الصفحة 2
الصفحة 2
Functional and operatorial statistics
An increasing number of statistical problems and methods involve infinite-dimensional aspects. This is due to the progress of technologies which allow us to store more and more information while modern instruments are able to collect data much more effectively due to their increasingly sophisticated design. This evolution directly concerns statisticians, who have to propose new methodologies while taking into account such high-dimensional data (e.g. continuous processes, functional data, etc.). The numerous applications (micro-arrays, paleo-ecological data, radar waveforms, spectrometric curves, speech recognition, continuous time series, 3-D images, etc.) in various fields (biology, econometrics, environmetrics, the food industry, medical sciences, paper industry, etc.) make researching this statistical topic very worthwhile. This book gathers important contributions on the functional and operatorial statistics fields
Fluconazole : Pharmacology, clinical uses and health effects
Fluconazole is a triazole antifungal drug used in the treatment and prevention of superficial and systemic fungal infections. In this book, the authors present current research in the study of the pharmacology, clinical uses and health effects of fluconazole. Topics discussed include the utilization of fluconazole in adult intensive care units; the use of fluconazole in veterinary species and a description of variances from the human experience as well as findings in veterinary species which may have applicability in human medicine; common clinical uses and in vitro activity features on fluconazole; and the discovery and development of medically-important antifungal agents, particularly the azole derivatives and the development of fluconazole and its clinical applications.
Environment Learning for Indoor Mobile Robots : A Stochastic State Estimation Approach to Simultaneous Localization and Map Building
This monograph covers theoretical aspects of simultaneous localization and map building for mobile robots, such as estimation stability, nonlinear models for the propagation of uncertainties, temporal landmark compatibility, as well as issues pertaining the coupling of control and SLAM. One of the most relevant topics covered in this monograph is the theoretical formalism of partial observability in SLAM. The authors show that the typical approach to SLAM using a Kalman filter results in marginal filter stability, making the final reconstruction estimates dependant on the initial vehicle estimates. However, by anchoring the map to a fixed landmark in the scene, they are able to attain full observability in SLAM, with reduced covariance estimates.
Entrepreneurial Orientation in Academia
In addition to research and education, today’s role of acadamia in the United States also includes the creation of wealth for society. Universities are active in fostering innovation and transferring technology. However, it should be noted that some universities act more as entrepreneurs than others and are more successful in selling licenses and spinning off companies. Based on the concept of entrepreneurial orientation, Jan Boehm elaborates on the relationship between dimensions of entrepreneurial orientation – such as autonomy, innovativeness, proactiveness, competitiveness, risk-taking, and interdisciplinarity – and technology transfer performance of U.S. universities. Using variance-based multivariate analysis and a survey of principal investigators, the author concludes that entrepreneurial orientation within research organizations has a positive impact on technology transfer.
Elements for Physics : Quantities, Qualities, and Intrinsic Theories
While usual presentations of physical theories emphasize the notion of physical quantity, this book shows that there is much to gain when introducing the notion of physical quality. The usual physical quantities simply appear as coordinates over the manifolds representing the physical qualities. This allows to develop physical theories that have a degree of invariance much deeper than the usual one. It is shown that properly developed physical theories contain logarithms and exponentials of tensors: their conspicuous absence in usual theories suggests, in fact, that the fundamental invariance principle stated in this book is lacking in present-day mathematical physics. The book reviews and extends the theory if Lie groups, develops differential geometry, proposing compact definitions of torsion and of curvature, and adapts the usual notion of linear tangent application to the intrinsic point of view proposed for physics. As an illustration, two simple theories are studied with some detail, the theory of heat conduction and the theory of linear elastic media. The equations found differ quantitatively and qualitatively from those usually presented.
Dependence in Probability and Statistics
This book gives a detailed account of some recent developments in the field of probability and statistics for dependent data. The book covers a wide range of topics from Markov chain theory and weak dependence with an emphasis on some recent developments on dynamical systems, to strong dependence in times series and random fields. A special section is devoted to statistical estimation problems and specific applications. The book is written as a succession of papers by some specialists of the field, alternating general surveys, mostly at a level accessible to graduate students in probability and statistics, and more general research papers mainly suitable to researchers in the field. The first part of the book considers some recent developments on weak dependent time series, including some new results for Markov chains as well as some developments on new notions of weak dependence. This part also intends to fill a gap between the probability and statistical literature and the dynamical system literature. The second part presents some new results on strong dependence with a special emphasis on non-linear processes and random fields currently encountered in applications. Finally, in the last part, some general estimation problems are investigated, ranging from rate of convergence of maximum likelihood estimators to efficient estimation in parametric or non-parametric time series models, with an emphasis on applications with non-stationary data.
Deep Learning to See : Towards New Foundations of Computer Vision
Topics and features: Presents a curiosity-driven approach, posing questions to stimulate readers to design novel computational models of vision Offers a rethinking of computer vision, arguing for an approach based on vision in nature, versus regarding visual signals as collections of images Provides an interdisciplinary commentary, aiming to unify computer vision, machine learning, human vision, and computational neuroscience Serving to inspire and stimulate critical reflection and discussion, yet requiring no prior advanced technical knowledge, the text can naturally be paired with classic textbooks on computer vision to better frame the current state of the art, open problems, and novel potential solutions.
Deep learning architecture and application
As one of the fastest-growing topics in machine learning, deep learning algorithms have achieved unprecedented success in recent years. Novel paradigms (such as contrastive learning and few-shot learning) in deep learning and rising neural network architectures (e.g., transformer and masked autoencoder) are dramatically changing the field of data-driven algorithms. More importantly, deep learning models are redefining the next generation of industrial applications spanning image recognition, speech processing, language translation, healthcare, and other sciences. For example, recent advances in deep representation learning are allowing us to learn about protein 3D structures, which sheds new light on fundamental medicine and biology along with potentially bringing in billions of dollars (e.g., in the pharmaceutical market).
Computer Vision Metrics : Survey, Taxonomy, and Analysis
Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features. This book provides necessary background to develop intuition about why interest point detectors and feature descriptors actually work, how they are designed, with observations about tuning the methods for achieving robustness and invariance targets for specific applications. The survey is broader than it is deep, with over 540 references provided to dig deeper. The taxonomy includes search methods, spectra components, descriptor representation, shape, distance functions, accuracy, efficiency, robustness and invariance attributes, and more.
Collecting spatial data : Optimum design of experiments for random fields
The book is concerned with the statistical theory for locating spatial sensors. It bridges the gap between spatial statistics and optimum design theory. The revised edition contains additional material on design for detecting spatial dependence and for estimating parametrized covariance functions.
Magnetism and Accelerator-Based Light Sources : Proceedings of the 7th International School ‘‘Synchrotron Radiation and Magnetism’’, Mittelwihr (France), 2018
Collects the contributions of the seventh school on Magnetism and Synchrotron Radiation held in Mittelwihr, France, from 7 to 12 October 2018. It starts with an introduction to the physics of modern X-ray sources followed by a general overview of magnetism.
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.
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.
Le choix bayésien: Principes et pratique
Covers the so-called Bayesian approach to statistical inference and in particular its decision-making aspects. The bases of this axiomatics (choice of the a priori, optimal decisions, tests and regions of confidence) are discussed in detail, as well as more recent openings of Bayesian analysis such as the choice of models, the use of numerical methods. Stochastic approximation (MCMC), the theory of noninformative laws (Berger-Bernardo axioms) and the relation to the classical theory of admissibility. Each chapter is completed by an extensive series of exercises of increasing difficulty and by bibliographical notes on the themes addressed. This book can be used in a Master's program in Applied Mathematics, Biometrics, Econometrics or any other program that uses quantitative information processing techniques. It only requires a basic course in probability theory and mathematical statistics as a preliminary.
Laws of Nature
The book is concerned with the laws of nature and in particular with the laws of physics. The authors discuss three important questions: First, whether the observed regularities are based on strict "laws of nature" that hold rigorously and without any exception. Second, what we call a "law of nature" is studied by comparing this concept with invariance principles, causality principles, teleological principles and means of predicting future events. Finally, on the basis of these investigations the authors treat the ambitious and intricate third question, why the laws of nature hold. Are there rational reasons for this largely unexplained phenomenon? This book addresses students as well as researchers. It will be an excellent reference for those interested in the philosophical foundations of the natural sciences.
Cambridge and Vienna : Frank P. Ramsey and the Vienna Circle
The Institute Vienna Circle held a conference in 2003, Cambridge and Vienna: Frank P. Ramsey and the Vienna Circle, to commemorate the philosophical and scientific work of Frank Plumpton Ramsey (1903-1930). This Ramsey conference provided historical and biographical perspectives on one of the most gifted thinkers of the Twentieth Century.
Biostatistics and microbiology : A survival manual
This book presents a step-by-step manner that eliminates the greatest obstacle to the learner, which is applying the many processes that comprise a statistical method. The author counters the fear of statistical methods by describing early in the book a step-by-step procedure to perform a statistical method - a process that we will term "the six-step procedure." All of the testing will be performed adhering to six well-defined steps, which will greatly simplify the statistical process. Each step in the sequence must be completed before moving on to the next step.
Biostatistica in radiologia : Progettare, realizzare e scrivere un lavoro scientifico radiologico = Biostatistics in Radiology: Designing, creating and writing a radiological scientific work
The progressive affirmation of evidence-based medicine requires radiology to make a qualitative leap: from demonstrating the ability to see more and better to demonstrating a significant improvement in the health or quality of life of patients.
Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series
This book discusses the statistical methods most often applied for such adjustments, ranging from ad hoc procedures to regression-based models. The latter are emphasized, because of their clarity, ease of application, and superior results. Each topic is illustrated with many real case examples. In order to facilitate understanding of their properties and limitations of the methods discussed, a real data example, the Canada Total Retail Trade Series, is followed throughout the book.This book brings together the scattered literature on these topics and presents them using a consistent notation and a unifying view.
Asymptotic Theory of Statistics and Probability
An encyclopedic treatment of classic as well as contemporary large sample theory, dealing with both statistical problems and probabilistic issues and tools. It is written in an extremely lucid style, with an emphasis on the conceptual discussion of the importance of a problem and the impact and relevance of the theorems. The book has 34 chapters over a wide range of topics, nearly 600 exercises for practice and instruction, and another 300 worked out examples. It also includes a large compendium of 300 useful inequalities on probability, linear algebra, and analysis that are collected together from numerous sources, as an invaluable reference for researchers in statistics, probability, and mathematics.
