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Ordinal Data Modeling is a comprehensive treatment of ordinal data models from both likelihood and Bayesian perspectives. Written for graduate students and researchers in the statistical and social sciences, this book describes a coherent framework for understanding binary and ordinal regression models, item response models, graded response models, and ROC analyses, and for exposing the close connection between these models. A unique feature of this text is its emphasis on applications. All models developed in the book are motivated by real datasets, and considerable attention is devoted to the description of diagnostic plots and residual analyses. Software and datasets used for all analyses described in the text are available on websites listed in the preface.

This in-depth revision of the successful first edition is one of the only books of its kind to cover the full range of craniomaxillofacial reconstructive and corrective bone surgery. This evolving field has a large number of contributions by worldwide clinicians covering new developments, especially in biomaterials, digital technologies, virtual surgical planning, patient specific implants, and navigation. These topics appeal to Oral and Maxillofacial Surgeons, Plastic Surgeons, ENT/Head and Neck Surgeons, and Neurosurgeons. Complete with updates on popular topics from the first edition, such as advanced jaw reconstruction with stem cells and tissue engineering, wide varieties of microvascular flaps, orthognathic surgery, endoscopic skull base surgery, dental implantology, craniofacial surgery and facial allotransplantation.

In "e;Beyond Fear,"e; Bruce Schneier invites us to take a critical look at not just the threats to our security, but the ways in which we're encouraged to think about security by law enforcement agencies, businesses of all shapes and sizes, and our national governments and militaries. Schneier believes we all can and should be better security consumers, and that the trade-offs we make in the name of security - in terms of cash outlays, taxes, inconvenience, and diminished freedoms - should be part of an ongoing negotiation in our personal, professional, and civic lives, and the subject of an open and informed national discussion.With a well-deserved reputation for original and sometimes iconoclastic thought, Schneier has a lot to say that is provocative, counter-intuitive, and just plain good sense. He explains in detail, for example, why we need to design security systems that don't just work well, but fail well, and why secrecy on the part of government often undermines security.  A skeptic of much that's promised by highly touted technologies like biometrics, Schneier is also a refreshingly positive, problem-solving force in the often self-dramatizing and fear-mongering world of security pundits.Schneier helps the reader to understand the issues at stake, and how to best come to one's own conclusions, including the vast infrastructure we already have in place, and the vaster systems--some useful, others useless or worse--that we're being asked to submit to and pay for.

Applying Generalized Linear Models describes how generalized linear modelling procedures can be used for statistical modelling in many different fields, without becoming lost in problems of statistical inference. Many students, even in relatively advanced statistics courses, do not have an overview whereby they can see that the three areas - linear normal, categorical, and survival models - have much in common. The author shows the unity of many of the commonly used models and provides the reader with a taste of many different areas, such as survival models, time series, and spatial analysis. This book should appeal to applied statisticians and to scientists with a basic grounding in modern statistics. With the many exercises included at the ends of chapters, it will be an excellent text for teaching the fundamental uses of statistical modelling. The reader is assumed to have knowledge of basic statistical principles, whether from a Bayesian, frequentist, or direct likelihood point of view, and should be familiar at least with the analysis of the simpler normal linear models, regression and ANOVA. The author is professor in the biostatistics department at Limburgs University, Diepenbeek, in the social science department at the University of Liege, and in medical statistics at DeMontfort University, Leicester. He is the author of nine other books.

Discussing the most current and pioneering techniques in breast reconstruction without the use of implants, THE ARTISTRY OF BREAST RECONSTRUCTION WITH AUTOLOGOUS TISSUE is the volume every breast surgeon has been waiting for. Focusing not only on how to reconstruct breasts following mastectomy but also on how to achieve the highest degree of aesthetic success possible, this volume describes in detail Dr. Kroll's techniques in using autologous tissue. Over 500 photographs and custom illustrations demonstrate and compare the different techniques used in breast reconstruction with autologous tissue such as conventional (pedicled) TRAM flaps, free TRAM flaps, the extended latissimus dorsi myocutaneous flap, the Rubens fat pad free flap, among others. Also include are chapters on immediate and delayed reconstructions, shaping the breast mound, nipple and areolar reconstruction and choice of technique, follow-up and patient selection. Dr. Kroll's approach to reconstructive breast surgery equally encompasses art and science and both are fully represented in this volume.

The decade prior to publication has seen an explosive growth in com- tational speed and memory and a rapid enrichment in our understa- ing of arti?cial neural networks. These two factors have cooperated to at last provide systems engineers and statisticians with a working, prac- cal, and successful ability to routinely make accurate complex, nonlinear models of such ill-understood phenomena as physical, economic, social, and information-based time series and signals and of the patterns h- den in high-dimensional data. The models are based closely on the data itself and require only little prior understanding of the stochastic mec- nisms underlying these phenomena. Among these models, the feedforward neural networks, also called multilayer perceptrons, have lent themselves to the design of the widest range of successful forecasters, pattern clas- ?ers, controllers, and sensors. In a number of problems in optical character recognition and medical diagnostics, such systems provide state-of-the-art performance and such performance is also expected in speech recognition applications. The successful application of feedforward neural networks to time series forecasting has been multiply demonstrated and quite visibly so in the formation of market funds in which investment decisions are based largely on neural network-based forecasts of performance. The purpose of this monograph, accomplished by exposing the meth- ology driving these developments, is to enable you to engage in these - plications and, by being brought to several research frontiers, to advance the methodology itself.

Our initial motivation for writing this book was the observation from various students that the subject of design and analysis of experiments can seem like "e;a bunch of miscellaneous topics. "e;Webelievethattheidenti?cationoftheobjectivesoftheexperimentandthepractical considerations governing the design form the heart of the subject matter and serve as the link between the various analytical techniques. We also believe that learning about design and analysis of experiments is best achieved by the planning, running, and analyzing of a simple experiment. With these considerations in mind, we have included throughout the book the details of the planning stage of several experiments that were run in the course of teaching our classes. The experiments were run by students in statistics and the applied sciences and are suf?ciently simple that it is possible to discuss the planning of the entire experiment in a few pages, and the procedures can be reproduced by readers of the book. In each of these experiments, we had access to the investigators' actual report, including the dif?culties they came across and how they decided on the treatment factors, the needed number of observations, and the layout of the design. In the later chapters, we have included details of a number of published experiments. The outlines of many other student and published experiments appear as exercises at the ends of the chapters. Complementing the practical aspects of the design are the statistical aspects of the anal ysis. We have developed the theory of estimable functions and analysis of variance with somecare,butatalowmathematicallevel.

This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place. Several variations to the conventional linear mixed model are discussed (a heterogeity model, conditional linear mid models). This book will be of interest to applied statisticians and biomedical researchers in industry, public health organizations, contract research organizations, and academia. The book is explanatory rather than mathematically rigorous. Most analyses were done with the MIXED procedure of the SAS software package, and many of its features are clearly elucidated. How3ever, some other commercially available packages are discussed as well. Great care has been taken in presenting the data analyses in a software-independent fashion. Geert Verbeke is Assistant Professor at the Biostistical Centre of the Katholieke Universiteit Leuven in Belgium. He received the B.S. degree in mathematics (1989) from the Katholieke Universiteit Leuven, the M.S. in biostatistics (1992) from the Limburgs Universitair Centrum, and earned a Ph.D. in biostatistics (1995) from the Katholieke Universiteit Leuven. Dr. Verbeke wrote his dissertation, as well as a number of methodological articles, on various aspects of linear mixed models for longitudinal data analysis. He has held visiting positions at the Gerontology Research Center and the Johns Hopkins University. Geert Molenberghs is Assistant Professor of Biostatistics at the Limburgs Universitair Centrum in Belgium. He received the B.S. degree in mathematics (1988) and a Ph.D. in biostatistics (1993) from the Universiteit Antwerpen. Dr. Molenberghs published methodological work on the analysis of non-response in clinical and epidemiological studies. He serves as an associate editor for Biometrics, Applied Statistics, and Biostatistics, and is an officer of the Belgian Statistical Society. He has held visiting positions at the Harvard School of Public Health.

This book explores the theory of strongly continuous one-parameter semigroups of linear operators. A special feature of the text is an unusually wide range of applications such as to ordinary and partial differential operators, to delay and Volterra equations, and to control theory. Also, the book places an emphasis on philosophical motivation and the historical background.

ItisnowwellknownthatFermat'slasttheoremhasbeenproved. For more than three and a half centuries, mathematicians - from the greatnamestothecleveramateurs-triedtoproveFermat'sfamous statement. The approach was new and involved very sophisticated theories. Finallythelong-soughtproofwasachieved. Thearithmetic theory of elliptic curves, modular forms, Galois representations, and their deformations, developed by many mathematicians, were the tools required to complete the di?cult proof. Linked with this great mathematical feat are the names of TANI- YAMA, SHIMURA, FREY, SERRE, RIBET, WILES, TAYLOR. Their contributions, as well as hints of the proof, are discussed in the Epilogue. This book has not been written with the purpose of presentingtheproofofFermat'stheorem. Onthecontrary, itiswr- ten for amateurs, teachers, and mathematicians curious about the unfolding of the subject. I employ exclusively elementary methods (except in the Epilogue). They have only led to partial solutions but their interest goes beyond Fermat's problem. One cannot stop admiring the results obtained with these limited techniques. Nevertheless, I warn that as far as I can see - which in fact is not much - the methods presented here will not lead to a proof of Fermat's last theorem for all exponents. vi Preface The presentation is self-contained and details are not spared, so the reading should be smooth. Most of the considerations involve ordinary rational numbers and only occasionally some algebraic (non-rational) numbers. For this reason I excluded Kummer's important contributions, which are treated in detail in my book, Classical Theory of Algebraic N- bers and described in my 13 Lectures on Fermat's Last Theorem (new printing, containing an Epilogue about recent results).

This book grew out of notes from several courses that the first author has taught over the past nine years at the California Institute of Technology, and earlier at the Johns Hopkins University, Cornell University, the University of Chicago, and the University of Crete. Our general aim is to provide a modern approach to number theory through a blending of complementary algebraic and analytic perspectives, emphasizing harmonic analysis on topological groups. Our more particular goal is to cover Jolm Tate's visionary thesis, giving virtually all of the necessary analytic details and topological preliminaries-technical prereq- uisites that are often foreign to the typical, more algebraically inclined number theorist. Most of the existing treatments of Tate's thesis, including Tate's own, range from terse to cryptic; our intent is to be more leisurely, more comprehen- sive, and more comprehensible. To this end we have assembled material that has admittedly been treated elsewhere, but not in a single volume with so much detail and not with our particular focus. We address our text to students who have taken a year of graduate-level courses in algebra, analysis, and topology. While our choice of objects and methods is naturally guided by the specific mathematical goals of the text, our approach is by no means narrow. In fact, the subject matter at hand is germane not only to budding number theorists, but also to students of harmonic analysis or the representation theory of Lie groups.

Some 350 years ago, in his Discorsi e Dimostrationi Matematici [Galilei], Galileo Galilei discussed whether or not light propagated with a finite though very high velocity, or with infinite speed, instantaneously. The ques- tion was an open one then, with prominent proponents for either position. For example, Rene Descartes argued on philosophical grounds that light dispersed itself into all of space instantaneously, whereas Galileo was more inclined toward the idea of a finite velocity. In fact, he even reported about an early experiment, which, however, would have to be refined and per- 1 formed again to reach a definite conclusion. "e;Sagredo: ... However, of which kind, and how high might we estimate the velocity of light? Is the appearance instantaneous, momentaneous, or, like other movements, temporal? Could one decide this experimentally? Simplicio: Daily experience teaches us, that the spreading of light be instantaneous; if in a large distance the artillery per- forms shooting exercises, we see the glare of the flame without the ear perceives the sound only after some time delay, while considerable time.

In keeping with my longstanding interest in the surgical corrrection of external ear deformities, I have followed Jack Davis' contributions to this challenging type of reconstructive and aesthetic plastic surgery since I read his first article in 1951. As a longtime good friend of Jack in our roles as editors of the journal, Aesthetic Plastic Surgery, and as past presidents of the International Society of Aesthetic Plastic Surgery (ISAPS), I have kept up- to-date in reading his numerous accomplishments in external ear surgery for these past 46 years. The reader might find it reassuring to learn that in this period of 4t decades, Jack Davis has contributed to our specialty 42 separate articles, lec- tures, discussions, chapters, and other items describing external ear surgery. In 1978 in our journal, Aesthetic Plastic Surgery, he presented an excellent re- view article on "e;History of the Aesthetic Surgery of the Ear,"e; which was co- authored with the assistance of Horacio H. Hernandez. This same subject was also presented in 1985 in a chapter in an ISAPS book devoted to the 'The Creation of Aesthetic Plastic Surgery."e; Even more importantly, and historically, Davis gave us his opus magnum publication in 1987, Aesthetic and Reconstructive Otoplasty, which covered almost every conceivable aspect of these types of surgery in its 581 pages.

This book presents a unified mathematical treatment of diverse problems in the fields of cognitive systems using Clifford, or geometric, algebra. Geometric algebra provides a rich general mathematical framework for the development of the ideas of multilinear algebra, projective and affine geometry, calculus on manifolds, the representation of Lie groups and Lie algebras, and many other areas of applications. By treating a wide spectrum of problems in a common geometric language, the book offers both new insights and new solutions that should be useful to scientists and engineers working in different but related areas of artificial intelligence. It looks at building intelligence systems through the construction of Perception Action Cycles; critical to this concept is incorporating representation and learning in a flexible geometric system. Each chapter is written in accessible terms accompanied by numerous examples and figures that clarify the application of geometric algebra to problems in geometric computing, image processing, computer vision, robotics, neural computing and engineering. Topics and features:*Introduces a nonspecialist to Clifford, or geometric, algebra and it shows applications in artificial intelligence*Thorough discussion of several tasks of signal and image processing, computer vision, robotics, neurocomputing and engineering using the geometric algebra framework*Features the computing frameworks of the linear model n-dimensional affine plane and the nonlinear model of Euclidean space known as the horosphere, and addresses the relationship of these models to conformal, affine and projective geometries*Applications of geometric algebra to other related areas: aeronautics, mechatronics, graphics engineering, and speech processing*Exercises and hints for the development of future computer software packages for extensive calculations in geometric algebra The book is an essential resource for computer scientists, AI researchers, and electrical engineers and includes computer programs to clarify and demonstrate the importance of geometric computing for cognitive systems and artificial autonomous systems research.

Many connections have been found between the theory of analytic functions of one or more complex variables and the study of commutative Banach algebras. While function theory has often been employed to answer algebraic questions such as the existence of idempotents in a Banach algebra, concepts arising from the study of Banach algebras including the maximal ideal space, the Silov boundary, Geason parts, etc. have led to new questions and to new methods of proofs in function theory. This book is concerned with developing some of the principal applications of function theory in several complex variables to Banach algebras. The authors do not presuppose any knowledge of several complex variables on the part of the reader and all relevant material is developed within the text. Furthermore, the book deals with problems of uniform approximation on compact subsets of the space of n complex variables. The third edition of this book contains new material on; maximum modulus algebras and subharmonicity, the hull of a smooth curve, integral kernels, perturbations of the Stone-Weierstrass Theorem, boundaries of analytic varieties, polynomial hulls of sets over the circle, areas, and the topology of hulls. The authors have also included a new chapter containing commentaries on history and recent developments and an updated and expanded reading list.

Some of the key mathematical results are stated without proof in order to make the underlying theory acccessible to a wider audience. The book assumes a knowledge only of basic calculus, matrix algebra, and elementary statistics. The emphasis is on methods and the analysis of data sets. The logic and tools of model-building for stationary and non-stationary time series are developed in detail and numerous exercises, many of which make use of the included computer package, provide the reader with ample opportunity to develop skills in this area. The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Additional topics include harmonic regression, the Burg and Hannan-Rissanen algorithms, unit roots, regression with ARMA errors, structural models, the EM algorithm, generalized state-space models with applications to time series of count data, exponential smoothing, the Holt-Winters and ARAR forecasting algorithms, transfer function models and intervention analysis. Brief introducitons are also given to cointegration and to non-linear, continuous-time and long-memory models. The time series package included in the back of the book is a slightly modified version of the package ITSM, published separately as ITSM for Windows, by Springer-Verlag, 1994. It does not handle such large data sets as ITSM for Windows, but like the latter, runs on IBM-PC compatible computers under either DOS or Windows (version 3.1 or later). The programs are all menu-driven so that the reader can immediately apply the techniques in the book to time series data, with a minimal investment of time in the computational and algorithmic aspects of the analysis.

This book is for all lovers ofmathematics. It is an attempt to under- stand the nature of mathematics from the point of view of its most important early source. Even if the material covered by Euclid may be considered ele- mentary for the most part, the way in which he presents it has set the standard for more than two thousand years. Knowing Euclid's Elements may be ofthe same importance for a mathematician today as knowing Greek architecture is for an architect. Clearly, no con- temporary architect will construct a Doric temple, let alone organize a construction site in the way the ancients did. But for the training ofan architect's aesthetic judgment, a knowledge ofthe Greek her- itage is indispensable. I agree with Peter Hilton when he says that genuine mathematics constitutesone ofthe finest expressions ofthe human spirit, and I may add that here as in so many other instances, we have learned that language ofexpression from the Greeks. While presenting geometry and arithmetic Euclid teaches us es- sential features of mathematics in a much more general sense. He displays the axiomatic foundation of a mathematical theory and its conscious development towards the solution of a specific problem. We see how abstraction works and enforces the strictly deductive presentation ofa theory. We learn what creative definitions are and v VI ----=P:. . :re:. ::::fa=ce how a conceptual grasp leads to toe classification ofthe relevant ob- jects.