Skip to main content
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.

  • 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.

  • 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.

  • Advanced Intelligence Methods for Data Science and Optimization

    • 1st Edition
    • Amir Hossein Gandomi + 2 more
    • English
    Advanced Intelligence Methods for Data Science and Optimization covers the latest research trends and applications of AI topics such as deep learning, reinforcement learning, evolutionary algorithms, Bayesian optimization, and swarm intelligence. The book is a comprehensive guide that provides readers with theoretical concepts and case studies for applying advanced intelligence methods to real-world problems. Authored by a team of renowned experts in the field, the book offers a holistic approach to understanding and applying intelligence methods across various domains.It explores the fundamental concepts of data science and optimization, providing a strong foundation for readers to build upon, and will be a welcomed resource for AI researchers, data scientists, engineers, and developers on key topics such as evolutionary optimization techniques, reinforcement learning, Natural Language Processing, Bayesian optimization, advanced analytics for large-scale data, fuzzy logic, quantum computing, graph theory, convex optimization, differential evolution, and 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.

  • Knowledge Graphs and Large Language Models

    Current Approaches, Challenges, and Future Directions
    • 1st Edition
    • Sanju Tiwari + 3 more
    • English
    Knowledge Graphs and Large Language Models: Current Approaches, Challenges, and Future Directions explores the cutting-edge fusion of two powerful artificial intelligence technologies: Large Language Models (LLMs) and Knowledge Graphs (KGs). The book is structured to provide a comprehensive understanding of this emerging field. Chapters introduce the synergy between LLMs and KGs, delve into the capabilities and challenges of LLMs, focus on the structure, function, and significance of KGs, present a conceptual framework for bridging LLMs and KGs, discuss techniques for their integration, explore how LLMs can enhance KGs and vice versa, and showcase applications of LLM-KG synergy across various domains.Final sections addresses ethical, social, and technical challenges and future innovations. The book concludes by summarizing key insights and advancements in intelligent systems. This is an essential resource for graduate students, researchers, and professionals in computer science. It offers valuable insights for adopting LLMs, KGs, and their advanced applications in research and product development. By bridging the gap between these technologies, this book equips readers with the knowledge to drive innovation and enhance the capabilities of intelligent systems.

  • Explainable AI for Transparent and Trustworthy Medical Decision Support

    • 1st Edition
    • Abhishek Kumar + 4 more
    • English
    Explainable AI for Transparent and Trustworthy Medical Decision Support equips readers with a comprehensive and timely resource that presents the principles, methodologies, and real-world applications of explainable AI (XAI) within the medical context. Covering a wide range of use cases—from radiology and pathology to genomics and clinical decision support systems—the book provides in-depth discussions on how XAI techniques can enhance interpretability, improve clinician trust, meet regulatory requirements, and ultimately lead to better patient outcomes. The book demystifies the workings of machine learning models and highlights techniques that make them interpretable.It is designed to empower not only AI researchers and developers but also healthcare administrators and policymakers with the knowledge needed to evaluate, adopt, and trust AI solutions in critical medical applications. The book's authors bring together theory, implementation strategies, ethical implications, and case studies under one cover, offering a multidisciplinary perspective that aligns computer science with medical practice and healthcare policy.

  • Confidential Computing

    Principles and Technology
    • 1st Edition
    • Jiewen Yao
    • English
    At present, major companies are launching their own confidential computing solutions, which pose significant challenges to users. This book summarizes the common designs of various mainstream TEE hardware, and explains their commonalities to help understand the working principles of TEE hardware, facilitating users to define TEE usage scenarios through abstract commonalities.Confid... Computing: Principles and Technology comprehensively introduces the design principles and usage methods of TEE in terms of security models, lifecycle, attestation models, attack methods, and mitigation strategies, helping readers understand the security attributes and implementation points of confidential computing. At the same time, this book takes the TEE provided by the mainstream X86, ARM, and RISC-V architectures in the industry as examples to analyze the specific implementation methods and similarities and differences of hardware TEE, helping users deeply understand the advantages and disadvantages of different implementations, and hoping to provide some inspiration for future TEE software and hardware designers.

  • Usability Testing Essentials

    Ready, Set ...Test!
    • 3rd Edition
    • Carol M. Barnum
    • English
    Usability Testing Essentials: Ready, Set ...Test!, Third Edition presents a practical, step-by-step approach to learning the entire process of planning and conducting a usability test. The book explains how to analyze and apply results and what to do when confronted with budgetary and time restrictions. This is the ideal book for anyone involved in usability or user-centered design—from students to seasoned professionals. Updated throughout, this book reflects the latest approaches, tools, and techniques needed to begin usability testing or to advance in this area.

  • 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.

Related subjects