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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.

BooksJournals

A History of Angiogenesis

  • 1st Edition
  • June 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.

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.

Programming Language Pragmatics

  • 5th Edition
  • April 4, 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

Statistical Modeling and Robust Inference for One-shot Devices

  • 1st Edition
  • April 1, 2025
  • Narayanaswamy Balakrishnan + 1 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 4 1 5 3 - 9
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 4 1 5 2 - 2
Statistical Modeling and Robust Interference for One-shot Devices offers a comprehensive investigation on robust techniques for one-shot devices under accelerated life tests. With numerous examples, case studies, and included R codes in each chapter, this book helps readers implement their own codes, use them in proposed examples, and conduct their own research on one-shot device testing data. Researchers, mathematicians, engineers, and students working on accelerated life testing data analysis and robust methodologies will surely find this to be a welcomed resource.The study of one-shot devices such as automobile airbags, fire extinguishers, and antigen tests is rapidly becoming an important problem in the area of reliability engineering. These devices, which get destroyed or must be rebuilt after use, are particular cases of extreme censoring, which makes the problem of estimating their reliability and lifetime challenging. As classical statistical and inferential methods do not consider the issue of robustness, this book is a welcomed addition to the conversation.

Data Mining

  • 5th Edition
  • April 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

Data Insights

  • 2nd Edition
  • April 1, 2025
  • Hunter Whitney
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 1 6 2 7 - 5
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 1 6 2 6 - 8
Data Insights: New Ways to Visualize and Make Sense of Data, Second Edition offers multi-disciplinary perspectives and useful information about how visualizations can open your eyes to data. This thought-provoking book takes a conversational approach to presenting an overview of the subject, while also focusing on key details. It highlights the ideas and work of a variety of people who are actively contributing to this still emerging field. Case studies from business analytics, healthcare, games, security, and network monitoring, among others, portray what is going on in data visualization today. A diverse blend of original illustrations and real-world examples, both classical and cutting-edge, help fill in the picture.This book provides an approachable overview of important aspects of data visualization, and: Demonstrates, with a variety of case studies, how visualizations can foster a clearer and more comprehensive understanding of data• Answers the question, How can data visualization help me? with discussions of how it fits into a wide array of purposes and situations; Makes the case that data visualization is not just about technology; it also involves a deeply human processThe second chapter of revised version of the book, the Human-Centered Design for Data Visualization focuses on two key areas affecting inclusion and diversity:· Debiasing your data and your visualizations· Neurodiversity and inclusion considerations for working with data and visualizations. Issues include: Color Blindness• Data Sonification; Multimodal data interfaces. These issues will be touched on throughout the book and will be brought up in the thought leaders interview sections. The book will explore the ways data analytics and visualization can decrease and decrease inequality.

Neural Network Algorithms and Their Engineering Applications

  • 1st Edition
  • April 1, 2025
  • Chao Huang + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 9 2 0 2 - 6
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 9 2 0 3 - 3
Neural Network Algorithms and Their Engineering Applications presents the relevant techniques used to improve the global search ability of neural network algorithms in solving complex engineering problems with multimodal properties. The book provides readers with a complete study of how to use artificial neural networks to design a population-based metaheuristic algorithm, which in turn promotes the application of artificial neural networks in the field of engineering optimization.The authors provide a deep discussion for the potential application of machine learning methods in improving the optimization performance of the neural network algorithm, helping readers understand how to use machine learning methods to design improved versions of the algorithm. Users will find a wealth of source code that covers all applied algorithms. Code applications enhance readers' understanding of methods covered and facilitate readers' ability to apply the algorithms to their own research and development projects.

Dimensionality Reduction in Machine Learning

  • 1st Edition
  • April 1, 2025
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 3 2 8 1 8 - 3
  • eBook
    9 7 8 - 0 - 4 4 3 - 3 2 8 1 9 - 0
Dimensionality Reduction in Machine Learning covers both the mathematical and programming sides of dimension reduction algorithms, comparing them in various aspects. Part One provides an introduction to Machine Learning and the Data Life Cycle, with chapters covering the basic concepts of Machine Learning, essential mathematics for Machine Learning, and the methods and concepts of Feature Selection. Part Two covers Linear Methods for Dimension Reduction, with chapters on Principal Component Analysis and Linear Discriminant Analysis. Part Three covers Non-Linear Methods for Dimension Reduction, with chapters on Linear Local Embedding, Multi-dimensional Scaling, and t-distributed Stochastic Neighbor Embedding.Finally, Part Four covers Deep Learning Methods for Dimension Reduction, with chapters on Feature Extraction and Deep Learning, Autoencoders, and Dimensionality reduction in deep learning through group actions. With this stepwise structure and the applied code examples, readers become able to apply dimension reduction algorithms to different types of data, including tabular, text, and image data.

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.

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.

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