This book addresses selected topics in electrical engineering, electronics and mechatronics that have posed serious challenges for both the scientific and engineering communities in recent years. The topics covered range from mathematical models of electrical and electronic components and systems, to simulation tools implemented for their analysis and further developments; and from multidisciplinary optimization, signal processing methods and numerical results, to control and diagnostic techniques. By bridging theory and practice in the modeling, design and optimization of electrical, electromechanical and electronic systems, and by adopting a multidisciplinary perspective, the book provides researchers and practitioners with timely and extensive information on the state of the art in the field - and a source of new, exciting ideas for further developments and collaborations. The book presents selected results of the XIII Scientific Conference on Selected Issues of Electrical Engineering and Electronics (WZEE 2016), held on May 04-08, 2016, in Rzeszow, Poland. The Conference was organized by the Rzeszow Division of Polish Association of Theoretical and Applied Electrical Engineering (PTETiS) in cooperation with the Faculty of Electrical and Computer Engineering of the Rzeszow University of Technology.

Includes examples on such cases as solidification of alloys, chemically-driven convection of dissociating gases, temperature-dependent predator-prey mite systems, multi-layer and two-phase fluid phenomena, viral-target cell interactions, diffusive and gravitational instabilities, and chemical, material science, optical, and ecological Turing patterns. Aims to make the process of quantification of scientific phenomena transparent. Is a hybrid semi-autobiographical account of research results and a monograph on pattern formation.

This book gathers peer-reviewed contributions submitted to the 21st European Conference on Mathematics for Industry, ECMI 2021, which was virtually held online, hosted by the University of Wuppertal, Germany, from April 13th to April 15th, 2021. The works explore mathematics in a wide variety of applications, ranging from problems in electronics, energy and the environment, to mechanics and mechatronics. Topics covered include: Applied Physics, Biology and Medicine, Cybersecurity, Data Science, Economics, Finance and Insurance, Energy, Production Systems, Social Challenges, and Vehicles and Transportation. The goal of the European Consortium for Mathematics in Industry (ECMI) conference series is to promote interaction between academia and industry, leading to innovations in both fields. These events have attracted leading experts from business, science and academia, and have promoted the application of novel mathematical technologies to industry. They have also encouraged industrial sectors to share challenging problems where mathematicians can provide fresh insights and perspectives. Lastly, the ECMI conferences are one of the main forums in which significant advances in industrial mathematics are presented, bringing together prominent figures from business, science and academia to promote the use of innovative mathematics in industry.

This book discusses heat transfer in underground energy systems. It covers a wide range of important and practical topics including the modeling and optimization of underground power cable systems, modeling of thermal energy storage systems utilizing waste heat from PV panels cooling. Modeling of PV pannels with cooling. While the performance of energy systems which utilize heat transfer in the ground is not yet fully understood, this book attempts to make sense of them. It provides mathematical modeling fundaments, as well as experimental investigation for underground energy systems. The book shows detailed examples, with solution procedures. The solutions are based on the Finite Element Method and the Finite Volume Method. The book allows the reader to perform a detailed design of various underground energy systems, as well as enables them to study the economic aspects and energy efficiency of underground energy systems. Therefore, this text is of interest to researchers, students, and lecturers alike.

Public-Private Partnerships (PPP or 3Ps) allow the public sector to seek alternative funding and expertise from the private sector during procurement processes. Such partnerships, if executed with due diligence, often benefit the public immensely. Unfortunately, Public-Private Partnerships can be vulnerable to corruption. This book looks at what measures we can put in place to check corruption during procurement and what good governance strategies the public sector can adopt to improve the performance of 3Ps. The book applies mathematical models to analyze 3Ps. It uses game theory to study the interaction and dynamics between the stakeholders and suggests strategies to reduce corruption risks in various 3Ps stages. The authors explain through game theory-based simulation how governments can adopt a evaluating process at the start of each procurement to weed out undesirable private partners and why the government should take a more proactive approach. Using a methodological framework rooted in mathematical models to illustrate how we can combat institutional corruption, this book is a helpful reference for anyone interested in public policymaking and public infrastructure management.

This attractive textbook with its easy-to-follow presentation provides a down-to-earth introduction to operations research for students in a wide range of fields such as engineering, business analytics, mathematics and statistics, computer science, and econometrics. It is the result of many years of teaching and collective feedback from students.The book covers the basic models in both deterministic and stochastic operations research and is a springboard to more specialized texts, either practical or theoretical. The emphasis is on useful models and interpreting the solutions in the context of concrete applications.The text is divided into several parts. The first three chapters deal exclusively with deterministic models, including linear programming with sensitivity analysis, integer programming and heuristics, and network analysis. The next three chapters primarily cover basic stochastic models and techniques, including decision trees, dynamic programming, optimal stopping, production planning, and inventory control. The final five chapters contain more advanced material, such as discrete-time and continuous-time Markov chains, Markov decision processes, queueing models, and discrete-event simulation.Each chapter contains numerous exercises, and a large selection of exercises includes solutions.

This attractive textbook with its easy-to-follow presentation provides a down-to-earth introduction to operations research for students in a wide range of fields such as engineering, business analytics, mathematics and statistics, computer science, and econometrics. It is the result of many years of teaching and collective feedback from students.The book covers the basic models in both deterministic and stochastic operations research and is a springboard to more specialized texts, either practical or theoretical. The emphasis is on useful models and interpreting the solutions in the context of concrete applications.The text is divided into several parts. The first three chapters deal exclusively with deterministic models, including linear programming with sensitivity analysis, integer programming and heuristics, and network analysis. The next three chapters primarily cover basic stochastic models and techniques, including decision trees, dynamic programming, optimal stopping, production planning, and inventory control. The final five chapters contain more advanced material, such as discrete-time and continuous-time Markov chains, Markov decision processes, queueing models, and discrete-event simulation.Each chapter contains numerous exercises, and a large selection of exercises includes solutions.

This volume tackles a variety of biological and medical questions using mathematical models to understand complex system dynamics. Working in collaborative teams of six, each with a senior research mentor, researchers developed new mathematical models to address questions in a range of application areas. Topics include retinal degeneration, biopolymer dynamics, the topological structure of DNA, ensemble analysis, multidrug-resistant organisms, tumor growth modeling, and geospatial modeling of malaria. The work is the result of newly formed collaborative groups begun during the Collaborative Workshop for Women in Mathematical Biology hosted by the Institute of Pure and Applied Mathematics at UCLA in June 2019. Previous workshops in this series have occurred at IMA, NIMBioS, and MBI.

Numerical simulation methods in all engineering disciplines gains more and more importance. The successful and efficient application of such tools requires certain basic knowledge about the underlying numerical techniques. The text gives a practice-oriented introduction in modern numerical methods as they typically are applied in mechanical, chemical, or civil engineering. Problems from heat transfer, structural mechanics, and fluid mechanics constitute a thematical focus of the text. For the basic understanding of the topic aspects of numerical mathematics, natural sciences, computer science, and the corresponding engineering area are simultaneously important. Usually, the necessary information is distributed in different textbooks from the individual disciplines. In the present text the subject matter is presented in a comprehensive multidisciplinary way, where aspects from the different fields are treated insofar as it is necessary for general understanding. Overarching aspects and important questions related to accuracy, efficiency, and cost effectiveness are discussed. The topics are presented in an introductory manner, such that besides basic mathematical standard knowledge in analysis and linear algebra no further prerequisites are necessary. The book is suitable either for self-study or as an accompanying textbook for corresponding lectures. It can be useful for students of engineering disciplines as well as for computational engineers in industrial practice.

Features Built around real-world case studies in a variety of different areas (finance, migration, trade, etc.) Suitable for students and professional researchers with an interest in complex network analysis Paired with a software package for readers who wish to apply the proposed models of centrality (in Python) available at https://github.com/SergSHV/slric.

The eigenvalue densities in various matrix models in quantum chromodynamics (QCD) are ultimately unified in this book by a unified model derived from the integrable systems. Many new density models and free energy functions are consequently solved and presented. The phase transition models including critical phenomena with fractional power-law for the discontinuities of the free energies in the matrix models are systematically classified by means of a clear and rigorous mathematical demonstration. The methods here will stimulate new research directions such as the important Seiberg-Witten differential in Seiberg-Witten theory for solving the mass gap problem in quantum Yang-Mills theory. The formulations and results will benefit researchers and students in the fields of phase transitions, integrable systems, matrix models and Seiberg-Witten theory.

Fifty years ago, a new approach to reaction kinetics began to emerge: one based on mathematical models of reaction kinetics, or formal reaction kinetics. Since then, there has been a rapid and accelerated development in both deterministic and stochastic kinetics, primarily because mathematicians studying differential equations and algebraic geometry have taken an interest in the nonlinear differential equations of kinetics, which are relatively simple, yet capable of depicting complex behavior such as oscillation, chaos, and pattern formation. The development of stochastic models was triggered by the fact that novel methods made it possible to measure molecules individually. Now it is high time to make the results of the last half-century available to a larger audience: students of chemistry, chemical engineering and biochemistry, not to mention applied mathematics. Based on recent papers, this book presents the most important concepts and results, together with a wealth of solved exercises. The book is accompanied by the authors' Mathematica package, ReactionKinetics, which helps both students and scholars in their everyday work, and which can be downloaded from http://extras.springer.com/ and also from the authors' websites. Further, the large set of unsolved problems provided may serve as a springboard for individual research.

Boundary value problems are of interest to mathematicians, engineers, scientists and the technique of investigating these problems for time scales is unique. The key topics here are BVDs, ordinary and partial differential equations, difference equations, and integral equations and so has broad appeal. The techniques presented here are applicable to these topics and the teaching and research. This book is a different take on the topic than the competitors, most offered at a higher level. This book will be accessible to advanced undergraduates, graduate students, and appeal to researchers as well.

This book explains the concept of man-machine systems by using the mining industry. The goal is to use a mathematical model based approach to improve the quality of human life of the workers and operators with the enhancement of productivity by controlling the process variables. The book will illustrate the formulation of mathematical modelling for manual operations. It will provide details in the investigation of many machine systems through the case study approach and provide data analysis using the concept of mathematical modelling and sensitivity. It presents how to solve a field problem through a field data-based modelling concept and highlights the collection of anthropometry data and its behavior. The book will be useful for researchers, academic libraries, professionals, post graduate students of Industrial, Mechanical, and Manufacturing Engineering programs.

This book was inspired by the general observation that the great theories of modern physics are based on simple and transparent underlying mathematical structures - a fact not usually emphasized in standard physics textbooks - which makes it easy for mathematicians to understand their basic features. It is a textbook on quantum theory intended for advanced undergraduate or graduate students: mathematics students interested in modern physics, and physics students who are interested in the mathematical background of physics and are dissatisfied with the level of rigor in standard physics courses. More generally, it offers a valuable resource for all mathematicians interested in modern physics, and all physicists looking for a higher degree of mathematical precision with regard to the basic concepts in their field.

One cannot watch or read about the news these days without hearing about the models for COVID-19 or the testing that must occur to approve vaccines or treatments for the disease. The purpose of Mathematical Modeling in the Age of a Pandemic is to shed some light on the meaning and interpretations of many of the types of models that are or might be used in the presentation of analysis. Understanding the concepts presented is essential in the entire modeling process of a pandemic. From the virus itself and its infectious rates and deaths rates to explain the process for testing a vaccine or eventually a cure, the author builds, presents, and shows model testing. This book is an attempt, based on available data, to add some validity to the models developed and used, showing how close to reality the models are to predicting "results" from previous pandemics such as the Spanish flu in 1918 and more recently the Hong Kong flu. Then the author applies those same models to Italy, New York City, and the United States as a whole. Modeling is a process. It is essential to understand that there are many assumptions that go into the modeling of each type of model. The assumptions influence the interpretation of the results. Regardless of the modeling approach the results generally indicate approximately the same results. This book reveals how these interesting results are obtained.

This book surveys new algorithmic approaches and applications to natural and man-made disasters such as oil spills, hurricanes, earthquakes and wildfires. Based on the "Third International Conference on Dynamics of Disasters" held in Kalamata, Greece, July 2017, this Work includes contributions in evacuation logistics, disaster communications between first responders, disaster relief, and a case study on humanitarian logistics. Multi-disciplinary theories, tools, techniques and methodologies are linked with disasters from mitigation and preparedness to response and recovery. The interdisciplinary approach to problems in economics, optimization, government, management, business, humanities, engineering, medicine, mathematics, computer science, behavioral studies, emergency services, and environmental studies will engage readers from a wide variety of fields and backgrounds.

Accurate estimation, diagnosis, and prevention of COVID-19 is a global challenge for healthcare organizations. Innovative measures can introduce and implement AI, and Mathematical Modeling applications. This book provides insight into the recent advances of applications, statistical methods, and mathematical modeling for the healthcare industry. This book covers the state-of-the-art applications of AI and Machine Learning in past epidemics, pandemics, and COVID-19. It offers recent global case studies, and discusses how AI and statistical methods, initiatives, and applications such as Machine Learning, Deep Learning, Correlation and Regression Analysis play a major role in the prediction, diagnosis, and prevention of a pandemic. It will also focus on how AI and statistical applications can facilitate and restructure the healthcare system. This book is written for Researchers, Students, Professionals, Executives, and the general public.

Future predictions are always a topic of interest. Precise estimates are crucial in many activities as forecasting errors can lead to big financial loss. The sequential analysis of data and information gathered from past to present is call time series analysis. This book covers the recent advancements in time series forecasting. The book includes theoretical as well as recent applications of time series analysis. It focuses on the recent techniques used, discusses a combination of methodology and applications, presents traditional and advanced tools, new applications, and identifies the gaps in knowledge in engineering applications. This book is aimed at scientists, researchers, postgraduate students and engineers in the areas of supply chain management, production, inventory planning, and statistical quality control.

A comprehensive, step-by-step introduction to wavelets in statistics.

What are wavelets? What makes them increasingly indispensable in statistical nonparametrics? Why are they suitable for "time-scale" applications? How are they used to solve such problems as denoising, regression, or density estimation? Where can one find up-to-date information on these newly "discovered" mathematical objects? These are some of the questions Brani Vidakovic answers in Statistical Modeling by Wavelets. Providing a much-needed introduction to the latest tools afforded statisticians by wavelet theory, Vidakovic compiles, organizes, and explains in depth research data previously available only in disparate journal articles. He carefully balances both statistical and mathematical techniques, supplementing the material with a wealth of examples, more than 100 illustrations, and extensive references—with data sets and S-Plus wavelet overviews made available for downloading over the Internet. Both introductory and data-oriented modeling topics are featured, including:

• Continuous and discrete wavelet transformations.
• Statistical optimality properties of wavelet shrinkage.
• Theoretical aspects of wavelet density estimation.
• Bayesian modeling in the wavelet domain.
• Properties of wavelet-based random functions and densities.
• Several novel and important wavelet applications in statistics.
• Wavelet methods in time series.

  Accessible to anyone with a background in advanced calculus and algebra, Statistical Modeling by Wavelets promises to become the standard reference for statisticians and engineers seeking a comprehensive introduction to an emerging field.

* Example-driven approach * Suitable as supplementary reading for a graduate or advanced undergraduate course in dynamical systems

* Example-driven approach * Suitable as supplementary reading for a graduate or advanced undergraduate course in dynamical systems

This volume presents a selection of advanced case studies that address a substantial range of issues and challenges arising in space engineering. The contributing authors are well-recognized researchers and practitioners in space engineering and in applied optimization.

The key mathematical modeling and numerical solution aspects of each application case study are presented in sufficient detail. Classic and more recent space engineering problems including cargo accommodation and object placement, flight control of satellites, integrated design and trajectory optimization, interplanetary transfers with deep space manoeuvres, low energy transfers, magnetic cleanliness modeling, propulsion system design, sensor system placement, systems engineering, space traffic logistics, and trajectory optimization are discussed. Novel points of view related to computational global optimization and optimal control, and to multidisciplinary design optimization are also given proper emphasis. A particular attention is paid also to scenarios expected in the context of future interplanetary explorations.

"Modeling and Optimization in Space Engineering" will benefit researchers and practitioners working on space engineering applications. Academics, graduate and post-graduate students in the fields of aerospace and other engineering, applied mathematics, operations research and optimal control will also find the book useful, since it discusses a range of advanced model development and solution techniques and tools in the context of real-world applications and new challenges."

Carefully separating the essential from the ornamental, Essentials of Control Techniques and Theory presents the nuts and bolts for designing a successful controller. It discusses the theory required to support the art of designing a working controller as well as the various aspects to convince a client, employer, or examiner of your expertise. A Compelling Account of the Basics of Control Theory Control solutions for practicing engineers Using the author's own Javascript On-Line Learning Interactive Environment for Simulation (Jollies), the text relies on computer-based graphical analysis methods, such as Nyquist, Nichols, root locus, and phase-plane, to illustrate how useful computer simulation can be for analyzing both linear and nonlinear systems. It explains step-by-step the design and modeling of various control systems, including discrete time systems and an inverted pendulum. Along with offering many web-based simulations, the book shows how mathematics, such as vectors, matrices, and the differential equations that govern state variables, can help us understand the concepts that underpin the controller's effects. From frequency domain analysis to time-domain state-space representation, this book covers many aspects of classical and modern control theory. It presents important methods for designing and analyzing linear systems and controllers.

Measurement Data Modeling and Parameter Estimation integrates mathematical theory with engineering practice in the field of measurement data processing. Presenting the first-hand insights and experiences of the authors and their research group, it summarizes cutting-edge research to facilitate the application of mathematical theory in measurement and control engineering, particularly for those interested in aeronautics, astronautics, instrumentation, and economics. Requiring a basic knowledge of linear algebra, computing, and probability and statistics, the book illustrates key lessons with tables, examples, and exercises. It emphasizes the mathematical processing methods of measurement data and avoids the derivation procedures of specific formulas to help readers grasp key points quickly and easily. Employing the theories and methods of parameter estimation as the fundamental analysis tool, this reference: Introduces the basic concepts of measurements and errors Applies ideas from mathematical branches, such as numerical analysis and statistics, to the modeling and processing of measurement data Examines methods of regression analysis that are closely related to the mathematical processing of dynamic measurement data Covers Kalman filtering with colored noises and its applications Converting time series models into problems of parameter estimation, the authors discuss modeling methods for the true signals to be estimated as well as systematic errors. They provide comprehensive coverage that includes model establishment, parameter estimation, abnormal data detection, hypothesis tests, systematic errors, trajectory parameters, and modeling of radar measurement data. Although the book is based on the authors' research and teaching experience in aeronautics and astronautics data processing, the theories and methods introduced are applicable to processing dynamic measurement data across a wide range of fields.