A Concise Introduction to Scientific Visualization
A Concise Introduction to Scientific Visualization

Author: Brad Eric Hollister

Publisher: Springer Nature

Published: 2022-01-01

Total Pages: 112

ISBN-13: 3030864197

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Scientific visualization has always been an integral part of discovery, starting first with simplified drawings of the pre-Enlightenment and progressing to present day. Mathematical formalism often supersedes visual methods, but their use is at the core of the mental process. As historical examples, a spatial description of flow led to electromagnetic theory, and without visualization of crystals, structural chemistry would not exist. With the advent of computer graphics technology, visualization has become a driving force in modern computing. A Concise Introduction to Scientific Visualization – Past, Present, and Future serves as a primer to visualization without assuming prior knowledge. It discusses both the history of visualization in scientific endeavour, and how scientific visualization is currently shaping the progress of science as a multi-disciplinary domain.

3D Scientific Visualization with Blender
3D Scientific Visualization with Blender

Author: Brian R. Kent

Publisher: Morgan & Claypool Publishers

Published: 2014-04-01

Total Pages: 125

ISBN-13: 1627056130

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This is the first book written on using Blender (an open-source visualization suite widely used in the entertainment and gaming industries) for scientific visualization. It is a practical and interesting introduction to Blender for understanding key parts of 3D rendering that pertain to the sciences via step-by-step guided tutorials. Any time you see an awesome science animation in the news, you will now know how to develop exciting visualizations and animations with your own data. 3D Scientific Visualization with Blender takes you through an understanding of 3D graphics and modeling for different visualization scenarios in the physical sciences. This includes guides and tutorials for: understanding and manipulating the interface; generating 3D models; understanding lighting, animation, and camera control; and scripting data import with the Python API. The agility of Blender and its well organized Python API make it an exciting and unique visualization suite every modern scientific/engineering workbench should include. Blender provides multiple scientific visualizations including: solid models/surfaces/rigid body simulations; data cubes/transparent/translucent rendering; 3D catalogs; N-body simulations; soft body simulations; surface/terrain maps; and phenomenological models. The possibilities for generating visualizations are considerable via this ever growing software package replete with a vast community of users providing support and ideas.

Visualize This
Visualize This

Author: Nathan Yau

Publisher: John Wiley & Sons

Published: 2011-06-13

Total Pages: 431

ISBN-13: 1118140265

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Practical data design tips from a data visualization expert of the modern age Data doesn't decrease; it is ever-increasing and can be overwhelming to organize in a way that makes sense to its intended audience. Wouldn't it be wonderful if we could actually visualize data in such a way that we could maximize its potential and tell a story in a clear, concise manner? Thanks to the creative genius of Nathan Yau, we can. With this full-color book, data visualization guru and author Nathan Yau uses step-by-step tutorials to show you how to visualize and tell stories with data. He explains how to gather, parse, and format data and then design high quality graphics that help you explore and present patterns, outliers, and relationships. Presents a unique approach to visualizing and telling stories with data, from a data visualization expert and the creator of flowingdata.com, Nathan Yau Offers step-by-step tutorials and practical design tips for creating statistical graphics, geographical maps, and information design to find meaning in the numbers Details tools that can be used to visualize data-native graphics for the Web, such as ActionScript, Flash libraries, PHP, and JavaScript and tools to design graphics for print, such as R and Illustrator Contains numerous examples and descriptions of patterns and outliers and explains how to show them Visualize This demonstrates how to explain data visually so that you can present your information in a way that is easy to understand and appealing.

Encyclopedia of Data Science and Machine Learning
Encyclopedia of Data Science and Machine Learning

Author: Wang, John

Publisher: IGI Global

Published: 2023-01-20

Total Pages: 3296

ISBN-13: 1799892212

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Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.

Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting
Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting

Author: Simone Balocco

Publisher: Academic Press

Published: 2016-12-12

Total Pages: 480

ISBN-13: 0128110198

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Computing and Visualization for Intravascular Imaging and Computer-Assisted Stenting presents imaging, treatment, and computed assisted technological techniques for diagnostic and intraoperative vascular imaging and stenting. These techniques offer increasingly useful information on vascular anatomy and function, and are poised to have a dramatic impact on the diagnosis, analysis, modeling, and treatment of vascular diseases. After setting out the technical and clinical challenges of vascular imaging and stenting, the book gives a concise overview of the basics before presenting state-of-the-art methods for solving these challenges. Readers will learn about the main challenges in endovascular procedures, along with new applications of intravascular imaging and the latest advances in computer assisted stenting. - Brings together scientific researchers, medical experts, and industry partners working in different anatomical regions - Presents an introduction to the clinical workflow and current challenges in endovascular Interventions - Provides a review of the state-of-the-art methodologies in endovascular imaging and their applications - Poses outstanding questions and discusses future research

Introduction to Information Visualization
Introduction to Information Visualization

Author: Riccardo Mazza

Publisher: Springer Science & Business Media

Published: 2009-02-28

Total Pages: 149

ISBN-13: 184800219X

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Information Visualization is a relatively young field that is acquiring more and more concensus in both academic and industrial environments. 'Information Visualization' explores the use of computer-supported interactive graphical representations to explain data and amplify cognition. It provides a means to comunicate ideas or facts about the data, to validate hypotheses, and facilitates the discovery of new facts via exploration. This book introduces the concepts and methods of Information Visualization in an easy-to-understand way, illustrating how to pictorially represent structured and unstructured data, making it easier to comprehend and interpret. Riccardo Mazza focuses on the human aspects of the process of visualization rather than the algorithmic or graphic design aspects.

Graphics and Visualization
Graphics and Visualization

Author: T. Theoharis

Publisher: CRC Press

Published: 2008-05-30

Total Pages: 786

ISBN-13: 1568812744

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This book is a comprehensive introduction to visual computing, dealing with the modeling and synthesis of visual data by means of computers. What sets this book apart from other computer graphics texts is the integrated coverage of computer graphics and visualization topics, including important techniques such as subdivision and multi-resolution modeling, scene graphs, shadow generation, ambient occlusion, and scalar and vector data visualization. Students and practitioners will benefit from the comprehensive coverage of the principles that are the basic tools of their trade, from fundamental computer graphics and classic visualization techniques to advanced topics.

A Concise Guide to Communication in Science and Engineering
A Concise Guide to Communication in Science and Engineering

Author: David H. Foster

Publisher: Oxford University Press

Published: 2017-10-27

Total Pages: 400

ISBN-13: 0191009385

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Success in scientific and engineering research depends on effective writing and presentation. The purpose of this guide is to help the reader achieve that goal. It enables students and researchers to write and present material to a professional modern standard, efficiently and painlessly, and with maximum impact. The approach is not prescriptive. Rather, the emphasis is on a logical approach to communication, informed by what needs to be achieved, what works in practice, and what interferes with success. Over 400 examples of good and bad writing and graphing are presented. Each is from a published research article and is accompanied by analysis, comment, and correction where needed. Journal reviewers' critiques of submitted manuscripts are included to illustrate common pitfalls. Above all, this is a "how-to" book, comprehensive but concise, suitable for continuous study or quick reference. Checklists at the end of each chapter enable the reader to test the readiness of a dissertation, journal submission, or conference presentation for assessment or review. Although oriented towards engineering and the physical and life sciences, it is also relevant to other areas, including behavioural and clinical sciences and medicine.

Interactive Data Visualization for the Web
Interactive Data Visualization for the Web

Author: Scott Murray

Publisher: "O'Reilly Media, Inc."

Published: 2013-03-15

Total Pages: 269

ISBN-13: 1449339735

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Create and publish your own interactive data visualization projects on the Web, even if you have no experience with either web development or data visualization. It’s easy with this hands-on guide. You’ll start with an overview of data visualization concepts and simple web technologies, and then learn how to use D3, a JavaScript library that lets you express data as visual elements in a web page. Interactive Data Visualization for the Web makes these skills available at an introductory level for designers and visual artists without programming experience, journalists interested in the emerging data journalism processes, and others keenly interested in visualization and publicly available data sources. Get a practical introduction to data visualization, accessible for beginners Focus on web-based tools that help you publish your creations quickly to a wide audience Learn about interactivity so you can engage users in exploring your data

Statistics
Statistics

Author: David W. Scott

Publisher: John Wiley & Sons

Published: 2020-07-13

Total Pages: 180

ISBN-13: 1119675847

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Statistic: A Concise Mathematical Introduction for Students and Scientists offers a one academic term text that prepares the student to broaden their skills in statistics, probability and inference, prior to selecting their follow-on courses in their chosen fields, whether it be engineering, computer science, programming, data sciences, business or economics. The book places focus early on continuous measurements, as well as discrete random variables. By invoking simple and intuitive models and geometric probability, discrete and continuous experiments and probabilities are discussed throughout the book in a natural way. Classical probability, random variables, and inference are discussed, as well as material on understanding data and topics of special interest. Topics discussed include: • Classical equally likely outcomes • Variety of models of discrete and continuous probability laws • Likelihood function and ratio • Inference • Bayesian statistics With the growth in the volume of data generated in many disciplines that is enabling the growth in data science, companies now demand statistically literate scientists and this textbook is the answer, suited for undergraduates studying science or engineering, be it computer science, economics, life sciences, environmental, business, amongst many others. Basic knowledge of bivariate calculus, R language, Matematica and JMP is useful, however there is an accompanying website including sample R and Mathematica code to help instructors and students.