• Health Policy and Management
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• v.12 no.1
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• pp.125-143
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• 2002

The objectives of this study were analysis of patient\`s characteristics and market segmentation in oriental medical care and western medical care. This study focused on medical utilization using Anderson's health utilization model. The source of data was 1998 National Health and Nutrition Survey which Korean Institute For Health and Social Affairs carried out. A stratified multistage probability sampling design was used in this survey. The analysis was conducted using the statistical software package SPSS version 10.0 and Answer Tree 2.1 which is one of data mining methodology. The results were as follows ; 1) 44.9% of respondents reported visiting oriental medical center within recent two weeks. 3.4% of them used oriental medical care. The group of age, kind of disease and medical expenditure are associated with the difference western and oriental medical utilization rate. 2) There were several factors related to utilization of oriental medical care according to decision tree. Especially, important factors that patient chose his medical center were kinds of disease, kinds of common medical use, and expenditure. 3) in the results of CART analysis, market of oriental medical care were classified by seven categories. The major groups who have a preference for oriental medicine were those musculo-skeletal, cerebra-vascular disease, or chronic headache patients, and they had a preference fur oriental medical care in common use. These results show that oriental and western medical market were divided into various areas by market segmentation.

• Journal of the Korean Society of Safety
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• v.27 no.5
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• pp.203-210
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• 2012

Traffic accident risk of young drivers(less than 25) is reported to have 8 times as high as that of middle aged drivers(between 30 and 49). Despite the rise of traffic accident risk, few have been attempted to take a look into driving characteristics of young drivers. The purpose of this paper is to analyze age-specific risks of young driver by means of database of insurance and vehicle inspection, thereby collecting data such as age, vehicle mileage, injuries and so on. We conducted Data-Mining(CART) and Portfolio analysis according to age groups(every 10 years). The conclusions which can be drawn from this empirical study are as follows: (1) Despite the fact that young drivers have low vehicle mileage, the rate of fatality is relatively high. (2) Being concerned of vehicle mileage, 24,000km of driving experience is thought to be critical in differing in fatality rate. Having annual average mileage fewer than 24,169 km, accident frequency is relatively lower than that exceeding 24,169 km(1,571 cases). Backed upon these, some recommendations about driver's license system for young driver to improve are given.

• Journal of Agricultural Extension & Community Development
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• v.23 no.3
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• pp.243-255
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• 2016

This study aims to identify the characteristics of businesses influencing the choice of their type in the 6th industry and analyze how they work. This study analyzed data of 752 businesses certified as belonging to the 6th industry in 2015 through the classification and regression tree (CART) algorithm in decision tree analysis. The results of analysis showed that the type of agricultural product processing, region, the type of service, and the production percentage in a province affected a choice of the type. The most important variable that impacted how businesses in the 6th industry chose their type was the type of agricultural product processing, and if a business produced simple agricultural products, it was likely to specialize into $1st^*2nd$ or $1st^*3rd$. Access to large consumption areas was a critical factor in the growth of 2nd and 3rd industrial functions. These findings would contribute to establishing a model to develop the 6th industry and empirically demonstrate the importance of access to large consumption areas for agricultural businesses and rural tourism.

• Journal of Information Technology Applications and Management
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• v.17 no.2
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• pp.71-90
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• 2010

Electronic learning(or e-learning) has created hype for companies, universities, and other educational institutions. It has led to the phenomenal growth in the use of web-based learning and experimentation with multimedia, video conferencing, and internet-based technologies. Many researchers are interested in the factors that affect to the performance of e-learning or e-learning services. In this sense, this study is aimed at proposing e-learning system reuse prediction models in which e-learner intention to reuse influence factors(i.e., system accessibility, system stability, information clarity, information validity, self-regulated efficacy, computer self-efficacy, perceived usefulness, perceived ease of use, flow, and parental expectation) affect e-learner intention to reuse positively. A web survey was conducted for the full members of the e-learning education institute A in Seoul, Republic of Korea, an exclusive e-learning company that provides real time video lectures via the desktop conferencing system. The web survey was conducted for 20 days from November 5, 2009, through the e-learning web site of the company A. In this study, three data mining techniques were used : the multivariate discriminant analysis, CART, and C5.0 algorithm. This study was conducted to provide the e-learning service providers, e-learning operators, and contents developers with marketing and management strategies for improving the e-learning service companies, based on the data mining analysis results.

• Journal of the Korean Society of School Health
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• v.19 no.1
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• pp.79-88
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• 2006

Purpose : To identify general characteristics of school personnel with recent fatigue which was the most frequent symptom among subjective symptoms and to explore fatigue-related factors by evaluating physical and perceived health status, life style, and symptoms through data mining techniques. Methods : We collected a data of the 1,147(male 545, female 602) who were elementary, middle, or high school personnel, answered a questionnaire, and received physical examination in Seoul School Health Center from September to November in 2000. And we investigated the differences between fatigue group and non-fatigue group for demographic characteristics, physical health status, perceived health status, symptoms, and laboratory values by frequency, chi-square test, t-test, or simple logistic regression analysis by SAS package 8.1, and then selected significant variables as input variables of a decision tree analysis of CART model by SAS E-miner. Results : In general characteristics, the fatigue consisted of 41.1%(male 35.2%, female 46.4%) among 1,147 school personnel. In classical statistics, factors related with fatigue were female, lower means of systolic and diastolic pressure, young age, personnel in middle school, irregular eating habit, no exercise a week or less than 30minutes exercise a day, perception of unhealthy status, and subjective symptoms including short of breath at exercise. In simple logistic regression to examine the relationship between selected independent variables and fatigue as a dependent variable, the odds ratio of gender (female vs male) was 1.58 times, and young age ( 20s vs 60s) 20.67 times, and middle vs high school personnel 1.86 times. However, we mined combined several characteristics by SAS-E miner. In CART model, if health perception was healthy, and age was >= 37.5 years, the proportion of the fatigue was only 19.3%. but if health perception was not healthy and symptom was severe 'short of breath' during exercise and age was < 53.5 years, and BMI was >= 22.69, the proportion of the fatigue was up to 84.8%. Conclusions : The fatigue consisted of 41.1%(male 35.2%, female 46.4%). In classical statistics, fatigue-related factors among school personnel were young age, female gender, perceived unhealthy status, subjective physical symptoms, poor life-style, and lower blood pressure rather than only physical health status. However, in data mining, if health perception was healthy and age was >= 37.5 years, the proportion of the fatigue was only 19.3%. but if health perception was not healthy and symptom was severe 'short of breath' during exercise and age was < 53.5 years, and BMI was >= 22.69, the proportion of the fatigue was up to 84.8%.

• 한국노년학
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• v.29 no.4
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• pp.1327-1340
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• 2009

The purposes of the study were (1) to identify the level of successful aging of older people living in a city, (2) to identify associated factors with successful aging, and (3) to identify a risk group for successful aging using classification and regression trees (CART) analysis. One hundred eighty seven older people (>65years) participated in the cross-sectional survey. Trained interviewers collected data with a structured questionnaire on demographic information, Korean geriatric depression score, activity of daily living(ADL), instrumental activity of daily living(IADL), and Young's successful aging instrument in subject's home. A CART analysis split subjects into ten homogeneous small groups based on five determinant factors. Older people who are male, with higher education, living with family, and not receiving Medicaid showed better scores in successful aging than their counter parts. Depression was a strong primary determinant for successful aging. A risk group for successful aging of older people was identified by depression and IADL. An intervention to prevent and manage depression and to improve physical function of older people can be developed to promote successful aging of older people. It is suggested to consider an assessment of depression to develop the policies for older people welfare.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1786-1797
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• 2010

Automatic understanding of contents in document image is a very hard problem due to involvement with mathematically challenging problems originated mainly from the over-determined system induced by document segmentation process. In both academic and industrial areas, there have been incessant and various efforts to improve core parts of content retrieval technologies by the means of separating out segmentation related issues using semi-structured document, e.g., invoice,. In this paper we proposed classification models for text lines on invoice document in which text lines were clustered into the five categories in accordance with their contents: purchase order header, invoice header, summary header, surcharge header, purchase items. Our investigation was concentrated on the performance of machine learning based models in aspect of linear-discriminant-analysis (LDA) and non-LDA (logic based). In the group of LDA, na$\"{\i}$ve baysian, k-nearest neighbor, and SVM were used, in the group of non LDA, decision tree, random forest, and boost were used. We described the details of feature vector construction and the selection processes of the model and the parameter including training and validation. We also presented the experimental results of comparison on training/classification error levels for the models employed.

• Proceedings of the KSME Conference
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• 2000.04b
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• pp.385-391
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• 2000

An analysis of the heat transfer in a PDP ventilation chamber has been conducted to investigate the required heat curve and temperature uniformity of the panels. Firstly, experiment in a test chamber has been carried out and compared with the unsteady 3D numerical simulation. Reasonable agreement was found, which suggested that the employed numerical model had its credibility in an actual PDP ventilation process. On this ground, tact-type heating/cooling system was analyzed. The panel temperature was more uniform in the $40^{\circ}C$ tact-type system than in the $80^{\circ}C$ one. Comparison of full simulation of a cart and simplified simulation of one panel shows the panel pitch, which is closely related to a production rate, can be also predicted.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.9
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• pp.1507-1515
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• 2008

It is essential for electric power companies to have a quick restoration system of the faulted pole transformers which occupy most of transformers to supply stable electricity. However, it takes too much time to restore it when a transformer is out of order suddenly because we now count on operator in investigating causes of failure and making decision of recovery methods. This paper presents the concept of 'Fault pattern analysis and Restoration prediction model using Data mining techniques’, which is based on accumulated fault record of pole transformers in the past. For this, it also suggests external and internal causes of fault which influence the fault pattern of pole transformers. It is expected that we can reduce not only defects in manufacturing procedure by upgrading quality but also the time of predicting fault patterns and recovering when faults occur by using the result.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.2
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• pp.19-29
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• 2015

The purpose of this study is to suggest the grid search method for selecting an optimal decision tree model. It chooses optimal values for the maximum depth of tree and the minimum number of observations that must exist in a node in order for a split to be attempted. Therefore, the grid search method guarantees building a decision tree model that shows more precise and stable classifying performance. Through empirical analysis using data of job satisfaction of workplace reserve force commanders, we show that the grid search method helps us generate an optimal decision tree model that gives us hints for the improvement direction of labor conditions of Korean workplace reserve force commanders.