الصفحة 17
الصفحة 17
Computational intelligence for modelling and prediction
This book contains recent advances in Computational Intelligence methods for modeling, optimization and prediction and covers a large number of applications. The book presents new Computational Intelligence theory and methods for modeling and prediction. The range of the various applications is captured with 5 chapters in image processing, 2 chapters in audio processing, 3 chapters in commerce and finance, 2 chapters in communication networks and 6 chapters containing other applications.
Computational intelligence based on lattice theory
The emergence of lattice theory within the field of computational intelligence (CI) is partially due to its proven effectiveness in neural computation. Moreover, lattice theory has the potential to unify a number of diverse concepts and aid in the cross-fertilization of both tools and ideas within the numerous subfields of CI. The compilation of this eighteen-chapter book is an initiative towards proliferating established knowledge in the hope to further expand it. This edited book is a balanced synthesis of four parts emphasizing, in turn, neural computation, mathematical morphology, machine learning, and (fuzzy) inference/logic. The articles here demonstrate how lattice theory may suggest viable alternatives in practical clustering, classification, pattern analysis, and regression applications.
Computational intelligence : Principles, techniques and applications
The book Computational Intelligence: Principles, Techniques and Applications presents both theories and applications of Computational Intelligence in a clear, precise and highly comprehensive style. The textbook addresses the fundamental aspects of Fuzzy Sets and Logic, Neural Networks, Evolutionary Computing and Belief Networks. The application areas include Fuzzy Databases, Fuzzy Control, Image Understanding, Expert Systems, Object Recognition, Criminal Investigation, Telecommunication Networks and Intelligent Robots. The book contains many numerical examples and homework problems with sufficient hints so that the students can solve them on their own. Emerging areas of Computational Intelligence such as artificial life, particle swarm optimization, artificial immune systems, fuzzy chaos theory, rough sets and granular computing have also been addressed with examples in this book. The book ends with a discussion on a number of open- ended research problems in Computational Intelligence. Graduate students interested to pursue their research in this subject will greatly be benefited with these problems.
Computational earthquake physics ; Part II
Exciting developments in earthquake science have benefited from new observations, improved computational technologies, and improved modeling capabilities. Designing realistic supercomputer simulation models for the complete earthquake generation process is a grand scientific challenge due to the complexity of phenomena and range of scales involved from microscopic to global. The present volume - Part II - incorporates computational environment and algorithms, data assimilation and understanding, model applications and iSERVO. Topics covered range from iSERVO and QuakeSim: implementing the international solid earth research virtual observatory by integrating computational grid and geographical information web services; LURR (Load-Unload Response Ratio) described in six papers involving this promising earthquake forecasting model; pattern informatics and phase dynamics and their applications, which was also a highlight in the Workshop; computational algorithms, including continuum damage models and visualization and analysis of geophysical datasets; evolution of mantle material; the state vector approach; and assimilation of data such as geodetic data, GPS data, and seismicity and laboratory experimental data.
Combinatorial pattern matching ; 18th Annual Symposium, CPM 2007, London, Canada, July 9-11, 2007, Proceedings
This book presented original research contri- tions on computational pattern matching and analysis, data compression and compressed text processing, sufix arrays and trees, and computational biology. Combinatorial Pattern Matching addresses issues of searching and matching strings and more complicated patterns such as trees, regular expressions, graphs, point sets, and arrays.The goal is to derive non-trivial combinatorial properties of such structures and to exploit these properties in order to either achieve superior performance for the corresponding computational problems or pinpoint conditions under which searches cannot be performed eficiently.
Combinatorial pattern matching ; 12th Annual Symposium, CPM 2001 Jerusalem, Israel, July 1-4, 2001 Proceedings
This book constitutes the refereed proceedings of the 12th Annual Symposium on Combinatorial Pattern Matching, CPM 2001, held in Jerusalem, Israel, in July 2001. The 21 revised papers presented together with one invited paper were carefully reviewed and selected from 35 submissions. The papers are devoted to current theoretical and algorithmic issues of searching and matching strings and more complicated patterns such as trees, regular expressions, graphs, point sets, and arrays as well as to advanced applications of CPM in areas such as the Internet, computational biology, multimedia systems, information retrieval, data compression, coding, computer vision, and pattern recognition.
Combinatorial image analysis ; 10th International Workshop, IWCIA 2004, Auckland, New Zealand, December 1-3, 2004, Proceedings
This volume presents the proceedings of the 10th International Workshop on Combinatorial Image Analysis,held 2004, in Auckland, New Zealand. For this workshop we received 86 submitted papers from 23 countries. We selected 55 papers for the conference. completed the program. Conference papers are presented in this volume under the following topical part titles: discrete tomography (3 papers), combinatorics and computational models (6), combinatorial algorithms (6), combinatorial mathematics (4), d- ital topology (7), digital geometry (7), approximation of digital sets by curves and surfaces (5), algebraic approaches (5), fuzzy image analysis (2), image s- mentation (6), and matching and recognition (7). These subjects are dealt with in the context of digital image analysis or computer vision.
Cluster Analysis for Data Mining and System Identification
Presents new approaches to data mining and system identification, and new techniques and tools are presented for the clustering, classification, regression and visualization of complex datasets.
Mathematical Models for Registration and Applications to Medical Imaging
Image registration is an emerging topic in image processing with many applications in medical imaging, picture and movie processing. The classical problem of image registration is concerned with ?nding an appropriate transformation between two data sets. This fuzzy de?nition of registration requires a mathematical modeling and in particular a mathematical speci?cation of the terms appropriate transformations and correlation between data sets. Depending on the type of application, typically Euler, rigid, plastic, elastic deformations are considered. The variety of similarity p measures ranges from a simpleL distance between the pixel values of the data to mutual information or entropy distances. This goal of this book is to highlight by some experts in industry and medicine relevant and emerging image registration applications and to show new emerging mathematical technologies in these areas. Currently, many registration application are solved based on variational prin- ple requiring sophisticated analysis, such as calculus of variations and the theory of partial differential equations, to name but a few. Due to the numerical compl- ity of registration problems ef?cient numerical realization are required. Concepts like multi-level solver for partial differential equations, non-convex optimization, and so on play an important role. Mathematical and numerical issues in the area of registration are discussed by some of the experts in this volume.
Mathematical Methods in Time Series Analysis and Digital Image Processing
The aim of this volume is to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences. In particular, mathematically justified algorithms and methods, the mathematical analysis of these algorithms, and methods as well as the investigation of connections between methods from time series analysis and image processing are reviewed. An interdisciplinary comparison of these methods, drawing upon common sets of test problems from medicine and geophysical/enviromental sciences, is also addressed.
Mathematical Formulas for Economists
This collection of formulas constitutes a compendium of mathematics for eco nomics and business. It contains the most important formulas, statements and algorithms in this significant subfield of modern mathematics and addresses primarily students of economics or business at universities, colleges and trade schools. But people dealing with practical or applied problems will also find this collection to be an efiicient and easy-to-use work of reference. First the book treats mathematical symbols and constants, sets and state ments, number systems and their arithmetic as well as fundamentals of com binatorics. The chapter on sequences and series is followed by mathematics of finance, the representation of functions of one and several independent vari ables, their differential and integral calculus and by differential and difference equations. In each case special emphasis is placed on applications and models in economics. The chapter on linear algebra deals with matrices, vectors, determinants and systems of linear equations. This is followed by the representation of struc tures and algorithms of linear programming. Finally, the reader finds formu las on descriptive statistics (data analysis, ratios, inventory and time series analysis), on probability theory (events, probabilities, random variables and distributions) and on inductive statistics (point and interval estimates, tests). Some important tables complete the work.
Marxist Philosophy in China : From Qu Qiubai to Mao Zedong, 1923-1945
The book sets the philosophical writings of philosophers in the context of the development of Marxist philosophy internationally, and examines particularly the influence on these philosophers of Soviet Marxist philosophy. It argues that these Chinese Marxist philosophers’ interpretations of Marxist philosophy were quite orthodox when judged by the standards of contemporary Soviet Marxism. The book explores core themes in Marxist philosophy in China, including the dilemma of determinism, and investigates the way in which these Chinese Marxist philosophers sought a formula for the ‘Sinification’ of Marxist philosophy that both retained the universal dimensions of Marxism and allowed its application to the Chinese context. The book concludes with analysis of the role of the Yanan New Philosophy Association in developing from Soviet Marxist philosophy the philosophical dimension of Mao Zedong Thought, the official ideology of the Chinese Communist Party after 1945.
Martingale Methods in Financial Modelling
This book provides a comprehensive, self-contained and up-to-date treatment of the main topics in the theory of option pricing. The first part of the text starts with discrete-time models of financial markets, including the Cox-Ross-Rubinstein binomial model. The passage from discrete- to continuous-time models, done in the Black-Scholes model setting, assumes familiarity with basic ideas and results from stochastic calculus. However, an Appendix containing all the necessary results is included. This model setting is later generalized to cover standard and exotic options involving several assets and/or currencies. An outline of the general theory of arbitrage pricing is presented. The second part of the text is devoted to the term structure modelling and the pricing of interest-rate derivatives. The main emphasis is on models that can be made consistent with market pricing practice.
Market-Consistent Actuarial Valuation
It is a challenging task to read the balance sheet of an insurance company. This derives from the fact that different positions are often measured by different yardsticks. Assets, for example, are mostly valued at market prices whereas liabilities are often measured by established actuarial methods. Market-Consistent Actuarial Valuation presents powerful methods to measure liabilities and assets in the same way. The mathematical framework that leads to market-consistent values for insurance liabilities is explained in detail by the authors. Topics covered are Stochastic discounting, Valuation portfolio in life and non-life insurance, Asset and liability management, Financial risks, Insurance technical risks, and Solvency.
Market-Conform Valuation of Options
we will investigate the 'market-conform' pricing of newly issued contingent claims. A contingent claim is a derivative whose value at any settlement date is determined by the value of one or more other underlying assets, e. g. , forwards, futures, plain-vanilla or exotic options with European or American-style exercise features. Market-conform pricing means that prices of existing actively traded securities are taken as given, and then the set of equivalent martingale measures that are consistent with the initial prices of the traded securities is derived using no-arbitrage arguments.
Manual of Digital Earth
This book offers a summary of the development of Digital Earth over the past twenty years. By reviewing the initial vision of Digital Earth, the evolution of that vision, the relevant key technologies, and the role of Digital Earth in helping people respond to global challenges, this publication reveals how and why Digital Earth is becoming vital for acquiring, processing, analysing and mining the rapidly growing volume of global data sets about the Earth.
Managing Risk and Information Security : Protect to Enable
Examine the evolving enterprise security landscape and discover how to manage and survive risk. While based primarily on the author’s experience and insights at major companies where he has served as CISO and CSPO, the book also includes many examples from other well-known companies and provides guidance for a management-level audience. Managing Risk and Information Security provides thought leadership in the increasingly important area of enterprise information risk and security. It describes the changing risk environment and why a fresh approach to information security is needed. Because almost every aspect of an enterprise is now dependent on technology not only for internal operations but increasing as a part of product or service creation, the focus of IT security must shift from locking down assets to enabling the business while managing and surviving risk. This edition discusses business risk from a broader perspective, including privacy and regulatory considerations. It describes the increasing number of threats and vulnerabilities and offers strategies for developing solutions. These include discussions of how enterprises can take advantage of new and emerging technologies—such as social media and the huge proliferation of Internet-enabled devices—while minimizing risk.
Management of deep carious lesions
Describes the challenges that deep carious lesions pose for dental practitioners, including the risk of endodontic complications and the difficulty of restorative treatment, and identifies options for overcoming these challenges on the basis of the best available evidence. The opening chapter sets the scene by discussing pathophysiology, histopathology, clinical symptomatology, and treatment thresholds. The various treatment options are then systematically presented and reviewed, covering non-selective, stepwise, and selective carious tissue removal and restoration, sealing of lesions using resin sealants or crowns, and non-restorative management approaches. In each case the current evidence with respect to the treatment is carefully evaluated. Advantages and disadvantages are explained and recommendations made on when to use the treatment in question. Illustrative clinical cases and treatment pathways for clinicians are included. This book will be of value for all practitioners who treat dental caries and carious lesions, whether in the permanent or the primary dentition. It will also be of interest to under- and postgraduate students in cariology and restorative, operative, preventive, and pediatric dentistry.
Machine Learning in Computer Vision
The goal of this book is to address the use of several important machine learning techniques into computer vision applications. An innovative combination of computer vision and machine learning techniques has the promise of advancing the field of computer vision, which contributes to better understanding of complex real-world applications. The effective usage of machine learning technology in real-world computer vision problems requires understanding the domain of application, abstraction of a learning problem from a given computer vision task, and the selection of appropriate representations for the learnable (input) and learned (internal) entities of the system. In this book, we address all these important aspects from a new perspective: that the key element in the current computer revolution is the use of machine learning to capture the variations in visual appearance, rather than having the designer of the model accomplish this. As a bonus, models learned from large datasets are likely to be more robust and more realistic than the brittle all-design models.
Machine Learning for Multimedia Content Analysis
Challenges in complexity and variability of multimedia data have led to revolutions in machine learning techniques. Multimedia data, such as digital images, audio streams and motion video programs, exhibit richer structures than simple, isolated data items. A number of pixels in a digital image collectively conveys certain visual content to viewers. A TV video program consists of both audio and image streams that unfold the underlying story. To recognize the visual content of a digital image, or to understand the underlying story of a video program, we may need to label sets of pixels or groups of image and audio frames jointly.
