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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

    • 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.

    • AI Platforms as Global Governance for the Health Ecosystem

      The Future's Global Hospital
      • 1st Edition
      • Dominique J. Monlezun
      • English
      AI Platforms as Global Governance for the Health Ecosystem: The Future’s Global Hospital provides comprehensive and actionable approaches for readers to understand and optimize responsible AI to create global governance for the healthcare ecosystem. The book explores how AI platforms can transform hospitals and clinical practice by digitally unifying patients, providers, and payors, advancing healthcare for all. Users will find content that defines and explains the main hurdles and technical innovations in responsibly governing AI platforms for efficient, equitable, and sustainable global healthcare.Additiona... sections delve into the history, science, politics, economics, ethics, policy, and future of these AI platforms, and how governance efforts can work toward the common good. Written from the first-hand perspective of a practicing physician-data scientist and AI ethicist, the book maps out how to develop successful governance for AI platforms.

    • 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.

    • AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice

      • 1st Edition
      • Olfa Boubaker + 1 more
      • English
      AI and Data Science in Precision Medicine, Predictive Analytics, and Medical Practice explores the transformative role of AI and data science in enhancing precision medicine, predictive analytics, and medical practice. The book covers diverse topics such as AI-driven personalized medicine, seizure prediction through EEG analysis, and the application of chaos theory in AI-driven healthcare. The volume also delves into medical practice and education, including ethical considerations, AI-driven supply chain management, and clinical documentation using natural language processing.Furthermo... it examines AI's role in telemedicine, patient engagement, and adherence, offering innovative solutions to improve healthcare delivery and outcomes.

    • AI and Data Science in Medical Research

      • 1st Edition
      • Olfa Boubaker
      • English
      AI and Data Science in Medical Research focuses on the integration of AI and data science into medical research, highlighting their impact on drug discovery, medical imaging, diagnostics, and genomic medicine. The book addresses the acceleration of therapeutic compound discovery and optimization of drug development pipelines through AI. The volume also discusses advancements in medical imaging, including early disease detection and neuroimaging. Additionally, it covers the application of AI in genomic medicine, offering insights into personalized treatment strategies.The volume concludes with an examination of AI's role in public health surveillance, particularly in disease detection and epidemiological research.

    • Digital Twins

      Core Principles and AI Integration
      • 1st Edition
      • Bedir Tekinerdogan + 1 more
      • English
      Digital Twins: Core Principles, System Engineering, and AI Integration provides a comprehensive overview of digital twin technology, a cutting-edge innovation that bridges the physical and digital worlds. The book addresses common challenges such as data integration, security, scalability, and the alignment of digital twin models with actual physical processes. After presenting core concepts of digital twins for software engineering, the book discusses integration with advanced digital solutions such as AI, IoT, Cloud computing, Big Data Analytics, and Extended Reality (XR). Next, the authors provide readers with a thorough presentation of digital twins' applications in a variety of settings and industry/research topics.Finally, the book concludes with a discussion of challenges and solutions, along with future trends in digital twins research and development. As digital twin technology evolves, its integration with various advanced digital solutions is becoming essential for achieving real-time insights and autonomous decision-making. Challenges include understanding the interoperability of these technologies, managing data complexity, ensuring security, and optimizing for low-latency environments.

    • Foundations of Human-Computer Interaction

      Designing for Cognitive Alignment
      • 1st Edition
      • Robert Atkinson
      • English
      Foundations of Human-Computer Interaction: Designing for Cognitive Alignment covers the fundamentals of human-computer interaction (HCI), usability, and user-centered design. It provides a holistic and engaging exploration of HCI by integrating historical perspectives, behavioral and cognitive insights, neuroscientific principles, and advanced technological tools. The book also discusses contemporary challenges such as dark patterns and surveillance capitalism, and offers an understanding of ethics and code of conduct to enable both students and practitioners to take their thinking and designs forward in a responsible way into the marketplace.The book's pedagogy emphasizes interactive learning, critical thinking, and iterative design processes, making the content accessible and engaging for both novices and advanced learners.

    • AI-Driven Human-Machine Interaction for Biomedical Engineering

      • 1st Edition
      • Kapil Gupta + 4 more
      • English
      AI-Driven Human-Machine Interaction for Biomedical Engineering: Concepts, Applications, and Methodologies offers a comprehensive examination of the intricate relationship between humans and machines, particularly through the transformative lens of artificial intelligence (AI). As AI technologies rapidly evolve, understanding their implications for human-machine interaction (HMI) has become essential across various domains, especially healthcare. This book addresses the pressing need for insights into AI-driven methodologies, providing scholars, practitioners, and learners with foundational knowledge and practical applications that enhance collaboration between human cognition and machine capabilities. Structured into well-defined chapters, the book begins with an introduction to AI-driven HMI, laying the groundwork for understanding its significance in sustainable healthcare and beyond. Subsequent chapters explore critical topics such as machine learning principles, advanced biomedical data classification methods, and the role of AI in telemedicine. Readers will delve into cutting-edge techniques, from deep learning to non-invasive computer vision, and examine the implications of these technologies across industries. Each chapter equips readers with actionable insights and highlights emerging trends, ethical considerations, and the future of AI in HMI, ensuring a well-rounded perspective on this dynamic field. AI-Driven Human-Machine Interaction for Biomedical Engineering: Concepts, Applications, and Methodologies is an invaluable resource for researchers, academics, and students in the fields of Biomedical Engineering, Computer Science, Data Science, Artificial Intelligence, and Healthcare Technology. By bridging theoretical foundations with practical applications, this book empowers its readers to effectively harness AI technologies, driving innovation and improving outcomes in healthcare and various sectors.

    • Digital Design using VerilogHDL

      VLSI Modeling, Coding and Verification
      • 1st Edition
      • Shilpi Birla + 2 more
      • English
      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
      • Valentina Emilia Balas + 4 more
      • English
      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.

Related subjects

Applications

Artificial intelligence

Business intelligence

Computer systems organization

Computer vision and pattern recognition

Computing milieux

Data

Graphics cad hci

Hardware and architecture

Information systems

Internet and web technology

Software

Theory and mathematics