Mathematical modelling Books

Book SynopsisThis book covers theoretical aspects of the physical processes, derivation of the governing equations and their solutions. It focusses on hydraulics, hydrology, and contaminant transport, including implementation of computer codes with practical examples. Python-based computer codes for all the solution approaches are provided for better understanding and easy implementation. The mathematical models are demonstrated through applications and the results are analyzed through data tables, plots, and comparison with analytical and experimental data. The concepts are used to solve practical applications like surface and ground water flow, flood routing, crop water requirement and irrigation scheduling. Combines the area of computational hydraulics, hydrology, and water resources engineering with Python Gives deep description of the basic equations and the numerical solutions of both 1D and 2D problems including the numerical codes IncludeTable of Contents1. Introduction to modelling in hydrology, hydraulics and contaminant transport. 2. Nonlinear and simultaneous equations. 3. Ordinary differential equations. 4. Partial differential equations in surface hydrology, free surface flows and ideal fluid flows. 5. Partial differential equations in subsurface flows. 6. Partial differential equations in contaminant transport. 7. Simple data-based models.

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Book SynopsisThe primary aim of this book is to put together an understanding of the appropriate principles of ensuring performance and sustainability of concrete. Broadly subdivided into three parts, first part contains the fundamental aspects introducing the constituent materials, the concepts of concrete mixture designs and the mathematical formulations of the various parameters involved in these designs. The second part is dedicated to discussing approaches and recommendations of American, British and European bodies related to mathematical modelling. Lastly, it discusses perceptions and prescriptions towards both the performance assessment and insurance of the resulting concrete compositions.Table of Contents1. CONCRETE AND MODELLING CONCEPTS. 2. CONSTITUENT MATERIALS AND PROCESSING. 3. CONCEPTS OF CEMENTITIOUS MIXTURE DESIGN. 4. MODELLING AND UNIFICATION CONCEPTS. 5. AMERICAN RECOMMENDATIONS. APPENDIX PROG-ACI-NCNA-5. APPENDIX NCNA-5. APPENDIX NCA-5. APPENDIX NSNA-5. APPENDIX NSA-5. APPENDIX HSN-5. APPENDIX HSP-5. 6. THE BRITISH APPROACH. APPENDIX LAB-6. APPENDIX BSN-6. 7. EURO-INTERNATIONAL VISION. 8. PERCEPTIONS OF PERFORMANCE AND SUSTAINABILITY. 9. VERY HIGH PERFORMANCE AND SUSTAINABLE COMPOSITIONS. 10. PERFORMANCE REGULATORY EFFORTS. 11. FUTURE PROSPECTS AND POTENTIALS.

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Book SynopsisIntroduction to Ocean Circulation and Modeling provide basics for physical oceanography covering ocean properties, ocean circulations and their modeling. First part of the book explains concepts of oceanic circulation, geostrophy, Ekman, Sverdrup dynamics, Stommel and Munk problems, two-layer dynamics, stratification, thermal and salt diffusion, vorticity/instability, and so forth. Second part highlights basic implementation framework for ocean models, discussion of different models, and their unique differences from the common framework with basin-scale modeling, regional modeling, and interdisciplinary modeling at different space and time scales.Features: Covers ocean properties, ocean circulations and their modeling. Explains the centrality of a rotating earth and its implications for ocean and atmosphere in a simple manner. Provides basic facts of ocean dynamics. Illustrative diagrams for clear undTable of Contents 1. Our Home – The Earth. 2. Responses and Forces. 3. Geostrophic Equilibrium. 4 Wind Driven Circulation. 5. The Abyssal Connection. 6. Time Dependent Circulation. 7. The Layering of Oceans. 8. Introduction to Modeling. 9. Turbulence and Eddies. 10. Multiscale Ocean Models. 11. Simulation and Prediction. 12. Synoptic Ocean Modeling. 13. Interdisciplinary Modeling. 14. Modeling of the Climate System.

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Book SynopsisEffectively Assess Intervention Options for Controlling Infectious DiseasesOur experiences with the human immunodeficiency virus (HIV), severe acute respiratory syndrome (SARS), and Ebola virus disease (EVD) remind us of the continuing need to be vigilant against the emergence of new infectious diseases. Mathematical modeling is increasingly used in the management of infectious disease control as a way to assess interventions relatively quickly, cheaply, and safely. Modeling to Inform Infectious Disease Control shows readers how to take advantage of these models when developing strategies to mitigate infectious disease transmission. The book presents a way of modeling as well as modeling results that help to guide the effective management of infectious disease transmission and outbreak response. It discusses the requirements for preventing epidemics and ways to quantify the impact of prevenTable of ContentsIntroduction. Minor outbreaks when infectives are homogeneous. Minor outbreaks in a community of households. Minor outbreaks when individuals differ. Transmission intensity function. Partially effective vaccines. Social distancing. Reducing epidemic size. Dynamics of infection incidence. Using data to inform model choice. Terminology and notation. References. Subject index.

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Book SynopsisModeling and Inverse Problems in the Presence of Uncertainty collects recent researchâincluding the authorsâ own substantial projectsâon uncertainty propagation and quantification. It covers two sources of uncertainty: where uncertainty is present primarily due to measurement errors and where uncertainty is present due to the modeling formulation itself. After a useful review of relevant probability and statistical concepts, the book summarizes mathematical and statistical aspects of inverse problem methodology, including ordinary, weighted, and generalized least-squares formulations. It then discusses asymptotic theories, bootstrapping, and issues related to the evaluation of correctness of assumed form of statistical models. The authors go on to present methods for evaluating and comparing the validity of appropriateness of a collection of models for describing a given data set, including statistically based model selection and comparison techniques. They also explore recent results on the estimation of probability distributions when they are embedded in complex mathematical models and only aggregate (not individual) data are available. In addition, they briefly discuss the optimal design of experiments in support of inverse problems for given models. The book concludes with a focus on uncertainty in model formulation itself, covering the general relationship of differential equations driven by white noise and the ones driven by colored noise in terms of their resulting probability density functions. It also deals with questions related to the appropriateness of discrete versus continuum models in transitions from small to large numbers of individuals.With many examples throughout addressing problems in physics, biology, and other areas, this book is intended for applied mathematicians interested in deterministic and/or stochastic models and their interactions. It is also sTable of ContentsIntroduction. Probability and Statistics Overview. Mathematical and Statistical Aspects of Inverse Problems. Model Comparison Criteria. Estimation of Probability Measures Using Aggregate Population Data. Optimal Design. Propagation of Uncertainty in a Continuous Time Dynamical System. A Stochastic System and Its Corresponding Deterministic System. Frequently Used Notations and Abbreviations. Index.

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Book SynopsisModel-Based Control of Nonlinear Systems presents model-based control techniques for nonlinear, constrained systems. It covers constructive control design methods with an emphasis on modeling constrained systems, generating dynamic control models, and designing tracking control algorithms for the models.The book's interdisciplinary approach illustrates how system modeling and control theory are essential to control design projects. Organized according to the steps in a control design project, the text first discusses kinematic and dynamic modeling methods, including programmed constraints, Lagrange's equations, Boltzmann-Hamel equations, and generalized programmed motion equations. The next chapter describes basic control concepts and the use of nonlinear control theory. After exploring stabilization strategies for nonlinear systems, the author presents existing model-based tracking control algorithms and path-following strategies fTable of ContentsIntroduction. Dynamics Modeling of Constrained Systems. Introduction to Nonlinear Control Theory. Stabilization Strategies for Nonlinear Systems. Model-Based Tracking Control of Nonlinear Systems. Path-Following Strategies for Nonlinear Systems. Model Reference Tracking Control of High-Order Nonholonomic Systems. Concluding Remarks.

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Book SynopsisThe topic of dynamic models tends to be splintered across various disciplines, making it difficult to uniformly study the subject. Moreover, the models have a variety of representations, from traditional mathematical notations to diagrammatic and immersive depictions. Collecting all of these expressions of dynamic models, the Handbook of Dynamic System Modeling explores a panoply of different types of modeling methods available for dynamical systems.Featuring an interdisciplinary, balanced approach, the handbook focuses on both generalized dynamic knowledge and specific models. It first introduces the general concepts, representations, and philosophy of dynamic models, followed by a section on modeling methodologies that explains how to portray designed models on a computer. After addressing scale, heterogeneity, and composition issues, the book covers specific model types that are often characterized by specific visual- or text-based grammars. It concludes with case studies thTable of ContentsIntroduction. Modeling Methodologies. Multiobject and System. Model Types. Case Studies.

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Book SynopsisMathematical Modelling of Solids with Nonregular Boundaries demonstrates the use of asymptotic methods and other analytical techniques for investigating problems in solid mechanics. Applications to solids with nonregular boundaries are described in detail, providing precise and rigorous treatment of current methods and techniques. The book addresses problems in fracture mechanics of inhomogeneous media and illustrates applications in strength analysis and in geophysics. The rigorous approach allows the reader to explicitly analyze the stress-strain state in continuous media with cavities or inclusions, in composite materials with small defects, and in elastic solids with sharp inclusions. Effective asymptotic procedures for eigenvalue problems in domains with small defects are clearly outlined, and methods for analyzing singularly perturbed boundary value problems are examined.Introductory material is provided in the first chapter of Mathematical Modelling of Solids with NonregularTrade Review"Of interest to advanced graduate students and scientists who work in the area of fracture mechanics."- Applied Mechanics Reviews, Volume 49, Number 3, March 1996Table of Contents1. Introduction 2. Modelling of Cracks and Thin Inclusions in Elastic Media 3. Domains with Conical and Cylindrical Boundaries 4. Stress-Strain State in the Vicinity of Sharp Inclusions 5. Integral Characteristics in Elasticity Problems for Nonhomogeneous Bodies

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Book SynopsisMathematical Modelling sets out the general principles of mathematical modelling as a means comprehending the world. Within the book, the problems of physics, engineering, chemistry, biology, medicine, economics, ecology, sociology, psychology, political science, etc. are all considered through this uniform lens. The author describes different classes of models, including lumped and distributed parameter systems, deterministic and stochastic models, continuous and discrete models, static and dynamical systems, and more. From a mathematical point of view, the considered models can be understood as equations and systems of equations of different nature and variational principles. In addition to this, mathematical features of mathematical models, applied control and optimization problems based on mathematical models, and identification of mathematical models are also presented.Features Each chapter includes four levelTable of Contents Foundations of mathematical modelling. Lecture. 1.1 Cognition and modelling. 1.2 Natural sciences and Mathematics. 1.3 Content or form? 1.4 Copernicus or Ptolemy? 1.5 Mathematical model of a body falling. 1.6 Principles of mathematical model determining. 1.7. Classification of mathematical models. Appendix. 1. Probe movement. 2. Missile flight. 3 Glider flight. Notes. I. Systems with lumped parameters. 2. Approximate solving of differential equations. Lecture. 2.1 Conception of approximate solution. 2.2 Euler method. 2.3 Probe movement. 2.4 Missile flight. 2.5. Glider flight. Appendix. 1. Runge-Kutta method. 2. Two-body problem. 3. Predator-pray model. Notes. 3. Mechanical Oscillations. Lecture. 3.1. Determination of the pendulum oscillation equation. 3.2 Solving of the pendulum oscillation equation. 3.3 Pendulum oscillation energy. 3.4 Oscillation of a pendulum with friction. 3.5 Equilibrium position of the pendulum. 3.6 Forced oscillations of the pendulum. Appendix. 1. Spring oscillation. 2. Large pendulum oscillations. 3. Problems of nonlinear oscillation theory. Notes. 4 Electrical Oscillations. Lecture. 4.1 Electrical circuit. 4.2 Energy of circuit. 4.3 Circuit with resistance. 4.4 Forced circuit oscillations. Appendix. 1. Forced oscillations of spring. 2. Circuit with nonlinear capacity. 3 Van der Pol circuit. Notes. 5. Elements of dynamical system theory. Lecture. 5.1. Evolutionary processes and differential equations. 5.2 General notions of dynamic systems theory. 5.3 Change in species number with excess food. 5.4 Oscillations of pendulum. 5.5 Stability of the equilibrium position. 5.6 Limit cycle. Appendix. 1. Exponential growth systems. 2. Brussellator. 3. System with two limit cycle. Notes. 6. Mathematical models in chemistry. Lecture. 6.1. Chemical kinetics equations. 6.2. Monomolecular reaction. 6.3. Bimolecular reaction. 6.4. Lotka reaction system. Appendix. 1. Brusselator. 2. Oregonator. 3. Chemical niche. 4. Laser healing model. Notes. 7. Mathematical model in biology. Lecture. 7.1. One species evolution. 7.2. Biological competition model. 7.3 Predator-prey model. 7.4 Symbiosis model. Appendix. 1. Models of chemical and physical competition. 2. Fluctuations in yield and fertility. 3. Ecological niche model. 4. SIR model for spread of disease. 5. Antibiotic resistance model. Notes. 8. Mathematical model of economics. Lecture. 1. One company evolution. 2. Economic competition model. 3. Economic niche model. 4. Free market model. 5. Monopolized market model. Appendix. 1. Ecological niche model. 2. Inflation model. 3. Model of economic cooperation. 4. Racketeer – entrepreneur model. 5. Solow model of economic growth. Notes. 9. Mathematical models in social sciences. Lecture. 9.1. Political competition. 9.2. Political niche. 9.3. Bipartisan system. 9.4. Trade union activity. 9.5 Allied relations. Appendix. 1. Competition models. 2. Niche models. 3. Predator-prey models. Notes. II. Systems with distributed parameters. 10. Mathematical models of transfer processes. Lecture. 10.1 Heat equation. 10.2 First boundary value problem for the homogeneous heat equation. 10.3 Non-homogeneous heat equation. Appendix. 1. Generalizations of the heat equation. 2. Second boundary value problem for the heat equation. 3. Diffusion equation. Notes. 11. Mathematical models of transfer processes. Lecture. 1. Heat equation and similarity theory. 2. Goods transfer equation. 3. Finite difference method for the heat equation. 4. Diffusion of chemical reactants. 5. Stefan problem for the heat equation. Appendix. 1. Overview of transfer processes. 2. Finite difference method. Implicit scheme. 3. Competitive species migration. 4. Hormone treatment of the tumor with hormone resistance. Notes. 12. Wave processes. Lecture. 12.1. Vibration of string. 12.2. Vibrations of string with fixed ends. 12.3 Infinitely long string. 12.4. Electrical vibrations in wires. Appendix. 1. Energy of vibrating string. 2. Mathematical models of wave processes. 3. Beam vibrations. 4. Maxwell equations. 5. Finite difference method for the vibrating string equation. Notes. 13. Mathematical models of stationary systems. Lecture. 13.1. Stationary heat transfer 13.2. Spherical and cylindrical coordinates. 13.3 Vector fields. 13.4. Electrostatic field. 13.5 Gravity field. Appendix. 1. Stationary fluid flow. 2. Steady oscillations. 3. Bending a thin elastic plate. 4. Variable separation method for the Laplace equation in a circle. 5. Establishment method. Notes. 14. Mathematical models of fluid and gas mechanics. Lecture. 14.1. Vibration string equation. 14.2. Ideal fluid movement. 14.3. Ideal fluid under the gravity field. 14.4. Viscous fluid movement. Appendix. 1. Burgers equation. 2. Surface wave movement. 3. Boundary layer model. 4. Acoustic problem. 5. Thermal convection. 6. Problems of magnetohydrodynamics. Notes. 15. Mathematical models of quantum mechanical systems. Lecture. 15.1. Quantum mechanics problems. 15.2. Wave function. 15.3. Schrödinger equation. 15.4. Particle movement under an external field. 15.5. Potential barrier. Appendix. 1. Wave function normalization. 2. Particle movement in a well with infinitely high walls. Notes. III. Other mathematical models. 16. Variational principles. Lecture. 1. Brachistochrone problem. 2. Lagrange problem. 3. Shortest curve. 4. Body falling problem and the concept of action. 5. Principle of least action. 6. Vibrations of string. Appendix. 1. Law of conservation of energy. 2. Fermat's principle and light refraction. 3. River crossing problem. 4. Pendulum oscillations. 5. Approximate solution of minimization problems. Notes. 17. Discrete models. Lecture. 17.1. Discrete population dynamics models. 17.2. Discrete heat transfer model. 17.3. Transportation problem. 17.4. Traveling salesman problem. 17.5. Prisoner's Dilemma. Appendix. 1. Discrete model of epidemic propagation. 2. Potential method for solving a transportation problem. 3. Production planning. 4. Concepts of game theory. Notes. 18. Stochastic models. Lecture. 18.1. Stochastic model of pure birth. 18.2. Monte Carlo method. 18.3. Stochastic model of population death. 18.4. Stochastic Malthus model. Appendix. 1. Malthus model with random population growth. 2. Models with random parameters. 3. Discrete model of selling goods. 4. Passage of a neutron through a plate. Notes. IV. Additions. 19. Mathematical problems of mathematical models. Lecture. 19.1. Cauchy problem properties for differential equations. 19.2. Properties of boundary value problems. 19.3. Boundary value problems for the heat equation. 19.4. Hadamard's example and well-posedness of problems. 19.5. Classical and generalized solution of problems. Appendix. 1. Nonlinear boundary value problems. 2. Euler's elastic problem. 3. Bénard problem. 4. Generalized model of stationary heat transfer. 5. Sequential model of stationary heat transfer. Notes. 20. Optimal control problems. Lecture. 20.1. Maximizing the shell fight range. 20.2. Maximizing the missile fight range. 20.3. General optimal control problem. 20.4. Solving of the maximization problem of the missile fight range. 20.5. Time-optimal control problem. Appendix. 1. Maximizing the probe's ascent height. 2. Approximate methods for solving optimality conditions. 3. Gradient methods. Notes. 21. Identification of mathematical models. Lecture. 21.1. Problem of determining the system parameters. 21.2. Inverse problems and their solving. 21.3. Heat equation with data at the final time. 21.4. Differentiation of functionals and gradient methods. 21.5. Solving of the heat equation with reversed time. Appendix. 1. Boundary inverse problem for the heat equation. 2. Inverse problem for the falling of body. 3. Inverse gravimetry problem. 4. Well-posedness of optimal control problems. Notes. Epilogue. Bibliography. Index.

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Book SynopsisThe goal of this book is to provide a reference for applications of mathematical modelling in social media and related network analysis and offer a theoretically sound background with adequate suggestions for better decision-making. Social Networks: Modelling and Analysis provides the essential knowledge of network analysis applicable to real-world data, with examples from today''s most popular social networks such as Facebook, Twitter, Instagram, YouTube, etc. The book provides basic notation and terminology used in social media and its network science. It covers the analysis of statistics for social network analysis such as degree distribution, centrality, clustering coefficient, diameter, and path length. The ranking of the pages using rank algorithms such as Page Rank and HITS are also discussed. Written as a reference this book is for engineering and management students, research scientists, as well as academicians involved in complex networks, mathematicaTable of Contents1. Introduction to Social Networks, 2. Network Statistics and Related Concepts. 3. Network Models. 4. Network Centrality. 5. Link Analysis. 6. Link Prediction. 7. Community Detention. 8. Ego Networks. 9. Network Cohesion. 10. Information Diffusion. 11. Security and Privacy in Social Network. 12. Social Network Analysis Tools.

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Book SynopsisIntroduction to Modeling and Simulation with MATLAB and Python is intended for students and professionals in science, social science, and engineering that wish to learn the principles of computer modeling, as well as basic programming skills. The book content focuses on meeting a set of basic modeling and simulation competencies that were developed as part of several National Science Foundation grants. Even though computer science students are much more expert programmers, they are not often given the opportunity to see how those skills are being applied to solve complex science and engineering problems and may also not be aware of the libraries used by scientists to create those models.The book interleaves chapters on modeling concepts and related exercises with programming concepts and exercises. The authors start with an introduction to modeling and its importance to current practices in the sciences and engineering. They introduce each of the prTrade ReviewGordon (Ohio State Univ.) and Guilfoos (Ohio Supercomputer Center) provide a practical introduction to the techniques involved in developing computer models and simulating those models. The emphasis in the text is on engineering applications, but natural and social science applications are addressed as well. The presentation is purposely constrained to a depth of coverage suitable for a first undergraduate course in the subject, with useful pointers for students who wish to visit the subject more deeply. The authors do a good job of introducing two computing environments for developing models and simulating them: the MATLAB commercial product and the freely available Python programming language. By judicious choice of Python libraries, the presentation of the two environments are virtually identical, leaving the choice of environment up to the instructor (or student). Readers using Python will need to correct minor errors in the text regarding how to set up the recommended Anaconda environment. Or, they might profitably choose simply to use the standard command line and code editor interface for that language.--C. Vickery, Queens College of CUNY (CHOICE)Gordon (Ohio State Univ.) and Guilfoos (Ohio Supercomputer Center) provide a practical introduction to the techniques involved in developing computer models and simulating those models. The emphasis in the text is on engineering applications, but natural and social science applications are addressed as well. The presentation is purposely constrained to a depth of coverage suitable for a first undergraduate course in the subject, with useful pointers for students who wish to visit the subject more deeply. The authors do a good job of introducing two computing environments for developing models and simulating them: the MATLAB commercial product and the freely available Python programming language. By judicious choice of Python libraries, the presentation of the two environments are virtually identical, leaving the choice of environment up to the instructor (or student). Readers using Python will need to correct minor errors in the text regarding how to set up the recommended Anaconda environment. Or, they might profitably choose simply to use the standard command line and code editor interface for that language.--C. Vickery, Queens College of CUNY (CHOICE)

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Book SynopsisModeling Tools for Environmental Engineers and Scientists enables environmental professionals, faculty, and students with minimal computer programming skills to develop computer-based mathematical models for natural and engineered environmental systems. The author illustrates how commercially available syntax-free authoring software can be adapted to create customized, high-level models of environmental phenomena in groundwater, soil, aquatic, and atmospheric systems, and in engineered reactors.This book includes a review of mathematical modeling and fundamental concepts such as material balance, reactor configurations, and fate and transport of environmental contaminants. It illustrates, using numerous examples, how mathematical and dynamic modeling software can be applied in analyzing and simulating natural and engineered environmental systems. The tools and examples included are applicable to a wide range of problems, both in the classroom and in the field.Trade Review"This book provides a catalog, descriptions and reviews 'Ecological models' ranging from statistical extrapolation models to population, Ecosystem and landscape models. The editors are leaders in the field. They and the authors have performed a valuable service to the ecorisk community. It is now the task of practitioners to explore this array of models and determine how to implement them in specific cases using realistically available data sets." -Glenn W. Suter, II, United States EPA, Cincinnati, Ohio, USATable of ContentsFUNDAMENTALS. Introduction to Modeling. Fundamentals of Mathematical Modeling. Primer on Mathematics. Fundamentals of Environmental Processes. Fundamentals of Engineered Systems. Fundamentals of Natural Systems. Software for Developing Mathematical Models. APPLICATIONS. Modeling Engineered Environmental Systems. Modeling Natural Environmental Systems.

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Book SynopsisField Programmable Gate Arrays (FPGAs) are currently recognized as the most suitable platform for the implementation of complex digital systems targeting an increasing number of industrial electronics applications. They cover a huge variety of application areas, such as: aerospace, food industry, art, industrial automation, automotive, biomedicine, process control, military, logistics, power electronics, chemistry, sensor networks, robotics, ultrasound, security, and artificial vision. This book first presents the basic architectures of the devices to familiarize the reader with the fundamentals of FPGAs before identifying and discussing new resources that extend the ability of the devices to solve problems in new application domains. Design methodologies are discussed and application examples are included for some of these domains, e.g., mechatronics, robotics, and power systems.Trade Review"The new book FPGAs: Fundamentals, Advanced Features, and Applications in Industrial Electronics presents all the facets of today’s field-programmable gate array (FPGA) technology. The aim of the authors is to offer engineers and, more generally, readers who have experience in industrial electronics a good understanding of both the basics and the latest trends related to FPGAs. FPGAs: Fundamentals, Advanced Features, and Applications in Industrial Electronics is a valuable textbook for all those who want to better comprehend FPGAs and their most recent evolutions to use them relevantly in industrial control systems."—IEEE Industrial Electronics Magazine, June 2017 IssueTable of ContentsFPGAs and their Role in the Design of Electronic Systems. Main Architectures and Hardware Resources of FPGAs. Embedded Processors in FPGA Architectures. Advanced Signal Processing Resources in FPGAs. Mixed-Signal FPGAs. Tools and Methodologies for FPGA-Based Design. Off-chip and in-chip communications for FPGA systems. Building Reconfigurable Systems using Commercial FPGAs. Industrial Electronics Applications of FPGAs.

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Book SynopsisStochastic Communities presents a theory of biodiversity by analyzing the distribution of abundances among species in the context of a community. The basis of this theory is a distribution called the J distribution. This distribution is a pure hyperbola and mathematically implied by the stochastic species hypothesis assigning equal probabilities of birth and death within the population of each species over varying periods of time. The J distribution in natural communities has strong empirical support resulting from a meta-study and strong theoretical support from a theorem that is mathematically implied by the stochastic species hypothesis.Trade Review"The science of ecology suffers from a disconnect between theory and direct observation. Mathematicians have thought that simple equations could explain ecology. Field ecologists have assumed the mathematicians are right. Thus, empirical ecological understanding and prediction have suffered. Dewdney is an exceptions; he does field work and he is a mathematician. In his wonderful book, he takes advantage of both parts of ecology. And if Dewdney has done his math right, this book opens a whole new door to understanding biodiversity and its myriad causes."- Daniel Botkin, Professor Emeritus in the Department of Ecology, Evolution, and Marine Biology at the University of California, Santa Barbara, and President of the Center for the Study of the Environment"… development of a theory and guide to sampling, … it will be of great interest to both empirical and theoretical ecologists." - Trends in Ecology and EvolutionTable of ContentsThe J-curve and the J distribution. The J-distribution and its variations. Sampling in practice and in theory. Compiling and analysing field data. Predictions from data. Extending the sample. Stochastic systems and the stochastic community. The metastudy: A review. Fossil J-curves. Summary of theory and open problems. Appendix A: Mathematical Notes and Computer Tools. Appendix B: Results of the metastudy for the J distribution. Appendix C: Results of the test for the J distribution in taxonomic data.

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Book SynopsisThis 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.Table of Contents1. Man Machine System. 2. Formulation of Problem. 3. Design of Experimentation. 4. Procedure of Experimentation and Experimental Results. 5. Mathematical Modelling of Operations, 6. ANN Simulation. 7. Sensitivity Analysis. 8. Analysis of Performance of the Model. 9. Quantitative Analysis on Face Drilling Operation.

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Book SynopsisThis book synthesizes the game-theoretic modeling of decision-making processes and an ancient moral requirement, called the Golden Rule of ethics. Of interest to undergraduate and graduate students and experts in the field of decision-making in complex control and management systems, or anyone interested in game theory and applications.Table of ContentsIntroduction. 1. Compendium. 2. Mathematical Model of the Golden Rule of Ethics in Form of Differential Positional Game Part I Games with Separated Dynamics. Part II Linear-Quadratic Game with Small Influence of One Player on the Rate of Change of State Vector. 3. Berge Equilibria in Multistage Games. Appendix 1 Exercises, Problems, and Solution Tips. Appendix 2 Pareto Equilibrium in Threats and Counter-Threats for a Differential Three-Player Game. Appendix 3 Guaranteed Solution for Risk-Neutral Decision-Maker: An Analog of Maximin in Single-Criterion Choice Problems. Appendix 4 The Concept of Strong Coalitional Equilibrium. Bibliography.

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Book SynopsisThis book synthesizes the game-theoretic modeling of decision-making processes and an ancient moral requirement called the Golden Rule of ethics (GR). This rule states Behave to others as you would like them to behave to you. The GR is one of the oldest, most widespread, and specific moral requirements that appear in Christianity, Islam, Judaism, Buddhism, and Confucianism. This book constructs and justifies mathematical models of dynamic socio-economic processes and phenomena that reveal the mechanism of the GR and are based on the concept of Berge equilibrium. The GR can be naturally used for resolving or balancing conflicts, and its altruistic character obviously excludes wars, blood-letting, and armed clashes. The previous book by the authors, The Berge Equilibrium: A Game-Theoretic Framework for the Golden Rule of Ethics, covers the static case of the GR. In this book, the dynamic case of the GR is investigated using the altruistic concept of Berge equilibrium and three factors as follows: 1) a modification of N.N. Krasovskiiâs mathematical formalization of differential positional games (DPGs), in view of the counterexamples given by A.I. Subbotin and A.F. Kononenko; 2) the method of guiding control, proposed by N.N. Krasovskii; and 3) the Germier convolution of the payoff functions of different players. Additionally, this book features exercises, problems, and solution tips collected together in Appendix 1, as well as new approaches to conflict resolution as presented in Appendices 2 to 4. This book will be of use to undergraduate and graduate students and experts in the field of decision-making in complex control and management systems, as well as anyone interested in game theory and applications.Table of ContentsIntroduction. 1. Compendium. 2. Mathematical Model of the Golden Rule of Ethics in Form of Differential Positional Game Part I Games with Separated Dynamics. Part II Linear-Quadratic Game with Small Influence of One Player on the Rate of Change of State Vector. 3. Berge Equilibria in Multistage Games. Appendix 1 Exercises, Problems, and Solution Tips. Appendix 2 Pareto Equilibrium in Threats and Counter-Threats for a Differential Three-Player Game. Appendix 3 Guaranteed Solution for Risk-Neutral Decision-Maker: An Analog of Maximin in Single-Criterion Choice Problems. Appendix 4 The Concept of Strong Coalitional Equilibrium. Bibliography.

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Book SynopsisThis book describes different mathematical modeling and soft computing techniques used to solve practical engineering problems. It gives an overview of the current state of soft computing techniques and describes the advantages and disadvantages of soft computing compared to traditional hard computing techniques. Through examples and case studies, the editors demonstrate and describe how problems with inherent uncertainty can be addressed and eventually solved through the aid of numerical models and methods. The chapters address several applications and examples in bioengineering science, drug delivery, solving inventory issues, Industry 4.0, augmented reality and weather forecasting. Other examples include solving fuzzy-shortest-path problems by introducing a new distance and ranking functions. Because, in practice, problems arise with uncertain data and most of them cannot be solved exactly and easily, the main objective is to develop models that deliver solutions with the aid of numerical methods. This is the reason behind investigating soft numerical computing in dynamic systems. Having this in mind, the authors and editors have considered error of approximation and have discussed several common types of errors and their propagations. Moreover, they have explained the numerical methods, along with convergence and consistence properties and characteristics, as the main objectives behind this book involve considering, discussing and proving related theorems within the setting of soft computing. This book examines dynamic models, and how time is fundamental to the structure of the model and data as well as the understanding of how a process unfolds â Discusses mathematical modeling with soft computing and the implementations of uncertain mathematical models â Examines how uncertain dynamic systems models include uncertain state, uncertain state space and uncertain stateâs transition functions â Assists readers to become familiar with many soft numerical methods to simulate the solution functionâs behaviorThis book is intended for system specialists who are interested in dynamic systems that operate at different time scales. The book can be used by engineering students, researchers and professionals in control and finite element fields as well as all engineering, applied mathematics, economics and computer science interested in dynamic and uncertain systems.Ali Ahmadian is a Senior Lecturer at the Institute of IR 4.0, The National University of Malaysia.Soheil Salahshour is an associate professor at Bahcesehir University.Table of Contents1. Soft Computing Techniques: An Overview. 2. Applications of Fuzzy Fractional Differential Equations in Medicine. 3. Industrial Internet of Things and Industry 4.0. 4. Industry 4.0 and its practice in terms of fuzzy uncertain environment. 5. Consistency of Aggregation Function-Based m-Polar Fuzzy Digraphs in Group Decision Making. 6. Path programming problems in fuzzy environment. 7. Weather forecast and climate prediction using soft computing methods. 8. Color Descriptor for Mobile Augmented Reality. 9. Cryptosystem for Meshed 3D through Cellular Automata. 10. Evolutionary Computing and Swarm Intelligence for Hyper Parameters Optimization Problem in Convolutional Neural Networks. 11. New Approach for Efficiently Computing Factors of the RSA Modulus. 12. Vision based Efficient Collision Avoidance Model Using Distance Measurement.

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Book SynopsisAccurate 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.Table of ContentsChapter 1 Deep Learning for COVID-19 Infection’s Diagnosis, Prevention, and Treatment Chapter 2Artificial Intelligence in Coronavirus Detection—Recent Findings and Future Perspectives Chapter 3Solutions of Differential Equations for Prediction of COVID-19 Cases by Homotopy Perturbation MethodChapter 4Predictive Models of Hospital Readmission Rate Using the Improved AdaBoost in COVID-19 Chapter 5Nigerian Medical Laboratory Diagnosis of COVID-19; from Grass to GraceChapter 6 COVID-19 CT Image Segmentation and Detection: Review Chapter 7Interactive Medical Chatbot for Assisting with COVID-related Queries Chapter 8 COVID-19 Outbreak Prediction After Lockdown, Based on Current Data Analytics Chapter 9A Deep Learning CNN Model for Genome Sequence ClassificationChapter 10 The Impact of Lockdown Strategies on COVID-19 Cases with a Confined Sentiment Analysis of COVID-19 Tweets Chapter 11 A Mathematical Model and Forecasting of COVID-19 Outbreak in India Chapter 12 Automatic Lung Infection Segmentation of COVID-19 in CT Scan Images Chapter 13 A Review of Feature Selection Algorithms in Determining the Factors Affecting COVID-19 Chapter 14 Industry 4.0 Technology-based Diagnosis for COVID-19 Index

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Book SynopsisFor almost every phenomenon in physics, chemistry, biology, medicine, economics, and other sciences, one can make a mathematical model that can be regarded as a dynamical system. One-Dimensional Dynamical Systems: An Example-Led Approach seeks to deep-dive into a standard maps as an example-driven way of explaining the modern theory of the subject in a way that will be engaging for students. Features Example-driven approach Suitable as supplementary reading for a graduate or advanced undergraduate course in dynamical systems Table of Contents1. Introduction. 2. Rotation Numbers. 2.1. Arnold Tongues for Double Standard Maps. 2.2 Arnold Tongues for ɑ-Standard Maps. 3. Topological conjugacy. 4. Critical points. 5. Topological theory of Chaos. 5.1. Topological Entropy. 5.2. Schwarzian Derivative. 6. Symbolic Dynamics. 6.1. Kneading Sequences for Double Standard Maps. 6.2 Kneading Sequences for ɑ-Standard Maps. 7. Tongues. 7.1. Length of Tongues. 7.2. Boundary of The Tongues. 7.3. Tip of the Tongues. 7.4. Connectedness of Tongues. 7.5. Arnold Tongues of Higher Periods for ɑ-Standard Maps. Bibliography.

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Book SynopsisFor almost every phenomenon in physics, chemistry, biology, medicine, economics, and other sciences, one can make a mathematical model that can be regarded as a dynamical system. One-Dimensional Dynamical Systems: An Example-Led Approach seeks to deep-dive into a standard maps as an example-driven way of explaining the modern theory of the subject in a way that will be engaging for students. Features Example-driven approach Suitable as supplementary reading for a graduate or advanced undergraduate course in dynamical systems Table of Contents1. Introduction. 2. Rotation Numbers. 2.1. Arnold Tongues for Double Standard Maps. 2.2 Arnold Tongues for ɑ-Standard Maps. 3. Topological conjugacy. 4. Critical points. 5. Topological theory of Chaos. 5.1. Topological Entropy. 5.2. Schwarzian Derivative. 6. Symbolic Dynamics. 6.1. Kneading Sequences for Double Standard Maps. 6.2 Kneading Sequences for ɑ-Standard Maps. 7. Tongues. 7.1. Length of Tongues. 7.2. Boundary of The Tongues. 7.3. Tip of the Tongues. 7.4. Connectedness of Tongues. 7.5. Arnold Tongues of Higher Periods for ɑ-Standard Maps. Bibliography.

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Book SynopsisThis book introduces the principle of carrying out a medium-term load forecast (MTLF) at power system level, based on the Big Data concept and Convolutionary Neural Network (CNNs). It also presents further research directions in the field of Deep Learning techniques and Big Data, as well as how these two concepts are used in power engineering.Efficient processing and accuracy of Big Data in the load forecast in power engineering leads to a significant improvement in the consumption pattern of the client and, implicitly, a better consumer awareness. At the same time, new energy services and new lines of business can be developed.The book will be of interest to electrical engineers, power engineers, and energy services professionals.Table of Contents1. Big Data Analysis Tools: Data Collection and Sampling. 2. Big Data and the Energy Field. 3. The Load Forecast: A New Application for Big Data. 4. Conclusions.

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Book SynopsisThis book, first published in 1981, offers a critical review of the techniques of mathematical modelling and their appropriate application to military operations research â the analysis of data (historical data, exercise and test results, and intelligence) in preparation for war. The virtues of sophistication via simplicity, and the beauty of the artful finesse, emerge as the signature of successful modelling. Table of Contents1. Introduction 2. Costing: Life Cycle Cost Models 3. Strategic Mobility 4. Modeling Strategic Bomber Penetration 5. The Theater Tactical Air Campaign 6. The Theater-Level Limited War 7. Strategic Nuclear Exchange Models 8. Phoenix – After the Holocaust: Is Recovery Possible? 9. Epilogue

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Book SynopsisThis book, first published in 1981, offers a critical review of the techniques of mathematical modelling and their appropriate application to military operations research the analysis of data (historical data, exercise and test results, and intelligence) in preparation for war. The virtues of sophistication via simplicity, and the beauty of the artful finesse, emerge as the signature of successful modelling. Table of Contents1. Introduction 2. Costing: Life Cycle Cost Models 3. Strategic Mobility 4. Modeling Strategic Bomber Penetration 5. The Theater Tactical Air Campaign 6. The Theater-Level Limited War 7. Strategic Nuclear Exchange Models 8. Phoenix – After the Holocaust: Is Recovery Possible? 9. Epilogue

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Book SynopsisFocusing on the orbital mechanics tools and techniques necessary to design, predict, and guide a trajectory of a spacecraft traveling between two or more bodies in a Solar System, this book covers the dynamical theory necessary for describing the motion of bodies in space, examines the N-body problem, and shows applications using this theory for designing interplanetary missions. While most orbital mechanics books focus primarily on Earth-orbiting spacecraft, with a brief discussion of interplanetary missions, this book reverses the focus and emphasizes the interplanetary aspects of space missions. Written for instructors, graduate students, and advanced undergraduate students in Aerospace and Mechanical Engineering, this book provides advanced details of interplanetary trajectory design, navigation, and targeting.Trade Review"This book is especially timely given the renewed interested in lunar mission and our focus on getting humans to Mars. We know that students are really interested in "new space" and space exploration. This book fills a need to prepare students for missions beyond earth orbit." - Ron Madler, Embry-Riddle Aeronautical University"Spencer and Conte have produced an excellent resource for the interplanetary trajectory designer. The topics covered in this text are appropriate for both the senior undergraduate orbital mechanics student and the advanced space mechanics graduate student. This is a must have reference for any Astrodynamicist." - Julio César Benavides, The University of Texas at ArlingtonTable of Contents1. Introduction. 2. Kinematics, Dynamics, and Astrodynamics. 3. N-Body Problem. 4. Coordinate Frames, Time, and Planetary Ephemerides. 5. Trajectory Design. 6. Navigation and Targeting. Appendices.References.

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Book SynopsisThis book is an introduction to numerical analysis in geomechanics and is intended for advanced undergraduate and beginning graduate study of the mechanics of porous, jointed rocks and soils. Although familiarity with the concepts of stress, strain and so on is assumed, a review of the fundamentals of solid mechanics including concepts of physical laws, kinematics and material laws is presented in an appendix. Emphasis is on the popular finite element method but brief explanations of the boundary element method, the distinct element method (also known as the discrete element method) and discontinuous deformation analysis are included. Familiarity with a computer programming language such as Fortran, C++ or Python is not required, although programming excerpts in Fortran are presented at the end of some chapters.This work begins with an intuitive approach to interpolation over a triangular element and thus avoids making the simple complex by not doing energy minimizatioTable of Contents1. Introduction. 2. Interpolation Over a Triangle. 3. Derivatives of Interpolation Functions. 4. Linear Interpolation Over a Quadrilateral. 5. Derivatives for a Linear Displacement Quadrilateral. 6. Element Equilibrium and Stiffness. 7. Global Equilibrium and Global Stiffness. 8. Static Condensation and a 4CST Element. 9. Equation Solving. 10. Material Nonlinearity. 11. Time Integration. 12. Finite Element Seepage Formulation. 13. Hydro-mechanical Coupling. 14. Boundary Element Formulations. 15. Distinct Element Formulations. 16. Conclusion. Appendix A: Review of Fundamental Concepts. Appendix B: Study Questions. Appendix C: Question Replies.

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Book SynopsisThis book is an introduction to numerical analysis in geomechanics and is intended for advanced undergraduate and beginning graduate study of the mechanics of porous, jointed rocks and soils. Although familiarity with the concepts of stress, strain and so on is assumed, a review of the fundamentals of solid mechanics including concepts of physical laws, kinematics and material laws is presented in an appendix. Emphasis is on the popular finite element method but brief explanations of the boundary element method, the distinct element method (also known as the discrete element method) and discontinuous deformation analysis are included. Familiarity with a computer programming language such as Fortran, C++ or Python is not required, although programming excerpts in Fortran are presented at the end of some chapters.This work begins with an intuitive approach to interpolation over a triangular element and thus avoids making the simple complex by not doing energy minimizatioTable of Contents1. Introduction. 2. Interpolation Over a Triangle. 3. Derivatives of Interpolation Functions. 4. Linear Interpolation Over a Quadrilateral. 5. Derivatives for a Linear Displacement Quadrilateral. 6. Element Equilibrium and Stiffness. 7. Global Equilibrium and Global Stiffness. 8. Static Condensation and a 4CST Element. 9. Equation Solving. 10. Material Nonlinearity. 11. Time Integration. 12. Finite Element Seepage Formulation. 13. Hydro-mechanical Coupling. 14. Boundary Element Formulations. 15. Distinct Element Formulations. 16. Conclusion. Appendix A: Review of Fundamental Concepts. Appendix B: Study Questions. Appendix C: Question Replies.

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Book Synopsis"This is an excellent and well-written text on discrete event simulation with a focus on applications in Operations Research. Methods are provided for generating pseudo-random numbers (including combining such streams) and for generating random numbers from most standard statistical distributions."Trade ReviewFrom the reviews: "This is an excellent and well-written text on discrete event simulation with a focus on applications in Operations Research. There is substantial attention to programming, output analysis, pseudo-random number generation and modelling and these sections are quite thorough. Methods are provided for generating pseudo-random numbers (including combining such streams) and for generating random numbers from most standard statistical distributions." ISI Short Book Reviews, Vol. 22/2, August 2002 "This 537-page book is primarily a text to support the teaching of discrete-event simulation for post-graduates and final-year undergraduates. ... The book is a reasonably full, theory based, introduction to the technique of discrete-event simulation. Fishman’s earlier texts (1973 and 1978) established themselves as common points of reference and this book is likely to join them. It is worth considering as a course text or as a reference work for simulation users, and certainly as a worthwhile addition to relevant libraries." (B. Hollocks, Journal of the Operational Research Society, Vol. 54, 2003) "This book is a comprehensive text and reference for simulation of continuous-time processes that change state only at discrete, typically random, times. ... The coverage is substantial ... . there is considerable detail on simulating particular kinds of interevent distributions and reasonable attention to interpretation and statistical analysis of simulation output ... . The SIM-SCRIPT programming language is used to illustrate specific techniques." (Alan F. Karr, Journal of the American Statistical Association, December, 2002) "Besides the good choice of material of the book and its clear and excellent methodological presentation the referee has ... to stress on two points that distinguish Fishman’s book positive from others. One is that each chapter finishes with three subchapters – lessons learned, (interesting) exercises, and (actual and voluminous) references. The second one is that the book contains a multitude of accessible through the internet software sources. ... Fishman’s book can be highly recommended for practitioners as well as for students and simulation specialists." (P. Köchel, Operations Research-Spektrum, Issue 17, 2003) "This is an excellent and well-written text on discrete event simulation with a focus on applications in Operations Research. There is substantial attention to programming (largely in SIMSCRIPT II.5), output analysis, pseudo-random number generation and modelling and these sections are quite thorough. ... a text that is accessible, coherent and readable on those topics of major interest to ‘simulationists’ in the management and engineering sciences." (D. L. McLeish, Short Book Reviews, August, 2002) "This book covers the whole life cycle of the discrete-event simulation process ... . the author gives an excellent and complete introduction to all aspects related to discrete-event computer simulation. ... this book is highly recommendable either to be used as a text for a course on discrete-event simulation or as a reference for discrete-event simulation, as it provides a balance between theoretical and practical issues, including coding in different simulation languages and plentiful examples which are well developed throughout the book." (Juan de Lara Jaramillo, Journal of Artificial Societies and Social Simulation Vol. 5 (3), September, 2002) "Since students often learn about discrete-event simulation through particular software’s modelling, sampling, analysis and reporting capabilities, their skills for overcoming impediments may be severely limited unless they are well versed in the basic concepts of discrete-event simulation. ... This book supplies a mean for providing the needed background. It gives relatively detailed account of the principal methodologies of discrete-event simulation. ... At the end of nearly all chapters are exercises, which are well described." (Barbara Pototschnig, Simulation News Europe, Issue 34, 2002) "Once a simulation procedure is adopted, one must apply the simulation techniques interactively with the adaptation of the modelling techniques ... . In this context the book is a valuable basis for acquiring the necessary skills ... . The book is highly recommended as an introductory course for graduate and advanced undergraduate students in the mathematical and engineering sciences, particularly operations research, industrial engineering, operations management ... and to the professionals in these fields who are interested to broaden their knowledge of discrete-event simulation." (Mihail Voicu, Zentralblatt MATH, Vol. 973, 2001)Table of ContentsSimulation in Perspective * Modeling Concepts * Data Collection and Averages * Programming and Execution * Search, Space, and Time * Output Analysis * Making Sense of Output and Increasing Efficiency * Sampling from Probability Distributions * Pseudorandom Number Generation * Preparing the Input *

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Book SynopsisWritten in a rigorous yet logical and easy to use style, spanning a range of disciplines, including business, mathematics, finance and economics, this comprehensive textbook offers a systematic, self-sufficient yet concise presentation of the main topics and related parts of stochastic analysis and statistical finance that are covered in the majority of university programmes.Providing all explanations of basic concepts and results with proofs and numerous examples and problems, it includes: an introduction to probability theory a detailed study of discrete and continuous time market models a comprehensive review of Ito calculus and statistical methods as a basis for statistical estimation of models for pricing a detailed discussion of options and their pricing, including American options in a continuous time setting. An excellent introduction to the topic, this textbook is an essential resource for all stTrade Review"The book provides a systematic, self-sufficient, and yet short presentation of the main topics of mathematical finance. …The book is suitable for undergraduate and graduate courses in mathematics, statistics, finance, and economics. It also provides fundamentals for further research and study in these fields."—Pavel Stoynov, Zentralblatt MATH 1173Table of Contents1. Review of Probability Theory 2. Basics of Stochastic Theory 3. Discrete Time Market Models 4. Basics of Ito Calculus and Stochastic Analysis 5. Continuous Time Market Models 6. American Options and Binomial Trees 7. Implied and Historical Volatility 8. Review of Statistical Estimation 9. Estimation of Models for Stock Prices

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Book SynopsisFirst published in 1967, this book explores the theme of geographical generalization, or model building. It is composed of five of the chapters from the original Models in Geography, published in 1967. The first chapter broadly outlines this theme and examines the nature and function of generalized statements, ranging from conceptual models to scale models, in a geographical context. The following chapters deal with mixed-system model building in geography, wherein data, techniques and concepts in both physical and human geography are integrated. The book contains chapters on organisms and ecosystems as geographical models as well as spatial patterns in human geography.This text represents a robustly anti-idiographic statement of modern work in one of the major branches of geography.Table of Contents1. Models, Paradigms and the New Geography 12. Regions, Models and Classes 13. Organism and Ecosystem as Geographical Models 14. Models of the Evolution of Spatial Patterns in Human Geography 15. Network Models in Geography; Index

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Book SynopsisFirst published in 1967, this book explores the theme of geographical generalization, or model building. It is composed of five of the chapters from the original Models in Geography, published in 1967. The first chapter broadly outlines this theme and examines the nature and function of generalized statements, ranging from conceptual models to scale models, in a geographical context. The following chapters deal with mixed-system model building in geography, wherein data, techniques and concepts in both physical and human geography are integrated. The book contains chapters on organisms and ecosystems as geographical models as well as spatial patterns in human geography.This text represents a robustly anti-idiographic statement of modern work in one of the major branches of geography.Table of Contents1. Models, Paradigms and the New Geography 12. Regions, Models and Classes 13. Organism and Ecosystem as Geographical Models 14. Models of the Evolution of Spatial Patterns in Human Geography 15. Network Models in Geography; Index

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Book SynopsisFirst published in 1967, this book explores the theme of geographical generalization, or model building. It is composed of eight of the chapters from the original Models in Geography, published in 1967. The first chapter broadly outlines geographical generalization and examines the nature and function of generalized statements, ranging from conceptual models to scale models, in a geographical context. The following chapter deals with model theory in a wider scientific framework and the rest of the book discusses models of physical systems and information models. The book considers model-type generalizations that are applied in the three fields of geomorphology, meteorology and climatology, and hydrology before focusing on the transference of information and ideas in geography. This text represents a robustly anti-idiographic statement of modern work in one of the major branches of geography.Table of ContentsAcnowledgements; 1. Models, Paradigms and the New Geography 2. The Use of Models in Science 3. Models in Geomorphology 4. Models in Meteorology and Climatology 5. Hydrological Models and Geography 16. Maps as Models 17. Hardware Models in Geography 18. Models of Geographical Teaching; Index

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Book SynopsisFirst published in 1967, this book explores the theme of geographical generalization, or model building. It is composed of eight of the chapters from the original Models in Geography, published in 1967. The first chapter broadly outlines geographical generalization and examines the nature and function of generalized statements, ranging from conceptual models to scale models, in a geographical context. The following chapter deals with model theory in a wider scientific framework and the rest of the book discusses models of physical systems and information models. The book considers model-type generalizations that are applied in the three fields of geomorphology, meteorology and climatology, and hydrology before focusing on the transference of information and ideas in geography. This text represents a robustly anti-idiographic statement of modern work in one of the major branches of geography.Table of ContentsAcnowledgements; 1. Models, Paradigms and the New Geography 2. The Use of Models in Science 3. Models in Geomorphology 4. Models in Meteorology and Climatology 5. Hydrological Models and Geography 16. Maps as Models 17. Hardware Models in Geography 18. Models of Geographical Teaching; Index

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Book SynopsisFirst published in 1970, this groundbreaking investigation into Entropy in Urban and Regional Modelling provides an extensive and detailed insight into the entropy maximising method in the development of a whole class of urban and regional models.The book has its origins in work being carried out by the author in 1966, when he realised that the well-known gravity model could be derived on the basis of an analogy with statistical, rather than Newtonian, mechanics. Subsequent investigation demonstrated that the entropy maximising method stems from an even higher level of generality, and the beginning of the book is devoted to an account of its importance and use as a general modelling tool.This reissue will be welcomed by a range of students and professionals from fields as diverse as urban and regional studies, economics, geography, planning, civil engineering, mathematics and statistics.Table of Contents1. What is Entropy? 2. Transport Models: The Theory of Trip Distribution, Mode Split and Route Split 3. Interrogational Commodity Flows 4. Location Models 5. Problems of Missing or Additional Information in Flow or Location Models 6. The Use of Entropy in the Analysis of Utility-Maximising Systems 7. Entropy, Social Physics and General Systems Theory 8. Some Conclusions

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Book SynopsisCovers a wide range of topics within mathematical modelling and the optimization of economic, demographic, technological and environmental phenomena. This book uses mathematical models and optimization methods to describe age-structured populations in economy, demography, technological change, and the environment.Table of Contents1. The genuine savings criterion and the value of population in an economy with endogenous fertility rate Kenneth J. Arrow, Alain Bensoussan, Qi Feng, and Suresh P. Sethi 2. Continuous time overlapping generations models Hippolyte d'Albis and Emmanuelle Augeraud-Véron 3. Modeling technological change in equipment replacement problems Chin Hon Tan and Joseph C. Hartman 4. Embodied technology adoption under uncertainty Bruno Cruz and Aude Pommeret 5. Viability, optimality, and sustainability in vintage models Noël Bonneuil 6. Embodied technical change and learning-by-doing in a two sector growth model with human capital accumulation Alberto Bucci, Herb Kunze and Davide La Torre 7. Age-structured optimization models in fisheries bioeconomics: a survey Olli Tahvonen 8. Age-structured models and optimal control in mathematical epidemiology: a survey David Greenhalgh 9. Optimal management of a size distributed forest with respect to timber and non-timber values Renan-Ulrich Goertz and Angels Xabadia 10. Optimal harvesting in a two-species model of size-structured population Nobuyuki Kato 11. Optimisation problems in the management of indigenous plant populations under grazing pressure Lynne McArthur, John Boland, and Fleur Tiver 12. Identification of age-structured contamination sources in ground water Sergey Lyashko, Dmitry Klyushin, Dmitry Nomirovsky, and Vladimir Semenov

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Book SynopsisThe safeguarding of children and young people participating in sport has become an increasingly prominent concern in policy-making and research communities around the world. Major organisations such as the IOC and UNICEF now officially recognize that children in sport can be at risk of exploitation and abuse, and this concern has led to the emergence of new initiatives and policies aimed at protecting vulnerable young people and athletes. This book is the first to comprehensively review contemporary developments in child protection and safeguarding in sport on a global level. The book is divided into two parts. Part One critically analyses current child protection and safeguarding policy and practice in sport across a range of countries, including the US, Canada, the UK, Australia, China and Germany, providing a global context for current policy and practice. This represents the most comprehensive review to date of the landscape of child protection and safeguarding in sport aTrade Review‘This is refreshing reading! In some parts of the sports movement is the new ideas already in the works. Swedish innebandys education model, SIU, is an example of that. But much remains to be done. The current anthology can be a good starting point for further discussions on how to do it.’- Lars H Gustafsson (2015) ‘Time to leave shelters perspective of a proactive, child rights oriented approach’, idrottsforum.orgTable of ContentsIntroduction: What is Safeguarding in Sport? PART 1 Chapter 1. Safeguarding and Child Protection in Sport in England Chapter 2. Safeguarding Children and Young People in Danish Sport Chapter 3. Preventing Child Maltreatment and Trangressive Behaviour in Flemish Sport Chapter 4. (Sexual) Intimidation in Sport: The Netherlands Chapter 5. Child Protection in German Sport Chapter 6. Safeguarding and Child Protection in Sport in Two Southern European Countries: Greece and the Republic of Cyprus Chapter 7. Child Protection and Welfare in Spanish Sport Chapter 8. Safeguarding Children from Violence and Abuse in Slovenian Sport Chapter 9. Protecting Children from Abuse and Exploitation in South African Sports Chapter 10. Athlete Welfare and Protection Policy Development in the USA Chapter 11. Athlete Welfare and Safeguarding in Sport in Canada Chapter 12. Child Safety and Wellbeing in Australian Sport Chapter 13. The Protection of Young Athletes in China: Policy and Practice Chapter 14. Who Safeguards the Child in Japanese Sports? PART 2 Chapter 15. Safeguarding Athletes from Emotional Abuse Chapter 16. Safeguarding the Welfare of Disabled People in Sport: Some Policy Issues and Considerations Chapter 17. Physical Training as a Potential Form of Abuse Chapter 18. Safeguarding, Injuries and Athlete Choice Chapter 19. Evaluation in Safeguarding and Child Protection in Sport Chapter 20. Conclusion

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Book SynopsisThis book demonstrates how to conduct latent variable modeling (LVM) in R by highlighting the features of each model, their specialized uses, examples, sample code and output, and an interpretation of the results. Each chapter features a detailed example including the analysis of the data using R, the relevant theory, the assumptions underlying the model, and other statistical details to help readers better understand the models and interpret the results. Every R command necessary for conducting the analyses is described along with the resulting output which provides readers with a template to follow when they apply the methods to their own data. The basic information pertinent to each model, the newest developments in these areas, and the relevant R code to use them are reviewed. Each chapter also features an introduction, summary, and suggested readings. A glossary of the text's boldfaced key terms and key R commands serve as helpful resources. The book is accompanied by a websiteTrade Review"Finch and French provide a timely, accessible, and integrated resource on using R to fit a broad range of latent variable models. It will be a valuable reference for researchers as well as students taking SEM, IRT, Factor Analysis, or Mixture Modeling courses. Coverage of simulation methods and advanced topics in IRT and SEM are particular assets." – Sonya Sterba, Vanderbilt University, USA"With this highly accessible, easy-to-follow, step-by-step guide for analyzing both simple and complex latent variable models in the increasingly popular R software program, Finch and French provide an extremely valuable service to researchers in various fields." – Christian Geiser, Utah State University, USA"A major characteristic of this book is the user-friendly presentation of content and easy to follow examples. It provides excellent instruction to gain basic proficiency in the methods and reaches a large audience." – Karl Schweizer, Goethe University, Germany"The book integrates technical details and examples in a way that is friendly to beginner users of structural equation modeling and item response theory, and helps readers assimilate the concepts and transfer to their own research needs." – Walter L. Leite, University of Florida, USA"A cohesive and accessible resource for applying the R language to analyze data in a latent variable framework. ... I found what was written to be easy to understand. ... I would use it, recommend it to others, and likely adopt it as a supplemental text." – Natalie D. Eggum, Arizona State University, USA"This book is truly unique. ...The writing style is clear and comprehensible. ... [It] will ... serve as a ... supplementary text in ... measurement, latent variable modeling, and IRT classes." – D. Betsy McCoach, University of Connecticut, USA"This ... book covers all the latent variable models commonly used in social sciences. ... [It] can be used as a text ... for ... courses ... in ... structural equation modelling, psychological measurement, item response theory, and mixture model or latent class analysis. ... [It] makes a significant contribution to the field. ... I will use [it] as a supplement ... and recommend it to my colleagues who ... teach Psychological Measurement and Item Response Theory."- Ke-Hai Yuan, University of Notre Dame, USA"The topic has the potential ... to be of broad interest in social, prevention, and public health sciences. ... [It] could be of great interest to ... my students in courses on latent variable modeling." – Patrick S. Malone, University of South Carolina, USATable of Contents1. Introduction to basic data handling in R 2. Exploratory Factor analysis 3. Confirmatory Factor analysis 4. Foundations of Structural Equation Modeling (SEM) 5. SEM for multiple groups, the MIMIC model, and latent means comparisons 6. Further Topics in SEM 7. Growth Curve Modeling 8. Mixture models 9. Item Response Theory for dichotomous and polytomous items 10. Further topics in Item Response Theory 11. Data simulation for latent variable modeling in R Appendix A. Key R Commands

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Book SynopsisThis book demonstrates how to conduct latent variable modeling (LVM) in R by highlighting the features of each model, their specialized uses, examples, sample code and output, and an interpretation of the results. Each chapter features a detailed example including the analysis of the data using R, the relevant theory, the assumptions underlying the model, and other statistical details to help readers better understand the models and interpret the results. Every R command necessary for conducting the analyses is described along with the resulting output which provides readers with a template to follow when they apply the methods to their own data. The basic information pertinent to each model, the newest developments in these areas, and the relevant R code to use them are reviewed. Each chapter also features an introduction, summary, and suggested readings. A glossary of the textâs boldfaced key terms and key R commands serve as helpful resources. The book is accompanied by a websiteTrade Review"Finch and French provide a timely, accessible, and integrated resource on using R to fit a broad range of latent variable models. It will be a valuable reference for researchers as well as students taking SEM, IRT, Factor Analysis, or Mixture Modeling courses. Coverage of simulation methods and advanced topics in IRT and SEM are particular assets." – Sonya Sterba, Vanderbilt University, USA"With this highly accessible, easy-to-follow, step-by-step guide for analyzing both simple and complex latent variable models in the increasingly popular R software program, Finch and French provide an extremely valuable service to researchers in various fields." – Christian Geiser, Utah State University, USA"A major characteristic of this book is the user-friendly presentation of content and easy to follow examples. It provides excellent instruction to gain basic proficiency in the methods and reaches a large audience." – Karl Schweizer, Goethe University, Germany"The book integrates technical details and examples in a way that is friendly to beginner users of structural equation modeling and item response theory, and helps readers assimilate the concepts and transfer to their own research needs." – Walter L. Leite, University of Florida, USA"A cohesive and accessible resource for applying the R language to analyze data in a latent variable framework. ... I found what was written to be easy to understand. ... I would use it, recommend it to others, and likely adopt it as a supplemental text." – Natalie D. Eggum, Arizona State University, USA"This book is truly unique. ...The writing style is clear and comprehensible. ... [It] will ... serve as a ... supplementary text in ... measurement, latent variable modeling, and IRT classes." – D. Betsy McCoach, University of Connecticut, USA"This ... book covers all the latent variable models commonly used in social sciences. ... [It] can be used as a text ... for ... courses ... in ... structural equation modelling, psychological measurement, item response theory, and mixture model or latent class analysis. ... [It] makes a significant contribution to the field. ... I will use [it] as a supplement ... and recommend it to my colleagues who ... teach Psychological Measurement and Item Response Theory."- Ke-Hai Yuan, University of Notre Dame, USA"The topic has the potential ... to be of broad interest in social, prevention, and public health sciences. ... [It] could be of great interest to ... my students in courses on latent variable modeling." – Patrick S. Malone, University of South Carolina, USATable of Contents1. Introduction to basic data handling in R 2. Exploratory Factor analysis 3. Confirmatory Factor analysis 4. Foundations of Structural Equation Modeling (SEM) 5. SEM for multiple groups, the MIMIC model, and latent means comparisons 6. Further Topics in SEM 7. Growth Curve Modeling 8. Mixture models 9. Item Response Theory for dichotomous and polytomous items 10. Further topics in Item Response Theory 11. Data simulation for latent variable modeling in R Appendix A. Key R Commands

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Book SynopsisThis book covers a wide range of topics within mathematical modelling and the optimization of economic, demographic, technological and environmental phenomena. Each chapter is written by experts in their field and represents new advances in modelling theory and practice. These essays are exemplary of the fruitful interaction between theory and practice when exploring global and local changes. The unifying theme of the book is the use of mathematical models and optimization methods to describe age-structured populations in economy, demography, technological change, and the environment. Emphasis is placed on deterministic dynamic models that take age or size structures, delay effects, and non-standard decision variables into account. In addition, the contributions deal with the age structure of assets, resources, and populations under study. Interdisciplinary modelling has enormous potential for discovering new insights in global and regional development. <Table of Contents1. The genuine savings criterion and the value of population in an economy with endogenous fertility rate Kenneth J. Arrow, Alain Bensoussan, Qi Feng, and Suresh P. Sethi 2. Continuous time overlapping generations models Hippolyte d'Albis and Emmanuelle Augeraud-Véron 3. Modeling technological change in equipment replacement problems Chin Hon Tan and Joseph C. Hartman 4. Embodied technology adoption under uncertainty Bruno Cruz and Aude Pommeret 5. Viability, optimality, and sustainability in vintage models Noël Bonneuil 6. Embodied technical change and learning-by-doing in a two sector growth model with human capital accumulation Alberto Bucci, Herb Kunze and Davide La Torre 7. Age-structured optimization models in fisheries bioeconomics: a survey Olli Tahvonen 8. Age-structured models and optimal control in mathematical epidemiology: a survey David Greenhalgh 9. Optimal management of a size distributed forest with respect to timber and non-timber values Renan-Ulrich Goertz and Angels Xabadia 10. Optimal harvesting in a two-species model of size-structured population Nobuyuki Kato 11. Optimisation problems in the management of indigenous plant populations under grazing pressure Lynne McArthur, John Boland, and Fleur Tiver 12. Identification of age-structured contamination sources in ground water Sergey Lyashko, Dmitry Klyushin, Dmitry Nomirovsky, and Vladimir Semenov

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