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Elsevier

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.

  • Intelligent Cyber-Physical Systems for Sustainable Healthcare

    • 1st Edition
    • Vandana Bajaj + 5 more
    • English
    Intelligent Cyber-Physical Systems for Sustainable Healthcare addresses the integration of emerging technologies like Virtual Reality, Smart Robotics, and Human-Computer Interaction, which are crucial for maximizing digital health's potential. The book includes case studies that highlight challenges faced by medical practitioners and industry professionals, providing valuable insights for designing sustainable iCPS solutions. Aimed at biomedical engineers, researchers, and industry professionals, it offers guidance for developing practical applications in sustainable healthcare. Additionally, shared, cross-disciplinary experiences assist engineers with less clinical expertise in enhancing healthcare applications in the intelligent digital health sector. Overall, case studies illustrate past challenges in the healthcare industry and present effective solutions to overcome them, making the book a comprehensive resource for advancing sustainable healthcare practices.

  • Understanding Models Developed with AI

    Including Applications with Python and MATLAB Code
    • 1st Edition
    • Ömer Faruk ErtuÄŸrul + 2 more
    • English
    Understanding Models Developed by AI: Including Applications with Python and MATLAB Code is a comprehensive guide on the intricacies of AI models and their real-world applications. The book demystifies complex AI methodologies by providing clear explanations and practical examples that are reinforced with Python and MATLAB program codes. Its content structure emphasizes a practical, applications-driven approach to understanding AI models, with hands-on coding examples throughout each chapter. Readers will find the tools they need to build AI models, along with the knowledge to make these models accessible and interpretable to stakeholders, thus fostering trust and reliability in AI systems.As the primary issues with the adoption of AI/ML models are reliability, transparency, interpretation of results, and bias (data and algorithm) management, this resource give researchers and developers what they need to be able to not only implement AI models, but also interpret and explain them. This is crucial in industries where decision-making processes must be transparent and understandable.

  • RISC-V System-on-Chip Design

    • 1st Edition
    • David Harris + 3 more
    • English
    RISC-V Microprocessor System-On-Chip Design is written to be accessible to an advanced undergraduate audience with limited background. It explains concepts from operating systems, VLSI, and memory systems as necessary, and High school mathematics is sufficient preparation for most of the book, although the floating point and division chapters will be primarily of interest to those with a curiosity about computer arithmetic. Like Harris and Harris’s Digital Design and Computer Architecture textbooks, this book will appeal to students with easy-to-read and complete explanations, sidebars, and occasional humor and cartoons.It comes with an open-source implementation and will include end-of-chapter problems to extend the RISC-V processor in various ways. Ancillary materials include a GitHub repository with complete open-source SystemVerilog code, validation code in C and assembly language, and code for benchmarking and booting Linux.

  • Foundations of Digital Twins

    • 1st Edition
    • Tuan Anh Nguyen + 2 more
    • English
    Foundations of Digital Twins explains the fundamentals of digital twins, how digital twin technologies can gather real world data using the sensor networks that comprise the Internet of Things, and how that data can be sorted, analyzed, and used to improve services and increase sustainability. Structured in five sections, the book begins with an introductory overview of each technology, establishing a clear understanding of their individual roles and their potential when combined. The second section delves into data acquisition, featuring advanced sensors, drones, robots and actuators. Part Three considers data exchange and security, focusing on CPS, the internet of things, and blockchain.Part Four looks at how digital twins can impact on data computing, such as video streaming, cloud computing, fog computing and edge-computing. The final section explores the future opportunities and risks of adopting advanced technologies in this evolving field, including artificial intelligence, the ethical issues concerned when collecting and using data, and the security implications.

  • AI and Computational Intelligence for Environmental Sustainability

    • 1st Edition
    • Rakesh Kumar + 2 more
    • English
    Climate change, biodiversity loss, resource depletion, and pollution are intensifying. Addressing these global issues requires fresh perspectives and cutting-edge solutions that integrate AI with environmental sustainability. AI and computational intelligence technologies are evolving at an unprecedented pace, offering new tools and methodologies for tackling environmental challenges. Yet existing resources often fail to capture the latest breakthroughs and interdisciplinary approaches needed to harness these innovations effectively.AI and Computational Intelligence for Environmental Sustainability showcases the potential of artificial intelligence and computational intelligence in tackling critical environmental challenges. As the urgency to combat climate change, optimize resource utilization, and promote sustainable practices grows, this book provides a comprehensive resource that bridges the gap between AI research and its practical applications in environmental sustainability, and offers insights into the latest developments and methodologies. It highlights real-world applications and case studies to inspire researchers, developers, and policymakers to create and implement AI-driven solutions for a more sustainable future, foster collaboration by bringing together experts from diverse fields to share knowledge and foster interdisciplinary collaboration in the pursuit of environmental sustainability. It also addresses the ethical and practical challenges of applying AI in sustainability, advocating for responsible AI development and low-energy computing practices.

  • GeoAI for Earth Observation Imagery

    Fundamentals and Practical Applications
    • 1st Edition
    • Dalton Lunga + 1 more
    • English
    GeoAI for Earth Observation Imagery: Fundamentals and Practical Applications comprehensively covers methodologies of AI and Machine Learning applications of image processing for Earth Observation (EO) Imagery. As traditional image processing methods face challenges with handling vast volumes of EO imagery, leading to efficiencies and limitations when extracting meaningful insights, AI-driven approaches can enhance the efficiency, accuracy, and scalability of image processing. Chapters cover essential methodologies including atmospheric compensation, image enhancement techniques like deblurring and superresolution, and advanced analysis methods such as semantic segmentation and object detection.Cutting-ed... approaches to computing, automating, and optimizing image processing tasks are also covered. Additionally, emerging trends in GeoAi and their implication on future research are reviewed. The book serves as an essential guide for navigating the complexities of spatial data and equips readers with knowledge to enhance their analytical capabilities.

  • Federated Learning

    Foundations and Applications
    • 1st Edition
    • Rajkumar Buyya + 2 more
    • English
    Federated Learning: Foundations and Applications provides a comprehensive guide to the foundations, architectures, systems, security, privacy, and applications of federated learning. Federated learning has become an increasingly important machine learning technique because it introduces local data analysis within clients and requires exchanging only model parameters between clients and servers. This book covers the fundamental concepts of federated learning, including machine learning, deep learning, centralized learning, and distributed learning processes. The book then progresses to cover the architectures, algorithms, and system models of federated learning, as well as security, privacy, and energy-efficiency techniques. Finally, the book presents various applications of federated learning through real-world case studies illustrating both centralized and decentralized federated learning.

  • Digital Outcasts

    Moving Technology Forward without Leaving People Behind
    • 2nd Edition
    • Kel Smith
    • English
    Digital Outcasts: Moving Technology Forward without Leaving People Behind, Second Edition comprehensively explores inclusive design in human-computer interaction. The book examines the real-life experiences of people with disabilities as they navigate systemic barriers in employment, education, healthcare, and social connectivity. This new edition covers the intersectionality of disability with other forms of economic and political discrimination, uncovering how biases related to race, gender, and ability are reflected in language models and AI algorithms. With digital access a foundational element of human existence, the consequences of exclusion are far-reaching and increasingly urgent.Citing case studies in law, creative arts, and social science, this updated edition also examines the historical and emergent impact people with disabilities have on culture and industry. Digital Outcasts emphases that disability has long served as a powerful catalyst for design innovation, driving transformational benefit for consumers of all abilities and backgrounds. Taking into account new legal and technological perspectives, this revision stands as an update on the progress we have made—and how far we have yet to go.

  • Foundations of Human-Computer Interaction

    Designing for Cognitive Alignment
    • 1st Edition
    • Robert Atkinson
    • English
    Foundations of Human-Computer Interaction: Designing for Cognitive Alignment reframes human-computer interaction (HCI), usability, and user-centered design by focusing on the conditions under which cognition stabilizes over time. It provides an integrated account of HCI by bringing together cognitive science, neuroscience, and design principles to explain how systems shape perception, regulate attention, and support stable reasoning across repeated encounters. This approach ensures that graduate and undergraduate students not only understand core theoretical frameworks but also recognize how design decisions influence reasoning, decision-making, and cognitive effort in real-world contexts. The book emphasizes structured learning and iterative design processes, making the material accessible to both novices and advanced learners. It also addresses contemporary challenges such as AI-driven systems, adaptive interfaces, and large-scale personalization, offering a framework for understanding how misalignment emerges as instability—seen in repetition, delayed decisions, fragmented attention, and unresolved effort—and how design can support clarity, recovery, and trust in responsible ways

  • Smart Wearable IoT

    Principles and Implementation of Development Modules with Wireless Biomedical SOC
    • 1st Edition
    • Shuenn-Yuh Lee + 1 more
    • English
    Smart Wearable IoT: Principles and Implementation of Development Modules with Wireless Biomedical SoC focuses on the development of intelligent wearable technology integrated with the Internet and various platforms. The book provides detailed guidance on building a user-friendly development platform that features intelligent wearable systems, including bio-signal SoCs/modules, user-friendly websites/apps, and artificial intelligence (AI) systems on edge/cloud. By exploring specific case studies, such as the ECG-based fatigue analysis system, readers will gain fundamental knowledge in biosignal acquisition and processing.This hands-on approach enables users to understand the integration of digital signal processing and artificial intelligence in analyzing physiological data, ultimately enhancing their skills in developing innovative wearable solutions.

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