الصفحة 9
الصفحة 9
Modern Multivariate Statistical Techniques : Regression, Classification, and Manifold Learning
Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has opened up the field of bioinformatics. These exciting developments, which led to the introduction of many innovative statistical tools for high-dimensional data analysis, are described here in detail. The author takes a broad perspective; for the first time in a book on multivariate analysis, nonlinear methods are discussed in detail as well as linear methods.
Modern Genome Annotation : The Biosapiens Network
An accurate description of current scientific developments in the field of bioinformatics and computational implementation is presented by research of the BioSapiens Network of Excellence. Bioinformatics is essential for annotating the structure and function of genes, proteins and the analysis of complete genomes and to molecular biology and biochemistry. Included is an overview of bioinformatics, the full spectrum of genome annotation approaches including; genome analysis and gene prediction, gene regulation analysis and expression, genome variation and QTL analysis, large scale protein annotation of function and structure, annotation and prediction of protein interactions, and the organization and annotation of molecular networks and biochemical pathways. Also covered is a technical framework to organize and represent genome data using the DAS technology and work in the annotation of two large genomic sets: HIV/HCV viral genomes and splicing alternatives potentially encoded in 1% of the human genome.
Modelling water and nutrient dynamics in soil-crop systems : Applications of different models to common data sets - Proceedings of a workshop held 2004 in Müncheberg, Germany
This book contains articles from a workshop on "Modelling water and nutrient dynamics in crop-soil systems". Data sets from lysimeters and experimental fields of multiyear crop rotations were provided for modellers. A unique data set is provided of a 100 year long term field experiment regarding crop yield and organic carbon development under different management systems. The book includes a detailed description of data sets which can be used by modellers and the papers describe the applications of 18 different modelling approaches describing soil-crop-atmosphere interactions for water, nitrogen and carbon dynamics.
Modeling Longitudinal Data
This book teaches the art and statistical science of modern longitudinal data analysis. The author emphasizes specifying, understanding, and interpreting longitudinal data models. He inspects the longitudinal data graphically, analyzes the time trend and covariates, models the covariance matrix, and then draws conclusions. The book has many figures and tables illustrating longitudinal data and numerous homework problems. The associated web site contains many longitudinal data sets, examples of computer code, and labs to re-enforce the material.
Modeling Decisions for Artificial Intelligence ; Vol.3885 ; 3rd International Conference, MDAI 2006, Tarragona, Spain, April 3-5, 2006, Proceedings
This book constitutes the refereed proceedings of the Third International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2006, held in Tarragona, Spain, in April 2006.
Modeling Decisions for Artificial Intelligence ; 4th International Conference, MDAI 2007, Kitakyushu, Japan, August 16-18, 2007, Proceedings
Decision modeling is a key area in the developing field of AI, and this timely work connects researchers and professionals with the very latest research. It constitutes the refereed proceedings of the 4th International Conference on Modeling Decisions for Artificial Intelligence, held in Kitakyushu, Japan, in August 2007.
Modeling decisions : Information fusion and aggregation operators
This book covers the underlying science and application issues related to aggregation operators, focusing on tools used in practical applications that involve numerical information. Starting with detailed introductions to information fusion and integration, measurement and probability theory, fuzzy sets, and functional equations.
Modeling and Management of Fuzzy Semantic RDF Data
Presents the latest research findings in fuzzy RDF data modeling and management. Fuzziness widely exist in many data and knowledge intensive applications. With the increasing amount of metadata available, efficient and scalable management of massive semantic data with uncertainty is of crucial importance. This book goes to great depth concerning the fast-growing topic of technologies and approaches of modeling and managing fuzzy metadata with Resource Description Framework (RDF) format. Its major topics include representation of fuzzy RDF data, fuzzy RDF graph matching, query of fuzzy RDF data, and persistence of fuzzy RDF data in diverse databases. The objective of the book is to provide the state-of-the-art information to researchers, practitioners, and postgraduates students who work on the area of big data intelligence and at the same time serve as the uncertain data and knowledge engineering professional as a valuable real-world reference.
Model-based Geostatistics
Geostatistics is concerned with estimation and prediction problems for spatially continuous phenomena, using data obtained at a limited number of spatial locations. The name reflects its origins in mineral exploration, but the methods are now used in a wide range of settings including public health and the physical and environmental sciences. Model-based geostatistics refers to the application of general statistical principles of modeling and inference to geostatistical problems. This volume is the first book-length treatment of model-based geostatistics. The authors have written an expository text, emphasizing statistical methods and applications rather than the underlying mathematical theory. Analyses of datasets from a range of scientific contexts feature prominently, and simulations are used to illustrate theoretical results. Readers can reproduce most of the computational results in the book by using the authors' R-based software package, geoR, whose usage is illustrated in a computation section at the end of each chapter.
Model Driven Architecture ; European MDA Workshops : Foundations and Applications, MDAFA 2003 and MDAFA 2004, Twente, The Netherlands, June 26-27, 2003, and Linköping, Sweden, June 10-11, 2004, Revised Selected Papers
Model-Driven Architecture (MDA) is an initiative proposedby the Object M- agement Group (OMG) for platform-generic software development. MDA s- arates the specification of system functionality from the implementation on a specific platform. It is aimed at making software assets more resilient to changes caused by emerging technologies. While stressing the importance of modeling, the MDA initiative covers a wide spectrum of research areas. Further efforts are required to bring them into a coherent approach based on open standards and supported by matured tools and techniques. This volume contains the selected papers of two workshops on “Model-Driven Architecture – Foundations and Applications” (MDAFA): MDAFA 2003 held at the University of Twente, Twente, The Netherlands, June 26–27, 2003, and MDAFA 2004 held at Linko ¨ping University, Link¨ oping, Sweden, June 10–11, 2004. The goal of the workshops was to understand the foundations of MDA, to share experience in applying MDA techniques and tools, and to outline future research directions. The workshops organizers encouraged authors of accepted papers to re-submit their papers to a post-workshop reviewing process; 15 of these papers were accepted to appear in this volume on MDA.
Mining Sequential Patterns from Large Data Sets
To meet the different needs of various applications, several models of sequential patterns have been proposed. This volume not only studies the mathematical definitions and application domains of these models, but also the algorithms on how to effectively and efficiently find these patterns. Mining Sequential Patterns from Large Data Sets provides a set of tools for analyzing and understanding the nature of various sequences by identifying the specific model(s) of sequential patterns that are most suitable. This book provides an efficient algorithm for mining these patterns.
Metric Spaces
The abstract concepts of metric ces are often perceived as difficult. This book offers a unique approach to the subject which gives readers the advantage of a new perspective familiar from the analysis of a real line. Rather than passing quickly from the definition of a metric to the more abstract concepts of convergence and continuity, the author takes the concrete notion of distance as far as possible, illustrating the text with examples and naturally arising questions. Attention to detail at this stage is designed to prepare the reader to understand the more abstract ideas with relative ease.
Metric Spaces
This volume provides a complete introduction to metric space theory for undergraduates. It covers the topology of metric spaces, continuity, connectedness, compactness and product spaces, and includes results such as the Tietze-Urysohn extension theorem, Picard's theorem on ordinary differential equations, and the set of discontinuities of the pointwise limit of a sequence of continuous functions.
Methods of microarray data analysis IV
As studies using microarray technology have evolved, so have the data analysis methods used to analyze these experiments. The CAMDA conference plays a role in this evolving field by providing a forum in which investors can analyze the same data sets using different methods. METHODS OF MICROARRAY DATA ANALYSIS IV is the fourth book in this series, and focuses on the important issue of associating array data with a survival endpoint. Previous books in this series focused on classification (Volume I), pattern recognition (Volume II), and quality control issues (Volume III). In this volume, four lung cancer data sets are the focus of analysis. We highlight three tutorial papers, including one to assist with a basic understanding of lung cancer, a review of survival analysis in the gene expression literature, and a paper on replication. In addition, 14 papers presented at the conference are included. This book is an excellent reference for academic and industrial researchers who want to keep abreast of the state-of-the-art of microarray data analysis.
MATLAB® Recipes for Earth Sciences
MATLAB is used in a wide range of applications in geosciences, such as image processing in remote sensing, generation and processing of digital elevation models and the analysis of time series. This book introduces basic methods of data analysis in geosciences using MATLAB. The text includes a brief description of each method and numerous examples demonstrating how MATLAB can be used on data sets from earth sciences. All MATLAB recipes can be easily modified in order to analyse the reader's own data sets.
MATLAB® Recipes for Earth Sciences
MATLAB® is used in a wide range of applications in geosciences, such as image processing in remote sensing, generation and processing of digital elevation models and the analysis of time series. This book introduces methods of data analysis in geosciences using MATLAB such as basic statistics for univariate, bivariate and multivariate datasets, jackknife and bootstrap resampling schemes, processing of digital elevation models, gridding and contouring, geostatistics and kriging, processing and georeferencing of satellite images, digitizing from the screen, linear and nonlinear time-series analysis and the application of linear time-invariant and adaptive filters. The revised and updated Second Edition includes new subchapters on windowed Blackman-Tukey, Lomb-Scargle and Wavelet powerspectral analysis, statistical analysis of point distributions and digital elevation models, and a full new chapter on the statistical analysis of directional data. The text includes a brief description of each method and numerous examples demonstrating how MATLAB can be used on data sets from earth sciences. All MATLAB recipes can be easily modified in order to analyse the reader's own data sets.
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.
Mathematics of Uncertainty : Ideas, Methods, Application Problems
Mathematics of Uncertainty" provides the basic ideas and foundations of uncertainty, covering the fields of mathematics in which uncertainty, variability, imprecision and fuzziness of data are of importance. This introductory book describes the basic ideas of the mathematical fields of uncertainty from simple interpolation to wavelets, from error propagation to fuzzy sets and neural networks. The book presents the treatment of problems of interpolation and approximation, as well as observation fuzziness which can essentially influence the preciseness and reliability of statements on functional relationships.
Mathematical Tools for Data Mining : Set Theory, Partial Orders, Combinatorics
Mathematics is presented in a thorough and rigorous manner offering a detailed explanation of each topic, with applications to data mining such as frequent item sets, clustering, decision trees also being discussed. More than 400 exercises are included and they form an integral part of the material. Some of the exercises are in reality supplemental material and their solutions are included. The reader is assumed to have a knowledge of elementary analysis.
Is it Safe to Eat? : Enjoy Eating and Minimize Food Risks
The author, discusses - in his easily understandable, ranging from GM food to natural toxins passionate, yet authoritative and informative book. But in contrast to many other authors, Ian Shaw sets the risks of food, foodborne pathogens and food contaminats in the context of life’s risks. Enjoyment of food and eating is a benefit that far outweighs the risks, at least if everybody is aware of those risks and uses measures to minimize them.
