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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.

  • Advances in Non-volatile Memory and Storage Technology

    • 1st Edition
    • Yoshio Nishi
    • English
    New solutions are needed for future scaling down of nonvolatile memory. Advances in Non-volatile Memory and Storage Technology provides an overview of developing technologies and explores their strengths and weaknesses. After an overview of the current market, part one introduces improvements in flash technologies, including developments in 3D NAND flash technologies and flash memory for ultra-high density storage devices. Part two looks at the advantages of designing phase change memory and resistive random access memory technologies. It looks in particular at the fabrication, properties, and performance of nanowire phase change memory technologies. Later chapters also consider modeling of both metal oxide and resistive random access memory switching mechanisms, as well as conductive bridge random access memory technologies. Finally, part three looks to the future of alternative technologies. The areas covered include molecular, polymer, and hybrid organic memory devices, and a variety of random access memory devices such as nano-electromechanic... ferroelectric, and spin-transfer-torque magnetoresistive devices. Advances in Non-volatile Memory and Storage Technology is a key resource for postgraduate students and academic researchers in physics, materials science, and electrical engineering. It is a valuable tool for research and development managers concerned with electronics, semiconductors, nanotechnology, solid-state memories, magnetic materials, organic materials, and portable electronic devices.

  • Cloud Networking

    Understanding Cloud-based Data Center Networks
    • 1st Edition
    • Gary Lee
    • English
    Cloud Networking: Understanding Cloud-Based Data Center Networks explains the evolution of established networking technologies into distributed, cloud-based networks. Starting with an overview of cloud technologies, the book explains how cloud data center networks leverage distributed systems for network virtualization, storage networking, and software-defined networking. The author offers insider perspective to key components that make a cloud network possible such as switch fabric technology and data center networking standards. The final chapters look ahead to developments in architectures, fabric technology, interconnections, and more. By the end of the book, readers will understand core networking technologies and how they’re used in a cloud data center.

  • Bridging UX and Web Development

    Better Results through Team Integration
    • 1st Edition
    • Jack Moffett
    • English
    The divide between UX and Web development can be stifling. Bridging UX and Web Development prepares you to break down those walls by teaching you how to integrate with your team’s developers. You examine the process from their perspective, discovering tools and coding principles that will help you bridge the gap between design and implementation. With these tried and true approaches, you’ll be able to capitalize on a more productive work environment. Whether you’re a novice UX professional finding your place in the software industry and looking to nail down your technical skills, or a seasoned UI designer looking for practical information on how to integrate your team with development, this is the must-have resource for your UX library.

  • Principles of Knowledge Representation and Reasoning

    Proceedings of the Fourth International Conference (KR '94)
    • 1st Edition
    • Jon Doyle + 2 more
    • English
    Principles of Knowledge Representation and Reasoning contains the proceedings of the Fourth International Conference on Principles of Knowledge Representation and Reasoning (KR '94) held in Bonn, Germany, on May 24-27, 1994. The conference provided a forum for reviewing the theory and principles underlying knowledge representation and reasoning. Topics covered range from reasoning about mental states and spatial reasoning with propositional logics to default logic as a query language. Comprised of 60 chapters, this book begins with a description of a formal language for representing and reasoning about time and action before turning to proof in context and how it can replace the most common uses of reflection principles. The reader is then introduced to reasoning with minimal models; belief ascription and mental-level modeling; and a unified framework for class-based representation formalisms. A general approach to specificity in default reasoning is also described, together with an ontology for engineering mathematics and the use of abduction to generate tests. The book concludes by considering the use of natural language for knowledge representation and reasoning. This monograph will be of interest to both students and practitioners in the fields of artificial intelligence and computer science.

  • Analog and Hybrid Computing

    • 1st Edition
    • D. E. Hyndman
    • N. Hiller
    • English
    Analog and Hybrid Computing considers the fundamental aspects and principled of analog and hybrid computers and their applications in various scientific investigations. This book is composed of eight chapters, and begins with a brief presentation of the history of computing devices using a generalized flow diagram of computation, illustrating the fundamental differences between analog and digital computers. The subsequent chapters deal with the theory and the operation of the basic units found in electronic analog computers, the methods of scaling problems for the computer, and the organization and operation of computer. These topics are followed by discussions on the solutions of time-varying and non-linear differential equations and the simulation of transfer functions, which is an important aspect of analog computation. The concluding chapter describes some of the additional hardware in modern computers. These chapters particularly highlight the features and advantages of hybrid computing. This book is of value to computer engineers, scientists, and researchers, as well as advanced computer engineering students.

  • Economics-Driven Software Architecture

    • 1st Edition
    • Ivan Mistrik + 3 more
    • English
    Economics-driven Software Architecture presents a guide for engineers and architects who need to understand the economic impact of architecture design decisions: the long term and strategic viability, cost-effectiveness, and sustainability of applications and systems. Economics-driven software development can increase quality, productivity, and profitability, but comprehensive knowledge is needed to understand the architectural challenges involved in dealing with the development of large, architecturally challenging systems in an economic way. This book covers how to apply economic considerations during the software architecting activities of a project. Architecture-centric approaches to development and systematic evolution, where managing complexity, cost reduction, risk mitigation, evolvability, strategic planning and long-term value creation are among the major drivers for adopting such approaches. It assists the objective assessment of the lifetime costs and benefits of evolving systems, and the identification of legacy situations, where architecture or a component is indispensable but can no longer be evolved to meet changing needs at economic cost. Such consideration will form the scientific foundation for reasoning about the economics of nonfunctional requirements in the context of architectures and architecting.

  • Museum Documentation Systems

    Developments and Applications
    • 1st Edition
    • Richard B. Light + 2 more
    • English

  • Distributed Artificial Intelligence

    Volume II
    • 1st Edition
    • Robin Gasser + 1 more
    • English
    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.

  • Artificial Intelligence in Design '91

    • 1st Edition
    • J. S. Gero
    • English
    Artificial Intelligence in Design '91 is a collection of 47 papers from the First International Conference on Artificial Intelligence in Design held at Edinburgh in June 1991. The papers in this book are grouped into 13 headings, starting with a background of AI design systems and to which extent AI that results from being used as planning tool be applied to quality-oriented design processes in architecture. A constraint-driven approach to object-oriented design is also shown on real-world objects. The use of CADSYN in the structural design of buildings is examined, along with design-dependent knowledge and design-independent knowledge. Discussions on empowering designers with integrated design environments are given whereby design objects may be retrieved from catalogues without requiring users to form queries. Mention is given to automated adjustment of parameter values frequently used in computer routine applications. The book also introduces the Computer Aided Design (CAD) as applied to architecture. Design representation using data models, non-monotonic reasoning in design, and the cognitive aspects of design using empirical studies are discussed. Topics of the industrial applications of AI in design, such as the needed steps to develop a successful AI-based tool, and a review of the Castlemain Project and telecommunication distribution networks follow. This book is suitable for programmers, computer science students, and architects and engineers who use computers in their line of work.

  • Machine Learning Proceedings 1993

    Proceedings of the Tenth International Conference on Machine Learning, University of Massachusetts, Amherst, June 27-29, 1993
    • 1st Edition
    • Lawrence A. Birnbaum
    • English
    Machine Learning: Proceedings of the Tenth International Conference covers the papers presented at the Tenth International Conference on Machine Learning, held at Amherst, Massachusetts in June 27-29, 1993. The book focuses on the advancements of techniques, practices, approaches, and methodologies in machine learning. The selection first offers information on automatic algorithm/model class selection, using decision trees to improve case-based learning, GALOIS, and multitask learning. Discussions focus on multitask connectionist learning in more detail; multitask decision trees; an algorithm for the incremental determination of the concept lattice; and empirical evaluation of GALOIS as a learning system. The text then examines the use of qualitative models to guide inductive learning; automation of path analysis for building causal models from data; and construction of hidden variables in Bayesian networks via conceptual clustering. The book ponders on synthesis of abstraction hierarchies for constraint satisfaction by clustering approximately equivalent objects; efficient domain-independent experimentation; learning search control knowledge for deep space network scheduling; and learning procedures from interactive natural language instructions. The selection is a dependable reference for researchers wanting to explore the field of machine learning.

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