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Longevity and Frailty
Contained in this book are the outcome of a colloquium sponsored by Fondation IPSEN in which interdisciplinary perspectives were brought to bear on conceptual, empirical and clinical aspects of this relationship. The result is a unique, innovative and timely blend of papers on topics ranging from frailty concepts in animal models and early Homo sapiens, to documentation of progress in morbidity compression, on the relationships between frailty and impairments and inflammation, and perspectives on long-term health care needs in an aging world.
Long Memory in Economics
When applying the statistical theory of long range dependent (LRD) processes to economics, the strong complexity of macroeconomic and financial variables, compared to standard LRD processes, becomes apparent. In order to get a better understanding of the behaviour of some economic variables, the book assembles three different strands of long memory analysis: statistical literature on the properties of, and tests for, LRD processes; mathematical literature on the stochastic processes involved; models from economic theory providing plausible micro foundations for the occurence of long memory in economics. Each chapter of the book will give a comprehensive survey of the state of the art and the directions that future developments are likely to take. Taken as a whole the book provides an overview of LRD processes which is accessible to economists, econometricians and statisticians.
Logic, language, information and computation ; 15th International Workshop, WoLLIC 2008 Edinburgh, UK, July 1-4, 2008 Proceedings
The papers cover all pertinent subjects in computer science with particular interest in cross-disciplinary topics. Typical areas of interest are: foundations of computing and programming; novel computation models and paradigms; broad notions of proof and belief; formal methods in software and hardware development; logical approach to natural language and reasoning; logics of programs, actions and resources; foundational aspects of information organization, search, flow, sharing, and protection.
Location Theory : A Unified Approach
Although modern location theory is now more than 90 years old, the focus of researchers in this area has been mainly problem oriented. However, a common theory, which keeps the essential characteristics of classical location models, is still missing. This monograph addresses this issue. A flexible location problem called the Ordered Median Problem (OMP) is introduced. For all three main subareas of location theory (continuous, network and discrete location) structural properties of the OMP are presented and solution approaches provided. Numerous illustrations and examples help the reader to become familiar with this new location model.
Local Pattern Detection ; International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers
Introduction The dramatic increase in available computer storage capacity over the last 10 years has led to the creation of very large databases of scienti?c and commercial information. The need to analyze these masses of data has led to the evolution of the new field knowledge discovery in databases (KDD) at the intersection of machine learning, statistics and database technology. Being interdisciplinary by nature, the field offers the opportunity to combine the expertise of different fields into a common objective. Moreover, within each field diverse methods have been developed and justified with respect to different quality criteria. We have to investigate how these methods can contributet o solving the problem of KDD. Traditionally, KDD was seeking to end global models for the data that - plain most of the instances of the database and describe the general structure of the data. Examples are statistical time series models, cluster models, logic programs with high coverageor classi?cation models like decision trees or linear decision functions. In practice, though, the use of these models often is very l- ited, because global models tend to end only the obvious patterns in the data, 1 which domain experts already are aware of . What is really of interest to the users are the local patterns that deviate from the already-known background knowledge. David Hand, who organized a workshop in 2002, proposed the new field of local patterns.
LMI Approach to Analysis and Control of Takagi-Sugeno Fuzzy Systems with Time Delay
A fuzzy system is, in a very broad sense, any fuzzy logic-based system where fuzzy logic can be used either asthebasisfor the representation of different forms of system knowledge or the model for the interactions and relationships among the system variables. Fuzzy systems have proven to be an important tool for modeling complex systems for which, due to complexity or imprecision, classical tools are unsuccessful. There have been diverse fields of applications of fuzzy technology from medicine to management, from engineering to behavioral science, from vehicle control to computational linguistics, and so on. Fuzzy modeling is a conjunction to understand the s- tem’s behavior and build useful mathematical models. Different types of fuzzy models have been proposed in the literature, among which the Takagi-Sugeno (T-S) fuzzy model is a rule-based one suitable for the accurate approximation and identi?cation of a wide class of nonlinear systems.
Liver carcinogenesis : Methods and protocols
Discusses the latest advancements in modern methodologies used to study liver carcinogenesis. The first half of this book describes pertinent preclinical models of hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), established either through orthotopic induction of ectopic implantation. The second half of this book covers a diverse array of techniques applied to characterize the biochemical and cellular composition of hepatic malignancies that operate at the single-cell and histological levels. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and tips on troubleshooting and avoiding known pitfalls.
Linked Democracy : Foundations, Tools, and Applications
This book shows the factors linking information flow, social intelligence, rights management and modelling with epistemic democracy, offering licensed linked data along with information about the rights involved. This model of democracy for the web of data brings new challenges for the social organisation of knowledge, collective innovation, and the coordination of actions. Licensed linked data, licensed linguistic linked data, right expression languages, semantic web regulatory models, electronic institutions, artificial socio-cognitive systems are examples of regulatory and institutional design (regulations by design). The web has been massively populated with both data and services, and semantically structured data, the linked data cloud, facilitates and fosters human-machine interaction. Linked data aims to create ecosystems to make it possible to browse, discover, exploit and reuse data sets for applications. Rights Expression Languages semi-automatically regulate the use and reuse of content.
Linkage in Evolutionary Computation
The whole volume consisting of 19 chapters is divided into 3 parts: Models and Theories; Operators and Frameworks; Applications. This edited volume will serve as a useful guide and reference for researchers who are currently working in the area of linkage. For postgraduate research students, this volume will serve as a good source of reference. It is also suitable as a text for a graduate level course focusing on linkage issues.
Linearization Methods for Stochastic Dynamic Systems
The aim of this book is to give a systematic introduction to and overview of the relatively simple and popular linearization methods available. The scope is limited to models with continous external and parametric excitations, yet these cover the majority of known approaches. The book contains an application chapter with emphasis on vibration analysis of stochastic mechanical structures as well as a chapter devoted to the assessment of the accuracy of the theoretical methods presented, both with respect to numerical and to experimental studies.
Linear Programming and its Applications
This book presents a unified treatment of linear programming. Without sacrificing mathematical rigor, the main emphasis of the book is on models and applications. The most important classes of problems are surveyed and presented by means of mathematical formulations, followed by solution methods and a discussion of a variety of "what-if" scenarios. Non-simplex based solution methods and newer developments such as interior point methods are covered along with a variety of approaches that incorporate multiple objectives in the model.
Linear Optimization Problems with Inexact Data
Linear programming attracted the interest of mathematicians during and after World War II when the first computers were constructed and methods for solving large linear programming problems were sought in connection with specific practical problems—for example, providing logistical support for the U.S. Armed Forces or modeling national economies. Early attempts to apply linear programming methods to solve practical problems failed to satisfy expectations. There were various reasons for the failure. One of them, which is the central topic of this book, was the inexactness of the data used to create the models. This phenomenon, inherent in most pratical problems, has been dealt with in several ways. At first, linear programming models used "average” values of inherently vague coefficients, but the optimal solutions of these models were not always optimal for the original problem itself. Later researchers developed the stochastic linear programming approach, but this too has its limitations. Recently, interest has been given to linear programming problems with data given as intervals, convex sets and/or fuzzy sets. The individual results of these studies have been promising, but the literature has not presented a unified theory. Linear Optimization Problems with Inexact Data attempts to present a comprehensive treatment of linear optimization with inexact data, summarizing existing results and presenting new ones within a unifying framework.
Linear Models for Optimal Test Design
Begins with a reflection on the history of test design--the core activity of all educational and psychological testing. It then presents a standard language for modeling test design problems as instances of multi-objective constrained optimization. The main portion of the book discusses test design models for a large variety of problems from the daily practice of testing, and illustrates their use with the help of numerous empirical examples. The presentation includes models for the assembly of tests to an absolute or relative target for their information functions, classical test assembly, test equating problems, item matching, test splitting, simultaneous assembly of multiple tests, tests with item sets, multidimensional tests, and adaptive test assembly. Two separate chapters are devoted to the questions of how to design item banks for optimal support of programs with fixed and adaptive tests. Linear Models for Optimal Test Design, which does not require any specific mathematical background, has been written to be a helpful resource on the desk of any test specialist.
Linear Models and Generalizations : Least Squares and Alternatives
Gives an up-to-date account of the theory and applications of linear models. The book can be used as a text for courses in statistics at the graduate level and as an accompanying text for courses in other areas. Some of the highlights in this book are as follows. A relatively extensive chapter on matrix theory (Appendix A) provides the necessary tools for proving theorems discussed in the text and offers a selection of classical and modern algebraic results that are useful in research work in econometrics, engineering, and optimization theory. The matrix theory of the last ten years has produced a series of fundamental results aboutthe de?niteness ofmatrices,especially forthe di?erences ofmatrices, which enable superiority comparisons of two biased estimates to be made for the ?rst time. We have attempted to provide a uni?ed theory of inference from linear models with minimal assumptions
Linear and Generalized Linear Mixed Models and Their Applications
This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it has included recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method in the context of mixed models.
Linear and Generalized Linear Mixed Models and Their Applications
This book covers two major classes of mixed effects models—linear mixed models and generalized linear mixed models—and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. It offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it discusses the latest developments and methods in the field, incorporating relevant updates since publication of the first edition. These include advances in high-dimensional linear mixed models in genome-wide association studies (GWAS), advances in inference about generalized linear mixed models with crossed random effects, new methods in mixed model prediction, mixed model selection, and mixed model diagnostics.
Light Shadow Space : Architectural Rendering with Cinema 4D®
The visualization of light in space, its effect on model cubature and scenery, is one of the great challenges in architectural rendering. This is a decisive reason for the use of 3D tools – both for architecture offices and students. This volume features a number of exercises that enable the reader to learn how to light architecture models correctly. Complete virtual 3D scenarios are included that allow for the step-by-step construction of a lighting set up with the help of Cinema 4D® software that creates a realistic spatial impression. The tutorials are complemented by a chapter on the use of Cinema 4D®, importing CAD models and light sources as well as shadow types, which have been revised and expanded in the 9.5 and 10 version.
Life Cycle Investing and Occupational Old-Age Provision in Switzerland
Florian Zainhofer uses the theory of life cycle investing, i.e. how we should optimally choose our savings rate and risky asset share throughout our lives, as a framework to study the implications of a potential BVG individualization. Following an introduction on the Swiss system of old-age provision, the author reviews recent life cycle models of portfolio choice and covers their numerical solution algorithms in depth. He presents an empirical analysis of Swiss workers’ earnings dynamics since these are important determinants of life cycle investment behavior. To further investigate the implications of a flexible contribution rate and risky asset share in the mandatory BVG, the author proposes a model adapted to Swiss conditions and parameterized with the estimated earnings dynamics.
Lewis Fry Richardson : His Intellectual Legacy and Influence in the Social Sciences
A pioneer in meteorology and peace research and remains a towering presence in both fields. This edited volume reviews his work and assesses its influence in the social sciences, notably his work on arms races and their consequences, mathematical models, the size distribution of wars, and geographical features of conflict
Level Crossing Methods in Stochastic Models
Since its inception in 1974, the level crossing approach for analyzing a large class of stochastic models has become increasingly popular among researchers. This volume traces the evolution of level crossing theory for obtaining probability distributions of state variables and demonstrates solution methods in a variety of stochastic models including: queues, inventories, dams, renewal models, counter models, pharmacokinetics, and the natural sciences. Results for both steady-state and transient distributions are given, and numerous examples help the reader apply the method to solve problems faster, more easily, and more intuitively.
