Tag: Mathematical

Viscoelasticity Mathematical Modeling, Numerical Simulations, and Experimental Work


Free Download Viscoelasticity: Mathematical Modeling, Numerical Simulations, and Experimental Work by Luís L. Ferrás and Alexandre M. Afonso
English | PDF | 2024 | 238 Pages | ISBN : 3036597506 | 24.6 MB
This Special Issue brings together the latest advancements across various facets of viscous and viscoelastic fluid flows. Encompassing a spectrum of contributions, the topics span from innovative numerical methods and sophisticated mathematical modeling to cutting-edge experimental research. In addition to providing insights into the current state of research in these domains, the issue aims to foster a comprehensive understanding of the intricate dynamics and behaviors exhibited by viscous and viscoelastic fluids.

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Mathematical Methods for Molecular Science Theory and Applications, Visualizations and Narrative


Free Download John E Straub, "Mathematical Methods for Molecular Science: Theory and Applications, Visualizations and Narrative"
English | ISBN: 1940380138 | 2022 | 542 pages | PDF | 110 MB
Straub’s stunning new text is an excellent choice for a one-semester course on mathematical methods, an affordable supplement for physical chemistry courses, or a self-study guide.

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Progress in Mathematics Probability Theory, Mathematical Statistics, and Theoretical Cybernetics


Free Download Progress in Mathematics: Probability Theory, Mathematical Statistics, and Theoretical Cybernetics by R. V. Gamkrelidze
English | PDF | 1971 | 131 Pages | ISBN : 1468433113 | 11.5 MB
This volume contains two review articles: "Stochastic Pro gramming" by Vo V. Kolbin, and "Application of Queueing-Theoretic Methods in Operations Research, " by N. Po Buslenko and A. P. Cherenkovo The first article covers almost all aspects of stochastic programming. Many of the results presented in it have not pre viously been surveyed in the Soviet literature and are of interest to both mathematicians and economists. The second article com prises an exhaustive treatise on the present state of the art of the statistical methods of queueing theory and the statistical modeling of queueing systems as applied to the analysis of complex systems. Contents STOCHASTIC PROGRAMMING V. V. Kolbin Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 § 1. The Geometry of Stochastic Linear Programming Problems. . . . . . . . . . . . . . . . . . . . 5 § 2. Chance-Constrained Problems . . . . . . . . . 8 § 3. Rigorous Statement of stochastic Linear Programming Problems . . . . . . . . . . 16 § 4. Game-Theoretic Statement of Stochastic Linear Programming Problems. . . . . . . . 18 § 5. Nonrigorous Statement of SLP Problems . . . 19 § 6. Existence of Domains of Stability of the Solutions of SLP Problems . . . . . . . . . 29 § 7. Stability of a Solution in the Mean. . . . . . . . . . . . 30 § 8. Dual Stochastic Linear Programming Problems. . . 37 § 9. Some Algorithms for the Solution of Stochastic Linear Programming Problems . . . . . . . . . . 40 § 10. Stochastic Nonlinear Programming: Some First Results . . . . . . . . . . . . . . . . . . . . . . 42 § 11. The Two-Stage SNLP Problem. . . . . . . . . . . . 47 § 12. Optimality and Existence of a Plan in Stochastic Nonlinear Programming Problems. 58 Literature Cited . . . . . . . . . . . . . . . . . . . . . . . . . .

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Mathematical Principles in Bioinformatics


Free Download Mathematical Principles in Bioinformatics
English | 2023 | ISBN: 3031482948 | 200 Pages | PDF EPUB (True) | 28 MB
This textbook introduces bioinformatics to students in mathematics with no biology background assumed and it provides solid mathematical tools for biology students along with an understanding of how to implement them in bioinformatics problems. In addition to the basics, the text offers new approaches to understanding biological sequences. The concise presentation distinguishes itself from others on the subject, discussing and providing principles that relate to current open problems in bioinformatics as well as considering a variety of models. The convex hull principle is highlighted, opening a new interdisciplinary research area at the intersection of biology, mathematics, and computer science. Prerequisites include first courses in linear algebra, probability and statistics, and mathematical analysis. Researchers in mathematics, biology, and math-biology, will also find aspects of this text useful.

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