Knowledge Base Grid Research Articles

Knowledge based Grid Using Semantic Web for the University System

The emergence of semantic web will result in an enormous amount of knowledge base resources on the web. The efficient use of knowledge resource totally depends on internet search engines which do not only help organization who are involved in the development of web browsers but also international economy as a whole buy facilitating efficient transition, managing and sending appropriate results to the web browser user. It is observed that data flowing from internet is often vague and therefore there is need to develop technology which has to get relevant and focused information. The Knowledge base grid in semantic web is an important instrument to enhance the application domain of semantic web. using the semantic web technologies for the solution of the problems of the students in the knowledge based grid distributed environment is major challenging task where they can collect coordinate publish and share knowledge to get the the admission in the course according to their ability. they can get knowledge about different universities, colleges and institutions in the distributed environment within these they select different courses according to their ability for decision making for their career and also find jobs available in the different colleges, universities and institutions in the distributed environment.

XML-Based Data Model and Architecture for a Knowledge-Based Grid-Enabled Problem-Solving Environment for High-Throughput Biological Imaging

High-throughput biological imaging uses automated imaging devices to collect a large number of microscopic images for analysis of biological systems and validation of scientific hypotheses. Efficient manipulation of these datasets for knowledge discovery requires high-performance computational resources, efficient storage, and automated tools for extracting and sharing such knowledge among different research sites. Newly emerging grid technologies provide powerful means for exploiting the full potential of these imaging techniques. Efficient utilization of grid resources requires the development of knowledge-based tools and services that combine domain knowledge with analysis algorithms. In this paper, we first investigate how grid infrastructure can facilitate high-throughput biological imaging research, and present an architecture for providing knowledge-based grid services for this field. We identify two levels of knowledge-based services. The first level provides tools for extracting spatiotemporal knowledge from image sets and the second level provides high-level knowledge management and reasoning services. We then present cellular imaging markup language, an extensible markup language-based language for modeling of biological images and representation of spatiotemporal knowledge. This scheme can be used for spatiotemporal event composition, matching, and automated knowledge extraction and representation for large biological imaging datasets. We demonstrate the expressive power of this formalism by means of different examples and extensive experimental results.

Knowledge base grid: A generic grid architecture for semantic web

The emergence of semantic web will result in an enormous amount of knowledge base resources on the web. In this paper, a generic Knowledge Base Grid Architecture (KB-Grid) for building large-scale knowledge systems on the semantic web is presented. KB-Grid suggests a paradigm that emphasizes how to organize, discover, utilize, and manage web knowledge base resources. Four principal components are under development: a semantic browser for retrieving and browsing semantically enriched information, a knowledge server acting as the web container for knowledge, an ontology server for managing web ontologies, and a knowledge base directory server acting as the registry and catalog of KBs. Also a referential model of knowledge service and the mechanisms required for semantic communication within KB-Grid are defined. To verify the design rationale underlying the KB-Grid, an implementation of Traditional Chinese Medicine (TCM) is described.

NETMAT: A knowledge-based grid system analysis tool

A novel current-based direct power control (CB-DPC) strategy for a grid-connected doubly-fed induction generator (DFIG) is proposed. The reported control scheme is applicable to DFIG-based variable-speed wind turbines that operate under unbalanced network voltages. The required DFIG rotor voltage for precise regulation of the stator active and reactive output powers and accurate elimination of their inherent pulsations are directly obtained using a nonlinear integral sliding-mode control (ISMC) scheme. Compared with other control methods, the proposed strategy is simpler since it is not based on the symmetrical components theory, does not need multiple synchronous coordinate transformations, and only requires DFIG voltage and current values as its inputs. Constant switching frequency of the rotor-side converter (RSC) is achieved by means of space vector pulse-width modulation (SVPWM) technique. Uncertainties in the parameters of the generator are included in the design. A compensation strategy is also proposed for tracking error mitigation of the powers that occur due to elimination of the chattering phenomena in the ISMC scheme. Simulation results on a 2MW DFIG under different operating conditions are presented to validate the effectiveness and robustness of the proposed method.

NETMAT: a knowledge-based grid system analysis tool

The increasing expansion of electric power systems renders the power system operator's task increasingly complex. The integration into energy management systems of further analytical algorithms implies that more data has to be analysed by the control engineer. For these reasons and many others, more sophisticated tools are required by power engineers to ease the pressure under which they perform their task. The advent of knowledge-based systems has led to a new approach to the problem. The combination of expert systems and numerical algorithms can be advantageously exploited to assist the power system engineer in operating the system. This paper presents the development of a knowledge-based tool for grid system analysis. The tool, NETMAT (NETwork Modelling AssistanT) , is to be used to analyse the impact of grid system maintenance and modification procedures and of new generating plants on power utilities, and in particular on their ability to generate and sell electricity. NE TMAT consists of a number of numerical applications interfaced to an expert system shell through specific problem domain knowledge bases. Results are presented based on the use of the IEEE-30 busbar network as a test network.