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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

    • Psychology of System Design

      • 1st Edition
      • Volume 17
      • June 28, 2014
      • D. Meister
      • English
      • Paperback
        9 7 8 1 4 9 3 3 0 8 0 1 9
      • eBook
        9 7 8 1 4 8 3 2 9 5 9 2 3
      This is a book about systems, including: systems in which humans control machines; systems in which humans interact with humans and the machine component is relatively unimportant; systems which are heavily computerized and those that are not; and governmental, industrial, military and social systems.The book deals with both traditional systems like farming, fishing and the military, and with systems just now tentatively emerging, like the expert and the interactive computer system. The emphasis is on the system concept and its implications for analysis, design and evaluation of these many different types of systems. The book attempts to make three major points: 1. System design, and particularly computer system design, must fit into and be directed by a comprehensive theory of system functioning. 2. Interactive computer design models itself upon our knowledge of how humans function. 3. Highly sophisticated interactive computer systems are presently mostly research vehicles, they are vastly different to general purpose, commercially available word processors and personal computers.The book represents an interdisciplinary approach, the author has used psychological, organizational, human factors, and engineering sources. The book is not a "how to do it" book but it is intended to stimulate thinking about the larger context in which systems, particularly computer systems of the future, should be designed and used.

    • Programming, The Impossible Challenge

      • 1st Edition
      • June 28, 2014
      • B. Walraet
      • English
      • Paperback
        9 7 8 1 4 9 3 3 0 5 6 0 5
      • eBook
        9 7 8 1 4 8 3 2 9 5 8 8 6
      In its modern form, the computer is only about 40 years old. And so is the job of the computer programmer. This book is a critical history of programming, written to give programmers and analysts in the commercial application field a more pragmatic insight into the background of their profession. It tells the story of why the technology evolved as it did, and how Fifth Generation techniques are already changing the situation.As well as charting the real advances and the passing fashions, this unusual book looks at the situation in perspective, drawing some sad and maybe surprising conclusions while discussing questions such as ``Is programming a job for human beings?'' ``Is it High Noon for the world of programming?''

    • 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.

    • Dynamic Modelling of Information Systems

      • 1st Edition
      • June 28, 2014
      • K.M. van Hee + 1 more
      • English
      • Paperback
        9 7 8 1 4 9 3 3 0 5 4 3 8
      • eBook
        9 7 8 1 4 8 3 2 9 4 8 4 1
      The use of dynamic models in the development of information systems is regarded by many researchers as a promising issue in design support. Modelling the dynamics of information systems is likely to improve the quality and the performance of the design products. Dynamic modelling as a new approach for dynamic analysis of problems within an existing situation, and design and evaluation of different solution strategies may overcome many difficulties in the design process.

    • Computer Programming and Architecture

      • 2nd Edition
      • June 28, 2014
      • Henry Levy + 1 more
      • English
      • Paperback
        9 7 8 1 4 9 3 3 0 8 2 4 8
      • eBook
        9 7 8 1 4 8 3 2 9 9 3 7 2
      Takes a unique systems approach to programming and architecture of the VAXUsing the VAX as a detailed example, the first half of this book offers a complete course in assembly language programming. The second describes higher-level systems issues in computer architecture. Highlights include the VAX assembler and debugger, other modern architectures such as RISCs, multiprocessing and parallel computing, microprogramming, caches and translation buffers, and an appendix on the Berkeley UNIX assembler.

    • Parallel Processing for Artificial Intelligence 2

      • 1st Edition
      • Volume 15
      • June 28, 2014
      • V. Kumar + 2 more
      • English
      • Paperback
        9 7 8 1 4 9 3 3 0 5 3 3 9
      • eBook
        9 7 8 1 4 8 3 2 9 5 7 5 6
      With the increasing availability of parallel machines and the raising of interest in large scale and real world applications, research on parallel processing for Artificial Intelligence (AI) is gaining greater importance in the computer science environment. Many applications have been implemented and delivered but the field is still considered to be in its infancy.This book assembles diverse aspects of research in the area, providing an overview of the current state of technology. It also aims to promote further growth across the discipline. Contributions have been grouped according to their subject: architectures (3 papers), languages (4 papers), general algorithms (6 papers), and applications (5 papers). The internationally sourced papers range from purely theoretical work, simulation studies, algorithm and architecture proposals, to implemented systems and their experimental evaluation.Since the book is a second volume in the parallel processing for AI series, it provides a continued documentation of the research and advances made in the field. The editors hope that it will inspire readers to investigate the possiblities for enhancing AI systems by parallel processing and to make new discoveries of their own!

    • Reliable Computer Systems

      • 2nd Edition
      • June 28, 2014
      • Daniel Siewiorek + 1 more
      • English
      • eBook
        9 7 8 1 4 8 3 2 9 7 4 3 9
      Enhance your hardware/software reliabilityEnhanceme... of system reliability has been a major concern of computer users and designers ¦ and this major revision of the 1982 classic meets users' continuing need for practical information on this pressing topic. Included are case studies of reliablesystems from manufacturers such as Tandem, Stratus, IBM, and Digital, as well as coverage of special systems such as the Galileo Orbiter fault protection system and AT&T telephone switching processors.

    • Languages, Compilers and Run-time Environments for Distributed Memory Machines

      • 1st Edition
      • Volume 3
      • June 28, 2014
      • J. Saltz + 1 more
      • English
      • Paperback
        9 7 8 1 4 9 3 3 0 5 4 0 7
      • eBook
        9 7 8 1 4 8 3 2 9 5 3 8 1
      Papers presented within this volume cover a wide range of topics related to programming distributed memory machines. Distributed memory architectures, although having the potential to supply the very high levels of performance required to support future computing needs, present awkward programming problems. The major issue is to design methods which enable compilers to generate efficient distributed memory programs from relatively machine independent program specifications. This book is the compilation of papers describing a wide range of research efforts aimed at easing the task of programming distributed memory machines.

    • Artificial Neural Networks and Statistical Pattern Recognition

      • 1st Edition
      • Volume 11
      • June 28, 2014
      • I.K. Sethi + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 4 8 8 7 4 1 2
      • eBook
        9 7 8 1 4 8 3 2 9 7 8 7 3
      With the growing complexity of pattern recognition related problems being solved using Artificial Neural Networks, many ANN researchers are grappling with design issues such as the size of the network, the number of training patterns, and performance assessment and bounds. These researchers are continually rediscovering that many learning procedures lack the scaling property; the procedures simply fail, or yield unsatisfactory results when applied to problems of bigger size. Phenomena like these are very familiar to researchers in statistical pattern recognition (SPR), where the curse of dimensionality is a well-known dilemma. Issues related to the training and test sample sizes, feature space dimensionality, and the discriminatory power of different classifier types have all been extensively studied in the SPR literature. It appears however that many ANN researchers looking at pattern recognition problems are not aware of the ties between their field and SPR, and are therefore unable to successfully exploit work that has already been done in SPR. Similarly, many pattern recognition and computer vision researchers do not realize the potential of the ANN approach to solve problems such as feature extraction, segmentation, and object recognition. The present volume is designed as a contribution to the greater interaction between the ANN and SPR research communities.

    • Machine Learning Proceedings 1992

      • 1st Edition
      • June 28, 2014
      • Peter Edwards + 1 more
      • English
      • Paperback
        9 7 8 1 5 5 8 6 0 2 4 7 2
      • eBook
        9 7 8 1 4 8 3 2 9 8 5 3 5
      Machine Learning: Proceedings of the Ninth International Workshop (ML92) covers the papers and posters presented at ML92, the Ninth International Machine Learning Conference, held at Aberdeen, Scotland on July 1-3, 1992. The book focuses on the advancements of practices, methodologies, approaches, and techniques in machine learning. The selection first offers information on the principal axes method for constructive induction; learning by incomplete explanations of failures in recursive domains; and eliminating redundancy in explanation-based learning. Topics include means-ends analysis search in recursive domains, description space transformation, distance metric, generating similarity matrix, and learning principal axes. The text then examines trading off consistency and efficiency in version-space induction; improving path planning with learning; finding the conservation of momentum; and learning to predict in uncertain continuous tasks. The manuscript elaborates on a teaching method for reinforcement learning, compiling prior knowledge into an explicit bias, spatial analogy and subsumption, and multistrategy learning with introspective meta-explanations. The publication also ponders on selecting typical instances in instance-based learning and temporal difference learning of backgammon strategy. The selection is a valuable source of information for researchers interested in machine learning.

Related subjects

Applications

Artificial intelligence

Business intelligence

Computer systems organization

Computer vision and pattern recognition

Computing milieux

Data

Graphics cad hci

Hardware and architecture

Information systems

Internet and web technology

Software

Theory and mathematics