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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.

BooksJournals

    • Metaverse in the Healthcare Industry

      • 1st Edition
      • September 6, 2025
      • Hemachandran Kannan + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 0 1 8 2 7
      • eBook
        9 7 8 0 4 4 3 3 0 1 8 3 4
      Metaverse in the Healthcare Industry: Potential Applications, Tools, and Techniques explores the intersection of rapidly evolving metaverse technology and its implications for the healthcare sector. The book provides a comprehensive overview of virtual and augmented reality, artificial intelligence, and other immersive technologies that have gained significant attention within the context of the metaverse in healthcare. It emphasizes how these technologies can revolutionize healthcare by enabling virtual clinics, patient education, remote medical training, therapeutic interventions, and much more. By bringing together diverse perspectives, it contributes to the ongoing discourse on the future of healthcare delivery and innovation.This book also delves into technical aspects of metaverse development and its integration with existing healthcare systems. It discusses ethical considerations and challenges associated with implementing metaverse technologies in healthcare settings. Additionally, it highlights the potential to reshape the healthcare landscape by fostering innovation, improving patient care, and revolutionizing medical training and research. Readers will gain insights into applications, tools, and techniques for leveraging the metaverse to create more effective and accessible healthcare solutions.

    • Applied Mathematical Modeling for Biomedical Robotics and Wearable Devices

      • 1st Edition
      • August 29, 2025
      • S. Sountharrajan + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 5 1 4 3
      • eBook
        9 7 8 0 4 4 3 3 3 5 1 5 0
      Applied Mathematical Modelling for Biomedical Robotics and Wearable Devices delves into the innovative convergence of mathematical frameworks and biomedical engineering. The book begins by exploring how advanced mathematical modelling underpins the development and optimization of robotic systems and wearable technologies tailored for medical applications. With a strong emphasis on practical implementation, it serves as a bridge between theoretical concepts and real-world engineering challenges in the healthcare sector. Readers will gain insights into the transformative role of mathematical techniques that drive precision, functionality, and human-centric design in cutting-edge medical technologies.The book also covers interdisciplinary applications, integrating domains like biomechanics, sensor technology, and data analytics. By highlighting case studies and real-world scenarios, it showcases practical advancements in wearable devices that monitor health metrics and robotic systems that assist in surgical procedures.

    • Healthcare Applications of Neuro-Symbolic Artificial Intelligence

      • 1st Edition
      • August 19, 2025
      • Boris Galitsky
      • English
      • Paperback
        9 7 8 0 4 4 3 3 0 0 4 6 2
      • eBook
        9 7 8 0 4 4 3 3 0 0 4 7 9
      Healthcare Applications of Neuro-Symbolic Artificial Intelligence provides a comprehensive introduction to the field of neuro-symbolic (NS) artificial intelligence (AI), presenting the most recent advances in deep learning and integration of NS systems and large language models (LLMs). This book evaluates traditional approaches, current approaches, as well as the author’s own approach to NS, to create hybrid architectures and reasoning techniques to overcome the limitations of most existing AI systems such as deep learning, neural networks, and symbolic AI.This book will be a welcome resource for researchers and graduate students in AI, natural language processing, and biomedical informatics, as well as professionals in software development looking to redesign current systems to leverage LLMs through the health application of NS architecture.

    • Minds, Machines, and Misinformation

      • 1st Edition
      • August 11, 2025
      • Don Donghee Shin
      • English
      • Paperback
        9 7 8 0 4 4 3 1 6 1 0 4 9
      • eBook
        9 7 8 0 4 4 3 1 6 1 0 5 6
      Algorithms have become the key organizer through which power is enacted in our society. A huge amount of data regarding our daily routines are monitored and analyzed to make recommendations that manage, control, and lead our behaviors in everyday life. AI, Humans, and Misinformation: How Does AI Alter Human Behavior and How Do Humans Influence Algorithmic Misinformation? is a guide to understanding the dynamics of AI and misinformation in human contexts by addressing meaningful questions—How does AI alter human behavior and how do humans influence algorithmic decision-making? In answering these questions, this book examines the role of misinformation, disinformation, and fake news, and shows readers how to develop AI methods and algorithms that combat misinformation by using AI design choices that provide users and developers alike with meaningful control over AI. This book brings together various perspectives on algorithms into an integrated conceptual framework, and provides a broad socio-technical analysis, addressing critical and ethical issues of misinformation and fake news. The book offers a compelling insight into the misinformation phenomenon and the future of AI-based society. Readers will find an integrated technical analysis of the logic and social implications of algorithmic processes. Reporting from the cutting edge of critical technical methods and research, the result is useful and constructive for developing the relations between algorithms and humans. This is an imperative methodology for understanding what is at stake as industry and government use AI to reshape the world.

    • Motion Control of Soft Robots

      • 1st Edition
      • July 30, 2025
      • Wenyu Liang + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 1 4 0 1 8 1
      • eBook
        9 7 8 0 4 4 3 1 4 0 1 9 8
      Motion Control of Soft Robots provides an overview of the general concepts and most recent technological updates in soft robot motion control. The book provides systematic coverage of theoretical and practical aspects in system modeling and motion control strategies, presenting novel ideas, methods, and future outlook related to motion control of soft actuators and robots, including model-based control, model-free control, and bioinspired control. This book is useful for researchers, engineers, and students of robotics who can expect to learn how to design and implement various techniques to obtain solutions to control problems in soft robot control and nonlinear system control.

    • Quantum Health AI

      • 1st Edition
      • July 30, 2025
      • Dominique J. Monlezun
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 3 5 3 8
      • eBook
        9 7 8 0 4 4 3 3 3 3 5 4 5
      Quantum Health AI: The Revolution of Medicine, Public Health, and Global Health is the first comprehensive book defining the transformation of the global health ecosystem by the fusion of our most powerful technologies—quantum computing and artificial intelligence—while defending an actionable human-centred approach to doing so responsibly, equitably, and sustainably. We can continue to watch wars, diseases, poverty, polarization, cyber-crime, and climate change only worsen. Our strongest technologies can remain centralized in a small number of companies and countries for their profit and power. Or we can cooperatively put quantum AI to work for the health of all of us, by better managing this technology’s overarching strategic competition between democracies and autocracies, along with the public and private sectors (balancing human security with national security, economic growth with household livelihoods, individual rights with the common good). This book draws on the decade plus of original research and first-hand perspective of the world’s first triple doctorate-trained physician-data scientist and AI ethicist. It unpacks the history, science, values, and political economics framing and driving quantum AI (including its physics, metaphysics, ethics, governance, computing, sensing, communication, materials, and security), the global health ecosystem (healthcare systems, public health agencies, biotechnology companies, and development institutions), and their growing integration, wins, and challenges. This one-stop book provides a global, inclusive, and practical guide for understanding and shaping these societal and technological trends. It thus empowers health, technology, and policy students, practitioners, professionals, researchers, and leaders in organizations, universities, companies, and governments—ultimate... to make and maintain the human-centred quantum AI safeguarding and advancing humanity’s health, home, and future.

    • Data Science for Teams

      • 1st Edition
      • July 30, 2025
      • Harris V. Georgiou
      • English
      • Paperback
        9 7 8 0 4 4 3 3 6 4 0 6 8
      • eBook
        9 7 8 0 4 4 3 3 6 4 0 7 5
      Managing human resources, time allocation, and risk management in R&D projects, particularly in Artificial Intelligence/Machine Learning/Data Analysis, poses unique challenges. Key areas such as model design, experimental planning, system integration, and evaluation protocols require specialized attention. In most cases, the research tends to focus primarily on one of the two main aspects: either the technical aspect of AI/ML/DA or the teams’ effort, or the typical management aspect and team members’ roles in such a project. Both are equally import for successful real-world R&D, but they are rarely examined together and tightly correlated. Data Science for Teams: 20 Lessons from the Fieldwork addresses the issue of how to deal with all these aspects within the context of real-world R&D projects, which are a distinct class of their own. The book shows the everyday effort within the team, and the adhesive substance in between that makes everything work. The core material in this book is organized over four main Parts with five Lessons each. Author Harris Georgiou goes into the difficulties progressively and dives into the challenges one step at a time, using a typical timeline profile of an R&D project as a loose template. From the formation of a team to the delivery of final results, whether it is a feasibility study or an integrated system, the content of each Lesson revisits hints, ideas and events from real-world projects in these fields, ranging from medical diagnostics and big data analytics to air traffic control and industrial process optimization. The scope of DA and ML is the underlying context for all, but most importantly the main focus is the team: how its work is organized, executed, adjusted, and optimized. Data Science for Teams presents a parallel narrative journey, with an imaginary team and project assignment as an example, running an R&D project from day one to its finish line. Every Lesson is explained and demonstrated within the team narrative, including personal hints and paradigms from real-world projects.

    • Up and Running with AutoCAD 2026

      • 1st Edition
      • July 25, 2025
      • Robert C. Kaebisch + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 6 5 9 3 5
      • eBook
        9 7 8 0 4 4 3 3 6 5 9 4 2
      Up and Running with AutoCAD 2026: 2D and 3D Drawing, Design and Modeling presents a combination of step-by-step instructions, examples, and insightful explanations. The book emphasizes core concepts and practical application of AutoCAD in engineering, architecture, and design. Equally useful in instructor-led classroom training, self-study, or as a professional reference, the book is written by a long-time AutoCAD professor and instructor with the user in mind.

    • Theoretical Foundations of Quantum Computing

      • 1st Edition
      • July 25, 2025
      • Daowen Qiu
      • English
      • Paperback
        9 7 8 0 4 4 3 2 7 7 0 4 7
      • eBook
        9 7 8 0 4 4 3 2 7 7 0 5 4
      Theoretical Foundations of Quantum Computing is an essential textbook for introductory courses in the quantum computing discipline. Quantum computing represents a paradigm shift in understanding computation. This textbook delves into the principles of quantum mechanics that underpin this revolutionary technology, making it invaluable for undergraduate and graduate students in computer science and related fields. Structured into eight meticulously crafted chapters, it covers everything from the historical context of quantum computing to advanced theories and applications. The book includes core topics such as basic models, quantum algorithms, cryptography, communication protocols, complexity, and error correction codes.Each chapter builds upon the last, ensuring a robust understanding of foundational concepts and cutting-edge research. It serves as both a foundational resource for students and a comprehensive guide for researchers interested in quantum computing. Its clarity makes it an excellent reference for deepening understanding or engaging in advanced research.

    • Data-Driven Insights and Analytics for Measurable Sustainable Development Goals

      • 1st Edition
      • July 24, 2025
      • Tilottama Goswami + 2 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 0 4 4 5
      • eBook
        9 7 8 0 4 4 3 3 3 0 4 5 2
      Data-Driven Insights and Analytics for Measurable Sustainable Development Goals discusses the growing imperative to understand, measure, and guide actions using data-driven insights. The SDGs encompass a broad spectrum of global challenges, from eradicating poverty and hunger to preserving the environment and fostering peace. To address these issues, one should be able to measure and analyze progress. This book bridges the gap between qualitative and quantitative assessments, recognizing that goals are not solely about numbers but also encompass complex social, environmental, and economic dynamics. By merging data science with qualitative analysis, readers can explore how SDGs intersect and influence each other.The book provides readers with an understanding of how to effectively leverage data science models and algorithms using descriptive analytics, allowing us to assess the current state of SDG performance and offering valuable insights into where we stand on these critical goals. Prescriptive analytics guides actions by offering actionable recommendations, while predictive analytics anticipates future trends and challenges, helping us navigate our path toward the SDGs effectively.

Related subjects

Applications

Artificial intelligence

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Computer systems organization

Computer vision and pattern recognition

Computing milieux

Data

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Hardware and architecture

Information systems

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Software

Theory and mathematics