Computational Technologies
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Computational Technologies in Materials Science
Advanced materials are essential for economic security and human well-being, with applications in industries aimed at addressing challenges in clean energy, national security, and human welfare. Yet, it can take years to move a material to the market after its initial discovery. Computational techniques have accelerated the exploration and development of materials, offering the chance to move new materials to the market quickly. Computational Technologies in Materials Science addresses topics related to AI, machine learning, deep learning, and cloud computing in materials science. It explores characterization and fabrication of materials, machine-learning-based models, and computational intelligence for the synthesis and identification of materials. This book • Covers material testing and development using computational intelligence • Highlights the technologies to integrate computational intelligence and materials science • Details case studies and detailed applications • Investigates challenges in developing and using computational intelligence in materials science • Analyzes historic changes that are taking place in designing materials. This book encourages material researchers and academics to develop novel theories and sustainable computational techniques and explores the potential for computational intelligence to replace traditional materials research.
Computational Technologies
Author: Petr N. Vabishchevich
language: en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date: 2014-12-11
This book discusses questions of numerical solutions of applied problems on parallel computing systems. Nowadays, engineering and scientific computations are carried out on parallel computing systems, which provide parallel data processing on a few computing nodes. In the development of up-to-date applied software, this feature of computers must be taken into account for the maximum efficient usage of their resources. In constructing computational algorithms, we should separate relatively independent subproblems in order to solve them on a single computing node.
Collaborative Computational Technologies for Biomedical Research
Methods, Processes, and Tools for Collaboration "The time has come to fundamentally rethink how we handle the building of knowledge in biomedical sciences today. This book describes how the computational sciences have transformed into being a key knowledge broker, able to integrate and operate across divergent data types." Bryn Williams-Jones, Associate Research Fellow, Pfizer The pharmaceutical industry utilizes an extended network of partner organizations in order to discover and develop new drugs, however there is currently little guidance for managing information and resources across collaborations. Featuring contributions from the leading experts in a range of industries, Collaborative Computational Technologies for Biomedical Research provides information that will help organizations make critical decisions about managing partnerships, including: Serving as a user manual for collaborations Tackling real problems from both human collaborative and data and informatics perspectives Providing case histories of biomedical collaborations and technology-specific chapters that balance technological depth with accessibility for the non-specialist reader A must-read for anyone working in the pharmaceuticals industry or academia, this book marks a major step towards widespread collaboration facilitated by computational technologies.