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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

    • Machine Reading Comprehension

      • 1st Edition
      • March 20, 2021
      • Chenguang Zhu
      • English
      • Paperback
        9 7 8 0 3 2 3 9 0 1 1 8 5
      • eBook
        9 7 8 0 3 2 3 9 0 1 1 9 2
      Machine reading comprehension (MRC) is a cutting-edge technology in natural language processing (NLP). MRC has recently advanced significantly, surpassing human parity in several public datasets. It has also been widely deployed by industry in search engine and quality assurance systems. Machine Reading Comprehension: Algorithms and Practice performs a deep-dive into MRC, offering a resource on the complex tasks this technology involves. The title presents the fundamentals of NLP and deep learning, before introducing the task, models, and applications of MRC. This volume gives theoretical treatment to solutions and gives detailed analysis of code, and considers applications in real-world industry. The book includes basic concepts, tasks, datasets, NLP tools, deep learning models and architecture, and insight from hands-on experience. In addition, the title presents the latest advances from the past two years of research. Structured into three sections and eight chapters, this book presents the basis of MRC; MRC models; and hands-on issues in application. This book offers a comprehensive solution for researchers in industry and academia who are looking to understand and deploy machine reading comprehension within natural language processing.

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

      • 1st Edition
      • Volume 121
      • January 23, 2021
      • English
      • Hardback
        9 7 8 0 1 2 8 2 1 9 9 1 1
      • eBook
        9 7 8 0 1 2 8 2 1 9 9 2 8
      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

      • 6th Edition
      • January 20, 2021
      • Larry L. Peterson + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 1 8 2 0 0 0
      • Paperback
        9 7 8 0 1 2 8 2 3 7 1 5 1
      • eBook
        9 7 8 0 1 2 8 1 8 2 0 1 7
      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

      • 2nd Edition
      • December 11, 2020
      • David A. Patterson + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 0 3 3 1 6
      • eBook
        9 7 8 0 1 2 8 2 4 5 5 8 3
      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
      • December 1, 2020
      • Mei Chen
      • English
      • Paperback
        9 7 8 0 1 2 8 1 4 9 7 2 0
      • eBook
        9 7 8 0 1 2 8 1 4 9 7 3 7
      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

      • 6th Edition
      • November 20, 2020
      • David A. Patterson + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 0 1 0 9 1
      • Paperback
        9 7 8 0 1 2 8 2 3 7 1 6 8
      • eBook
        9 7 8 0 1 2 8 2 2 6 7 4 2
      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)

      • 2nd Edition
      • November 20, 2020
      • Joel J.P.C. Rodrigues
      • English
      • Paperback
        9 7 8 0 0 8 1 0 2 7 9 3 6
      • eBook
        9 7 8 0 0 8 1 0 2 7 9 4 3
      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
      • November 18, 2020
      • Nicole Seiberlich + 6 more
      • English
      • Paperback
        9 7 8 0 1 2 8 1 7 0 5 7 1
      • eBook
        9 7 8 0 1 2 8 1 7 0 5 8 8
      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

      • 1st Edition
      • November 12, 2020
      • Vincenzo Piuri + 3 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 2 2 2 6 3
      • eBook
        9 7 8 0 1 2 8 2 3 2 6 8 2
      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

      • 1st Edition
      • November 10, 2020
      • Hamid Jahankhani + 4 more
      • English
      • Paperback
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      • eBook
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      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.

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