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Books in Computer science

The Computing collection presents a range of foundational and applied content across computer and data science, including fields such as Artificial Intelligence; Computational Modelling; Computer Networks, Computer Organization & Architecture, Computer Vision & Pattern Recognition, Data Management; Embedded Systems & Computer Engineering; HCI/User Interface Design; Information Security; Machine Learning; Network Security; Software Engineering.

BooksJournals

    • Digital Picture Processing

      • 2nd Edition
      • Volume 1
      • January 9, 2014
      • Azriel Rosenfeld + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 4 1 2 1 5 5 3
      • eBook
        9 7 8 0 3 2 3 1 3 9 9 1 5
      The rapid rate at which the field of digital picture processing has grown in the past five years had necessitated extensive revisions and the introduction of topics not found in the original edition.

    • Real Time Programming 1986

      • 1st Edition
      • May 23, 2014
      • J. Szlanko
      • English
      • Paperback
        9 7 8 1 4 9 3 3 0 5 2 1 6
      • eBook
        9 7 8 1 4 8 3 2 9 8 0 4 7
      The 1986 IFAC/IFIP Workshop on real-time programming represents the 14th meeting of this workshop since it was first organized in 1971. Traditionally a meeting of a small number of experts, the papers presented at this meeting concentrate on the topics of real-time environment and executives, software development tools and languages, and special real-time applications. The continuing progress being made in this field of programming is amply reflected by the papers and should be of interest to anyone wishing to be kept up to date in the field.

    • Parallel Processing for Artificial Intelligence 1

      • 1st Edition
      • Volume 14
      • June 28, 2014
      • L.N. Kanal + 3 more
      • English
      • Paperback
        9 7 8 1 4 9 3 3 0 5 5 5 1
      • eBook
        9 7 8 1 4 8 3 2 9 5 7 4 9
      Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge representation in semantic networks, production rules, mechanization of logic, constraint satisfaction, parsing of natural language, data filtering and data mining. The publication is divided into six sections. The first addresses parallel computing for processing and understanding images. The second discusses parallel processing for semantic networks, which are widely used means for representing knowledge - methods which enable efficient and flexible processing of semantic networks are expected to have high utility for building large-scale knowledge-based systems. The third section explores the automatic parallel execution of production systems, which are used extensively in building rule-based expert systems - systems containing large numbers of rules are slow to execute and can significantly benefit from automatic parallel execution. The exploitation of parallelism for the mechanization of logic is dealt with in the fourth section. While sequential control aspects pose problems for the parallelization of production systems, logic has a purely declarative interpretation which does not demand a particular evaluation strategy. In this area, therefore, very large search spaces provide significant potential for parallelism. In particular, this is true for automated theorem proving. The fifth section considers the problem of constraint satisfaction, which is a useful abstraction of a number of important problems in AI and other fields of computer science. It also discusses the technique of consistent labeling as a preprocessing step in the constraint satisfaction problem. Section VI consists of two articles, each on a different, important topic. The first discusses parallel formulation for the Tree Adjoining Grammar (TAG), which is a powerful formalism for describing natural languages. The second examines the suitability of a parallel programming paradigm called Linda, for solving problems in artificial intelligence.Each of the areas discussed in the book holds many open problems, but it is believed that parallel processing will form a key ingredient in achieving at least partial solutions. It is hoped that the contributions, sourced from experts around the world, will inspire readers to take on these challenging areas of inquiry.

    • Topics in Expert System Design

      • 1st Edition
      • Volume 5
      • June 28, 2014
      • C. Tasso + 1 more
      • English
      • Paperback
        9 7 8 1 4 9 3 3 0 5 5 6 8
      • eBook
        9 7 8 1 4 8 3 2 9 7 7 7 4
      Expert Systems are so far the most promising achievement of artificial intelligence research. Decision making, planning, design, control, supervision and diagnosis are areas where they are showing great potential. However, the establishment of expert system technology and its actual industrial impact are still limited by the lack of a sound, general and reliable design and construction methodology.This book has a dual purpose: to offer concrete guidelines and tools to the designers of expert systems, and to promote basic and applied research on methodologies and tools. It is a coordinated collection of papers from researchers in the USA and Europe, examining important and emerging topics, methodological advances and practical experience obtained in specific applications. Each paper includes a survey introduction, and a comprehensive bibliography is provided.

    • Artificial Neural Networks

      • 1st Edition
      • June 28, 2014
      • K. Mäkisara + 3 more
      • English
      • eBook
        9 7 8 1 4 8 3 2 9 8 0 0 9
      This two-volume proceedings compiles a selection of research papers presented at the ICANN-91. The scope of the volumes is interdisciplinary, ranging from mathematics and engineering to cognitive sciences and biology. European research is well represented. Volume 1 contains all the orally presented papers, including both invited talks and submitted papers. Volume 2 contains the plenary talks and the poster presentations.

    • A Discipline of Software Engineering

      • 1st Edition
      • June 28, 2014
      • B. Walraet
      • English
      • Paperback
        9 7 8 1 4 9 3 3 0 5 6 4 3
      • eBook
        9 7 8 1 4 8 3 2 9 4 2 1 6
      This comprehensive approach to the creation of software systems charts a road through system modelling techniques, allowing software engineers to create software meeting two very basic requirements:• that the software system represent a narrow emulation of the organization system that served as its model; • and that the software system display life attributes identical to those of the organization system that it automatizes.The result is a quantum leap increase in software application quality. Such benefit is achieved by the introduction of a fundamental paradigm: the office-floor metaphor which incorporates such well-balanced basic ideas as the functional normalization of tasks and information (in sharp contrast to the classic data normalization) and the principle of tenant-ownership.

    • Foundations of Deductive Databases and Logic Programming

      • 1st Edition
      • May 12, 2014
      • Jack Minker
      • English
      • Paperback
        9 7 8 1 4 8 3 2 0 7 6 9 8
      • eBook
        9 7 8 1 4 8 3 2 2 1 1 2 0
      Foundations of Deductive Databases and Logic Programming focuses on the foundational issues concerning deductive databases and logic programming. The selection first elaborates on negation in logic programming and towards a theory of declarative knowledge. Discussions focus on model theory of stratified programs, fixed point theory of nonmonotonic operators, stratified programs, semantics for negation in terms of special classes of models, relation between closed world assumption and the completed database, negation as a failure, and closed world assumption. The book then takes a look at negation as failure using tight derivations for general logic programs, declarative semantics of logic programs with negation, and declarative semantics of deductive databases and logic programs. The publication tackles converting AND-control to OR-control by program transformation, optimizing dialog, equivalences of logic programs, unification, and logic programming and parallel complexity. Topics include parallelism and structured and unstructured data, parallel algorithms and complexity, solving equations, most general unifiers, systems of equations and inequations, equivalences of logic programs, and optimizing recursive programs. The selection is a valuable source of data for researchers interested in pursuing further studies on the foundations of deductive databases and logic programming.

    • Practical Knowledge Engineering

      • 1st Edition
      • June 28, 2014
      • Richard Kelly
      • English
      • Paperback
        9 7 8 1 5 5 5 5 8 0 7 0 4
      • eBook
        9 7 8 1 4 8 3 2 9 5 8 1 7
      This book provides knowledge engineers with practical methods for initiating, designing, building, managing, and demonstrating successful commercial expert systems. It is a record of what actually works (and does not work) in the construction of expert systems, drawn from the author's decade of experience in building expert systems in all major areas of application for American, European, and Japanese organizations.The book features:* knowledge engineering programming techniques* useful skills for demonstrating expert systems * practical costing and metrics* guidelines for using knowledge representation techniques* solutions to common difficulties in design and implementation

    • Scalable Shared-Memory Multiprocessing

      • 1st Edition
      • June 28, 2014
      • Daniel E. Lenoski + 1 more
      • English
      • Paperback
        9 7 8 1 4 9 3 3 0 6 1 4 5
      • eBook
        9 7 8 1 4 8 3 2 9 6 0 1 2
      Dr. Lenoski and Dr. Weber have experience with leading-edge research and practical issues involved in implementing large-scale parallel systems. They were key contributors to the architecture and design of the DASH multiprocessor. Currently, they are involved with commercializing scalable shared-memory technology.

    • Distributed Artificial Intelligence

      • 1st Edition
      • May 23, 2014
      • Robin Gasser + 1 more
      • English
      • Paperback
        9 7 8 1 5 5 8 6 0 0 9 2 8
      • eBook
        9 7 8 1 4 8 3 2 9 4 8 1 0
      Research Notes in Artificial Intelligence: Distributed Artificial Intelligence, Volume II focuses on the growing interest in Distributed Artificial Intelligence (DAI). The selection first offers information on a unified theory of communication and social structure and boundary objects and heterogeneous distributed problem solving. Discussions focus on types of boundary objects, heterogeneous problem solving and boundary objects, social structures and social groups, and social cooperation and communication. The text then examines representing and using organizational knowledge in DAI systems, dynamics of computational ecosystems, and communication-free interactions among rational agents. The publication takes a look at conflict-resolution strategies for nonhierarchical distributed agents, constraint-directed negotiation of resource reallocations, and plans for multiple agents. Topics include plan verification, generation, and execution, negotiation operators, representation, network management problem, and conflict-resolution paradigms. The manuscript then elaborates on negotiating task decomposition and allocation using partial global planning and mechanisms for assessing nonlocal impact of local decisions in distributed planning. The selection is a valuable source of information for researchers interested in distributed artificial intelligence.

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