• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.331-336
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• 2005

A lot of manufacturing knowledge and method have applied to increase manufacturing efficiency in industry field. DES(Discrete Event Simulation) is one of solution to deal with manufacturing problems in factory. Beginning of research, old maintenance system of KNR ( Korea National Railroad) and its technical problems are basically investigated. KNR has maintained railway vehicle with their own solution based on experience. Very advanced railway vehicles such as KTX (Korea Train Express) and TTX(Tilting Train Express) will be difficult to maintain with their old maintenance method. In order to apply knowledge of DES, maintenance field of railway must be considered. Imaginary maintenance machine are selected to variable of DES. Maintenance capability of each machine will be evaluated base on imaginary data from imaginary machine. The machine could be very expensive as well as difficult to replace. Target of research is minimization of number of machine in railway workshop. So basic knowledge of discrete event simulation is introduced. Then five essential stages of discrete event simulation are provided. Each maintenance case defined as event. Each event is discrete and simulated base on different case such as one maintenance line with one machine and one maintenance line with two machines in railway workshop. simple maintenance method, discrete event simulation, will be come out very powerful in complicate maintenance system and will be helpful to reduce maintenance cost as well as maintenance labor.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.2
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• pp.141-160
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• 2011

This study suggested knowledge base and search engine for the libraries that have the largescaled data. For this purpose, 3 components of knowledge bases(triple ontology, concept-based knowledge base, inverted file) were constructed and 3 search engines(search engine JENA for rule-based reasoning, Concept-based search engine, keyword-based Lucene retrieval engine) were implemented to measure their performance. As a result, concept-based retrieval engine showed the best performance, followed by ontology-based Jena retrieval engine, and then by a normal keyword search engine.

• Journal of the Korean Society of Safety
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• v.16 no.1
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• pp.84-87
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• 2001

Severe accident management can be defined as the use of existing and alternative resources, systems, and actions to prevent or mitigate a core-melt accident in nuclear power plants. TRAIN (Training pRogram for AMP In NPP), developed for training control room staff and the technical group, is introduced in this paper. The TRAIN composes of phenomenological knowledge base (KB), accident sequence KB and accident management procedures with AM strategy control diagrams and information needs. This TRAIN might contribute to training them by obtaining phenomenological knowledge of severe accidents, understanding plant vulnerabilities, and solving problems under high stress.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.54 no.5
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• pp.205-211
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• 2005

Recently, power system is getting larger and more complex. When the complex power system has a problem, it is very difficult even for the experts to find out where the problem is and to make a timely decision by operators. There have been many studies on these problems but the results are not good enough for applying to real power system. Therefore, power system operators always had to judge the exact state of power system and be preparative for the problems that can occur later. We developed new methods that can be applied to complex power system by dividing the system into small modules. By using 'module', we can combine small modules together to make complex power systems and the knowledge base that is applied to fault diagnosis system. As a result, compared to previously developed diagnosis products, operation time is shortened and the knowledge base is become simpler and clearer, which made online usage capable. This system can be used as a complementary measurement that helps the operator from making any mistakes.

• Proceedings of the Technology Innovation Conference
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• 2000.06a
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• pp.47-64
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• 2000

This paper analyses characteristics of the numerical controller industry in market formation and the Flow of information between users and producers and the characteristic of knowledge base of the industry and discusses the difficulties derived, from the characteristics, in accumulation of technological capability In market formation betweenusers and producers, the multi-layered market is not favorable to domestic producers in that lower end market is not large enough to provide cardle market to them which produce inferior quality and lower price than importer products. The credibility of the permance of a product is difficult to prove until a critical mass of products are sold. Therefore gaining market share is deterred by unproven credibility of the performance of the product. The flow of information between users and producers is limited. The flow of information on users environment through mass market to producers is essential for improving credibility of a product. The nature of knowledge base is tacit and the means of knowledge transmission is limited. Technological licensing and reverse engineering, Which have been conventional industry. These characteristics provide conditions of vicious circle in accumulation of technological capability of the numerical controller industry. This paper argues that these characteristics of the industry challenges existing approach to R&D management and framework of science and technology policy.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.760-765
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• 2009

Since the features in object-images such as color and shape cannot clearly express the characteristic of objects, those features lead to vagueness of object-image recognition. Recently there have been studied on object-image recognition based on knowledge base in order to reduce the vagueness. However, because images are represented by numerical information but knowledge bases are represented by conceptual information, combining two kinds of information is difficult. In this paper, we compose knowledge base by using ontology to reduce the gap between the two kinds of information, and propose a method for object-image recognition to reduce the vagueness by using information on inner-object. Moreover, we confirm the usefulness of the proposed method through the experiments on object-image recognition in fruit domain.

• IE interfaces
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• v.18 no.2
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• pp.148-157
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• 2005

The manufacturing industry with Make-to-Order production system is difficult to decide the standard information for the product and the demand is variable to estimate. In this paper, we concerned with the process planning method using data mining in the manufacturing industry with Make-to-Order environment. The subject of our study is the industry transformer plant which is received an diverse order of customer and then produced the product. Currently, process planning method is classified the standard information by hand based on the acquired knowledge through the experience. The standard information stored the various information, such as work sequence, time and so on. This process planning method needs an experts which possesses the field experience for several years. For the product specification which is varied in each order, current process planning method is not efficient due to need many times To solve this problem, we extract the information using data mining process for each processing time, and then construct the knowledge base. We propose a method which is the process planning of the industry transformer product in Make-to-Order environment using the knowledge base.

• Genomics & Informatics
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• v.3 no.3
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• pp.68-73
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• 2005

Pharmacogenomics research requires an intelligent integration of large-scale genomic and clinical data with public and private knowledge resources. We developed a web-based knowledge base for KPRN (Korea Pharmacogenomics Research Network, http://kprn.snubi. org/). Four major types of information is integrated; genetic variation, drug information, disease information, and literature annotation. Eighteen Korean pharmacogenomics research groups in collaboration have submitted 859 genotype data sets for 91 disease-related genes. Integrative analysis and visualization of the large collection of data supported by integrated biomedical path­ways and ontology resources are provided with a user-friendly interface and visualization engine empowered by Generic Genome Browser.

• Journal of Physiology & Pathology in Korean Medicine
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• v.29 no.3
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• pp.246-255
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• 2015

The purpose of this study is to investigate the reliability and validity of the questionnaire of pattern identification (PI) in traditional chinese medicine (TCM), through the systematic review of china national knowledge infrastructure (CNKI) database. We searched the articles related with reliability and validity of the questionnaire of PI and published from January 1994 to December 2013. Seventeen questionnaires were analyzed in this study. The twelve (70.6%) questionnaires were developed on the base of specific disease, and five (29.4%) ones were developed on the base of non-specific disease. Three of PI questionnaires showed low inter-item consistency reliability. Exploratory factor analysis of construct validity, content validity, and criterion validity analysis were commonly used on the assessment of validity, but none of them was analysed at the same study. There was only one questionnaire of the ischemic stroke that examined the sensitivity and specificity of both training and test groups in spite of the absence of a gold standard.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.271-275
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• 2005

In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this Purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between $0\∼1$. Second, RDB and SQL(Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS(Knowledge Management Systems)