In this unique book, Alexander Lian, a practicing commercial litigator, advances the thesis that the most famous article in American jurisprudence, Oliver Wendell Holmes's “The Path of the Law,” presents Holmes's leading ideas on legal education. Through meticulous analysis, Lian explores Holmes's fundamental ideas on law and its study. He puts “The Path of the Law” within the trajectory of Holmes's jurisprudence, from earliest scholarship to The Common Law to the occasional pieces Holmes wrote or delivered after joining the U.S. Supreme Court. Lian takes a close look at the reactions “The Path of the Law” has evoked, both positive and negative, and restates the essay's core teachings for today's legal educators. Lian convincingly shows that Holmes's “theory of legal study” broke down artificial barriers between theory and practice. For contemporary legal educators, Stereoscopic Law reformulates Holmes's fundamental message that the law must been seen and taught three-dimensionally.
There are certain parallels between the operations Vladimir Putin initiated in the wake of the Ukraine crisis of 2014 and the approach Stalin took in the region during the Second World War.Stalin's ruthless use of scorched earth tactics, the deliberate provocation of reprisals of the occupiers against the civilian population, the destruction of their own villages, the chaotic collection of taxes in kind from the population, accompanied by everyday looting, benders, fornication and violence, fratricidal internal conflicts, the use of doping, the operational use of bacteriological weapons, and even cannibalism -- all this was not a random price for the massive bloodshed and no spontaneous response of the population to the brutality of the German occupation in the 1940s. These were, as Alexander Gogun shows in his historiographical investigation, planned or consciously accepted phenomena and peculiarities of Stalin's warfare tactics.A book that makes an important contribution to the historical context of the current crisis in Ukraine.Es finden sich Parallelen zwischen den von Wladimir Putin im Zuge der Ukraine-Krise 2014 initiierten Operationen in der Ukraine und dem dortigen Vorgehen Stalins während des zweiten Weltkriegs. Stalins rücksichtslose Anwendung der Taktik der verbrannten Erde, das absichtliche Provozieren von Repressalien der Besatzer gegen die Zivilisten, die Vernichtung eigener Dörfer, die chaotische Eintreibung von Naturalsteuern von der Bevölkerung, begleitet von alltäglichen Plünderungen, Besäufnissen, Unzucht und Gewalt, brudermörderische innere Konflikte, die Benutzung von Doping, der operative Einsatz bakteriologischer Waffen und sogar Kannibalismus -- all das war in den 1940er Jahren kein zufälliger Preis für das massenhafte Blutvergießen und auch keine spontane Antwort des Volkes auf die Brutalität der deutschen Besatzungsherrschaft. Dies waren, wie Alexander Gogun in seiner vorliegenden historiographischen Untersuchung aufzeigt, geplante oder bewusst in Kauf genommene Erscheinungen und Besonderheiten der Kriegsführung Stalins.Ein Buch, das einen wichtigen Beitrag zur historischen Einordnung der aktuellen Ukraine-Krise leistet.
Statistical methods for sequential hypothesis testing and changepoint detection have applications across many fields, including quality control, biomedical engineering, communication networks, econometrics, image processing, security, etc. This book presents an overview of methodology in these related areas, providing a synthesis of research from the last few decades. The methods are illustrated through real data examples, and software is referenced where possible. The emphasis is on providing all the theoretical details in a unified framework, with pointers to new research directions.
This book is about conformal prediction, an approach to prediction that originated in machine learning in the late 1990s. The main feature of conformal prediction is the principled treatment of the reliability of predictions. The prediction algorithms described — conformal predictors — are provably valid in the sense that they evaluate the reliability of their own predictions in a way that is neither over-pessimistic nor over-optimistic (the latter being especially dangerous). The approach is still flexible enough to incorporate most of the existing powerful methods of machine learning. The book covers both key conformal predictors and the mathematical analysis of their properties. Algorithmic Learning in a Random World contains, in addition to proofs of validity, results about the efficiency of conformal predictors. The only assumption required for validity is that of "randomness" (the prediction algorithm is presented with independent and identically distributed examples); in later chapters, even the assumption of randomness is significantly relaxed. Interesting results about efficiency are established both under randomness and under stronger assumptions. Since publication of the First Edition in 2005 conformal prediction has found numerous applications in medicine and industry, and is becoming a popular machine-learning technique. This Second Edition contains three new chapters. One is about conformal predictive distributions, which are more informative than the set predictions produced by standard conformal predictors. Another is about the efficiency of ways of testing the assumption of randomness based on conformal prediction. The third new chapter harnesses conformal testing procedures for protecting machine-learning algorithms against changes in the distribution of the data. In addition, the existing chapters have been revised, updated, and expanded.
Sequential Analysis: Hypothesis Testing and Changepoint Detection systematically develops the theory of sequential hypothesis testing and quickest changepoint detection. It also describes important applications in which theoretical results can be used efficiently. The book reviews recent accomplishments in hypothesis testing and changepoint detection both in decision-theoretic (Bayesian) and non-decision-theoretic (non-Bayesian) contexts. The authors not only emphasize traditional binary hypotheses but also substantially more difficult multiple decision problems. They address scenarios with simple hypotheses and more realistic cases of two and finitely many composite hypotheses. The book primarily focuses on practical discrete-time models, with certain continuous-time models also examined when general results can be obtained very similarly in both cases. It treats both conventional i.i.d. and general non-i.i.d. stochastic models in detail, including Markov, hidden Markov, state-space, regression, and autoregression models. Rigorous proofs are given for the most important results. Written by leading authorities in the field, this book covers the theoretical developments and applications of sequential hypothesis testing and sequential quickest changepoint detection in a wide range of engineering and environmental domains. It explains how the theoretical aspects influence the hypothesis testing and changepoint detection problems as well as the design of algorithms.
An easily accessible introduction to log-linear modeling for non-statisticians Highlighting advances that have lent to the topic's distinct, coherent methodology over the past decade, Log-Linear Modeling: Concepts, Interpretation, and Application provides an essential, introductory treatment of the subject, featuring many new and advanced log-linear methods, models, and applications. The book begins with basic coverage of categorical data, and goes on to describe the basics of hierarchical log-linear models as well as decomposing effects in cross-classifications and goodness-of-fit tests. Additional topics include: The generalized linear model (GLM) along with popular methods of coding such as effect coding and dummy coding Parameter interpretation and how to ensure that the parameters reflect the hypotheses being studied Symmetry, rater agreement, homogeneity of association, logistic regression, and reduced designs models Throughout the book, real-world data illustrate the application of models and understanding of the related results. In addition, each chapter utilizes R, SYSTAT®, and §¤EM software, providing readers with an understanding of these programs in the context of hierarchical log-linear modeling. Log-Linear Modeling is an excellent book for courses on categorical data analysis at the upper-undergraduate and graduate levels. It also serves as an excellent reference for applied researchers in virtually any area of study, from medicine and statistics to the social sciences, who analyze empirical data in their everyday work.
Cypriot Arabic, an unwritten language and mother tongue of several hundred bilingual (Arabic/Greek) Maronites from Kormakiti (N.W. Cyprus), evolved from a medieval Arabic colloquial brought to the island by Christian Arab migrants (probably from Asia Minor and Syria). It represents the outcome of a unique linguistic and cultural synthesis drawing on Arabic, Aramaic, and Greek; its Arabic component also shows a hybrid areal profile combining Greater Syrian traits with formal features typical of the contemporary S.E.Anatolian-Mesopotamian dialectal continuum. A number of rare Aramaic substratal elements in Cypriot Arabic suggest a relatively early separation of its parent dialect from mainstream Arabic. This lexicon surveys about 2000 Cypriot Arabic terms against the background of extensive comparative material from the Arabic dialects, Old Arabic, and colloquial and literary varieties of Aramaic. Many Cypriot Arabic terms are here cited with illustrative examples and ethnographic commentary where relevant. Cypriot Arabic is an endangered language; the present glossary is the most comprehensive lexical record of this scientifically intriguing variety of peripheral Arabic. It is primarily intended for orientalists and linguists specializing in comparative Semitics and Arabic dialectology.
The main emphasis of this work is the mathematical theory of quantum channels and their entropic and information characteristics. Quantum information theory is one of the key research areas, since it leads the way to vastly increased computing speeds by using quantum systems to store and process information. Quantum cryptography allows for secure communication of classified information. Research in the field of quantum informatics, including quantum information theory, is in progress in leading scientific centers throughout the world. The past years were marked with impressive progress made by several researchers in solution of some difficult problems, in particular, the additivity of the entropy characteristics of quantum channels. This suggests a need for a book that not only introduces the basic concepts of quantum information theory, but also presents in detail some of the latest achievements.
Advanced Mathematical Tools for Automatic Control Engineers, Volume 2: Stochastic Techniques provides comprehensive discussions on statistical tools for control engineers. The book is divided into four main parts. Part I discusses the fundamentals of probability theory, covering probability spaces, random variables, mathematical expectation, inequalities, and characteristic functions. Part II addresses discrete time processes, including the concepts of random sequences, martingales, and limit theorems. Part III covers continuous time stochastic processes, namely Markov processes, stochastic integrals, and stochastic differential equations. Part IV presents applications of stochastic techniques for dynamic models and filtering, prediction, and smoothing problems. It also discusses the stochastic approximation method and the robust stochastic maximum principle. - Provides comprehensive theory of matrices, real, complex and functional analysis - Provides practical examples of modern optimization methods that can be effectively used in variety of real-world applications - Contains worked proofs of all theorems and propositions presented
Alexander Dierks conceptualizes and applies a more nuanced model of the brand purchase funnel. The re-conceptualization builds on a holistic, theory-based, and practically applicable set of 10 propositions, which capture dynamics of consumers’ contemporary search and decision behavior and allow for a more differentiated assessment of brand performance across the buying cycle. The model’s value add is investigated based on two survey-based studies from the automotive and the electricity industry. Using logistic regression analysis, the author uncovers insightful differences in the determinants of consumers’ purchase decisions depending on the stage of consideration set formation. The findings support the employment of the more nuanced funnel in brand management.
Covering the main fields of mathematics, this handbook focuses on the methods used for obtaining solutions of various classes of mathematical equations that underlie the mathematical modeling of numerous phenomena and processes in science and technology. The authors describe formulas, methods, equations, and solutions that are frequently used in scientific and engineering applications and present classical as well as newer solution methods for various mathematical equations. The book supplies numerous examples, graphs, figures, and diagrams and contains many results in tabular form, including finite sums and series and exact solutions of differential, integral, and functional equations.
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