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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.

  • A Comprehensive Guide to R Programming for Data Analytics

    • 1st Edition
    • Parul Acharya
    • English
    A Comprehensive Guide to R Programming for Data Analytics provides a comprehensive presentation of univariate and multivariate statistical models within the general linear model and generalized linear model framework to analyze simple and complex data using R software. This book presents popular R packages that are used in data mining (e.g., caret-classification and regression, lubridate-dates and times, string-R for string data) and visualization (e.g., ggplot, ggthemes, ggtext). The R packages used to analyze data using a particular statistical model are explained through real-world and publicly available datasets. R codes are presented in a manner that helps readers understand the program code syntax.Examples of real-world data sets from a variety of academic disciplines are provided so that a wide audience can learn R programming to analyze data in their research. The book provides tips, recommendations, and strategies to troubleshoot common issues in R syntax, as well as definitions of key terms. Checkpoints are included to recap the concepts learned in each chapter. The book helps readers enhance their conceptual understanding and practical application of statistical models to real-world datasets, and enables readers to gain competency in R programming, which is an important skill in today’s data-driven market.

  • Artificial Intelligence and Machine Learning for Safety-Critical Systems

    A Comprehensive Guide
    • 1st Edition
    • Rajiv Pandey + 3 more
    • English
    Artificial Intelligence and Machine Learning for Safety-Critical Systems: A Comprehensive Guide provides engineers and system designers who are exploring the application of AI/ML methods for safety-critical systems with a dedicated resource on the challenges and mitigation strategies involved in their design. The book's authors present ML techniques in safety-critical systems across multiple domains, including pattern recognition, image processing, edge computing, Internet of Things (IoT), encryption, hardware accelerators, and many others. These applications help readers understand the many challenges that need to be addressed in order to increase the deployment of ML models in critical systems. In addition, the book shows how to improve public trust in ML systems by providing explainable model outputs rather than treating the system as a black box for which the outputs are difficult to explain. Finally, the authors demonstrate how to meet legal certification and regulatory requirements for the appropriate ML models. In essence, the goal of this book is to help ensure that AI-based critical systems better utilize resources, avoid failures, and increase system safety and public safety.

  • Federated Intelligence in Medicine

    AI-Driven Robotics for Secure and Intelligent Healthcare Systems
    • 1st Edition
    • Manisha Guduri + 3 more
    • English
    Federated Intelligence in Medicine: AI-Driven Robotics for Secure and Intelligent Healthcare Systems explores the rapidly evolving field where medical robotics intersects with cutting-edge artificial intelligence and secure data-sharing technologies. Covering a comprehensive range of topics, the book begins with foundational knowledge in medical robotics and Generative AI, progressing to advanced concepts such as federated learning and architectural modeling tailored for AI-driven robotic systems. Readers will explore algorithms enhancing surgical robotics, remote robotic surgeries, and human-robot interaction. The text also tackles AI-driven diagnostic robots, privacy preservation through homomorphic encryption, and differential privacy and emerging medical imaging techniques integrated with robotics.Later chapters examine the synergy of large language models, agent AI, and edge AI with robotic technologies, providing both theoretical frameworks and practical case studies that illuminate real-world applications and challenges. This book is an invaluable resource for researchers and academicians engaged in artificial intelligence, robotics, and medical technology. It also serves undergraduate and graduate students in Biomedical Engineering, Electronics and Electrical Engineering, and Computer Science and Engineering.

  • System of Systems Engineering

    Innovations, Challenges, and Future Directions
    • 1st Edition
    • Bedir Tekinerdogan + 1 more
    • English
    System of Systems Engineering: Innovations, Challenges, and Future Directions focuses on the many aspects of System of Systems Engineering. Part I, Foundations of System of Systems Engineering, introduces the field, characterizes and classifies SoS, and discusses key concepts. Part II, Governance and Management of SoSE, covers strategic governance, policy and regulatory frameworks, and leadership and decision-making in SoSE projects. Part III, Methodologies and Tools, explores systems thinking and modeling approaches, lifecycle management, and interoperability and integration strategies. Part IV, AI and System of Systems Engineering, delves into leveraging AI for enhanced decision-making, machine learning applications, AI-driven automation and control, and ethical considerations.Final... Part V, Case Studies and Emerging Challenges, presents real-world applications in defense and aerospace, smart cities, healthcare, environmental and energy systems, and discusses future directions and research opportunities. This book offers significant benefits to graduate students, researchers, and professionals in software engineering, systems engineering, aerospace engineering, defense, telecommunications, and other fields where SoSE is relevant.

  • Company Digital Twins

    Emerging Trends, Technologies, and Applications
    • 1st Edition
    • Joseph Bamidele Awotunde
    • English
    The concept of the digital twin, a virtual representation of a physical system, has gained significant attention due to advancements in Artificial Intelligence, Internet of Things, and data analytics. It plays a crucial role in enhancing efficiency, sustainability, and decision-making across industries, such as manufacturing, healthcare, and urban planning. The timeliness of this topic lies in the rapid digital transformation and the increasing complexity of systems requiring real-time, intelligent management to achieve competitive advantages and sustainability goals. Company Digital Twins explores virtual companies based on digital twin technologies. Digital twin computing not only reduces the gap between a real company and a virtual company, but generates new datasets, making the company digital twin a bridge between the real and virtual company. A company digital twin is also the mirror that reflects the real company into the virtual company. The structure of the book is comprised of 15 chapters that discuss the foundational concepts emerging trends, underlying technologies, practical applications; and future directions, and includes data security and privacy concerns, integration issues, and the scalability of digital twins across large companies. Sitting within the series, Advances in Digital Twin Computing and Sensor Networks, Company Digital Twins is essential reading for anyone who needs to benefit from the capabilities of digital twins within the organization.

  • ARM Processors for Power Electronic Applications

    Fundamentals to Programming
    • 1st Edition
    • P. Ponnambalam + 2 more
    • English
    ARM Processors for Power Electronic Applications: Fundamentals to Programming teaches the concept of controlling power converters using the ARM processor, from its fundamentals to implementation procedure, including using advanced controllers for energy management. The book discusses coding the ARM processor for different power converters and a variety of applications. It covers the step-by-step procedure in the design of advanced controllers, the ARM processor and parallel processing, creating driver circuits to interface the ARM processor with power circuits, the peripherals to ARM processors so it can used to control power converters and coding for power circuits.

  • Full-Stack Web Development from the Ground Up

    Principles, Practices, and Technologies
    • 1st Edition
    • Christopher D Hundhausen
    • English
    Full-Stack Development from the Ground Up: Principles, Practices, and Technologies addresses the growing need for a comprehensive upper-division computer science textbook that provides in-depth treatment of full-stack web development using the modern web development technologies that students are likely to encounter in industry. Professional full-stack web developers who are capable of developing both the front-end user interfaces and back-end databases and services for dynamic websites are in high demand. The book begins by laying a foundation in HTML, CSS and JavaScript—the building blocks of client-side web development.It then explores one particular web development stack in detail: MERN, which stands for MongoDB, Express.js, React.js and Node.js. Together, these four technologies provide powerful support for full-stack web development in a single programming language—JavaScript. The crucial final step in the web development process is deploying apps to a server, so users can interact with them. This book simplifies deployment by focusing on just one web deployment environment: Amazon Web Services (AWS), and only those AWS tools that are absolutely necessary to deploy MERN applications.

  • Principles of Medical Biohybrid Microrobots

    • 1st Edition
    • Veronika Magdanz + 1 more
    • English

  • Healthcare 5.0

    Applications of Artificial Intelligence, Machine Learning, IoMT, and Big Data
    • 1st Edition
    • Yugal Kumar + 2 more
    • English
    Healthcare 5.0: Applications of Artificial Intelligence, Machine Learning, IoMT, and Big Data addresses the urgent need for innovation in today’s complex healthcare data landscape, characterized by pandemics, aging populations, and escalating chronic conditions. This book introduces the concept of ‘Healthcare 5.0’ as an interconnected, data-driven, and patient-centric framework, where advanced technologies—such as AI, ML, IoMT, Big Data, and Large Language Models (LLMs)—converge to optimize care, streamline operations, and deliver personalized, predictive solutions that meet real-world challenges. Comprising six comprehensive sections, the book moves from core AI applications in electronic health records, drug discovery, data management, and privacy, through cutting-edge big data analytics for precise disease forecasting and diagnosis. It explores new research advances in the Internet of Medical Things including connected device architectures and their fusion with AI for dynamic decision-making. The third section focuses on data analytics in telemedicine, remote care, system usability, and integration in Healthcare 5.0. The personalized healthcare section details analysis and applications in AI- and IoT-powered assistance, and real-time monitoring. The last section explores the development of LLMs and their applications in medical imaging, clinical decision support, predictive analytics, system architectures, as well as the ethical challenges of their deployment in healthcare. Healthcare 5.0: Applications of Artificial Intelligence, Machine Learning, IoMT, and Big Data serves as an essential resource for graduate students, researchers, and engineers in computer science, data science, and biomedical informatics. It bridges theory and practical application, offering interdisciplinary insights, foundational background, detailed case studies, and guidance on navigating the next generation of healthcare data systems. Whether for research or real-world innovation, readers gain the tools to design, analyze, and implement intelligent healthcare data solutions for a rapidly evolving digital era.

  • The Deterministic Universe

    Exploring Chaos, Free Will, Prediction, and Modeling
    • 1st Edition
    • Paul A. Gagniuc
    • English
    The Deterministic Universe: Exploring Chaos, Free Will, Prediction, and Modeling equips readers with the tools to learn the foundational concepts of chaos, randomness, and determinism through examples and applied case studies. The book helps readers gain insight into how deterministic algorithms handle complex, chaotic data, providing an interdisciplinary exploration of chaos theory, determinism, and free will, grounded in scientific principles, computational models, and philosophical insights. The content builds on established theories in physics, bioinformatics, and systems biology, weaving them into broader existential questions. The material emphasizes the interplay between randomness, noise, and order, providing a fresh lens to view the universe and our place within it. The book connects these ideas to practical tools like random number generators and nonlinear equations, machine learning algorithms, computational and predictive models, extending their implications to biological systems, human thought, and decision-making. By addressing both scientific fundamentals and philosophical debates, the book bridges abstract ideas with real-world phenomena and demonstrates the role of randomness and noise in predictive models and simulations, helping readers understand the limits of computational systems in mimicking real-world processes.

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