Skip to main content

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.

261-270 of 2576 results in All results

Computer Organization and Design MIPS Edition

  • 6th Edition
  • November 2, 2020
  • David A. Patterson + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 2 0 1 0 9 - 1
  • 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.

Data Stewardship

  • 2nd Edition
  • October 31, 2020
  • David Plotkin
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 2 2 1 3 2 - 7
  • eBook
    9 7 8 - 0 - 1 2 - 8 2 2 1 6 7 - 9
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/organizational 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/company 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.

Computer Networks

  • 6th Edition
  • October 1, 2020
  • Larry L. Peterson + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 8 2 0 0 - 0
  • 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. 

The Art of Multiprocessor Programming

  • 2nd Edition
  • September 8, 2020
  • Maurice Herlihy + 3 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 4 1 5 9 5 0 - 1
  • eBook
    9 7 8 - 0 - 1 2 - 3 9 1 4 0 6 - 4
The Art of Multiprocessor Programming, Second Edition, provides users with an authoritative guide to multicore programming. This updated edition introduces higher level software development skills relative to those needed for efficient single-core programming, and includes comprehensive coverage of the new principles, algorithms, and tools necessary for effective multiprocessor programming. The book is an ideal resource for students and professionals alike who will benefit from its thorough coverage of key multiprocessor programming issues.

Fault-Tolerant Systems

  • 2nd Edition
  • September 1, 2020
  • Israel Koren + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 8 1 0 5 - 8
  • eBook
    9 7 8 - 0 - 1 2 - 8 1 8 1 0 6 - 5
Fault-Tolerant Systems, Second Edition, is the first book on fault tolerance design utilizing a systems approach to both hardware and software. No other text takes this approach or offers the comprehensive and up-to-date treatment that Koren and Krishna provide. The book comprehensively covers the design of fault-tolerant hardware and software, use of fault-tolerance techniques to improve manufacturing yields, and design and analysis of networks. Incorporating case studies that highlight more than ten different computer systems with fault-tolerance techniques implemented in their design, the book includes critical material on methods to protect against threats to encryption subsystems used for security purposes. The text’s updated content will help students and practitioners in electrical and computer engineering and computer science learn how to design reliable computing systems, and how to analyze fault-tolerant computing systems.

Intelligent Data Security Solutions for e-Health Applications

  • 1st Edition
  • August 26, 2020
  • Amit Kumar Singh + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 9 5 1 1 - 6
  • eBook
    9 7 8 - 0 - 1 2 - 8 1 9 5 3 8 - 3
E-health applications such as tele-medicine, tele-radiology, tele-ophthalmology, and tele-diagnosis are very promising and have immense potential to improve global healthcare. They can improve access, equity, and quality through the connection of healthcare facilities and healthcare professionals, diminishing geographical and physical barriers. One critical issue, however, is related to the security of data transmission and access to the technologies of medical information. Currently, medical-related identity theft costs billions of dollars each year and altered medical information can put a person’s health at risk through misdiagnosis, delayed treatment or incorrect prescriptions. Yet, the use of hand-held devices for storing, accessing, and transmitting medical information is outpacing the privacy and security protections on those devices. Researchers are starting to develop some imperceptible marks to ensure the tamper-proofing, cost effective, and guaranteed originality of the medical records. However, the robustness, security and efficient image archiving and retrieval of medical data information against these cyberattacks is a challenging area for researchers in the field of e-health applications. Intelligent Data Security Solutions for e-Health Applications focuses on cutting-edge academic and industry-related research in this field, with particular emphasis on interdisciplinary approaches and novel techniques to provide security solutions for smart applications. The book provides an overview of cutting-edge security techniques and ideas to help graduate students, researchers, as well as IT professionals who want to understand the opportunities and challenges of using emerging techniques and algorithms for designing and developing more secure systems and methods for e-health applications.

Soft Numerical Computing in Uncertain Dynamic Systems

  • 1st Edition
  • August 19, 2020
  • Tofigh Allahviranloo + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 2 2 8 5 5 - 5
  • eBook
    9 7 8 - 0 - 1 2 - 8 2 2 9 9 4 - 1
Soft Numerical Computing in Uncertain Dynamic Systems is intended for system specialists interested in dynamic systems that operate at different time scales. The book discusses several types of errors and their propagation, covering numerical methods—including convergence and consistence properties and characteristics—and proving of related theorems within the setting of soft computing. Several types of uncertainty representation like interval, fuzzy, type 2 fuzzy, granular, and combined uncertain sets are discussed in detail. The book can be used by engineering students in control and finite element fields, as well as all engineering, applied mathematics, economics, and computer science students. One of the important topics in applied science is dynamic systems and their applications. The authors develop these models and deliver solutions with the aid of numerical methods. Since they are inherently uncertain, soft computations are of high relevance here. This is the reason behind investigating soft numerical computing in dynamic systems. If these systems are involved with complex-uncertain data, they will be more practical and important. Real-life problems work with this type of data and most of them cannot be solved exactly and easily—sometimes they are impossible to solve. Clearly, all the numerical methods need to consider error of approximation. Other important applied topics involving uncertain dynamic systems include image processing and pattern recognition, which can benefit from uncertain dynamic systems as well. In fact, the main objective is to determine the coefficients of a matrix that acts as the frame in the image. One of the effective methods exhibiting high accuracy is to use finite differences to fill the cells of the matrix.

Designing with the Mind in Mind

  • 3rd Edition
  • August 14, 2020
  • Jeff Johnson
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 8 2 0 2 - 4
  • eBook
    9 7 8 - 0 - 1 2 - 8 1 8 2 0 3 - 1
User interface (UI) design rules and guidelines, developed by early HCI gurus and recognized throughout the field, were based on cognitive psychology (study of mental processes such as problem solving, memory, and language), and early practitioners were well informed of its tenets. But today practitioners with backgrounds in cognitive psychology are a minority, as user interface designers and developers enter the field from a wide array of disciplines. HCI practitioners today have enough experience in UI design that they have been exposed to UI design rules, but it is essential that they understand the psychological basis behind the rules in order to effectively apply them. In Designing with the Mind in Mind, best-selling author Jeff Johnson provides designers with just enough background in perceptual and cognitive psychology that UI design guidelines make intuitive sense rather than being just a list of rules to follow.

Advanced Machine Vision Paradigms for Medical Image Analysis

  • 1st Edition
  • August 11, 2020
  • Tapan K. Gandhi + 4 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 1 9 2 9 5 - 5
  • eBook
    9 7 8 - 0 - 1 2 - 8 1 9 2 9 6 - 2
Computer vision and machine intelligence paradigms are prominent in the domain of medical image applications, including computer assisted diagnosis, image guided radiation therapy, landmark detection, imaging genomics, and brain connectomics. Medical image analysis and understanding are daunting tasks owing to the massive influx of multi-modal medical image data generated during routine clinal practice. Advanced computer vision and machine intelligence approaches have been employed in recent years in the field of image processing and computer vision. However, due to the unstructured nature of medical imaging data and the volume of data produced during routine clinical processes, the applicability of these meta-heuristic algorithms remains to be investigated. Advanced Machine Vision Paradigms for Medical Image Analysis presents an overview of how medical imaging data can be analyzed to provide better diagnosis and treatment of disease. Computer vision techniques can explore texture, shape, contour and prior knowledge along with contextual information, from image sequence and 3D/4D information which helps with better human understanding. Many powerful tools have been developed through image segmentation, machine learning, pattern classification, tracking, and reconstruction to surface much needed quantitative information not easily available through the analysis of trained human specialists. The aim of the book is for medical imaging professionals to acquire and interpret the data, and for computer vision professionals to learn how to provide enhanced medical information by using computer vision techniques. The ultimate objective is to benefit patients without adding to already high healthcare costs.

Ascend AI Processor Architecture and Programming

  • 1st Edition
  • July 27, 2020
  • Xiaoyao Liang
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 2 3 4 8 8 - 4
  • eBook
    9 7 8 - 0 - 1 2 - 8 2 3 4 8 9 - 1
Ascend AI Processor Architecture and Programming: Principles and Applications of CANN offers in-depth AI applications using Huawei’s Ascend chip, presenting and analyzing the unique performance and attributes of this processor. The title introduces the fundamental theory of AI, the software and hardware architecture of the Ascend AI processor, related tools and programming technology, and typical application cases. It demonstrates internal software and hardware design principles, system tools and programming techniques for the processor, laying out the elements of AI programming technology needed by researchers developing AI applications. Chapters cover the theoretical fundamentals of AI and deep learning, the state of the industry, including the current state of Neural Network Processors, deep learning frameworks, and a deep learning compilation framework, the hardware architecture of the Ascend AI processor, programming methods and practices for developing the processor, and finally, detailed case studies on data and algorithms for AI.