Concise Guide to Computing Foundations

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.

Provides self-guided modules that allow students to learn independently Explains the computer science fundamentals used by science software Presents content that can be integrated into a range of different introductory courses in science Includes supplementary material: sn.pub/extras Request lecturer material: sn.pub/lecturer-material

Autorentext

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.

Klappentext

This unique textbook pioneers a new approach to educating the general student about computing to practically address the needs of today's society. This approach provides an accessible introduction to the key concepts in computer science and how these are applied to support other areas of science, highlighting the important interconnections between the different disciplines.

Topics and features:

• Provides a strong interdisciplinary introduction to computational science
• Discusses such issues as the use of computer simulations, the limits of precision in a computer, and the amount of work performed by software to complete a task
• Covers the cross-disciplinary application of data representation, algorithms, self-defining data, and performance complexity
• Examines the close links between computer science and such scientific and engineering fields as bioinformatics, chemical kinetics, hydrogeological modeling, and mechanics of materials
• Describes the contributions of computer science to engineering analysis, GIS, flow analysis, solving equations, curve fitting, optimization, and data acquisition
• Contains review questions, exercises, and discussion prompts throughout the text, together with chapter objectives and an appendix on using LabQuestThis classroom-tested and activity-based textbook has been developed for teaching second-semester freshmen and sophomore non-computer science STEM majors, structured around a discovery learning approach. The work is also ideal for self-teaching.

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.

Inhalt
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.