Self-checking digital and tabulating equipment was used for calculation of the tables. For ber, bei, ber', and bei', the number of significant figures is either 13 or 14 for the two absolutely larger functions but is generally less for the remaining two. For ker, and so forth, the number of significant figures varies from a minimum of 9 for the absolutely largest function at arguments near 9 to a maximum of 14 elsewhere; 13 or 14 is achieved for all arguments greater than 14. The number of significant figures for the remaining three functions of the second kind is in general less at a given argument than for the absolutely largest function.
Original articles on all aspects of numerical mathematics, book reviews, mathematical tables, and technical notes. Covers advances in numerical analysis, application of computer methods, high speed calculating, and other aids to computation.
A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines. Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed. Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other well-known techniques from machine learning and statistics are discussed, including support-vector machines, neural networks, splines, regularization networks, relevance vector machines and others. Theoretical issues including learning curves and the PAC-Bayesian framework are treated, and several approximation methods for learning with large datasets are discussed. The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.
The topic of hydrogen in an on metals and alloys is important in a number ofdisciplines including solid-state physics, materials science, physical chemistry, and energy technology. This volume treats the dynamics of hydrogen in intermetallic compounds, surface properties, kinetics, and applications of metal hydrides in energy technology. In addition, selected experimental methods are described. The introductory chapter will enable non-specialists to gain an overall picture of the field and to appreciate the relevant scientific issue. The companion volume, Hydrogene in Intermetallic Compounds I, was published as Vol. 63 of Topics in Applied Physics.
HEAT TRANSFER Provides authoritative coverage of the fundamentals of heat transfer, written by one of the most cited authors in all of Engineering Heat Transfer presents the fundamentals of the generation, use, conversion, and exchange of heat between physical systems. A pioneer in establishing heat transfer as a pillar of the modern thermal sciences, Professor Adrian Bejan presents the fundamental concepts and problem-solving methods of the discipline, predicts the evolution of heat transfer configurations, the principles of thermodynamics, and more. Building upon his classic 1993 book Heat Transfer, the author maintains his straightforward scientific approach to teaching essential developments such as Fourier conduction, fins, boundary layer theory, duct flow, scale analysis, and the structure of turbulence. In this new volume, Bejan explores topics and research developments that have emerged during the past decade, including the designing of convective flow and heat and mass transfer, the crucial relationship between configuration and performance, and new populations of configurations such as tapered ducts, plates with multi-scale features, and dendritic fins. Heat Transfer: Evolution, Design and Performance: Covers thermodynamics principles and establishes performance and evolution as fundamental concepts in thermal sciences Demonstrates how principles of physics predict a future with economies of scale, multi-scale design, vascularization, and hierarchical distribution of many small features Explores new work on conduction architecture, convection with nanofluids, boiling and condensation on designed surfaces, and resonance of natural circulation in enclosures Includes numerous examples, problems with solutions, and access to a companion website Heat Transfer: Evolution, Design and Performance is essential reading for undergraduate and graduate students in mechanical and chemical engineering, and for all engineers, physicists, biologists, and earth scientists.
This book surveys the latest advances in radial basis function (RBF) meshless collocation methods which emphasis on recent novel kernel RBFs and new numerical schemes for solving partial differential equations. The RBF collocation methods are inherently free of integration and mesh, and avoid tedious mesh generation involved in standard finite element and boundary element methods. This book focuses primarily on the numerical algorithms, engineering applications, and highlights a large class of novel boundary-type RBF meshless collocation methods. These methods have shown a clear edge over the traditional numerical techniques especially for problems involving infinite domain, moving boundary, thin-walled structures, and inverse problems. Due to the rapid development in RBF meshless collocation methods, there is a need to summarize all these new materials so that they are available to scientists, engineers, and graduate students who are interest to apply these newly developed methods for solving real world’s problems. This book is intended to meet this need. Prof. Wen Chen and Dr. Zhuo-Jia Fu work at Hohai University. Prof. C.S. Chen works at the University of Southern Mississippi.
