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Between dirt and discussion : Methods, methodology and interpretation in historical archaeology
The cases presented in this volume revisit old methods and previous scholarly approaches with new perspectives, along with incorporating the newest technologies available to understanding the past.
Automorphic Forms and Lie Superalgebras
Most known examples of Lie superalgebras with a related automorphic form such as the Fake Monster Lie algebra whose reflection group is given by the Leech lattice arise from (super)string theory and can be derived from lattice vertex algebras. The No-Ghost Theorem from dual resonance theory and a conjecture of Berger-Li-Sarnak on the eigenvalues of the hyperbolic Laplacian provide strong evidence that they are of rank at most 26.The aim of this book is to give the reader the tools to understand the ongoing classification and construction project of this class of Lie superalgebras and is ideal for a graduate course.
Aspects of Automatic Text Analysis
This book It collects contributions of authors from a multidisciplinary area who focus on the topic of automatic text analysis from several (i.e. linguistic, mathematical, and information theoretical) perspectives. It describes methodological as well as methodical foundations and collects approaches in the field of text and corpus linguistics. In this sense, it contributes to the computational linguistic and information theoretical grounding of automatic text analysis.
Artificial intelligence in recognition and classification of astrophysical and medical images
This book presents innovative techniques in Recognition and Classification of Astrophysical and Medical Images. The contents include: Introduction to pattern recognition and classification in astrophysical and medical images. Image standardization and enhancement. Region-based methods for pattern recognition in medical and astrophysical images. Advanced information processing using statistical methods. Feature recognition and classification using spectral method
Applied Statistics Using SPSS, STATISTICA, MATLAB and R
The book provides a comprehensive coverage of the main statistical analysis topics important for practical applications such as data description, statistical inference, classification and regression, factor analysis, survival data and directional statistics.
Applied soft computing technologies : The challenge of complexity
This volume presents the proceedings of the 9th Online World Conference on Soft Computing in Industrial Applications (WSC9), September 20th - October 08th, 2004, held on the World Wide Web. It contains plenary lectures, original papers and tutorials presented during the conference. The book brings together outstanding research and developments in the field of soft computing (evolutionary computation, fuzzy logic, neural networks, and their fusion) and its applications in science and technology.
Applied Remote Sensing for Urban Planning, Governance and Sustainability
Despite the promising and exciting possibilities presented by new and fast-developing remote sensing technologies applied to urban areas, there is still a gap perceived between the generally academic and research-focused spectrum of results offered by the “urban remote sensing” community and the application of these data and products by the local governmental bodies of urban cities and regions. While there is no end of interesting science questions that we can ask about cities, sometimes these questions don't match well with what the operational problems and concerns of a given city are. The authors present data from six urban regions from all over the world. They explain what the important questions are, and how one can use data and scientific skills to help answer them.
Applied Probability and Statistics
This text is designed for a one-semester course on Probability and Statistics. The exposition unfolds systematically from an introductory chapter to such topics as random variables and vectors, stochastic processes, estimation, testing and regression. The topics are well chosen and the presentation is enriched by many examples from real life. Following every chapter, the reader will find many original, solved and unsolved problems and hundreds of multiple choice questions, enabling those unfamiliar with the topics to master them. Additionally appealing are the interesting historical notes on the mathematicians mentioned throughout and a useful bibliography. A distinguishing character of the book is the thorough and succinct handling of the various topics.
Applied Graph Theory in Computer Vision and Pattern Recognition
It presents the application of graph theory to low-level processing of digital images, presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, and provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks.
Analysis of variance for random models, Vol. 2 : Unbalanced data : Theory, methods, applications, and data analysis
Analysis of variance (ANOVA) models have become widely used tools and play a fundamental role in much of the application of statistics today. In particular, ANOVA models involving random effects have found widespread application to experimental design in a variety of fields requiring measurements of variance, including agriculture, biology, animal breeding, applied genetics, econometrics, quality control, medicine, engineering, and social sciences. This two-volume work is a comprehensive presentation of different methods and techniques for point estimation, interval estimation, and tests of hypotheses for linear models involving random effects. Both Bayesian and repeated sampling procedures are considered. Volume I examines models with balanced data (orthogonal models); Volume II studies models with unbalanced data (nonorthogonal models).
Algorithmic topology and classification of 3-manifolds
This book provides a comprehensive and detailed account of different topics in algorithmic 3-dimensional topology. The book is intended to combine the pedagogical approach of a graduate textbook with the completeness and reliability of a research monograph.
Algebraic Groups and Lie Groups with Few Factors
Algebraic groups are treated in this volume from a group theoretical point of view and the obtained results are compared with the analogous issues in the theory of Lie groups. The main body of the text is devoted to a classification of algebraic groups and Lie groups having only few subgroups or few factor groups of different type. In particular, the diversity of the nature of algebraic groups over fields of positive characteristic and over fields of characteristic zero is emphasized. This is revealed by the plethora of three-dimensional unipotent algebraic groups over a perfect field of positive characteristic, as well as, by many concrete examples which cover an area systematically. In the final section, algebraic groups and Lie groups having many closed normal subgroups are determined.
Algebraic Geometry and Geometric Modeling
Algebraic Geometry provides an impressive theory targeting the understanding of geometric objects defined algebraically. Geometric Modeling uses every day, in order to solve practical and difficult problems, digital shapes based on algebraic models. In this book, we have collected articles bridging these two areas. The confrontation of the different points of view results in a better analysis of what the key challenges are and how they can be met. We focus on the following important classes of problems: implicitization, classification, and intersection. The combination of illustrative pictures, explicit computations and review articles will help the reader to handle these subjects.
Advances of Computational Intelligence in Industrial Systems
Advances of Computational Intelligence in Industrial Systems reports the exploration of CI frontiers with an emphasis on a broad spectrum of real-world applications. Section I – Theory and Foundation presents some of the latest developments in CI.
Advances in Web Intelligence and Data Mining
The new Web-related research directions include intelligent methods usually associated with the fields of computational intelligence, soft computing, and data mining. This book presents state-of-the-art developments in the area of computationally intelligent methods applied to various aspects and ways of Web exploration and Web mining. Some novel data mining algorithms that can lead to more effective and intelligent Web-based systems are also described. Scientists, engineers, and research students are expected to find many inspiring ideas in this volume.
Advances in statistical methods for the health sciences : Applications to cancer and AIDS studies, genome sequence analysis, and survival analysis
This volume, an outgrowth of an "International Conference on Statistical Methods in Health Sciences," covers a wide range of topics pertaining to new statistical methods and novel applications in the health sciences.
Advances in Sensing with Security Applications
The chapters in this volume were presented at the July 2005NATO Advanced Study Institute on Advances in Sensing with Security App- cations. The ASI was divided into three broadly de?ned but interrelated areas: the - creasing need for fast and accurate sensing, the scienti?c underpinnings of the ongoing revolution in sensing, and speci?c sensing algorithms and techniques. The ASI brought together world leaders from academia, government, andindustry,withextensivemultidisciplinarybackgroundsevidencedby theirresearchandparticipationinnumerousworkshopsandconferences.
Advances in Ranking and Selection, Multiple Comparisons, and Reliability: Methodology and Applications
S. Panchapakesan has made significant contributions to ranking and selection and has published in many other areas of statistics, including order statistics, reliability theory, stochastic inequalities, and inference. Written in his honor, the twenty invited articles in this volume reflect recent advances in these fields and form a tribute to Panchapakesan’s influence and impact on these areas. Thematically organized, the chapters cover a broad range of topics from: Inference / Ranking and Selection / Multiple Comparisons and Tests / Agreement Assessment / Reliability / Biostatistics
Advances in Probabilistic Graphical Models
This carefully edited book brings together in one volume some of the most important topics of current research in probabilistic graphical modelling, learning from data and probabilistic inference. This includes topics such as the characterisation of conditional independence, the sensitivity of the underlying probability distribution of a Bayesian network to variation in its parameters, the learning of graphical models with latent variables and extensions to the influence diagram formalism. In addition, attention is given to important application fields of probabilistic graphical models, such as the control of vehicles, bioinformatics and medicine.
Advances in Data Analysis ; Proceedings of the 30th Annual Conference of the Gesellschaft für Klassifikation e.V., Freie Universität Berlin, March 8-10, 2006
Focuses on exploratory data analysis, learning of latent structures in datasets, and unscrambling of knowledge. Coverage details a broad range of methods from multivariate statistics, clustering and classification.
