• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2003년도 제2차 연례학술대회 발표논문집
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• pp.66-72
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• 2003

Toxicogenomics is now emerging as one of the most important genomics application because the toxicity test based on gene expression profiles is expected more precise and efficient than current histopathological approach in pre-clinical phase. One of the challenging points in Toxicogenomics is the construction of intelligent database management system which can deal with very heterogeneous and complex data from many different experimental and information sources. Here we present a new Toxicogenomics database developed as a part of 'Toxicogenomics for Efficient Safety Test (TEST) project'. The TEST database is especially focused on the connectivity of heterogeneous data and intelligent query system which enables users to get inspiration from the complex data sets. The database deals with four kinds of information; compound information, histopathological information, gene expression information, and annotation information. Currently, TEST database has Toxicogenomics information fer 12 molecules with 4 efficacy classes; anti cancer, antibiotic, hypotension, and gastric ulcer. Users can easily access all kinds of detailed information about there compounds and simultaneously, users can also check the confidence of retrieved information by browsing the quality of experimental data and toxicity grade of gene generated from our toxicology annotation system. Intelligent query system is designed for multiple comparisons of experimental data because the comparison of experimental data according to histopathological toxicity, compounds, efficacy, and individual variation is crucial to find common genetic characteristics .Our presented system can be a good information source for the study of toxicology mechanism in the genome-wide level and also can be utilized fur the design of toxicity test chip.

• 지식경영연구
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• 제9권1호
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• pp.39-59
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• 2008

This paper is an empirical study to analyze the flow of knowledge in science and technology in order to predict technology innovation. Here, we use the information of scientific papers and patents to look into the characteristics of how knowledge is created in science, technology and industry. Based on the characteristics we find, we are able to understand the relationships between science and technology, and technology and industry. In this paper, we adopt multivariate analysis of variance (MANOVA) using scientific papers in SCI database and US patents filed by Korean inventors in order to analyze the patterns of knowledge flows of science and technology. Finally, we present the direction for future study by using the research results.

• 정보관리학회지
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• 제11권2호
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• pp.89-110
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• 1994

기술정보실 경영층의 지원도 및 환경적 변수가 연구자의 이용만족도와 유용성을 결정하는 정보봉사의 효율성과 상관관계를 분석하였다. 연구 결과로는 소장자료 규모, 체계적 정리, 접근성, 속보성, 데이타베이스 설치 및 정보망 가입, 경영층지원 등으로 결정되는 이용만족도와 유용성이 정보봉사의 효율성을 높이는 데 유효한 것으로 분석되었다.

• 동의생리병리학회지
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• 제24권6호
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• pp.1129-1133
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• 2010

The treatment of Atopic dermatitis and its untapped herbal elements are recognized as possible solutions to incurable diseases stemming from overdosage of chemical drugs. Synthesizing clinical results from the Oriental medicine with scientific results from the field of Molecular biology is in the mainstream. The main goal of this research is, by objectifying the methodology of abstracting information into a compendium, to establish knowledge-based database on natural materials mingling every single related information from both Oriental and Western medicine. The constructed system, ATODERM, is the first database system about the medical herb for the treatment of Atopic Dermatitis which bearing the integrated information on Oriental medicine and Western medicine. The construction of this database renders new ways of treatment and prescriptions for researchers in the field of the Oriental medicine. Using the database that has been intensively accumulated, the possibility of creating the plausible cure for the disease can be anticipated.

• 동의생리병리학회지
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• 제33권6호
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• pp.303-310
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• 2019

In order to search for the causes of having difficulty with the scientification task of the Korean medicine, the definition and conception of science were reviewed first and then formalization of reasoning scheme and a practical method of scientification were proposed. Science in its definition is meant by foundation of method and system for production of scientific knowledge not by knowledge of science itself. The formation of science is composed of complex processes including not only scientific knowledge but also politicosocial output containing activity of scientist society, spreading of social value and intercommunication. The production of scientific knowledge of Korean medicine is begun from logicality of the differential diagnosis and treatment theory through abductive verification of analogical inference by yinyang and 5 phase theory. For the commensurability between the various heterogenic theories within Korean medicine, the scientific activity of collecting, compiling, analyzing, distributing, and discussing the significant knowledge gained through abductive verification in the experiment and clinical process should be formed broadly. Based on these knowledge database, organization of scientist society with Korean medicine, life science, medical engineering, social expansion and generalization of pattern conception, and then social propagation and contribution for national health should be driven forward.

• 약학회지
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• 제42권6호
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• pp.627-633
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• 1998

Impurity profiling analysis of methamphetamine seized in Korea was investigated for the evidential and intelligent purpose. Samples were extracted with ethylacetate which contai ns internal standard of dioctylsebacate under basic condition and extracts were analyzed by GC-FID. Ephedrine, chloroephedrine & 1,2-dimethyl-3-phenylaziridine were identified impurities in illicit methamphetamine by GC-MS. These impurities revealed that most of abused methamphetamine in Korea were synthesized from ephedrine as a starting material. For the classification of samples. firstly, 24 impurity peaks were selected after inspection of every peak in 50 samples as the specific markers of impurities. Secondly, corresponding peak retention time and area ratio to the internal standard were calculated and database was created with values of 24 peaks by in-house program. Finally, cluster analysis was attempted with the resultant profiles using the STAR plot, which was based on the Euclidian distance for evaluating similarity among samples. A total of 76 samples were divided into 8 different groups within 90% statistical similarity and inter-batch samples showed similar impurity patterns by this procedure. In conclusion, the analysis of impurities is a suitable index for estimation the common or different origin of methamphetamine sample.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.627-630
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.

• 대한원격탐사학회지
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• 제22권5호
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• pp.457-462
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• 2006

Sequential Pattern Mining is the mining approach which addresses the problem of discovering the existent maximal frequent sequences in a given databases. In the daily and scientific life, sequential data are available and used everywhere based on their representative forms as text, weather data, satellite data streams, business transactions, telecommunications records, experimental runs, DNA sequences, histories of medical records, etc. Discovering sequential patterns can assist user or scientist on predicting coming activities, interpreting recurring phenomena or extracting similarities. For the sake of that purpose, the core of sequential pattern mining is finding the frequent sequence which is contained frequently in all data sequences. Beside the discovery of frequent itemsets, sequential pattern mining requires the arrangement of those itemsets in sequences and the discovery of which of those are frequent. So before mining sequences, the main task is checking if one sequence is a subsequence of another sequence in the database. In this paper, we implement the subsequence matching method as the preprocessing step for sequential pattern mining. Matched sequences in our implementation are the normalized sequences as the form of number chain. The result which is given by this method is the review of matching information between input mapped sequences.

• Journal of Information Processing Systems
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• 제20권3호
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• pp.317-327
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• 2024

Along with the rapid development of the database technology, as well as the widespread application of the database management systems are more and more large. Now the data mining technology has already been applied in scientific research, financial investment, market marketing, insurance and medical health and so on, and obtains widespread application. We discuss data mining technology and analyze the questions of it. Therefore, the research in a new data mining method has important significance. Some literatures did not consider the differences between attributes, leading to redundancy when constructing concept lattices. The paper proposes a new method of uncertain data mining based on the concept lattice of connotation difference degree (c_diff). The method defines the two rules. The construction of a concept lattice can be accelerated by excluding attributes with poor discriminative power from the process. There is also a new technique of calculating c_diff, which does not scan the full database on each layer, therefore reducing the number of database scans. The experimental outcomes present that the proposed method can save considerable time and improve the accuracy of the data mining compared with U-Apriori algorithm.

• 신재생에너지
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• 제5권3호
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• pp.13-21
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• 2009

National wind atlas of Korea requires effective database management because it has been constructed by 5-year long-term time-series numerical wind simulation. Therefore, database of the national wind map has been developed to increase data structure efficiency using IDL scientific programming language which has outstanding feature in mega-capacity numerical dataset. Visualization module also has been developed under IDL environment and it is anticipated to maximize post processing efficiency and applicability of the national wind map especially in the standing points of researchers and developers.