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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.

  • Current Molecular Targets of Heterocyclic Compounds for Cancer Therapy

    • 1st Edition
    • April 10, 2024
    • Vivek Asati + 1 more
    • English
    Current Molecular Targets of Heterocyclic Compounds for Cancer Therapy discusses recently developed treatments based on molecular targets which are genetically altered in cancer cells and are essential for tumor development and survival. Considerable research effort has been devoted to the development of targeted drugs that inhibit the action of pathogenic kinases, and clinical studies performed so far have validated the positive effects of kinase inhibitors for cancer treatment. Each chapter discusses a molecular target, such as ALK2, ATR, CK, Src-Abl, EGFR, Fyn-Blk-Lyn, IGFs, and PAK1.The book's chapters are written by experts who actively work on the targets to help readers fully understand how they can be used. This is a valuable resource for cancer researchers, oncologists, graduate students and members of the biomedical field who are interested in the potential of novel cancer therapies based on molecular targets.

  • Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment

    • 1st Edition
    • April 4, 2024
    • Zhijun Chen
    • English
    Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment not only supports the development of Intelligent & Connected Transportation, but also promotes the landing application of autonomous driving. Areas covered include the fusion target perception method based on vehicle vision and millimeter wave radar, cross-field of view object perception method, vehicle motion recognition method based on vehicle road fusion information, vehicle trajectory prediction method based on improved hybrid neural network and driving map construction driven by road perception fusion are introduced in this book.Benefiting from the development of computer technique, the advanced machine learning and artificial intelligence theories are used by this book to show readers the construction process of the Autonomous Driving Map.

  • Computational Intelligence and Blockchain in Complex Systems

    System Security and Interdisciplinary Applications
    • 1st Edition
    • March 26, 2024
    • Fadi Al-Turjman
    • English
    Computational Intelligence and Blockchain in Complex Systems: System Security and Interdisciplinary Applications provides readers with a guide to understanding the dynamics of AI, machine learning, and computational intelligence in blockchain, and how these rapidly developing technologies are revolutionizing a variety of interdisciplinary research fields and applications. This book examines the role of computational intelligence and machine learning in the development of algorithms to deploy blockchain technology across a number of applications, including healthcare, insurance, smart grid, smart contracts, digital currency, precision agriculture, and supply chain. The authors cover the unique and developing intersection between cyber security and blockchain in modern networks, as well as in-depth studies on cybersecurity challenges and multidisciplinary methods in modern blockchain networks. Readers will find mathematical equations throughout the book as part of the underlying concepts and foundational methods, especially the complex algorithms involved in blockchain security aspects for hashing, coding, and decoding. This book also provides readers with the most in-depth technical guide to the intersection of computational intelligence and blockchain, two of the most important technologies for the development of next-generation complex systems

  • Smart Spaces

    • 1st Edition
    • March 18, 2024
    • Zhihan Lyu
    • English
    Smart Spaces covers the latest concepts and technologies surrounding smart spaces, providing technical personnel engaged in smart space related research and industries a more in-depth understanding of smart spaces. This book can be used as a reference for practicing this emerging discipline, but it will also be useful for researchers, scientists, developers, practitioners, and graduate students working in the fields of smart spaces and artificial intelligence. It combines the study of working or living spaces with computing, information equipment, and multimodal sensing devices, and with natural and convenient interactive interfaces to support how people can easily obtain services from computer systems.People's work and life in smart spaces use computer systems; it is a process of uninterrupted interaction between people and the computer system. In this process, the computer is no longer just an information processing tool that passively executes explicit human operation commands but a collaborator with people to complete tasks – a partner to human beings. International research on smart spaces is quite extensive, which shows the important role of smart spaces in ubiquitous computing research.

  • Object-Oriented Analysis and Design for Information Systems

    Modeling with BPMN, OCL, IFML, and Python
    • 2nd Edition
    • March 16, 2024
    • Raul Sidnei Wazlawick
    • English
    Object-Oriented Analysis and Design for Information Systems, Second Edition clearly explains real object-oriented programming in practice. Expert author Raul Sidnei Wazlawick explains concepts such as object responsibility, visibility, and the real need for delegation in detail. The object-oriented code generated by using these concepts in a systematic way is concise, organized and reusable.The patterns and solutions presented in this book are based in research and industrial applications. You will come away with clarity regarding processes and use cases and a clear understanding of how to expand a use case. Wazlawick clearly explains how to build meaningful sequence diagrams. Object-Oriented Analysis and Design for Information Systems illustrates how and why building a class model is not just placing classes into a diagram. You will learn the necessary organizational patterns so that your software architecture will be maintainable. The Second Edition includes all new content shifting the focus of the book to agile software development, including Scrum software project management, BPMN diagrams, user stories, and Python code examples.

  • Artificial Intelligence for Medicine

    An Applied Reference for Methods and Applications
    • 1st Edition
    • March 14, 2024
    • Shai Ben- David + 5 more
    • English
    Artificial Intelligence for Medicine: An Applied Reference for Methods and Applications introduces readers to the methodology and AI/ML algorithms as well as cutting-edge applications to medicine, such as cancer, precision medicine, critical care, personalized medicine, telemedicine, drug discovery, molecular characterization, and patient mental health. Research in medicine and tailored clinical treatment are being quickly transformed by artificial intelligence (AI) and machine learning (ML). The content in this book is tailored to the reader's needs in terms of both type and fundamentals. It covers the current ethical issues and potential developments in this field.This book will be beneficial for academics, professionals in the IT industry, educators, students, and anyone else involved in the use and development of AI in the medical field.

  • Data Fusion Techniques and Applications for Smart Healthcare

    • 1st Edition
    • March 12, 2024
    • Amit Kumar Singh + 1 more
    • English
    Data Fusion Techniques and Applications for Smart Healthcare covers cutting-edge research from both academia and industry, with a particular emphasis on recent advances in algorithms and applications that involve combining multiple sources of medical information. The book can be used as a reference for practicing engineers, scientists, and researchers, but it will also be useful for graduate students and practitioners from government and industry as well as healthcare technology professionals working on state-of-the-art information fusion solutions for healthcare applications.Medical data exists in several formats, from structured data and medical reports to 1D signals, 2D images, 3D volumes, or even higher dimensional data such as temporal 3D sequences. Healthcare experts can make auscultation reports in text format; electrocardiograms can be printed in time series format, X-rays saved as images; volume can be provided through angiography; temporal information by echocardiograms, and 4D information extracted through flow MRI.

  • Sequences and the de Bruijn Graph

    Properties, Constructions, and Applications
    • 1st Edition
    • February 29, 2024
    • Tuvi Etzion
    • English
    Sequences and the de Bruijn Graph: Properties, Constructions, and Applications explores the foundations of theoretical mathematical concepts and their important applications to computer science, electrical engineering, and bioinformatics. The book introduces the various concepts, ideas, and techniques associated with the use of the de Bruijn Graph, providing comprehensive coverage of sequence classification, one-dimensional and two-dimensional properties, constructions, and interconnection networks. This book is suitable for researchers, graduate students, professors, and professionals working in the fields of applied mathematics, electrical engineering, computer science, and bioinformatics.The de Bruijn graph was defined in 1946 to enumerate the number of closed sequences where each n-tuple appears exactly once as a window in a sequence. Through the years, the graph and its sequences have found numerous applications – in space technology, wireless communication, cryptography, parallel computation, genome assembly, DNA storage, and microbiome research, among others.

  • The Metaverse and Smart Cities

    Urban Environments in the Age of Digital Connectivity
    • 1st Edition
    • February 28, 2024
    • Zaheer Allam + 1 more
    • English
    The Metaverse and Smart Cities: Urban Environments in the Age of Digital Connectivity explores the intersection between the rapidly growing metaverse and the future of cities. The metaverse is a virtual world that is increasingly gaining attention as a new frontier for human interaction and commerce. At the same time, cities are undergoing significant transformation as they face challenges such as population growth, urbanization, and environmental degradation. Urban planners and city administrators will find valuable insights on how the metaverse can be integrated into the planning and development of smart, sustainable, and future cities.The book begins with an introduction to the concepts and technology of the metaverse as well as its history. It then sheds light on the current and future challenges and opportunities that the metaverse presents to cities and the quality of life of urban dwellers. It delves into the ways in which the metaverse can change cities, both in terms of their physical and virtual environments, and the impact it can have on the lives of those who live in them. It brings together the latest research and perspectives from experts in the fields of virtual reality, urban planning, and sustainability, to provide a comprehensive and up-to-date picture of this rapidly evolving field.

  • Machine Learning with Noisy Labels

    Definitions, Theory, Techniques and Solutions
    • 1st Edition
    • February 23, 2024
    • Gustavo Carneiro
    • English
    Machine Learning and Noisy Labels: Definitions, Theory, Techniques and Solutions provides an ideal introduction to machine learning with noisy labels that is suitable for senior undergraduates, post graduate students, researchers and practitioners using, and researching, machine learning methods. Most of the modern machine learning models based on deep learning techniques depend on carefully curated and cleanly labeled training sets to be reliably trained and deployed. However, the expensive labeling process involved in the acquisition of such training sets limits the number and size of datasets available to build new models, slowing down progress in the field. This book defines the different types of label noise, introduces the theory behind the problem, presents the main techniques that enable the effective use of noisy-label training sets, and explains the most accurate methods.

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