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The book Modeling Reality covers a wide range of fascinating subjects, accessible to anyone who wants to learn about the use of computer modeling to solve a diverse range of problems, but who does not possess a specialized training in mathematics or computer science. The material presented is pitched at the level of high-school graduates, even though it covers some advanced topics (cellular automata, Shannon's measure of information, deterministic chaos, fractals, game theory, neural networks, genetic algorithms, and Turing machines). These advanced topics are explained in terms of well known simple concepts: Cellular automata - Game of Life, Shannon's formula - Game of twenty questions, Game theory - Television quiz, etc. The book is unique in explaining in a straightforward, yet complete, fashion many important ideas, related to various models of reality and their applications.
This book summarizes the results of our modeling-from-reality (MFR) project which took place over the last decade or so. The goal of this project is to develop techniques for modeling real objects and/or environments into geometric and photometric models through computer vision techniques. By developing such techniques, time consuming modeling process, currently un dertaken by human programmers, can be (semi-)automatically performed, and, as a result, we can drastically shorten the developing time of such virtual reality systems, reduce their developing cost, and widen their application areas. Originally, we began to develop geometric modeling techniques that acquire shape information of objects/environments for object recognition. Soon, this effort evolved into an independent modeling project, virtual-reality modeling, with the inclusion of photometric modeling aspects that acquire appearance information, such as color, texture, and smoothness. Over the course of this development, it became apparent that environmental modeling techniques were necessary when applying our techniques to mixed realities that seamlessly combine generated virtual models with other real/virtual images. The material in his book covers these aspects of development.
Simulating the behavior of a human heart, predicting tomorrow's weather, optimizing the aerodynamics of a sailboat, finding the ideal cooking time for a hamburger: to solve these problems, cardiologists, meteorologists, sportsmen, and engineers can count on math help. This book will lead you to the discovery of a magical world, made up of equations, in which a huge variety of important problems for our life can find useful answers.
Attempts to understand various aspects of the empirical world often rely on modelling processes that involve a reconstruction of systems under investigation. Typically the reconstruction uses mathematical frameworks like gauge theory and renormalization group methods, but more recently simulations also have become an indispensable tool for investigation. This book is a philosophical examination of techniques and assumptions related to modelling and simulation with the goal of showing how these abstract descriptions can contribute to our understanding of the physical world. Particular issues include the role of fictional models in science, how mathematical formalisms can yield physical information, and how we should approach the use of inconsistent models for specific types of systems. It also addresses the role of simulation, specifically the conditions under which simulation can be seen as a technique for measurement, replacing more traditional experimental approaches. Inherent worries about the legitimacy of simulation "knowledge" are also addressed, including an analysis of verification and validation and the role of simulation data in the search for the Higgs boson. In light of the significant role played by simulation in the Large Hadron Collider experiments, it is argued that the traditional distinction between simulation and experiment is no longer applicable in some contexts of modern science. Consequently, a re-evaluation of the way and extent to which simulation delivers empirical knowledge is required. "This is a, lively, stimulating, and important book by one of the main scholars contributing to current topics and debates in our field. It will be a major resource for philosophers of science, their students, scientists interested in examining scientific practice, and the general scientifically literate public."-Bas van Fraassen, Distinguished Professor of Philosophy, San Francisco State University
Clinical musings on the nature of reality and “known experience.” Therapists must rely on their clients’ reporting of experience in order to assess, treat, and offer help. Yet we all experience the world through various filters of one sort or another, and our experiences are transformed through several nonconscious processes before reaching our conscious awareness. Science, philosophy, and wisdom traditions share the belief that our awareness is very restricted. How, then, can anyone accurately report their experience, let alone get help with it? Neuropsychologist Aldrich Chan examines how our experience of reality is assembled and shaped by biological, psychological, sociocultural, and existential processes. Each chapter explores processes within these domains that may act as “veils.” Topics in the book include: the default mode network, cognitive distortions, decision-making heuristics, the interconnected mind, memory, and cultural concepts of distress. By understanding the ways in which reality can be distorted, clinicians can more effectively help their clients reach their personal psychotherapeutic goals.
Now in paperback, “a compelling, accessible, and provocative piece of work that forces us to question many of our assumptions” (Gillian Tett, author of Fool’s Gold). Quants, physicists working on Wall Street as quantitative analysts, have been widely blamed for triggering financial crises with their complex mathematical models. Their formulas were meant to allow Wall Street to prosper without risk. But in this penetrating insider’s look at the recent economic collapse, Emanuel Derman—former head quant at Goldman Sachs—explains the collision between mathematical modeling and economics and what makes financial models so dangerous. Though such models imitate the style of physics and employ the language of mathematics, theories in physics aim for a description of reality—but in finance, models can shoot only for a very limited approximation of reality. Derman uses his firsthand experience in financial theory and practice to explain the complicated tangles that have paralyzed the economy. Models.Behaving.Badly. exposes Wall Street’s love affair with models, and shows us why nobody will ever be able to write a model that can encapsulate human behavior.
The interaction between a user and a device forms the foundation of today’s application design. Covering the following topics: A suite of five structural principles helping designers to structure their mockups; An agile method for exploiting desktop eye tracker equipment in combination with mobile devices; An approach to explore large-scale collections based on classification systems; A framework based on the use of modeling and components composition techniques to simplify the development of organizational collaborative systems; A low-cost virtual reality system that provides highly satisfying virtual experiences; Popular hardware and software tools and technologies for developing augmented and virtual reality applications; An implementation to handle connectivity between virtual reality applications and SensAble® Technology Phantom Haptic Devices; The results of a research study implementing a teaching technological strategy to help Down syndrome children develop their reading skills; Platform independent models decreasing the level of cohesion between communication technologies and software for ubiquitous computing; A method for applying gamification as a tool to improve the participation and motivation of people in performing different tasks. New Trends in Interaction, Virtual Reality and Modeling collects the best research from Interacción 2012 and MexIHC 2012, and presents the state-of-the-art in human-computer interaction, user interfaces, user experience and virtual reality. Written by researchers from leading universities, research institutes and industry, this volume forms a valuable source of reference for researchers in HCI and VR.
The nature of an information system; Naming; Relationships; Attributes; Types and categories and sets; Models; The record model; The other three popular models; The modelling of relationships; Elementary concepts; Philosophy.
The volume is based on the papers that were presented at the Interna tional Conference Model-Based Reasoning in Scientific Discovery (MBR'98), held at the Collegio Ghislieri, University of Pavia, Pavia, Italy, in December 1998. The papers explore how scientific thinking uses models and explanatory reasoning to produce creative changes in theories and concepts. The study of diagnostic, visual, spatial, analogical, and temporal rea soning has demonstrated that there are many ways of performing intelligent and creative reasoning that cannot be described with the help only of tradi tional notions of reasoning such as classical logic. Traditional accounts of scientific reasoning have restricted the notion of reasoning primarily to de ductive and inductive arguments. Understanding the contribution of model ing practices to discovery and conceptual change in science requires ex panding scientific reasoning to include complex forms of creative reasoning that are not always successful and can lead to incorrect solutions. The study of these heuristic ways of reasoning is situated at the crossroads of philoso phy, artificial intelligence, cognitive psychology, and logic; that is, at the heart of cognitive science. There are several key ingredients common to the various forms of model based reasoning to be considered in this book. The models are intended as in terpretations of target physical systems, processes, phenomena, or situations. The models are retrieved or constructed on the basis of potentially satisfying salient constraints of the target domain.