• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2006년도 추계공동학술대회
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• pp.293-297
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• 2006

Recently most universities are suffering from students leaving their majors. In order to make a countermeasure for reducing major separation rate, many universities are trying to find a proper solution. As a similar endeavor, this paper uses decision tree algorithm which is one of the data mining techniques which conduct grouping or prediction into several sub-groups from interested groups. This technique can analyze a feature of type on students leaving their majors. The dataset consists of 5,115 features through data selection from total data of 13,346 collected from a university in Kangwon-Do during seven years(2000.3.1 $\sim$ 2006.6.30). The main objective of this study is to evaluate performance of algorithms including CHAID, CART and C4.5 for classification of students leaving their majors with ROC Chart, Lift Chart and Gains Chart. Also, this study provides values about accuracy, sensitivity, specificity using classification table. According to the analysis result, CART showed the best performance for classification of students leaving their majors.

• 한국정보통신학회논문지
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• 제13권1호
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• pp.193-198
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• 2009

본 논문에서는 최근에 널리 사용되고 있는 RFID 설계 Tool인 HFSS를 이용하여 UHF RFID 세라믹 안테나를 개발하였다. 개발한 세라믹 안테나는 HFSS를 이용하여 반사손실(Return Loss)과 스미스 차트(Smith Chart)를 통해 특성을 분석하였다. HFSS 설계를 바탕으로 세라믹 안테나를 제작하였고, 네트워크 분석기(Network Analyzer)를 이용하여 임피던스 매칭과 이득을 측정하여 성능을 분석하였다. 그리고 UHF RFID 휴대용 단말기에 세라믹 안테나를 부착하여 일반적으로 널리 사용되는5가지 형태의 RFID 태그(Tag)에 대해서 거리측정을 실시하여 그 성능을 입증하였다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제36권7호
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• pp.571-579
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• 2009

차트 파싱 알고리즘에서 left-corner와 look-ahead 정보를 이용하여 불필요한 중간 구조가 생성되지 않도록 함으로써 파싱 속도를 향상시키는 방법이 제안된 바 있다. left-corner와 look-ahead 정보를 이용할 경우 불필요한 중간 구조가 생성되지 않으므로 파싱 속도가 빨라지겠지만 이러한 정보를 유지 관리하고 참조하는 데 따른 추가 비용이 발생한다. 이러한 추가 비용이 발생함에도 불구하고 대규모 문법을 사용하여 파싱을 할 때에는 파싱 속도가 상당한 많이 향상되었다는 연구 결과가 있었다. 본 논문에서 는 소규모 문법을 사용했을 때 파싱 속도가 어느 정도 향상되는가를 관찰하는 실험을 하였다. 실험 결과 소규모의 문법에서는 파싱 속도 향상 정도가 상대적으로 낮았으며 left-corner 정보는 파싱 속도를 향상 시키는 것이 아니라 오히려 저해한다는 사실을 알 수 있었다.

• 대한안전경영과학회지
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• 제8권5호
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• pp.17-25
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• 2006

Nowadays most colleges are confronting with a serious problem because many students have left their majors at the colleges. In order to make a countermeasure for reducing major separation rate, many universities are trying to find a proper solution. As a similar endeavor, the objective of this paper Is to find a predicting model of students leaving their majors. The sample for this study was chosen from a university in Kangwon-Do during seven years(2000.3.1 $\sim$ 2006. 6.30). In this study, the ratio of training sample versus testing sample among partition data was controlled as 50% : 50% for a validation test of data division. Also, this study provides values about accuracy, sensitivity, specificity about three kinds of algorithms including CHAID, CART and C4.5. In addition, ROC chart and gains chart were used for classification of students leaving their majors. The analysis results were very informative since those enable us to know the most important factors such as semester taking a course, grade on cultural subjects, scholarship, grade on majors, and total completion of courses which can affect students leaving their majors.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2006년도 춘계공동학술대회
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• pp.45-50
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• 2006

The main objective of this study is to provide feature analysis of industrial accidents in manufacturing industries using CHAID algorithm. In this study, data on 10,536 accidents were analyed to create risk groups, Including the risk of disease and accident. The sample for this work chosen from data related to manufacturing industries during three years $(2002\sim2004)$ in Korea. The resulting classification rules have been incorporated into development of a developed database tool to help quantify associated risks and act as an early warning system to individual industrial accident in manufacturing industries.

• 한국의상디자인학회지
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• 제4권3호
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• pp.55-64
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• 2002

The purpose of this study is to review the grading practices and size systems of women's apparel industry in Korea and thereby, analyze the grading problems to find their solutions. Compared with other pattern producing processes, the working principles and methods of grading seem to be consistent, repeatable and stable. Therefore, if the grading deviation setting and working method should be standardized and systematized, it is much easier to automate the grading work than other pattern works. Nevertheless, it was found through this study that grading deviation setting or its application depending on body forms or age groups is not systematic. Moreover, since size identifications, basic sizes or intervals differ among apparel businesses, consumers may be confused in selection of the apparels fitting their body forms. Thus, it is deemed necessary to precisely analyze consumers' body sizes and determine on grading gains or losses in consideration of the body forms.

• 대한안전경영과학회지
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• 제8권2호
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• pp.51-59
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• 2006

So far, there is no technique of quantitative evaluation on danger related to industrial accidents. Therefore, as an endeavor for obtaining technique of quantitative evaluation, this study presents feature analysis of industrial accidents in manufacturing field using QUEST algorithm. In order to analyze feature of industrial accidents, a retrospective analysis was performed in 10,536 subjects (10,313 injured people, 223 deaths). The sample for this work chosen from data related to manufacturing businesses during three years $(2002\sim2004)$ in Korea. The analysis results were very informative since those enable us to know the most important variables such as occurrence type, company size, and occurrence time which can affect injured people. Also, it is found that classification using QUEST algorithm which was performed in this study is very reliable.

• 대한안전경영과학회지
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• 제8권4호
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• pp.1-11
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• 2006

의사결정나무 알고리즘은 데이터마이닝 기법중 하나인데 관심이 되는 데이터들에 대하여 분류 및 예측을 가능하게 해준다. 이 기법은 데이터 형태의 특성을 분석할 수 있고 산업재해 형태의 차이점을 찾아내는데 사용될 수 있다. 본 연구에서는 산업재해 데이터의 특성을 파악하고자 C4.5 알고리즘을 사용하였다. 본 연구에서 분석을 위하여 사용된 데이터는 강원도에서 발생한 2년 동안의 산업재해 관련 데이터로서 연구에 적용된 데이터의 수는 19,909개로 구성되어 있다. 본 연구의 목적을 위하여 한 개의 목표변수와 여덟 개의 독립변수가 산업재해 형태에 따라 세분화 되었다. 분석 후 데이터는 222개의 전체 나뭇가지와 151개의 줄기가지로 분류되었다. 또한 본 연구에서는 재해자들의 위험도 관리와 감소를 위하여 이익도표를 제공하였다.

• Journal of Korean Biological Nursing Science
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• 제9권2호
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• pp.105-117
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• 2007

Purpose: The purpose of this study was two folds: first, to identify the level of self care behavior of the hemodialysis patients and second, to find the correlation between the self care behavior and the physiologic indices. Method: The subjects were 52 hemodialysis patients, male and female, who have regularly received hemodialysis dialysis at the Dialysis Room in a leading teaching hospital, Seoul. The patients responded to the self care behavior questionnaires including their socio-demographic characteristics. The respondents have regularly recorded the self care log book. The physiologic indices, clinical characteristics related to the disease and hemodialysis were collected by the chart review. Result: The mean score of the self care behavior was 3.46. The mean score of the self care behavior on categories demonstrated as follows: medication 4.29, fistula management 4.13, management of physical problem 3.71, diet 3.28, exercise and rest 3.22, blood pressure and body weight management 2.97 and social adjustment 2.05 in order. Thirty patients managed discomfort of their fistula. Eleven patients took exercise for 0.5-1 hr/week. Thirty patients measured their body weight daily and thirty two measured their blood pressure daily. The score of self care behavior was significantly correlated with the mean weight gains between the dialysis sessions(r=-.312, p=.05). The mean weight gains between dialysis sessions was found to be high as the level of serum phosphorus and potassium increased(r=-.316, p=.05, r=-.465, p=.01). Conclusion: The result suggests that nursing intervention to the hemodialysis patients to improve self care behavior should be encouraged and further developed.

• International Journal of Safety
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• 제5권1호
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• pp.37-41
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• 2006

The major objective of the statistical analysis about industrial accidents is to determine the safety factors so that it is possible to prevent or decrease the number of future accidents by educating those who work in a given industrial field in safety management. So far, however, there exists no quantitative method for evaluating danger related to industrial accidents. Therefore, as a method for developing quantitative evaluation technique, this study presents feature analysis of industrial accidents in manufacturing field using QUEST algorithm. In order to analyze features of industrial accidents, a retrospective analysis was performed on 10,536 subjects (10,313 injured people, 223 deaths). The sample for this work was chosen from data related to manufacturing businesses during a three-year period ($2002{\sim}2004$) in Korea. This study used AnswerTree of SPSS and the analysis results enabled us to determine the most important variables that can affect injured people such as the occurrence type, the company size, and the time of occurrence. Also, it was found that the classification system adopted in the present study using QUEST algorithm is quite reliable.