الصفحة 8
الصفحة 8
Matematica generale con il calcolatore
By introducing mathematical objects, it teaches students how to use a computer to perform numerical and symbolic calculations, define a function and calculate its values, plot and explore graphs, and execute simple algorithms. The course is rich in examples, applications, and models, drawn from economics, physics, biology, statistics, and mathematics itself. The analysis of these models constitutes, in a certain sense, the true purpose of the mathematical theory covered. Automatic calculation tools (mathematics software, spreadsheets) are used extensively to explore and illustrate concepts and properties. Mathcad® software, in particular, was used, both as a calculation tool and as a simple yet powerful programming language. Considerable space is devoted to approximation, emphasizing the distinction between numerical and symbolic calculation; to algorithms as a synthesis of the syntactic and semantic aspects of mathematical objects; and to computer simulation, interpreted as a "physical" experiment and a source of conjecture. The ability to use a calculator marks a sort of "democratization" of mathematics: even complex results, which have always required a broad background of knowledge and laborious calculations, are now quickly accessible to anyone who understands the meaning of mathematical objects and knows how to use the syntax.
Macroscopic Transport Equations for Rarefied Gas Flows : Approximation Methods in Kinetic Theory
This book discusses classical and modern methods to derive macroscopic transport equations for rarefied gases from the Boltzmann equation, for small and moderate Knudsen numbers, i.e.as well as the new order of magnitude method, which avoids the short-comings of the classical methods, but retains their benefits.
Machine learning methods for reverse engineering of defective structured surfaces
Pascal Laube presents machine learning approaches for three key problems of reverse engineering of defective structured surfaces: parametrization of curves and surfaces, geometric primitive classification and inpainting of high-resolution textures. The proposed methods aim to improve the reconstruction quality while further automating the process. The contributions demonstrate that machine learning can be a viable part of the CAD reverse engineering pipeline.
Machine learning for risk calculations : A practitioner's view
Fundamental Approximation Methods. Machine Learning -- Deep Neural Nets -- Chebyshev Tensors -- The toolkit - plugging in approximation methods. Introduction: why is a toolkit needed -- Composition techniques -- Tensors in TT format and Tensor Extension Algorithms -- Sliding Technique -- The Jacobian projection technique -- Hybrid solutions - approximation methods and the toolkit.
Lung cancer : causes, diagnosis, treatment
Lung cancer remains the leading cause of cancer-related deaths in the United States and the world - responsible for approximately 1.8 million deaths annually Lung cancer is still expected to cause more than 4 million deaths over the next 50 years. Thus, in addition to tobacco control efforts, a focus on early detection and treatment interventions will be critical to further reducing the burden of lung cancer...
Longs COVID-19 patients
Nearly 250 million people around the world have recovered from Covid-19. But here, the word "recovered" refers only to the acute phase of the illness. Approximately 10 and 40 percent of Covid patients continue to experience symptoms several weeks to months after falling sick, a nebulous condition now referred to as post-Covid condition, or long Covid. In long Covid, we are witnessing the emergence of a legitimate new illness, officially recognized by the World Health Organization's International Classification of Diseases...
Logistics Systems Analysis
It has two new sections, a new appendix, and more than half a dozen new figures. A few references have also been added, Much of the new material is based on work , The financial support of the National Science Foundation and the Volvo Foundations Center of Excellence for the Future of Urban Transportation at U. C. Berkeley is also acknowledged. The new appendix presents the logic behind the traveling salesman and vehicle routing results used in Sec. 4. 2 to describe the transportation ope- tion; Chapter 4 is more self-contained as a result. New section 5. 6 int- duces and evaluates a general method that automatically translates the c- tinuum approximation recipes of Chapters 4 and 5 into discrete system designs. This closes a gap in previous editions. Other additions include an explanation of how to develop system designs that can efficiently acc- modate real-time control strategies to manage uncertainty (new section 4. 6. 3), and extensions of the many-to-many design ideas of Chap. 6
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.
Light Scattering by Optically Soft Particles: Theory and Applications
Deals with a particular class of approximation methods in the context of light scattering by small particles. This class of approximations has been termed as eikonal or soft particle approximations. The eikonal approximation was studied extensively in the potential scattering and then adopted in optical scattering problems. In this context, the eikonal and other soft particle approximations pertain to scatterers whose relative refractive index compared to surrounding medium is close to unity. The study of these approximations is very important because soft particles occur abundantly in nature. For example, the particles that occur in ocean optics, biomedical optics, atmospheric optics and in many industrial applications can be classified as soft particles. This book was written in recognition of the long-standing and current interest in the field of scattering approximations for soft particles. It should prove to be a useful addition for researchers in the field of light scattering.
Learning Classifier Systems ; International Workshops, IWLCS 2003-2005, Revised Selected Papers
The work embodied in this volume was presented across three consecutive e- tions of the International Workshop on Learning Classi?er Systems that took place in Chicago (2003), Seattle (2004), and Washington (2005). The Genetic and Evolutionary Computation Conference, the main ACM SIGEvo conference, hosted these three editions.
Learning Classifier Systems ; 10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006 and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007, Revised Selected Papers
Constitutes the thoroughly refereed joint post-conference proceedings of two consecutive International Workshops on Learning Classifier Systems that took place in Seattle, WA, USA in July 2006, and in London, UK, in July 2007 - all hosted by the Genetic and Evolutionary Computation Conference, GECCO.The 14 revised full papers presented were carefully reviewed and selected from the workshop contributions. The papers are organized in topical sections on knowledge representation, analysis of the system, mechanisms, new directions, as well as applications.
Le dépistage du cancer du col de lutérus = Cervical cancer screening
Each year, cervical cancer kills approximately 1,000 people in France, making it the fifth leading cause of cancer death and the eighth most common cancer among women. While eradicating cervical cancer is not possible, a national screening campaign should significantly reduce its incidence. This campaign should be based, in particular, on the systematic use of Pap smears. Conventional Pap smears have already reduced the number of invasive cancers by more than 50%. Improving them requires optimizing their sensitivity. This book details the natural history of cervical cancer, its incidence and mortality, and the various aspects of screening: general principles, the French screening program, the different types of Pap smears, the role and contribution of the HPV test, the management of abnormal Pap smears, the role of colposcopy, and the follow-up of treated women. It is intended for all those involved in this screening : specialist interns and gynecologists, pathologists and biologists, public health physicians, but also general practitioners whose role in screening is privileged since they are at the forefront of medical demand.
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.
Large-Scale Scientific Computing ; 6th International Conference, LSSC 2007, Sozopol, Bulgaria, June 5-9, 2007. Revised Papers
The 6th International Conference on Large-Scale Scienti?c Computations (LSSC 2007) was held in Sozopol, Bulgaria, June 5–9, 2007. The conference was organized by the Institute for Parallel Processing at the Bulgarian Academy of Sciences in cooperation with SIAM (Society for Industrial and Applied Ma- ematics). Partial support was also provided from project BIS-21++ funded by the European Commission in FP6 INCO via grant 016639/2005. The conference was devoted to the 60th anniversary of Richard E. Professor Ewing is internati- ally well known with his contributions in applied mathematics, mathematical modeling, and large-scale scientific computations.
Large-Scale Cognitive Assessment : Analyzing PIAAC Data
Summarises existing analysing techniques using data from PIAAC, a study initiated by the OECD that assesses key cognitive and occupational skills of the adult population in more than 40 countries. The approximately 65 PIAAC datasets that has been published worldwide to date has been widely received and used by an interdisciplinary research community
Knowledge Representation Techniques : A Rough Set Approach
The basis for the material in this book centers around a long term research project with autonomous unmanned aerial vehicle systems. One of the main research topics in the project is knowledge representation and reasoning. The focus of the research has been on the development of tractable combinations of approximate and nonmonotonic reasoning systems. The techniques developed are based on intuitions from rough set theory. Efforts have been made to take theory into practice by instantiating research results in the context of traditional relational database or deductive database systems.
Knowledge Processing with Interval and Soft Computing
In particular, these chapters cover computing techniques for interval linear systems of equations, interval matrix singular-value decomposition, interval function approximation, and decision making with statistical and graph-based data processing. To enable these applications, the book presents a standards-based object-oriented interval computing environment in C++.
Jets From Young Stars III : Numerical MHD and Instabilities
This volume contains the lecture notes of the Third JETSET School on Jets from Young Stars focussing on Numerical MHD and Instabilities. The introductory lectures presented here cover the basic concepts of the numerical methods for the integration of hydrodynamic and magnetohydrodynamic equations and of the applications of these methods to the treatment of the instabilities relevant for the physics of stellar jets. The first part of the book contains an introduction to the finite difference and finite volume methods for computing the solutions of hyperbolic partial differential equations and a discussion of approximate Riemann solvers for both hydrodynamic and magnetohydrodynamic problems. The second part is devoted to the discussion of some of the main instability processes that may take place in stellar jets, namely: the Kelvin-Helmholtz, the radiative shock, the pressure driven and the thermal instabilities.
Java Methods for Financial Engineering : Applications in Finance and Investment
This book is structured around the main theories and models used by practitioners to engineer finance and investment tools. The methods developed and implemented in the text are organized as chapters which cover the core areas.
Iterative Approximation of Fixed Points
The aim of this monograph is to give a unified introductory treatment of the most important iterative methods for constructing fixed points of nonlinear contractive type mappings. It summarizes the most significant contributions in the area by presenting, for each iterative method considered (Picard iteration, Krasnoselskij iteration, Mann iteration, Ishikawa iteration etc.), some of the most relevant, interesting, representative and actual convergence theorems. Applications to the solution of nonlinear operator equations as well as the appropriate error analysis of the main iterative methods, are also presented.
