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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.

  • AI-Driven Urban Planning

    Shaping the Future of Cities
    • 1st Edition
    • Zhong-Ren Peng
    • English
    AI-Driven Urban Planning: Shaping the Future of Cities presents a comprehensive guide to the transformative potential of artificial intelligence in urban planning. This book equips readers with the knowledge to harness data, analytics, and AI for creating sustainable, equitable, and livable urban environments. Exploring diverse applications—from understanding human mobility patterns to enhancing disaster response strategies and optimizing design processes—the book offers practical projects and illustrates how AI is shaping contemporary urban landscapes. By addressing both theoretical and practical dimensions, this resource aims to empower students, professionals, and policymakers with a holistic understanding of Urban Planning AI.It is organized into five parts, each tackling crucial aspects of Urban Planning AI. It first introduces core concepts, types, mechanisms, and ethical considerations surrounding AI. Part II then discusses the history of computer applications in urban and regional planning. Part III focuses on AI Applications in Urban Planning, addressing critical domains such as transportation, environmental, housing, economic, participatory, and health and safety planning. Part IV tackles challenges and ethical considerations, emphasizing equity, transparency, and data-related issues. Lastly, Part V explores future pathways of urban planning AI, discussing current trends, future visions, and interdisciplinary approaches essential for effective governance and policymaking.

  • 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.

  • Robotics for Intervention in Healthcare

    From Technology to Clinical Practice
    • 1st Edition
    • Françoise J Siepel
    • English
    Robotics for Intervention in Healthcare: From Technology to Clinical Practice bridges the gap between deep-core robotic intervention technology and clinical aspects, including content that is appropriate for physicians and clinicians. The book gives insights on the importance of connectivity in early stages, thoroughly addressing which aspects are important to improve the innovation chain.

  • Digital Transformation and Equitable Global Health

    A Future-Ready Perspective
    • 1st Edition
    • Arletty Pinel + 2 more
    • English
    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.

  • Autonomous Vehicle Safety Solutions

    Foundations, Technologies, and Prospects for the Future
    • 1st Edition
    • Aparna Kumari
    • English
    Autonomous Vehicle Safety Solutions: Foundations, Technologies, and Prospects for the Future addresses the dynamically evolving state of the art that traverses and brings together automotive engineering, electronics engineering, and computer science. Its technical overview of smart vehicles' capabilities, propelled by headway in artificial intelligence and sensor technologies, enables in-depth understanding of the safety-assurance complexities that guide their design and operation.The comprehensive volume distinguishes itself for its treatment of several exciting, emerging opportunities and trends, including machine learning algorithms, V2X connectivity, and cybersecurity. Up-to-date applications are featured through practical examples and expert insights, bringing additional value to a discourse which underscores the critical need for ongoing safety advancements and adaptability in the fast-moving context of autonomous driving systems, with their related implications on sustainability and society as a whole.The outcome is a cornerstone resource for academia and industry alike that encourages further transformative, interdisciplinary investigations to bring safety solutions to maturity and subsequent rigorous testing for validation standards to be defined, thus realizing, in a future not distant from now, a scenario where self-driving vehicles can co-exist seamlessly with traditional modes of transportation and also integrate reliably, efficiently, and without risks within the larger infrastructure.

  • Up and Running with AutoCAD 2027

    2D and 3D Drawing, Design and Modeling
    • 1st Edition
    • Robert C. Kaebisch
    • English
    Up and Running with AutoCAD® 2027: 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. To improve student learning, the early chapters have been revised and expanded with additional assignments, more explicit step-by-step guidance for the earliest assignments, improved readability, and a new concise drafting fundamentals reference section focusing on orthographic projection, basic standards, and naming conventions.

  • Agile Systems Engineering with SysML v2 and AI

    • 2nd Edition
    • Bruce Powel Douglass
    • English
    Agile Systems Engineering, Second Edition presents a vision of systems engineering where precise specification of requirements, structure, and behavior meet larger concerns as such as safety, security, reliability, and performance in an agile engineering context. World-renowned author and speaker Dr. Bruce Powel Douglass incorporates agile methods and model-based systems engineering (MBSE) to define the properties of entire systems while avoiding errors that can occur when using traditional textual specifications. Dr. Douglass covers the lifecycle of systems development, including requirements, analysis, design, and the handoff to specific engineering disciplines. In addition to agile SE, the workflows and practices of Model-Driven Dev Sec Ops (MDDSO) will be introduced and discussed. In the new Second Edition, all the examples and discussion use SysML v2 and are rendered in the Cameo System Modeler tool. Throughout the book, Dr. Douglass couples agile methods with SysML and MBSE to arm system engineers with the conceptual and methodological tools they need to avoid specification defects and improve system quality while simultaneously reducing the effort and cost of systems engineering.

  • GeoAI for Earth Observation Imagery

    Fundamentals and Practical Applications
    • 1st Edition
    • Dalton Lunga + 1 more
    • English
    GeoAI for Earth Observation Imagery: Fundamentals and Practical Applications comprehensively covers methodologies of AI and Machine Learning applications of image processing for Earth Observation (EO) Imagery. Traditional image processing methods face challenges with handling vast volumes of EO imagery, leading to efficiencies and limitations when extracting meaningful insights. AI-driven approaches can enhance the efficiency, accuracy, and scalability of image processing. Chapters cover essential methodologies including atmospheric compensation, image enhancement techniques like deblurring and superresolution, and advanced analysis methods such as semantic segmentation and object detection. Cutting edge approaches to computing, automating, and optimizing image processing tasks are also covered. Additionally, emerging trends in GeoAi and their implication on future research are reviewed. The book serves as an essential guide for navigating the complexities of spatial data and equips readers with knowledge to enhance their analytical capabilities.

  • Advances in Multimodal Large Language Models for Healthcare

    Methods and Applications
    • 1st Edition
    • Hari Mohan Pandey + 4 more
    • English
    Advances in Multimodal Large Language Models for Healthcare: Methods and Applications provides valuable insights on Large Language Models in healthcare applications for researchers, academics, and practitioners. The book explains key concepts, including artificial intelligence, machine learning, deep learning, and the evolution of neural networks and transformer models. It then covers generative AI and LLMs for a wide spectrum of healthcare applications, including mental health, clinical decision support, interactive system design, and sensitive analysis. Readers will find this to be a valuable deep dive into the emergent intersection of LLMs and health care, with guidance into applications, technical and programming methods, and more.Although LLMs have shown some promising results in the healthcare sector, numerous challenges need to be addressed before they can be used in patient care. The two key issues with the adoption of LLMs regarding healthcare settings are reliability, transparency, interpretation of results and bias (data and algorithm) management. Unless properly and adequately validated, there may be incorrect medical information provided by the LLM-based systems, which can lead to misdiagnosis or hazardous treatment errors. At this point, LLMs have not only been used for decision making or documentation, they have also proven to be useful in patient engagement through QA systems, medical chatbots, and virtual healthcare.

  • Artificial Intelligence Applications in Emerging Healthcare Technologies

    • 1st Edition
    • Miguel Antonio Wister Ovando + 2 more
    • English
    Artificial Intelligence Applications in Emerging Healthcare Technologies presents the latest advances and state-of-the-art methods and applications of computer science and emerging AI technologies in health and medicine. It explores the impact of artificial intelligence (AI) in healthcare for medical decision-making and data analysis, tackling topics such as cloud computing, cybersecurity, the internet of things, natural language processing, virtual health, data science applied to healthcare, personalized medicine, imaging, diagnosis, drug discovery, and diseases, among others. It is a great resource for researchers and students to learn how machine learning algorithms and other data science techniques have been implemented to solve healthcare-related problems. Chapters present adaptations or improvements on previous models and algorithms to process data from different sources. Other chapters investigate new formulations for the optimization of known procedures and algorithms. Finally, all chapters use experimental methods to study problems of interest in healthcare.

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