By converting the expression values of each sample into the corresponding rank values, the rank-based approach enables the direct integration of multiple microarray data produced by different laboratories and/or different techniques. In this study, we verify through statistical and experimental methods that informative genes can be extracted from multiple microarray data integrated by the rank-based approach (briefly, integrated rank-based microarray data). First, after showing that a nonparametric technique can be used effectively as a scoring metric for rank-based microarray data, we prove that the scoring results from integrated rank-based microarray data are statistically significant. Next, through experimental comparisons, we show that the informative genes from integrated rank-based microarray data are statistically more significant than those of single-microarray data. In addition, by comparing the lists of informative genes extracted from experimental data, we show that the rank-based data integration method extracts more significant genes than the z-score-based normalization technique or the rank products technique. Public cancer microarray data were used for our experiments and the marker genes list from the CGAP database was used to compare the extracted genes. The GO database and the GSEA method were also used to analyze the functionalities of the extracted genes.

A huge amount of information is being accumulated on the Internet as the Internet usage spreads and numbers of Web pages increase. However, it is also becoming very difficult to find required information, even when the information exists. The actual value of the Web is thus much lower than its potential value. In order to solve this problem, technologies which allow machines to handle Web content in an efficient, accurate, and flexible way by using machine-readable metadata are being developed. This paper is a survey of knowledge representation on the Web, and the utilization of metadata and ontology for data integration and information sharing, with a focus on the Semantic Web concept.

Motion capture technology is widely used to make a realistic motion in these days. Different motion capture devices use different motion capture data formats. Because of the lack of compatibility of motion capture data animators can't reuse the already captured motion sequence. In addition, it is difficult for integrating, storing and retrieving motion capture data with different formats in the storage. In this paper, we propose a standard format for integrating a different motion capture data formats. In addition, we propose a framework of a system that manages motion capture data using our standard format. Our standard format is called MCML (Motion Capture Markup Language). It is a markup language for motion capture data and is based on XML (extensible Markup Language). Our system designed to manage motion capture data consists of a several components -- Mocap Syntax Analyzer, MCML Converter, MCML Editor, Motion Viewer, MCML Storage Wrapper.

This paper proposes an efficient query evaluation scheme for a mediator system intended to integrate heterogeneous computing environment in terms of operating systems, database management systems, and other software. Most of mediator systems transform a global query into a set of sub-queries based on their target remote servers. Each sub-query is evaluated by the query modification method to evaluate a global query. However, it is possible to reduce the evaluation cost of a global query when the results of frequently requested sub-queries are materialized in a mediator. In a mediator, its integrating schema can be incrementally modified and the evaluation frequency of a global query can also be continuously varied. In order to select the optimized set of materialized sub-queries with respect to their current evaluation frequencies, the proposed method applies a decay factor for modeling the recent access behavior of each sub-query. In other words, the latest access of a sub-query gets the highest attention in the selection process of materialized sub-queries. As a result, it is possible to adjust the optimized set of materialized sub-queries adaptively according to the recent changes in the evaluation frequencies of sub-queries. Since finding the optimum solution of this problem is NP-hard, it takes too long to be used in practice when the number of sub-queries is large. Consequently, given the size of mediator storage, the rank-based selection algorithm proposed in this paper finds the set of materialized sub-queries which minimizes the total evaluation cost of global queries in linear search complexity.

In this paper, an efficient voice/data integrated access algorithm for future personal communication networks (PCNs) is proposed and analyzed based on an equilibrium point analysis (EPA) method. A practical wireless communication channel may be impaired by noise and multipath distortion, and thus corrupted real-time packets have to recompete immediately in order to be transmitted within the stringent delay constraint. Also, real-time traffic users have to transmit their packets irrespective of the amount of non real-time data messages so that heavy non real-time traffic does not degrade the quality of real-time traffic. In the proposed algorithm, request subslots are distributed in the beginning of every slot to reduce access delay of real-time traffic. Moreover, slots are assigned to real-time traffic first and the remaining idle slots are assigned later to non real-time traffic by using the scheme of contention separation. We analyze the throughput and delay characteristics of this system based on an EPA mothod, and validate their performances by simulations. This scheme can support different quality of services (QoSs) imposed by different services efficiently and show good quality of real-time traffic, especially voice packets, no matter how heavy non real-time traffic is.