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The last decade has seen a remarkable development of the "Marginal and Moment Problems" as a research area in Probability and Statistics. Its attractiveness stemmed from its lasting ability to provide a researcher with difficult theoretical problems that have direct consequences for appli cations outside of mathematics. The relevant research aims centered mainly along the following lines that very frequently met each other to provide sur prizing and useful results : -To construct a probability distribution (to prove its existence, at least) with a given support and with some additional inner stochastic property defined typically either by moments or by marginal distributions. -To study the geometrical and topological structure of the set of prob ability distributions generated by such a property mostly with the aim to propose a procedure that would result in a stochastic model with some optimal properties within the set of probability distributions. These research aims characterize also, though only very generally, the scientific program of the 1996 conference "Distributions with given marginals and moment problems" held at the beginning of September in Prague, Czech Republic, to perpetuate the tradition and achievements of the closely related 1990 Roma symposium "On Frechet Classes" 1 and 1993 Seattle" AMS Summer Conference on Marginal Problem".
This book is a collection of papers presented at the 'Forum "Math-for-Industry" 2016 ' (FMfl2016), held at Queensland University of Technology, Brisbane, Australia, on November 21–23, 2016. The theme for this unique and important event was “Agriculture as a Metaphor for Creativity in All Human Endeavors”, and it brought together leading international mathematicians and active researchers from universities and industry to discuss current challenging topics and to promote interactive collaborations between mathematics and industry. The success of agricultural practice relies fundamentally on its interconnections with and dependence on biology and the environment. Both play essential roles, including the biological adaption to cope with environmental challenges of biotic and abiotic stress and global warming. The book highlights the development of mathematics within this framework that successful agricultural practice depends upon and exploits.
A mathematical introduction to deep learning, written by a group of leading experts in the field.
Entropy theory has wide applications to a range of problems in the fields of environmental and water engineering, including river hydraulic geometry, fluvial hydraulics, water monitoring network design, river flow forecasting, floods and droughts, river network analysis, infiltration, soil moisture, sediment transport, surface water and groundwater quality modeling, ecosystems modeling, water distribution networks, environmental and water resources management, and parameter estimation. Such applications have used several different entropy formulations, such as Shannon, Tsallis, Rényi, Burg, Kolmogorov, Kapur, configurational, and relative entropies, which can be derived in time, space, or frequency domains. More recently, entropy-based concepts have been coupled with other theories, including copula and wavelets, to study various issues associated with environmental and water resources systems. Recent studies indicate the enormous scope and potential of entropy theory in advancing research in the fields of environmental and water engineering, including establishing and explaining physical connections between theory and reality. The objective of this Special Issue is to provide a platform for compiling important recent and current research on the applications of entropy theory in environmental and water engineering. The contributions to this Special Issue have addressed many aspects associated with entropy theory applications and have shown the enormous scope and potential of entropy theory in advancing research in the fields of environmental and water engineering.
The first volume of this comprehensive global perspective on Integrated Drought Management is focused on understanding drought, causes, and the assessment of drought impacts. It explains different types of drought: agricultural, meteorological, hydrological, and socioeconomic droughts, their indices and the impact of climate change on drought. The volume also examines spatiotemporal analysis of drought, variability and patterns, assessment, and drought evaluation. With numerous case studies from India, Mexico, Turkey, Brazil, US, and other countries, this volume serves as a valuable resource for all readers who want to advance their knowledge on drought and risk management. Features: Provides a global perspective on drought prediction and management and a synthesis of the recent state of knowledge. Covers a wide range of topics from essential concepts and advanced techniques for forecasting and modeling drought to societal impacts, consequences, and planning. Presents numerous case studies with different management approaches from different regions and countries. Addresses how climate change impacts drought, the increasing challenges associated with managing drought, decision making, and policy implications. Includes contributions from hundreds of experts around the world. Professionals, researchers, academics, and postgraduate students with knowledge in environmental sciences, ecology, agriculture, forestry, hydrology, water resources engineering, and earth sciences, as well as those interested in how climate change impacts drought management, will gain new insights from the experts featured in this two-volume handbook.
In 1978 Edwin T. Jaynes and Myron Tribus initiated a series of workshops to exchange ideas and recent developments in technical aspects and applications of Bayesian probability theory. The first workshop was held at the University of Wyoming in 1981 organized by C.R. Smith and W.T. Grandy. Due to its success, the workshop was held annually during the last 18 years. Over the years, the emphasis of the workshop shifted gradually from fundamental concepts of Bayesian probability theory to increasingly realistic and challenging applications. The 18th international workshop on Maximum Entropy and Bayesian Methods was held in Garching / Munich (Germany) (27-31. July 1998). Opening lectures by G. Larry Bretthorst and by Myron Tribus were dedicated to one of th the pioneers of Bayesian probability theory who died on the 30 of April 1998: Edwin Thompson Jaynes. Jaynes revealed and advocated the correct meaning of 'probability' as the state of knowledge rather than a physical property. This inter pretation allowed him to unravel longstanding mysteries and paradoxes. Bayesian probability theory, "the logic of science" - as E.T. Jaynes called it - provides the framework to make the best possible scientific inference given all available exper imental and theoretical information. We gratefully acknowledge the efforts of Tribus and Bretthorst in commemorating the outstanding contributions of E.T. Jaynes to the development of probability theory.
This book collects the papers presented at the 7th International Conference on Risk Analysis and Crisis Response (RACR-2019) held in Athens, Greece, on October 15-19, 2019. The overall theme of the seventh international conference on risk analysis and crisis response is Risk Analysis Based on Data and Crisis Response Beyond Knowledge, highlighting science and technology to improve risk analysis capabilities and to optimize crisis response strategy. This book contains primarily research articles of risk issues. Underlying topics include natural hazards and major (chemical) accidents prevention, disaster risk reduction and society resilience, information and communication technologies safety and cybersecurity, modern trends in crisis management, energy and resources security, critical infrastructure, nanotechnology safety and others. All topics include aspects of multidisciplinarity and complexity of safety in education and research. The book should be valuable to professors, engineers, officials, businessmen and graduate students in risk analysis and risk management.