In Situ Visualization for Computational Science


Book Description

This book provides an overview of the emerging field of in situ visualization, i.e. visualizing simulation data as it is generated. In situ visualization is a processing paradigm in response to recent trends in the development of high-performance computers. It has great promise in its ability to access increased temporal resolution and leverage extensive computational power. However, the paradigm also is widely viewed as limiting when it comes to exploration-oriented use cases. Furthermore, it will require visualization systems to become increasingly complex and constrained in usage. As research efforts on in situ visualization are growing, the state of the art and best practices are rapidly maturing. Specifically, this book contains chapters that reflect state-of-the-art research results and best practices in the area of in situ visualization. Our target audience are researchers and practitioners from the areas of mathematics computational science, high-performance computing, and computer science that work on or with in situ techniques, or desire to do so in future.




Geostatistical Reservoir Modeling


Book Description

A revised edition that provides a full update on the most current methods, tools, and research in petroleum geostatistics.




Visualization and Mathematics


Book Description

Visualization and mathematics have begun a fruitful relationship, establishing links between problems and solutions of both fields. In some areas of mathematics, like differential geometry and numerical mathematics, visualization techniques are applied with great success. However, visualization methods are relying heavily on mathematical concepts.Applications of visualization in mathematical research and the use of mathematical methods in visualization have been topic of an international workshop in Berlin in June 1995. Selected contributions treat topics of particular interest in current research. Experts are reporting on their latest work, giving an overview on this fascinating new area. The reader will get insight to state-of-the-art techniques for solving visualization problems and mathematical questions.




New Frontiers in Multiscale Modelling of Advanced Materials


Book Description

Atomistic simulations, based on ab-initio and semi-empirical approaches, are nowadays widespread in many areas of physics, chemistry and, more recently, biology. Improved algorithms and increased computational power widened the areas of application of these computational methods to extended materials of technological interest, in particular allowing unprecedented access to the first-principles investigation of their electronic, optical, thermodynamical and mechanical properties, even where experiments are not available. However, for a big impact on the society, this rapidly growing field of computational approaches to materials science has to face the unfavourable scaling with the system size, and to beat the time-scale bottleneck. Indeed, many phenomena, such as crystal growth or protein folding for example, occur in a space/time scale which is normally out of reach of present simulations. Multi-scale approaches try to combine different scale algorithms along with matching procedures in order to bridge the gap between first-principles and continuum-level simulations. This Research Topic aims at the description of recent advances and applications in these two emerging fields of ab-inito and multi-scale materials modelling for both ground and excited states. A variety of theoretical and computational techniques are included along with the application of these methods to systems at increasing level of complexity, from nano to micro. Crossing the borders between several computational, theoretical and experimental techniques, this Research Topic aims to be of interest to a broad community, including experimental and theoretical physicists, chemists and engineers interested in materials research in a broad sense.







Introduction to Data Science


Book Description

Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.







Advances in Visual Computing


Book Description

The two volume set LNCS 6938 and LNCS 6939 constitutes the refereed proceedings of the 7th International Symposium on Visual Computing, ISVC 2011, held in Las Vegas, NV, USA, in September 2011. The 68 revised full papers and 46 poster papers presented together with 30 papers in the special tracks were carefully reviewed and selected from more than 240 submissions. The papers of part I (LNCS 6938) are organized in computational bioimaging, computer graphics, motion and tracking, segmentation, visualization; mapping modeling and surface reconstruction, biomedical imaging, computer graphics, interactive visualization in novel and heterogeneous display environments, object detection and recognition. Part II (LNCS 6939) comprises topics such as immersive visualization, applications, object detection and recognition, virtual reality, and best practices in teaching visual computing.




International Assessment of Research and Development in Simulation-based Engineering and Science


Book Description

Simulation-Based Engineering and Science (SBE&S) cuts across disciplines, showing tremendous promise in areas from storm prediction and climate modeling to understanding the brain and the behavior of numerous other complex systems.In this groundbreaking volume, nine distinguished leaders assess the latest research trends, as a result of 52 site visits in Europe and Asia and hundreds of hours of expert interviews, and discuss the implications of their findings for the US government.The authors conclude that while the US remains the quantitative leader in SBE&S research and development, it is very much in danger of losing that edge to Europe and Asia.Commissioned by the National Science Foundation, this multifaceted study will capture the attention of Fortune 500 companies and policymakers.Distinguished contributors: Sharon C Goltzer, University of Michigan, Ann Arbor, USA Sangtae Kim, Morgridge Institute for Research, USA Peter T Cummings, Vanderbilt University, USA and Oak Ridge National Laboratory, USA Abhijit Deshmukh, Texas A&M University, USA Martin Head-Gordon, University of California, Berkeley, USA George Em Karniadakis, Brown University, USA Linda Petzold, University of California, Santa Barbara, USA Celeste Sagui, North Carolina State University, USA Masanobu Shinozuka, University of California, Irvine, USA




Computational Science - ICCS 2007


Book Description

Annotation The four-volume set LNCS 4487-4490 constitutes the refereed proceedings of the 7th International Conference on Computational Science, ICCS 2007, held in Beijing, China in May 2007. More than 2400 submissions were made to the main conference and its 35 topical workshops. The 80 revised full papers and 11 revised short papers of the main track were carefully reviewed and selected from 360 submissions and are presented together with 624 accepted workshop papers in four volumes. According to the ICCS 2007 theme "Advancing Science and Society through Computation" the papers cover a large volume of topics in computational science and related areas, from multiscale physics, to wireless networks, and from graph theory to tools for program development. The papers are arranged in topical sections on efficient data management, parallel monte carlo algorithms, simulation of multiphysics multiscale systems, dynamic data driven application systems, computer graphics and geometric modeling, computer algebra systems, computational chemistry, computational approaches and techniques in bioinformatics, computational finance and business intelligence, geocomputation, high-level parallel programming, networks theory and applications, collective intelligence for semantic and knowledge grid, collaborative and cooperative environments, tools for program development and analysis in CS, intelligent agents in computing systems, CS in software engineering, computational linguistics in HCI, internet computing in science and engineering, workflow systems in e-science, graph theoretic algorithms and applications in cs, teaching CS, high performance data mining, mining text, semi-structured, Web, or multimedia data, computational methods in energy economics, risk analysis, advances in computational geomechanics and geophysics, meta-synthesis and complex systems, scientific computing in electronics engineering, wireless and mobile systems, high performance networked media and services, evolution toward next generation internet, real time systems and adaptive applications, evolutionary algorithms and evolvable systems.