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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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101-110 of 2559 results in All results

Artificial Intelligence and Machine Learning for Open-world Novelty

  • 1st Edition
  • Volume 134
  • February 19, 2024
  • Ganesh Chandra Deka + 1 more
  • English
  • Hardback
    9 7 8 - 0 - 3 2 3 - 9 9 9 2 8 - 1
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 9 9 2 9 - 8
Artificial Intelligence and Machine Learning for Open-world Novelty, Volume 134 in the Advances in Computers series presents innovations in computer hardware, software, theory, design and applications, with this updated volume including new chapters on AI and Machine Learning for Real-world problems, Graph Neural Network for learning complex problems, Adaptive Software platform architecture for Aerial Vehicle Safety Levels in real-world applications, OODA Loop for Learning Open-world Novelty Problems, Privacy-Aware Crowd Counting Methods for Real-World Environment, AI and Machine Learning for 3D Computer Vision Applications in Open-world, and PIM Hardware accelerators for real-world problems.Other sections cover Irregular Situations in Real-World Intelligent Systems, Offline Reinforcement Learning Methods for Real-world Problems, Addressing Uncertainty Challenges for Autonomous Driving in Real-World Environments, and more.

Federated Learning

  • 1st Edition
  • February 9, 2024
  • Lam M. Nguyen + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 9 0 3 7 - 7
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 9 0 3 8 - 4
Federated Learning: Theory and Practi ce provides a holisti c treatment to federated learning as a distributed learning system with various forms of decentralized data and features. Part I of the book begins with a broad overview of opti mizati on fundamentals and modeling challenges, covering various aspects of communicati on effi ciency, theoretical convergence, and security. Part II featuresemerging challenges stemming from many socially driven concerns of federated learning as a future public machine learning service. Part III concludes the book with a wide array of industrial applicati ons of federated learning, as well as ethical considerations, showcasing its immense potential for driving innovation while safeguarding sensitive data.Federated Learning: Theory and Practi ce provides a comprehensive and accessible introducti on to federated learning which is suitable for researchers and students in academia, and industrial practitioners who seek to leverage the latest advance in machine learning for their entrepreneurial endeavors.

Internet of Things: Architectures for Enhanced Living Environments

  • 1st Edition
  • Volume 133
  • February 7, 2024
  • Goncalo Marques
  • English
  • Hardback
    9 7 8 - 0 - 3 2 3 - 9 1 0 8 9 - 7
  • eBook
    9 7 8 - 0 - 3 2 3 - 9 1 0 9 0 - 3
Internet of Things: Architectures for Enhanced Living Environments, Volume 133 presents interesting chapters on a variety of timely topics, including Explainable Artificial Intelligence for Enhanced Living Environments: A Study on User Perspective, Human behavioral anomaly pattern mining within an IoT environment: an exploratory study, Indoor Activity Localization Technologies for Assisted Living: Opportunities, Challenges, and Future Directions, Smart Indoor Air Quality Monitoring for Enhanced Living Environments and Ambient Assisted Living, Usability evaluation for the IoT use in Enhanced Living Environments, Roadmap to the elderly enhanced living and care environments: applications and challenges on the Internet of Things domain, and much more.

Engineering Simulation and its Applications

  • 1st Edition
  • February 1, 2024
  • Xin-She Yang
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 4 0 8 4 - 6
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 4 0 8 5 - 3
Engineering Simulation and its Applications: Algorithms and Numerical Methods covers the essential quantitative methods needed for engineering simulations, introducing optimization techniques that can be used in the design of systems to minimize cost and maximize efficiency. This book serves as a reference and textbook for courses such as engineering simulation, design optimization, mathematical modeling, numerical methods, data analysis, and engineering management. Diverse coverage of the various subject areas within the field puts the essential topics into a single book for easy access for graduates and senior undergraduates. It also serves as a reference book for lecturers and industrial practitioners.

Trolley Crash

  • 1st Edition
  • January 26, 2024
  • Peggy Wu + 3 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 5 9 9 1 - 6
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 5 9 9 2 - 3
The prolific deployment of Artificial Intelligence (AI) across different fields has introduced novel challenges for AI developers and researchers. AI is permeating decision making for the masses, and its applications range from self-driving automobiles to financial loan approvals. With AI making decisions that have ethical implications, responsibilities are now being pushed to AI designers who may be far-removed from how, where, and when these ethical decisions occur.Trolley Crash: Approaching Key Metrics for Ethical AI Practitioners, Researchers, and Policy Makers provides audiences with a catalogue of perspectives and methodologies from the latest research in ethical computing. This work integrates philosophical and computational approaches into a unified framework for ethical reasoning in the current AI landscape, specifically focusing on approaches for developing metrics. Written for AI researchers, ethicists, computer scientists, software engineers, operations researchers, and autonomous systems designers and developers, Trolley Crash will be a welcome reference for those who wish to better understand metrics for ethical reasoning in autonomous systems and related computational applications.

Computational Intelligence Methods for Sentiment Analysis in Natural Language Processing Applications

  • 1st Edition
  • January 19, 2024
  • D. Jude Hemanth
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 2 0 0 9 - 8
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 2 0 1 0 - 4
Computational Intelligence for Sentiment Analysis in Natural Language Processing Applications provides a solution to this problem through detailed technical coverage of AI-based Sentiment Analysis methods for various applications. The book's authors provide readers with an in-depth look at the challenges and associated solutions, including case studies and real-world scenarios from across the globe. Development of scientific and enterprise applications are covered that will aid computer scientists in building practical/real-world AI-based Sentiment Analysis systems. With the vast increase in Big Data, computational intelligence approaches have become a necessity for Natural Language Processing and Sentiment Analysis in a wide range of decision-making application areas.

Human-Computer Interaction

  • 2nd Edition
  • January 12, 2024
  • I. Scott MacKenzie
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 4 0 9 6 - 9
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 4 0 9 7 - 6
Human-Computer Interaction: An Empirical Research Perspective is the definitive guide to empirical research in HCI. The book begins with foundational topics, including historical context, the human factor, interaction elements, and the fundamentals of science and research. From there, the book progresses to the methods for conducting an experiment to evaluate a new computer interface or interaction technique. There are detailed discussions and how-to analyses on models of interaction, focusing on descriptive models and predictive models. Writing and publishing a research paper is explored with helpful tips for success.Throughout the book, readers will find hands-on exercises, checklists, and real-world examples. This is a must-have, comprehensive guide to empirical and experimental research in HCI – an essential addition to your HCI library.

Fractional Difference, Differential Equations, and Inclusions

  • 1st Edition
  • January 11, 2024
  • Saïd Abbas + 3 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 3 6 0 1 - 3
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 3 6 0 2 - 0
Fractional Difference, Differential Equations, and Inclusions: Analysis and Stability is devoted to the existence and stability (Ulam-Hyers-Rassias stability and asymptotic stability) of solutions for several classes of functional fractional difference equations and inclusions. Covered equations include delay effects of finite, infinite, or state-dependent nature, and tools used to establish the existence results for the proposed problems include fixed point theorems, densifiability techniques, monotone iterative technique, notions of Ulam stability, attractivity and the measure of non-compactness, as well as the measure of weak noncompactness. The tools of fractional calculus are found to be of great utility in improving the mathematical modeling of many natural phenomena and processes occurring in the areas of engineering, social, natural, and biomedical sciences. All abstract results in the book are illustrated by examples in applied mathematics, engineering, biomedical, and other applied sciences.

Targeting Angiogenesis, Inflammation and Oxidative Stress in Chronic Diseases

  • 1st Edition
  • January 10, 2024
  • Tapan Behl + 2 more
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 1 3 5 8 7 - 3
  • eBook
    9 7 8 - 0 - 4 4 3 - 1 3 5 8 8 - 0
Targeting Angiogenesis, Inflammation and Oxidative Stress in Chronic Diseases presents recent advances in the vivid molecular pathways targeting angiogenesis, inflammation, and oxidative stress that contribute very widely to the genesis of chronic diseases. The books highlights drugs from natural and synthetic origins in the management/prevention/treatment of diseases, along with the drug delivery approaches. The book’s authors from various key institutions around the globe deliver well-structured and designed chapters. The systematic presented information and knowledge will surely aid consistency and continuity. The multifaceted book is enriched with deep scientific content. Each chapter clearly defines the facts, the emerging role of molecular pathways, and targets and focus, along with key challenges and future directions that will provide new areas for researchers to explore new targets in the domain.

Synthetic Data and Generative AI

  • 1st Edition
  • January 9, 2024
  • Vincent Granville
  • English
  • Paperback
    9 7 8 - 0 - 4 4 3 - 2 1 8 5 7 - 6
  • eBook
    9 7 8 - 0 - 4 4 3 - 2 1 8 5 6 - 9
Synthetic Data and Generative AI covers the foundations of machine learning with modern approaches to solving complex problems and the systematic generation and use of synthetic data. Emphasis is on scalability, automation, testing, optimizing, and interpretability (explainable AI). For instance, regression techniques – including logistic and Lasso – are presented as a single method without using advanced linear algebra. Confidence regions and prediction intervals are built using parametric bootstrap without statistical models or probability distributions. Models (including generative models and mixtures) are mostly used to create rich synthetic data to test and benchmark various methods.

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