Field analysis: experimental and computational methods.
Read Online
Share

Field analysis: experimental and computational methods.

  • 807 Want to read
  • ·
  • 37 Currently reading

Published by Van Nostrand in London, New York [etc.] .
Written in English

Subjects:

  • Engineering mathematics.,
  • Electromechanical analogies.

Book details:

Edition Notes

Includes bibliographies.

Classifications
LC ClassificationsTA343 .V5
The Physical Object
Paginationxv, 503 p.
Number of Pages503
ID Numbers
Open LibraryOL5983653M
LC Control Number66013032

Download Field analysis: experimental and computational methods.

PDF EPUB FB2 MOBI RTF

This book gathers the latest advances, innovations, and applications in the field of computational engineering, as presented by leading international researchers and engineers at the 24th International Conference on Computational & Experimental Engineering and Sciences (ICCES), held in Tokyo, Japan on March , In Protein Dynamics: Methods and Protocols, expert researchers in the field detail both experimental and computational methods to interrogate molecular level fluctuations. Chapters detail best-practice recipes covering both experimental and computational . This book contains edited versions of most of the papers presented at the Tenth International Conference on Computational Methods and Experimental Measurements (CMEM), a highly successful series providing a unique forum for the review of the latest work in this field. This book provides a comprehensive guide to scientists, engineers, and students that employ metabolomics in their work, with an emphasis on the understanding and interpretation of the data. Chapters guide readers through common tools for data processing, using database resources, major techniques in data analysis, and integration with other data types and .

Provides rigorous mathematical treatment of practical statistical methods for data analysis. Serves as a graduate textbook and reference guide for those interested in the fundamentals of data analysis. Useful for all fields of science and engineering requiring an understanding of statistical methods applied to experimental : Springer International Publishing. This text is a reference for biomedical professionals interested in expanding their knowledge of computational techniques for NGS data analysis. The book is also useful for graduate and post-graduate students in bioinformatics. Flow field analysis of the four models Velocity distributions were obtained by simulating the flow field in the cyclone separator. In the cyclone separator, the three-dimensional, strong, swirling turbulence is complicated, and the flow field in the separator is non-axially : Li Qiang, Wang Qinggong, Xu Weiwei, Zhu Zilin, Zhu Konghao. The definitive introduction to data analysis in quantitative proteomics. This book provides all the necessary knowledge about mass spectrometry based proteomics methods and computational and statistical approaches to pursue the planning, design and analysis of .

Book Description. Featuring contributions from leading researchers in the field, this book uniquely discusses both the contemporary experimental and computational manifestations of soft condensed matter physics. It will equip graduate students and experienced researchers for collaborative and interdisciplinary research efforts relating to a range Format: Hardcover. This book contains most of the papers presented at the 13th International Conference on Computational Methods and Experimental Measurements (CMEM/07) held in Prague in This series of conferences started in Washington DC at the beginning of the s and has been reconvened every two years with continuous success. In truth, a better title for the course is Experimental Design and Analysis, and that is the title of this book. Experimental Design and Statistical Analysis go hand in hand, and neither can be understood without the other. Only a small fraction of the myriad statistical analytic methods are covered in this book, but my rough guess is that. Computational Physics With Python. This book covers the following topics: Useful Introductory Python, Python Basics, Basic Numerical Tools, Numpy, Scipy, and MatPlotLib, Ordinary Differential Equations, Chaos, Monte Carlo Techniques, Stochastic Methods and Partial Differential Equations.