Presents a unique study of Integrative Problem-Solving (IPS). The consideration of 'Decadence' is essential in the scientific study of environmental and other problems and their rigorous solution, because the broad context within which the problems emerge can affect their solution. Stochastic reasoning underlines the conceptual and methodological framework of IPS, and its formulation has a mathematical life of its own that accounts for the multidisciplinarity of real world problems, the multisourced uncertainties characterizing their solution, and the different thinking modes of the people involved. Only by interpolating between the full range of disciplines (including stochastic mathematics, physical science, neuropsychology, philosophy, and sociology) and the associated thinking modes can scientists arrive at a satisfactory account of problem-solving, and be able to distinguish between a technically complete problem-solution, and a solution that has social impact.

Quantitative Analysis and Modeling of Earth and Environmental Data: Space-Time and Spacetime Data Considerations introduces the notion of chronotopologic data analysis that offers a systematic, quantitative analysis of multi-sourced data and provides information about the spatial distribution and temporal dynamics of natural attributes (physical, biological, health, social). It includes models and techniques for handling data that may vary by space and/or time, and aims to improve understanding of the physical laws of change underlying the available numerical datasets, while taking into consideration the in-situ uncertainties and relevant measurement errors (conceptual, technical, computational). It considers the synthesis of scientific theory-based methods (stochastic modeling, modern geostatistics) and data-driven techniques (machine learning, artificial neural networks) so that their individual strengths are combined by acting symbiotically and complementing each other. The notions and methods presented in Quantitative Analysis and Modeling of Earth and Environmental Data: Space-Time and Spacetime Data Considerations cover a wide range of data in various forms and sources, including hard measurements, soft observations, secondary information and auxiliary variables (ground-level measurements, satellite observations, scientific instruments and records, protocols and surveys, empirical models and charts). Including real-world practical applications as well as practice exercises, this book is a comprehensive step-by-step tutorial of theory-based and data-driven techniques that will help students and researchers master data analysis and modeling in earth and environmental sciences (including environmental health and human exposure applications). - Explores the analysis and processing of chronotopologic (i.e., space-time and spacetime) data that varies spatially and/or temporally, which is the case with the majority of data in scientific and engineering disciplines - Studies the synthesis of scientific theory and empirical evidence (in its various forms) that offers a mathematically rigorous and physically meaningful assessment of real-world phenomena - Covers a wide range of data describing a variety of attributes characterizing physical phenomena and systems including earth, ocean and atmospheric variables, environmental and ecological parameters, population health states, disease indicators, and social and economic characteristics - Includes case studies and practice exercises at the end of each chapter for both real-world applications and deeper understanding of the concepts presented

This volume examines Popper’s philosophy by analyzing the criticism of his most popular critics: Thomas Kuhn, Paul Feyerabend and Imre Lakatos. They all followed his rejection of the traditional view of science as inductive. Starting from the assumption that Hume’s criticism of induction is valid, the book explores the central criticism and objections that these three critics have raised. Their objections have met with great success, are significant and deserve paraphrase. One also may consider them reasonable protests against Popper’s high standards rather than fundamental criticisms of his philosophy. The book starts out with a preliminary discussion of some central background material and essentials of Popper’s philosophy. It ends with nutshell representations of the philosophies of Popper. Kuhn, Feyerabend and Lakatos. The middle section of the book presents the connection between these philosophers and explains what their central ideas consists of, what the critical arguments are, how they presented them, and how valid they are. In the process, the author claims that Popper's popular critics used against him arguments that he had invented (and answered) without saying so. They differ from him mainly in that they demanded of all criticism that it should be constructive: do not stop believing a refuted theory unless there is a better alternative to it. Popper hardly ever discussed belief, delegating its study to psychology proper; he usually discussed only objective knowledge, knowledge that is public and thus open to public scrutiny.

Spatiotemporal Random Fields: Theory and Applications, Second Edition, provides readers with a new and updated edition of the text that explores the application of spatiotemporal random field models to problems in ocean, earth, and atmospheric sciences, spatiotemporal statistics, and geostatistics, among others. The new edition features considerable detail of spatiotemporal random field theory, including ordinary and generalized models, as well as space-time homostationary, isostationary and hetrogeneous approaches. Presenting new theoretical and applied results, with particular emphasis on space-time determination and interpretation, spatiotemporal analysis and modeling, random field geometry, random functionals, probability law, and covariance construction techniques, this book highlights the key role of space-time metrics, the physical interpretation of stochastic differential equations, higher-order space-time variability functions, the validity of major theoretical assumptions in real-world practice (covariance positive-definiteness, metric-adequacy etc.), and the emergence of interdisciplinary phenomena in conditions of multi-sourced real-world uncertainty. - Contains applications in the form of examples and case studies, providing readers with first-hand experiences - Presents an easy to follow narrative which progresses from simple concepts to more challenging ideas - Includes significant updates from the previous edition, including a focus on new theoretical and applied results

In eleven sharp essays, the contributors to Decay attend to the processes and experiences of symbolic and material decay in a variety of sociopolitical contexts across the globe. They examine decay in its myriad manifestations—biological, physical, organizational, moral, political, personal, and social and in numerous contexts, including colonialism and imperialism, governments and the state, racism, the environment, and infrastructure. The volume's topics are wide in scope, ranging from the discourse of social decay in contemporary Australian settler colonialism and the ways infrastructures both create and experience decay to cultural decay in the aftermath of the Sri Lankan civil war and the relations among individual, institutional, and societal decay in an American high-security prison. By using decay as a problematic and expounding its mechanisms, conditions, and temporalities, the contributors provide nuanced and rigorous means to more fully grapple with the exigencies of the current sociopolitical moment. Contributors. Cameo Dalley, Peter D. Dwyer, Akhil Gupta, Ghassan Hage, Michael Herzfeld, Elise Klein, Bart Klem, Tamara Kohn, Michael Main, Fabio Mattioli, Debra McDougall, Monica Minnegal, Violeta Schubert

The validity of certain critical reasoning steps carried out during or on the sidelines of the environmental science, public health survey, medical experiment, population risk assessment, or disease space-time mapping under conditions of in situ uncertainty and space-time heterogeneity, is often not given sufficient attention and may even be out of the investigator's line of thought. For example, the technical complexity of an environmental exposure experiment may overshadow the logical assumptions made when moving from one phase of the experiment to the next, or the study of population risk assessment may focus on analytical and computational matters, whereas methodological and cultural factors are neglected.This book helps health investigators structure their thinking so that they avoid logical mistakes and argument pitfalls, and also gain new insights about reality, improve their awareness of the environment and context within which one's thinking takes place.

Leverage Big Data analytics methodologies to add value to geophysical and petrophysical exploration data Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models demonstrates a new approach to geophysics and petrophysics data analysis using the latest methods drawn from Big Data. Written by two geophysicists with a combined 30 years in the industry, this book shows you how to leverage continually maturing computational intelligence to gain deeper insight from specific exploration data. Case studies illustrate the value propositions of this alternative analytical workflow, and in-depth discussion addresses the many Big Data issues in geophysics and petrophysics. From data collection and context through real-world everyday applications, this book provides an essential resource for anyone involved in oil and gas exploration. Recent and continual advances in machine learning are driving a rapid increase in empirical modeling capabilities. This book shows you how these new tools and methodologies can enhance geophysical and petrophysical data analysis, increasing the value of your exploration data. Apply data-driven modeling concepts in a geophysical and petrophysical context Learn how to get more information out of models and simulations Add value to everyday tasks with the appropriate Big Data application Adjust methodology to suit diverse geophysical and petrophysical contexts Data-driven modeling focuses on analyzing the total data within a system, with the goal of uncovering connections between input and output without definitive knowledge of the system's physical behavior. This multi-faceted approach pushes the boundaries of conventional modeling, and brings diverse fields of study together to apply new information and technology in new and more valuable ways. Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models takes you beyond traditional deterministic interpretation to the future of exploration data analysis.

This book reports on a research program designed to construct the basics of a new type of literacy that teaches pupils social problem-solving at individual and collective levels. It is the first of a series of books about a chain of intervention research subprojects started in 2009 teaching pupils basic skills to make well-balanced decisions; to resolve conflicts in a nonviolent manner; and to develop good social relationships and responsibility, critical thinking, and other abilities which give children and young people the tools needed to pursue their options in life. According to the United Nations, there is no systematic program in schools that develops these capacities in pupils. This volume fills the gap by describing successful classroom interventions and by developing a framework for social problem-solving literacy as mandated by the United Nations Child Convention.

The Encyclopedia of Mathematical Geosciences is a complete and authoritative reference work. It provides concise explanation on each term that is related to Mathematical Geosciences. Over 300 international scientists, each expert in their specialties, have written around 350 separate articles on different topics of mathematical geosciences including contributions on Artificial Intelligence, Big Data, Compositional Data Analysis, Geomathematics, Geostatistics, Geographical Information Science, Mathematical Morphology, Mathematical Petrology, Multifractals, Multiple Point Statistics, Spatial Data Science, Spatial Statistics, and Stochastic Process Modeling. Each topic incorporates cross-referencing to related articles, and also has its own reference list to lead the reader to essential articles within the published literature. The entries are arranged alphabetically, for easy access, and the subject and author indices are comprehensive and extensive.

Contrary to optimistic visions of a free internet for all, the problem of the ‘digital divide’ – the disparity between those with access to internet technology and those without – has persisted for close to twenty-five years. In this textbook, Jan van Dijk considers the state of digital inequality and what we can do to tackle it. Through an accessible framework based on empirical research, he explores the motivations and challenges of seeking access and the development of requisite digital skills. He addresses key questions such as: Does digital inequality reduce or reinforce existing, traditional inequalities? Does it create new, previously unknown social inequalities? While digital inequality affects all aspects of society and the problem is here to stay, Van Dijk outlines policies we can put in place to mitigate it. The Digital Divide is required reading for students and scholars of media, communication, sociology, and related disciplines, as well as for policymakers.