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This book is aimed to help instructional designers, science game designers, science faculty, lab designers, and content developers in designing interactive learning experiences using emerging technologies and cyberlearning. The proposed solutions are for undergraduate and graduate scientific communication, engineering courses, scientific research communication, and workforce training. Reviewing across the science education literature reveals various aspects of unresolved challenges or inabilities in the visualization of scientific concepts. Visuospatial thinking is the fundamental part of learning sciences; however, promoting spatial thinking has not been emphasized enough in the educational system (Hegarty, 2014). Cognitive scientists distinguish between the multiple aspects of spatial ability and stresse that various problems or disciplines require different types of spatial skills. For example, the spatial ability to visualize anatomy cross-sections is significantly associated with mental rotation skills. The same is true for physical problems that often deal with spatial representations. However, most of the physics problems are marked by dynamicity, and visualizing dynamicity is inferred by the integrations of different participating components in the system. Therefore, what is needed for learning dynamicity is visualizing the mental animation of static episodes. This book is a leap into designing framework for using mixed reality (XR) technologies and cyberlearning in communicating advanced scientific concepts. The intention is to flesh out the cognitive infrastructure and visuospatial demands of complex systems and compare them in various contexts and disciplines. The practical implementation of emerging technology can be achieved by foreseeing each XR technology’s affordances and mapping those out to the cognitive infrastructure and visuospatial demands of the content under development.
Dynamic Patterns explores the role of patterns in designed landscapes. Patterns are inherently relational, and the search for and the creation of patterns are endemic to many scientific and artistic endeavors. Recent advances in optical tools, sensors, and computing have expanded our understanding of patterns as a link between natural and cultural realms. Looking beyond the surface manifestation of pattern, M’Closkey and VanDerSys delve into a multifaceted examination that explores new avenues for engagement with patterns using digital media. Examining the theoretical implications of pattern-making, they probe the potential of patterns to conjoin landscape’s utilitarian and aesthetic functions. With full color throughout and over one hundred and twenty images, Dynamic Patterns utilizes work from a wide range of artists and designers to demonstrate how novel modes of visualization have facilitated new ways of seeing patterns and therefore of understanding and designing landscapes.
Here is an ideal textbook on software visualization, written especially for students and teachers in computer science. It provides a broad and systematic overview of the area including many pointers to tools available today. Topics covered include static program visualization, algorithm animation, visual debugging, as well as the visualization of the evolution of software. The author's presentation emphasizes common principles and provides different examples mostly taken from seminal work. In addition, each chapter is followed by a list of exercises including both pen-and-paper exercises as well as programming tasks.
This book is aimed to help instructional designers, science game designers, science faculty, lab designers, and content developers in designing interactive learning experiences using emerging technologies and cyberlearning. The proposed solutions are for undergraduate and graduate scientific communication, engineering courses, scientific research communication, and workforce training. Reviewing across the science education literature reveals various aspects of unresolved challenges or inabilities in the visualization of scientific concepts. Visuospatial thinking is the fundamental part of learning sciences; however, promoting spatial thinking has not been emphasized enough in the educational system (Hegarty, 2014). Cognitive scientists distinguish between the multiple aspects of spatial ability and stresse that various problems or disciplines require different types of spatial skills. For example, the spatial ability to visualize anatomy cross-sections is significantly associated with mental rotation skills. The same is true for physical problems that often deal with spatial representations. However, most of the physics problems are marked by dynamicity, and visualizing dynamicity is inferred by the integrations of different participating components in the system. Therefore, what is needed for learning dynamicity is visualizing the mental animation of static episodes. This book is a leap into designing framework for using mixed reality (XR) technologies and cyberlearning in communicating advanced scientific concepts. The intention is to flesh out the cognitive infrastructure and visuospatial demands of complex systems and compare them in various contexts and disciplines. The practical implementation of emerging technology can be achieved by foreseeing each XR technology's affordances and mapping those out to the cognitive infrastructure and visuospatial demands of the content under development.
The 6th International Conference on the Theory and Application of Diagrams – Diagrams 2010 – was held in Portland, USA in August 2010. Diagrams is an international and interdisciplinary conference series, which continues to present the very best work in all aspects of research on the theory and application of diagrams. Some key questions that researchers are tackling concern gaining an insight into how diagrams are used, how they are rep- sented, which types are available and when it is appropriate to use them. The use of diagrammatic notations is studied for a variety of purposes including communication, cognition, creative thought, computation and problem-solving. Clearly, this must be pursued as an interdisciplinary endeavor, and Diagrams is the only conference series that provides such a united forum for all areas that are concerned with the study of diagrams: for example, architecture, arti?cial intelligence,cartography,cognitivescience,computer science,education,graphic design, history of science, human–computer interaction, linguistics, logic, ma- ematics, philosophy, psychology, and software modelling. The articles in this volume re?ect this variety and interdisciplinarity of the ?eld.
Discrete Networked Dynamic Systems: Analysis and Performance provides a high-level treatment of a general class of linear discrete-time dynamic systems interconnected over an information network, exchanging relative state measurements or output measurements. It presents a systematic analysis of the material and provides an account to the math development in a unified way. The topics in this book are structured along four dimensions: Agent, Environment, Interaction, and Organization, while keeping global (system-centered) and local (agent-centered) viewpoints. The focus is on the wide-sense consensus problem in discrete networked dynamic systems. The authors rely heavily on algebraic graph theory and topology to derive their results. It is known that graphs play an important role in the analysis of interactions between multiagent/distributed systems. Graph-theoretic analysis provides insight into how topological interactions play a role in achieving coordination among agents. Numerous types of graphs exist in the literature, depending on the edge set of G. A simple graph has no self-loop or edges. Complete graphs are simple graphs with an edge connecting any pair of vertices. The vertex set in a bipartite graph can be partitioned into disjoint non-empty vertex sets, whereby there is an edge connecting every vertex in one set to every vertex in the other set. Random graphs have fixed vertex sets, but the edge set exhibits stochastic behavior modeled by probability functions. Much of the studies in coordination control are based on deterministic/fixed graphs, switching graphs, and random graphs. - This book addresses advanced analytical tools for characterization control, estimation and design of networked dynamic systems over fixed, probabilistic and time-varying graphs - Provides coherent results on adopting a set-theoretic framework for critically examining problems of the analysis, performance and design of discrete distributed systems over graphs - Deals with both homogeneous and heterogeneous systems to guarantee the generality of design results
Summary Visualizing Graph Data teaches you not only how to build graph data structures, but also how to create your own dynamic and interactive visualizations using a variety of tools. This book is loaded with fascinating examples and case studies to show you the real-world value of graph visualizations. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Assume you are doing a great job collecting data about your customers and products. Are you able to turn your rich data into important insight? Complex relationships in large data sets can be difficult to recognize. Visualizing these connections as graphs makes it possible to see the patterns, so you can find meaning in an otherwise over-whelming sea of facts. About the Book Visualizing Graph Data teaches you how to understand graph data, build graph data structures, and create meaningful visualizations. This engaging book gently introduces graph data visualization through fascinating examples and compelling case studies. You'll discover simple, but effective, techniques to model your data, handle big data, and depict temporal and spatial data. By the end, you'll have a conceptual foundation as well as the practical skills to explore your own data with confidence. What's Inside Techniques for creating effective visualizations Examples using the Gephi and KeyLines visualization packages Real-world case studies About the Reader No prior experience with graph data is required. About the Author Corey Lanum has decades of experience building visualization and analysis applications for companies and government agencies around the globe. Table of Contents PART 1 - GRAPH VISUALIZATION BASICS Getting to know graph visualization Case studies An introduction to Gephi and KeyLines PART 2 VISUALIZE YOUR OWN DATA Data modeling How to build graph visualizations Creating interactive visualizations How to organize a chart Big data: using graphs when there's too much data Dynamic graphs: how to show data over time Graphs on maps: the where of graph visualization
This book constitutes the thoroughly refereed post-proceedings of the 9th International Conference on Visual Information Systems, VISUAL 2007, held in Shanghai, China, in June 2007. The papers are organized in topical section on image and video retrieval, visual biometrics, intelligent visual information processing, visual data mining, ubiquitous and mobile visual information systems, semantics, 2D/3D graphical visual data retrieval, and applications of visual information systems.
This open access book addresses the way in which urban and urbanizing regions profoundly impact and are impacted by climate change. The editors and authors show why cities must wage simultaneous battles to curb global climate change trends while adapting and transforming to address local climate impacts. This book addresses how cities develop anticipatory and long-range planning capacities for more resilient futures, earnest collaboration across disciplines, and radical reconfigurations of the power regimes that have institutionalized the disenfranchisement of minority groups. Although planning processes consider visions for the future, the editors highlight a more ambitious long-term positive visioning approach that accounts for unpredictability, system dynamics and equity in decision-making. This volume brings the science of urban transformation together with practices of professionals who govern and manage our social, ecological and technological systems to design processes by which cities may achieve resilient urban futures in the face of climate change.