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Showing 1 - 10 of 41 results

  •  Preorder
    Expected by: 01 December 2022

    Trustworthy Autonomic Computing

    Thaddeus Eze  2022

    This book covers challenges and solutions of autonomic computing trustworthiness from methods and techniques to achieve consistent and reliable system self-management. This is an ideal tutorial guide for independent study with simple and well documented diagrams to explain techniques and processes.

  •  Preorder
    Expected by: 01 October 2022

    Streaming Analytics

    Concepts, architectures, platforms, use cases and applications  
    Pethuru Raj, Chellammal Surianarayanan, Koteeswaran Seerangan, George Ghinea  2022

    In this book, the authors articulate the challenges associated with streaming data and analytics, describe data analytics algorithms and approaches, present edge and fog computing concepts and technologies and show how streaming analytics can be accomplished in edge device clouds. They also delineate several industry use cases.

  •  Preorder
    Expected by: 01 October 2022

    Demystifying Graph Data Science

    Graph algorithms, analytics methods, platforms, databases, and use cases  
    Pethuru Raj, Abhishek Kumar, Vicente García Díaz, Nachamai Muthuraman Sundar  2022

    Graph analytics are being empowered through novel analytics techniques to explore and pinpoint beneficial relationships between different entities such as organizations, people and transactions. This edited book presents the various aspects and importance of graph data science, with contributions by authors from academia and industry.

  •  Preorder
    Expected by: 31 August 2022

    Graphical Programming Using LabVIEW™

    Fundamentals and advanced techniques  
    Julio César Rodríguez-Quiñonez, Oscar Real-Moreno  2022

    Starting with the concepts of data flow and concurrent programming, the authors cover the development of state machines, event programming and consumer producer systems using LabVIEW™ programming for instrumentation and automation systems. The book is a useful resource for undergraduate and graduate students and entry-level engineers.

  •  In stock

    Computer Vision and Recognition Systems Using Machine and Deep Learning Approaches

    Fundamentals, technologies and applications  
    Chiranji Lal Chowdhary, Mamoun Alazab, Ankit Chaudhary, Saqib Hakak, Thippa Reddy Gadekallu  2021

    Written by a team of International experts, this edited book covers state-of-the-art research in the fields of computer vision and recognition systems from fundamental concepts to methodologies and technologies and real-world applications. The book will be useful for industry and academic researchers, scientists and engineers.

  •  In stock

    Handbook of Big Data Analytics

    Volume 1: Methodologies  
    Vadlamani Ravi, Aswani Kumar Cherukuri  2021

    This comprehensive edited 2-volume handbook provides a unique platform for researchers, engineers, developers, educators and advanced students in the field of Big Data analytics. The first volume presents methodologies that support Big Data analytics, while the second volume offers a wide range of Big Data analytics applications.

  •  In stock

    Handbook of Big Data Analytics

    Volume 2: Applications in ICT, security and business analytics  
    Vadlamani Ravi, Aswani Kumar Cherukuri  2021

    This comprehensive edited 2-volume handbook provides a unique platform for researchers, engineers, developers, educators and advanced students in the field of Big Data analytics. The first volume presents methodologies that support Big Data analytics, while the second volume offers a wide range of Big Data analytics applications.

  •  In stock

    ReRAM-based Machine Learning

    Hao Yu, Leibin Ni, Sai Manoj Pudukotai Dinakarrao  2021

    Serving as a bridge between researchers in the computing domain and computing hardware designers, this book presents ReRAM techniques for distributed computing using IMC accelerators, ReRAM-based IMC architectures for machine learning (ML) and data-intensive applications, and strategies to map ML designs onto hardware accelerators.