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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.

  • Digital Twins in the Smart Classroom

    Utilising Sensor Networks in the Educational Environment
    • 1st Edition
    • Tuan Anh Nguyen
    • English
    Digital Twins in the Smart Classroom: Utilising Sensor Networks in the Educational Environment explores virtual schools that have incorporated digital twin computing into the day-to-day running of the classroom. The book discusses the foundational concepts, practical applications, future directions, and the various aspects of virtual school, such as the student's daily activities, intelligent wireless sensor networks, privacy issues, and how the internet of things, artificial intelligence, machine learning, cloud computing, and fog/edge-computing can enable a smarter, more efficient, more optimized classroom.The smart classroom allows the incorporation of digital devices and learning software into the school environment, as well as sensor networks for tracking classroom processes, for data gathering, and to developed insights into the management of scholarly activity. Additionally, modern infrastructure within schools can involve the installation of advanced Information and communication technology (ICT): student-friendly data can be collected from wearable devices (personal digital assistants, iPads, iPods, smart watches, etc.) via wireless sensor networks; smart sensors can monitor the classroom environment, such as noise level, CO2 level, temperature, humidity, lecturers’ voice, and students/lecturers’ motion (by PIR - passive infrared sensors), and much more.

  • Machine Learning Made Visual with Python

    • 1st Edition
    • Weisheng Jiang
    • English
    Machine Learning Made Visual with Python makes machine learning intuitive through Python coding and dynamic visualizations. The book helps readers grasp complex math concepts by showing how algorithms evolve step-by-step. Readers will learn how to develop a hands-on, visual, and practical path to mastering core machine learning algorithms. Importantly, the book includes practical examples and coding exercises.

  • Green Intrusion Detection Systems for IoT

    • 1st Edition
    • Saeid Jamshidi + 3 more
    • English
    Green Intrusion Detection Systems for IoT tackles the pressing security challenges posed by the rapid expansion of the Internet of Things (IoT). The book delves into innovative, lightweight security models and energy-aware IDS mechanisms that strike a balance between security efficacy, computational efficiency, and environmental sustainability. Sections discuss the transformative role of IoT and the need for sustainable security solutions, highlight the distinctions between traditional and Green IDS, focus on lightweight security models essential for resource-constrained IoT devices, and delve into energy-efficient network designs.Additional sections explore green IDS mechanisms, including machine learning and distributed approaches, IoT vulnerabilities and mitigation strategies, practical examples of sustainable IDS in various smart environments, real-world case studies, and future directions in sustainable IoT security. The book concludes with actionable recommendations that align technological advancements with global sustainability goals.

  • Artificial Intelligence, Machine Learning and Blockchain in Digital Twin Computing

    • 1st Edition
    • Parikshit Narendra Mahalle + 1 more
    • English
    Artificial Intelligence, Machine Learning and Blockchain in Digital Twin Computing explores the synergy between artificial intelligence, machine learning, blockchain technology, and digital twin computing. The book overviews each technology, establishing a clear understanding of their individual roles and potential when combined. The second section delves into the integration of these technologies, focusing on key themes such as enhancing system simulations, ensuring data integrity, and enabling secure, real-time decision-making. Practical applications and case studies are used to illustrate how this convergence can drive innovation in industries like manufacturing, healthcare, and smart cities. Final sections look ahead, discussing emerging trends, challenges, and future opportunities.Digita... twin computing is the bridge between the real and virtual worlds. Digital twin computing also is the mirror that reflects the real world into the virtual world. Blockchain technology can refine the digital twins (DTs) by ensuring transparency, decentralized data storage, data immutability, and peer-to-peer communication in various applications. DT provides a powerful tool able to generate a huge amount of training data for machine learning algorithms (MLAs).

  • Encyclopedia of Multi-Attribute Decision Making (MADM)

    • 1st Edition
    • Gholamreza Haseli + 2 more
    • English
    Encyclopedia of Multi-Attribute Decision Making (MADM) presents current methods in MADM in a simple way, including Sections on Weighting Methods, Extensions for the MADM Methods, Ranking Methods, and Outranking Methods. Each method chapter presents two numerical examples for each method, one simple example with less than six criteria and six alternatives, and one complex example with six or more criteria and six or more alternatives. In addition, most chapters are written by the original developers of the method, ensuring insight into and practical application of MADM. The book is also filled with over 200 full-color figures that illustrate methods and applications.The book, in one volume, demystifies the complex world of MADM, blending theoretical concepts with hands-on practices and case studies. It bridges the gap between theory and practical implementation, providing clear and practical understanding of the key principles and techniques essential for harnessing the power of MADM.

  • Grey Wolf Optimizer

    A Pack of Solutions for Your Optimization Problems
    • 1st Edition
    • Seyedali Mirjalili
    • English
    Grey Wolf Optimizer: A Pack of Solutions for Your Optimization Problems offers in-depth coverage of recent theoretical advancements in GWO, as well as several variants, improvements, and hybrid approaches developed to enhance the GWO's performance and adaptability. The use of generative AI to improve this algorithm and make it more generic is also explored, along with diverse applications across multiple fields to illustrate the practical utility and versatility of the methods presented. The book offers a deep dive into the algorithm's foundations and presents new developments to help researchers overcome common challenges.It features numerous case studies and real-world examples across various fields, such as engineering, healthcare, finance, and environmental management. These applications demonstrate the versatility and effectiveness of the GWO in addressing complex, interdisciplinary challenges, making the content highly relevant and practical for readers. Written by some of the world’s most highly cited researchers in the field of artificial intelligence, algorithms, and machine learning, the book serves as an essential resource for researchers and practitioners interested in applying and developing the Grey Wolf Optimizer.

  • Digital Twin Technology and Smart Grid

    • 1st Edition
    • Iraklis Varlamis + 2 more
    • English
    Digital Twin Technology and Smart Grid explores the intersection of these technologies, which are essential for the evolution of energy systems. The book explains how it utilizes intelligent wireless sensor networks, the Internet of Things, artificial intelligence, machine learning, cloud, edge, and fog-computing to monitor power consumption. It discusses how security risks and privacy challenges can be accommodated, and explains the ethical/legal implications of collecting data. As the global energy landscape moves toward greater sustainability and decentralization, digital twins present unprecedented opportunities to enhance grid efficiency, bolster resilience, and support the integration of renewable energy sources.The integration of Digital Twin (DT) technology with Smart Grids (SG) represents a groundbreaking development in energy management, making this a highly significant and timely topic. As urban areas expand and energy demands rise, the need for more efficient, sustainable, and resilient energy systems becomes critical. DT technology, with its ability to create real-time, virtual replicas of physical systems, offers unprecedented opportunities for enhancing the performance, reliability, and security of smart grids.

  • Complexity in Mathematical Biology for Sustainable Development

    Modeling Climate, Disease, and Ecosystems through Difference, Differential, and Fractional Theory
    • 1st Edition
    • Fatma Bozkurt
    • English
    Complexity in Mathematical Biology for Sustainable Development: Modeling Climate, Disease, and Ecosystems through Difference, Differential, and Fractional Theory introduces new mathematical methods to derive complex modeling solutions for a wide range of engineering and scientific research applications. The book strikes a balance between high-level mathematical theory and technical derivations, offering step-by-step explanations, real-world case studies, and clear introductions to advanced mathematical models. Solutions include modeling and quantifying complexity, with emphasis placed on the growing need for interdisciplinary collaboration, the integration of real-time data into models, and the development of adaptive frameworks challenges such as pandemics, biodiversity loss, and climate uncertainty.The book is designed to meet the needs of a diverse primary audience, from graduate students to professionals in fields such as computer science, public health, environmental policy, applied mathematics, and biotechnology. By providing both theoretical foundations and practical applications, the book equips readers with the skills and knowledge to tackle pressing global challenges through mathematical models, making it a valuable resource for both academic and professional development.

  • Smart Healthcare 2.0

    Integrating Digital Twins with AI-Driven Predictive Analytics
    • 1st Edition
    • Ramesh Chandra Poonia + 1 more
    • English
    Smart Healthcare 2.0: Integrating Digital Twins with AI-Driven Predictive Analytics offers a groundbreaking exploration of how digital twin technology, combined with real-time sensing and predictive analytics, is transforming healthcare delivery. As the global healthcare landscape shifts toward proactive, personalized care, this book addresses the urgent need for comprehensive resources that unify artificial intelligence, Internet of Things (IoT), and biomedical engineering within the digital twin framework. It provides an essential guide for researchers, engineers, and clinicians aiming to harness virtual patient models and data-driven insights to improve health outcomes and system efficiency in the era of ubiquitous healthcare.This volume covers a wide spectrum of topics, starting with foundational concepts of digital twins in precision health and advancing through smart sensing technologies, scalable system architectures, and AI-powered predictive analytics. Readers will explore detailed discussions on edge-cloud computing, secure communication protocols including blockchain, and simulation platforms that enable virtual patient modeling. The book also addresses critical themes such as chronic disease management, emergency response optimization, ethical AI deployment, interoperability standards, and workforce readiness. Real-world case studies and future-focused chapters on cognitive twins and quantum simulation provide a rich, multidisciplinary perspective.

  • AI-Powered Developments in Medical Robotics

    Data-Driven Techniques for Enhanced Surgical Efficiency
    • 1st Edition
    • Thomas Heinrich Musiolik + 3 more
    • English
    AI-Powered Developments in Medical Robotics: Data-Driven Techniques for Enhanced Surgical Efficiency offers a comprehensive exploration of AI-driven innovations, robotics, and data-driven techniques specifically tailored for medical applications. This book strikes a balance by addressing foundational principles, emerging technologies, and their practical implementation in real-world scenarios. It enhances its value through the inclusion of real-world case studies and interdisciplinary perspectives, making it relevant for professionals, researchers, and students alike. The book explores future developments, such as augmented and virtual reality in medical robotics, positioning itself as a forward-thinking resource. By addressing current gaps in the field, including regulatory challenges, training needs, and cost-effectiveness, it ensures a well-rounded approach that appeals to both advanced and emerging markets. This multifaceted perspective enriches the reader's understanding and equips them with actionable insights for navigating the complexities of AI-driven healthcare robotics. The book serves as a definitive reference for a global audience seeking innovation and practical solutions in the rapidly evolving landscape of medical technology, bridging the gap between theory and practice in a critical area of healthcare advancement.

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