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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

    • Intelligent Systems and Learning Data Analytics in Online Education

      • 1st Edition
      • June 15, 2021
      • Santi Caballé + 4 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 3 4 1 0 5
      • eBook
        9 7 8 0 1 2 8 2 3 1 2 7 2
      Intelligent Systems and Learning Data Analytics in Online Education provides novel artificial intelligence (AI) and analytics-based methods to improve online teaching and learning. This book addresses key problems such as attrition and lack of engagement in MOOCs and online learning in general. This book explores the state of the art of artificial intelligence, software tools and innovative learning strategies to provide better understanding and solutions to the various challenges of current e-learning in general and MOOC education. In particular, Intelligent Systems and Learning Data Analytics in Online Education shares stimulating theoretical and practical research from leading international experts. This publication provides useful references for educational institutions, industry, academic researchers, professionals, developers, and practitioners to evaluate and apply.

    • Machine Learning, Big Data, and IoT for Medical Informatics

      • 1st Edition
      • June 13, 2021
      • Pardeep Kumar + 2 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 1 7 7 7 1
      • eBook
        9 7 8 0 1 2 8 2 1 7 8 1 8
      Machine Learning, Big Data, and IoT for Medical Informatics focuses on the latest techniques adopted in the field of medical informatics. In medical informatics, machine learning, big data, and IOT-based techniques play a significant role in disease diagnosis and its prediction. In the medical field, the structure of data is equally important for accurate predictive analytics due to heterogeneity of data such as ECG data, X-ray data, and image data. Thus, this book focuses on the usability of machine learning, big data, and IOT-based techniques in handling structured and unstructured data. It also emphasizes on the privacy preservation techniques of medical data. This volume can be used as a reference book for scientists, researchers, practitioners, and academicians working in the field of intelligent medical informatics. In addition, it can also be used as a reference book for both undergraduate and graduate courses such as medical informatics, machine learning, big data, and IoT.

    • Executing Data Quality Projects

      • 2nd Edition
      • May 21, 2021
      • Danette McGilvray
      • English
      • Paperback
        9 7 8 0 1 2 8 1 8 0 1 5 0
      • eBook
        9 7 8 0 1 2 8 1 8 0 1 6 7
      Executing Data Quality Projects, Second Edition presents a structured yet flexible approach for creating, improving, sustaining and managing the quality of data and information within any organization. Studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. Help is here! This book describes a proven Ten Step approach that combines a conceptual framework for understanding information quality with techniques, tools, and instructions for practically putting the approach to work – with the end result of high-quality trusted data and information, so critical to today’s data-dependent organizations. The Ten Steps approach applies to all types of data and all types of organizations – for-profit in any industry, non-profit, government, education, healthcare, science, research, and medicine. This book includes numerous templates, detailed examples, and practical advice for executing every step. At the same time, readers are advised on how to select relevant steps and apply them in different ways to best address the many situations they will face. The layout allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, best practices, and warnings. The experience of actual clients and users of the Ten Steps provide real examples of outputs for the steps plus highlighted, sidebar case studies called Ten Steps in Action. This book uses projects as the vehicle for data quality work and the word broadly to include: 1) focused data quality improvement projects, such as improving data used in supply chain management, 2) data quality activities in other projects such as building new applications and migrating data from legacy systems, integrating data because of mergers and acquisitions, or untangling data due to organizational breakups, and 3) ad hoc use of data quality steps, techniques, or activities in the course of daily work. The Ten Steps approach can also be used to enrich an organization’s standard SDLC (whether sequential or Agile) and it complements general improvement methodologies such as six sigma or lean. No two data quality projects are the same but the flexible nature of the Ten Steps means the methodology can be applied to all. The new Second Edition highlights topics such as artificial intelligence and machine learning, Internet of Things, security and privacy, analytics, legal and regulatory requirements, data science, big data, data lakes, and cloud computing, among others, to show their dependence on data and information and why data quality is more relevant and critical now than ever before.

    • Computer-Aided Oral and Maxillofacial Surgery

      • 1st Edition
      • April 29, 2021
      • Jan Egger + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 3 2 9 9 6
      • eBook
        9 7 8 0 1 2 8 2 3 4 2 3 5
      Computer-Aided Oral and Maxillofacial Surgery: Developments, Applications, and Future Perspectives is an ideal resource for biomedical engineers and computer scientists, clinicians and clinical researchers looking for an understanding on the latest technologies applied to oral and maxillofacial surgery. In facial surgery, computer-aided decisions supplement all kind of treatment stages, from a diagnosis to follow-up examinations. This book gives an in-depth overview of state-of-the-art technologies, such as deep learning, augmented reality, virtual reality and intraoperative navigation, as applied to oral and maxillofacial surgery. It covers applications of facial surgery that are at the interface between medicine and computer science. Examples include the automatic segmentation and registration of anatomical and pathological structures, like tumors in the facial area, intraoperative navigation in facial surgery and its recent developments and challenges for treatments like zygomatic implant placement.

    • The Era of Artificial Intelligence, Machine Learning, and Data Science in the Pharmaceutical Industry

      • 1st Edition
      • April 23, 2021
      • Stephanie K. Ashenden
      • English
      • Paperback
        9 7 8 0 1 2 8 2 0 0 4 5 2
      • eBook
        9 7 8 0 1 2 8 2 0 4 4 9 8
      The Era of Artificial Intelligence, Machine Learning and Data Science in the Pharmaceutical Industry examines the drug discovery process, assessing how new technologies have improved effectiveness. Artificial intelligence and machine learning are considered the future for a wide range of disciplines and industries, including the pharmaceutical industry. In an environment where producing a single approved drug costs millions and takes many years of rigorous testing prior to its approval, reducing costs and time is of high interest. This book follows the journey that a drug company takes when producing a therapeutic, from the very beginning to ultimately benefitting a patient’s life. This comprehensive resource will be useful to those working in the pharmaceutical industry, but will also be of interest to anyone doing research in chemical biology, computational chemistry, medicinal chemistry and bioinformatics.

    • Intelligence Science

      • 1st Edition
      • April 16, 2021
      • Zhongzhi Shi
      • English
      • Paperback
        9 7 8 0 3 2 3 8 5 3 8 0 4
      • eBook
        9 7 8 0 3 2 3 8 8 4 9 8 3
      Intelligence Science: Leading the Age of Intelligence covers the emerging scientific research on the theory and technology of intelligence, bringing together disciplines such as neuroscience, cognitive science, and artificial intelligence to study the nature of intelligence, the functional simulation of intelligent behavior, and the development of new intelligent technologies. The book presents this complex, interdisciplinary area of study in an accessible volume, introducing foundational concepts and methods, and presenting the latest trends and developments. Chapters cover the Foundations of neurophysiology, Neural computing, Mind models, Perceptual intelligence, Language cognition, Learning, Memory, Thought, Intellectual development and cognitive structure, Emotion and affect, and more. This volume synthesizes a very rich and complex area of research, with an aim of stimulating new lines of enquiry.

    • The Natural Language for Artificial Intelligence

      • 1st Edition
      • March 28, 2021
      • Dioneia Motta Monte-Serrat + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 4 1 1 8 9
      • eBook
        9 7 8 0 3 2 3 8 5 9 2 1 9
      The Natural Language for Artificial Intelligence presents the biological and logical structure typical of human language in its dynamic mediating process between reality and the human mind. The book explains linguistic functioning in the dynamic process of human cognition when forming meaning. After that, an approach to artificial intelligence (AI) is outlined, which works with a more restricted concept of natural language that leads to flaws and ambiguities. Subsequently, the characteristics of natural language and patterns of how it behaves in different branches of science are revealed to indicate ways to improve the development of AI in specific fields of science. A brief description of the universal structure of language is also presented as an algorithmic model to be followed in the development of AI. Since AI aims to imitate the process of the human mind, the book shows how the cross-fertilization between natural language and AI should be done using the logical-axiomatic structure of natural language adjusted to the logical-mathematical processes of the machine.

    • Thinking Machines

      • 1st Edition
      • March 27, 2021
      • Shigeyuki Takano
      • English
      • Paperback
        9 7 8 0 1 2 8 1 8 2 7 9 6
      • eBook
        9 7 8 0 1 2 8 1 8 2 8 0 2
      Thinking Machines: Machine Learning and Its Hardware Implementation covers the theory and application of machine learning, neuromorphic computing and neural networks. This is the first book that focuses on machine learning accelerators and hardware development for machine learning. It presents not only a summary of the latest trends and examples of machine learning hardware and basic knowledge of machine learning in general, but also the main issues involved in its implementation. Readers will learn what is required for the design of machine learning hardware for neuromorphic computing and/or neural networks.This is a recommended book for those who have basic knowledge of machine learning or those who want to learn more about the current trends of machine learning.

    • Visual Thinking for Information Design

      • 2nd Edition
      • March 26, 2021
      • Colin Ware
      • English
      • Paperback
        9 7 8 0 1 2 8 2 3 5 6 7 6
      • eBook
        9 7 8 0 1 2 8 2 3 5 6 8 3
      Visual Thinking for Information Design, Second Edition brings the science of perception to the art of design. The book takes what we now know about perception, cognition and attention and transforms it into concrete advice that students and designers can directly apply. It demonstrates how designs can be considered as tools for cognition and extensions of the viewer’s brain in much the same way that a hammer is an extension of the user’s hand. The book includes hundreds of examples, many in the form of integrated text and full-color diagrams. Renamed from the first edition, Visual Thinking for Design, to more accurately reflect its focus on infographics, this timely revision has been updated throughout and includes more content on pattern perception, the addition of new material illustrating color assimilation, and a new chapter devoted to communicating ideas through images.

    • Applications of Multi-Criteria Decision-Making Theories in Healthcare and Biomedical Engineering

      • 1st Edition
      • March 25, 2021
      • Ilker Ozsahin + 2 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 4 0 8 6 1
      • eBook
        9 7 8 0 1 2 8 2 4 0 8 7 8
      Applications of Multi-Criteria Decision-Making Theories in Healthcare and Biomedical Engineering contains several practical applications on how decision-making theory could be used in solving problems relating to the selection of best alternatives. The book focuses on assisting decision-makers (government, organizations, companies, general public, etc.) in making the best and most appropriate decision when confronted with multiple alternatives. The purpose of the analytical MCDM techniques is to support decision makers under uncertainty and conflicting criteria while making logical decisions. The knowledge of the alternatives of the real-life problems, properties of their parameters, and the priority given to the parameters have a great effect on consequences in decision-making. In this book, the application of MCDM has been provided for the real-life problems in health and biomedical engineering issues.

Related subjects

Applications

Artificial intelligence

Business intelligence

Computer systems organization

Computer vision and pattern recognition

Computing milieux

Data

Graphics cad hci

Hardware and architecture

Information systems

Internet and web technology

Software

Theory and mathematics