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Foundations of Intelligent Systems: 15th International Symposium ISMIS 2005, Saratoga Springs, NY, USA, May 25-28, 2005, Proceedings (Lecture Notes in Computer Science #3488)

Foundations of Intelligent Systems: 13th International Symposium, ISMIS 2002, Lyon, France, June 27-29, 2002. Proceedings (Lecture Notes in Computer Science #2366)

Foundations of Intelligent Systems: 25th International Symposium, ISMIS 2020, Graz, Austria, September 23–25, 2020, Proceedings (Lecture Notes in Computer Science #12117)

This book constitutes the proceedings of the 25th International Symposium on Foundations of Intelligent Systems, ISMIS 2020, held in Graz, Austria, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 35 full and 8 short papers presented in this volume were carefully reviewed and selected from 79 submissions. Included is also one invited talk. The papers deal with topics such as natural language processing; deep learning and embeddings; digital signal processing; modelling and reasoning; and machine learning applications.

Foundations of Intelligent Systems: 19th International Symposium, ISMIS 2011, Warsaw, Poland, June 28-30, 2011, Proceedings (Lecture Notes in Computer Science #6804)

This book constitutes the refereed proceedings of the 19th International Symposium on Methodologies for Intelligent Systems, ISMIS 2011, held in Warsaw, Poland, in June 2011. The 71 revised papers presented together with 3 invited papers were carefully reviewed and selected from 131 submissions. The papers are organized in topical sections on rough sets - in memoriam Zdzisław Pawlik, challenges in knowledge discovery and data mining - in memoriam Jan Żytkov, social networks, multi-agent systems, theoretical backgrounds of AI, machine learning, data mining, mining in databases and warehouses, text mining, theoretical issues and applications of intelligent web, application of intelligent systems in sound processing, intelligent applications in biology and medicine, fuzzy sets theory and applications, intelligent systems, tools and applications, and contest on music information retrieval.

Foundations of Intelligent Systems: 23rd International Symposium, ISMIS 2017, Warsaw, Poland, June 26-29, 2017, Proceedings (Lecture Notes in Computer Science #10352)

This book constitutes the proceedings of the 23rd International Symposium on Foundations of Intelligent Systems, ISMIS 2017, held in Warsaw, Poland, in June 2017. The 56 regular and 15 short papers presented in this volume were carefully reviewed and selected from 118 submissions. The papers include both theoretical and practical aspects of machine learning, data mining methods, deep learning, bioinformatics and health informatics, intelligent information systems, knowledge-based systems, mining temporal, spatial and spatio-temporal data, text and Web mining. In addition, four special sessions were organized; namely, Special Session on Big Data Analytics and Stream Data Mining, Special Session on Granular and Soft Clustering for Data Science, Special Session on Knowledge Discovery with Formal Concept Analysis and Related Formalisms, and Special Session devoted to ISMIS 2017 Data Mining Competition on Trading Based on Recommendations, which was launched as a part of the conference.

Foundations of Intelligent Systems: 12th International Symposium, ISMIS 2000, Charlotte, NC, USA October 11-14, 2000 Proceedings (Lecture Notes in Computer Science #1932)

Foundations of Intelligent Systems: 18th International Symposium, ISMIS 2009, Prague, Czech Republic, September 14-17, 2009, Proceedings (Lecture Notes in Computer Science #5722)

This book constitutes the refereed proceedings of the 18th International Symposium on Methodologies for Intelligent Systems, ISMIS 2009, held in Prague, Czech Republic, in September 2009. The 60 revised papers presented together with 4 plenary talks were carefully reviewed and selected from over 111 submissions. The papers are organized in topical sections on knowledge discovery and data mining, applications and intelligent systems in Medicine, logical and theoretical aspects of intelligent systems, text mining, applications of intelligent sysems in music, information processing, agents, machine learning, applications of intelligent systems, complex data, general AI as well as uncertainty.

Foundations of Intelligent Systems: Proceedings of the Sixth International Conference on Intelligent Systems and Knowledge Engineering, Shanghai, China, Dec 2011 (ISKE 2011) (Advances in Intelligent and Soft Computing #122)

Proceedings of the Sixth International Conference on Intelligent System and Knowledge Engineering presents selected papers from the conference ISKE 2011, held December 15-17 in Shanghai, China. This proceedings doesn’t only examine original research and approaches in the broad areas of intelligent systems and knowledge engineering, but also present new methodologies and practices in intelligent computing paradigms. The book introduces the current scientific and technical advances in the fields of artificial intelligence, machine learning, pattern recognition, data mining, information retrieval, knowledge-based systems, knowledge representation and reasoning, multi-agent systems, natural-language processing, etc. Furthermore, new computing methodologies are presented, including cloud computing, service computing and pervasive computing with traditional intelligent methods. The proceedings will be beneficial for both researchers and practitioners who want to utilize intelligent methods in their specific research fields. Dr. Yinglin Wang is a professor at the Department of Computer Science and Engineering, Shanghai Jiao Tong University, China; Dr. Tianrui Li is a professor at the School of Information Science and Technology, Southwest Jiaotong University, China.

Foundations of Intelligent Systems: Proceedings of the Eighth International Conference on Intelligent Systems and Knowledge Engineering, Shenzhen, China, Nov 2013 (ISKE 2013) (Advances in Intelligent Systems and Computing #277)

"Foundations of Intelligent Systems" presents selected papers from the 2013 International Conference on Intelligent Systems and Knowledge Engineering (ISKE2013). The aim of this conference is to bring together experts from different expertise areas to discuss the state-of-the-art in Intelligent Systems and Knowledge Engineering, and to present new research results and perspectives on future development. The topics in this volume include, but not limited to: Artificial Intelligence Theories, Pattern Recognition, Intelligent System Models, Speech Recognition, Computer Vision, Multi-Agent Systems, Machine Learning, Soft Computing and Fuzzy Systems, Biological Inspired Computation, Game Theory, Cognitive Systems and Information Processing, Computational Intelligence, etc. The proceedings are benefit for both researchers and practitioners who want to utilize intelligent methods in their specific research fields. Dr. Zhenkun Wen is a Professor at the College of Computer and Software Engineering, Shenzhen University, China. Dr. Tianrui Li is a Professor at the School of Information Science and Technology, Southwest Jiaotong University, Xi’an, China.

Foundations of Intelligent Systems: 14th International Symposium, ISMIS 2003, Maebashi City, Japan, October 28-31, 2003, Proceedings (Lecture Notes in Computer Science #2871)

This volume contains the papers selected for presentation at the 14th International Symposium on Methodologies for Intelligent Systems, ISMIS 2003, held in Maebashi City, Japan, 28–31 October, 2003. The symposium was organized by the Maebashi Institute of Technology in co-operation with the Japanese Society for Artificial Intelligence. It was sponsored by the Maebashi Institute of Technology, Maebashi Convention Bureau, Maebashi City Government, Gunma Prefecture Government, US AFOSR/AOARD, the Web Intelligence Consortium (Japan), Gunma Information Service Industry Association, and Ryomo Systems Co., Ltd. ISMIS is a conference series that was started in 1986 in Knoxville, Tennessee. Since then it has been held in Charlotte (North Carolina), Knoxville (Tennessee), Turin (Italy), Trondheim (Norway), Warsaw (Poland), Zakopane (Poland), and Lyon (France). The program committee selected the following major areas for ISMIS 2003: active media human-computer interaction, autonomic and evolutionary computation, intelligent agent technology, intelligent information retrieval, intelligent information systems, knowledge representation and integration, knowledge discovery and data mining, logic for artificial intelligence, soft computing, and Web intelligence.

Foundations of Java for ABAP Programmers

First and only book on the Java 5, including new Java EE 5, for SAP/ABAB programmers The author has given the first course of its kind in Belgium, and employs his experience and approach in this book More Java development or exposure to Java needed by SAP/ABAP programmers and developers as evidenced by NetWeaver, for example

Foundations of Joomla!

Foundations of Joomla is a step by step practical guide that explains building web sites and blogs using Joomla - a very popular and powerful content management system (CMS). The book takes you through the steps of installing Joomla, configuring your database, creating a blog and a website, followed by instructions on creating new posts and adding content to your site. Even if you are an absolute beginner and don't have any programming experience, you can build responsive, powerful, and fully featured websites quickly. Following clear and easy to understand instructions, you'll master Joomla 3 by building a sample site throughout the book.

Foundations of JSP Design Patterns

* Andrew Patzer was the principal author of the best selling Professional Java Server Programming—among the first to cover J2EE technologies; JSP design patterns books should sell as well as the sister version: J2EE design patterns books. * Includes best practices, enterprise design patterns, and architectural constructs to provide unit testing, load testing and automated deployment procedures. * Covers new features of the JSP 2.0 specification including the standard filtering mechanism.

Foundations of Knowledge Acquisition: Machine Learning (The Springer International Series in Engineering and Computer Science #195)

One of the most intriguing questions about the new computer technology that has appeared over the past few decades is whether we humans will ever be able to make computers learn. As is painfully obvious to even the most casual computer user, most current computers do not. Yet if we could devise learning techniques that enable computers to routinely improve their performance through experience, the impact would be enormous. The result would be an explosion of new computer applications that would suddenly become economically feasible (e. g. , personalized computer assistants that automatically tune themselves to the needs of individual users), and a dramatic improvement in the quality of current computer applications (e. g. , imagine an airline scheduling program that improves its scheduling method based on analyzing past delays). And while the potential economic impact of successful learning methods is sufficient reason to invest in research into machine learning, there is a second significant reason: studying machine learning helps us understand our own human learning abilities and disabilities, leading to the possibility of improved methods in education. While many open questions remain about the methods by which machines and humans might learn, significant progress has been made.

Foundations of Knowledge Acquisition: Cognitive Models of Complex Learning (The Springer International Series in Engineering and Computer Science #194)

One of the most intriguing questions about the new computer technology that has appeared over the past few decades is whether we humans will ever be able to make computers learn. As is painfully obvious to even the most casual computer user, most current computers do not. Yet if we could devise learning techniques that enable computers to routinely improve their performance through experience, the impact would be enormous. The result would be an explosion of new computer applications that would suddenly become economically feasible (e. g. , personalized computer assistants that automatically tune themselves to the needs of individual users), and a dramatic improvement in the quality of current computer applications (e. g. , imagine an airline scheduling program that improves its scheduling method based on analyzing past delays). And while the potential economic impact ofsuccessful learning methods is sufficient reason to invest in research into machine learning, there is a second significant reason: studying machine learning helps us understand our own human learning abilities and disabilities, leading to the possibility of improved methods in education. While many open questions remain aboutthe methods by which machines and humans might learn, significant progress has been made.

Foundations of Knowledge Base Management: Contributions from Logic, Databases, and Artificial Intelligence Applications (Topics in Information Systems)

In the past, applied artificial intelligence systems were built with particular emphasis on general reasoning methods intended to function efficiently, even when only relatively little domain-specific knowledge was available. In other words, AI technology aimed at the processing of knowledge stored under comparatively general representation schemes. Nowadays, the focus has been redirected to the role played by specific and detailed knowledge, rather than to the reasoning methods themselves. Many new application systems are centered around knowledge bases, i. e. , they are based on large collections offacts, rules, and heuristics that cap­ ture knowledge about a specific domain of applications. Experience has shown that when used in combination with rich knowledge bases, even simple reasoning methods can be extremely effective in a wide variety of problem domains. Knowledge base construction and management will thus become the key factor in the development of viable knowledge-based ap­ plications. Knowledge Base Management Systems (KBMSs) are being proposed that provide user-friendly environments for the construction, retrieval, and manipUlation of large shared knowledge bases. In addition to deductive reasoning, KBMSs require operational characteristics such as concurrent access, integrity maintenance, error recovery, security, and perhaps distribution. For the development ofKBMSs, the need to integrate concepts and technologies from different areas, such as Artificial Intel­ ligence, Databases, and Logic, has been widely recognized. One of the central issues for KBMSs is the framework used for knowledge representation-semantic networks, frames, rules, and logics are proposed by the AI and logic communities.

Foundations of Knowledge Systems: with Applications to Databases and Agents (Advances in Database Systems #13)

One of the main uses of computer systems is the management of large amounts of symbolic information representing the state of some application domain, such as information about all the people I communicate with in my personal address database, or relevant parts of the outer space in the knowledge base of a NASA space mission. While database management systems offer only the basic services of information storage and retrieval, more powerful knowledge systems offer, in addition, a number of advanced services such as deductive and abductive reasoning for the purpose of finding explanations and diagnoses, or generating plans. In order to design and understand database and knowledge-based applications it is important to build upon well-established conceptual and mathematical foundations. What are the principles behind database and knowledge systems? What are their major components? Which are the important cases of knowledge systems? What are their limitations? Addressing these questions, and discussing the fundamental issues of information update, knowledge assimilation, integrity maintenance, and inference-based query answering, is the purpose of this book. Foundations of Databases and Knowledge Systems covers both basic and advanced topics. It may be used as the textbook of a course offering a broad introduction to databases and knowledge bases, or it may be used as an additional textbook in a course on databases or Artificial Intelligence. Professionals and researchers interested in learning about new developments will benefit from the encyclopedic character of the book, which provides organized access to many advanced concepts in the theory of databases and knowledge bases.

Foundations of Large-Scale Multimedia Information Management and Retrieval: Mathematics of Perception

"Foundations of Large-Scale Multimedia Information Management and Retrieval: Mathematics of Perception" covers knowledge representation and semantic analysis of multimedia data and scalability in signal extraction, data mining, and indexing. The book is divided into two parts: Part I - Knowledge Representation and Semantic Analysis focuses on the key components of mathematics of perception as it applies to data management and retrieval. These include feature selection/reduction, knowledge representation, semantic analysis, distance function formulation for measuring similarity, and multimodal fusion. Part II - Scalability Issues presents indexing and distributed methods for scaling up these components for high-dimensional data and Web-scale datasets. The book presents some real-world applications and remarks on future research and development directions. The book is designed for researchers, graduate students, and practitioners in the fields of Computer Vision, Machine Learning, Large-scale Data Mining, Database, and Multimedia Information Retrieval.Dr. Edward Y. Chang was a professor at the Department of Electrical & Computer Engineering, University of California at Santa Barbara, before he joined Google as a research director in 2006. Dr. Chang received his M.S. degree in Computer Science and Ph.D degree in Electrical Engineering, both from Stanford University.

Foundations of Libvirt Development: How to Set Up and Maintain a Virtual Machine Environment with Python

Discover the essential concepts of libvirt development and see how to interface to Linux virtualization environments, such as QEMU/KVM, XEN, Virtuozzo, VMWare ESX, LXC, Bhyve, and more. This book will prepare you to set up and maintain a virtual machine environment.You'll start by reviewing virtualization in general and then move on to libvirt-specific concepts using Python, including virtualized operating systems and networks, connections, storage pools, and event and error handling. This work concludes with a comprehensive look at the XML schema definitions for domains, networks, devices, network filtering, storage, node devices, and more.The libvirt API covers the entire life cycle of virtual objects, from creation to destruction. It contains everything needed for the management of a virtual object during that life cycle. While libvirt has APIs that support many languages, Foundations of Libvirt Development concentrates on Python exclusively, and how to use the APIs to control virtual machines under the QEMU/KVM system. and more. What You'll LearnInterface Python to the libvirt library.Review the class layout and methods of the libvirt library.Install and manipulate virtual machines via Python/libvirt.Create XML to manipulate domains, networks, and devices.Write Python programs to perform libvirt functions without human intervention.Who This Book Is For​Maintainers of virtual machines in a UNIX/Linux environment ranging from managing code on a single virtual machine through an entire installation of virtual machines.

Foundations of Linux Debugging, Disassembling, and Reversing: Analyze Binary Code, Understand Stack Memory Usage, and Reconstruct C/C++ Code with Intel x64

Review topics ranging from Intel x64 assembly language instructions and writing programs in assembly language, to pointers, live debugging, and static binary analysis of compiled C and C++ code. This book is ideal for Linux desktop and cloud developers. Using the latest version of Debian, you’ll focus on the foundations of the diagnostics of core memory dumps, live and postmortem debugging of Linux applications, services, and systems, memory forensics, malware, and vulnerability analysis. This requires an understanding of x64 Intel assembly language and how C and C++ compilers generate code, including memory layout and pointers. This book provides the back­ground knowledge and practical foundations you’ll need in order to master internal Linux program structure and behavior. It consists of practical step-by-step exercises of increasing complexity with explanations and ample diagrams. You’ll also work with the GDB debugger and use it for disassembly and reversing. By the end of the book, you will have a solid understanding of how Linux C and C++ compilers generate binary code. In addition, you will be able to analyze such code confidently, understand stack memory usage, and reconstruct original C/C++ code. Foundations of Linux Debugging, Disassembling, and Reversing is the perfect companion to Foundations of ARM64 Linux Debugging, Disassembling, and Reversing for readers interested in the cloud or cybersecurity.What You'll LearnReview the basics of x64 assembly languageExamine the essential GDB debugger commands for debugging and binary analysis Study C and C++ compiler code generation with and without compiler optimizations Look at binary code disassembly and reversing patternsSee how pointers in C and C++ are implemented and usedWho This Book Is ForSoftware support and escalation engineers, cloud security engineers, site reliability engineers, DevSecOps, platform engineers, software testers, Linux C/C++ software engineers and security researchers without Intel x64 assembly language background, beginners learning Linux software reverse engineering techniques, and engineers coming from non-Linux environments.

Foundations of Logic and Mathematics: Applications to Computer Science and Cryptography

This modern introduction to the foundations of logic and mathematics not only takes theory into account, but also treats in some detail applications that have a substantial impact on everyday life (loans and mortgages, bar codes, public-key cryptography). A first college-level introduction to logic, proofs, sets, number theory, and graph theory, and an excellent self-study reference and resource for instructors.

Foundations of Logic Programming (Symbolic Computation)

This book gives an account oC the mathematical Coundations oC logic programming. I have attempted to make the book selC-contained by including prooCs of almost all the results needed. The only prerequisites are some Camiliarity with a logic programming language, such as PROLOG, and a certain mathematical maturity. For example, the reader should be Camiliar with induction arguments and be comCortable manipulating logical expressions. Also the last chapter assumes some acquaintance with the elementary aspects of metric spaces, especially properties oC continuous mappings and compact spaces. Chapter 1 presents the declarative aspects of logic programming. This chapter contains the basic material Crom first order logic and fixpoint theory which will be required. The main concepts discussed here are those oC a logic program, model, correct answer substitution and fixpoint. Also the unification algorithm is discussed in some detail. Chapter 2 is concerned with the procedural semantics oC logic programs. The declarative concepts are implemented by means oC a specialized Corm oC resolution, called SLD-resolution. The main results of this chapter concern the soundness and completeness oC SLD-resolution and the independence oC the computation rule. We also discuss the implications of omitting the occur check from PROLOG implementations. Chapter 3 discusses negation. Current PROLOG systems implement a form of negation by means of the negation as failure rule. The main results of this chapter are the soundness and completeness oC the negation as failure rule.

Foundations of Logic Programming (Symbolic Computation)

In the two and a half years since the frrst edition of this book was published, the field of logic programming has grown rapidly. Consequently, it seemed advisable to try to expand the subject matter covered in the first edition. The new material in the second edition has a strong database flavour, which reflects my own research interests over the last three years. However, despite the fact that the second edition has about 70% more material than the first edition, many worthwhile topic!! are still missing. I can only plead that the field is now too big to expect one author to cover everything. In the second edition, I discuss a larger class of programs than that discussed in the first edition. Related to this, I have also taken the opportunity to try to improve some of the earlier terminology. Firstly, I introduce "program statements", which are formulas of the form A+-W, where the head A is an atom and the body W is an arbitrary formula. A "program" is a finite set of program statements. There are various restrictions of this class. "Normal" programs are ones where the body of each program statement is a conjunction of literals. (The terminology "general", used in the first edition, is obviously now inappropriate).

Foundations of Mathematical Modelling for Engineering Problem Solving (Studies in Autonomic, Data-driven and Industrial Computing)

This book aims at improving the mathematical modelling skills of users by enhancing the ability to understand, connect, apply and use the mathematical concepts to the problem at hand. This book provides the readers with an in-depth knowledge of the various categories/classes of research problems that professionals, researchers and students might encounter following which the applications of appropriate mathematical models is explained with the help of case studies. The book is targeted at academicians, researchers, students and professionals who belong to all engineering disciplines.

Foundations of Microprogramming: Architecture, Software, and Applications

Foundations of Microprogramming: Architecture, Software, and Applications discusses the foundations and trends in microprogramming, focusing on the architectural, software, and application aspects of microprogramming. The book reviews microprocessors, microprogramming concepts, and characteristics, as well as the architectural features in microprogrammed computers. The text explains support software and the different hierarchies or levels of languages. These include assembler languages which are mnemonic or symbolic representation of machine commands; the procedure oriented machine-dependent; and the procedure oriented machine independent. A simulator is used to interpret programs written in machine or micro-language before the instructions in the program can be run. A simulator and translator (which change some steps from one program written in another language to another program) should interface with the design language of the computer for these components to operate even when a new machine is developed. The book cites four existing computers which have "simple" diagonal microinstructions such as the Hewlett-Packard HP21MX and the Microdata 3200. Horizontal types of microinstructions allow parallel execution of many micro-operations, such as the Cal Data family of computers, the Varian 73, and the NANODATA QM-1. Microprogramming is applied in emulation, program enhancement, operating systems, signal processing, and graphics. The text can benefit programmers, computer engineers, computer technicians, and computer instructors dealing with many aspects of computers such as programming, hardware interface, networking, engineering or design.