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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.

    • Digital Transformation and Equitable Global Health

      • 1st Edition
      • May 15, 2026
      • Arletty Pinel + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 1 4 9 8 1
      • eBook
        9 7 8 0 4 4 3 2 1 4 8 8 2
      Digital Transformation and Equitable Global Health: A Future-Ready Perspective presents a collective body of knowledge and global experiences that demonstrate current status and future trends in the use of exponential technologies and their potential for poverty reduction, improving health outcomes, strengthening health systems, and transforming traditional development aid structures. The book uses a translational innovation perspective to guide the reader—regardless of their area of expertise—on the rationale behind the co-creation of human-centered, affordable, and sustainable digital solutions.It addresses the interest of professionals from multiple areas (e.g., technology, health, social development, global financing), and it is a valuable resource for professionals, social scientists, practitioners, researchers, instructors, and undergraduate and graduate students interested in understanding the challenges and complexities of global public health and the applied uses of health technologies for equitable access to primary health care and universal health coverage.
    • Synthetic Media, Deepfakes, and Cyber Deception

      • 1st Edition
      • May 1, 2026
      • Cameron H. Malin + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 3 8 8 7 1
      • eBook
        9 7 8 0 4 4 3 2 3 8 8 8 8
      Synthetic Media, Deepfakes, and Cyber Deception: Attacks, Analysis, and Defenses introduces the only analytical Synthetic Media Analysis Framework (SMAF) to help describe cyber threats and help security professionals anticipate and analyze attacks. This framework encompasses seven dimensions: Credibility, Control, Medium, Interactivity, Familiarity, Intended Target, and Evocation. Synthetic media is a broad term that encompasses the artificial manipulation, modification, and production of information, covering a spectrum from audio-video deepfakes to text-based chatbots. Synthetic media provides cyber attackers and scammers with a game-changing advantage over traditional ROSE attacks because they have the potential to convincingly impersonate close associates through text, imagery, voice, and video.This burgeoning threat has yet to be meaningfully addressed through any written treatment on the topic. The book is co-authored by three cyber influence and deception experts who have gained deep knowledge and experience on the topic through diverse, true operational pathways and backgrounds. The diversity and perspectives of the author team makes the content in the book the broadest and deepest treatment of synthetic media attacks available to readers.
    • Advances in Medical Imaging

      • 1st Edition
      • May 1, 2026
      • Dilber Uzun Ozsahin + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 8 9 6 7 5
      • eBook
        9 7 8 0 4 4 3 2 8 9 6 8 2
      Medical Imaging Application in Health Assessment and Disease Management is an all-encompassing book that explores the transformative power of medical imaging in various fields of medicine. It showcases the latest advancements and applications of medical imaging modalities, ranging from neurology and oncology to audiology and osteoporosis. The book highlights the role of medical imaging in understanding and treating neurological conditions, assessing bone health, unraveling hearing disorders, and diagnosing and treating oncological conditions. It also delves into the potential of artificial intelligence and machine learning in improving cancer diagnosis and treatment. The book explores the use of medical imaging in observing mental health conditions such as autism spectrum disorder and stress-related behavioral changes. This comprehensive resource is essential for researchers and professional engineers in the fields of medical image computing/processing... computer science, artificial intelligence, radiology, neuroscience, and biomedical research.
    • Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence

      • 1st Edition
      • May 1, 2026
      • Manuel González Canché
      • English
      • Paperback
        9 7 8 0 4 4 3 2 1 9 6 1 0
      • eBook
        9 7 8 0 4 4 3 2 1 9 6 0 3
      Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence empowers qualitative and mixed methods researchers in the data science movement by offering no-code, cost-free software access so that they can apply cutting-edge and innovative methods to synthetize qualitative data. The book builds on the idea that qualitative and mixed methods researchers should not have to learn to code to benefit from rigorous open-source, cost-free software that uses artificial intelligence, machine learning, and data visualization tools—just as people do not need to know C++ or TypeScript to benefit from Microsoft Word. The real barrier is the hundreds of R code lines required to apply these concepts to their databases. By removing the coding proficiency hurdle, this book will empower their research endeavors and help them become active members of and contributors to the applied data science community. The book offers a comprehensive explanation of data science and machine learning methodologies, along with access to software application tools to implement these techniques without any coding proficiency. The book addresses the need for innovative tools that enable researchers to tap into the insights that come out of cutting-edge data science tools with absolutely no computer language literacy requirements.
    • Federated Learning for the Metaverse

      • 1st Edition
      • May 1, 2026
      • Noor Zaman Jhanjhi + 3 more
      • English
      Federated Learning for the Metaverse: Applications in Virtual Environments provides readers with insights into how federated learning, a decentralized machine learning paradigm, can be strategically applied to address critical aspects of the metaverse. The book covers a wide range of topics, including privacy-preserving personalization, security, collaboration, adaptive learning environments, real-time communication, decentralized governance, language understanding, immersive learning experiences, avatar customization, and dynamic scene rendering.
    • Advanced Intelligence Methods for Data Science and Optimization

      • 1st Edition
      • April 1, 2026
      • Amir Hossein Gandomi + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 8 9 4 0 8
      • eBook
        9 7 8 0 4 4 3 2 8 9 4 1 5
      Advanced Intelligence Methods for Data Science and Optimization covers the latest research trends and applications of AI topics such as deep learning, reinforcement learning, evolutionary algorithms, Bayesian optimization, and swarm intelligence. The book is a comprehensive guide that provides readers with theoretical concepts and case studies for applying advanced intelligence methods to real-world problems. Authored by a team of renowned experts in the field, the book offers a holistic approach to understanding and applying intelligence methods across various domains.It explores the fundamental concepts of data science and optimization, providing a strong foundation for readers to build upon, and will be a welcomed resource for AI researchers, data scientists, engineers, and developers on key topics such as evolutionary optimization techniques, reinforcement learning, Natural Language Processing, Bayesian optimization, advanced analytics for large-scale data, fuzzy logic, quantum computing, graph theory, convex optimization, differential evolution, and more.
    • Digital Design using VerilogHDL

      • 1st Edition
      • April 1, 2026
      • Shilpi Birla + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 9 0 8 8 6
      • eBook
        9 7 8 0 4 4 3 2 9 0 8 9 3
      Digital Design using VerilogHDL: VLSI Modeling, Coding and Verification covers the concepts of digital logic design, including, logic simplification and optimization for digital circuit synthesis and implementation, design and integration of logics (combinational and sequential) in the building of digital circuits and systems, the practical aspects of number systems, the use of VerilogHDL in the logic design, testbench verification, and the synthesis of digital circuits and systems with HDL code examples. Users will find an approach to the design, integration, verification, and synthesizing of a digital logic circuit, complete with coding examples.
    • Digital Twins for Sustainable Development

      • 1st Edition
      • April 1, 2026
      • Valentina Emilia Balas + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 7 3 8 8 9
      • eBook
        9 7 8 0 4 4 3 2 7 3 8 9 6
      Digital Twins for Sustainable Development covers digital twins for sustainability as a virtual representation of a physical system or environment, such as a building, city, or natural ecosystem and how they are used to support sustainable development and management practices. The book demonstrates how data from a variety of sources, such as sensors, satellite imagery, and other monitoring tools can be used for advanced analytics and modeling techniques to simulate the system's behavior over time. This allows researchers and professionals in computer science to manage complex systems and promote sustainable development and resource management practices.
    • Digital Outcasts

      • 2nd Edition
      • April 1, 2026
      • Kel Smith
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 6 7 7 5
      • eBook
        9 7 8 0 4 4 3 3 3 6 7 8 2
      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.
    • The Governance of Artificial Intelligence

      • 1st Edition
      • April 1, 2026
      • Tshilidzi Marwala
      • English
      • Paperback
        9 7 8 0 4 4 3 3 6 3 2 2 1
      • eBook
        9 7 8 0 4 4 3 3 6 3 2 3 8
      The Governance of Artificial Intelligence stands out as a comprehensive guide that unifies the essential dimensions of artificial intelligence—values, data, algorithms, computing, applications, and governance—within a single volume. The book offers expert guidance on each of these topics, blending engineering insight with governance strategies. It proposes a holistic approach to AI governance, emphasizing the importance of proactive and balanced policies that foster innovation while safeguarding ethical standards. Prioritizing social welfare and human rights, this work advocates for maximizing AI’s benefits and minimizing its risks through effective, integrative governance structures.Moreover, the book highlights the need for a versatile governance model that draws from various disciplines and champions diversity. It stresses the importance of leveraging existing regulatory frameworks, ethical guidelines, and industry standards, while encouraging active collaboration among governments, businesses, civil society, and academia. Structured into six sections and 33 chapters, the book systematically explores core principles, data concerns, algorithms, computing, practical applications, and governance challenges, making it a crucial resource for understanding the evolving landscape of AI oversight.