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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.

  • 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. Sections cover fundamental concepts, including machine learning, deep learning, centralized learning, and distributed learning processes. The book then progresses to coverage of 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.Federated Learning has become an increasingly important machine learning technique because it introduces local data analysis within clients and requires exchange of only model parameters between clients and servers, hence the addition of this new release is ideal for those interested in the topics presented.

  • 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.

  • Pioneering Autonomous Technology: A Deep Dive into Hyper Automation

    • 1st Edition
    • Volume 143
    • English
    Pioneering Autonomous Technology: A Deep Dive into Hyper Automation, Volume 143 in the Advances in Computers series, showcases the transformative role of artificial intelligence, deep learning, and machine learning in creating safer, more efficient, and socially inclusive environments. This volume explores how autonomous technologies are reshaping healthcare, transportation, agriculture, and urban living. Chapters cover important topics such as a Survey on Deep Learning Based Autonomous Medical Diagnosis Models for Chronic Disease Identification, Human-Robot Interaction: Ensuring Safe and Effective Coordination, Blazing Trails: Cutting-Edge Technologies Revolutionizing Forest Fire Screening, Connected Communities: Fostering Social Inclusion and Equity in Smart Cities through IoT Integration, and much more.Additional chapters cover a Preliminary Study of Retinal Biomarkers Detection on Fundus Images for the Diagnosis of Alzheimer’s and Parkinson’s Diseases, Deep Learning Driven Classification of Sweet Lime Leaves: A Superior CNN Approach for Agricultural Automation, Machine Learning in Healthcare: Advancements, Applications, and Challenges, Feature Extraction and Object Recognition in Autonomous Systems, The Future of Autonomous Vehicles: Industry Trends, Technologies, and Challenges, Autonomous Systems: Shaping the Future of Industries and Transportation, and many other topics that will be of interest to readers.

  • Data Compression for Data Mining Algorithms

    • 1st Edition
    • Xiaochun Wang
    • English
    Data Compression for Data Mining Algorithms tackles the important problems in the design of more efficient data mining algorithms by way of data compression techniques and provides the first systematic and comprehensive description of the relationships between data compression mechanisms and the computations involved in data mining algorithms. Data mining algorithms are powerful analytical techniques used across various disciplines, including business, engineering, and science. However, in the big data era, tasks such as association rule mining and classification often require multiple scans of databases, while clustering and outlier detection methods typically depend on Euclidean distance for similarity measures, leading to high computational costs.Data Compression for Data Mining Algorithms addresses these challenges by focusing on the scalarization of data mining algorithms, leveraging data compression techniques to reduce dataset sizes and applying information theory principles to minimize computations involved in tasks such as feature selection and similarity computation. The book features the latest developments in both lossless and lossy data compression methods and provides a comprehensive exposition of data compression methods for data mining algorithm design from multiple points of view.Key discussions include Huffman coding, scalar and vector quantization, transforms, subbands, wavelet-based compression for scalable algorithms, and the role of neural networks, particularly deep learning, in feature selection and dimensionality reduction. The book’s contents are well-balanced for both theoretical analysis and real-world applications, and the chapters are well organized to compose a solid overview of the data compression techniques for data mining. To provide the reader with a more complete understanding of the material, projects and problems solved with Python are interspersed throughout the text.

  • Distributed AI in the Modern World

    Technical and Social Aspects of Interacting Intelligent Agents
    • 1st Edition
    • Andrei Olaru + 3 more
    • English
    Distributed AI in the Modern World: Technical and Social Aspects of Interacting Intelligent Agents presents state-of-the-art insights into the various forms of distribution of artificial intelligence, with practical application instances. Sections provide readers with practical solutions at an architectural level, with solutions presented on the distribution of the learning process and the utilization of machine learning models in a distributed system, tools that enable the distribution and interaction of artificial learning entities, how multi-agent systems and machine learning can be combined, the physical embodiment of intelligent agents, and the interaction of intelligent computing units bound to physical space.Following sections emphasize the challenges that are common to all scenarios and solutions that apply in a wider range of cases. This book does not analyze the internal workings of machine learning models (for instance, in the case of multi-agent reinforcement learning), but instead provides readers with an overview of the challenges brought by the need of artificially intelligent entities to interact with other entities and with their environments, along with practical solutions at an architectural level.

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