الصفحة 2
الصفحة 2
Modelling community structure in freshwater ecosystems
"The book presents approaches and methodologies for predicting the structure and diversity of key aquatic communities (namely diatoms, benthic macroinvertebrates and fish), under natural conditions and under man-made disturbance. Such an approach will make it possible to: 1) set up procedures for robust and sensitive ecosystem evaluation, based on the prediction of the excepted community structure; 2) model community structure in disturbed ecosystems, taking into account all the relevant ecological variables; 3) test ecosystem sensitivity to natural and anthropic disturbance; and 4) explore specific actions to be taken for the restoration of ecosystem integrity."--Jacket.
Modeling with Itô Stochastic Differential Equations
This modeling procedure is thoroughly explained and illustrated for randomly varying systems in population biology, chemistry, physics, engineering, and finance. Introductory chapters present the fundamental concepts of random variables, stochastic processes, stochastic integration, and stochastic differential equations. These concepts are explained in a Hilbert space setting which unifies and simplifies the presentation. Computer programs, given throughout the text, are useful in solving representative stochastic problems. Analytical and computational exercises are provided in each chapter that complement the material in the text.
Model checking software ; 14th International SPIN Workshop, Berlin, Germany, July 1-3, 2007, Proceedings
This book presents the proceedings of the 14th International SPIN workshop on Model Checking Software, held in Berlin, Germany. The papers are organized into topical sections covering directed model checking, partial order reduction, program analysis, exploration advances, modeling and case studies, and tool demonstrations.
Microsoft Visual C# Step by Step
Guide to Microsoft Visual C# fundamentals with Visual Studio. Expand your expertiseand teach yourself the fundamentals of programming with the latest version of Visual C# with Visual Studio. If you are an experienced software developer, you'll get all the guidance, exercises, and code you need to start building responsive, scalable, cloud-connected applications that can run almost anywhere. Discover how to: Quickly start creating Visual C# code and projects with Visual Studio Work with variables, operators, expressions, methods, and program flow Build more robust apps with error, exception, and resource management Spot problems fast with the Visual Studio debugger Make the most of improvements to C# methods, parameters, and switch statements Master the C# object model, and create your own functional data structures Leverage advanced properties, indexers, generics, and collection classes Create Windows 10 apps that share data, collaborate, and use cloud services Integrate Cortana to voice-enable your applications Perform complex queries over object collections with LINQ
Metodi Matematici della Fisica = Mathematical Methods of Physics
This text draws its origin from my old notes, prepared for the course of Mathematical Methods of Physics and gradually arranged, refined and updated over the course of many years of teaching. The aim has always been to provide as simple and direct a presentation as possible of the mathematical methods relevant to Physics: Fourier series, Hilbert spaces, linear operators, functions of complex variables, Fourier and Laplace transforms, distributions. In addition to these basic topics, a brief introduction to the first notions of group theory, Lie algebras and symmetries in view of their applications to Physics is presented in the Appendix.
Metaheuristics : Progress in Complex Systems Optimization
The aim of METAHEURISTICS: Progress in Complex Systems Optimization is to provide several different kinds of information: a delineation of general metaheuristics methods, a number of state-of-the-art articles from a variety of well-known classical application areas as well as an outlook to modern computational methods in promising new areas. Therefore, this book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field.
Metaheuristics : Progress as Real Problem Solvers
Metaheuristics: Progress as Real Problem Solvers is a peer-reviewed volume of eighteen current, cutting-edge papers by leading researchers in the field. Included are an invited paper by F. Glover and G. Kochenberger, which discusses the concept of Metaheuristic agent processes, and a tutorial paper by M.G.C. Resende and C.C. Ribeiro discussing GRASP with path-relinking. Other papers discuss problem-solving approaches to timetabling, automated planograms, elevators, space allocation, shift design, cutting stock, flexible shop scheduling, colorectal cancer and cartography. A final group of methodology papers clarify various aspects of Metaheuristics from the computational view point
Metaheuristic Procedures for Training Neural Networks
Metaheuristic Procedures For Training Neural Networks provides successful implementations of metaheuristic methods for neural network training. Apart from Chapter 1, which reviews classical training methods, the chapters are divided into three main categories. The first one is devoted to local search based methods, including Simulated Annealing, Tabu Search, and Variable Neighborhood Search.
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005 ; 8th International Conference, Palm Springs, CA, USA, October 26-29, 2005, Proceedings, Part I
This paper presents a method for classification of medical images, using machine learning and deformation-based morphometry. A morphological representation of the anatomy of interest is first obtained using highdimensional template warping, from which regions that display strong correlations between morphological measurements and the classification (clinical) variable are extracted using a watershed segmentation, taking into account the regional smoothness of the correlation map which is estimated by a crossvalidation strategy in order to achieve robustness to outliers. A Support Vector Machine-Recursive Feature Elimination (SVM-RFE) technique is then used to rank computed features from the extracted regions, according to their effect on the leave-one-out error bound. Finally, SVM classification is applied using the best set of features, and it is tested using leave-one-out. The results from a group of 61 brain images of female normal controls and schizophrenia patients demonstrate not only high classification accuracy (91.8%) and steep ROC curves, but also exceptional stability with respect to the number of selected features and the SVM kernel size
Measurement Uncertainty : An Approach via the Mathematical Theory of Evidence
This text is the first to make full use of the mathematical theory of evidence to express the uncertainty in measurements. It gives an overview of the current standard, then pinpoints and constructively resolves its limitations through its unique approach. The text presents various tools for evaluating uncertainty, beginning with the probabilistic approach and concluding with the expression of uncertainty using random-fuzzy variables. The exposition is driven by numerous examples. The book is designed for immediate use and application in research and laboratory work.
Measure and analyze the internal factors affecting the marketability of the private banks services
Aims to define the influencing factors of net interest margin in Syria banking sector. Within this scope, the effects of six internal explanatory variables on net interest margin were analyzed. Moreover, annual data for the period between 2017 and 2021 was used in this study...
Mathématiques de base pour économistes = Basic Mathematics for Economists
This book contains fundamental elements of mathematics and includes the following elements: notion of logic, propositions, theorems, sets, relations and functions; graphical representations of functions, economic applications of lines and functions, sequences, limits and first derivative, differential economic applications of derivatives; integrals: undefined and defined with economic applications; mathematical series; functions of several variables, partial derivatives, Lagrange multiplier with economic applications; linear algebra: matrix calculus, system of linear equations, vectors, differential calculus in matrix form.
Introduction to Probability with Statistical Applications
This textbook is an introduction to probability and statistics for non-mathematics majors who do not need the exhaustive detail and mathematical depth provided in more comprehensive treatments of the subject. The presentation covers the mathematical laws of random phenomena, including discrete and continuous random variables, expectation and variance, and common probability distributions such as the binomial, Poisson, and normal distributions. Main statistical concepts considered are point and interval estimates, hypothesis testing, power function, various statistical tests: z, t, chi-square and Kolmogorov-Smirnov.
Introduction to Complex Analysis in Several Variables
This book gives a comprehensive introduction to complex analysis in several variables. It clearly focusses on special topics in complex analysis rather than trying to encompass as much material as possible. Many cross-references to other parts of mathematics, such as functional analysis or algebras, are pointed out in order to broaden the view and the understanding of the chosen topics. A major focus is extension phenomena alien to the one-dimensional theory, which are expressed in the famous Hartog's Kugelsatz, the theorem of Cartan-Thullen, and Bochner's theorem.
Introduction to Bayesian Statistics
This is the second and translated edition of the German book “Einf ̈uhrung in die Bayes-Statistik, Springer-Verlag, Berlin Heidelberg New York, 2000”. It has been completely revised and numerous new developments are pointed out together with the relevant literature. The Chapter 5.2.4 is extended by the stochastic trace estimation for variance components. The new Chapter 5.2.6 presents the estimation of the regularization parameter of type Tykhonov regularization for inverse problems as the ratio of two variance components.The reconstruction and the smoothing of digital three-dimensional images is demonstrated in the new Chapter 5.3. The Chapter 6.2.1 on importance sampling for the Monte Carlo integration is rewritten to solve a more general integral. This chapter contains also the derivation of the SIR (sampling-importance-resampling) algorithm as an alternative to the rejection method for generating random samples. Markov Chain Monte Carlo methods are now frequently applied in Bayesian statistics.
Interactive and dynamic graphics for data analysis : With R and Ggobi
This richly illustrated book describes the use of interactive and dynamic graphics as part of multidimensional data analysis. Chapters include clustering, supervised classification, and working with missing values. A variety of plots and interaction methods are used in each analysis, often starting with brushing linked low-dimensional views and working up to manual manipulation of tours of several variables. The role of graphical methods is shown at each step of the analysis, not only in the early exploratory phase, but in the later stages, too, when comparing and evaluating models.
Intelligent Computing in Engineering and Architecture ; 13th EG-ICE Workshop 2006, Ascona, Switzerland, June 25-30, 2006, Revised Selected Papers
Providing computer support for tasks in civil engineering and architecture is hard. Projects can be complex, long and costly. Firms that contribute to design, construction and maintenance are often worth less than the value of their projects. Everyone in the field is justifiably risk adverse. Contextual variables have a strong influence making generalization difficult. The product life cycle may exceed one hundred years and functional requirements may evolve during the service life. It is therefore no wonder that practitioners in this area have been so reluctant to adopt advanced computing systems. After decades of research and industrial pilot projects, advanced computing s- tems are now being recognized by many leading practitioners to be strategically - portant for the future profitability of firms involved in engineering and architecture. Engineers and architects with advanced computing knowledge are hired quickly in the market place. Closer collaboration between research and practice is leading to more comprehensive validation processes for new research ideas. This is feeding devel- ment of more useful systems, thus accelerating progress. These are exciting times. th This volume contains papers that were presented at the 13 Workshop of the Eu- pean Group for Intelligent Computing in Engineering. Over five days, 70 participants from around the world listened to 59 paper presentations in a single session format.
Intelligent Algorithms for Packing and Cutting Problem
Introduces intelligent solving algorithms for classical packing and cutting problem and their variants / Investigates novel methods, e.g. reinforcement learning algorithms, for rectangular and irregular packing problems / Presents practical engineering application cases in combination of theory and practice / investigates in detail the two-dimensional packing and cutting problems in the field of operations research and management science. It introduces the mathematical models and intelligent solving algorithms for these problems, as well as their engineering applications. Most intelligent methods reported in this book have already been applied in reality, which can provide reference for the engineers. The presented novel methods for the two-dimensional packing problem provide a new way to solve the problem for researchers interested in operations research or computer science. This book also introduces three new variants of packing problems and their solving methods, which offer a different research direction.
Impact of Corporate Governance on Earnings Management
This research was aimed to study the impact of corporate governance on earnings management, and to explain the relationship between both of these variables. To achieve that goal the research depended on practical study; by extracting an actual data from the 8 conventional banks listed in DSE. the extracted data were then analyzed by using descriptive statistics, simple and multiple linear regression test and ANOVA test to examine the research hypothesis. The results showed that there is a governance impact on earnings management, and defined the relationship between audit committee and earnings management as negative relationship. and also, a negative relationship between top share and earnings management. And finally, we found no impact of CEO duality on earnings management.
Ideals, Varieties, and Algorithms : An Introduction to Computational Algebraic Geometry and Commutative Algebra
Algebraic Geometry is the study of systems of polynomial equations in one or more variables.The solutions of a system of polynomial equations form a geometric object called a variety; the corresponding algebraic object is an ideal. There is a close relationship between ideals and varieties which reveals the intimate link between algebra and geometry. Written at a level appropriate to undergraduates, this book covers such topics as the Hilbert Basis Theorem, the Nullstellensatz, invariant theory, projective geometry, and dimension theory.
