This book constitutes the refereed post-proceedings of the 10th IFIP WG 2.5 Working Conference on Uncertainty Quantification in Scientific Computing, WoCoUQ 2011, held in Boulder, CO, USA, in August 2011. The 24 revised papers were carefully reviewed and selected from numerous submissions. They are organized in the following topical sections: UQ need: risk, policy, and decision making, UQ theory, UQ tools, UQ practice, and hot topics. The papers are followed by the records of the discussions between the participants and the speaker.
Effective visualization is the best way to communicate information from the increasingly large and complex datasets in the natural and social sciences. But with the increasing power of visualization software today, scientists, engineers, and business analysts often have to navigate a bewildering array of visualization choices and options. This practical book takes you through many commonly encountered visualization problems, and it provides guidelines on how to turn large datasets into clear and compelling figures. What visualization type is best for the story you want to tell? How do you make informative figures that are visually pleasing? Author Claus O. Wilke teaches you the elements most critical to successful data visualization. Explore the basic concepts of color as a tool to highlight, distinguish, or represent a value Understand the importance of redundant coding to ensure you provide key information in multiple ways Use the book’s visualizations directory, a graphical guide to commonly used types of data visualizations Get extensive examples of good and bad figures Learn how to use figures in a document or report and how employ them effectively to tell a compelling story
This book captures the state of the art in visual research. Margolis and Pauwels have brought together, in one volume, a unique survey of the field of visual research that will be essential reading for scholars and students across the social sciences, arts and humanities. The SAGE Handbook of Visual Research Methods encompasses the breadth and depth of the field, and points the way to future research possibilities. It illustrates ′cutting edge′ as well as long-standing and recognized practices. This book is not only ′about′ research, it is also an example of the way that the visual can be incorporated into data collection and the presentation of research findings. Chapters describe a methodology or analytical framework, its strengths and limitations, possible fields of application and practical guidelines on how to apply the method or technique. The Handbook is organized into seven main sections: - Framing the Field of Visual Research - Producing Visual Data and Insight - Participatory and Subject-Centered Approaches - Analytical Frameworks and Approaches - Visualization Technologies and Practices - Moving Beyond the Visual - Options and Issues for Using and Presenting Visual Research. Eric Margolis is an Associate Professor in the Hugh Downs School of Human Communication. He is President of the International Visual Sociology Association. Luc Pauwels is Professor of Visual Culture at the University of Antwerp. He is Chair of the Visual Communication Studies Division of the ICA and Vice-President of the International Visual Sociology Association (IVSA).
This book presents the latest advances in modeling and simulation for human factors research. It reports on cutting-edge simulators such as virtual and augmented reality, multisensory environments, and modeling and simulation methods used in various applications, including surgery, military operations, occupational safety, sports training, education, transportation and robotics. Based on two AHFE 2020 Virtual Conferences such as the AHFE 2020 Virtual Conference on Human Factors and Simulation and the AHFE 2020 Virtual Conference on Digital Human Modeling and Applied Optimization, held on July 16–20, 2020, the book serves as a timely reference guide for researchers and practitioners developing new modeling and simulation tools for analyzing or improving human performance. It also offers a unique resource for modelers seeking insights into human factors research and more feasible and reliable computational tools to foster advances in this exciting field.
The second, thoroughly revised and expanded, edition of The SAGE Handbook of Visual Research Methods presents a wide-ranging exploration and overview of the field today. As in its first edition, the Handbook does not aim to present a consistent view or voice, but rather to exemplify diversity and contradictions in perspectives and techniques. The selection of chapters from the first edition have been fully updated to reflect current developments. New chapters to the second edition cover key topics including picture-sorting techniques, creative methods using artefacts, visual framing analysis, therapeutic uses of images, and various emerging digital technologies and online practices. At the core of all contributions are theoretical and methodological debates about the meanings and study of the visual, presented in vibrant accounts of research design, analytical techniques, fieldwork encounters and data presentation. This handbook presents a unique survey of the discipline that will be essential reading for scholars and students across the social and behavioural sciences, arts and humanities, and far beyond these disciplinary boundaries. The Handbook is organized into seven main sections: PART 1: FRAMING THE FIELD OF VISUAL RESEARCH PART 2: VISUAL AND SPATIAL DATA PRODUCTION METHODS AND TECHNOLOGIES PART 3: PARTICIPATORY AND SUBJECT-CENTERED APPROACHES PART 4: ANALYTICAL FRAMEWORKS AND PERSPECTIVES PART 5: MULTIMODAL AND MULTISENSORIAL RESEARCH PART 6: RESEARCHING ONLINE PRACTICES PART 7: COMMUNICATING THE VISUAL: FORMATS AND CONCERNS
The rising reliance on testing in American education and for licensure and certification has been accompanied by an escalation in cheating on tests at all levels. Edited by two of the foremost experts on the subject, the Handbook of Quantitative Methods for Detecting Cheating on Tests offers a comprehensive compendium of increasingly sophisticated data forensics used to investigate whether or not cheating has occurred. Written for practitioners, testing professionals, and scholars in testing, measurement, and assessment, this volume builds on the claim that statistical evidence often requires less of an inferential leap to conclude that cheating has taken place than do other, more common sources of evidence. This handbook is organized into sections that roughly correspond to the kinds of threats to fair testing represented by different forms of cheating. In Section I, the editors outline the fundamentals and significance of cheating, and they introduce the common datasets to which chapter authors' cheating detection methods were applied. Contributors describe, in Section II, methods for identifying cheating in terms of improbable similarity in test responses, preknowledge and compromised test content, and test tampering. Chapters in Section III concentrate on policy and practical implications of using quantitative detection methods. Synthesis across methodological chapters as well as an overall summary, conclusions, and next steps for the field are the key aspects of the final section.
The contributors to Best Practices in Quantitative Methods envision quantitative methods in the 21st century, identify the best practices, and, where possible, demonstrate the superiority of their recommendations empirically. Editor Jason W. Osborne designed this book with the goal of providing readers with the most effective, evidence-based, modern quantitative methods and quantitative data analysis across the social and behavioral sciences. The text is divided into five main sections covering select best practices in Measurement, Research Design, Basics of Data Analysis, Quantitative Methods, and Advanced Quantitative Methods. Each chapter contains a current and expansive review of the literature, a case for best practices in terms of method, outcomes, inferences, etc., and broad-ranging examples along with any empirical evidence to show why certain techniques are better. Key Features: Describes important implicit knowledge to readers: The chapters in this volume explain the important details of seemingly mundane aspects of quantitative research, making them accessible to readers and demonstrating why it is important to pay attention to these details. Compares and contrasts analytic techniques: The book examines instances where there are multiple options for doing things, and make recommendations as to what is the "best" choice—or choices, as what is best often depends on the circumstances. Offers new procedures to update and explicate traditional techniques: The featured scholars present and explain new options for data analysis, discussing the advantages and disadvantages of the new procedures in depth, describing how to perform them, and demonstrating their use. Intended Audience: Representing the vanguard of research methods for the 21st century, this book is an invaluable resource for graduate students and researchers who want a comprehensive, authoritative resource for practical and sound advice from leading experts in quantitative methods.
How should we understand and visualise the uncertainty inherent in decision-making? Using the right visualisation tools can improve our decisions. But this positive impact should never be taken for granted: visualisations can also have unexpected side-effects, and there is the risk that they can be misinterpreted or otherwise misused.
Art History is centrally concerned with a vast array of three-dimensional objects, such as sculptures, and spaces, such as architecture. Digital technologies allow the creation of virtual spaces, which in turn allow us to simulate and compare aspects of a visual culture's three-dimensional timespace that cannot be communicated as a single, still image. The third issue, thus, focusses on the third dimension in Art History, and the digital realm that continues to mediate and transform it.
This open access book focuses on processing, modeling, and visualization of anisotropy information, which are often addressed by employing sophisticated mathematical constructs such as tensors and other higher-order descriptors. It also discusses adaptations of such constructs to problems encountered in seemingly dissimilar areas of medical imaging, physical sciences, and engineering. Featuring original research contributions as well as insightful reviews for scientists interested in handling anisotropy information, it covers topics such as pertinent geometric and algebraic properties of tensors and tensor fields, challenges faced in processing and visualizing different types of data, statistical techniques for data processing, and specific applications like mapping white-matter fiber tracts in the brain. The book helps readers grasp the current challenges in the field and provides information on the techniques devised to address them. Further, it facilitates the transfer of knowledge between different disciplines in order to advance the research frontiers in these areas. This multidisciplinary book presents, in part, the outcomes of the seventh in a series of Dagstuhl seminars devoted to visualization and processing of tensor fields and higher-order descriptors, which was held in Dagstuhl, Germany, on October 28-November 2, 2018.
