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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

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
    9 7 8 - 0 - 1 2 - 8 2 1 4 4 2 - 8
  • eBook
    9 7 8 - 0 - 1 2 - 8 2 1 4 5 9 - 6
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.

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
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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
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  • eBook
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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.

Related subjects

Applications

Artificial intelligence

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Computer vision and pattern recognition

Computing milieux

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Hardware and architecture

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