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Conception optimale de structures = Optimal structural design
Optimal Structural Design deals with all aspects of shape optimization, parametric, geometric and topological, and gives a large place to numerical algorithms, gradient methods and stochastic methods (with an original contribution by Marc Schoenauer for this last point). In particular, most of the structural optimization algorithms have been implemented in the FreeFem ++ finite element software and the programs are freely available on the web. Optimal structural design is devoted to structural or shape optimization and is intended for a mixed audience of applied mathematicians and mechanicians. It discusses parametric, geometric and topology optimization and gives deterministic and stochastic numerical algorithms (implemented in the FreeFem ++ finite element software).
Computational Intelligence in Reliability Engineering : Evolutionary Techniques in Reliability Analysis and Optimization
This book covers the recent applications of computational intelligence techniques in reliability engineering. This volume contains a survey of the contributions made to the optimal reliability design literature in the resent years and chapters devoted to different applications of a genetic algorithm in reliability engineering and to combinations of this algorithm with other computational intelligence techniques. Genetic algorithms are one of the most widely used metaheuristics, inspired by the optimization procedure that exists in nature, the biological phenomenon of evolution.
Clinical textbook of mood disorders
Mood disorders affect around 1 in 5 people, but the diagnosis and management of these conditions can be challenging. This practical handbook presents a comprehensive overview of these disorders, as well as detailed guidelines for their treatment. The handbook takes a transdisciplinary approach to mood disorders, focusing not only on the biological aspects but also on psychosocial features of importance for optimal diagnosis and management. Content covers nosological considerations, historical aspects, peculiarities along the lifespan, and the associations between mood disorders and other conditions, with a focus on their implications for the optimal management of patients. Practical and evidence-based information is discussed on the role of guidelines related to treatment in selected population groups, including youth, the elderly, and women. With a practical, reader-friendly approach, this book will be invaluable for mental health professionals involved in the treatment of patients with mood disorders, including trainees from different mental health areas.
Clinical pharmacy and therapeutics ; 6th ed.
Combines the skills of an interdisciplinary team of clinicians, pharmacists and nurses to present an integrated understanding of disease processes, evidence-based clinical pharmacology and optimal drug regimes.
Clinical pharmacy and therapeutics ; 5th ed.
Multi-disciplinary textbook continues to draw on the skills of pharmacists, clinicians and nurses to present optimal drug regimens. The authors integrate an understanding of the disease processes with an appreciation of the pathophysiological processes, clinical pharmacy and the evidence base. Each chapter is co-written by a pharmacist and a clinician, and each chapter begins with key points and ends with cases to test understanding.
Mathematical Control Theory and Finance
This book highlights recent developments in mathematical control theory and its applications to finance. It presents a collection of original contributions by distinguished scholars, addressing a large spectrum of problems and techniques. Control theory provides a large set of theoretical and computational tools with applications in a wide range of fields, ranging from "pure" areas of mathematics up to applied sciences like finance. Stochastic optimal control is a well established and important tool of mathematical finance. Other branches of control theory have found comparatively less applications to financial problems, but the exchange of ideas and methods has intensified in recent years. This volume should contribute to establish bridges between these separate fields. The diversity of topics covered as well as the large array of techniques and ideas brought in to obtain the results make this volume a valuable resource for advanced students and researchers.
Mathematical Control Theory : An Introduction
Mathematical Control Theory: An Introduction presents, in a mathematically precise manner, a unified introduction to deterministic control theory. With the exception of a few more advanced concepts required for the final part of the book, the presentation requires only a knowledge of basic facts from linear algebra, differential equations, and calculus. In addition to classical concepts and ideas, the author covers the stabilization of nonlinear systems using topological methods, realization theory for nonlinear systems, impulsive control and positive systems, the control of rigid bodies, the stabilization of infinite dimensional systems, and the solution of minimum energy problems.
Materials Issues for Generation IV Systems ; Status, Open Questions and Challenges
Global warming, shortage of low-cost oil resources and the increasing demand for energy are currently controlling the world's economic expansion while often opposing desires for sustainable and peaceful development. In this context, atomic energy satisfactorily fulfills the criteria of low carbon gas production and high overall yield. However, in the absence of industrial fast-breeders the use of nuclear fuel is not optimal, and the production of high activity waste materials is at a maximum. These are the principal reasons for the development of a new, fourth generation of nuclear reactors, minimizing the undesirable side-effects of current nuclear energy production technology while increasing yields by increasing operation temperatures and opening the way for the industrial production of hydrogen through the decomposition of water.
Markov Decision Processes with Their Applications
Markov decision processes (MDPs), also called stochastic dynamic programming, were first studied in the 1960s. MDPs can be used to model and solve dynamic decision-making problems that are multi-period and occur in stochastic circumstances. There are three basic branches in MDPs: discrete-time MDPs, continuous-time MDPs and semi-Markov decision processes. Starting from these three branches, many generalized MDPs models have been applied to various practical problems. These models include partially observable MDPs, adaptive MDPs, MDPs in stochastic environments, and MDPs with multiple objectives, constraints or imprecise parameters.
Maintenance Theory of Reliability
The book provides a detailed introduction to maintenance policies, updates the reader on the current status of the field and indicates future directions. The reader will learn the theory of maintenance and how to apply models in practice.
Low-Cost Approaches to Promote Physical and Mental Health : Theory, Research, and Practice
Most physical and mental health professionals will agree that their time, space, and funds are generally in short supply, even under optimal conditions. Their participants (clients or patients), too, will admit to similar deficits of time and patience, even with optimal motivation. Overburdened mental health facilities are trying to cope with limited budgets and overworked and underpaid personnel. Low-Cost Approaches to Promote Physical and Mental Health addresses both sides of this shortfall by offering either self-administered or easily administered verbal and non-verbal interventions designed to promote positive health behaviors while requiring little or no outside funding.
Linear Systems Control : Deterministic and Stochastic Methods
Modern control theory and in particular state space or state variable methods can be adapted to the description of many different systems because it depends strongly on physical modeling and physical intuition. The laws of physics are in the form of differential equations and for this reason, this book concentrates on system descriptions in this form. This means coupled systems of linear or nonlinear differential equations. The physical approach is emphasized in this book because it is most natural for complex systems. It also makes what would ordinarily be a difficult mathematical subject into one which can straightforwardly be understood intuitively and which deals with concepts which engineering and science students are already familiar.
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.
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.
Les techniques de monitorage hémodynamique en réanimation = Hemodynamic monitoring techniques in intensive care
The hemodynamic monitoring of intensive care patients is undergoing major changes. Technological advances such as computerization and miniaturization have made it possible to considerably expand the range of assessment tools available at the bedside. Thus, the approach to cardiovascular monitoring - which was once readily "invasive" and global - is gradually becoming non-invasive and locoregional or even tissue. At the same time, the combined evolution of technology and physiological and pathophysiological concepts now provides the clinician with access to a variety of "functional hemodynamic monitoring". The aim of this book is to provide a better understanding of the interest and the limits of the hemodynamic parameters accessible by current hemodynamic monitoring techniques. It thus aims to ensure that the use of these techniques is perfectly mastered by resuscitators and anesthetists-resuscitators so that patient care is ultimately optimal.
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.
Lagrangian and Hamiltonian Methods for Nonlinear Control 2006 ; Proceedings from the 3rd IFAC Workshop, Nagoya, Japan, July 2006
A Differential-Geometric Approach for Bernstein’s Degrees-of-Freedom Problem.- Nonsmooth Riemannian Optimization with Applications to Sphere Packing and Grasping.- Synchronization of Networked Lagrangian Systems.- An Algorithm to Discretize One-Dimensional Distributed Port Hamiltonian Systems.- Virtual Lagrangian Construction Method for Infinitedimensional Systems with Homotopy Operators.- Direct Discrete-Time Design for Sampled-Data Hamiltonian Control Systems.- Kinematic Compensation in Port-Hamiltonian Telemanipulation.- Interconnection and Damping Assignment Passivity-Based Control of a Four-Tank System.- Towards Power-based Control Strategies for a Class of Nonlinear Mechanical Systems.- Power Shaping Control of Nonlinear Systems: A Benchmark Example.- Total Energy Shaping Control of Mechanical Systems: Simplifying the Matching Equations via Coordinate Changes.- Simultaneous Interconnection and Damping Assignment Passivity–Based Control: Two Practical Examples.
Kanban-Controlled Manufacturing Systems
Kanban control systems bear a great potential to significantly improve operations. A company may reap the full benefits of kanban control only after determining an optimal or near-optimal system configuration. To do that, methods are needed to evaluate the performance and operating costs of individual system configurations. We propose an innovative construction-kit approach that enables us to build stochastic analytical models of a large class of single- and multi-product kanban systems. The presented construction-kit approach may be extended and augmented in various directions
