• 지식경영연구
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• 제12권2호
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• pp.81-90
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• 2011

This paper aims at the application of knowledge management in teaching Korean traditional dance (KTD) for elderly people. KTD has been taught using the traditional method of individual verbal instructions. Applying the traditional method in teaching a group of elderly people has limitations for both instructors and for the elderly people. Because there is no uniform method in teaching KTD, each instructor has to create his or her own teaching plan. Also, due to diminishing memory among the elderly people, it is difficult for them to recall what they were verbally instructed. To overcome these limitations in teaching KTD, we propose the application of knowledge management (KM) process. The KM process will allow collecting, storing, sharing, and optimizing the tacit knowledge of KTD. The findings and implications in this study would provide insights not only for the KTD instructors but for the silver industry as well.

• 한국건설관리학회:학술대회논문집
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• 한국건설관리학회 2002년도 학술대회지
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• pp.515-518
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• 2002

지식경영이 기업의 생존에 있어 없어서는 안되는 패러다임으로 여겨지면서, 기업은 지식관리시스템 혹은 기타 시스템을 이용하여 무형지식을 관리하려는 노력하고 있다. 그래서, 각 기업은 자사에 맞는 지식관리시스템을 개발하고 자산에 맞는 지식분류체계를 작성하고 활용하고 있다. 건설산업 또한 예외는 아니다 대기업을 중심으로 이루어지고 있지만, 현 건설업체에서 가지고 있는 지식분류체계는 타 산업(제조업, 금융 등)과의 차별성을 느낄 수 없는 전 산업적인 지식 분류체계를 가지고 있다. 그래서, 건설업이 가지고 암묵지를 형식지화 하는데 더욱 어려움이 있는 것이다. 또한, 지식 분류체계를 작성하고 있더라도 이런 지식을 평가하기 위한 활용방안 및 정량적 기준이 미흡하다. 본 연구는 건설업체에서 실시하고 있는 KMS을 벤치마킹하여 문제점을 찾고, 문헌조사를 통하여 건설 지식분류체계를 통하여 공기, 스킬, 비용 등의 관점으로 지식을 평가할 수 있는 모델 제시하고자 한다.

• 대한전기학회논문지
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• 제39권7호
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• pp.720-728
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• 1990

A learning control method is proposed in this paper, using a knowledge base which contains control rules, data, and patterns of the past experience of a plant. The knowledge for plant control is retrieved from measurement data during operation and continually modified after control performance evaluation. A control method is proposed using tinually modified after control performance evaluation. A control method is proposed using fuzzy model of the plant and a recursive statistic decision method of fuzzy subset for control rule generation. Also, the resulting knowledge-based control algorithm has been applied to aprocess and its performance improvement and proper generation of appropriate control rules have been verified.

• 산경연구논집
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• 제8권6호
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• pp.61-73
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• 2017

Purpose - Aviation control, navigation, and aircraft control in the air transportation area are very specialized. Each part is in progress for safety, efficiency, automation, and further. On the other hand co-work among each part including knowledge sharing has been inattentive for many reasons. The purpose of this research is to show how practicians and professionals in the air transportation area perceive the issue of knowledge sharing and to recall the necessity of knowledge sharing in the area. And we try to find ways to activate the knowledge sharing in the area. Research design, data, methodology - For the research, we inquired into whether practicians and professionals think knowledge sharing can effect safe aviation positively or not and what steps are necessary to activate knowledge sharing in the area. We adopted survey method using questionnaires for current practicians and interview for specialists. The survey and interview results were analyzed using regression analysis and AHP method. The interview for specialists and analyzing the results using AHP was to investigate what are the precedence factors to activate the knowledge sharing. Results - First, practicians perceive that knowledge sharing will affect aviation safe positively. Second objective knowledges such as, tower air traffic control procedure of aviation control area, flight principle and structure of aircraft control area, instrument landing system of navigation area, for knowledge sharing of each area were identified. Also the precedence factors such as, knowledge absorbability of personal factor, personal expectation of result of expectation factor, leadership of management of Structure factor, method of knowledge spread of application factor for knowledge sharing were found. Conclusions - Knowledge sharing for practicians and professionals in the aviation area is very important especially from the perspective of safety. However, for various many reasons including the environment of each special area that focusing on their own area, knowledge sharing has not been emphasized. We found that practicians in the area feel that knowledge sharing is necessary and helpful. For it, each practician's active participation is the most important and many ways such as chatting room to share knowledge are to be developed. And the organization culture should be changed to encourage knowledge sharing.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.343-346
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• 1998

This paper deals with the decision in vague knowledge, One method is a classic theory. That is to say, constraints and goals in the vague knowledge. Another method is the fuzzy catastrophe. If there exist two fuzzy variables, there may be a discontinuity which plays an important role in decision.

• 한국과학교육학회지
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• 제27권4호
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• pp.346-353
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• 2007

본 연구에서는 그동안의 평가결과로부터 얻을 수 없었던 집단별, 개인별 정보를 끄집어 낼 수 있는 평가도구를 소개하고 있다. 본 연구의 목적은 우리 나라 중고등학생들에게 적용 가능하며, 학생들의 평가결과를 이용하여 학습준비도 및 학습진전도를 파악할 수 있는 지식상태분석법의 활용성을 분석하는 것이다. 이를 위해 마찰전기 평가 문항을 개발하고 개발된 평가문항에 대하여 지식공간론을 적용하여 중학교 2학년 학생들의 평가결과를 분석하였다. 학습전 학생들의 지식상태는 문항간 위계 관계가 형성되지 않았고, 예상위계도에 비해 학생들의 마찰전기에 대한 지식상태가 비구조화 되어 있는 것으로 나타났다. 학습 후에는 학습 전보다는 좀 더 세분화되고 구조화된 위계 관계로 지식상태가 변화했음을 볼 수 있었다. 학습후에 얻어진 학생들의 위계도를 이용하여 학습전 학습자 집단 혹은 학습자 개인의 지식상태를 분석할 수 있었고, 학습전 학생들의 지식상태와 학습후의 지식상태를 비교하여 학생들이 학습한 과학개념의 구조를 가시적으로 파악하는 것이 가능하였으며, 학습자 개개인에 대한 학습전후 진단도 가능한 것으로 나타났다. 따라서 지식상태분석법을 학습 진단평가도구로 활용할 수 있다고 볼 수 있다.

• 한국정보시스템학회지:정보시스템연구
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• 제15권2호
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• pp.125-152
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• 2006

The purpose of this study is to explore the process of knowledge creation at the infusion stage in IT adoption. Because of the lack of the prior research on the infusion and the process of individual knowledge creation we employed Grounded Theory Method which is a qualitative method for building a theory inductively. Collecting and analyzing data from 13 knowledge workers including medical doctors, project managers, and bankers, a process model is developed through the serial process of open, axial and selective coding. We conceptualized the knlowledge creation at the infusion stage as a social process where knowledge is expressed through private and public justifications. This study also found that organizational politics, top management supports, and organization strategy are important factors facilitating the knowledge creation process.

• 한국CDE학회논문집
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• 제12권3호
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• pp.153-162
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• 2007

In this paper, we propose a knowledge-based method for generating CNC torch path for laser cutting of the outlines of planar shapes. The proposed method consists of two main phases: laser cutting knowledge construction and CNC torch path generation using the knowledge. In the first phase, cutting experiments are conducted on various operating parameters, and then empirical data are stored and analyzed to make up the knowledge of laser cutting. With this knowledge, we can inquire what a kerf width is for specific operating parameters. In the second phase, using the knowledge of laser cutting, CNC torch path is generated for cutting the outlines of the given planar shapes. This phase is basically based on the offset generation of each outline by a sequence of arc splines, where the offset distance is the same as the half of the kerf width determined from the constructed knowledge. The proposed method based on laser cutting knowledge makes full use of arc interpolators in CNC torch path generation. The method can efficiently reduce the number of path segments while keeping the torch path within the desired accuracy.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.447-450
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• 2003

In this research, we propose an automatic knowledge acquisition and composite knowledge expression mechanism based on machine learning and relational database. Most of traditional approaches to develop a knowledge base and inference engine of expert systems were based on IF-THEN rules, AND-OR graph, Semantic networks, and Frame separately. However, there are some limitations such as automatic knowledge acquisition, complicate knowledge expression, expansibility of knowledge base, speed of inference, and hierarchies among rules. To overcome these limitations, many of researchers tried to develop an automatic knowledge acquisition, composite knowledge expression, and fast inference method. As a result, the adaptability of the expert systems was improved rapidly. Nonetheless, they didn't suggest a hybrid and generalized solution to support the entire process of development of expert systems. Our proposed mechanism has five advantages empirically. First, it could extract the specific domain knowledge from incomplete database based on machine learning algorithm. Second, this mechanism could reduce the number of rules efficiently according to the rule extraction mechanism used in machine learning. Third, our proposed mechanism could expand the knowledge base unlimitedly by using relational database. Fourth, the backward inference engine developed in this study, could manipulate the knowledge base stored in relational database rapidly. Therefore, the speed of inference is faster than traditional text -oriented inference mechanism. Fifth, our composite knowledge expression mechanism could reflect the traditional knowledge expression method such as IF-THEN rules, AND-OR graph, and Relationship matrix simultaneously. To validate the inference ability of our system, a real data set was adopted from a clinical diagnosis classifying the dermatology disease.

• 지식경영연구
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• 제21권1호
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• pp.99-116
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• 2020

Text is the most widely used means of exchanging or expressing knowledge and information in the real world. Recently, researches on structuring unstructured text data for text analysis have been actively performed. One of the most representative document embedding method (i.e. doc2Vec) generates a single vector for each document using the whole corpus included in the document. This causes a limitation that the document vector is affected by not only core words but also other miscellaneous words. Additionally, the traditional document embedding algorithms map each document into only one vector. Therefore, it is not easy to represent a complex document with interdisciplinary subjects into a single vector properly by the traditional approach. In this paper, we introduce a multi-vector document embedding method to overcome these limitations of the traditional document embedding methods. After introducing the previous study on multi-vector document embedding, we visually analyze the effects of the multi-vector document embedding method. Firstly, the new method vectorizes the document using only predefined keywords instead of the entire words. Secondly, the new method decomposes various subjects included in the document and generates multiple vectors for each document. The experiments for about three thousands of academic papers revealed that the single vector-based traditional approach cannot properly map complex documents because of interference among subjects in each vector. With the multi-vector based method, we ascertained that the information and knowledge in complex documents can be represented more accurately by eliminating the interference among subjects.