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• Blackboard Essentials for Teachers; Blackboard Essentials for Teachers; Credits; About the Author; About the Reviewers; www.PacktPub.com; Support files, eBooks, discount offers and more; Why Subscribe?; Free Access for Packt account holders; Preface; What this book covers; What you need for this book; Who this book is for; Conventions; Reader feedback; Customer support; Errata; Piracy; Questions;
• 1. The Blackboard Experience; Home page; Announcements; Discussion Board; Gradebook; Content Page; Learning Module; Blog; Forum; Uploaded files; Video; Wiki; Assignment; Test; Groups; Summary.

• 2. Organizing a Course with Pages and Learning ModulesAdding Content Areas to hold and organize course content; What is Content Area?; How to add a Content Area; What's next?; Adding a Blank Page tool, which can hold any content or links that you want; What is a Blank Page?; How to add a Blank Page; What's next?; Adding a Blank Page to your course; Adding a Blank Page to the Content Area; Composing a page with the HTML editor; What's next?; Creating a sequential path for the student to work through, using a Learning Module; When to use a learning path; How to add a learning path.

• Adding a Learning Module to a Content AreaWhat's next?; About the Availability and View settings; Keeping students informed with Course Tools; What are Course Tools?; How to add Course Tools; Adding a Course Tool to the Course Menu; Adding a Course Tool to the home page; Summary;
• 3. Adding Static Material to a Course; Adding a file for students to download; File versus item; Content Collections; How to add a file; Adding an item; What's next?; Adding a video to your course; Uploading a video in your course; Linking to a video that is on another site; Embedding a video on a Blank Page.

• Embedding a video that is hosted on another siteWhat's next?; Adding a web link to your course; Adding a link to an external website; Adding a link to a Course Asset; Adding an image to your course; Adding an image to a Content Area; Summary;
• 4. Discussion Boards; About Discussion Boards; Creating forums with Discussion Board; Making Discussion Board available to students; Adding a link to Discussion Board on the Course Menu; Creating a link to a forum; Managing a forum; Collecting posts in a forum; Grading posts in a forum; Summary;
• 5. Blogs and Wikis; About blogs.

• Individual versus class blogsBlogs Course Tool link; Creating a blog; Making blogs available to students; Managing a blog; Grading blogs; Deleting and editing entries and comments; Adding a link to the Blogs page; Creating a link to a blog; About wikis; Creating a wiki; Adding a link to the Wikis page; Summary;
• 6. Assignments; About assignments; Adding an assignment; Responding to an assignment; Summary;
• 7. Testing Students; Creating a test; Creating a blank test; Determining the behavior of questions by using Question Settings; Adding and creating questions on Test Canvas.

This book develops a sample site with lots of step-by-step instructions and screenshots to get you up and running in no time at all. If you are a teacher or course builder, you need only basic computer skills to get the most from this book. You don't need any background in online teaching or building Web pages.
(source: Nielsen Book Data)

• Introduction to Recommender Systems Handbook.- Part I Basic Techniques.- Data Mining Methods for Recommender Systems.- Content-based Recommender Systems: State of the Art and Trends.- A Comprehensive Survey of Neighborhood-based Recommendation Methods.- Advances in Collaborative Filtering.- Developing Constraint-based Recommenders.- Context-Aware Recommender Systems.- Part II Applications and Evaluation of RSs.- Evaluating Recommendation Systems.- A Recommender System for an IPTV Service Provider: a Real Large-Scale Production Environment.- How to Get the Recommender Out of the Lab?.- Matching Recommendation Technologies and Domains.- Recommender Systems in Technology Enhanced Learning.- Part III Interacting with Recommender Systems.- On the Evolution of Critiquing Recommenders.- Creating More Credible and Persuasive Recommender Systems: The Influence of Source Characteristics on Recommender System Evaluations.- Designing and Evaluating Explanations for Recommender Systems.- Usability Guidelines for Product Recommenders Based on Example Critiquing Research.- Map Based Visualization of Product Catalogs.- Part IV Recommender Systems and Communities.- Communities, Collaboration, and Recommender Systems in Personalized Web Search.- Social Tagging Recommender Systems.- Trust and Recommendations.- Group Recommender Systems: Combining Individual Models.- Aggregation of Preferences in Recommender Systems.- Active Learning in Recommender Systems.- Multi-Criteria Recommender Systems.- Robust Collaborative Recommendation.- Index.
• (source: Nielsen Book Data)

The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these options. Recommender systems have proven to be a valuable way for online users to cope with the information overload and have become one of the most powerful and popular tools in electronic commerce. Correspondingly, various techniques for recommendation generation have been proposed. During the last decade, many of them have also been successfully deployed in commercial environments. Recommender Systems Handbook, an edited volume, is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and consumer behavior. Theoreticians and practitioners from these fields continually seek techniques for more efficient, cost-effective and accurate recommender systems. This handbook aims to impose a degree of order on this diversity, by presenting a coherent and unified repository of recommender systems' major concepts, theories, methodologies, trends, challenges and applications. Extensive artificial applications, a variety of real-world applications, and detailed case studies are included. Recommender Systems Handbook illustrates how this technology can support the user in decision-making, planning and purchasing processes. It works for well known corporations such as Amazon, Google, Microsoft and AT&T. This handbook is suitable for researchers and advanced-level students in computer science as a reference.
(source: Nielsen Book Data)

Using qualitative methods to deal with imperfect information. In this book Simon Parsons describes qualitative methods for reasoning under uncertainty, "uncertainty" being a catch-all term for various types of imperfect information. The advantage of qualitative methods is that they do not require precise numerical information. Instead, they work with abstractions such as interval values and information about how values change. The author does not invent completely new methods for reasoning under uncertainty but provides the means to create qualitative versions of existing methods. To illustrate this, he develops qualitative versions of probability theory, possibility theory, and the Dempster-Shafer theory of evidence. According to Parsons, these theories are best considered complementary rather than exclusive. Thus the book supports the contention that rather than search for the one best method to handle all imperfect information, one should use whichever method best fits the problem. This approach leads naturally to the use of several different methods in the solution of a single problem and to the complexity of integrating the results problem to which qualitative methods provide a solution.
(source: Nielsen Book Data)

• Preface
• Algorithms Based on Paraconsistent Annotated Logic for Applications in Expert Systems
• Expert Systems in Flow Analysis
• The Potential of Expert Systems in Remote Sensing Applications Domain
• Domain-Wide Expert System Applications
• Modeling a Parser as an Expert System
• Embedded Expert System for Cognitive Congestion & Flow Control in WLANs
• An Enhanced Approach for Developing an Expert System for Fund Raising Management
• Algebraic Approaches to the Development of Rule Based Expert Systems
• Application of Fuzzy Inference Systems (FIS) in the Mineral Industry
• Hierarchical Fuzzy Expert Decision Making Systems
• Index.
• (source: Nielsen Book Data)

This book presents current research in the study of expert system software, including algorithms based on paraconsistent annotated logic in expert systems; expert flow systems in the agronomical, industrial, environmental, pharmaceutical and geological fields; expert systems in remote sensing; domain-wide expert system applications; modeling a parser as an expert system; embedded expert systems for flow control of delay sensitive real-time traffic in WLANs; expert systems in fund-raising management and algebraic approaches in the development of rule based expert systems.
(source: Nielsen Book Data)

• Editorial Preface
• 1. Contextual and Conceptual Information Retrieval and Navigation on the Web
• 2. Automatic Invocation Linking for Collaborative Web-Based Corpora
• 3. WS-Query - A Framework to Efficiently Query Semantic Web Service
• 4. RDF-GL: A SPARQL-Based Graphical Query Language for RDF
• 5. Semantics-based Intelligent Indexing and Retrieval of Digital Images - A Case Study
• 6. Harvesting Intelligence in Multimedia Social Tagging Systems
• 7. User Profiles Modeling in Information Retrieval Systems
• 8. Human-Web Interactions
• 9. Web Recommender Agents with Inductive Learning Capabilities
• 10. Capturing the Semantics of User interaction: A Review and Case Study
• 11. Analysis of Usage Patterns in Large Multimedia Websites
• 12. An Adaptation Framework for Web Multimedia Presentations
• 13. A Multifactor Secure Authentication System For Wireless Payment
• 14. A Lightweight Authentication Protocol for Web Applications in Mobile Environments
• 15. Developing Access Control Model of Web OLAP over Trusted and Collaborative Data Warehouses
• 16. Security in distributed collaborative environments: limitations and solutions
• 17. A Low-cost and secure solution for e-commerce
• 18. Hyperchaotic Encryption for Secure E-Mail Communication.
• (source: Nielsen Book Data)

Richard Chbeir, Youakim Badr, Ajith Abraham, and Aboul-Ella Hassanien Abstract As the Web continues to grow and evolve, more and more data are becoming available. Particularly, multimedia and XML-based data are produced regularly and in increasing way in our daily digital activities, and their retrieval and access must be explored and studied in this emergent web-based era. This book provides reviews of the cutting-edge technologies and insights of various topics related to XML-based and multimedia information access and retrieval under the umbrella of Web Intelligence and reporting how organizations can gain compe- tive advantages by applying new different emergent techniques in the real-world scenarios. The primary target audience for the book includes researchers, scholars, postgraduate students and developers who are interested in advanced information retrieval on the web research and related issues. 1 Introduction Since the last two decades, Internet has changed our daily life by rede?ning the meanings and processes of business, commerce, marketing, ?nance, publishing, R. Chbeir Universite ' de Bourgogne, LE2I-UMR CNRS 5158, Fac. de Sciences Mirande, 21078 Dijon Cedex, France e-mail: richard. chbeir@u-bourgogne. fr Y. Badr INSA de Lyon, Universite ' de Lyon, Depart ' ement Informatique, 7 avenue Jean Capelle, 69621 Villeurbanne CX, France e-mail: youakim. badr@insa-lyon. fr A. Abraham Norwegian University of Science & Technology, Center for Quanti?able Quality of Service in Communication Systems, O. S. Bragstads plass 2E, 7491 Trondheim, Norway e-mail: ajith. abraham@ieee. org A. -E. Hassanien Kuwait University, College of Business & Administration, Dept.
(source: Nielsen Book Data)

• Editorial Preface
• 1. The Dilated Triple
• 2. Semantic Web Technologies and Artificial Neural Networks for Intelligent Web Knowledge Source Discovery
• 3. Computing Similarity of Semantic Web Services in Semantic Nets with Multiple Concept Relations
• 4. General-Purpose Computing on a Semantic Network Substrate
• 5. Agent Technology meets the Semantic Web: Interoperability and Communication Issues
• 6. Mining of Semantic Image Content Using Collective Web Intelligence
• 7. Suited Support for Distributed Web Intelligence Cooperative Work
• 8. Web services and Software Agents for Tailorable Groupware Design
• 9. Toward Distributed Knowledge Discovery on Grid systems
• 10. Metamodel of ontology learning from text
• 11. An Analysis of Constructed Categories for Textual Classification using Fuzzy Similarity and Agglomerative Hierarchical Methods
• 12. Emergent XML mining: Discovering an efficient mapping from XML instances to relational schemas
• 13. XML based information systems and formal semantics of programming languages
• 14. Modeling and Testing of Web Based Systems
• 15. Web-Based Support By Thin-Client Co-Browsing
• 16. NetPay Micro-payment Protocols for three Networks
• 17. Enforcing Honesty in Fair Exchange Protocols.
• (source: Nielsen Book Data)

The success of the World Wide Web depends on the ability of users to store, p- cess and retrieve digital information regardless of distance boundaries, languages and domains of knowledge. The universality and ?exibility of the World Wide Web have also enabled the rapid growth of a variety of new services and applications based on human-machine interaction. The semantics of exchanged information and services should be useful not only for human to human communications, but also in that machines would be able to understand and automatically process web content. Semanticsgive well-de?nedmeaningto web content and enable computersand p- ple to work in cooperation. Today, the crucial challenge becomes the development of languages to express information in a machine processable format. Now more than ever, new advanced techniques and intelligent approaches are required to tra- form the Web into a universal reasoning and computing machine. Web intelligence attempts to deal with this challenge by exploiting information technologies and - ti?cial intelligence approaches to design the next generation of web-empowered systems and services.
(source: Nielsen Book Data)

• Introduction
• Reminders on Relational Databases
• Basic Notions on Fuzzy Sets
• Non-Fuzzy Approaches to Preference Queries: A Brief Overview
• Simple Fuzzy Queries
• Fuzzy Queries Involving Quantified Statements or Aggregates
• Division and Antidivision of Fuzzy Relations
• Bipolar Fuzzy Queries
• Fuzzy Group By
• Empty and Plethoric Answers.
• (source: Nielsen Book Data)

The manipulation of databases is an integral part of a world which is becoming increasingly and pervasively information-focused. This book puts forward a suggestion to advocate preference queries and fuzzy sets as a central concern in database queries and offers an important contribution to the design of intelligent information systems. It provides a comprehensive study on fuzzy preference queries in the context of relational databases. Preference queries, a recent hot topic in database research, provide a basis for rank-ordering the items retrieved, which is especially valuable for large sets of answers.This book aims to show that fuzzy set theory constitutes a highly expressive framework for modeling preference queries. It presents a study of the algorithmic aspects related to the evaluation of such queries in order to demonstrate that this framework offers a good trade-off between expressivity and efficiency. Numerous examples and proofs are liberally and lucidly demonstrated throughout, and greatly enhance the detailed theoretical aspects explored in the book.Researchers working in databases will greatly benefit from this comprehensive and up-to-date study of fuzzy preference queries, and it will also become an invaluable reference point for postgraduate students interested in advanced database techniques.The only other books which deal with this topic are edited books or conference proceedings which include a few contributions about some specific aspects of the question. This book provides a comprehensive view of the issue, starting with basic notions related to relational databases and fuzzy set theory, up to the detailed study of complex fuzzy queries and the way they can be efficiently processed. It is the compendium of more than 20 years of research by the authors who benefit from a great international recognition in the domain of intelligent information systems, on the subject.
(source: Nielsen Book Data)

• The JADE platform and experiences with mobile MAS applications / Fabio Bellifemine, Giovanni Caire, Giosue Vitaglione, Giovanni Rimassa and Dominic Greenwood
• A-globe : agent development platform with inaccessibility and mobility support / David Sislak, Martin Rehak, Michal Pechoucek, Milan Rollo and Dusan Pavlicek
• Supporting agent development in Erlang through the eXAT platform / Antonella Di Stefano and Corrado Santoro
• Living systems technology suite / Giovanni Rimassa, Monique Calisti and Martin E. Kernland
• Multi agent system development kit / Vladimir Gorodetsky, Oleg Karsaev, Vladimir Samoylov, Victor Konushy, Evgeny Mankov and Alexey Malyshev.

This book introduces major agent platforms, frameworks, systems, tools, and applications. Each system is described by their developers in sufficient detail so that the reader can get a good understanding of the architecture, functionality, and application areas of the system. All systems are running systems. One main focus of the book lies on agent platforms and toolkits.
(source: Nielsen Book Data)

The Knowledge Grid is an intelligent and sustainable interconnection environment that enables people and machines to effectively capture, publish, share and manage knowledge resources. It also provides appropriate on-demand services to support scientific research, technological innovation, cooperative teamwork, problem solving, and decision making. It incorporates epistemology and ontology to reflect human cognitive characteristics; exploits social, ecological and economic principles; and adopts techniques and standards developed during work toward the future web. This book presents its methodology, theory, models and applications systematically for the first time.
(source: Nielsen Book Data)

• Foreword; Preface; Contents;
• Chapter 1 The Knowledge Grid Methodology;
• Chapter 2 The Semantic Link Network;
• Chapter 3 A Resource Space Model;
• Chapter 4 The Single Semantic Image;
• Chapter 5 Knowledge Flow;
• Chapter 6 Exploring Scale-Free Networks; Bibliography; Index.

The Knowledge Grid is an intelligent and sustainable interconnection environment that enables people and machines to effectively capture, publish, share and manage knowledge resources. It also provides appropriate on-demand services to support scientific research, technological innovation, cooperative teamwork, problem solving, and decision making. It incorporates epistemology and ontology to reflect human cognitive characteristics; exploits social, ecological and economic principles; and adopts techniques and standards developed during work toward the future web. This book presents its method.

• Genetic Algorithms for Design
• Evolutionary and Immune Computations in Optimal Design and Inverse Problems
• Applications of GA and GP to Industrial Design Optimization and Inverse Problems
• Advances in Neural Networks in Computational Mechanics and Engineering
• Selected Problems of Artificial Neural Networks Development
• Neural Networks: Some Successful Applications in Computational Mechanics.

The articles in this book present advanced soft methods related to genetic and evolutionary algorithms, immune systems, formulation of deterministic neural networks and Bayesian NN. Many attention is paid to hybrid systems for inverse analysis fusing soft methods and the finite element method. Numerical efficiency of these soft methods is illustrated on the analysis and design of complex engineering structures.

• Preface
• 1. Declarative programming in AnsProlog*: introduction and preliminaries
• 2. Simple modules for declarative programming with answer sets
• 3. Principles and properties of declarative programming with answer sets
• 4. Declarative problem solving and reasoning in AnsProlog*
• 5. Reasoning about actions and planning in AnsProlog*
• 6. Complexity, expressiveness, and other properties of AnsProlog* programs
• 7. Answer set computing algorithms
• 8. Query answering and answer set computing systems
• 9. Further extensions of and alternatives to AnsProlog*
• 10. Appendix A: Ordinals, lattices, and fixpoint theory
• 11. Appendix B: Turing machines
• Bibliography
• Index of notation
• Index of terms.
• (source: Nielsen Book Data)

Knowledge management and knowledge-based intelligence are areas of importance in the economy and society, and to exploit them fully and efficiently it is necessary both to represent and reason about knowledge via a declarative interface whose input language is based on logic. In this book, originally published in 2003, Chitta Baral shows exactly how to go about doing that: how to write programs that behave intelligently by giving them the ability to express knowledge and reason about it. He presents a language, AnsProlog, for both knowledge representation and reasoning, and declarative problem solving. The results have been organised here into a form that will appeal to practising and would-be knowledge engineers wishing to learn more about the subject, either in courses or through self-teaching. A comprehensive bibliography rounds off the book.
(source: Nielsen Book Data)

• Title Page; Preface; Contents; Goals of Modularity: A Voice from the Foundational Viewpoint; Modularity Issues in Biomedical Ontologies; Query Inseparability and Module Extraction in OWL 2 QL; Applying Community Detection Algorithms on Ontologies for Identifying Concept Groups; The Modular Structure of an Ontology: Atomic Decomposition and Module Count; Modular Approach for a New Ontology; Exploiting Modularity for Ontology Verification; Modularization Requirements in Bio-Ontologies: A Case Study of ChEBI.

• Modeling the Diversity of Spatial Information by Using Modular Ontologies and Their CombinationsSimple Reasoning for Contextualized RDF Knowledge; The Onto-Logical Translation Graph; Constructing an Ontology Repository: A Case Study with Theories of Time Intervals; Subject Index; Author Index.

Modularity has been and continues to be one of the central research topics in ontology engineering, still catching up with 40 years of related research in software engineering. The workshops on Modular Ontologies (WoMO) bring together researchers from different disciplines who study the problem of modularity in ontologies at a fundamental level, develop design tools for distributed ontology engineering, and apply modularity to different use cases and application scenarios. The contributions in this volume are of interest to researchers, students and practitioners interested in foundations of o.

• The Mathematical Theory of Fuzzy Systems
• Fuzzy Logic, Systems and Control
• Fuzzy Optimization and Decision-Making
• Fuzzy Information, Identification and Clustering
• Fuzzy Engineering Application and Soft Computing Method.

This book is the proceedings of the 5th Annual Conference on Fuzzy Information and Engineering (ACFIE2010) from Sep. 23-27, 2010 in Huludao, China. This book contains 89 papers, divided into five main parts: In Section I, we have 15 papers on “the mathematical theory of fuzzy systems”. In Section II, we have 15 papers on “fuzzy logic, systems and control”. In Section III, we have 24 papers on “fuzzy optimization and decision-making”. In Section IV, we have 17 papers on “fuzzy information, identification and clustering”. In Section V, we have 18 papers on “fuzzy engineering application and soft computing method”.

• and Preliminaries.- Basic Notions.- Rough Sets.- Relational and Deductive Databases.- Non-Monotonic Reasoning.- From Relations to Knowledge Representation.- Rough Knowledge Databases.- Combining Rough and Crisp Knowledge.- Weakest Sufficient and Strongest Necessary Conditions.- CAKE: Computer Aided Knowledge Engineering.- Formalization of Default Logic Using CAKE.- A UAV Scenario: A Case Study.- From Sensors to Relations.- Information Granules.- Tolerance Spaces.- A Rough Set Approach to Machine Learning.- UAV Learning Process: A Case Study.
• (source: Nielsen Book Data)

This book contains a cohesive, self-contained collection of theoretical and applied research results that have been achieved in this project which pertain to nonmonotonic and approximate easoning systems developed for an experimental unmanned aerial vehicle system used in the project. This book should be of interest to the theoretician and applied researcher alike and to autonomous system developers and software agent and intelligent system developers.
(source: Nielsen Book Data)

This book highlights recent research on Intelligent Systems and Nature Inspired Computing. It presents 212 selected papers from the 18th International Conference on Intelligent Systems Design and Applications (ISDA 2018) and the 10th World Congress on Nature and Biologically Inspired Computing (NaBIC), which was held at VIT University, India. ISDA-NaBIC 2018 was a premier conference in the field of Computational Intelligence and brought together researchers, engineers and practitioners whose work involved intelligent systems and their applications in industry and the "real world." Including contributions by authors from over 40 countries, the book offers a valuable reference guide for all researchers, students and practitioners in the fields of Computer Science and Engineering

• Logical Foundations of Rule-Based Systems.- Propositional Logic.- Predicate Calculus.- Attribute Logic.- Resolution.- Dual Resolution.- Principles of Rule-Based Systems.- Basic Structure of Rule-Based Systems.- Rule-Based Systems in Propositional Logic.- Rule-Based Systems in Attributive Logic.- Rule-Based Systems in First-Order Logic.- Inference Control in Rule-Based Systems.- Logic Programming and Prolog.- Verification of Rule-Based Systems.- Principles of Verification of Rule-Based Systems.- Analysis of Redundancy.- Analysis of Indeterminism and Inconsistency.- Reduction of Rule-Based Systems.- Analysis of Completeness.- Design of Rule-Based Systems.- An Introduction to Design of Rule-Based Systems.- Logical Foundations: the ?-Trees Based Approach.- Design of Tabular Rule-Based Systems with XTT.- Design Example: Thermostat.- Concluding Remarks.
• (source: Nielsen Book Data)

Thinking in terms of facts and rules is perhaps one of the most common ways of approaching problem de?nition and problem solving both in everyday life and under more formal circumstances. The best known set of rules, the Ten Commandments have been accompanying us since the times of Moses; the Decalogue proved to be simple but powerful, concise and universal. It is logically consistent and complete. There are also many other attempts to impose rule-based regulations in almost all areas of life, including professional work, education, medical services, taxes, etc. Some most typical examples may include various codes (e.g. legal or tra?c code), regulations (especially military ones), and many systems of customary or informal rules. The universal nature of rule-based formulation of behavior or inference principles follows from the concept of rules being a simple and intuitive yet powerful concept of very high expressive power. Moreover, rules as such encode in fact functional aspects of behavior and can be used for modeling numerous phenomena.
(source: Nielsen Book Data)

• Segmenting time series : a survey and novel approach / E. Keogh [and others]
• A survey of recent methods for efficient retrieval of similar time sequences / M.L. Hetland
• Indexing of compressed time series / E. Fink and K.B. Pratt
• Indexing time-series under conditions of noise / M. Vlachos, D. Gunopulos, and G. Das
• Change detection in classification models induced from time series data / G. Zeira [and others]
• Classification and detection of abnormal events in time series of graphs / H. Bunke and M. Kraetzl
• Boosting interval-based literals : variable length and early classification / C.J. Alonso González and J.J. Rodríguez Diez
• Median strings : a review / X. Jiang, H. Bunke, and J. Csirik.

Adding the time dimension to real-world databases produces Time Series Databases (TSDB) and introduces new aspects and difficulties to data mining and knowledge discovery. This book covers the state-of-the-art methodology for mining time series databases. The novel data mining methods presented in the book include techniques for efficient segmentation, indexing, and classification of noisy and dynamic time series. A graph-based method for anomaly detection in time series is described and the book also studies the implications of a novel and potentially useful representation of time series as strings. The problem of detecting changes in data mining models that are induced from temporal databases is additionally discussed.
(source: Nielsen Book Data)

Intended for those who have at least a cursory understanding of Infusionsoft and already know how to use the visual drag and drop builders (campaign builder, e-mail builder, and so on). Perhaps you've set up a couple of things already and want to take it to the next level. Maybe you are very fluent in the software but lack the high-level strategic understanding of how to take your business and automate it for the better. If you are a certified partner that has been around for a long time, this book will empower you to provide better results for your clients, faster!.
(source: Nielsen Book Data)

• Fuzzy (r, s)-minimal preopen sets and fuzzy (r, s)-M precontinuous mappings on (r, s)-fuzzy minimal spaces.- On fuzzy (r, s)-minimal ss-open sets on (r, s)-fuzzy minimal spaces.- Handling Very Large Cooccurrence Matrices in Fuzzy Co-clustering by Sampling Approaches.- Fuzzy c-Regression Models Based on Optimal Scaling of Categorical Observation with Tolerance.- Building a Knowledge Base for Expert System in Information Security.- Fuzzy logic and neural network based induction control in a diesel engine.- Evaluation and Analysis of Relationship and Individual Role Adaptation for Team Sports using SOM.- Recursive Neuro-Fuzzy Algorithm for Flow Prediction and Pump On-Off Minimization
• Logotype Design Support System Based on Sketches.- An Artificial Neural Network Based on the Architecture of the Cerebellum for Behavior Learning.
• (source: Nielsen Book Data)

This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and ss-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, individual role adaptation for team sports, application of polynomial neural networks, recursive neuro-fuzzy algorithm for water management, application of interactive genetic algorithm, and Artificial Neural Network (ANN) model. This edition is published in original, peer reviewed contributions covering from initial design to final prototypes and verification.
(source: Nielsen Book Data)