Resistivity and induced polarization methods are used for a wide range of near-surface applications, including hydrogeology, civil engineering and archaeology, as well as emerging applications in the agricultural and plant sciences. This comprehensive reference text covers both theory and practice of resistivity and induced polarization methods, demonstrating how to measure, model and interpret data in both the laboratory and the field. Marking the 100 year anniversary of the seminal work of Conrad Schlumberger (1920), the book covers historical development of electrical geophysics, electrical properties of geological materials, instrumentation, acquisition and modelling, and includes case studies that capture applications to societally relevant problems. The book is also supported by a full suite of forward and inverse modelling tools, allowing the reader to apply the techniques to a wide range of applications using digital datasets provided online. This is a valuable reference for graduate students, researchers and practitioners interested in near-surface geophysics.

This textbook is concerned with the mathematical modeling of biological and physiological phenomena for mathematically sophisticated students. A range of topics are discussed: diffusion population dynamics, autonomous differential equations and the stability of ecosystems, biogeography, pharmokinetics, biofluid mechanics, cardiac mechanics, the spectral analysis of heart sounds using FFT techniques. The last chapter deals with a wide variety of commonly used medical devices. This edition includes new chapters on epidemiology, including modeling the spread of AIDS through a population. Coverage is based on courses taught by the author over many years and the material is class tested. The reader is aided by many exercises that examine key points and extend the presentation in the body of the text. All students of mathematical biology will find this book to be a highly useful resource.

Cloud research is a rapidly developing branch of climate science that's vital to climate modelling. With new observational and simulation technologies our knowledge of clouds and their role in the warming climate is accelerating. This book provides a comprehensive overview of research on clouds and their role in our present and future climate, covering theoretical, observational, and modelling perspectives. Part I discusses clouds from three different perspectives: as particles, light and fluid. Part II describes our capability to model clouds, ranging from theoretical conceptual models to applied parameterised representations. Part III describes the interaction of clouds with the large-scale circulation in the tropics, mid-latitudes, and polar regions. Part IV describes how clouds are perturbed by aerosols, the land-surface, and global warming. Each chapter contains end-of-chapter exercises and further reading sections, making this an ideal resource for advanced students and researchers in climatology, atmospheric science, meteorology, and climate change.

This book reports on advanced theories and methods in three related fields of research: applied physics, system science and computers. The first part covers applied physics topics, such as lasers and accelerators; fluid dynamics, optics and spectroscopy, among others. It also addresses astrophysics, security, and medical and biological physics. The second part focuses on advances in computers, such as those in the area of social networks, games, internet of things, deep learning models and more. The third part is especially related to systems science, covering swarm intelligence, smart cities, complexity and more. Advances in and application of computer communication, artificial intelligence, data analysis, simulation and modeling are also addressed. The book offers a collection of contributions presented at the 3nd International Conference on Applied Physics, System Science and Computers (APSAC), held in Dubrovnik, Croatia on September 26-28, 2018. Besides presenting new methods, it is also intended to promote collaborations between different communities working on related topics at the interface between physics, computer science and engineering.

Continuous-system simulation is an increasingly important tool for optimizing the performance of real-world systems. The book presents an integrated treatment of continuous simulation with all the background and essential prerequisites in one setting. It features updated chapters and two new sections on Black Swan and the Stochastic Information Packet (SIP) and Stochastic Library Units with Relationships Preserved (SLURP) Standard. The new edition includes basic concepts, mathematical tools, and the common principles of various simulation models for different phenomena, as well as an abundance of case studies, real-world examples, homework problems, and equations to develop a practical understanding of concepts.

This book discusses statistical modeling of single- and multi-channel synthetic aperture radar (SAR) images and the applications of these newly developed models in land and ocean monitoring, such as target detection and terrain classification. It is a valuable reference for researchers and engineers interested in information processing of remote sensing, radar signal processing, and image interpretation.

Cardiovascular diseases have a major impact in Western countries. Mathematical models and numerical simulations can help the understanding of physiological and pathological processes, complementing the information provided to medical doctors by medical imaging and other non-invasive means, and opening the possibility of a better diagnosis and more in-depth surgical planning. This book offers a mathematical update of the state of the art of the research in the field, and serves as a useful reference for the development of mathematical models and numerical simulation codes. It is structured into different chapters, written by outstanding experts in the field. Many fundamental issues are considered, such as: the mathematical representation of vascular geometries extracted from medical images, modelling blood rheology and the complex multilayer structure of the vascular tissue, and its possible pathologies, the mechanical and chemical interaction between blood and vascular walls; the different scales coupling local and systemic dynamics. All of these topics introduce challenging mathematical and numerical problems, demanding for advanced analysis and efficient simulation techniques. This book is addressed to graduate students and researchers in the field of bioengineering, applied mathematics and medicine, wishing to engage themselves in the fascinating task of modeling the cardiovascular system or, more broadly, physiological flows

This book provides a concise introduction to continuum mechanics, with a particular emphasis on fluid dynamics, suitable for upper undergraduate students in applied mathematics and related subjects. Starting with a preliminary chapter on tensors, the main topic of the book begins in earnest with the chapters on continuum kinematics and dynamics. Following chapters cover linear elasticity and both incompressible and compressible fluids. Special topics of note include nonlinear acoustics and the theory of motion of viscous thermal conducting compressible fluids. Based on an undergraduate course taught for over a decade, this textbook assumes only familiarity with multivariate calculus and linear algebra. It includes many exercises with solutions and can serve as textbook for lecture courses at the undergraduate and masters level.

This 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.

The principles of game theory apply to a wide range of topics in biology. This book presents the central concepts in evolutionary game theory and provides an authoritative and up-to-date account. The focus is on concepts that are important for biologists in their attempts to explain observations. This strong connection between concepts and applications is a recurrent theme throughout the book which incorporates recent and traditional ideas from animal psychology, neuroscience, and machine learning that provide a mechanistic basis for behaviours shown by players of a game. The approaches taken to modelling games often rest on idealized and unrealistic assumptions whose limitations and consequences are not always appreciated. The authors provide a novel reassessment of the field, highlighting how to overcome limitations and identifying future directions. Game Theory in Biology is an advanced textbook suitable for graduate level students as well as professional researchers (both empiricists and theoreticians) in the fields of behavioural ecology and evolutionary biology. It will also be of relevance to a broader interdisciplinary audience including psychologists and neuroscientists.

This book gathers the peer-reviewed proceedings of the 15th Annual Meeting of the Bulgarian Section of the Society for Industrial and Applied Mathematics, BGSIAM'20, held in Sofia, Bulgaria. The general theme of BGSIAM'20 was industrial and applied mathematics with particular focus on mathematical physics, numerical analysis, high-performance computing, optimization and control, mathematical biology, stochastic modeling, machine learning, digitization and imaging, advanced computing in environmental, and biomedical and engineering applications.

Fixed Income Modelling offers a unified presentation of dynamic term structure models and their applications to the pricing and risk management of fixed income securities. It explains the basic fixed income securities and their properties and uses as well as the relations between those securities. The book presents and compares the classical affine models, Heath-Jarrow-Morton models, and LIBOR market models, and demonstrates how to apply those models for the pricing of various widely traded fixed income securities. It offers a balanced presentation with both formal mathematical modelling and economic intuition and understanding.
The book has a number of distinctive features including a thorough and accessible introduction to stochastic processes and the stochastic calculus needed for the modern financial modelling approach used in the book, as well as a separate chapter that explains how the term structure of interest rates relates to macro-economic variables and to what extent the concrete interest rate models are founded in general economic theory. The book focuses on the most widely used models and the main fixed income securities, instead of trying to cover all the many specialized models and the countless exotic real-life products. The in-depth explanation of the main pricing principles, techniques, and models as well as their application to the most important types of securities will enable the reader to understand and apply other models and price other securities. The book includes chapters on interest rate risk management, credit risk, mortgage-backed securities, and relevant numerical techniques. Each chapter concludes with a number of exercises of varying complexity.
Suitable for MSc students specializing in finance and economics, quantitatively oriented MBA students, and first- or second-year PhD students, this book will also be a useful reference for researchers and finance professionals and can be used in specialized courses on fixed income or broader courses on derivatives.

This self-contained book systematically explores the statistical dynamics on and of complex networks with a special focus on time-varying networks. In the constantly changing modern world, there is an urgent need to understand problems related to systems that dynamically evolve in either structure or function, or both. This work is an attempt to address such problems in the framework of complex networks. Dynamics on and of Complex Networks, Volume 2: Applications to Time-Varying Dynamical Systems is a collection of surveys and cutting-edge research contributions exploring key issues, challenges, and characteristics of dynamical networks that emerge in various complex systems. Toward this goal, the work is thematically organized into three main sections with the primary thrust on time-varying networks: Part I studies social dynamics; Part II focuses on community identification; and Part III illustrates diffusion processes. The contributed chapters in this volume are intended to promote cross-fertilization in several research areas and will be valuable to newcomers in the field, experienced researchers, practitioners, and graduate students interested in pursuing research in dynamical networks with applications to computer science, statistical physics, nonlinear dynamics, linguistics, and the social sciences. This volume follows Dynamics On and Of Complex Networks: Applications to Biology, Computer Science, and the Social Sciences (2009), ISBN 978-0-8176-4750-6.

This hands-on introduction to numerical geodynamic modelling provides a solid grounding in the necessary mathematical theory and techniques, including continuum mechanics and partial differential equations, before introducing key numerical modelling methods and applications. Fully updated, this second edition includes four completely new chapters covering the most recent advances in modelling inertial processes, seismic cycles and fluid-solid interactions, and the development of adaptive mesh refinement algorithms. Many well-documented, state-of-the-art visco-elasto-plastic 2D models are presented, which allow robust modelling of key geodynamic processes. Requiring only minimal prerequisite mathematical training, and featuring over sixty practical exercises and ninety MATLAB (R) examples, this user-friendly resource encourages experimentation with geodynamic models. It is an ideal introduction for advanced courses and can be used as a self-study aid for graduates seeking to master geodynamic modelling for their own research projects.

This edited monograph collects research contributions and addresses the advancement of efficient numerical procedures in the area of model order reduction (MOR) for simulation, optimization and control. The topical scope includes, but is not limited to, new out-of-the-box algorithmic solutions for scientific computing, e.g. reduced basis methods for industrial problems and MOR approaches for electrochemical processes. The target audience comprises research experts and practitioners in the field of simulation, optimization and control, but the book may also be beneficial for graduate students alike.

Model theory begins with an audacious idea: to consider statements about mathematical structures as mathematical objects of study in their own right. While inherently important as a tool of mathematical logic, it also enjoys connections to and applications in diverse branches of mathematics, including algebra, number theory and analysis. Despite this, traditional introductions to model theory assume a graduate-level background of the reader. In this innovative textbook, Jonathan Kirby brings model theory to an undergraduate audience. The highlights of basic model theory are illustrated through examples from specific structures familiar from undergraduate mathematics, paying particular attention to definable sets throughout. With numerous exercises of varying difficulty, this is an accessible introduction to model theory and its place in mathematics.

Multiple criteria decision aid (MCDA) methods are illustrated in this book through theoretical and computational techniques utilizing Python. Existing methods are presented in detail with a step by step learning approach. Theoretical background is given for TOPSIS, VIKOR, PROMETHEE, SIR, AHP, goal programming, and their variations. Comprehensive numerical examples are also discussed for each method in conjunction with easy to follow Python code. Extensions to multiple criteria decision making algorithms such as fuzzy number theory and group decision making are introduced and implemented through Python as well. Readers will learn how to implement and use each method based on the problem, the available data, the stakeholders involved, and the various requirements needed. Focusing on the practical aspects of the multiple criteria decision making methodologies, this book is designed for researchers, practitioners and advanced graduate students in the applied mathematics, information systems, operations research and business administration disciplines, as well as other engineers and scientists oriented in interdisciplinary research. Readers will greatly benefit from this book by learning and applying various MCDM/A methods. (Adiel Teixeira de Almeida, CDSID-Center for Decision System and Information Development, Universidade Federal de Pernambuco, Recife, Brazil) Promoting the development and application of multicriteria decision aid is essential to ensure more ethical and sustainable decisions. This book is a great contribution to this objective. It is a perfect blend of theory and practice, providing potential users and researchers with the theoretical bases of some of the best-known methods as well as with the computing tools needed to practice, to compare and to put these methods to use. (Jean-Pierre Brans, Vrije Universiteit Brussel, Brussels, Belgium) This book is intended for researchers, practitioners and students alike in decision support who wish to familiarize themselves quickly and efficiently with multicriteria decision aiding algorithms. The proposed approach is original, as it presents a selection of methods from the theory to the practical implementation in Python, including a detailed example. This will certainly facilitate the learning of these techniques, and contribute to their effective dissemination in applications. (Patrick Meyer, IMT Atlantique, Lab-STICC, Univ. Bretagne Loire, Brest, France)

The subject of these notes is counting and related topics, viewed from a computational perspective. A major theme of the book is the idea of accumulating information about a set of combinatorial structures by performing a random walk on those structures. These notes will be of value not only to teachers of postgraduate courses on these topics, but also to established researchers. For the first time this body of knowledge has been brought together in a single volume.

The idea of forecasting the weather by calculation was first dreamt of by Lewis Fry Richardson. The first edition of this book, published in 1922, set out a detailed algorithm for systematic numerical weather prediction. The method of computing atmospheric changes, which he mapped out in great detail in this book, is essentially the method used today. He was greatly ahead of his time because, before his ideas could bear fruit, advances in four critical areas were needed: better understanding of the dynamics of the atmosphere; stable computational algorithms to integrate the equations; regular observations of the free atmosphere; and powerful automatic computer equipment. Over the ensuing years, progress in numerical weather prediction has been dramatic. Weather prediction and climate modelling have now reached a high level of sophistication, and are witness to the influence of Richardson's ideas. This edition contains a new foreword by Peter Lynch that sets the original book in context.

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.

When predictions of Einstein's theory of General Relativity are compared against observations of our Universe, a huge inconsistency is found. The most popular fix for this inconsistency is to "invent" around 94% of the content of the universe: dark matter and dark energy. The dark energy is some exotic substance responsible for the apparent observed acceleration of the Universe. Another fix is to modify the theory of gravity: it is entirely plausible that Einstein's theory of General Relativity breaks down on cosmological scales, just as Newton's theory of gravity breaks down in the extreme gravitational field of the Sun. There are many alternative theories of gravity, each with the aim of describing observations of our Universe where General Relativity fails. Whether it is dark energy or some modified theory of gravity, it is clear that there is some "dark sector" in the Universe. In this thesis the author constructs a unifying framework for understanding the observational impact of general classes of dark sector theories, by formulating equations of state for the dark sector perturbations.

Many physical problems that are usually solved by differential equation methods can be solved more effectively by integral equation methods. Such problems abound in applied mathematics, theoretical mechanics, and mathematical physics. This uncorrected soft cover reprint of the second edition places the emphasis on applications and presents a variety of techniques with extensive examples.Originally published in 1971, Linear Integral Equations is ideal as a text for a beginning graduate level course. Its treatment of boundary value problems also makes the book useful to researchers in many applied fields.

This SpringerBrief focuses on modeling and power evaluation of high-speed craft. The various power prediction methods, a principal design objective for high-speed craft of displacement, semi-displacement, and planing type, are addressed. At the core of the power prediction methods are mathematical models for resistance and propulsion efficiency. The models are based on the experimental data of various high-speed hull and propeller series. The regression analysis and artificial neural network (ANN) methods are used as an extraction tool for this kind of mathematical models. A variety of mathematical models of this type are discussed in the book. Once these mathematical models have been developed and validated, they can be readily programmed into software tools, thereby enabling the parametric analyses required for the optimization of a high-speed craft design. This book provides the foundational reference for these software tools, and their use in the design of high-speed craft. High-speed craft are very different from conventional ships. Current professional literature leaves a gap in the documentation of best design practices for high-speed craft. This book is aimed at naval architects who design and develop various types of high-speed vessels.

Partition functions arise in combinatorics and related problems of statistical physics as they encode in a succinct way the combinatorial structure of complicated systems. The main focus of the book is on efficient ways to compute (approximate) various partition functions, such as permanents, hafnians and their higher-dimensional versions, graph and hypergraph matching polynomials, the independence polynomial of a graph and partition functions enumerating 0-1 and integer points in polyhedra, which allows one to make algorithmic advances in otherwise intractable problems. The book unifies various, often quite recent, results scattered in the literature, concentrating on the three main approaches: scaling, interpolation and correlation decay. The prerequisites include moderate amounts of real and complex analysis and linear algebra, making the book accessible to advanced math and physics undergraduates.

This volume provides a comprehensive introduction to the modern theory of differential-operator and kinetic models including Vlasov-Maxwell, Fredholm, Lyapunov-Schmidt branching equations to name a few. This book will bridge the gap in the considerable body of existing academic literature on the analytical methods used in studies of complex behavior of differential-operator equations and kinetic models. This monograph will be of interest to mathematicians, physicists and engineers interested in the theory of such non-standard systems.