A Concise Introduction To Scientific Visualization
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A Concise Introduction to Scientific Visualization
Author: Brad Eric Hollister
language: en
Publisher: Springer Nature
Release Date: 2022-01-01
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
Author: Brian R. Kent
language: en
Publisher: Morgan & Claypool Publishers
Release Date: 2014-04-01
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.
Encyclopedia of Data Science and Machine Learning
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.