Download or read book Issues in Water and Power Engineering 2013 Edition written by and published by ScholarlyEditions. This book was released on 2013-05-01 with total page 743 pages. Available in PDF, EPUB and Kindle. Book excerpt: Issues in Water and Power Engineering / 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Fusion Engineering. The editors have built Issues in Water and Power Engineering: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Fusion Engineering in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Water and Power Engineering: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Download or read book Monte Carlo Methods for Particle Transport written by Alireza Haghighat and published by CRC Press. This book was released on 2020-08-09 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fully updated with the latest developments in the eigenvalue Monte Carlo calculations and automatic variance reduction techniques and containing an entirely new chapter on fission matrix and alternative hybrid techniques. This second edition explores the uses of the Monte Carlo method for real-world applications, explaining its concepts and limitations. Featuring illustrative examples, mathematical derivations, computer algorithms, and homework problems, it is an ideal textbook and practical guide for nuclear engineers and scientists looking into the applications of the Monte Carlo method, in addition to students in physics and engineering, and those engaged in the advancement of the Monte Carlo methods. Describes general and particle-transport-specific automated variance reduction techniques Presents Monte Carlo particle transport eigenvalue issues and methodologies to address these issues Presents detailed derivation of existing and advanced formulations and algorithms with real-world examples from the author’s research activities

Download or read book Monte Carlo Methods for Equilibrium Solutions in Neutron Multiplication written by E. L. Kaplan and published by . This book was released on 1958 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Transactions of the American Nuclear Society written by American Nuclear Society and published by . This book was released on 2001 with total page 952 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Graph Representation Learning written by William L. William L. Hamilton and published by Springer Nature. This book was released on 2022-06-01 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.

Download or read book Information Physics and Computation written by Marc Mézard and published by Oxford University Press. This book was released on 2009-01-22 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: A very active field of research is emerging at the frontier of statistical physics, theoretical computer science/discrete mathematics, and coding/information theory. This book sets up a common language and pool of concepts, accessible to students and researchers from each of these fields.

Download or read book Theory Application and Implementation of Monte Carlo Method in Science and Technology written by and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Data Science and Machine Learning written by Dirk P. Kroese and published by CRC Press. This book was released on 2019-11-20 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code

Download or read book Core Statistics written by Simon N. Wood and published by Cambridge University Press. This book was released on 2015-04-13 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: Core Statistics is a compact starter course on the theory, models, and computational tools needed to make informed use of powerful statistical methods.

Download or read book A Monte Carlo Primer written by Stephen A. Dupree and published by Springer Science & Business Media. This book was released on 2002 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: The mathematical technique of Monte Carlo, as applied to the transport of sub-atomic particles, has been described in numerous reports and books since its formal development in the 1940s. Most of these instructional efforts have been directed either at the mathematical basis of the technique or at its practical application as embodied in the several large, formal computer codes available for performing Monte Carlo transport calculations. This book attempts to fill what appears to be a gap in this Monte Carlo literature between the mathematics and the software. Thus, while the mathematical basis for Monte Carlo transport is covered in some detail, emphasis is placed on the application of the technique to the solution of practical radiation transport problems. This is done by using the PC as the basic teaching tool. This book assumes the reader has a knowledge of integral calculus, neutron transport theory, and Fortran programming. It also assumes the reader has available a PC with a Fortran compiler. Any PC of reasonable size should be adequate to reproduce the examples or solve the exercises contained herein. The authors believe it is important for the reader to execute these examples and exercises, and by doing so to become accomplished at preparing appropriate software for solving radiation transport problems using Monte Carlo. The step from the software described in this book to the use of production Monte Carlo codes should be straightforward.

Download or read book Introduction to Statistics and Data Analysis written by Roxy Peck and published by . This book was released on 2015-03-27 with total page 844 pages. Available in PDF, EPUB and Kindle. Book excerpt: INTRODUCTION TO STATISTICS AND DATA ANALYSIS introduces you to the study of statistics and data analysis by using real data and attention-grabbing examples. The authors guide you through an intuition-based learning process that stresses interpretation and communication of statistical information. Simple notation--including frequent substitution of words for symbols--helps you grasp concepts and cement your comprehension. You'll also find coverage of most major technologies as a problem-solving tool, plus hands-on activities in each chapter that allow you to practice statistics firsthand.

Download or read book Fast Spectrum Reactors written by Alan E. Waltar and published by Springer Science & Business Media. This book was released on 2011-09-28 with total page 717 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a complete update of the classic 1981 FAST BREEDER REACTORS textbook authored by Alan E. Waltar and Albert B. Reynolds, which , along with the Russian translation, served as a major reference book for fast reactors systems. Major updates include transmutation physics (a key technology to substantially ameliorate issues associated with the storage of high-level nuclear waste ), advances in fuels and materials technology (including metal fuels and cladding materials capable of high-temperature and high burnup), and new approaches to reactor safety (including passive safety technology), New chapters on gas-cooled and lead-cooled fast spectrum reactors are also included. Key international experts contributing to the text include Chaim Braun, (Stanford University) Ronald Omberg, (Pacific Northwest National Laboratory, Massimo Salvatores (CEA, France), Baldev Raj, (Indira Gandhi Center for Atomic Research, India) , John Sackett (Argonne National Laboratory), Kevan Weaver, (TerraPower Corporation) ,James Seinicki(Argonne National Laboratory). Russell Stachowski (General Electric), Toshikazu Takeda (University of Fukui, Japan), and Yoshitaka Chikazawa (Japan Atomic Energy Agency).

Download or read book Econometric Models For Industrial Organization written by Matthew Shum and published by World Scientific. This book was released on 2016-12-14 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: Economic Models for Industrial Organization focuses on the specification and estimation of econometric models for research in industrial organization. In recent decades, empirical work in industrial organization has moved towards dynamic and equilibrium models, involving econometric methods which have features distinct from those used in other areas of applied economics. These lecture notes, aimed for a first or second-year PhD course, motivate and explain these econometric methods, starting from simple models and building to models with the complexity observed in typical research papers. The covered topics include discrete-choice demand analysis, models of dynamic behavior and dynamic games, multiple equilibria in entry games and partial identification, and auction models.

Download or read book Statistical Mechanics written by James Sethna and published by OUP Oxford. This book was released on 2006-04-07 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: In each generation, scientists must redefine their fields: abstracting, simplifying and distilling the previous standard topics to make room for new advances and methods. Sethna's book takes this step for statistical mechanics - a field rooted in physics and chemistry whose ideas and methods are now central to information theory, complexity, and modern biology. Aimed at advanced undergraduates and early graduate students in all of these fields, Sethna limits his main presentation to the topics that future mathematicians and biologists, as well as physicists and chemists, will find fascinating and central to their work. The amazing breadth of the field is reflected in the author's large supply of carefully crafted exercises, each an introduction to a whole field of study: everything from chaos through information theory to life at the end of the universe.

Download or read book Dynamical Modelling Estimation in Wastewater Treatment Processes written by D. Dochain and published by IWA Publishing. This book was released on 2001-12-01 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Environmental quality is becoming an increasing concern in our society. In that context, waste and wastewater treatment, and more specifically biological wastewater treatment processes play an important role. In this book, we concentrate on the mathematical modelling of these processes. The main purpose is to provide the increasing number of professionals who are using models to design, optimise and control wastewater treatment processes with the necessary background for their activities of model building, selection and calibration. The book deals specifically with dynamic models because they allow us to describe the behaviour of treatment plants under the highly dynamic conditions that we want them to operate (e.g. Sequencing Batch Reactors) or we have to operate them (e.g. storm conditions, spills). Further extension is provided to new reactor systems for which partial differential equation descriptions are necessary to account for their distributed parameter nature (e.g. settlers, fixed bed reactors). The model building exercise is introduced as a step-wise activity that, in this book, starts from mass balancing principles. In many cases, different hypotheses and their corresponding models can be proposed for a particular process. It is therefore essential to be able to select from these candidate models in an objective manner. To this end, structure characterisation methods are introduced. Important sections of the book deal with the collection of high quality data using optimal experimental design, parameter estimation techniques for calibration and the on-line use of models in state and parameter estimators. Contents Dynamical Modelling Dynamical Mass Balance Model Building and Analysis Structure Characterisation (SC) Structural Identifiability Practical Identifiability and Optimal Experiment Design for Parameter Estimation (OED/PE) Estimation of Model Parameters Recursive State and Parameter Estimation Glossary Nomenclature

Download or read book Fundamentals of Semiconductors written by Peter YU and published by Springer Science & Business Media. This book was released on 2007-05-08 with total page 651 pages. Available in PDF, EPUB and Kindle. Book excerpt: Excellent bridge between general solid-state physics textbook and research articles packed with providing detailed explanations of the electronic, vibrational, transport, and optical properties of semiconductors "The most striking feature of the book is its modern outlook ... provides a wonderful foundation. The most wonderful feature is its efficient style of exposition ... an excellent book." Physics Today "Presents the theoretical derivations carefully and in detail and gives thorough discussions of the experimental results it presents. This makes it an excellent textbook both for learners and for more experienced researchers wishing to check facts. I have enjoyed reading it and strongly recommend it as a text for anyone working with semiconductors ... I know of no better text ... I am sure most semiconductor physicists will find this book useful and I recommend it to them." Contemporary Physics Offers much new material: an extensive appendix about the important and by now well-established, deep center known as the DX center, additional problems and the solutions to over fifty of the problems at the end of the various chapters.

Download or read book Statistical Foundations of Data Science written by Jianqing Fan and published by CRC Press. This book was released on 2020-09-21 with total page 942 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.