Concise Guide To Computing Foundations: Core Concepts And Select Scientific Applications by Kevin BrewerConcise Guide To Computing Foundations: Core Concepts And Select Scientific Applications by Kevin Brewer

Concise Guide To Computing Foundations: Core Concepts And Select Scientific Applications

byKevin Brewer, Cathy Bareiss

Paperback | June 16, 2018

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This book will help future scientists to become more intelligent users of computing technology in their practice of science. The content is suitable for introductory courses on the foundations of computing and the specific application of computers in different areas of science. The text presents a set of modules for use in existing science courses in order to integrate individual aspects of computational thinking, as well as a set of modules introducing the computer science concepts needed to understand the computing involved. These modules guide science students in their independent learning. The book covers computing applications in such diverse areas as bioinformatics, chemical kinetics, hydrogeological modeling, and mechanics of materials, geographic information systems, flow analysis, the solving of equations, curve fitting, optimization, and scientific data acquisition. The computing topics covered include simulations, errors, data representation, algorithms, XMS, compression, databases, performance, and complexity.

Dr. Kevin Brewer  is Co-Chair and Professor in the Department of Engineering in the Walker School of Engineering at Olivet Nazarene University, Bourbonnais, IL, USA.Dr. Cathy Bareiss  is a Professor of Computer Science at the same institution.
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Title:Concise Guide To Computing Foundations: Core Concepts And Select Scientific ApplicationsFormat:PaperbackDimensions:191 pagesPublished:June 16, 2018Publisher:Springer NatureLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3319806947

ISBN - 13:9783319806945

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Table of Contents

Introduction to Computational Science

Types of Visualization and Modeling

Data Types: Representation, Abstraction, Limitations

Scientific Data Acquisition

Procedures: Algorithms and Abstraction

Solving Equations

Iterative Solutions

Solving Sets of Equations

Procedures: Performance and Complexity

Self-Defining Data: Compression, XML and Databases

Searching

Curve Fitting

Optimization

Data Organization and Analysis

Appendix A: NetLogo

Appendix B: LabQuest

Appendix C: GIS