Scientific computing has become an indispensable tool in numerous fields, such as physics, mechanics, biology, finance and industry. For example, it enables us, thanks to efficient algorithms adapted to current computers, to simulate, without the help of models or experimentations, the deflection of beams in bending, the sound level in a theater room or a fluid flowing around an aircraft wing. This book presents the scientific computing techniques applied to parallel computing for the numerical simulation of large-scale problems; these problems result from systems modeled by partial differential equations. Computing concepts will be tackled via examples. Implementation and programming techniques resulting from the finite element method will be presented for direct solvers, iterative solvers and domain decomposition methods, along with an introduction to MPI and OpenMP.

Discourse analysis and rhetoric are very much developed in communication, linguistics, cognitive science and artificial intelligence. Besides theoretical investigations, discourse analysis is central in a number of application areas such as dialogue and negotiation, the semantic web, question answering or authoring systems. Music is also a natural language, more abstract and mathematical, which follows very strict construction principles. However, there is very limited and no recent literature on Music Discourse analysis using computational principles. This book aims at developing a central issue in musical discourse: modeling rhetoric and argumentation. It also contributes to the development of high-level multimedia annotation schemes for non-verbal communication.

Researchers and practitioners in food science and technology routinely face several challenges, related to sparseness and heterogeneity of data, as well as to the uncertainty in the measurements and the introduction of expert knowledge in the models. Evolutionary algorithms (EAs), stochastic optimization techniques loosely inspired by natural selection, can be effectively used to tackle these issues. In this book, we present a selection of case studies where EAs are adopted in real-world food applications, ranging from model learning to sensitivity analysis.

Business Intelligence (BI) has emerged as a field which seeks to support managers in decision-making. It encompasses the techniques, methods and tools for conducting analytically-based IT solutions, which are referred to as OLAP (OnLine Analytical Processing). Within this field, SQL has a role as a leader and is continuously evolving to cover both transactional and analytical data management. This book discusses the functions provided by Microsoft® SQL Server 2014/2016 in terms of business intelligence. The analytic functions are considered as an enrichment of the SQL language. They combine a series of practical functions to answer complex analysis requests with all the simplicity, elegance and acquired performance of the SQL language. Drawing on the wide experience of the author in teaching and research, as well as insights from contacts in the industry, this book focuses on the issues and difficulties faced by academics (students and teachers) and professionals engaged in data analysis with the SQL Server 2014/2016 database management system.

The author investigates the Cramer –Lundberg model, collecting the most interesting theorems and methods, which estimate probability of default for a company of insurance business. These offer different kinds of approximate values for probability of default on the base of normal and diffusion approach and some special asymptotic.

This book provides the mathematical basis for investigating numerically equations from physics, life sciences or engineering. Tools for analysis and algorithms are confronted to a large set of relevant examples that show the difficulties and the limitations of the most naïve approaches. These examples not only provide the opportunity to put into practice mathematical statements, but modeling issues are also addressed in detail, through the mathematical perspective.

This book is the first of a set dedicated to the mathematical tools used in partial differential equations derived from physics. Its focus is on normed or semi-normed vector spaces, including the spaces of Banach, Fréchet and Hilbert, with new developments on Neumann spaces, but also on extractable spaces. The author presents the main properties of these spaces, which are useful for the construction of Lebesgue and Sobolev distributions with real or vector values and for solving partial differential equations. Differential calculus is also extended to semi-normed spaces. Simple methods, semi-norms, sequential properties and others are discussed, making these tools accessible to the greatest number of students – doctoral students, postgraduate students – engineers and researchers without restricting or generalizing the results.

Estimation of Stochastic Processes is intended for researchers in the field of econometrics, financial mathematics, statistics or signal processing. This book gives a deep understanding of spectral theory and estimation techniques for stochastic processes with stationary increments. It focuses on the estimation of functionals of unobserved values for stochastic processes with stationary increments, including ARIMA processes, seasonal time series and a class of cointegrated sequences. Furthermore, this book presents solutions to extrapolation (forecast), interpolation (missed values estimation) and filtering (smoothing) problems based on observations with and without noise, in discrete and continuous time domains. Extending the classical approach applied when the spectral densities of the processes are known, the minimax method of estimation is developed for a case where the spectral information is incomplete and the relations that determine the least favorable spectral densities for the optimal estimations are found.

Computers and the Internet are an undeniable and inextricable part of our daily lives. This book is for those who wish to better understand how this came to be. It explores the technological bases of computers, networks, software and data management, leading to the development of four pillars on which the essential applications that have a strong impact on individuals and society are based: embedded systems, Artificial Intelligence, the Internet, image processing and vision. We will travel to the heart of major application areas: robotics, virtual reality, health, mobility, energy, the factory of the future, not forgetting the major questions that this digitization can raise. This book is the authors testimony after fifty years spent in environments that are very open to new technologies. It offers perspectives on the evolution of the digital world that we live in.

Evolutionary algorithms are bio-inspired algorithms based on Darwin’s theory of evolution. They are expected to provide non-optimal but good quality solutions to problems whose resolution is impracticable by exact methods. In six chapters, this book presents the essential knowledge required to efficiently implement evolutionary algorithms. Chapter 1 describes a generic evolutionary algorithm as well as the basic operators that compose it. Chapter 2 is devoted to the solving of continuous optimization problems, without constraint. Three leading approaches are described and compared on a set of test functions. Chapter 3 considers continuous optimization problems with constraints. Various approaches suitable for evolutionary methods are presented. Chapter 4 is related to combinatorial optimization. It provides a catalog of variation operators to deal with order-based problems. Chapter 5 introduces the basic notions required to understand the issue of multi-objective optimization and a variety of approaches for its application. Finally, Chapter 6 describes different approaches of genetic programming able to evolve computer programs in the context of machine learning.