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This paper extends XMDR[19] into G-XMDR (Global-Extended Metadata Registry) to ensure the interoperability of data, and to describe multi agent system using G-XMDR. The proposal G-XMDR will be solved the problem of data heterogeneity and inconsistency in sharing and exchanging each local data in virtual pervasive computing environments. Data heterogeneity is generated by different definition or mismatched expression of the same meaning data. Therefore, we define and design G-XMDR based on XMDR(ISO/IEC 11179) specification to interoperate various each local data in pervasive computing. We also describe our synchronizing multi agent system, which uses G-XMDR to solve data heterogeneity for data interoperability through synchronizing data. It provides more efficient agent through reducing errors that happened on synchronizing requests and adding new pervasive computing environments with their own each local data. [ABSTRACT FROM AUTHOR]

The development of ubiquitous systems for maintenance and control of treatment systems to assist individuals in managing their medical treatment plan would provide an improved system for home healthcare. The assistance of agent-based systems to help doctors and further automate medical treatment systems is limited by medical knowledge data mining accuracy and the complexity of each patient's health history and individual. Automation of knowledge base development for each individual patient would allow efficient personalization of each patient's treatment plan and allow integration of the doctor's individual diagnosis and treatment plan. This paper presents an overview of agent based technologies and describes both historical and state-of-the-art applications of agent technologies in the medical field. Current research and development activity is identified and an algorithm to address the knowledge acquisition bottleneck for diagnostic medical knowledge is present. The algorithm can reduce time consuming knowledge acquisition and allow efficient development of individually tailored medical treatment knowledge bases. [ABSTRACT FROM AUTHOR]

This paper presents data grid system based on agent for an efficient interoperability of distributed data. Purpose of the data grid system is an efficient interoperability through sharing and exchanging data among distributed databases. Interoperability of distributed data is a basic condition for cooperation of existing legacy systems. More nodes for cooperation, better for distributed environment. On the other hand, we have to overcome heterogeneous characteristics of data and physical problems of network. Therefore, we use agent system which is independent, autonomous and mobile in distributed platform for solving this problem. As mobile Agent interacts asynchronously, it could lessen network traffic and support workload and distributed processing of services so that it is suitable for data grid system. Also we use XMDR(eXtended Metadata Registry) in ISO/IEC 11179 for sharing and exchanging data and overcome the heterogeneity of data. Therefore we improve availability and transparency of distributed data based on data grid middle- ware using proposed mobile agent and could construct data grid system with low cost. [ABSTRACT FROM AUTHOR]

The features of image data are useful to discrimination of images. In this paper, we propose the high speed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Maps provides a mapping from high dimensional feature vectors onto a two-dimensional space. The mapping preserves the topology of the feature vectors. The map is called topological feature map. A topological feature map preserves the mutual relations in feature spaces of input data. and clusters mutually similar feature vectors in a neighboring nodes. Each node of the topological feature map holds a node vector and similar images that is closest to each node vector. In topological feature map, there are empty nodes in which no image is classified. We experiment on the performance of our algorithm using color feature vectors extracted from images. Keywords: Self-organizing maps, Image databases, Similarity retrieval, Content-based image retrieval. [ABSTRACT FROM AUTHOR]

The feedback control method proposed in this paper predicts the queue length in the switch using the slope of queue length prediction function and queue length changes in time-series. The predicted congestion information is backward to the node. NLMS and neural network are used as the predictive control functions, and they are compared from performance on the queue length prediction. Simulation results show the efficiency of the proposed method compared to the feedback control method without the prediction. Therefore, we conclude that the efficient congestion and stability of the queue length controls are possible using the prediction scheme that can resolve the problems caused from the longer delays of the feedback information. Keywords: multimedia communication, ABR traffic control, information prediction, neural network. [ABSTRACT FROM AUTHOR]