics is discussed at length. It is argued, in agreement with Anderson, that symmetry is central to fundamental physics, but, more importantly, it is shown that what symmetry offers is a subtle constraining influence that is not the same as cause and effect, but is nevertheless central to the concept of explanation and understanding. It is argued that the laws of thermodynamics and the laws of particle physics are in a relationship of mutual consistency with neither able to render the other superfluous. Numerous examples are invoked.

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17

Goldberg, Jan. Great Jobs for Computer Science Majors 2nd Ed. 2nd ed. McGraw-Hill, 2002.

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18

Goldberg, Jan. Great Jobs for Computer Science Majors 2nd Ed. McGraw-Hill, 2002.

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19

(Firm), Peterson's, ed. Peterson's job opportunities for engineering and computer science majors. Princeton, N.J: Peterson's, 1998.

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20

Peterson's Job Opportunities for Engineering and Computer Science Majors: 1999 (Peterson's Job Opportunities : Engineering and Computer Science). Petersons, 1998.

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21

Peterson's Job Opportunities for Engineering and Computer Science Majors, 1998. Petersons, 1997.

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22

(Editor), Karen Hansen, ed. Peterson's Job Opportunities for Engineering and Computer Science Majors: 1998 (Annual). Petersons, 1997.

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23

Salzman, Harold, and Stephen R. Rosenthal. Software by Design. Oxford University Press, 1994. http://dx.doi.org/10.1093/oso/9780195083408.001.0001.

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As computers become more and more integral to business and other organizational operations around the world, software design must increasingly meet the social demands of the workplace. This book provides an informative, cogent examination of how various social factors--such as organizational structure, workplace relations, and market conditions--together shape software developers' technical design decisions. Through a survey of major software companies and in-depth case studies of the banking, hospital, and equipment field service industries, the authors identify factors that influence specific design strategies and examine the significant consequences that engineering decisions have on users' work, workplace quality of life, and opportunities for autonomy and skill development. The book concludes with a chapter devoted to exploring how a progressive design approach can improve both the performance and working conditions of an organization. By providing an important empirical study of the social construction of technology, the authors offer an insightful understanding of the challenges inherent in effective software design. The book will appeal to professionals and students in software design, information systems management, computer science, and the sociology of work and technology.

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24

United States. General Accounting Office., United States. Congress. House. Committee on Government Reform and Oversight. Subcommittee on Government Management, Information, and Technology., and United States. Congress. House. Committee on Science. Subcommittee on Technology., eds. Year 2000 computing crisis: Strong leadership and effective public/private cooperation needed to avoid major disruptions : statement of Gene L. Dodaro, Assistant Comptroller General, Accounting and Information Management Division, before the Subcommittee on Government Management, Information and Technology, Committee on Government Reform and Oversight, and the Subcommittee on Technology, Committee on Science, House of Representatives. Washington, D.C: The Office, 1998.

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25

Traditions of Systems Theory: Major Figures and Contemporary Developments. Taylor & Francis Group, 2017.

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26

Traditions of Systems Theory: Major Figures and Contemporary Developments. Taylor & Francis Group, 2013.

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27

United States. Dept. of the Army, ed. CREST, Career Related Experience in Science & Technology Program: For undergraduate & graduate students with majors in engineering, mathematics, computer science. [Washington, D.C.?]: Dept. of the Army, 1997.

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28

United States. Dept. of the Army, ed. CREST, Career Related Experience in Science & Technology Program: For undergraduate & graduate students with majors in engineering, mathematics, computer science. [Washington, D.C.?]: Dept. of the Army, 1997.

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29

Job Opps for Eng & Comp Sci Majors 00 (Peterson's Job Opportunities : Engineering and Computer Science). 2nd ed. Peterson's, 1999.

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30

Levitin, Anany, and Maria Levitin. Algorithmic Puzzles. Oxford University Press, 2011. http://dx.doi.org/10.1093/oso/9780199740444.001.0001.

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While many think of algorithms as specific to computer science, at its core algorithmic thinking is defined by the use of analytical logic to solve problems. This logic extends far beyond the realm of computer science and into the wide and entertaining world of puzzles. In Algorithmic Puzzles, Anany and Maria Levitin use many classic brainteasers as well as newer examples from job interviews with major corporations to show readers how to apply analytical thinking to solve puzzles requiring well-defined procedures. The book's unique collection of puzzles is supplemented with carefully developed tutorials on algorithm design strategies and analysis techniques intended to walk the reader step-by-step through the various approaches to algorithmic problem solving. Mastery of these strategies--exhaustive search, backtracking, and divide-and-conquer, among others--will aid the reader in solving not only the puzzles contained in this book, but also others encountered in interviews, puzzle collections, and throughout everyday life. Each of the 150 puzzles contains hints and solutions, along with commentary on the puzzle's origins and solution methods. The only book of its kind, Algorithmic Puzzles houses puzzles for all skill levels. Readers with only middle school mathematics will develop their algorithmic problem-solving skills through puzzles at the elementary level, while seasoned puzzle solvers will enjoy the challenge of thinking through more difficult puzzles.

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31

Gabbay, Dov M., C. J. Hogger, and J. A. Robinson, eds. Handbook of Logic in Artificial Intelligence and Logic Programming: Volume 5: Logic Programming. Oxford University Press, 1998. http://dx.doi.org/10.1093/oso/9780198537922.001.0001.

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Logic is now widely recognized as one of the foundational disciplines of computing and has applications in virtually all aspects of the subject, from software engineering and hardware to programming languages and artificial intelligence. The Handbook of Logic in Artificial Intelligence and its companion The Handbook of Logic in Computer Science were created in response to the growing need for an in-depth survey of these applications. This handbook comprises five volumes, each an in-depth overview of one of the major topics in this area. The result of years of cooperative effort by internationally renowned researchers, it will be the standard reference work in AI for years to come. Volume 5 focuses on logic programming. The chapters, which in many cases are of monograph length and scope, emphasize possible unifying themes.

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32

Monge, Peter R., and Noshir Contractor. Theories of Communication Networks. Oxford University Press, 2003. http://dx.doi.org/10.1093/oso/9780195160369.001.0001.

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To date, most network research contains one or more of five major problems. First, it tends to be atheoretical, ignoring the various social theories that contain network implications. Second, it explores single levels of analysis rather than the multiple levels out of which most networks are comprised. Third, network analysis has employed very little the insights from contemporary complex systems analysis and computer simulations. Foruth, it typically uses descriptive rather than inferential statistics, thus robbing it of the ability to make claims about the larger universe of networks. Finally, almost all the research is static and cross-sectional rather than dynamic. Theories of Communication Networks presents solutions to all five problems. The authors develop a multitheoretical model that relates different social science theories with different network properties. This model is multilevel, providing a network decomposition that applies the various social theories to all network levels: individuals, dyads, triples, groups, and the entire network. The book then establishes a model from the perspective of complex adaptive systems and demonstrates how to use Blanche, an agent-based network computer simulation environment, to generate and test network theories and hypotheses. It presents recent developments in network statistical analysis, the p* family, which provides a basis for valid multilevel statistical inferences regarding networks. Finally, it shows how to relate communication networks to other networks, thus providing the basis in conjunction with computer simulations to study the emergence of dynamic organizational networks.

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33

Ortloff, Charles R. Water Engineering in the Ancient World. Oxford University Press, 2009. http://dx.doi.org/10.1093/oso/9780199239092.001.0001.

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Charles Ortloff provides a new perspective on archaeological studies of the urban and agricultural water supply and distribution systems of the major ancient civilizations of South America, the Middle East, and South-East Asia, by using modern computer analysis methods to extract the true hydraulic/hydrological knowledge base available to these peoples. His many new revelations about the capabilities and innovations of ancient water engineers force us to re-evaluate what was known and practised in the hydraulic sciences in ancient times. Given our current concerns about global warming and its effect on economic stability, it is fascinating to observe how some ancient civilizations successfully coped with major climate change events by devising defensive agricultural survival strategies, while others, which did not innovate, failed to survive.

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34

Asudeh, Ash, and Gianluca Giorgolo. Enriched Meanings. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198847854.001.0001.

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This book presents a theory of enriched meanings for natural language interpretation. Certain expressions that exhibit complex effects at the semantics/pragmatics boundary live in an enriched meaning space while others live in a more basic meaning space. These basic meanings are mapped to enriched meanings just when required compositionally, which avoids generalizing meanings to the worst case. The theory is captured formally using monads, a concept from category theory. Monads are also prominent in functional programming and have been successfully used in the semantics of programming languages to characterize certain classes of computation. They are used here to model certain challenging linguistic computations at the semantics/pragmatics boundary. Part I presents some background on the semantics/pragmatics boundary, informally presents the theory of enriched meanings, reviews the linguistic phenomena of interest, and provides the necessary background on category theory and monads. Part II provides novel compositional analyses of the following phenomena: conventional implicature, substitution puzzles, and conjunction fallacies. Part III explores the prospects of combining monads, with particular reference to these three cases. The authors show that the compositional properties of monads model linguistic intuitions about these cases particularly well. The book is an interdisciplinary contribution to Cognitive Science: These phenomena cross not just the boundary between semantics and pragmatics, but also disciplinary boundaries between Linguistics, Philosophy and Psychology, three of the major branches of Cognitive Science, and are here analyzed with techniques that are prominent in Computer Science, a fourth major branch. A number of exercises are provided to aid understanding, as well as a set of computational tools (available at the book's website), which also allow readers to develop their own analyses of enriched meanings.

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35

Boden, Margaret A. 1. What is artificial intelligence? Oxford University Press, 2018. http://dx.doi.org/10.1093/actrade/9780199602919.003.0001.

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Artificial intelligence (AI) seeks to make computers do the sorts of things that minds can do, which involves psychological skills such as perception, association, prediction, planning, and motor control. Intelligence is a richly structured space of diverse information-processing capacities. Accordingly, AI uses many different techniques, addressing many different tasks. ‘What is Artificial Intelligence?’ explains the two main aims of AI: one being technological and the other scientific. It looks at AI’s influence on the life sciences and philosophy. Can any AI system possess real intelligence, creativity, or life? It also considers how AI began, virtual machines, the major types of AI, and cybernetics.

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36

Alger, Bradley E. Defense of the Scientific Hypothesis. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780190881481.001.0001.

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This book explains and defends the scientific hypothesis. Explanation is needed to counteract the misinformation and misunderstanding about the hypothesis that even scientists have concerning its nature and place in the tapestry of modern science. A survey revealed that most biological scientists receive little or no formal training in scientific thinking. Defense is needed because the hypothesis is under attack by critics who claim it is irrelevant to science. Defense is important, too, because the hypothesis is perhaps the major element in scientific thinking, and familiarity with it is necessary for an understanding of modern science and scientific thinking. The public needs to understand the hypothesis in order to appreciate and evaluate scientific controversies (e.g., global climate change, vaccine safety, etc.). The first chapters thoroughly describe and analyze in elementary terms the scientific hypothesis and examine various kinds of science. Following chapters that review the hypothesis in the context of the Reproducibility Crisis and present survey data, two chapters assess cognitive matters that affect the hypothesis. In a series of chapters, the book makes practical and policy recommendations for teaching and learning about the hypothesis. The final chapter considers two possible futures for the hypothesis in science as the Big Data revolution looms: in one scenario, the hypothesis is displaced by the Big Data Mindset that forgoes understanding in favor of correlation and prediction. In the other, robotic science incorporates the hypothesis into mechanized laboratories guided by artificial intelligence. An epilogue envisions a third way—the Centaur Scientist, a symbiotic relationship of human scientists and computers.

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37

Snijders, Tom A. B., and Mark Pickup. Stochastic Actor Oriented Models for Network Dynamics. Edited by Jennifer Nicoll Victor, Alexander H. Montgomery, and Mark Lubell. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190228217.013.10.

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Stochastic Actor Oriented Models for Network Dynamics are used for the statistical analysis of longitudinal network data collected as a panel. The probability model defines an unobserved stochastic process of tie changes, where social actors add new ties or drop existing ties in response to the current network structure; the panel observations are snapshots of the resulting changing network. The statistical analysis is based on computer simulations of this process, which provides a great deal of flexibility in representing data constraints and dependence structures. In this Chapter we begin by defining the basic model. We then explicate a new model for nondirected ties, including several options for the specification of how pairs of actors coordinate tie changes. Next, we describe coevolution models. These can be used to model the dynamics of several interdependent sets of variables, such as the analysis of panel data on a network and the behavior of the actors in the network, or panel data on two or more networks. We finish by discussing the differences between Stochastic Actor Oriented Models and some other longitudinal network models. A major distinguishing feature is the treatment of time, which allows straightforward application of the model to panel data with different time lags between waves. We provide a variety of applications in political science throughout.

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38

Schomer, Donald L., and Fernando H. Lopes da Silva, eds. Niedermeyer's Electroencephalography. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.001.0001.

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This book deals with the field of Electroencephalography in the widest possible sense, from the cellular foundations of the electric activities of the brain to a vast number of clinical applications. The basic science sections were up-dated to include advanced computer modeling approaches. The chapters on normal and pathological EEG findings in premature infants, newborns and children were thoroughly revised to keep up with the advances that have taken place recently in studying brain developmental issues. Major advances have taken place in neurophysiological findings in a variety of neurodegenerative disorders, which led to thoroughly revised chapters. Other rapidly changing subjects related to EEG recording/monitoring in ICU's, EMUs, and operating rooms, in patients with epilepsy, head injuries, infectious disorders and those undergoing surgical procedures, led to radically updating a number of chapters and to the addition of a chapter dedicated to invasive recordings for the treatment of patients with movement disorders. A previously missing chapter on the neurophysiology of myoclonus was added. Chapters that deal with automated EEG interpretation techniques and with standardizing EEG reporting using ILAE/IFCN approved terminology, were also added. Many chapters in the on-line version of the book will have the ability to link to a database of over 150 complete EEGs that cover the scope seen in a general EEG Lab. This link will allow the reader to manipulate the EEG display parameters as if they were in their own lab, generate a report and compare it to one generated by a panel of senior EEGers.

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39

Sætre, Glenn-Peter, and Mark Ravinet. Evolutionary Genetics. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198830917.001.0001.

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Evolutionary genetics is the study of how genetic variation leads to evolutionary change. With the recent explosion in the availability of whole genome sequence data, vast quantities of genetic data are being generated at an ever-increasing pace with the result that programming has become an essential tool for researchers. Most importantly, a thorough understanding of evolutionary principles is essential for making sense of this genetic data. This up-to-date textbook covers all the major components of modern evolutionary genetics, carefully explaining fundamental processes such as mutation, natural selection, genetic drift, and speciation, together with their consequences. In addition to the text, study questions are provided to motivate the reader to think and reflect on the concepts in each chapter. Practical experience is essential when it comes to developing an understanding of how to use genetic data to analyze and address interesting questions in the life sciences and how to interpret results in meaningful ways. Throughout the book, a series of online, computer-based tutorials serves as an introduction to programming and analysis of evolutionary genetic data centered on the R programming language, which stands out as an ideal all-purpose platform to handle and analyze such data. The book and its online materials take full advantage of the authors’ own experience in working in a post-genomic revolution world, and introduce readers to the plethora of molecular and analytical methods that have only recently become available.

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