ALBERT

Description / Table of Contents: Today, the risks associated with global environmental change and the dangers of extreme climatic and geological events remind us of humanity's dependence on favourable environmental conditions. Our relationships with the landscapes and ecologies that we are a part of, the plants and animals that we share them with, and the natural resources that we extract, lie at the heart of contemporary social and political debates. It is no longer possible to understand key social scientific concerns without at the same time also understanding contemporary patterns of ecosystem change.The Routledge Interna

Description / Table of Contents: "The Earth is a dynamic system. Internal processes, together with external gravitational forces of the Sun, Moon and planets, displace the Earth's mass, impacting on its shape, rotation and gravitational field. Doug Smylie provides a rigorous overview of the dynamical behaviour of the solid Earth, explaining the theory and presenting methods for numerical implementation. Topics include advanced digital analysis, earthquake displacement fields, Free Core Nutations observed by the Very Long Baseline Interferometric technique, translational modes of the solid inner core observed by the superconducting gravimeters, and dynamics of the outer fluid core. This book is supported by freeware computer code, available online for students to implement the theory. Online materials also include a suite of graphics generated from the numerical analysis, combined with 100 graphic examples in the book to make this an ideal tool for researchers and graduate students in the fields of geodesy, seismology and solid earth geophysics"--

Description / Table of Contents: This volume examines the processes responsible for sedimentation in modern glacimarine environments, and how such modern studies can be used as analogues in the interpretation of ancient glacimarine sequences. Sediments released from glaciers grounded in tidewater, floating ice shelves, ice tongues, icebergs and sea ice form complex sequences governed by glaciological, oceanographic, sedimentary and biogenic controls. Ten per cent of the world’s oceans and epicontinental seas contain such active glacimarine environments, but during Cenozoic glacial periods this area was doubled. This book will, therefore, be of relevance to all scientists concerned with high and middle latitude marine environments. The early chapters are concerned largely with processes of sedimentation in modern glacimarine environments; examples are drawn from Alaska, the Canadian Arctic, Svalbard and Antarctica. Studies of ancient sequences, both Cenzoic and pre-Cenozoic, from the Barents Sea, Greenland, Sweden, Alaska and the northwest European continental shelf, form the latter part of the book.

Description / Table of Contents: Bringing together papers written by Norman Fairclough over a 25 year period, Critical Discourse Analysis represents a comprehensive and important contribution to the development of this popular field.  The book is divided into seven sections covering the following themes:  language in relation to ideology and powerdiscourse in processes of social and cultural change dialectics of discourse, dialectical relations between discourse and other moments of social lifemethodology of critical discourse analysis research analysis of political discourse discourse in globalisation and ?transition' critic

Description / Table of Contents: Modern science is a model-building activity. But how are models contructed? How are they related to theories and data? How do they explain complex scientific phenomena, and which role do computer simulations play? To address these questions which are highly relevant to scientists as well as to philosophers of science, 8 leading natural, engineering and social scientists reflect upon their modeling work, and 8 philosophers provide a commentary

Description / Table of Contents: Modern science is a model-building activity. But how are models contructed? How are they related to theories and data? How do they explain complex scientific phenomena, and which role do computer simulations play? To address these questions which are highly relevant to scientists as well as to philosophers of science, 8 leading natural, engineering and social scientists reflect upon their modeling work, and 8 philosophers provide a commentary. U. Gähde and J. H. Wolf, University of Hamburg; S. Hartmann, Ludwig-Maximilians-Universität Munich.

Description / Table of Contents: Provides a deeper understanding of earthquake processes, based on laboratory-derived physical laws and formulae, for researchers, professionals and graduate students

Description / Table of Contents: PREFACE There are problems, when applying statistical inference to the analysis of data, which are not readily solved by the inferential methods of the standard statistical techniques. One example is the computation of confidence intervals for variance components or for functions of variance components. Another example is the statistical inference on the random parameters of the mixed model of the standard statistical techniques or the inference on parameters of nonlinear models. Bayesian analysis gives answers to these problems. The advantage of the Bayesian approach is its conceptual simplicity. It is based on Bayes' theorem only. In general, the posterior distribution for the unknown parameters following from Bayes' theorem can be readily written down. The statistical inference is then solved by this distribution. Often the posterior distribution cannot be integrated analytically. However, this is not a serious drawback, since efficient methods exist for the numerical integration. The results of the standard statistical techniques concerning the linear models can also be derived by the Bayesian inference. These techniques may therefore be considered as special cases of the Bayesian analysis. Thus, the Bayesian inference is more general. Linear models and models closely related to linear models will be assumed for the analysis of the observations which contain the information on the unknown parameters of the models. The models, which are presented, are well suited for a variety of tasks connected with the evaluation of data. When applications are considered, data will be analyzed which have been taken to solve problems of surveying engineering. This does not mean, of course, that the applications are restricted to geodesy. Bayesian statistics may be applied wherever data need to be evaluated, for instance in geophysics. After an introduction the basic concepts of Bayesian inference are presented in Chapter 2. Bayes' theorem is derived and the introduction of prior information for the unknown parameters is discussed. Estimates of the unknown parameters, of confidence regions and the testing of hypotheses are derived and the predictive analysis is treated. Finally techniques for the numerical integration of the integrals are presented which have to be solved for the statistical inference. Chapter 3 introduces models to analyze data for the statistical inference on the unknown parameters and deals with special applications. First the linear model is presented with noninformative and informative priors for the unknown parameters. The agreement with the results of the standard statistical techniques is pointed out. Furthermore, the prediction of data and the linear model not of full rank are discussed. A method for identifying a model is presented and a less sensitive hypothesis test for the standard statistical techniques is derived. The Kalman-Bucy filter for estimating unknown parameters of linear dynamic systems is also given. Nonlinear models are introduced and as an example the fit of a straight line is treated. The resulting posterior distribution for the unknown parameters is analytically not tractable, so that numerical methods have to be applied for the statistical inference. In contrast to the standard statistical techniques, the Bayesian analysis for mixed models does not discriminate between fixed and random parameters, it distinguishes the parameters according to their prior information. The Bayesian inference on the parameters, which correspond to the random parameters of the mixed model of the standard statistical techniques, is therefore readily accomplished. Noninformafive priors of the variance and covariance components are derived for the linear model with unknown variance and covariance components. In addition, informative priors are given. Again, the resulting posterior distributions are analytically not tractable, so that numerical methods have to be applied for the Bayesian inference. The problem of classification is solved by applying the Bayes rule, i.e. the posterior expected loss computed by the predictive density function of the observations is minimized. Robust estimates of the standard statistical techniques, which are maximum likelihood type estimates, the so-called M-estimates, may also be derived by Bayesian inference. But this approach not only leads to the M-estimates, but also any inferential problem for the parameters may be solved. Finally, the reconstruction of digital images is discussed. Numerous methods exist for the analysis of digital images. The Bayesian approach unites some of them and gives them a common theoretical foundation. This is due to the flexibility by which prior information for the unknown parameters can be introduced. It is assumed that the reader has a basic knowledge of the standard statistical techniques. Whenever these results are needed, for easy reference the appropriate page of the book "Parameter Estimation and Hypothesis Testing in Linear Models" by the author (Koch 1988a) is cited. Of course, any other textbook on statistical techniques can serve this purpose. To easily recognize the end of an example or a proof, it is marked by a A or a t~, respectively. I want to thank all colleagues and students who contributed to this book. In particular, I thank Mr. Andreas Busch, Dipl.-Ing., for his suggestions. I also convey my thanks to Mrs. Karin Bauer, who prepared the copy of the book. The assistance of the Springer- Verlag in checking the English text is gratefully acknowledged. The responsibility of errors, of course, remains with the author.

Description / Table of Contents: PART I: BIOGRAPHICAL NOTES ON PROFESSOR MIYAKE --- An Account of My Past Half / S.Miyake / pp. 1-5 --- PART II: NEUTRINOS IN COSMIC RAY RESEARCH --- A Quarter Century of Cosmic Ray Experiments Underground in the Kolar Gold Mines / M. R. Krishnaswamy, M. G. K. Menon, V. S. Narasimham, P. V. Ramanamurty, and B. V. Sreekantan / pp. 7-69 --- The Early Days of Experimental Neutrino Physics / F. Reines / pp. 71-84 --- Underground Experiments on Cosmic Rays / M. Crouch / pp. 85-102 --- PART III: NEUTRINOS IN ASTROPHYSICS --- Neutrinos in High-Energy Astrophysics / C. T. Hill, D. N. Schramm, and T. P. Walker / pp. 103-123 --- Relic Particles from the Primeval Fire-Ball / H. Sato / pp. 125-169 --- Neutrino Physics in Stars and Collapsing Stellar Cores / K. Sato / pp. 171-189 --- The Origin of the Cosmic Radiation / A. W. Wolferidale / pp. 191-199 --- Astrochemical Aspects of the Origin of Cosmic Rays / K. Sakurai and K. Ito / pp. 201-215 --- The Solar Neutrino Problem / K. Sakurai / pp. 217-254 --- PART IV: PUBLICATION LIST OF PROFESSOR MIYAKE / pp. 255-261