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Uncertainty Quantification: An Accelerated Course with Advanced Applications in Computational Engineering (Interdisciplinary Applied Mathematics #47)

This book presents the fundamental notions and advanced mathematical tools in the stochastic modeling of uncertainties and their quantification for large-scale computational models in sciences and engineering. In particular, it focuses in parametric uncertainties, and non-parametric uncertainties with applications from the structural dynamics and vibroacoustics of complex mechanical systems, from micromechanics and multiscale mechanics of heterogeneous materials. Resulting from a course developed by the author, the book begins with a description of the fundamental mathematical tools of probability and statistics that are directly useful for uncertainty quantification. It proceeds with a well carried out description of some basic and advanced methods for constructing stochastic models of uncertainties, paying particular attention to the problem of calibrating and identifying a stochastic model of uncertainty when experimental data is available. This book is intended to be a graduate-level textbook for students as well as professionals interested in the theory, computation, and applications of risk and prediction in science and engineering fields.

Uncertainty Quantification and Predictive Computational Science: A Foundation for Physical Scientists and Engineers

This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties. It addresses a critical knowledge gap in the widespread adoption of simulation in high-consequence decision-making throughout the engineering and physical sciences. Constructing sophisticated techniques for prediction from basic building blocks, the book first reviews the fundamentals that underpin later topics of the book including probability, sampling, and Bayesian statistics. Part II focuses on applying Local Sensitivity Analysis to apportion uncertainty in the model outputs to sources of uncertainty in its inputs. Part III demonstrates techniques for quantifying the impact of parametric uncertainties on a problem, specifically how input uncertainties affect outputs. The final section covers techniques for applying uncertainty quantification to make predictions under uncertainty, including treatment of epistemic uncertainties. It presents the theory and practice of predicting the behavior of a system based on the aggregation of data from simulation, theory, and experiment. The text focuses on simulations based on the solution of systems of partial differential equations and includes in-depth coverage of Monte Carlo methods, basic design of computer experiments, as well as regularized statistical techniques. Code references, in python, appear throughout the text and online as executable code, enabling readers to perform the analysis under discussion. Worked examples from realistic, model problems help readers understand the mechanics of applying the methods. Each chapter ends with several assignable problems. Uncertainty Quantification and Predictive Computational Science fills the growing need for a classroom text for senior undergraduate and early-career graduate students in the engineering and physical sciences and supports independent study by researchers and professionals who must include uncertainty quantification and predictive science in the simulations they develop and/or perform.

Uncertainty Quantification in Computational Fluid Dynamics (Lecture Notes in Computational Science and Engineering #92)

Fluid flows are characterized by uncertain inputs such as random initial data, material and flux coefficients, and boundary conditions. The current volume addresses the pertinent issue of efficiently computing the flow uncertainty, given this initial randomness. It collects seven original review articles that cover improved versions of the Monte Carlo method (the so-called multi-level Monte Carlo method (MLMC)), moment-based stochastic Galerkin methods and modified versions of the stochastic collocation methods that use adaptive stencil selection of the ENO-WENO type in both physical and stochastic space. The methods are also complemented by concrete applications such as flows around aerofoils and rockets, problems of aeroelasticity (fluid-structure interactions), and shallow water flows for propagating water waves. The wealth of numerical examples provide evidence on the suitability of each proposed method as well as comparisons of different approaches.

Uncertainty Quantification in Scientific Computing: 10th IFIP WG 2.5 Working Conference, WoCoUQ 2011, Boulder, CO, USA, August 1-4, 2011, Revised Selected Papers (IFIP Advances in Information and Communication Technology #377)

This book constitutes the refereed post-proceedings of the 10th IFIP WG 2.5 Working Conference on Uncertainty Quantification in Scientific Computing, WoCoUQ 2011, held in Boulder, CO, USA, in August 2011. The 24 revised papers were carefully reviewed and selected from numerous submissions. They are organized in the following topical sections: UQ need: risk, policy, and decision making, UQ theory, UQ tools, UQ practice, and hot topics. The papers are followed by the records of the discussions between the participants and the speaker.

Uncertainty, Rationality, and Agency

This volume concerns Rational Agents - humans, players in a game, software or institutions - which must decide the proper next action in an atmosphere of partial information and uncertainty. The book collects formal accounts of Uncertainty, Rationality and Agency, and also of their interaction. It will benefit researchers in artificial systems which must gather information, reason about it and then make a rational decision on which action to take.

Uncertainty Reasoning for the Semantic Web I: ISWC International Workshop, URSW 2005-2007, Revised Selected and Invited Papers (Lecture Notes in Computer Science #5327)

Uncertainty Reasoning for the Semantic Web II: International Workshops URSW 2008-2010 Held at ISWC and UniDL 2010 Held at Floc, Revised Selected Papers (Lecture Notes in Computer Science #7123)

This book contains revised and significantly extended versions of selected papers from three workshops on Uncertainty Reasoning for the Semantic Web (URSW), held at the International Semantic Web Conferences (ISWC) in 2008, 2009, and 2010 or presented at the first international Workshop on Uncertainty in Description Logics (UniDL), held at the Federated Logic Conference (FLoC) in 2010. The 17 papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on probabilistic and Dempster-Shafer models, fuzzy and possibilistic models, inductive reasoning and machine learning, and hybrid approaches.

Uncertainty Reasoning for the Semantic Web III: ISWC International Workshops, URSW 2011-2013, Revised Selected Papers (Lecture Notes in Computer Science #8816)

This book contains revised and significantly extended versions of selected papers from three workshops on Uncertainty Reasoning for the Semantic Web (URSW), held at the International Semantic Web Conferences (ISWC) in 2011, 2012, and 2013. The 16 papers presented were carefully reviewed and selected from numerous submissions. The papers included in this volume are organized in topical sections on probabilistic and Dempster-Shafer models, fuzzy and possibilistic models, inductive reasoning and machine learning, and hybrid approaches.

Uncertainty Theory (Springer Uncertainty Research)

When no samples are available to estimate a probability distribution, we have to invite some domain experts to evaluate the belief degree that each event will happen. Perhaps some people think that the belief degree should be modeled by subjective probability or fuzzy set theory. However, it is usually inappropriate because both of them may lead to counterintuitive results in this case.In order to rationally deal with belief degrees, uncertainty theory was founded in 2007 and subsequently studied by many researchers. Nowadays, uncertainty theory has become a branch of axiomatic mathematics for modeling belief degrees.This is an introductory textbook on uncertainty theory, uncertain programming, uncertain statistics, uncertain risk analysis, uncertain reliability analysis, uncertain set, uncertain logic, uncertain inference, uncertain process, uncertain calculus, and uncertain differential equation. This textbook also shows applications of uncertainty theory to scheduling, logistics, networks, data mining, control, and finance.

Uncertainty Theory: A Branch of Mathematics for Modeling Human Uncertainty (Studies in Computational Intelligence #300)

Uncertainty theory is a branch of mathematics based on normality, monotonicity, self-duality, countable subadditivity, and product measure axioms. Uncertainty is any concept that satisfies the axioms of uncertainty theory. Thus uncertainty is neither randomness nor fuzziness. It is also known from some surveys that a lot of phenomena do behave like uncertainty. How do we model uncertainty? How do we use uncertainty theory? In order to answer these questions, this book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory, including uncertain programming, uncertain risk analysis, uncertain reliability analysis, uncertain process, uncertain calculus, uncertain differential equation, uncertain logic, uncertain entailment, and uncertain inference. Mathematicians, researchers, engineers, designers, and students in the field of mathematics, information science, operations research, system science, industrial engineering, computer science, artificial intelligence, finance, control, and management science will find this work a stimulating and useful reference.

Uncertainty Theory: An Introduction to its Axiomatic Foundations (Studies in Fuzziness and Soft Computing #154)

As a branch of mathematics that studies the behavior of random, fuzzy and rough events, uncertainty theory is the generic name of probability theory, credibility theory, and trust theory. The main purpose of this book is to provide axiomatic foundations of uncertainty theory. Itwasgenerallybelievedthatthestudyofprobabilitytheorywasstartedby Pascal and Fermat in 1654 when they succeeded in deriving the exact pro- bilities for certain gambling problem. Great progress was achieved when Von Mises initialized the concept of sample space, and ?lled the gape between probability theory and measure theory in 1931. A complete axiomatic fo- dation of probability theory was given by Kolmogoro? in 1933. Since then, probability theory has been developed steadily and has been widely applied in science and engineering. The axiomatic foundation of probability theory will be introduced in Chapter 2. Fuzzy set was initialized by Zadeh via membership function in 1965, and was well developed and applied in a wide variety of real problems. As a fuzzy set of real numbers, the term fuzzy variable was ?rst introduced by Kaufmann in 1975. In order to make a mathematical foundation, Nahmias gave three axioms to de?ne possibility measure in 1978, and Liu gave the fourth axiom to de?ne product possibility measure in 2002. There are three types of measure in the fuzzy world: possibility, necessity, and credibility.

Uncertainty Theory (Studies in Fuzziness and Soft Computing #154)

This book provides a self-contained, comprehensive and up-to-date presentation of uncertainty theory. The purpose is to equip the readers with an axiomatic approach to deal with uncertainty. For this new edition the entire text has been totally rewritten. The chapters on chance theory and uncertainty theory are completely new. Mathematicians, researchers, engineers, designers, and students will find this work a stimulating and useful reference.

Uncoded Multimedia Transmission (Multimedia Computing, Communication and Intelligence)

An uncoded multimedia transmission (UMT) system is one that skips quantization and entropy coding in compression and all subsequent binary operations, including channel coding and bit-to-symbol mapping of modulation. By directly transmitting non-binary symbols with amplitude modulation, the uncoded system avoids the annoying cliff effect observed in the coded transmission system. This advantage makes uncoded transmission more suited to both unicast in varying channel conditions and multicast to heterogeneous users. Particularly, in the first part of Uncoded Multimedia Transmission, we consider how to improve the efficiency of uncoded transmission and make it on par with coded transmission. We then address issues and challenges regarding how to better utilize temporal and spatial correlation of images and video in the uncoded transmission, to achieve the optimal transmission performance. Next, we investigate the resource allocation problem for uncoded transmission, including subchannel, bandwidth and power allocation. By properly allocating these resources, uncoded transmission can achieve higher efficiency and more robust performance. Subsequently, we consider the image and video delivery in MIMO broadcasting networks with diverse channel quality and varying numbers of antennas across receivers. Finally, we investigate the cases where uncoded transmission can be used in conjunction with digital transmission for a balanced efficiency and adaptation capability. This book is the very first monograph in the general area of uncoded multimedia transmission written in a self-contained format. It addresses both the fundamentals and the applications of uncoded transmission. It gives a systematic introduction to the fundamental theory and concepts in this field, and at the same time, also presents specific applications that reveal the great potential and impacts for the technologies generated from the research in this field. By concentrating several important studies and developments currently taking place in the field of uncoded transmission in a single source, this book can reduce the time and cost required to learn and improve skills and knowledge in the field. The authors have been actively working in this field for years, and this book is the final essence of their years of long research in this field. The book may be used as a collection of research notes for researchers in this field, a reference book for practitioners or engineers, as well as a textbook for a graduate advanced seminar in this field or any related fields. The references collected in this book may be used as further reading lists or references for the readers.

Uncoded Multimedia Transmission (Multimedia Computing, Communication and Intelligence)

An uncoded multimedia transmission (UMT) system is one that skips quantization and entropy coding in compression and all subsequent binary operations, including channel coding and bit-to-symbol mapping of modulation. By directly transmitting non-binary symbols with amplitude modulation, the uncoded system avoids the annoying cliff effect observed in the coded transmission system. This advantage makes uncoded transmission more suited to both unicast in varying channel conditions and multicast to heterogeneous users. Particularly, in the first part of Uncoded Multimedia Transmission, we consider how to improve the efficiency of uncoded transmission and make it on par with coded transmission. We then address issues and challenges regarding how to better utilize temporal and spatial correlation of images and video in the uncoded transmission, to achieve the optimal transmission performance. Next, we investigate the resource allocation problem for uncoded transmission, including subchannel, bandwidth and power allocation. By properly allocating these resources, uncoded transmission can achieve higher efficiency and more robust performance. Subsequently, we consider the image and video delivery in MIMO broadcasting networks with diverse channel quality and varying numbers of antennas across receivers. Finally, we investigate the cases where uncoded transmission can be used in conjunction with digital transmission for a balanced efficiency and adaptation capability. This book is the very first monograph in the general area of uncoded multimedia transmission written in a self-contained format. It addresses both the fundamentals and the applications of uncoded transmission. It gives a systematic introduction to the fundamental theory and concepts in this field, and at the same time, also presents specific applications that reveal the great potential and impacts for the technologies generated from the research in this field. By concentrating several important studies and developments currently taking place in the field of uncoded transmission in a single source, this book can reduce the time and cost required to learn and improve skills and knowledge in the field. The authors have been actively working in this field for years, and this book is the final essence of their years of long research in this field. The book may be used as a collection of research notes for researchers in this field, a reference book for practitioners or engineers, as well as a textbook for a graduate advanced seminar in this field or any related fields. The references collected in this book may be used as further reading lists or references for the readers.

Unconstrained Face Recognition (International Series on Biometrics #5)

Face recognition has been actively studied over the past decade and continues to be a big research challenge. Just recently, researchers have begun to investigate face recognition under unconstrained conditions. Unconstrained Face Recognition provides a comprehensive review of this biometric, especially face recognition from video, assembling a collection of novel approaches that are able to recognize human faces under various unconstrained situations. The underlying basis of these approaches is that, unlike conventional face recognition algorithms, they exploit the inherent characteristics of the unconstrained situation and thus improve the recognition performance when compared with conventional algorithms. Unconstrained Face Recognition is structured to meet the needs of a professional audience of researchers and practitioners in industry. This volume is also suitable for advanced-level students in computer science.

Unconventional Computation: 6th International Conference, UC 2007, Kingston, Canada, August 13-17, 2007, Proceedings (Lecture Notes in Computer Science #4618)

There is a world beyond Turing, as more and more computer researchers are demonstrating, but where would you find out about the current leading edge in unconventional computation? Here, in this fascinating work that is the refereed proceedings of the 6th International Conference on Unconventional Computation, held in Kingston, Canada, in August 2007. The 17 revised full papers presented together with 4 invited papers were carefully reviewed and selected for inclusion in the book. All current aspects of unconventional computation are addressed.

Unconventional Computation: 9th International Conference, UC 2010, Tokyo, Japan, June 21-25, 2010, Proceedings (Lecture Notes in Computer Science #6079)

The 9th International Conference on Unconventional Computation, UC 2010, was organized under the auspices of EATCS and Academia Europaea, by the University of Tokyo (Tokyo, Japan), and the Center for Discrete Mathematics and Theoretical Computer Science (Auckland, New Zealand). It was held in Tokyoduring June 21–25,2010(seehttp://arn.local.frs.riken.jp/UC10/). The venue was the Sanjo (Hilltop) Conference Hall at Hongo Campus of the University of Tokyo. Hongo Campus was formerly the residence of the Maeda family, one of the richest feudal lords in the Edo period of Japan. The Japanese garden in the residence is partially preserved, including the pond and the hill on which the conference hall is located. Within walking distance from Hongo Campus are Ueno park with many museums, the Akihabara area, which is now the center of Japanesepop culture, and the Korakuenamusement park/baseball stadium. The International Conference on Unconventional Computation (UC) series (seehttp://www.cs.auckland.ac.nz/CDMTCS/conferences/uc/)isdevotedto all aspects of unconventional computation — theory as well as experiments and applications. Typical, but not exclusive, topics are: natural computing including quantum, cellular, molecular, membrane, neural, and evolutionary computing, as well as chaos and dynamical system-based computing, and various proposals for computational mechanisms that go beyond the Turing model.

Unconventional Computation: 4th International Conference, UC 2005, Sevilla, Spain, October 3-7, Proceedings (Lecture Notes in Computer Science #3699)

The Fourth International Conference on Unconventional Computation, UC 2005, organized under the auspices of EATCS by the Centre for Discrete Mathematics and Theoretical Computer Science and the Department of C- puter Science and Arti?cial Intelligence of the University of Seville, was held in Seville, October 3–7, 2005. Seville, one of the most beautiful cities in Spain, is at its best in October. An explosion of colour and contrast: ?amenco, bull?ghting, and a lively at- sphere in the streets due to the open and friendly nature of its people. The river Guadalquivir, the Cathedral and the Golden Tower are all places full of magic where the visitor can feel the spirit of a city which is eternally romantic. The series of International Conferences Unconventional Computation (UC),https://www.cs.auckland.ac.nz/CDMTCS/conferences/uc/isdevoted to all aspects of unconventional computation, theory as well as experiments and applications. Typical, but not exclusive, topics are: natural computing including quantum, cellular,molecular, neural and evolutionarycomputing; chaosand - namical systems based computing; and various proposals for computations that go beyond the Turing model. The ?rst venue of the Unconventional Computation Conference (formerly called Unconventional Models of Computation) was Auckland, New Zealand in 1998; subsequent sites of the conference were Brussels, Belgium in 2000 and Kobe, Japan in 2002. The titles of the proceedings volumes from past UC Conferences are as follows: 1. C.S. Calude, J. Casti, M.J. Dinneen (eds.). Unconventional Models of C- putation, Springer-Verlag, Singapore, 1998, viii + 426 pp. ISBN: 981-3083- 69-7.

Unconventional Computation: 10th International Conference, UC 2011, Turku, Finland, June 6-10, 2011. Proceedings (Lecture Notes in Computer Science #6714)

This book constitutes the refereed proceedings of the 10th International Conference on Unconventional Computation, UC 2011, held in Turku, Finland, in June 2011. The 17 revised full papers presented together with 6 extended abstracts of invited talks, and 3 extended abstracts of tutorials were carefully reviewed and selected from 33 initial submissions. The papers are devoted to all aspects of unconventional computation theory as well as experiments and applications. Typical topics are: natural computing including quantum, cellular, molecular, membrane, neural, and evolutionary computing, as well as chaos and dynamical system-based computing, and various proposals for computational mechanisms that go beyond the Turing model.

Unconventional Computation: 8th International Conference, UC 2009, Ponta Delgada, Portugal, September 7-11, 2009, Proceedings (Lecture Notes in Computer Science #5715)

This book constitutes the refereed proceedings of the 8th International Conference on Unconventional Computation, UC 2009, held in Ponta Delgada, Portugal, in September 2009. The 18 revised full papers presented together with 8 invited talks, 3 tutorials and 5 posters were carefully reviewed and selected from 40 submissions. The papers are devoted to all aspects of unconventional computation ranging from theoretical and experimental aspects to various applications. Typical topics are: natural computing including quantum; cellular, molecular, neural and evolutionary computing; chaos and dynamical system-based computing; and various proposals for computational mechanisms that go beyond the Turing model.

Unconventional Computation: 7th International Conference, UC 2008, Vienna, Austria, August 25-28, 2008, Proceedings (Lecture Notes in Computer Science #5204)

This book constitutes the refereed proceedings of the 7th International Conference on Unconventional Computation, UC 2008, held in Vienna, Austria, in August 2008. The 16 revised full papers presented together with 4 invited papers were carefully reviewed and selected for inclusion in the book. The papers are devoted to all aspects of unconventional computation ranging from theoretical and experimental aspects to various applications. Typical topics are: natural computing including quantum, cellular, molecular, neural and evolutionary computing, chaos and dynamical system-based computing, and various proposals for computations that go beyond the Turing model.

Unconventional Computation: 5th International Conference, UC 2006, York, UK, September 4-8, 2006, Proceedings (Lecture Notes in Computer Science #4135)

This book constitutes the refereed proceedings of the 5th International Conference on Unconventional Computation, UC 2006, held in York, UK, in September 2006. The 17 revised full papers presented together with four invited full papers were carefully reviewed and selected for inclusion in the book. All current aspects of unconventional computation are addressed - theory as well as experiments and applications.

Unconventional Computation and Natural Computation: 15th International Conference, UCNC 2016, Manchester, UK, July 11-15, 2016, Proceedings (Lecture Notes in Computer Science #9726)

This book constitutes the refereed proceedings of the 15th International Conference on Unconventional Computation and Natural Computation, UCNC 2016, held in Manchester, UK, in July 2016.The 15 revised full papers presented together with 5 invited papers were carefully reviewed and selected from 30 submissions. The papers cover a wide range of topics including molecular, cellular, quantum, optical and chaos computing; cellular automata; neural and evolutionary computation; artificial immune systems; Ant algorithms and swarm intelligence; amorphous computing; membrane computing; computational systems biology and computational neuroscience; and synthetic biology.

Unconventional Computation and Natural Computation: 14th International Conference, UCNC 2015, Auckland, New Zealand, August 30 -- September 3, 2015, Proceedings (Lecture Notes in Computer Science #9252)

This book constitutes the refereed proceedings of the 14th International Conference on Unconventional Computation and Natural Computation, UCNC 2015, held in Auckland, New Zealand, in August/September 2015. The 16 revised full papers were carefully reviewed and selected from 38 submissions. The papers cover a wide range of topics including among others molecular (DNA) computing; quantum computing; optical computing; chaos computing; physarum computing; computation in hyperbolic spaces; collision-based computing; cellular automata; neural computation; evolutionary computation; swarm intelligence; nature-inspired algorithms; artificial immune systems; artificial life; membrane computing; amorphous computing; computational systems biology; genetic networks; protein-protein networks; transport networks; synthetic biology; cellular (in vivo) computing; and computations beyond the Turing model and philosophical aspects of computing.

Unconventional Computation and Natural Computation: 21st International Conference, UCNC 2024, Pohang, South Korea, June 17–21, 2024, Proceedings (Lecture Notes in Computer Science #14776)

This book constitutes the proceedings of the 21st International Conference on Unconventional Computation and Natural Computation, UCNC 2024, held in Pohang, South Korea, during June 17–21, 2024. The 19 full papers included in this book were carefully reviewed and selected from 27 submissions. Typical, but not exclusive, UCNC topics of interest include amorphous computing, cellular automata, chaos and dynamical systems-based computing, cellular, chemical, evolutionary, bacterial, molecular, neural and optical computing, collision-based computing, quantum computing, DNA computing, membrane computing, material computing and programmable matter, super-Turing computation, swarm intelligence, and other nature-inspired algorithms.