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使用雲端運算機制開發模糊搜尋引擎
http://ir.ncue.edu.tw/ir/handle/987654321/11908
title: 使用雲端運算機制開發模糊搜尋引擎First Report of Knowledge Discovery in Predicting Protein Folding Rate Change upon Single Mutation
http://ir.ncue.edu.tw/ir/handle/987654321/11907
title: First Report of Knowledge Discovery in Predicting Protein Folding Rate Change upon Single Mutation abstract: To explore the mechanism of protein folding is one of the important topics in protein research. The accurate prediction of protein folding rate change is helpful and useful in protein design. In earlier study, we have firstly analyzed the prediction of folding rate change upon single point mutation and constructed a non-redundant dataset of F467. F467 consists of 467 mutants with various features and widely distributed on secondary structure, solvent accessibility, conservation score and long-range contacts. In this work, we therefore focused on effectively developing the knowledge in F467 dataset. We have systematically analyzed the dataset and presented several representative data mining techniques, including decision tree, decision table and association rule algorithms. Furthermore, we have interpreted, evaluated, and compared the knowledge obtained from different techniques. The experimental results showed that the present approach can effectively develop the knowledge in the dataset and the outcomes can increase the understanding of predicting protein folding rate change upon single mutation. We have also created a website with related information about this work and it is freely available at http://bioinformatics.myweb.hinet.net/kdfreedom.htm.
<br>The Performance Impact of Different Master Nodes on Parallel Loop Self-Scheduling Schemes for Rule-based Expert Systems
http://ir.ncue.edu.tw/ir/handle/987654321/11906
title: The Performance Impact of Different Master Nodes on Parallel Loop Self-Scheduling Schemes for Rule-based Expert Systems abstract: The technique of parallel loop self-scheduling has been successfully applied to auto-parallelize rule-based expert systems previously. In a
heterogeneous system, different compute nodes have different computer powers. Therefore, we have to choose a node to run the master process before running an application. In this paper, we focus on how different master nodes influence the performances of different self-scheduling schemes. In addition, we will investigate how the file system influences the performance. Experimental results give users the good guidelines on how to choose the master node, the self-scheduling scheme, and the file system for storing the results.
<br>Developing a Fuzzy Search Engine Based on Fuzzy Ontology and Semantic Search
http://ir.ncue.edu.tw/ir/handle/987654321/11905
title: Developing a Fuzzy Search Engine Based on Fuzzy Ontology and Semantic Search abstract: Most of existing search engines retrieve web pages by means of finding exact keywords. Traditional keyword-based search engines suffer several problems. First, synonyms and terms similar to keywords are not taken into consideration to search web pages. Users may need to input several similar keywords individually to complete a search. Second, traditional search engines treat all keywords as the same importance and cannot differentiate the importance of one keyword from that of another. Third, traditional search engines lack an applicable classification mechanism to reduce the search space and improve the search results. In this paper, we develop a fuzzy search engine, called Fuzzy-Go. First, a fuzzy ontology is constructed by using fuzzy logic to capture the similarities of terms in the ontology, which offering appropriate semantic distances between
terms to accomplish the semantic search of keywords. The Fuzzy- Go search engine can thus automatically retrieve web pages that contain synonyms or terms similar to keywords. Second, users can input multiple keywords with different degrees of importance based on their needs. The totally satisfactory degree of keywords can be aggregated based on their degrees of importance and degrees of satisfaction. Third, the domain classification of web pages offers users to select the appropriate domain for searching web pages, which excludes web pages in the inappropriate
domains to reduce the search space and to improve the search results.
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