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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

    • Biostatistics and Computer-based Analysis of Health Data using Stata

      • 1st Edition
      • August 24, 2016
      • Christophe Lalanne + 1 more
      • English
      • Hardback
        9 7 8 1 7 8 5 4 8 1 4 2 0
      • eBook
        9 7 8 0 0 8 1 0 1 0 8 4 6
      This volume of the Biostatistics and Health Sciences Set focuses on statistics applied to clinical research. The use of Stata for data management and statistical modeling is illustrated using various examples. Many aspects of data processing and statistical analysis of cross-sectional and experimental medical data are covered, including regression models commonly found in medical statistics. This practical book is primarily intended for health researchers with basic knowledge of statistical methodology. Assuming basic concepts, the authors focus on the practice of biostatistical methods essential to clinical research, epidemiology and analysis of biomedical data (including comparison of two groups, analysis of categorical data, ANOVA, linear and logistic regression, and survival analysis). The use of examples from clinical trials and epideomological studies provide the basis for a series of practical exercises, which provide instruction and familiarize the reader with essential Stata packages and commands.

    • Advanced Data Analysis and Modelling in Chemical Engineering

      • 1st Edition
      • August 23, 2016
      • Denis Constales + 4 more
      • English
      • Hardback
        9 7 8 0 4 4 4 5 9 4 8 5 3
      • eBook
        9 7 8 0 4 4 4 5 9 4 8 4 6
      Advanced Data Analysis and Modeling in Chemical Engineering provides the mathematical foundations of different areas of chemical engineering and describes typical applications. The book presents the key areas of chemical engineering, their mathematical foundations, and corresponding modeling techniques. Modern industrial production is based on solid scientific methods, many of which are part of chemical engineering. To produce new substances or materials, engineers must devise special reactors and procedures, while also observing stringent safety requirements and striving to optimize the efficiency jointly in economic and ecological terms. In chemical engineering, mathematical methods are considered to be driving forces of many innovations in material design and process development.

    • The Basics of Cyber Safety

      • 1st Edition
      • August 20, 2016
      • John Sammons + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 4 1 6 6 5 0 9
      • eBook
        9 7 8 0 1 2 4 1 6 6 3 9 4
      The Basics of Cyber Safety: Computer and Mobile Device Safety Made Easy presents modern tactics on how to secure computer and mobile devices, including what behaviors are safe while surfing, searching, and interacting with others in the virtual world. The book's author, Professor John Sammons, who teaches information security at Marshall University, introduces readers to the basic concepts of protecting their computer, mobile devices, and data during a time that is described as the most connected in history. This timely resource provides useful information for readers who know very little about the basic principles of keeping the devices they are connected to—or themselves—secure while online. In addition, the text discusses, in a non-technical way, the cost of connectedness to your privacy, and what you can do to it, including how to avoid all kinds of viruses, malware, cybercrime, and identity theft. Final sections provide the latest information on safe computing in the workplace and at school, and give parents steps they can take to keep young kids and teens safe online.

    • Advances in Computers

      • 1st Edition
      • Volume 103
      • August 19, 2016
      • English
      • Hardback
        9 7 8 0 1 2 8 0 9 9 4 1 4
      • eBook
        9 7 8 0 1 2 8 0 5 1 6 7 2
      Advances in Computers, the latest volume in the series published since 1960, presents detailed coverage of innovations in computer hardware, software, theory, design, and applications. In addition, it provides contributors with a medium in which they can explore their subjects in greater depth and breadth than journal articles usually allow. As a result, many articles have become standard references that continue to be of significant, lasting value in this rapidly expanding field.

    • Automated Theorem Proving: A Logical Basis

      • 1st Edition
      • August 19, 2016
      • D.W. Loveland
      • English
      • Paperback
        9 7 8 1 4 9 3 3 0 5 5 1 3
      • eBook
        9 7 8 1 4 8 3 2 9 6 7 7 7
      Fundamental Studies in Computer Science, Volume 6: Automated Theorem Proving: A Logical Basis aims to organize, augment, and record the major conceptual advances in automated theorem proving. The publication first examines the role of logical systems and basic resolution. Discussions focus on the Davis-Putnam procedure, ground resolution, semantic trees, general resolution procedure, basic concepts of first-order logic, refutation procedures, and preparation of formulas. The text then takes a look at the refinements of resolution, including unit preference and set-of-support, ordered clause deductions, and setting and linear refinements. The monograph tackles subsumption, resolution with equality, and resolution and problem reduction format. Topics include problem reduction format, paramodulation and linear refinements, paramodulation, and subsumption for linear and nonlinear procedures. The publication is a dependable reference for students and researchers interested in automated theorem proving.

    • Up and Running with AutoCAD 2017

      • 1st Edition
      • August 18, 2016
      • Elliot J. Gindis
      • English
      • Paperback
        9 7 8 0 1 2 8 1 1 0 5 8 4
      • eBook
        9 7 8 0 1 2 8 1 1 0 5 9 1
      Up and Running with AutoCAD 2017: 2D and 3D Drawing and Modeling presents Gindis’ combination of step-by-step instruction, examples, and insightful explanations. The emphasis from the beginning is on core concepts and practical application of AutoCAD in engineering, architecture, and design. Equally useful in instructor-led classroom training, self-study, or as a professional reference, the book is written with the user in mind by a long-time AutoCAD professional and instructor based on what works in the industry and the classroom.

    • Resolving Spectral Mixtures

      • 1st Edition
      • Volume 30
      • August 13, 2016
      • English
      • Hardback
        9 7 8 0 4 4 4 6 3 6 3 8 6
      • eBook
        9 7 8 0 4 4 4 6 3 6 4 4 7
      Resolving Spectral Mixtures: With Applications from Ultrafast Time-Resolved Spectroscopy to Superresolution Imaging offers a comprehensive look into the most important models and frameworks essential to resolving the spectral unmixing problem—from multivariate curve resolution and multi-way analysis to Bayesian positive source separation and nonlinear unmixing. Unravelling total spectral data into the contributions from individual unknown components with limited prior information is a complex problem that has attracted continuous interest for almost four decades. Spectral unmixing is a topic of interest in statistics, chemometrics, signal processing, and image analysis. For decades, researchers from these fields were often unaware of the work in other disciplines due to their different scientific and technical backgrounds and interest in different objects or samples. This led to the development of quite different approaches to solving the same problem. This multi-authored book will bridge the gap between disciplines with contributions from a number of well-known and strongly active chemometric and signal processing research groups. Among chemists, multivariate curve resolution methods are preferred to extract information about the nature, amount, and location in time (process) and space (imaging and microscopy) of chemical constituents in complex samples. In signal processing, assumptions are usually around statistical independence of the extracted components. However, the chapters include the complexity of the spectral data to be unmixed as well as dimensionality and size of the data sets. Advanced spectroscopy is the key thread linking the different chapters. Applications cover a large part of the electromagnetic spectrum. Time-resolution ranges from femtosecond to second in process spectroscopy and spatial resolution covers the submicronic to macroscopic scale in hyperspectral imaging.

    • The Data and Analytics Playbook

      • 1st Edition
      • August 12, 2016
      • Lowell Fryman + 2 more
      • English
      • Paperback
        9 7 8 0 1 2 8 0 2 3 0 7 5
      • eBook
        9 7 8 0 1 2 8 0 2 5 4 7 5
      The Data and Analytics Playbook: Proven Methods for Governed Data and Analytic Quality explores the way in which data continues to dominate budgets, along with the varying efforts made across a variety of business enablement projects, including applications, web and mobile computing, big data analytics, and traditional data integration. The book teaches readers how to use proven methods and accelerators to break through data obstacles to provide faster, higher quality delivery of mission critical programs. Drawing upon years of practical experience, and using numerous examples and an easy to understand playbook, Lowell Fryman, Gregory Lampshire, and Dan Meers discuss a simple, proven approach to the execution of multiple data oriented activities. In addition, they present a clear set of methods to provide reliable governance, controls, risk, and exposure management for enterprise data and the programs that rely upon it. In addition, they discuss a cost-effective approach to providing sustainable governance and quality outcomes that enhance project delivery, while also ensuring ongoing controls. Example activities, templates, outputs, resources, and roles are explored, along with different organizational models in common use today and the ways they can be mapped to leverage playbook data governance throughout the organization.

    • Managing Trade-offs in Adaptable Software Architectures

      • 1st Edition
      • August 11, 2016
      • Ivan Mistrik + 4 more
      • English
      • Paperback
        9 7 8 0 1 2 8 0 2 8 5 5 1
      • eBook
        9 7 8 0 1 2 8 0 2 8 9 1 9
      Managing Trade-Offs in Adaptable Software Architectures explores the latest research on adapting large complex systems to changing requirements. To be able to adapt a system, engineers must evaluate different quality attributes, including trade-offs to balance functional and quality requirements to maintain a well-functioning system throughout the lifetime of the system. This comprehensive resource brings together research focusing on how to manage trade-offs and architect adaptive systems in different business contexts. It presents state-of-the-art techniques, methodologies, tools, best practices, and guidelines for developing adaptive systems, and offers guidance for future software engineering research and practice. Each contributed chapter considers the practical application of the topic through case studies, experiments, empirical validation, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited to, how to architect a system for adaptability, software architecture for self-adaptive systems, understanding and balancing the trade-offs involved, architectural patterns for self-adaptive systems, how quality attributes are exhibited by the architecture of the system, how to connect the quality of a software architecture to system architecture or other system considerations, and more.

    • Machine Learning and Medical Imaging

      • 1st Edition
      • August 9, 2016
      • Guorong Wu + 2 more
      • English
      • Hardback
        9 7 8 0 1 2 8 0 4 0 7 6 8
      • eBook
        9 7 8 0 1 2 8 0 4 1 1 4 7
      Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/codin... and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.

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