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Modeling Infectious Diseases in Humans and Animals
by Pejman Rohani Matt J. KeelingFor epidemiologists, evolutionary biologists, and health-care professionals, real-time and predictive modeling of infectious disease is of growing importance. This book provides a timely and comprehensive introduction to the modeling of infectious diseases in humans and animals, focusing on recent developments as well as more traditional approaches.Matt Keeling and Pejman Rohani move from modeling with simple differential equations to more recent, complex models, where spatial structure, seasonal "forcing," or stochasticity influence the dynamics, and where computer simulation needs to be used to generate theory. In each of the eight chapters, they deal with a specific modeling approach or set of techniques designed to capture a particular biological factor. They illustrate the methodology used with examples from recent research literature on human and infectious disease modeling, showing how such techniques can be used in practice. Diseases considered include BSE, foot-and-mouth, HIV, measles, rubella, smallpox, and West Nile virus, among others. Particular attention is given throughout the book to the development of practical models, useful both as predictive tools and as a means to understand fundamental epidemiological processes. To emphasize this approach, the last chapter is dedicated to modeling and understanding the control of diseases through vaccination, quarantine, or culling.Comprehensive, practical introduction to infectious disease modelingBuilds from simple to complex predictive modelsModels and methodology fully supported by examples drawn from research literaturePractical models aid students' understanding of fundamental epidemiological processesFor many of the models presented, the authors provide accompanying programs written in Java, C, Fortran, and MATLABIn-depth treatment of role of modeling in understanding disease control
Modeling Information Diffusion in Online Social Networks with Partial Differential Equations (Surveys and Tutorials in the Applied Mathematical Sciences #7)
by Feng Wang Haiyan Wang Kuai XuThe book lies at the interface of mathematics, social media analysis, and data science. Its authors aim to introduce a new dynamic modeling approach to the use of partial differential equations for describing information diffusion over online social networks. The eigenvalues and eigenvectors of the Laplacian matrix for the underlying social network are used to find communities (clusters) of online users. Once these clusters are embedded in a Euclidean space, the mathematical models, which are reaction-diffusion equations, are developed based on intuitive social distances between clusters within the Euclidean space. The models are validated with data from major social media such as Twitter. In addition, mathematical analysis of these models is applied, revealing insights into information flow on social media. Two applications with geocoded Twitter data are included in the book: one describing the social movement in Twitter during the Egyptian revolution in 2011 and another predicting influenza prevalence. The new approach advocates a paradigm shift for modeling information diffusion in online social networks and lays the theoretical groundwork for many spatio-temporal modeling problems in the big-data era.
Modeling MEMS and NEMS
by John A. Pelesko David H. BernsteinDesigning small structures necessitates an a priori understanding of various device behaviors. The way to gain such understanding is to construct, analyze, and interpret the proper mathematical model.Through such models, Modeling MEMS and NEMS illuminates microscale and nanoscale phenomena, thereby facilitating the design and optimization o
Modeling Methods for Marine Science
by David M. Glover William J. Jenkins Scott C. DoneyThis advanced textbook on modeling, data analysis and numerical techniques for marine science has been developed from a course taught by the authors for many years at the Woods Hole Oceanographic Institute. The first part covers statistics: singular value decomposition, error propagation, least squares regression, principal component analysis, time series analysis and objective interpolation. The second part deals with modeling techniques: finite differences, stability analysis and optimization. The third part describes case studies of actual ocean models of ever increasing dimensionality and complexity, starting with zero-dimensional models and finishing with three-dimensional general circulation models. Throughout the book the general principles and goals of scientific visualization are emphasized through technique and application. Ideal as a textbook for advanced students of oceanography on courses in data analysis and numerical modeling, the book is also an invaluable resource for a broad range of scientists undertaking modeling in chemical, biological, geological and physical oceanography.
Modeling Methods for Medical Systems Biology: Regulatory Dynamics Underlying the Emergence of Disease Processes (Advances in Experimental Medicine and Biology #1069)
by María Elena Álvarez-Buylla Roces Juan Carlos Martínez-García José Dávila-Velderrain Elisa Domínguez-Hüttinger Mariana Esther Martínez-SánchezThis book contributes to better understand how lifestyle modulations can effectively halt the emergence and progression of human diseases. The book will allow the reader to gain a better understanding of the mechanisms by which the environment interferes with the bio-molecular regulatory processes underlying the emergence and progression of complex diseases, such as cancer. Focusing on key and early cellular bio-molecular events giving rise to the emergence of degenerative chronic disease, it builds on previous experience on the development of multi-cellular organisms, to propose a mathematical and computer based framework that allows the reader to analyze the complex interplay between bio-molecular processes and the (micro)-environment from an integrative, mechanistic, quantitative and dynamical perspective. Taking the wealth of empirical evidence that exists it will show how to build and analyze models of core regulatory networks involved in the emergence and progression of chronic degenerative diseases, using a bottom-up approach.
Modeling Monetary Economies
by Scott Freeman Bruce Champ Joseph HaslagThe approach of this text is to teach monetary economics using the classical paradigm of rational agents in a market setting. Too often monetary economics has been taught as a collection of facts about existing institutions for students to memorize. By teaching from first principles instead, the authors aim to instruct students not only in the monetary policies and institutions that exist today in the United States and Canada, but also in what policies and institutions may or should exist tomorrow and elsewhere. The text builds on a simple, clear monetary model and applies this framework consistently to a wide variety of monetary questions. The authors have added in this third edition new material on money as a means of replacing imperfect social record keeping, the role of currency in banking panics, and a description of the policies implemented to deal with the banking crises that began in 2007.
Modeling Multiphase Materials Processes
by Manabu Iguchi Olusegun J. IlegbusiModeling Multiphase Materials Processes: Gas-Liquid Systems describes the methodology and application of physical and mathematical modeling to multi-phase flow phenomena in materials processing. The book focuses on systems involving gas-liquid interaction, the most prevalent in current metallurgical processes. The performance characteristics of these processes are largely dependent on transport phenomena. This volume covers the inherent characteristics that complicate the modeling of transport phenomena in such systems, including complex multiphase structure, intense turbulence, opacity of fluid, high temperature, coupled heat and mass transfer, chemical reactions in some cases, and poor wettability of the reactor walls. Also discussed are: solutions based on experimental and numerical modeling of bubbling jet systems, recent advances in the modeling of nanoscale multi-phase phenomena and multiphase flows in micro-scale and nano-scale channels and reactors. Modeling Multiphase Materials Processes: Gas-Liquid Systems will prove a valuable reference for researchers and engineers working in mathematical modeling and materials processing.
Modeling Nonlinear Problems in the Mechanics of Strings and Rods: The Role of the Balance Laws (Interaction of Mechanics and Mathematics)
by Oliver M. O'ReillyThis book presents theories of deformable elastic strings and rods and their application to broad classes of problems. Readers will gain insights into the formulation and analysis of models for mechanical and biological systems. Emphasis is placed on how the balance laws interplay with constitutive relations to form a set of governing equations. For certain classes of problems, it is shown how a balance of material momentum can play a key role in forming the equations of motion. The first half of the book is devoted to the purely mechanical theory of a string and its applications. The second half of the book is devoted to rod theories, including Euler’s theory of the elastica, Kirchhoff ’s theory of an elastic rod, and a range of Cosserat rod theories. A variety of classic and recent applications of these rod theories are examined. Two supplemental chapters, the first on continuum mechanics of three-dimensional continua and the second on methods from variational calculus, are included to provide relevant background for students.This book is suited for graduate-level courses on the dynamics of nonlinearly elastic rods and strings.
Modeling Nonlinearity and Interaction in Regression Analysis Using Spline Variables (Quantitative Applications in the Social Sciences)
by Roger A. Wojtkiewicz"Spline variables and their interactions play a crucial role in the field of social science. This book offers a comprehensive and detailed exploration of this method, providing valuable insights and information for researchers in the field." --Man-Kit Lei, The University of Georgia This volume addresses the issue of linear constraints in regression modeling. Author Roger A. Wojtkiewicz uses the method of knotted spline variables (also known as piecewise linear regression) and a new method involving group spline variables to model nonlinearity in a variety of situations. Using spline variables to model nonlinearity allows researchers to specify unrestricted models for models that involve interval variables, allowing for greater flexibility in modeling any possible interaction.
Modeling Nonlinearity and Interaction in Regression Analysis Using Spline Variables (Quantitative Applications in the Social Sciences)
by Roger A. Wojtkiewicz"Spline variables and their interactions play a crucial role in the field of social science. This book offers a comprehensive and detailed exploration of this method, providing valuable insights and information for researchers in the field." --Man-Kit Lei, The University of Georgia This volume addresses the issue of linear constraints in regression modeling. Author Roger A. Wojtkiewicz uses the method of knotted spline variables (also known as piecewise linear regression) and a new method involving group spline variables to model nonlinearity in a variety of situations. Using spline variables to model nonlinearity allows researchers to specify unrestricted models for models that involve interval variables, allowing for greater flexibility in modeling any possible interaction.
Modeling Online Auctions
by Wolfgang Jank Galit ShmueliExplore cutting-edge statistical methodologies for collecting, analyzing, and modeling online auction data Online auctions are an increasingly important marketplace, as the new mechanisms and formats underlying these auctions have enabled the capturing and recording of large amounts of bidding data that are used to make important business decisions. As a result, new statistical ideas and innovation are needed to understand bidders, sellers, and prices. Combining methodologies from the fields of statistics, data mining, information systems, and economics, Modeling Online Auctions introduces a new approach to identifying obstacles and asking new questions using online auction data. The authors draw upon their extensive experience to introduce the latest methods for extracting new knowledge from online auction data. Rather than approach the topic from the traditional game-theoretic perspective, the book treats the online auction mechanism as a data generator, outlining methods to collect, explore, model, and forecast data. Topics covered include: Data collection methods for online auctions and related issues that arise in drawing data samples from a Web site Models for bidder and bid arrivals, treating the different approaches for exploring bidder-seller networks Data exploration, such as integration of time series and cross-sectional information; curve clustering; semi-continuous data structures; and data hierarchies The use of functional regression as well as functional differential equation models, spatial models, and stochastic models for capturing relationships in auction data Specialized methods and models for forecasting auction prices and their applications in automated bidding decision rule systems Throughout the book, R and MATLAB software are used for illustrating the discussed techniques. In addition, a related Web site features many of the book's datasets and R and MATLAB code that allow readers to replicate the analyses and learn new methods to apply to their own research. Modeling Online Auctions is a valuable book for graduate-level courses on data mining and applied regression analysis. It is also a one-of-a-kind reference for researchers in the fields of statistics, information systems, business, and marketing who work with electronic data and are looking for new approaches for understanding online auctions and processes. Visit this book's companion website by clicking here
Modeling Operations Research and Business Analytics (ISSN)
by William P Fox Robert E. BurksThis book provides sample exercises, techniques, and solutions to employ mathematical modeling to solve problems in Operations Research and Business Analytics. Each chapter begins with a scenario and includes exercises built on realistic problems faced by managers and others working in operations research, business analytics, and other fields employing applied mathematics. A set of assumptions is presented, and then a model is formulated. A solution is offered, followed by examples of how that model can be used to address related issues.Key elements of this book include the most common problems the authors have encountered over research and while consulting the fields including inventory theory, facilities' location, linear and integer programming, assignment, transportation and shipping, critical path, dynamic programming, queuing models, simulation models, reliability of system, multi-attribute decision-making, and game theory.In the hands of an experienced professional, mathematical modeling can be a powerful tool. This book presents situations and models to help both professionals and students learn to employ these techniques to improve outcomes and to make addressing real business problems easier. The book is essential for all managers and others who would use mathematics to improve their problem-solving techniques.No previous exposure to mathematical modeling is required. The book can then be used for a first course on modeling, or by those with more experience who want to refresh their memories when they find themselves facing real-world problems. The problems chosen are presented to represent those faced by practitioners.The authors have been teaching mathematical modeling to students and professionals for nearly 40 years. This book is presented to offer their experience and techniques to instructors, students, and professionals.
Modeling Ordered Choices: A Primer
by William H. Greene David A. HensherIt is increasingly common for analysts to seek out the opinions of individuals and organizations using attitudinal scales such as degree of satisfaction or importance attached to an issue. Examples include levels of obesity, seriousness of a health condition, attitudes towards service levels, opinions on products, voting intentions, and the degree of clarity of contracts. Ordered choice models provide a relevant methodology for capturing the sources of influence that explain the choice made amongst a set of ordered alternatives. The methods have evolved to a level of sophistication that can allow for heterogeneity in the threshold parameters, in the explanatory variables (through random parameters), and in the decomposition of the residual variance. This book brings together contributions in ordered choice modeling from a number of disciplines, synthesizing developments over the last fifty years, and suggests useful extensions to account for the wide range of sources of influence on choice.
Modeling Psychophysical Data in R
by Laurence T. Maloney Kenneth KnoblauchMany of the commonly used methods for modeling and fitting psychophysical data are special cases of statistical procedures of great power and generality, notably the Generalized Linear Model (GLM). This book illustrates how to fit data from a variety of psychophysical paradigms using modern statistical methods and the statistical language R. The paradigms include signal detection theory, psychometric function fitting, classification images and more. In two chapters, recently developed methods for scaling appearance, maximum likelihood difference scaling and maximum likelihood conjoint measurement are examined. The authors also consider the application of mixed-effects models to psychophysical data. R is an open-source programming language that is widely used by statisticians and is seeing enormous growth in its application to data in all fields. It is interactive, containing many powerful facilities for optimization, model evaluation, model selection, and graphical display of data. The reader who fits data in R can readily make use of these methods. The researcher who uses R to fit and model his data has access to most recently developed statistical methods. This book does not assume that the reader is familiar with R, and a little experience with any programming language is all that is needed to appreciate this book. There are large numbers of examples of R in the text and the source code for all examples is available in an R package MPDiR available through R. Kenneth Knoblauch is a researcher in the Department of Integrative Neurosciences in Inserm Unit 846, The Stem Cell and Brain Research Institute and associated with the University Claude Bernard, Lyon 1, in France. Laurence T. Maloney is Professor of Psychology and Neural Science at New York University. His research focusses on applications of mathematical models to perception, motor control and decision making.
Modeling Real Life
by Ron Larson Laurie BoswellThe Big Ideas Math: Modeling Real Life Student Edition Volume 2 provides students with learning targets and success criteria at the chapter and lesson level to make learning visible. There are diverse opportunities to develop problem-solving and communication skills through the balanced instructional design of Explore and Grow, Think and Grow, Apply and Grow, and Think and Grow: Modeling Real Life. Students master content, skills, and embedded mathematical practices through engaging activities with opportunities to enhance with games, songs, literature-based exercises that connect mathematics to the real world in an ideal context for elementary students.
Modeling Real Life, Grade 2, Volume 1 (Big Ideas Math)
by Ron Larson Laurie BoswellNIMAC-sourced textbook
Modeling Real Life, Grade 2, Volume 2 (Big Ideas Math)
by Ron Larson Laurie BoswellNIMAC-sourced textbook
Modeling Real Life, Grade 3, Volume 1 (Big Ideas Math)
by Ron Larson Laurie BoswellNIMAC-sourced textbook
Modeling Real Life, Grade 5, Volume 1 (Big Ideas Math)
by Ron Larson Laurie BoswellNIMAC-sourced textbook
Modeling Real Life, Grade 5, Volume 2 (Big Ideas Math)
by Ron Larson Laurie BoswellNIMAC-sourced textbook
Modeling Real Life, Grade 7, Accelerated (Big Ideas Math)
by Ron Larson Laurie BoswellNIMAC-sourced textbook
Modeling Real Life: Grade 6 Advanced (Big Ideas Math)
by Ron Larson Laurie BoswellNIMAC-sourced textbook