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Elsevier

Libros en Ciencias de la Computación

  • Machine Learning for Low-Latency Communications

    • 1 Edición
    • Yong Zhou + 4 más
    • Inglés
    Machine Learning for Low-Latency Communications presents the principles and practice of various deep learning methodologies for mitigating three critical latency components: access latency, transmission latency, and processing latency. In particular, the book develops learning to estimate methods via algorithm unrolling and multiarmed bandit for reducing access latency by enlarging the number of concurrent transmissions with the same pilot length. Task-oriented learning to compress methods based on information bottleneck are given to reduce the transmission latency via avoiding unnecessary data transmission.Lastly, three learning to optimize methods for processing latency reduction are given which leverage graph neural networks, multi-agent reinforcement learning, and domain knowledge. Low-latency communications attracts considerable attention from both academia and industry, given its potential to support various emerging applications such as industry automation, autonomous vehicles, augmented reality and telesurgery. Despite the great promise, achieving low-latency communications is critically challenging. Supporting massive connectivity incurs long access latency, while transmitting high-volume data leads to substantial transmission latency.

  • Computational Intelligence in Sustainable Computing and Optimization

    Trends and Applications
    • 1 Edición
    • Balamurugan Balusamy + 4 más
    • Inglés
    Computational Intelligence in Sustainable Computing and Optimization: Trends and Applications focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in applications, such as agriculture, biomedical systems, bioinformatics, business intelligence, economics, disaster management, e-learning, education management, financial management, and environmental policies. The book presents research in sustainable computing and optimization, combining methods from engineering, mathematics, artificial intelligence, and computer science to optimize environmental resourcesComputation... intelligence in the field of sustainable computing combines computer science and engineering in applications ranging from Internet of Things (IoT), information security systems, smart storage, cloud computing, intelligent transport management, cognitive and bio-inspired computing, and management science. In addition, data intelligence techniques play a critical role in sustainable computing. Recent advances in data management, data modeling, data analysis, and artificial intelligence are finding applications in energy networks and thus making our environment more sustainable.

  • Fuzzy Methods for Assessment and Decision Making

    • 1 Edición
    • Michael Gr. Voskoglou
    • Inglés
    Fuzzy Methods for Assessment and Decision Making presents the assessment of learning and problem-solving skills with qualitative grades. These methods are outcomes of the author’s research work on the subject for more than 20 years. In particular, a hybrid assessment model uses the Center of Gravity (COG) defuzzification technique, closed real intervals (grey numbers), neutrosophic sets, and soft sets as tools. The book starts with the basic mathematical background that is needed for an understanding of its contents. The Rectangular Fuzzy Assessment Model (RFAM) of Subbotin and Voskoglou is presented next, the outcomes of which are compared to those of the GPA index.The book presents innovative fuzzy assessment methods, enabling readers to assess the mean and quality performance of learning or problem-solving skills of a group of students when qualitative (linguistic) grades are used for this purpose. In the case of using linguistic grades for the assessment of a group’s skills, the classical method of calculating the mean value of the (numerical) grades cannot be applied. Also, no safe conclusions can be obtained on comparing the quality performance of two groups when the values of their GPA index are equal.

  • A Practical Introduction to Virtual Reality

    From Concepts to Executables
    • 1 Edición
    • Lori Rebenitsch + 2 más
    • Inglés
    A Practical Introduction to Virtual Reality: From Concepts to Executables is written for the undergraduate computer science student taking a course in virtual reality. This tutorial-based text is organized so that by the end of the semester students will have created their first VR game, including sound and various interactions. The materials are written from the position of the student and the student’s professor as opposed to the professional with prior graphics experience.Beginning with an introductory chapter covering the ten universal basics necessary for VR coding, the book moves on to such topics as putting together a VR set-up, creating Heads Up displays, building scene trees, learning how to import 3D models and animations, lighting and audio, and more, until by the end of the book, students will have a final project game ready for beta testing and publishing!

  • Handbook of Robotic Surgery

    • 1 Edición
    • Stênio de Cássio Zequi + 1 más
    • Inglés
    Handbook of Robotic Surgery serves as a primer covering the main areas of knowledge in robotic surgery. This comprehensive book provides essential information on all aspects related to robotic surgery, from the present up to the future. The discussion presented in sections ranges from the historical background of robotic surgery up to more recent and future technological innovations such as remote controls, surgically distant collaboration, simulators, modern surgical robotics, fluorescence-guided surgery, and virtual reality. The book also contains sections dedicated to the safety conditions in surgery and patient protection, which will be suitable for surgeons, health professionals, biomedical engineering professionals, healthcare administrators, and students. There are specific chapters for all areas in which robotic surgery has been used in daily clinical practice or is under development.

  • Data Science in the Medical Field

    • 1 Edición
    • Seifedine Kadry + 1 más
    • Inglés
    Data science has the potential to influence and improve fundamental services such as the healthcare sector. This book recognizes this fact by analyzing the potential uses of data science in healthcare. Every human body produces 2 TB of data each day. This information covers brain activity, stress level, heart rate, blood sugar level, and many other things. More sophisticated technology, such as data science, allows clinicians and researchers to handle such a massive volume of data to track the health of patients. The book focuses on the potential and the tools of data science to identify the signs of illness at an extremely early stage.

  • High Performance Computing

    Modern Systems and Practices
    • 2 Edición
    • Thomas Sterling + 2 más
    • Inglés
    Performance Computing: Modern Systems and Practices is a fully comprehensive and easily accessible treatment of high performance computing, covering fundamental concepts and essential knowledge while also providing key skills training. With this book, students will begin their careers with an understanding of possible directions for future research and development in HPC, domain scientists will learn how to use supercomputers as a key tool in their quest for new knowledge, and practicing engineers will discover how supercomputers can employ HPC systems and methods to the design and simulation of innovative products.This new edition has been fully updated, and has been reorganized and restructured to improve accessibility for undergraduate students while also adding trending content such as machine learning and a new chapter on CUDA.

  • Uncertainty in Computational Intelligence-Based Decision Making

    • 1 Edición
    • Ali Ahmadian + 3 más
    • Inglés
    Uncertainty in Computational Intelligence-Based Decision-Making focuses on techniques for reasoning and decision-making under uncertainty that are used to solve issues in artificial intelligence (AI). It covers a wide range of subjects, including knowledge acquisition and automated model construction, pattern recognition, machine learning, natural language processing, decision analysis, and decision support systems, among others.The first chapter of this book provides a thorough introduction to the topics of causation in Bayesian belief networks, applications of uncertainty, automated model construction and learning, graphic models for inference and decision making, and qualitative reasoning. The following chapters examine the fundamental models of computational techniques, computational modeling of biological and natural intelligent systems, including swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems, and evolutionary computation. They also examine decision making and analysis, expert systems, and robotics in the context of artificial intelligence and computer science.

  • Artificial Intelligence of Things (AIoT)

    Current and Future Trends
    • 1 Edición
    • Fadi Al-Turjman + 2 más
    • Inglés
    Artificial Intelligence of Things (AIoT): Current and Future Trends brings together researchers and developers from a wide range of domains to share ideas on how to implement technical advances, create application areas for intelligent systems, and how to develop new services and smart devices connected to the Internet. Section One covers AIoT in Everything, providing a wide range of applications for AIoT methods and technologies. Section Two gives readers comprehensive guidance on AIoT in Societal Research and Development, with practical case studies of how AIoT is impacting cultures around the world. Section Three covers the impact of AIoT in educational settings.The book also covers new capabilities such as pervasive sensing, multimedia sensing, machine learning, deep learning, and computing power. These new areas come with various requirements in terms of reliability, quality of service, and energy efficiency.

  • Speech Signal Processing Based on Deep Learning in Complex Acoustic Environments

    • 1 Edición
    • Xiao-Lei Zhang
    • Inglés
    Speech Signal Processing Based on Deep Learning in Complex Acoustic Environments provides a detailed discussion of deep learning-based robust speech processing and its applications. The book begins by looking at the basics of deep learning and common deep network models, followed by front-end algorithms for deep learning-based speech denoising, speech detection, single-channel speech enhancement multi-channel speech enhancement, multi-speaker speech separation, and the applications of deep learning-based speech denoising in speaker verification and speech recognition.

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