Earticle

The continuous quality improvement has become a trend in the contemporary medical society, and that can be achieved by the specialty database implement. Decision-support system in the academic and clinical aspects are included in the process such continuous quality improvement. The database has its limitation in the decision-support due to deficiency of on-line analytic function. The data warehouse offers the sophisticated function for decision-support processes. However, the implement of data warehouse may face a lot of obstacles, included expensive cost and large personnel. We had previously established a database of orthopedics, which collected the patients’ data since 2002. The new system was constructed based on this specialty database, the knowledge architectures was build up via specialists committee and accreditation indicators. The major function was to generate sufficient information for decision-support process in the academic and clinical aspects. The execution efficiency of this system is more effective than database. The unique knowledge architecture can form a distinguishing feature of the department. The cost that saved from personnel and time reduced from reports generation for accreditation is remarkable. The stratification of web-based interface application can be assessed through questionnaires; the outcome is satisfactory as what we previously expected. The sophisticate function of the data warehouse is hard to express in a solitary department of the hospital, especially when they had already owned traditional database. The experience of this system construction can be useful as one option for upgrade of specialty database and a step forward to the goal of the continuous quality improvement.

In this paper, we propose a statistical scheme for recognizing three-dimensional textures shown in motion images, e.g., ultrasound imaging, which we call “dynamic textures”. The texture characteristics emerge as the distinct movement in the motion images, and the dynamic cues would be useful especially for recognizing ambiguous texture patterns in noisy images. We apply cubic higher-order auto-correlation (CHLAC) to extract features both of the textures and their movements, and then linear regression to evaluate (recognize) the texture. For the linear regression, we extend ordinary multiple regression analysis so as to reduce within-class fluctuations. In the experiment for estimating quality of beef meat by using ultrasound motion images, the proposed method exhibits the favorable performances which are close to ground truth given by the experts.

A wireless sensor network consists of tiny sensing devices, with limited energy and processing ability. Some time we have to distribute a database on sensor network, because of limited energy in sensors, load balanced distributing database can increase the lifetime of this networks. In this paper we propose Fuzzy based approach for Load balanced distributing database on sensor Network that prolonging the network lifetime. We use vertical partitioning algorithms for distributing database on sensors. First we clustering the network and then distribute partitions on clusters. A simulator was built and Results of various simulation runs are consistent with the hypothesis.

An XML summary should enable cardinality estimations of different kinds on an XML document to flexibly support query optimization for languages such as XPath or XQuery. In contrast to conventional methods which typically emulate the document structure and record path-oriented statistics for it, element-centered XML summarization methods collect statistical information for document nodes and their axes relationships and aggregate them separately for each distinct element/attribute name. It has already partially proven its superiority in quality, space consumption, and evaluation performance. Surprisingly, this kind of inversion seems to have more service capability than conventional approaches. It is not only confined to the cardinality estimation of child and descendant axes, but also allows to approximate parent and ancestor axes, too. Therefore, we refined and extended elementcentered XML summarization methods to capture more statistical information and propose new estimation procedures. We tested our ideas on a set of documents with largely varying characteristics.1

To extract structural features from tree-structured documents among nodes in which characteristic words appear, we described a text-mining algorithm for enumerating all frequent consecutive path patterns (CPP) on a list W of words in Uchida et al., PAKDD 2004 [14]. In this paper, we first extend a CPP to a tree pattern, which is called a tree association pattern (TAP), over a set W of words. A TAP is an ordered rooted tree t such that the root of t has no child or at least two children, all leaves of t are labeled with non-empty subsets of W and all internal nodes, if they exist, are labeled with strings. By modifying text-mining algorithms to find all frequent CPPs, next, we present text-mining algorithms for enumerating all maximal frequent TAPs in tree-structured documents, where a TAP t is maximal if there exists no frequent TAP, which has t as a proper subpattern. Then, we tested our algorithms using Reuters news wires. Finally, as one application of CPPs, we present an algorithm for a wrapper based on CPP using XSLT transformation language and demonstrate simply the use of the wrapper to translate one of the Reuters news wires into other XML document.