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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

  • The Blockchain Technology for Secure and Smart Applications across Industry Verticals

    • 1st Edition
    • Volume 121
    • English
    The Blockchain Technology for Secure and Smart Applications across Industry Verticals, Volume 121, presents the latest information on a type of distributed ledger used for maintaining a permanent and tamper-proof record of transactional data. The book presents a novel compendium of existing and budding Blockchain technologies for various smart applications. Chapters in this new release include the Basics of Blockchain, The Blockchain History, Architecture of Blockchain, Core components of Blockchain, Blockchain 2.0: Smart Contracts, Empowering Digital Twins with Blockchain, Industrial Use Cases at the Cusp of the IoT and Blockchain Paradigms, Blockchain Components and Concepts, Digital Signatures, Accumulators, Financial Systems, and more. This book is a unique effort to illuminate various techniques to represent, improve and authorize multi-institutional and multidisciplinary research in a different type of smart applications, like the financial system, smart grid, transportation system, etc. Readers in identity-privacy, traceability, immutability, transparency, auditability, and security will find it to be a valuable resource.

  • Computer Networks

    A Systems Approach
    • 6th Edition
    • Larry L. Peterson + 1 more
    • English
    Computer Networks: A Systems Approach, Sixth Edition, explores the key principles of computer networking, using real world examples from network and protocol design. Using the Internet as the primary example, this best-selling classic textbook explains various protocols and networking technologies. The systems-oriented approach encourages students to think about how individual network components fit into a larger, complex system of interactions. This sixth edition contains completely updated content with expanded coverage of the topics of utmost importance to networking professionals and students, as provided by numerous contributors via a unique open source model developed jointly by the authors and publisher.Hallmark features of the book are retained, including chapter problem statements, which introduce issues to be examined; shaded sidebars that elaborate on a topic or introduce a related advanced topic; What’s Next? discussions that deal with emerging issues in research, the commercial world, or society; and exercises. This book is intended primarily for graduate or upper-division undergraduate classes in computer networking. It will also be useful for industry professionals retraining for network-related assignments, as well as for network practitioners seeking to understand the workings of network protocols and the big picture of networking.

  • Computer Organization and Design RISC-V Edition

    The Hardware Software Interface
    • 2nd Edition
    • David A. Patterson + 1 more
    • English
    Computer Organization and Design RISC-V Edition: The Hardware Software Interface, Second Edition, the award-winning textbook from Patterson and Hennessy that is used by more than 40,000 students per year, continues to present the most comprehensive and readable introduction to this core computer science topic. This version of the book features the RISC-V open source instruction set architecture, the first open source architecture designed for use in modern computing environments such as cloud computing, mobile devices, and other embedded systems. Readers will enjoy an online companion website that provides advanced content for further study, appendices, glossary, references, links to software tools, and more.

  • Computer Vision for Microscopy Image Analysis

    • 1st Edition
    • Mei Chen
    • English
    Are you a computer scientist working on image analysis? Are you a biologist seeking tools to process the microscopy data from image-based experiments? Computer Vision for Microscopy Image Analysis provides a comprehensive and in-depth discussion of modern computer vision techniques, in particular deep learning, for microscopy image analysis that will advance your efforts.Progress in imaging techniques has enabled the acquisition of large volumes of microscopy data and made it possible to conduct large-scale, image-based experiments for biomedical discovery. The main challenge and bottleneck in such experiments is the conversion of "big visual data" into interpretable information.Visual analysis of large-scale microscopy data is a daunting task. Computer vision has the potential to automate this task. One key advantage is that computers perform analysis more reproducibly and less subjectively than human annotators. Moreover, high-throughput microscopy calls for effective and efficient techniques as there are not enough human resources to advance science by manual annotation.This book articulates the strong need for biologists and computer vision experts to collaborate to overcome the limits of human visual perception, and devotes a chapter each to the major steps in analyzing microscopy images, such as detection and segmentation, classification, tracking, and event detection.

  • Computer Organization and Design MIPS Edition

    The Hardware/Software Interface
    • 6th Edition
    • David A. Patterson + 1 more
    • English
    Computer Organization and Design: The Hardware/Software Interface, Sixth Edition, the leading, award-winning textbook from Patterson and Hennessy used by more than 40,000 students per year, continues to present the most comprehensive and readable introduction to this core computer science topic. Improvements to this new release include new sections in each chapter on Domain Specific Architectures (DSA) and updates on all real-world examples that keep it fresh and relevant for a new generation of students.

  • Advances in Delay-Tolerant Networks (DTNs)

    Architecture and Enhanced Performance
    • 2nd Edition
    • Joel J.P.C. Rodrigues
    • English
    Advances in Delay-Tolerant Networks: Architecture and Enhanced Performance, Second Edition provides an important overview of delay-tolerant networks (DTNs) for researchers in electronics, computer engineering, telecommunications and networking for those in academia and R&D in industrial sectors. Part I reviews the technology involved and the prospects for improving performance, including different types of DTN and their applications, such as satellite and deep-space communications and vehicular communications. Part II focuses on how the technology can be further improved, addressing topics, such as data bundling, opportunistic routing, reliable data streaming, and the potential for rapid selection and dissemination of urgent messages. Opportunistic, delay-tolerant networks address the problem of intermittent connectivity in a network where there are long delays between sending and receiving messages, or there are periods of disconnection.

  • Quantitative Magnetic Resonance Imaging

    • 1st Edition
    • Volume 1
    • Nicole Seiberlich + 6 more
    • English
    Quantitative Magnetic Resonance Imaging is a ‘go-to’ reference for methods and applications of quantitative magnetic resonance imaging, with specific sections on Relaxometry, Perfusion, and Diffusion.Each section will start with an explanation of the basic techniques for mapping the tissue property in question, including a description of the challenges that arise when using these basic approaches. For properties which can be measured in multiple ways, each of these basic methods will be described in separate chapters. Following the basics, a chapter in each section presents more advanced and recently proposed techniques for quantitative tissue property mapping, with a concluding chapter on clinical applications. The reader will learn: The basic physics behind tissue property mapping How to implement basic pulse sequences for the quantitative measurement of tissue properties The strengths and limitations to the basic and more rapid methods for mapping the magnetic relaxation properties T1, T2, and T2* The pros and cons for different approaches to mapping perfusion The methods of Diffusion-weighted imaging and how this approach can be used to generate diffusion tensor maps and more complex representations of diffusion How flow, magneto-electric tissue property, fat fraction, exchange, elastography, and temperature mapping are performed How fast imaging approaches including parallel imaging, compressed sensing, and Magnetic Resonance Fingerprinting can be used to accelerate or improve tissue property mapping schemes How tissue property mapping is used clinically in different organs

  • Trends in Deep Learning Methodologies

    Algorithms, Applications, and Systems
    • 1st Edition
    • Vincenzo Piuri + 3 more
    • English
    Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful computational models. Chapters elaborate on these models which have shown significant success in dealing with massive data for a large number of applications, given their capacity to extract complex hidden features and learn efficient representation in unsupervised settings. Chapters investigate deep learning-based algorithms in a variety of application, including biomedical and health informatics, computer vision, image processing, and more. In recent years, many powerful algorithms have been developed for matching patterns in data and making predictions about future events. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. Deep learning methods can deal with multiple levels of representation in which the system learns to abstract higher level representations of raw data. Earlier, it was a common requirement to have a domain expert to develop a specific model for each specific application, however, recent advancements in representation learning algorithms allow researchers across various subject domains to automatically learn the patterns and representation of the given data for the development of specific models.

  • Strategy, Leadership, and AI in the Cyber Ecosystem

    The Role of Digital Societies in Information Governance and Decision Making
    • 1st Edition
    • Hamid Jahankhani + 4 more
    • English
    Strategy, Leadership and AI in the Cyber Ecosystem investigates the restructuring of the way cybersecurity and business leaders engage with the emerging digital revolution towards the development of strategic management, with the aid of AI, and in the context of growing cyber-physical interactions (human/machine co-working relationships). The book explores all aspects of strategic leadership within a digital context. It investigates the interactions from both the firm/organization strategy perspective, including cross-functional actors/stakeholders who are operating within the organization and the various characteristics of operating in a cyber-secure ecosystem. As consumption and reliance by business on the use of vast amounts of data in operations increase, demand for more data governance to minimize the issues of bias, trust, privacy and security may be necessary. The role of management is changing dramatically, with the challenges of Industry 4.0 and the digital revolution. With this intelligence explosion, the influence of artificial intelligence technology and the key themes of machine learning, big data, and digital twin are evolving and creating the need for cyber-physical management professionals.

  • Data Stewardship

    An Actionable Guide to Effective Data Management and Data Governance
    • 2nd Edition
    • David Plotkin
    • English
    Data stewards in any organization are the backbone of a successful data governance implementation because they do the work to make data trusted, dependable, and high quality. Since the publication of the first edition, there have been critical new developments in the field, such as integrating Data Stewardship into project management, handling Data Stewardship in large international companies, handling "big data" and Data Lakes, and a pivot in the overall thinking around the best way to align data stewardship to the data—moving from business/organizatio... function to data domain. Furthermore, the role of process in data stewardship is now recognized as key and needed to be covered.Data Stewardship, Second Edition provides clear and concise practical advice on implementing and running data stewardship, including guidelines on how to organize based on organizational/compa... structure, business functions, and data ownership. The book shows data managers how to gain support for a stewardship effort, maintain that support over the long-term, and measure the success of the data stewardship effort. It includes detailed lists of responsibilities for each type of data steward and strategies to help the Data Governance Program Office work effectively with the data stewards.

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