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Computer-based information technologies have been extensively used to help industries manage their processes and information systems hereby - come their nervous center. More specially, databases are designed to s- port the data storage, processing, and retrieval activities related to data management in information systems. Database management systems p- vide efficient task support and database systems are the key to impleme- ing industrial data management. Industrial data management requires da- base technique support. Industrial applications, however, are typically data and knowledge intensive applications and have some unique character- tics that makes their management difficult. Besides, some new techniques such as Web, artificial intelligence, and etc. have been introduced into - dustrial applications. These unique characteristics and usage of new te- nologies have put many potential requirements on industrial data mana- ment, which challenge today’s database systems and promote their evolvement. Viewed from database technology, information modeling in databases can be identified at two levels: (conceptual) data modeling and (logical) database modeling. This results in conceptual (semantic) data model and logical database model. Generally a conceptual data model is designed and then the designed conceptual data model will be transformed into a chosen logical database schema. Database systems based on logical database model are used to build information systems for data mana- ment. Much attention has been directed at conceptual data modeling of - dustrial information systems. Product data models, for example, can be views as a class of semantic data models (i. e.
This book constitutes the thoroughly refereed and revised post-workshop proceedings of two international meetings devoted to deductive databases and logic programming. The technical papers presenting original research results were carefully reviewed and selected for inclusion in the present book, together with several survey articles summarizing the state of the art in the area. Thus, the book is the ultimate reference for anybody interested in the theory and application of deductive databases and logic programming.
Searching for Semantics: Data Mining, Reverse Engineering Stefano Spaccapietra Fred M aryanski Swiss Federal Institute of Technology University of Connecticut Lausanne, Switzerland Storrs, CT, USA REVIEW AND FUTURE DIRECTIONS In the last few years, database semantics research has turned sharply from a highly theoretical domain to one with more focus on practical aspects. The DS- 7 Working Conference held in October 1997 in Leysin, Switzerland, demon strated the more pragmatic orientation of the current generation of leading researchers. The papers presented at the meeting emphasized the two major areas: the discovery of semantics and semantic data modeling. The work in the latter category indicates that although object-oriented database management systems have emerged as commercially viable prod ucts, many fundamental modeling issues require further investigation. Today's object-oriented systems provide the capability to describe complex objects and include techniques for mapping from a relational database to objects. However, we must further explore the expression of information regarding the dimensions of time and space. Semantic models possess the richness to describe systems containing spatial and temporal data. The challenge of in corporating these features in a manner that promotes efficient manipulation by the subject specialist still requires extensive development.
Contains 17 papers written by an international group of academic and industrial specialists in computer science. Some of the topics addressed include the design and implementation of video servers in video-on-demand systems; a framework for the development of globally convergent adaptive learning rate algorithms; a vector-based approach to analysis of file space properties; load balancing for unstructured mesh applications; musical composition based on genetic algorithms and fuzzy transformations of traditional Greek music patterns; and frequency-adaptive join for shared nothing machines. Most papers consist of an abstract, key words, an introduction, discussion, conclusions, suggestions for future research, and references. Several contributions are printed in a rather dark, compacted font that is difficult to read. c. Book News Inc.
This volume details the development of updated dry lab and wet lab based methods for the reconstruction of Gene regulatory networks (GRN). Chapters guide readers through culprit genes, in-silico drug discovery techniques, genome-wide ChIP-X data, high-Throughput Transcriptomic Data Exome Sequencing, Next-Generation Sequencing, Fuorescence Spectroscopy, data analysis in Bioinformatics, Computational Biology, and S-system based modeling of GRN. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Reverse Engineering of Regulatory Networks aims to be a useful and practical guide to new researchers and experts looking to expand their knowledge.
This book contains the refereed proceedings of the 8th International Conference on Database and Expert Systems Applications, DEXA '97, held in Toulouse, France, September 1997. The 62 revised full papers presented in the book, together with three invited contributions, were selected from a total of 159 submissions. The papers are organized in sections on modeling, object-oriented databases, active and temporal aspects, images, integrity constraints, multimedia databases, deductive databases and knowledge-based systems, allocation concepts, data interchange, digital libraries, transaction concepts, learning issues, optimization and performance, query languages, maintenance, federated databases, uncertainty handling and qualitative reasoning, and software engineering and reusable software.
This is the fifth volume in a sub-series based on the joint effort of Nordic and Japanese scientists in the field of information modelling and knowledge bases.
In recent years, the science of managing and analyzing large datasets has emerged as a critical area of research. In the race to answer vital questions and make knowledgeable decisions, impressive amounts of data are now being generated at a rapid pace, increasing the opportunities and challenges associated with the ability to effectively analyze this data.
The annual series Global Conferences on Sustainable Manufacturing (GCSM) sponsored by the International Academy for Production Engineering (CIRP) is committed to excellence in the creation of sustainable products and processes that conserve energy and natural resources, have minimal negative impacts upon the natural environment and society, and adhere to the core principle of sustainability by considering the needs of the present without compromising the ability of future generations to meet their own needs. To promote this noble goal, there is a great need for increased awareness in education and training, including the dissemination of new findings on principles and practices of sustainability applied to manufacturing. The series Global Conferences on Sustainable Manufacturing offers international colleagues the opportunity to network, expand their knowledge, and improve practice globally.
During the last decade, the French-speaking scientific community developed a very strong research activity in the field of Knowledge Discovery and Management (KDM or EGC for “Extraction et Gestion des Connaissances” in French), which is concerned with, among others, Data Mining, Knowledge Discovery, Business Intelligence, Knowledge Engineering and SemanticWeb. The recent and novel research contributions collected in this book are extended and reworked versions of a selection of the best papers that were originally presented in French at the EGC 2009 Conference held in Strasbourg, France on January 2009. The volume is organized in four parts. Part I includes five papers concerned by various aspects of supervised learning or information retrieval. Part II presents five papers concerned with unsupervised learning issues. Part III includes two papers on data streaming and two on security while in Part IV the last four papers are concerned with ontologies and semantic.