Refine Results
Sort By
From
To
Page 15
Page 15
Applications of Agent Technology in Traffic and Transportation
Building effective and user-friendly transportation systems is one of the big challenges for engineers in the 21st century. There is an increasing need to understand, model, and govern such systems at both the individual (micro) and the society (macro) level. Still, this raises significant technical problems, as transportation systems may contain thousands of autonomous, "intelligent" entities that need to be simulated and/or controlled. Therefore, traffic and transportation scenarios are extraordinarily appealing for Distributed Artificial Intelligence, and (multi-) agent technology in particular. This book gives an overview of recent advances in agent-based transportation systems. It includes both a state-of-the-art survey and reports on cutting-edge research in the field.
Applications and Innovations in Intelligent Systems XV ; Proceedings of AI-2007, the Twenty-seventh SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence
The papers in this volume are the refereed application papers presented at AI-2007, the Twenty-seventh SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge in December 2007.
Application of power electronics converters in smart grids and renewable energy systems
Focuses on the applications of Power Electronics Converters in smart grids and renewable energy systems. The topics covered include methods to CO2 emission control, schemes for electric vehicle charging, reliable renewable energy forecasting methods, and various power electronics converters. The converters include the quasi neutral point clamped inverter, MPPT algorithms, the bidirectional DC-DC converter, and the push–pull converter with a fuzzy logic controller.
Anomaly Detection : Techniques and Applications
When information in the data warehouse is processed, it follows a definite pattern. An unexpected deviation in the data pattern from the usual behavior is called an anomaly. The anomaly in the data is also referred to as noise, outlier, spammer, deviations, novelties and exceptions. Identification of the rare items, events, observations, patterns which raise suspension by differing significantly from the majority of data is called anomaly detection. With progress in the technologies and the widespread use of data for the purpose for business the increase in the spams faced by the individuals and the companies are increasing day by day. This noisy data has boomed as a major problem in various areas such as Internet of Things, web service, Machine Learning, Artificial Intelligence, Deep learning, Image Processing, Cloud Computing, Audio processing, Video Processing, VoIP, Data Science, Wireless Sensor etc. Identifying the anomaly data and filtering them before processing is a major challenge for the data analyst. This anomaly is unavoidable in all areas of research. This book covers the techniques and algorithms for detecting the deviated data.
Analyzing computer system performance with Perl::PDQ
Analyzing computer system performance is often regarded by most system administrators, IT professionals and software engineers as a black art that is too time consuming to learn and apply. Finally, this book by acclaimed performance analyst Dr. Neil Gunther makes this subject understandable and applicable through programmatic examples. The means to this end is the open-source performance analyzer Pretty Damn Quick (PDQ) written in Perl As the epigraph in this book points out, Common sense is the pitfall of performance analysis. The performance analysis framework that replaces common sense is revealed in the first few chapters of Part I. The important queueing concepts embedded in PDQ are explained in a very simple style that does not require any knowledge of formal probability theory. Part II begins with a full specification of how to set up and use PDQ replete with examples written in Perl. Subsequent chapters present applications of PDQ to the performance analysis of multicomputer architectures, benchmark results, client/server scalability, and Web-based applications.
Analysis and Development of Sustainable Urban Production Systems
Manufacturing of products in urban production sites is connected to unique potentials, yet also to specific challenges. Urban factories can provide functional diversity and contribute positive impacts to a city. The concept of urban production receives rising attention in research and industry and it is recognized in its interdisciplinary nature. With a holistic approach from both the urban perspective and the factory perspective, negative impacts can be minimized, positive effects enabled and mutually beneficial, symbiotic combinations created. The presented framework and methods for the evaluation and implementation of sustainable urban production systems allow the assessment of impacts and provide the means to control and utilize the unique strengths of urban factories for cities and industry. This will allow a structured derivation of methods and measures from the concept of urban production for producing enterprises and the urban stakeholders.
An Undergraduate Primer in Algebraic Geometry
This book consists of two parts. The first is devoted to an introduction to basic concepts in algebraic geometry: affine and projective varieties, some of their main attributes and examples. The second part is devoted to the theory of curves: local properties, affine and projective plane curves, resolution of singularities, linear equivalence of divisors and linear series, Riemann–Roch and Riemann–Hurwitz Theorems.The approach in this book is purely algebraic. The main tool is commutative algebra, from which the needed results are recalled, in most cases with proofs. The prerequisites consist of the knowledge of basics in affine and projective geometry, basic algebraic concepts regarding rings, modules, fields, linear algebra, basic notions in the theory of categories, and some elementary point–set topology.
An Introduction to Quantum and Vassiliev Knot Invariants
Provides an accessible introduction to knot theory, focussing on Vassiliev invariants, quantum knot invariants constructed via representations of quantum groups, and how these two apparently distinct theories come together through the Kontsevich invariant. Consisting of four parts, the book opens with an introduction to the fundamentals of knot theory, and to knot invariants such as the Jones polynomial. The second part introduces quantum invariants of knots, working constructively from first principles towards the construction of Reshetikhin-Turaev invariants and a description of how these arise through Drinfeld and Jimbo's quantum groups. Its third part offers an introduction to Vassiliev invariants, providing a careful account of how chord diagrams and Jacobi diagrams arise in the theory, and the role that Lie algebras play. The final part of the book introduces the Konstevich invariant. This is a universal quantum invariant and a universal Vassiliev invariant, and brings together these two seemingly different families of knot invariants. The book provides a detailed account of the construction of the Jones polynomial via the quantum groups attached to sl(2), the Vassiliev weight system arising from sl(2), and how these invariants come together through the Kontsevich invariant.
An introduction to ontology engineering
Provides the reader with a comprehensive introductory overview of ontology engineering. A secondary aim is to provide hands-on experience in ontology development that illustrate the theory. The book is divided into three blocks: Block I: logic foundations for ontologies both regarding the languages (mainly First Order predicate Logic, Description Logics, and OWL) and automated reasoning. Block II: developing good ontologies with methods and methodologies, the top-down approach with foundational ontologies, and the bottom-up approach to extract as much useful content as possible from legacy material. Block III: advanced topics with a selection of areas of specialisation, including Ontology-Based Data Access, the interaction between ontologies and natural languages (multilingual ontologies, controlled natural language), and advanced modelling with additional language features (fuzzy and temporal ontologies)
An Introduction to Language Processing with Perl and Prolog : An Outline of Theories, Implementation, and Application with Special Consideration of English, French, and German
This book teaches the principles of natural language processing, first covering linguistics issues such as encoding, entropy, and annotation schemes; defining words, tokens and parts of speech; and morphology. It then details the language-processing functions involved, including part-of-speech tagging using rules and stochastic techniques; using Prolog to write phase-structure grammars; parsing techniques and syntactic formalisms; semantics, predicate logic and lexical semantics; and analysis of discourse, and applications in dialog systems. The key feature of the book is the author's hands-on approach throughout, with extensive exercises, sample code in Prolog and Perl, and a detailed introduction to Prolog. The reader is supported with a companion website that contains teaching slides, programs, and additional material.
An Introduction to Knowledge Engineering
Knowledge Engineering refers to the development of systems that use knowledge, rather than data, to solve many novel computing problems. This is achieved by the application of computing techniques, closely associated with human cognitive processes, for transforming data into knowledge. An Introduction to Knowledge Engineering presents a simple but detailed exploration of current and established work in the field.
An introduction to description logics
Designed so that domain knowledge can be described and so that computers can reason about this knowledge. DLs have recently gained increased importance since they form the logical basis of widely used ontology languages, in particular the web ontology language OWL. Written by four renowned experts, this is the first textbook on description logics. It is suitable for self-study by graduates and as the basis for a university course. Starting from a basic DL, the book introduces the reader to their syntax, semantics, reasoning problems and model theory and discusses the computational complexity of these reasoning problems and algorithms to solve them.
Ambisonics : A Practical 3D Audio Theory for Recording, Studio Production, Sound Reinforcement, and Virtual Reality
Provides a concise explanation of the fundamentals and background of the surround sound recording and playback technology Ambisonics. It equips readers with the psychoacoustical, signal processing, acoustical, and mathematical knowledge needed to understand the inner workings of modern processing utilities, special equipment for recording, manipulation, and reproduction in the higher-order Ambisonic format. The book comes with various practical examples based on free software tools and open scientific data for reproducible research. The book includes an extensive mathematical appendix. The book offers readers a deeper understanding of Ambisonic technologies, and will especially benefit scientists, audio-system and audio-recording engineers.
Ambient intelligence : A novel paradigm
Ambient Intelligence (AmI) is an integrating technology for supporting a pervasive and transparent infrastructure for implementing smart environments. Such technology is used to enable environments for detecting events and behaviors of people and for responding in a contextually relevant fashion. AmI proposes a multi-disciplinary approach for enhancing human machine interaction. The authors start with a description of the iDorm as an example of a smart environment conforming to the AmI paradigm, and introduces computer vision as an important component of the system. Other computer vision examples describe visual monitoring for the elderly, classic and novel surveillance techniques using clusters of cameras installed in indoor and outdoor application domains, and the monitoring of public spaces. Face and speech recognition systems are also covered as well as enhanced LEGO blocks for novel educational purposes. The book closes with a provocative chapter on how a cybernetic system can be designed as the backbone of a human machine interaction.
Algorithms on Trees and Graphs : With Python Code
Introduces graph algorithms on an intuitive basis followed by a detailed exposition using structured pseudocode, with correctness proofs as well as worst-case analyses. Centered around the fundamental issue of graph isomorphism, the content goes beyond classical graph problems of shortest paths, spanning trees, flows in networks, and matchings in bipartite graphs. Advanced algorithmic results and techniques of practical relevance are presented in a coherent and consolidated way. Numerous illustrations, examples, problems, exercises, and a comprehensive bibliography support students and professionals in using the book as a text and source of reference. Furthermore, Python code for all algorithms presented is given in an appendix. Topics and features: Algorithms are first presented on an intuitive basis, followed by a detailed exposition using structured pseudocode / Correctness proofs are given, together with a worst-case analysis of the algorithms / Full implementation of all the algorithms in Python / An extensive chapter is devoted to the algorithmic techniques used in the book / Solutions to all the problems
Algorithms in Bioinformatics : Theory and Implementation
Explores a comprehensive and insightful treatment of the practical application of bioinformatic algorithms in a variety of fields. Delivers a fulsome treatment of some of the main algorithms used to explain biological functions and relationships. It introduces readers to the art of algorithms in a practical manner which is linked with biological theory and interpretation. The book covers many key areas of bioinformatics, including global and local sequence alignment, forced alignment, detection of motifs, Sequence logos, Markov chains or information entropy. Other novel approaches are also described, such as Self-Sequence alignment, Objective Digital Stains (ODSs) or Spectral Forecast and the Discrete Probability Detector (DPD) algorithm. Readers will also benefit from the inclusion of: A detailed presentation of new methods, such as Self-sequence alignment, Objective Digital Stains and Spectral Forecast ; A treatment of sequence alignment, including local sequence alignment, global sequence alignment and forced sequence alignment with full implementations ; Discussions of position-specific weight matrices, including the count, weight, relative frequencies, and log-likelihoods matrices ; A detailed presentation of the methods related to Markov Chains as well as a description of their implementation in Bioinformatics and adjacent fields ; An examination of information and entropy, including sequence logos and explanations related to their meaning ; A chapter on philosophical transactions that allows the reader a broader view of the prediction process ; Extensive worked examples with detailed case studies that point out the meaning of different results
Algorithms for Sensor and Ad Hoc Networks : Advanced Lectures
Thousands of mini computers (comparable to a stick of chewing gum in size), equipped with sensors, are deployed in some terrain or other. After activation the sensors form a self-organized network and provide data, for example about a forthcoming earthquake. The trend towards wireless communication increasingly affects electronic devices in almost every sphere of life. Conventional wireless networks rely on infrastructure such as base stations; mobile devices interact with these base stations in a client/server fashion. In contrast, current research is focusing on networks that are completely unstructured, but are nevertheless able to communicate (via several hops) with each other, despite the low coverage of their antennas. Such systems are called sensor or ad hoc networks, depending on the point of view and the application. Wireless ad hoc and sensor networks have gained an incredible research momentum. Computer scientists and engineers of all flavors are embracing the area. Sensor networks have been adopted by researchers in many fields: from hardware technology to operating systems, from antenna design to databases, from information theory to networking, from graph theory to computational geometry.
Algorithms and Models for the Web-Graph ; 4th International Workshop, WAW 2006, Banff, Canada, November 30 - December 1, 2006. Revised Papers
his book constitutes the revised papers of the Fourth International Workshop on Algorithms and Models for the Web-Graph, WAW 2006, held in Banff, Canada, November 30 - December 1, 2006.
Algorithmic Learning in a Random World
This new monograph integrates mathematical theory and revealing experimental work. It demonstrates mathematically the validity of the reliability claimed by conformal predictors when they are applied to independent and identically distributed data, and it confirms experimentally that the accuracy is sufficient for many practical problems. Later chapters generalize these results to models called repetitive structures, which originate in the algorithmic theory of randomness and statistical physics. The approach is flexible enough to incorporate most existing methods of machine learning, including newer methods such as boosting and support vector machines and older methods such as nearest neighbors and the bootstrap.
Algorithmic Aspects of Bioinformatics
Advances in bioinformatics and systems biology require improved computational methods for analyzing data, while progress in molecular biology is in turn influencing the development of computer science methods. This book introduces some key problems in bioinformatics, discusses the models used to formally describe these problems, and analyzes the algorithmic approaches used to solve them. After introducing the basics of molecular biology and algorithmics, Part I explains string algorithms and alignments; Part II details the field of physical mapping and DNA sequencing; and Part III examines the application of algorithmics to the analysis of biological data. Exciting application examples include predicting the spatial structure of proteins, and computing haplotypes from genotype data. This book describes topics in detail and presents formal models in a mathematically precise, yet intuitive manner, with many figures and chapter summaries, detailed derivations, and examples. It is well suited as an introduction into the field of bioinformatics, and will benefit students and lecturers in bioinformatics and algorithmics, while also offering practitioners an update on current research topics.
