This book is based on the best papers accepted for presentation during the International Conference on Actual Problems of Applied Mathematics and Computer Systems (APAMCS-2022), Russia. The book includes research materials on modern mathematical problems, solutions in the field of scientific computing, data analysis and modular computing. The scope of numerical methods in scientific computing presents original research, including mathematical models and software implementations, related to the following topics: numerical methods in scientific computing; solving optimization problems; methods for approximating functions, etc. The studies in data analysis and modular computing include contributions in the field of deep learning, neural networks, mathematical statistics, machine learning methods, residue number system and artificial intelligence. Finally, the book gives insights into the fundamental problems in mathematics education. The book intends for readership specializing in the field of scientific computing, parallel computing, computer technology, machine learning, information security and mathematical education.

This volume is an excellent resource for professionals in various areas of applications of mathematics, modeling, and computational science. It focuses on recent progress and modern challenges in these areas. The volume provides a balance between fundamental theoretical and applied developments, emphasizing the interdisciplinary nature of modern trends and detailing state-of-the-art achievements in Applied Mathematics, Modeling, and Computational Science. The chapters have been authored by international experts in their respective fields, making this book ideal for researchers in academia, practitioners, and graduate students. It can also serve as a reference in the diverse selected areas of applied mathematics, modelling, and computational sciences, and is ideal for interdisciplinary collaborations.

Mark Alber, Bei Hu and Joachim Rosenthal ... ... vii Part I Some Remarks on Applied Mathematics Roger Brockett ... ... ... ... ... 1 Mathematics is a Profession Christopher 1. Byrnes ... ... ... ... . 4 Comments on Applied Mathematics Avner Friedman ... ... ... ... . . 9 Towards an Applied Mathematics for Computer Science Jeremy Gunawardena ... ... ... ... . 11 Infomercial for Applied Mathematics Darryl Holm ... ... ... ... ... 15 On Research in Mathematical Economics M. Ali Khan ... ... ... ... ... 21 Applied Mathematics in the Computer and Communications Industry Brian Marcus ... ... ... ... ... 25 'frends in Applied Mathematics Jerrold E. Marsden ... ... ... ... 28 Applied Mathematics as an Interdisciplinary Subject Clyde F. Martin ... ... ... ... . 31 vi Contents Panel Discussion on Future Directions in Applied Mathe matics Laurence R. Taylor ... ... ... ... 38 Part II Feedback Stabilization of Relative Equilibria for Mechanical Systems with Symmetry A.M. Bloch, J.E. Marsden and G. Sanchez ... ... . 43 Oscillatory Descent for Function Minimization R. Brockett ... ... ... ... ... 65 On the Well-Posedness of the Rational Covariance Extension Problem C. l. Byrnes, H.J. Landau and A. Lindquist ... ... 83 Singular Limits in Fluid Mechanics P. Constantin ... ... ... ... ... 109 Singularities and Defects in Patterns Far from Threshold N.M. Ercolani ... ... ... ... ... 137 Mathematical Modeling and Simulation for Applications of Fluid Flow in Porous Media R.E. Ewing ... ... ... ... ... 161 On Loeb Measure Spaces and their Significance for N on Cooperative Game Theory M.A. Khan and Y. Sun ... ... ... ... 183 Mechanical Systems with Symmetry, Variational Principles, and Integration Algorithms J.E. Marsden and J.M. Wendlandt ... ... ... 219 Preface The applied sciences are faced with increasingly complex problems which call for sophisticated mathematical models.

This book is based on the best papers accepted for presentation during the International Conference on Current Problems of Applied Mathematics and Computer Systems (APAMCS-2023). The book includes research materials on mathematical problems and solutions in the field of scientific computing, artificial intelligence, data analysis and modular computing. The scope of numerical methods in scientific computing presents original research, including mathematical models and software implementations, related to the following topics: numerical methods in scientific computing; solving optimization problems; methods for approximating functions, etc. The studies in data analysis and modular computing include contributions in the field of deep learning, neural networks, mathematical statistics, machine learning methods, residue number system and artificial intelligence. In addition, some articles focus on mathematical modeling of nonlinear physical phenomena. Finally, the book gives insights into the fundamental problems in mathematics education. The book intends for readership specializing in the field of scientific computing, parallel computing, computer technology, machine learning, information security and mathematical education

Thirty years ago mathematical, as opposed to applied numerical, computation was difficult to perform and so relatively little used. Three threads changed that: the emergence of the personal computer; the discovery of fiber-optics and the consequent development of the modern internet; and the building of the Three “M’s” Maple, Mathematica and Matlab. We intend to persuade that Mathematica and other similar tools are worth knowing, assuming only that one wishes to be a mathematician, a mathematics educator, a computer scientist, an engineer or scientist, or anyone else who wishes/needs to use mathematics better. We also hope to explain how to become an "experimental mathematician" while learning to be better at proving things. To accomplish this our material is divided into three main chapters followed by a postscript. These cover elementary number theory, calculus of one and several variables, introductory linear algebra, and visualization and interactive geometric computation.

Because trainees need to learn about the underlying technologies to use automation safely and efficiently, the development of automated aviation systems training is a growing challenge. Task analysis has been singled out as the basis of the training, but it can be more time-consuming than traditional development techniques. Cases on Modern Computer Systems in Aviation is an essential reference source that covers new information technology use in aviation systems to streamline the cybersecurity, decision-making, planning, and design processes within the aviation industry. Featuring coverage on a broad range of topics such as computer systems in aviation, artificial intelligence, software-defined networking (SDN), air navigation systems, decision support systems (DSS), and more, this publication is ideally designed for aviation specialists and industry professionals, technicians, practitioners, researchers, and academicians seeking current research on modern modeling approaches to streamline management in aviation.