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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.

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121-130 of 2559 results in All results

Biomarkers in Cancer Detection and Monitoring of Therapeutics

  • 1st Edition
  • November 16, 2023
  • Ranbir Chander Sobti + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 3 2 3 - 9 5 1 1 6 - 6
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 5 1 1 7 - 3
Biomarkers in Cancer Detection and Monitoring of Therapeutics, Volume One, Discovery and Technologies discusses how molecular biomarkers are used to determine predisposition, facilitate detection, improve treatment and offer prevention guidelines for different cancer types. This first volume in the series focuses on techniques and approaches recently developed to assist in the decision of which biomarker to use for specific conditions. Topics covered include circulating tumor cells and circulating tumor DNA, exomes, tumor microenvironment, gene editing, artificial intelligence and robotics. In addition, the book discusses the development and applications of organoids and precision medicine.This book will be a valuable resource for cancer researchers, oncologists, graduate students and members of the biomedical field who are interested in the potential of biomarkers in cancer research.

Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images

  • 1st Edition
  • November 16, 2023
  • D. Jude Hemanth
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 3 9 9 9 - 4
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 4 0 0 0 - 6
Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images comprehensively examines the wide range of AI-based mammogram analysis methods for medical applications. Beginning with an introductory overview of mammogram data analysis, the book covers the current technologies such as ultrasound, molecular breast imaging (MBI), magnetic resonance (MR), and Positron Emission mammography (PEM), as well as the recent advancements in 3D breast tomosynthesis and 4D mammogram. Deep learning models are presented in each chapter to show how they can assist in the efficient processing of breast images.The book also discusses hybrid intelligence approaches for early-stage detection and the use of machine learning classifiers for cancer detection, staging and density assessment in order to develop a proper treatment plan. This book will not only aid computer scientists and medical practitioners in developing a real-time AI based mammogram analysis system, but also addresses the issues and challenges with the current processing methods which are not conducive for real-time applications.

Picture Fuzzy Logic and Its Applications in Decision Making Problems

  • 1st Edition
  • November 8, 2023
  • Chiranjibe Jana + 3 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 2 0 2 4 - 1
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 2 0 2 3 - 4
Picture Fuzzy Logic and Its Applications in Decision Making Problems provides methodological frameworks and the latest empirical research findings in the field of picture fuzzy operators and their applications in scientific research and real-world engineering problems. In this book, picture fuzzy sets are investigated, and different types of operators are defined to solve a number of important decision-making and optimization problems. The hybrid operator on picture fuzzy set based on the combination of picture fuzzy weighted averaging operators and picture fuzzy weighted geometric operators is developed and named Hybrid Picture Fuzzy Weighted Averaging Geometric (H-PFWAG) operator. In addition, another operator is developed for interval-valued picture fuzzy environment, which is named Hybrid Interval-Valued Picture Fuzzy Weighted Averaging Geometric (H-IVPFWAG) operator. These two operators are then demonstrated as solutions to Multiple-Attribute Decision-Making (MADM) problems. The picture fuzzy soft weighted aggregation operators (averaging and geometric) are defined, and these are applied to develop a multi-criteria group decision making system.

Embedded Systems

  • 2nd Edition
  • October 28, 2023
  • Jason D. Bakos
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 2 2 5 7 5 - 2
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 0 3 0 2 - 8
Embedded Systems: ARM Programming and Optimization, Second Edition combines an exploration of the ARM architecture with an examination of the facilities offered by the Linux operating system to explain how various features of program design can influence processor performance. The book demonstrates methods by which a programmer can optimize program code in a way that does not impact its behavior but instead improves its performance. Several applications, including image transformations, fractal generation, image convolution, computer vision tasks, and now machine learning are used to describe and demonstrate these methods. From this, the reader will gain insight into computer architecture and application design, as well as practical knowledge in embedded software design for modern embedded systems. The second edition has been expanded to include more topics of interest to upper level undergraduate courses in embedded systems.

Multi-Criteria Decision-Making for Renewable Energy

  • 1st Edition
  • October 24, 2023
  • Mohamed Abdel-Basset + 3 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 3 3 7 8 - 7
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 3 3 8 9 - 3
Multi-Criteria Decision-Making for Renewable Energy: Methods, Applications, and Challenges brings together the latest fuzzy and soft computing methods, models, and algorithms as applied to the field of renewable energy and supported by specific application examples and case studies. The book begins by approaching renewable energy sources, challenges and factors that affect their development, as well as green renewable energy sites and the utilization of fuzzy multi-criteria decision-making (MCDM) techniques in these broad contexts, as well as utilization in addressing the various environmental, economic, and social barriers to ensuring the sustainability of energy resources. Detailed chapters focus on the application of multi-criteria decision-making methods for planning, modeling and prioritization in specific areas of renewable energy, including solar energy, wind farms, solar-powered hydrogen production plants, biofuel production, energy storage, hydropower, and marine energy. Finally, future opportunities and research directions are explored.

Recent Advances in Nanocarriers for Pancreatic Cancer Therapy

  • 1st Edition
  • October 22, 2023
  • Prashant Kesharwani + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 9 1 4 2 - 8
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 5 2 8 8 - 7
Recent Advances in Nanocarriers for Pancreatic Cancer Therapy reviews thriving strategies concerning pancreatic cancer therapy, thoroughly describing the most recent developments in emerging modern drug delivery systems focused on, and derived from, nanotechnology. By providing a holistic understanding of the molecular pathways, conventional therapy and novel nanocarriers mediated drug delivery against pancreatic cancer, this work can be considered a complete package. The book offers a solution to the dissemination of data from a broad range of resources by providing an overview of the molecular pathways and conventional therapy of pancreatic cancer, the application of various nanocarriers, and more. This book equips scientists, clinicians and students to make rational treatment approaches based on nanomedicine for improving and extending the human life against pancreatic cancer.

Artificial Intelligence in the Age of Neural Networks and Brain Computing

  • 2nd Edition
  • October 10, 2023
  • Robert Kozma + 3 more
  • English
  • Paperback
    9 7 8 - 0 - 3 2 3 - 9 6 1 0 4 - 2
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 5 8 1 6 - 5
Artificial Intelligence in the Age of Neural Networks and Brain Computing, Second Edition demonstrates that present disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity, and smart autonomous search engines. The book covers the major basic ideas of "brain-like computing" behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as possible future alternatives. The present success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel, and Amazon, can be interpreted using the perspective presented in this book by viewing the co-existence of a successful synergism among what is referred to as computational intelligence, natural intelligence, brain computing, and neural engineering. The new edition has been updated to include major new advances in the field, including many new chapters.

Embedded System Design

  • 1st Edition
  • September 14, 2023
  • Lawrence J. Henschen + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 8 4 7 0 - 3
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 8 4 7 1 - 0
Embedded Systems Design: Methodologies and Issues presents methodologies for designing these systems and discusses major issues, both present and future, that designers must consider in bringing products with embedded processing to market. The book starts from the first step after product proposal (behavioral modeling) and goes through the steps for modeling internal operations. Specific areas of focus include methods for designing safe, reliable, and robust embedded systems. Sections cover selection of processors and related hardware as well as issues involved in designing related software. Finally, the book present issues that will occur in systems designed for the Internet of Things. This book is for junior/senior/MS students in computer science, computer engineering, and electrical engineering who intend to take jobs in industry designing and implementing embedded systems and Internet of Things applications.

Energy Management in Homes and Residential Microgrids

  • 1st Edition
  • September 14, 2023
  • Reza Hemmati
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 3 7 2 8 - 7
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 3 7 2 9 - 4
Energy Management in Homes and Residential Microgrids: Short-Term Scheduling and Long-Term Planning provides an in-depth exploration of Home Energy Management Systems (HEMS), with a focus on practical applications for both short- and long-term models. Through this guide, readers will learn how to create efficient systems that facilitate the integration of renewable energy into the grid and simultaneously manage end-users' energy consumption. The short-term operation of Home Energy Management Systems is analyzed through various lenses, including renewable energy integration, energy storage integration, uncertainty in parameters, off-grid operation, outages and events, resilience, electric vehicle integration, and battery swapping strategy.The modelling of these topics is explained with step-by-step instructions, and the parameters and implications are thoroughly discussed. Additionally, the book offers insight into the long-term expansion planning for residential microgrids, providing a detailed examination of dynamic modeling, control, and stability of these small-scale energy systems. Throughout the book, simple and advanced examples are provided, and each example comes with numerical data, detailed formulation, modelling, and simulation.

Machine Learning for Biomedical Applications

  • 1st Edition
  • September 7, 2023
  • Maria Deprez + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 1 2 - 8 2 2 9 0 4 - 0
  • eBook
    9 7 8 - 0 - 1 2 - 8 2 2 9 0 5 - 7
Machine Learning for Biomedical Applications: With Scikit-Learn and PyTorch presents machine learning techniques most commonly used in a biomedical setting. Avoiding a theoretical perspective, it provides a practical and interactive way of learning where concepts are presented in short descriptions followed by simple examples using biomedical data. Interactive Python notebooks are provided with each chapter to complement the text and aid understanding. Sections cover uses in biomedical applications, practical Python coding skills, mathematical tools that underpin the field, core machine learning methods, deep learning concepts with examples in Keras, and much more. This accessible and interactive introduction to machine learning and data analysis skills is suitable for undergraduates and postgraduates in biomedical engineering, computer science, the biomedical sciences and clinicians.

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