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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

    • Artificial Intelligence for the Water-Energy-Food Nexus

      • 1st Edition
      • December 1, 2025
      • Shahryar Jafarinejad + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 4 0 1 9 2
      • eBook
        9 7 8 0 4 4 3 3 4 0 2 0 8
      Artificial Intelligence for the Water–Energy–Food Nexus considers the interrelationships among water, energy, and food, which are key to sustainable development and the potential of artificial intelligence (AI) as a useful tool to facilitate research and development within and between these areas as well as the water–energy–food (WEF) nexus.The first chapter introduces the WEF nexus concepts, assessment/analysis methodologies and tools, challenges, trends, and future perspectives. The second chapter summarizes AI applications to the water sector/industry with a focus on the importance, general applications, and real-world applications, as well as the challenges and future perspectives. The third chapter focuses on the application of AI techniques to the water and wastewater treatment systems, including treatment processes, urban drinking water systems, and integrated urban drainage systems. The fourth chapter explores the application of AI techniques to the nonrenewable and renewable energy systems, load monitoring, load demand forecasting, smart grids, energy optimization and process control, energy storage systems, and case studies and real-world applications, as well as the challenges in AI application to the energy industry and future directions. The application of AI techniques in the food industry in the areas of organoleptic properties, nutrition, toxicology, and food chemistry; biotechnology processes and microbiology security; food processing and manufacturing; conservation and storage conditions; supply chains, markets, and distribution; and food industry environments (circular economy, water, and energy management), as well as the challenges and opportunities are discussed in the fifth chapter. The final chapter reviews/presents the application of AI techniques to address problems associated with the WEF nexus. This book can be of interest to all those who are looking to understand and utilize AI techniques in the context of water, energy, food, and the WEF nexus, including researchers, advanced students, faculty, engineers, R&D, industry professionals, and policymakers.

    • Advances in Fog Computing and the Internet of Things for Smart Healthcare

      • 1st Edition
      • November 19, 2025
      • Joseph Bamidele Awotunde + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 4 4 1 2
      • eBook
        9 7 8 0 4 4 3 3 3 4 4 2 9
      Advances in Fog Computing and the Internet of Things for Smart Healthcare delves into the transformative impact of fog computing and IoT on modern healthcare systems. This comprehensive guide educates researchers and graduate students on the fundamental concepts of these technologies, illustrating their practical applications in healthcare. Real-world use cases showcase the technologies' ability to enhance patient monitoring and personalized medicine. The book also addresses significant challenges such as privacy, security, data management, and regulatory compliance, providing strategies for overcoming them.Alongside its companion book, Fundamentals of Fog Computing and the Internet of Things for Smart Healthcare, this volume empowers various industries to leverage IoT technologies while optimizing performance and system efficiency. It highlights the crucial role of fog computing in processing data closer to the source, ensuring faster and more efficient data processing and contributing to the creation of effective IoT ecosystems. This synergy between fog computing and IoT facilitates smarter applications and services, advancing the landscape of healthcare with more efficient, personalized, and accessible services.

    • Advances in Image Processing, Reliability, and Artificial Intelligence

      • 1st Edition
      • November 16, 2025
      • Mario J. Divan + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 4 2 6 6 0
      • eBook
        9 7 8 0 4 4 3 3 4 2 6 7 7
      Advances in Image Processing, Reliability, and Artificial Intelligence: Data Centred-Techniques and Applications in Edge Computing provides a clear outlook of the mechanisms, risks, challenges, and opportunities in system reliability for image processing and AI applications running on edge devices. It provides Best Known Configuration (BKC) and Methods (BKM) while discussing trends and future works based on current research. The content serves as a reference for practitioners and provides a state-of-the-art for researchers in the area. It provides foundations to analyse and replicate different applications through use cases. It tackles concerns for how reliability aspects (i.e., fault tolerance, availability, maturity, and recoverability) are addressed for applications running in an environment that is not fully controlled and exposed to environmental variations.

    • Green Flexible Electronics for Sustainable Healthcare

      • 1st Edition
      • November 14, 2025
      • Anitha Velu + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 7 5 5 4 8
      • eBook
        9 7 8 0 4 4 3 2 7 5 5 5 5
      Flexible electronics, or flex circuits, involve the construction of electrical circuits using flexible plastic substrates, such as polyimide, PEEK, or transparent conductive polyester sheets. Flexible electronic assemblies are made using a variety of manufacturing techniques, including printing, laminating, and deposition, which enables the circuit board to bend or take on a desired shape. They allow the user to create extremely flexible, light-weight, and thin electronic components such as batteries, screens, and sensors. Green Flexible Electronics for Sustainable Healthcare discusses incorporating flexible and printed electronics in the field of sustainable healthcare. It details how to utilise natural materials in the design, fabrication and application of flexible electronic-based wearables and sensors. It also offers a detailed analysis of the effects and challenges of integrating flexible electronics within the healthcare ecosystem. Green Flexible Electronics for Sustainable Healthcare considers the implications of the advances in flexible electronics with regards data privacy, security and scalability.

    • Multimodal Learning Using Heterogeneous Data

      • 1st Edition
      • November 14, 2025
      • Saeid Eslamian + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 7 5 2 8 9
      • eBook
        9 7 8 0 4 4 3 2 7 5 2 9 6
      Multimodal Learning Using Heterogeneous Data is a comprehensive guide to the emerging field of multimodal learning, which focuses on integrating diverse data types such as text, images, and audio within a unified framework. The book delves into the challenges and opportunities presented by multimodal data and offers insights into the foundations, techniques, and applications of this interdisciplinary approach. It is intended for researchers and practitioners interested in learning more about multimodal learning and is a valuable resource for those working on projects involving data analysis from multiple modalities.The book begins with a comprehensive introduction, focusing on multimodal learning's foundational principles and the intricacies of heterogeneous data. It then delves into feature extraction, fusion techniques, and deep learning architectures tailored for multimodal data. It also covers transfer learning, pre-processing challenges, and cross-modal information retrieval. The book highlights the application of multimodal learning in specialized contexts such as sentiment analysis, data generation, medical imaging, and ethical considerations. Real-world case studies are woven into the narrative, illuminating the applications of multimodal learning in diverse domains such as natural language processing, multimedia content analysis, autonomous systems, and cognitive computing. The book concludes with an insightful exploration of multimodal data analytics across social media, surveillance, user behavior, and a forward-looking examination of future trends and practical implementations. As a collective resource, Multimodal Learning Using Heterogeneous Data illuminates the powerful utility of multimodal learning to elevate machine learning tasks while also highlighting the need for innovative solutions and methodologies. The book acknowledges the challenges associated with deep learning and the growing importance of ethical considerations in the collection and analysis of multimodal data.Overall, Multimodal Learning Using Heterogeneous Data provides an expansive panorama of this rapidly evolving field, its potential for future research and application, and its vital role in shaping machine learning's evolution.

    • Mathematical Modeling for Big Data Analytics

      • 1st Edition
      • November 3, 2025
      • Passent El-Kafrawy + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 6 7 3 5 2
      • eBook
        9 7 8 0 4 4 3 2 6 7 3 6 9
      Mathematical Modelling for Big Data Analytics is a comprehensive guidebook that explores the use of mathematical models and algorithms for analyzing large and complex datasets. The book covers a range of topics, including statistical modeling, machine learning, optimization techniques, and data visualization, and provides practical examples and case studies to demonstrate their applications in real-world scenarios. Users will find a clear and accessible resource to enhance their skills in mathematical modeling and data analysis for big data analytics. Real-world examples and case studies demonstrate how to approach and solve complex data analysis problems using mathematical modeling techniques.This book will help readers understand how to translate mathematical models and algorithms into practical solutions for real-world problems. Coverage of the theoretical foundations of big data analytics, including qualitative and quantitative analytics techniques, digital twins, machine learning, deep learning, optimization, and visualization techniques make this a must have resource.

    • Video Health Monitoring in Hospitals

      • 1st Edition
      • November 1, 2025
      • Wenjin Wang + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 6 5 8 6 0
      • eBook
        9 7 8 0 4 4 3 2 6 5 8 7 7
      Video Health Monitoring in Hospitals discusses the emergence of camera-based, contactless physiological measurement as a groundbreaking solution in healthcare monitoring. The book highlights the technology's non-invasiveness, capacity for continuous and long-term monitoring, and its ability to capture not only vital signs but also contextual information and behaviors. A unique aspect of this book is its rich set of compelling healthcare applications that will attract broader audiences (including researchers, engineers, clinicians, and students) from multidisciplinary fields.Finally, the book discusses the role of artificial intelligence in enhancing healthcare applications and aims to engage the healthcare industry in adopting this innovative approach to improve patient care and outcomes.

    • Human-Machine interfaces in Medical Robotics

      • 1st Edition
      • November 1, 2025
      • Yanpei Huang + 6 more
      • English
      • Paperback
        9 7 8 0 4 4 3 1 3 7 2 3 5
      • eBook
        9 7 8 0 4 4 3 1 3 7 2 4 2
      Human-Machine Interfaces in Medical Robotics presents essential and advanced information on developing intuitive human-machine interfaces (HMI) for robotic surgery and rehabilitation. This book provides extensive coverage of multidisciplinary information needed to develop efficient HMI, discussing core technologies of the field, including hand-free control strategies, sensory feedback, data-driven approaches, human-robot shared control, autonomous control, human motor adaption, training, and learning.Arranged in three parts, including interfaces in medical robotics, intelligent machines, and human users, this book provides potential solutions to open questions like what the optimal interface and efficient interaction mode is to facilitate a surgeon’s operation, a patient’s motor control, or human augmentation.

    • Energy-Efficient Devices and Circuits for Neuromorphic Computing

      • 1st Edition
      • October 31, 2025
      • Farooq Ahmad Khanday
      • English
      • Paperback
        9 7 8 0 4 4 3 2 9 9 8 1 0
      • eBook
        9 7 8 0 4 4 3 2 9 9 8 2 7
      Energy-Efficient Devices and Circuits for Neuromorphic Computing is an important contribution to this field, covering topics from neuron dynamics to energy-efficient CMOS devices and circuits. The book delves into theoretical analysis of learning processes in spiking neural networks, two-terminal neuromorphic devices, material-engineered neuromorphic devices, and novel biomimetic Si devices. It offers insights into the latest developments in non-volatile memory crossbar arrays and emerging post-CMOS devices. Overall, it provides a comprehensive overview of energy-efficient neuromorphic computing architecture. This book is an essential resource for researchers, engineers, and students working in neuromorphic computing and energy-efficient electronics.

    • Recent Advances in Computational Intelligence Applications for Biometrics and Biomedical Devices

      • 1st Edition
      • October 30, 2025
      • Aditya Khamparia + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 0 1 2 4
      • eBook
        9 7 8 0 4 4 3 3 3 0 1 3 1
      Recent Advances in Computational Intelligence Applications for Biometrics and Biomedical Devices focuses on the intersection of biometric-driven computational approaches and techniques within a connected multi-modal environment, particularly emphasizing their applications in healthcare. The book explores cutting-edge methodological approaches that leverage technologies like blockchain and integrate them with information fusion, data security for medical devices, and trust management. Readers with find this to be a comprehensive overview of the topics covered, including machine learning and deep learning for biomedical-based biometrics, computational medical imaging techniques, security strategies for healthcare systems, AI technology for multimodal biometrics, and feature reduction techniques.Other sections cover blockchain and fog computing models for medical sensor data storage and evolutionary optimization for biometric feature identification and recognition, amongst others.

Related subjects

Applications

Artificial 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