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Meaning-Based Translation is designed for training beginning translators and organized chapter by chapter as drill material for the textbook "Meaning-Based Translation." The textbook emphasizes the importance of a translation being accurate, clear and natural and the exercises give the student practice in achieving this goal. The exercises follow closely the content of the textbook since this is a drill manual for added practice. The textbook has some exercises as well, but the workbook provides additional practice from one basic source, thus giving students a wider variety of problems to solve during practice time. It also provides material that can be used as homework or as testing material..
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This book presents an innovative synthesis of methods used to study the problems of equivalence and symmetry that arise in a variety of mathematical fields and physical applications. It draws on a wide range of disciplines, including geometry, analysis, applied mathematics, and algebra. Dr. Olver develops systematic and constructive methods for solving equivalence problems and calculating symmetries, and applies them to a variety of mathematical systems, including differential equations, variational problems, manifolds, Riemannian metrics, polynomials, and differential operators. He emphasizes the construction and classification of invariants and reductions of complicated objects to simple canonical forms. This book will be a valuable resource for students and researchers in geometry, analysis, algebra, mathematical physics and related fields..
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Equivalence testing has grown significantly in importance over the last two decades, especially as its relevance to a variety of applications has become understood. Yet published work on the general methodology remains scattered in specialists' journals, and for the most part, it focuses on the relatively narrow topic of bioequivalence assessment.With a far broader perspective, Testing Statistical Hypotheses of Equivalence provides the first comprehensive treatment of statistical equivalence testing. The author addresses a spectrum of specific, two-sided equivalence testing problems, from the one-sample problem with normally distributed observations of fixed known variance to problems involving several samples and multivariate data. The treatment includes a concise review of basic mathematical results on optimal tests for equivalence, and the author makes available on the Internet a collection of computer programs that allow easy implementation of the methods presented.In a field as complex and rich in potential applications as equivalence testing, Testing Statistical Hypotheses of Equivalence stands alone as a coherent reference that furnishes both the theoretical and practical tools needed for dealing with equivalence trials of any complexity and in any phase. .
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Our civilization employs increasingly complex human-made systems, such as large-scale electric power grids, air traffic control systems, manufacturing plants and supply chains, the Internet and other communication networks. Performance evaluation of these systems is accomplished by using simulation models rather than experiment with the real systems. However, these systems operate and evolve in time via human-made rules of operation which are difficult to describe and capture by succinct mathematical models. And while simulation models are often used for design validation and other purposes, computational constraints and the changing nature of the problem domain make them unsuitable for optimization purposes.

If we accept the need for search based methods as a complement to the more established analytical techniques, then quickly narrowing the search for optimum performance (ordinal optimization) is more important than accurately estimating the values of system performance during the process of optimization (cardinal optimization). The purpose of this book is to address the difficulties of simulation optimization problems — the optimization of complex systems via simulation models or other computation-intensive models involving possible stochastic effects and discrete choices. This book will establish the distinct advantages of the "softer" ordinal approach for search-based type problems, analyze some of its general properties, and show the many orders of magnitude improvement in computational efficiency that is possible. As such, the book is complementary to existing optimization literature. The tools described here do not replace but can be used separately or in conjunction with other methodological tools of optimization.

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This book develops rigorous foundations for parametrized homotopy theory, which is the algebraic topology of spaces and spectra that are continuously parametrized by the points of a base space. It also begins the systematic study of parametrized homology and cohomology theories. The parametrized world provides the natural home for many classical notions and results, such as orientation theory, the Thom isomorphism, Atiyah and Poincaré duality, transfer maps, the Adams and Wirthmüller isomorphisms, and the Serre and Eilenberg-Moore spectral sequences. But in addition to providing a clearer conceptual outlook on these classical notions, it also provides powerful methods to study new phenomena, such as twisted $K$-theory, and to make new constructions, such as iterated Thom spectra. Duality theory in the parametrized setting is particularly illuminating and comes in two flavors. One allows the construction and analysis of transfer maps, and a quite different one relates parametrized homology to parametrized cohomology. The latter is based formally on a new theory of duality in symmetric bicategories that is of considerable independent interest. The text brings together many recent developments in homotopy theory. It provides a highly structured theory of parametrized spectra, and it extends parametrized homotopy theory to the equivariant setting. The theory of topological model categories is given a more thorough treatment than is available in the literature. This is used, together with an interesting blend of classical methods, to resolve basic foundational problems that have no nonparametrized counterparts..
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