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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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1-10 of 2573 results in All results

Intelligent Data Analytics for Solar Energy Prediction and Forecasting

  • 1st Edition
  • May 1, 2025
  • Amit Kumar Yadav + 2 more
  • English
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 3 4 8 3 - 8
Intelligent Data Analytics for Solar Energy Prediction and Forecasting: Advances in Resource Assessment and PV Systems Optimization explores the utilization of advanced neural networks, machine learning and data analytics techniques for solar radiation prediction, solar energy forecasting, installation and maximum power generation. The book addresses relevant input variable selection, solar resource assessment, tilt angle calculation, and electrical characteristics of PV modules, including detailed methods, coding, modeling and experimental analysis of PV power generation under outdoor conditions. It will be of interest to researchers, scientists and advanced students across solar energy, renewables, electrical engineering, AI, machine learning, computer science, information technology and engineers. In addition, R&D professionals and other industry personnel with an interest in applications of AI, machine learning, and data analytics within solar energy and energy systems will find this book to be a welcomed resource.

A History of Angiogenesis

  • 1st Edition
  • April 1, 2025
  • Gianfranco Natale + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 3 9 7 9 - 6
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 3 9 8 0 - 2
A History of Angiogenesis: Discoveries, Research and the Therapeutic Potential presents a recent history of discoveries in the angiogenic field that contribute to the development of the anatomical knowledge of the process, experimental models, and new pharmacological approaches in different angiogenesis-related diseases. This multifaceted book is enriched with deep scientific contents, and each chapter clearly defines historical steps, the emerging role during the years of new morphological findings, molecular pathways, and targets. Focus is also directed on key challenges associated and future directions.The history of angiogenesis research is an intriguing tool for discovering answers to a wide array of queries arising in the biological and medical world. This comprehensive resource skillfully integrates all the key aspects related to angiogenesis, and will be of immense help to students, researchers, and industry experts who want to explore the last two decades of angiogenesis discoveries and research.

Encyclopedia of Bioinformatics and Computational Biology

  • 2nd Edition
  • March 22, 2025
  • Shoba Ranganathan + 2 more
  • English
  • Hardback
    9 7 8 - 0 - 3 2 3 - 9 5 5 0 2 - 7
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 5 5 0 3 - 4
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.

Programming Language Pragmatics

  • 5th Edition
  • March 21, 2025
  • Michael Scott + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 3 2 3 - 9 9 9 6 6 - 3
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 8 4 2 3 - 2
Programming Language Pragmatics is the most comprehensive programming language textbook available today, with nearly 1000 pages of content in the book, plus hundreds more pages of reference materials and ancillaries online. Michael Scott takes theperspective that language design and language implementation are tightly interconnected, and that neither can be fully understood in isolation. In an approachable, readable style, he discusses more than 50 languages in the context of understanding how code isinterpreted or compiled, providing an organizational framework for learning new languages, regardless of platform. This edition has been thoroughly updated to cover the most recent developments in programming language design and provides both a solid understanding of the most important issues driving software development today

Digital Twin, Blockchain, and Sensor Networks in the Healthy and Mobile City

  • 1st Edition
  • March 3, 2025
  • Tuan Anh Nguyen
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 3 4 1 7 4 - 8
  • eBook
    9 7 8 - 0 - 4 4 3 - 3 4 1 7 5 - 5
The global smart cities market size was valued at USD 1,226.9 billion in 2022 and is expected to register a compound annual growth rate (CAGR) of 25.8% from 2023 to 2030. Firstly and visually, a smart city is a city that has no traffic jams. In the smart cities, both information and communication technologies are integrated for exchanging real-time data between their citizens, governments, and organisations. Blockchain has been considered as the key driver for development of smart cities. Blockchain technology can provide high security for large communications and transactions between many stakeholders in the smart cities. In addition, digital twins are also considered as the starting key for construction of smart cities. Digital twin refers to a simulation of physical products in virtual space. This simulation makes full use of physical models/wireless sensor networks/ historical data of city operation to integrate big information (digital twin cities) under multi-discipline, multi-physical quantities, multi-scale, and multi-probability. Digital Twin, Blockchain, and Sensor Networks in the Healthy and Mobile City explores how digital twins and blockchain can be used in smart cities. Section 1 deals with their promising applications for safe and healthy cities, respectively. Section 2 covers other promising applications and current perspectives of blockchain and digital twin for future smart cities. Together with its companion volume, Digital Twin, Blockchain, and Sensor Networks in the City, this book will help us make sense of the vast amount of data around the city, and will guide us to use that data to create happy, healthy, safe and productive lives.

Data Mining

  • 5th Edition
  • March 1, 2025
  • James Foulds + 4 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 5 8 8 8 - 9
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 5 8 8 9 - 6
Data Mining: Practical Machine Learning Tools and Techniques, Fifth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated new edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including more recent deep learning content on topics such as generative AI (GANs, VAEs, diffusion models), large language models (transformers, BERT and GPT models), and adversarial examples, as well as a comprehensive treatment of ethical and responsible artificial intelligence topics. Authors Ian H. Witten, Eibe Frank, Mark A. Hall, and Christopher J. Pal, along with new author James R. Foulds, include today’s techniques coupled with the methods at the leading edge of contemporary research

Accelerating Digital Transformation with the Cloud and the Internet of Things (IoT)

  • 1st Edition
  • March 1, 2025
  • Yacine Atif + 1 more
  • Fatos Xhafa
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 2 2 1 7 - 7
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 2 2 1 8 - 4
Accelerating Digital Transformation with the Cloud and the Internet of Things (IoT) is a reference for IT engineers and decision-makers who may engage in IoT platform pilot projects. The resources covered in this book help establish plans for sustainable operations and management and assist with the long-term procurement of relevant IoT technologies. The aim of the book is to be exhaustive and holistic by pointing out numerous issues and related solution options that guide with daily challenges when deploying and running IoT platforms.The book is divided into three parts where each part includes relevant theoretical chapters and applied case studies. Part One focuses on architectural and federation options for the design and implementation of IoT platforms that foster strategic collaboration opportunities. Part Two addresses vertical security challenges across IoT platform layers. Finally, Part Three shows how IoT is driving the digital transformation wheel through existing and forthcoming case studies.

Federated Learning for Medical Imaging

  • 1st Edition
  • March 1, 2025
  • Xiaoxiao Li + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 3 6 4 1 - 9
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 3 6 4 2 - 6
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.In addition, it 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 is a complete resource for computer scientists and engineers as well as clinicians and medical care policymakers wanting to learn about the application of federated learning to medical imaging.

Necrobotics for Healthcare Applications and Management

  • 1st Edition
  • March 1, 2025
  • Hemachandran Kannan + 4 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 4 8 3 2 - 0
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 4 8 3 3 - 7
Necrobotics for Healthcare Applications and Management delves into the emerging area of necrobotics and its implications for healthcare. Exploring the convergence of robotics, technology, and healthcare, the book presents leading-edge research, practical implementations, and ethical considerations. It bridges a significant gap in healthcare literature, furnishing a contemporary and comprehensive perspective on necrobotics. Highlighting its distinct applications, management nuances, and ethical dimensions in the domain of medical robotics, the book equips readers with an in-depth grasp of this evolving field. It offers insights into technological intricacies, practical utilization, and ethical guidelines. Through real-world case studies and exemplar practices, it vividly demonstrates successful necrobotics deployments while addressing integration challenges. The book facilitates adept navigation of necrobotics complexities, spur innovation, enhance patient outcomes, and contribute to healthcare evolution. Catering to the distinct information requisites and daily obstacles encountered by engineers, healthcare practitioners, and researchers, the book offers extensive insights into necrobotics technologies, real-life case studies, and ethical reflections. It stands as a valuable resource for individuals striving to harness necrobotics' potential for efficacious healthcare solutions.

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

  • 1st Edition
  • March 1, 2025
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 3 0 0 7 8 - 3
  • eBook
    9 7 8 - 0 - 4 4 3 - 3 0 0 7 9 - 0
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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Applications

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