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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.

  • Scalable Shared-Memory Multiprocessing

    • 1st Edition
    • Daniel E. Lenoski + 1 more
    • English
    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.

  • Computer Hardware Description Languages and their Applications

    Proceedings of the IFIP WG 10.2 Tenth International Symposium on Computer Hardware Description Languages and their Applications, Marseille, France, 22-24 April 1991
    • 1st Edition
    • D. Borrione + 1 more
    • English
    The topic areas presented within this volume focus on design environments and the applications of hardware description and modelling – including simulation, verification by correctness proofs, synthesis and test. The strong relationship between the topics of CHDL'91 and the work around the use and re-standardization of the VHDL language is also explored. The quality of this proceedings, and its significance to the academic and professional worlds is assured by the excellent technical programme here compiled.

  • Pattern Recognition and Artificial Intelligence, Towards an Integration

    Proceedings of an International Workshop held in Amsterdam, May 18-20, 1988
    • 1st Edition
    • Volume 7
    • L.N. Kanal + 1 more
    • English
    This volume brings together the results of research into the methodology and applications of pattern recognition, with particular emphasis given to the incorporation of artificial intelligence methodologies into pattern recognition systems.The first part of this volume covers image analysis and processing software, systems and algorithms. Pattern analysis and classifier design are dealt with in part two, while the last part deals with model based and expert systems, including uncertainty calculus methods in pattern analysis and object recognition. A number of specific application areas are considered, including such diverse topics as fingerprinting, astronomy, molecular biology and pathology.

  • Safety of Computer Control Systems 1990 (SAFECOMP'90)

    Proceedings of the IFAC/EWICS/SARS Symposium Gatwick, UK, 30 October - 2 November 1990
    • 1st Edition
    • B.K. Daniels
    • English
    The market for safe, secure and reliable computer systems is expanding continuously and these Proceedings provide an opportunity to review the growth during the last decade and identify skills and technologies required for continued development in the area. The papers cover the experiences gained from specifying, creating, operating, and licensing computers in safety, security and reliability related applications. There are reviews of guidelines and industrial applications, with a section covering methods and tools used in designing, documenting, analysing, testing and assessing systems dependent on the SAFECOMP factors.

  • Uncertainty in Artificial Intelligence

    • 1st Edition
    • Volume 4
    • L.N. Kanal + 1 more
    • English
    How to deal with uncertainty is a subject of much controversy in Artificial Intelligence. This volume brings together a wide range of perspectives on uncertainty, many of the contributors being the principal proponents in the controversy.Some of the notable issues which emerge from these papers revolve around an interval-based calculus of uncertainty, the Dempster-Shafer Theory, and probability as the best numeric model for uncertainty. There remain strong dissenting opinions not only about probability but even about the utility of any numeric method in this context.

  • Machine Learning

    An Artificial Intelligence Approach, Volume III
    • 1st Edition
    • Yves Kodratoff + 1 more
    • English
    Machine Learning: An Artificial Intelligence Approach, Volume III presents a sample of machine learning research representative of the period between 1986 and 1989. The book is organized into six parts. Part One introduces some general issues in the field of machine learning. Part Two presents some new developments in the area of empirical learning methods, such as flexible learning concepts, the Protos learning apprentice system, and the WITT system, which implements a form of conceptual clustering. Part Three gives an account of various analytical learning methods and how analytic learning can be applied to various specific problems. Part Four describes efforts to integrate different learning strategies. These include the UNIMEM system, which empirically discovers similarities among examples; and the DISCIPLE multistrategy system, which is capable of learning with imperfect background knowledge. Part Five provides an overview of research in the area of subsymbolic learning methods. Part Six presents two types of formal approaches to machine learning. The first is an improvement over Mitchell's version space method; the second technique deals with the learning problem faced by a robot in an unfamiliar, deterministic, finite-state environment.

  • Machine Learning Proceedings 1991

    Proceedings of the Eighth International Workshop (ML91)
    • 1st Edition
    • Lawrence A. Birnbaum + 1 more
    • English
    Machine Learning: Proceedings of the Eighth International Workshop (ML91) covers the papers presented at ML91, the Eighth International Workshop on Machine Learning, held at Northwestern University, Evanston, Illinois, USA, in June 1991. The book focuses on constructive induction, learning from theory and data, automated knowledge acquisition, learning in intelligent information retrieval, machine learning in engineering automation, computational models of human learning, and learning reaction strategies. The selection first offers information on design rationale capture as knowledge acquisition, a domain-independent framework for effective experimentation in planning, and knowledge refinement using a high-level, non-technical vocabulary. The text then elaborates on improving the performance of inconsistent knowledge bases via combined optimization method, flexibility of speculative refinement, and a prototype based symbolic concept learning system. Topics include using task descriptions to generate error candidates, functional descriptions of knowledge-based systems, combined optimization method, and inconsistency and related work. The book ponders on learning words from context, modeling the acquisition and improvement of motor skills, a computational model of acquisition for children's addition strategies, and computer modeling of acquisition orders in child language. The manuscript also takes a look at knowledge acquisition combining analytical and empirical techniques; designing integrated learning systems for engineering design; and machine learning for nondestructive evaluation. The selection is highly recommended for researchers interested in machine learning.

  • Progress in Pattern Recognition 1

    • 1st Edition
    • L.N. Kanal + 1 more
    • English
    Progress in Pattern Recognition, Volume 1 focuses on the processes, techniques, and approaches involved in pattern recognition, including conceptual clustering, cross-correlation, syntax, software, data structures, and distance transforms. The selection first tackles progress in syntactic pattern recognition and clustering objects into classes characterized by conjunctive concepts. Discussions focus on an overview of clustering problems, conjunctive conceptual clustering, primitive selection and pattern grammars, high dimensional grammars for pattern description, syntactic pattern recognition using stochastic languages, and syntactic approach to shape and texture analysis. The text then elaborates on database representations in hierarchical scene analysis and medium level vision. The book examines image processing software and analysis and synthesis of image patterns by spatial interaction models. Topics include synopsis of discrete spatial interaction models, nonrecursive models over infinite lattices, finite lattice models, and the MSFC image processing package. The text also reviews the mathematical aspects of image reconstruction from projection and recognition of stereo-image cross-correlation errors. The selection is a highly recommended source of data for researchers interested in the process of pattern recognition.

  • Neural Network PC Tools

    A Practical Guide
    • 1st Edition
    • Russell C. Eberhart
    • English
    This is the first practical guide that enables you to actually work with artificial neural networks on your personal computer. It provides basic information on neural networks, as well as the following special features:

  • The Digital Technical Documentation Handbook

    • 1st Edition
    • Susan K. Schultz + 3 more
    • English
    The Digital Technical Documentation Handbook describes the process of developing and producing technical user information at Digital Equipment Corporation. * Discusses techniques for making user information _more effective * Covers the draft and reviewprocess, the production and distribution of printed and electronic media, archiving, indexing, testing for usability, and many other topics * Provides quality assurance checklists, contains a glossary and a bibliography of resources for technicalcommunicato...

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