• Journal of Microbiology
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• v.43 no.5
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• pp.406-410
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• 2005

In contrast to Saccharomyces cerevisiae, little is known about the kinesin-like protein (KLP) in Candida albicans. The motor domain of kinesin, or KLP, contains a subregion, which is well conserved from yeast to humans. A similarity search, with the murine ubiquitous kinesin heavy chain region as a query, revealed 6 contigs that contain putative KLPs in the genome of C. albicans. Of these, the length of an open reading (ORF) of 375 amino acids, temporarily designated CaKAR3, was noticeably short compared with the closely related S. cerevisiae KAR3 (ScKAR3) of 729 amino acids. This finding prompted us to isolate a ${\lambda}$ genomic clone containing the complete CaKAR3 ORF, and here the complete sequence of CaKAR3 is reported. CaKAR3 is a C-terminus motor protein, of 687 amino acids, encoded by a non-disrupting gene. When compared with ScKAR3, the amino terminal region of 112 amino acids was unique, with the middle part of the 306 amino acids exhibiting $25\%$ identity and $44\%$ similarity, while the remaining C-terminal motor domain exhibited $64\%$ identity and $78\%$ similarity, and have been submitted to GeneBank under the accession number AY182242.

• Journal of the Korea Society of Computer and Information
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• v.14 no.5
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• pp.19-28
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• 2009

Prediction problem of the time-series data has been a research issue for a long time among many researchers and a number of methods have been proposed in the literatures. In this paper, a method is proposed that similarities among time-series data are examined by use of Hidden Markov Model and Likelihood and future direction of the data movement is determined. Query sequence is modeled by Hidden Markov Modeling and then the model is examined over the pre-recorded time-series to find the subsequence which has the greatest similarity between the model and the extracted subsequence. The similarity is evaluated by likelihood. When the best subsequence is chosen, the next portion of the subsequence is used to predict the next phase of the data movement. A number of experiments with different parameters have been conducted to confirm the validity of the method. We used KOSPI to verify suggested method.

• Journal of Information Science Theory and Practice
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• v.12 no.3
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• pp.49-62
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• 2024

Strategy monitoring is essential for business management and for administrators, including managers and executives, to build a data-driven organization. Having a tool that is able to visualize strategic data is significant for business intelligence. Unfortunately, there are gaps between business users and information technology departments or business intelligence experts that need to be filled to meet user requirements. For example, business users want to be self-reliant when using business intelligence systems, but they are too inexperienced to deal with the technical difficulties of the business intelligence systems. This research aims to create an automatic matching framework between the key performance indicators (KPI) formula and the data in database systems, based on ontology concepts, in the case study of Prince of Songkla University. The mapping data schema with ontology (MapDSOnto) framework is created through knowledge adaptation from the literature review and is evaluated using sample data from the case study. String similarity methods are compared to find the best fit for this framework. The research results reveal that the "fuzz.token_set_ratio" method is suitable for this study, with a 91.50 similarity score. The two main algorithms, database schema mapping and domain schema mapping, present the process of the MapDS-Onto framework using the "fuzz.token_set_ratio" method and database structure ontology to match the correct data of each factor in the KPI formula. The MapDS-Onto framework contributes to increasing self-reliance by reducing the amount of database knowledge that business users need to use semantic business intelligence.

• Journal of Internet Computing and Services
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• v.16 no.4
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• pp.39-50
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• 2015

In information retrieval process through search engine, some users want to retrieve several documents that are corresponding with specific time period situation. For example, if user wants to search a document that contains the situation before 'Japanese invasions of Korea era', he may use the keyword 'Japanese invasions of Korea' by using searching query. Then, search engine gives all of documents about 'Japanese invasions of Korea' disregarding time period in order. It makes user to do an additional work. In addition, a large percentage of cases which is related to historical documents have different time period between generation date of a document and record time of contents. If time period in document contents can be extracted, it may facilitate effective information for retrieval and various applications. Consequently, we pursue a research extracting time period of Joseon era's historical documents by using historic literature for Joseon era in order to deduct the time period corresponding with document content in this paper. We define historical objects based on historic literature that was collected from web and confirm a possibility of extracting time period of web document by machine learning techniques. In addition to the machine learning techniques, we propose and apply the similarity filtering based on the comparison between the historical objects. Finally, we'll evaluate the result of temporal indexing accuracy and improvement.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.177-186
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• 2005

In this Paper. we propose vision-based camera localization technique using 3D information which is created by mapping of DEM and mountain image. Typically, image features for localization have drawbacks, it is variable to camera viewpoint and after time information quantify increases . In this paper, we extract invariance features of geometry which is irrelevant to camera viewpoint and estimate camera extrinsic Parameter through accurate corresponding Points matching by Proposed similarity evaluation function and Graham search method we also propose 3D information creation method by using graphic theory and visual clues, The Proposed method has the three following stages; point features invariance vector extraction, 3D information creation, camera extrinsic Parameter estimation. In the experiments, we compare and analyse the proposed method with existing methods to demonstrate the superiority of the proposed methods.

• International Journal of Industrial Entomology and Biomaterials
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• v.39 no.2
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• pp.67-73
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• 2019

The genomic structure of the Cu/Zn superoxide dismutase (SOD1) gene from the entomopathogenic fungus, Cordyceps pruinosa was characterized. The SOD1 gene of C. pruinosa spans 947 nucleotides and consisted of four exons encoding for 154 amino acids and three introns. Four exons of the SOD1 gene are composed of 13, 331, 97 and 20 nucleotides respectively. Homology search of amino acid sequences of the SOD1 gene of C. pruinosa with another 13 fungi species showed higher sequence similarity of 69% ~ 95% and had the most highest sequence identity of 95% with Beauveria bassiana and Cordyceps militaris, which can easely infect domesticated Bombyx mori and another wild lepidopteran species in artificial or natual manner of infection. This SOD1 gene sequence showed copper, zinc and beta-barrel fold sites. Homology search showed that the Cu/Zn SOD1 gene from the entomopathogenic fungus, C. pruinosa is an orthologous gene homolog present in different species of organism whose ancestor predates the split between the relating species. In addition, C. pruinosa SOD1 gene is placed together within the ascomycetes group of fungal clade. From these results it is concluded that C. pruinosa SOD1 gene is orthologous gene having the same or very similar functions with a common evolutionary ancestor.

• Bulletin of the Korean Chemical Society
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• v.32 no.2
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• pp.645-650
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• 2011

The 3D-QSAR study of 2-arylbenzoxazoles as novel cholesteryl ester transfer protein inhibitors was performed by comparative molecular field analysis (CoMFA), CoMFA region focusing (CoMFA-RF) for optimizing the region for the final PLS analysis, and comparative molecular similarity indices analysis (CoMSIA) methods to determine the factors required for the activity of these compounds. The best orientation was searched by all-orientation search strategy using AOS, to minimize the effect of the initial orientation of the structures. The predictive ability of CoMFARF and CoMSIA were determined using a test set of twelve compounds giving predictive correlation coefficients of 0.886, and 0.754 respectively indicating good predictive power. Further, the robustness and sensitivity to chance correlation of the models were verified by bootstrapping and progressive scrambling analyses respectively. Based upon the information derived from CoMFA(RF) and CoMSIA, identified some key features that may be used to design new inhibitors for cholesteryl ester transfer protein.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.299-303
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• 2000

The goal of the information retrieval system is to search the docments which the user wants to obtain in fast and effiecient way. Many information retrieval models, including boolean models, vector models and fuzzy models based on the trasitional fuzzy set theory, have been proposed to achieve these kinds of objectives. However, the previous models have a limitation on the fact that they do not consider the users' preference in the search of documents. In this paper, we proposed a new extenced fuzzy information retrieval System which can handle the shortcomings of the previous ones. In the proposed model, a new similarity measure was applied in order to calculate the degree among documents, which can expliot the users' preference.

• Herbal Formula Science
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• v.22 no.2
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• pp.45-54
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• 2014

Objectives : The main objective of this study is to classify herbal components to 4 groups which are similar to Gunsinjwasa grades by using herbal composition ratio of prescription. Another objective is to design the searching system which compares prescriptions and improves efficiency with 4 groups like Gunsinjwasa grades. Methods : This study was proceeded with Acess 2007 on Microsoft Windows 7 and we created composition ratio based on weight by using prescriptions of Donguibogam, Uihagipmun and Banghakhabpyun. We could make comparison and searching method of prescriptions. Results : We could search using composition ratio degree of herbs which composes prescription. And the similarity comparison of prescription was possible with value from 0 to 10. Conclusions : We could increase the accuracy of the searching prescriptions and comparison with putting into the information about composition degree and composition ratio of herbs which compose a prescription.

• Journal of Korea Society of Industrial Information Systems
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• v.10 no.2
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• pp.26-31
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• 2005

In this paper, we present the document summarizers which are simpler and more condense than the existing ones generally used in the web search engines. This method is a statistic-based summarization method using the concept of the complete graph. We suppose that each sentence as a vertex and the similarity between two sentences as a link of the graph. We compare this summarizer with those of Clustering and MMR techniques which are well-known as the good summarization methods. For the comparison, we use FScore using the summarization results generated by human subjects. Our experimental results verify the accuracy of this method, being about $30\%$ better than the others.