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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.

  • Edge Intelligence in Cyber-Physical Systems

    Foundations and Applications
    • 1st Edition
    • Wei Yu
    • English
    Edge Intelligence in Cyber-Physical Systems: Foundations and Applications provides a comprehensive overview of best practices for building edge intelligence into cyber-physical systems. This book covers the foundations and applications of synergizing machine learning at the edge of CPS, leveraging an edge computing infrastructure. Divided into four parts, the first section of the book reviews the foundations, principles, and representative application domains of CPS. The second part covers machine learning, edge computing, and their needs in CPS, defining edge intelligence and its principles, challenges, and research directions. The third part presents tutorials and foundational research works on realizing edge intelligence in representative CPS. The fourth part explores the problem space of threats and countermeasures in building edge intelligence into CPS. Researchers, graduate students and professionals in computer science, data science, and electrical engineering will find this to be a valuable resource on the principles and applications of edge intelligence in cyber-physical systems as well as the development of interdisciplinary techniques to advance the field.

  • Advanced Machine Learning for Cyber-Attack Detection in IoT Networks

    • 1st Edition
    • Dinh Thai Hoang + 3 more
    • English
    Advanced Machine Learning for Cyber-Attack Detection in IoT Networks analyzes diverse machine learning techniques, including supervised, unsupervised, reinforcement, and deep learning, along with their applications in detecting and preventing cyberattacks in future IoT systems. Chapters investigate the key challenges and vulnerabilities found in IoT security, how to handle challenges in data collection and pre-processing specific to IoT environments, as well as what metrics to consider for evaluating the performance of machine learning models. Other sections look at the training, validation, and evaluation of supervised learning models and present case studies and examples that demonstrate the application of supervised learning in IoT security.

  • Medical Oncology Compendium

    • 1st Edition
    • Ramon Andrade B de Mello
    • English
    Medical Oncology Compendium discusses several important topics in oncology with the help of leading experts worldwide who incorporate not only knowledge on recent developments in the field, but contextualize them within diverse socioeconomic environments to guarantee the applicability of the content in challenging scenarios. The book comprehensively discusses topics such as surgery, radiology, carcinogenesis, screening, assessment tools, evidence-based medicine, and precision oncology as applicable to different cancer types as non-small and small cell lung cancer, mesothelioma, breast cancer, gastric-rectal cancer, female specific cancers, prostate, skin and bone sarcomas.In addition, it discusses options to minimize oncology pain and palliative care. It is a valuable resource for oncologists, clinicians, researchers, healthcare workers and members of biomedical field who needs to understand more about diagnosis, treatment options and support for cancer patients.

  • Emerging Fuzzy Intelligent Systems for Smart Healthcare Management

    Applications of Disc q-Rung Orthopair Fuzzy Sets
    • 1st Edition
    • Shahzaib Ashraf + 3 more
    • English
    Emerging Fuzzy Intelligent Systems for Smart Healthcare Management: Applications of Disc q-Rung Orthopair Fuzzy Sets presents comprehensive methodological frameworks and the latest empirical research findings concerning disc q-rung orthopair fuzzy operators, with a specific focus on their applications in smart technologies for healthcare management. The book solves a crucial problem by offering readers an invaluable opportunity to conduct a comparative analysis, contrasting the proposed methods with their existing knowledge base. Disc q-Rung Orthopair sets, being the generalization of q-Rung Orthopair fuzzy sets, which are, in turn, the generalization of Pythagorean fuzzy sets, extend the capabilities of handling uncertainty beyond conventional fuzzy sets.The authors strive to narrow the knowledge gap by clarifying the practical applications of disc q-rung orthopair fuzzy logic. In addition, it explores an enhanced version of q-Rung Orthopair Fuzzy Sets, specifically focusing on Disc q-Rung Orthopair Fuzzy Sets, introducing various types of operators. These operators play a crucial role in solving decision-making and optimization problems. A notable contribution is the development of a hybrid operator, termed as the Disc q-Rung Orthopair Fuzzy Hybrid Weighted Averaging/Geometric (D-qROFHWA/G) operator.

  • ChatGPT

    Principles and Architecture
    • 1st Edition
    • Ge Cheng
    • English
    ChatGPT: Principles and Architecture bridges the knowledge gap between theoretical AI concepts and their practical applications. It equips industry professionals and researchers with a deeper understanding of large language models, enabling them to effectively leverage these technologies in their respective fields. In addition, it tackles the complexity of understanding large language models and their practical applications by demystifying underlying technologies and strategies used in developing ChatGPT and similar models. By combining theoretical knowledge with real-world examples, the book enables readers to grasp the nuances of AI technologies, thus paving the way for innovative applications and solutions in their professional domains.Sections focus on the principles, architecture, pretraining, transfer learning, and middleware programming techniques of ChatGPT, providing a useful resource for the research and academic communities. It is ideal for the needs of industry professionals, researchers, and students in the field of AI and computer science who face daily challenges in understanding and implementing complex large language model technologies.

  • Statistical Modeling and Robust Inference for One-shot Devices

    • 1st Edition
    • Narayanaswamy Balakrishnan + 1 more
    • English
    The study of one-shot devices such as automobile airbags, fire extinguishers, or antigen tests, is rapidly becoming an important problem in the area of reliability engineering. These devices, which are destroyed or must be rebuilt after use, are a particular case of extreme censoring, which makes the problem of estimating their reliability and lifetime challenging. However, classical statistical and inferential methods do not consider the issue of robustness.Statistic... Modeling and Robust Interference for One-shot Devices offers a comprehensive investigation of robust techniques of one-shot devices under accelerated-life tests. With numerous examples and case studies in which the proposed methods are applied, this book includes detailed R codes in selected chapters to help readers implement their own codes and use them in the proposed examples and in their own research on one-shot devicetesting data. Researchers, mathematicians, engineers, and students working on acceleratedlife testing data analysis and robust methodologies will find this to be a welcome resource.

  • Encyclopedia of Bioinformatics and Computational Biology

    • 2nd Edition
    • Shoba Ranganathan + 2 more
    • English
    Bioinformatics and Computational Biology (BCB) combine elements of computer science, information technology, mathematics, statistics, and biotechnology, providing the methodology and in silico solutions to mine biological data and processes, for knowledge discovery.In the era of molecular diagnostics, targeted drug design, translational medicine and Big Data for personalized medicine, computational methods for data analysis are essential tools for biochemistry, biology, biotechnology, pharmacology, biomedical and computer science, as well as mathematics and statistics. New areas are emerging, and relatively isolated fields are becoming current hot research areas in BCB, such as Artificial Intelligence, Quantitative Biology, Computational Vaccinology, Epidemiology and Infection Diffusion, Synthetic Biology, and Phenomics. The role of BCB in characterizing SARS-CoV-2 variants and facing the COVID-19 pandemic is just one example of how these tools can help us better prepare for such future events.This Encyclopedia comprises three sections, covering Methods, Topics, and Applications. The methodologies and algorithms underpinning BCB are described in the Methods section; Topics covers traditional areas such as phylogeny, as well as more recent areas such as translational bioinformatics, cheminformatics and environmental informatics; Applications provides guidance for commonly asked “how to” questions.Navigating the maze of confusing jargon and the plethora of software tools is often confronting for students and researchers alike. This comprehensive and unique resource provides up-to-date theory and application content to address molecular data analysis requirements, with precise definitions of terminology and lucid explanations by field experts.

  • The UX Book

    Agile UX Design for a Quality User Experience
    • 3rd Edition
    • Rex Hartson + 1 more
    • English
    The UX Book: Agile Design for a Quality User Experience, Third Edition, takes a practical, applied, hands-on approach to UX design based on the application of established and emerging best practices, principles, and proven methods to ensure a quality user experience. The approach is about practice, drawing on the creative concepts of design exploration and visioning to make designs that appeal to the emotions of users, while moving toward processes that are lightweight, rapid, and agile—to make things as good as resources permit and to value time and other resources in the process.Designed as a textbook for aspiring students and a how-to handbook and field guide for UX professionals, the book is accompanied by in-class exercises and team projects.The approach is practical rather than formal or theoretical. The primary goal is to imbue an understanding of what a good user experience is and how to achieve it. To better serve this, processes, methods, and techniques are introduced early to establish process-related concepts as context for discussion in later chapters.

  • Federated Learning for Medical Imaging

    Principles, Algorithms, and Applications
    • 1st Edition
    • Xiaoxiao Li + 2 more
    • English
    Federated Learning for Medical Imaging: Principles, Algorithms, and Applications gives a deep understanding of the technology of federated learning (FL), the architecture of a federated system, and the algorithms for FL. It shows how FL allows multiple medical institutes to collaboratively train and use a precise machine learning (ML) model without sharing private medical data via practical implantation guidance. The book includes real-world case studies and applications of FL, demonstrating how this technology can be used to solve complex problems in medical imaging. The book also provides an understanding of the challenges and limitations of FL for medical imaging, including issues related to data and device heterogeneity, privacy concerns, synchronization and communication, etc.This book is a complete resource for computer scientists and engineers, as well as clinicians and medical care policy makers, wanting to learn about the application of federated learning to medical imaging.

  • Deep Learning in Action: Image and Video Processing for Practical Use

    • 1st Edition
    • Abdussalam Elhanashi + 1 more
    • English
    Artificial intelligence technology has entered an extraordinary phase of fast development and wide application. The techniques developed in traditional AI research areas, such as computer vision and object recognition, have found many innovative applications in an array of real-world settings. The general methodological contributions from AI, such as a variety of recently developed deep learning algorithms, have also been applied to a wide spectrum of fields such as surveillance applications, real-time processing, IoT devices, and health care systems. The state-of-the-art and deep learning models have wider applicability and are highly efficient. Deep Learning in Action: Image and Video Processing for Practical Use provides a comprehensive and accessible resource for both intermediate to advanced readers seeking to harness the power of deep learning in the domains of video and image processing. The book bridges the gap between theoretical concepts and practical implementation by emphasizing lightweight approaches, enabling readers to efficiently apply deep learning techniques to real-world scenarios. It focuses on resource-efficient methods, making it particularly relevant in contexts where computational constraints are a concern.

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