Unmanned aerial vehicles (UAVs) are increasingly used in military missions because they have the advantages of not placing human life at risk and of lowering operation costs via decreased vehicle weight. These benefits can be fully realized only if UAVs work cooperatively in groups with an efficient exchange of information. This book provides an authoritative reference on cooperative decision and control of UAVs and the means available to solve problems involving them
The 2018–2020 Ebola virus disease epidemic in Democratic Republic of the Congo (DRC) resulted in 3481 cases (probable and confirmed) and 2299 deaths. In this paper, we use a novel statistical method to analyze the individual-level incidence and hospitalization data on DRC Ebola victims. Our analysis suggests that an increase in the rate of quarantine and isolation that has shortened the infectiousness period by approximately one day during the epidemic's third and final wave was likely responsible for the eventual containment of the outbreak. The analysis further reveals that the total effective population size or the average number of individuals at risk for the disease exposure in three epidemic waves over the period of 24 months was around 16,000–a much smaller number than previously estimated and likely an evidence of at least partial protection of the population at risk through ring vaccination and contact tracing as well as adherence to strict quarantine and isolation policies.
"Stress tests are the most innovative regulatory tool to prevent and fight financial crises. Their use has fundamentally changed the mathematical modeling of financial systems, financial risk management in the public and private sector, and the policies designed to prevent and mitigate financial crises. When financial crises hit, stress tests take center stage. Despite their centrality to public policy, the optimal design and use of stress tests remains highly contested. Written by an international team of leading thinkers from academia, the public sector and the private sector, this handbook comprehensively surveys and evaluates the state of play and charts the innovations that will determine the path ahead. It is a comprehensive and interdisciplinary resource that bridges theory and practice and places financial stress testing in its wider context. This guide is essential reading for researchers, practitioners and policymakers working on financial risk management and financial regulation"--
In many branches of science relevant observations are taken sequentially over time. Bayesian Analysis of Time Series discusses how to use models that explain the probabilistic characteristics of these time series and then utilizes the Bayesian approach to make inferences about their parameters. This is done by taking the prior information and via Bayes theorem implementing Bayesian inferences of estimation, testing hypotheses, and prediction. The methods are demonstrated using both R and WinBUGS. The R package is primarily used to generate observations from a given time series model, while the WinBUGS packages allows one to perform a posterior analysis that provides a way to determine the characteristic of the posterior distribution of the unknown parameters. Features Presents a comprehensive introduction to the Bayesian analysis of time series. Gives many examples over a wide variety of fields including biology, agriculture, business, economics, sociology, and astronomy. Contains numerous exercises at the end of each chapter many of which use R and WinBUGS. Can be used in graduate courses in statistics and biostatistics, but is also appropriate for researchers, practitioners and consulting statisticians. About the author Lyle D. Broemeling, Ph.D., is Director of Broemeling and Associates Inc., and is a consulting biostatistician. He has been involved with academic health science centers for about 20 years and has taught and been a consultant at the University of Texas Medical Branch in Galveston, The University of Texas MD Anderson Cancer Center and the University of Texas School of Public Health. His main interest is in developing Bayesian methods for use in medical and biological problems and in authoring textbooks in statistics. His previous books for Chapman & Hall/CRC include Bayesian Biostatistics and Diagnostic Medicine, and Bayesian Methods for Agreement.
An Introduction to Economic Dynamics provides a framework for students to appreciate and understand the basic intuition behind economic models and to experiment with those models using simulation techniques in MATLAB. This book goes beyond the often-limited scope of other texts on economic models, which have largely focused on elucidating static equilibrium models. Comparative static analysis inhibits students from asking how the equilibrium position is achieved from an initial out-of-equilibrium position and limits their understanding of the dynamics that underlie such analysis. In this textbook, readers are introduced to ten well-established macroeconomic models - including Keynesian multiplier models, Samuelson's multiplier and Solow's growth model - and guided through the dynamical systems behind each model. Every chapter begins with an overview of the economic problem which the model is designed to help solve followed by an explanation of the mathematics of the model. Solutions are provided using simulation and visualisation techniques in MATLAB, which are interwoven organically with the analysis and are introduced in a step-by-step fashion to guide the reader along the way. Appendices provide an introduction to MATLAB along with all the necessary codes. The book is ideally suited for courses in economic dynamics, macroeconomic modelling and computational economics, as well as for students of finance, mathematics and engineering who are interested in economic models
Around the term 'place' a process of theory formation has emerged in English-language philosophy with hermeneutic and phenomenological orientation, which in Germany has until now rarely been acknowledged. This book changes that - with both foundational philosophical contributions from relevant authors on thinking about 'place' as well as with articles which illustrate the difficulties of 'place' via individual analyses of concrete examples. It addresses among others the meaning of 'place' in literature, popular media such as film and computer games, cults and myths, as well as in the fusion of economy and everyday experience.
X and the City, a book of diverse and accessible math-based topics, uses basic modeling to explore a wide range of entertaining questions about urban life. How do you estimate the number of dental or doctor's offices, gas stations, restaurants, or movie theaters in a city of a given size? How can mathematics be used to maximize traffic flow through tunnels? Can you predict whether a traffic light will stay green long enough for you to cross the intersection? And what is the likelihood that your city will be hit by an asteroid? Every math problem and equation in this book tells
The investigation of special topics in systems dynamics -uncertain dynamic processes, viability theory, nonlinear dynamics in models for biomathematics, inverse problems in control systems theory-has become a major issue at the System and Decision Sciences Research Program of the International Insti tute for Applied Systems Analysis. The above topics actually reflect two different perspectives in the investigation of dynamic processes. The first, motivated by control theory, is concerned with the properties of dynamic systems that are stable under vari ations in the systems' parameters. This allows us to specify classes of dynamic systems for which it is possible to construct and control a whole "tube" of trajectories assigned to a system with uncertain parameters and to resolve some inverse problems of control theory within numerically stable solution schemes. The second perspective is to investigate generic properties of dynamic systems that are due to nonlinearity (as bifurcations theory, chaotic behavior, stability properties, and related problems in the qualitative theory of differential systems). Special stress is given to the applications of non linear dynamic systems theory to biomathematics and ecoloey.
"In this paper, we consider a nonlinear $p-$Kirchhoff type hyperbolic equation with damping and source terms $$u_{tt}-M\left( \underset{\Omega }{\int }\left\vert \nabla u\right\vert ^{p}dx\right) \Delta _{p}u+\left\vert u_{t}\right\vert ^{m-2}u_{t}=\left\vert u\right\vert ^{r-2}u.$$ Under suitable assumptions and positive initial energy, we prove the global existence of solution by using the potential energy and Nehari's functionals. Finally, the stability of equation is established based on Komornik's integral inequality."
Intro -- Preface -- Contents -- Acronyms -- 1. Introduction -- Part I. Fractional modeling of large crowds of pedestrians -- 2. Microscopic model of fractional order for evacuation of crowds -- 3. Macroscopic model of fractional order for crowds of pedestrians -- 4. Mesoscopic model of fractional order for crowds of pedestrians -- Part II: Fractional control of large crowds of pedestrians -- 5. Cluster consensus for crowds of pedestrians at micro-scale -- 6. Feedback control of crowds of pedestrians at macro-scale -- 7. Intelligent evacuation systems for crowds of pedestrians -- Index
Leveraging the research efforts of more than sixty experts in the area, this book reviews cutting-edge practices in machine learning for financial markets. Instead of seeing machine learning as a new field, the authors explore the connection between knowledge developed by quantitative finance over the past forty years and techniques generated by the current revolution driven by data sciences and artificial intelligence. The text is structured around three main areas: 'Interactions with investors and asset owners,' which covers robo-advisors and price formation; 'Risk intermediation,' which discusses derivative hedging, portfolio construction, and machine learning for dynamic optimization; and 'Connections with the real economy,' which explores nowcasting, alternative data, and ethics of algorithms. Accessible to a wide audience, this invaluable resource will allow practitioners to include machine learning driven techniques in their day-to-day quantitative practices, while students will build intuition and come to appreciate the technical tools and motivation for the theory