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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.

  • Quantum Health AI

    The Revolution of Medicine, Public Health, and Global Health by Quantum Computing-Powered Artificial Intelligence
    • 1st book:metaData.edition
    • Dominique J. Monlezun
    • publicationLanguages:en
    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.

  • Motion Control of Soft Robots

    • 1st book:metaData.edition
    • Wenyu Liang contributors.plusContributors
    • publicationLanguages:en
    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.

  • Up and Running with AutoCAD 2026

    2D and 3D Drawing, Design and Modeling
    • 1st book:metaData.edition
    • Robert C. Kaebisch contributors.plusContributors
    • publicationLanguages:en
    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 book:metaData.edition
    • Daowen Qiu
    • publicationLanguages:en
    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 book:metaData.edition
    • Tilottama Goswami contributors.plusContributors
    • publicationLanguages:en
    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.

  • Decentralized Optimization in Networks

    Algorithmic Efficiency and Privacy Preservation
    • 1st book:metaData.edition
    • Qingguo Lü contributors.plusContributors
    • publicationLanguages:en
    Decentralized Optimization in Networks: Algorithmic Efficiency and Privacy Preservation provides the reader with theoretical foundations, practical guidance, and solutions to decentralized optimization problems. The book demonstrates the application of decentralized optimization algorithms to enhance communication and computational efficiency, solve large-scale datasets, maintain privacy preservation, and address challenges in complex decentralized networks. The book covers key topics such as event-triggered communication, random link failures, zeroth-order gradients, variance-reduction, Polyak’s projection, stochastic gradient, random sleep, and differential privacy. It also includes simulations and practical examples to illustrate the algorithms' effectiveness and applicability in real-world scenarios.

  • Artificial Intelligence

    Data and Model Safety
    • 1st book:metaData.edition
    • Yu-Gang Jiang contributors.plusContributors
    • publicationLanguages:en
    Artificial Intelligence Data and Model Safety: Risks, Attacks and Defenses offers a comprehensive overview of the evolution of AI and its security concerns. The book delves into how historical advancements in AI have both bolstered and complicated the issue of safeguarding data and models. By reflecting on the interplay between machine learning innovations and vulnerabilities, it sets the stage for readers to understand the critical importance of robust defenses in this era of digital and algorithmic reliance. In addition to contextualizing the historical trajectory of AI security, the book examines foundational elements of machine learning, emphasizing the mechanisms that contribute to, or mitigate, risks.Readers are guided through case studies of real-world attacks, illustrating the practical implications of security weaknesses, while proposed defense strategies provide actionable insights for strengthening AI systems.

  • Mastering Prompt Engineering

    Deep Insights for Optimizing Large Language Models (LLMs)
    • 1st book:metaData.edition
    • Anand Nayyar contributors.plusContributors
    • publicationLanguages:en
    Mastering Prompt Engineering: Deep Insights for Optimizing Large Language Models (LLMs) is a comprehensive guide that takes readers on a journey through the world of Large Language Models (LLMs) and prompt engineering. Covering foundational concepts, advanced techniques, ethical considerations, and real-world case studies, this book equips both novices and experts to navigate the complex LLM landscape. It provides insights into LLM architecture, training, and prompt engineering methods, while addressing ethical concerns such as bias and privacy. Real-world case studies showcase the practical application of prompt engineering in a wide range of settings. This resource is not just for specialists but is a practical and ethically conscious guide for AI practitioners, students, scientific researchers, and anyone interested in harnessing the potential of LLMs in natural language processing and generation. Mastering Prompt Engineering serves as a gateway to a deeper understanding of LLMs and their responsible and effective utilization through its comprehensive, ethical, and practical approach.

  • The Decentralized Hydrogen Revolution Using Artificial Intelligence, Internet of Things, and Blockchain

    • 1st book:metaData.edition
    • Hossein Pourrahmani contributors.plusContributors
    • publicationLanguages:en
    The Decentralized Hydrogen Revolution Using Artificial Intelligence, Internet of Things, and Blockchain provides an essential guide to understanding the transformative potential of advanced technologies in decentralized hydrogen communities. This comprehensive resource covers the intersection of AI, IoT, and blockchain with sustainable energy, offering insights from foundational principles to advanced applications. Readers will learn about the environmental benefits of hydrogen over fossil fuels, electrolysis, and the integration of innovative technologies to enhance hydrogen production and distribution. The book delves into the role of fuel cells in clean energy, advanced AI algorithms in hydrogen production, blockchain trust in hydrogen networks, and IoT connectivity.Economi... considerations, policy frameworks, and the future of decentralized hydrogen communities are also explored, making this an invaluable reference for researchers, industry professionals, policymakers, and students interested in the hydrogen economy.

  • Advanced Topics in Inverse Data Envelopment Analysis

    Approaches for Handling Ratio Data
    • 1st book:metaData.edition
    • Mehdi Soltanifar contributors.plusContributors
    • publicationLanguages:en
    Advanced Topics in Inverse Data Envelopment Analysis: Approaches for Handling Ratio Data explores and tackles the most significant challenges encountered by researchers and practitioners in decision analysis and performance evaluation. This book delves into the sophisticated realm of Ratio Data Envelopment Analysis (DEA-R), offering a thorough examination of advanced methodologies, practical examples, and insights into managing complex problems involving both non-negative and negative data. Filling crucial gaps in existing literature, this comprehensive resource focuses on the emerging field of Inverse DEA-R, equipping readers with the necessary tools and knowledge to address a wide range of challenging data types. This book serves as an essential guide for making informed and efficient decisions, guiding researchers and graduate students in computer science, applied mathematics, industrial engineering, and finance, navigating the complexities of decision analysis in today's data-driven world.

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