• Industrial Engineering and Management Systems
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• 제4권1호
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• pp.102-108
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• 2005

This paper studies medical data classification methods, comparing decision tree and system reconstruction analysis as applied to heart disease medical data mining. The data we study is collected from patients with coronary heart disease. It has 1,723 records of 71 attributes each. We use the system-reconstruction method to weight it. We use decision tree algorithms, such as induction of decision trees (ID3), classification and regression tree (C4.5), classification and regression tree (CART), Chi-square automatic interaction detector (CHAID), and exhausted CHAID. We use the results to compare the correction rate, leaf number, and tree depth of different decision-tree algorithms. According to the experiments, we know that weighted data can improve the correction rate of coronary heart disease data but has little effect on the tree depth and leaf number.

• 한국산학기술학회논문지
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• 제11권9호
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• pp.3366-3374
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• 2010

본 연구는 일개 지역의 노인을 대상으로 고혈압과 당뇨병 유무에 따른 건강관리 및 인식 패턴을 파악하고자 하였다. 고혈압, 당뇨병 유무에 다른 분석 중 군간 유의하게 나타난 생존변수 성별, 결혼상태, 직업, 건강관리방법, 연령대를 기초로 만성질환에 따른 패턴을 CART로 연구하였다. 직업군 패턴 결과 농업 직업군에서는 당뇨병이 가장 높은 빈도를 나타냈으나 어업, 공무원 직업군에서는 정상군이 가장 높은 빈도를 나타났다. 직업군이 상업 또는 기타에서는 연령에 80, 90대로 점차 갈수록 당뇨병의 발생 빈도는 높아지는 것으로 나타났다. 최근 들어 노인 인구가 증가하고 있는 현실에서 노인들의 질병과 활동제한으로 건강에 문제가 발생하고 있는 시점에서 생활기능의 증가를 통하여 노인의 삶을 높이고, 노인들의 삶의 질적인 면까지 고려하여 건강하고 만족하는 생활을 하면서 여생을 보낼 수 있도록 하여야 할 것이다.

• 한국컴퓨터정보학회논문지
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• 제21권6호
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• pp.9-19
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• 2016

In finance literature, stock liquidity showing how stocks can be cashed out in the market has received rich attentions from both academicians and practitioners. The reasons are plenty. First, it is known that stock liquidity affects significantly asset pricing. Second, macroeconomic announcements influence liquidity in the stock market. Therefore, stock liquidity itself affects investors' decision and managers' decision as well. Though there exist a great deal of literature about stock liquidity in finance literature, it is quite clear that there are no studies attempting to investigate the stock liquidity issue as one of decision making problems. In finance literature, most of stock liquidity studies had dealt with limited views such as how much it influences stock price, which variables are associated with describing the stock liquidity significantly, etc. However, this paper posits that stock liquidity issue may become a serious decision-making problem, and then be handled by using data mining techniques to estimate its future extent with statistical validity. In this sense, we collected financial data set from a number of manufacturing companies listed in KRX (Korea Exchange) during the period of 2010 to 2013. The reason why we selected dataset from 2010 was to avoid the after-shocks of financial crisis that occurred in 2008. We used Fn-GuidPro system to gather total 5,700 financial data set. Stock liquidity measure was computed by the procedures proposed by Amihud (2002) which is known to show best metrics for showing relationship with daily return. We applied five data mining techniques (or classifiers) such as Bayesian network, support vector machine (SVM), decision tree, neural network, and ensemble method. Bayesian networks include GBN (General Bayesian Network), NBN (Naive BN), TAN (Tree Augmented NBN). Decision tree uses CART and C4.5. Regression result was used as a benchmarking performance. Ensemble method uses two types-integration of two classifiers, and three classifiers. Ensemble method is based on voting for the sake of integrating classifiers. Among the single classifiers, CART showed best performance with 48.2%, compared with 37.18% by regression. Among the ensemble methods, the result from integrating TAN, CART, and SVM was best with 49.25%. Through the additional analysis in individual industries, those relatively stabilized industries like electronic appliances, wholesale & retailing, woods, leather-bags-shoes showed better performance over 50%.

• 대한치과교정학회지
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• 제43권6호
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• pp.279-287
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• 2013

Objective: To investigate the dentoskeletal factors which may predict soft-tissue chin strain during lip closure. Methods: The pretreatment frontal and lateral facial photographs and lateral cephalograms of 209 women (aged 18-30 years) with Angle's Class I or II malocclusion were examined. The subjects were categorized by three examiners into the no-strain and strain groups according to the soft-tissue chin tension or deformation during lip closure. Relationships of the cephalometric measurements with the group classification were analyzed by logistic regression analysis, and a classification and regression tree (CART) model was used to define the predictive variables for the group classification. Results: The lower the value of the overbite depth indicator (ODI) and the higher the values of upper incisor to Nasion-Pogonion (U1-NPog, mm), overjet, and upper incisor to upper lip (U1-upper lip, mm), the more likely was the subject to be classified into the strain group. The CART showed that U1-NPog was the most prominent predictor of soft-tissue chin strain (cut-off value of 14.2 mm), followed by overjet. Conclusions: To minimize strain of the soft-tissue chin, orthodontic treatment should be oriented toward increasing the ODI value while decreasing the U1-NPog, overjet, and U1 upper lip values.

• 한국콘텐츠학회논문지
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• 제14권7호
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• pp.407-426
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• 2014

본 연구는 인터넷 소비자의 구매지연행동에 영향을 미치는 요인을 규명하고자 하였고, 인터넷 소비자의 상황적 요인과 지각된 불확실성이 구매지연행동에 미치는 영향을 분석하였다. 서울 수도권 지역의 인터넷 소비자를 대상으로 설문조사를 하여 394부의 자료를 분석에 사용하였다. 본 연구의 결과를 요약하면 첫째, 전반적 구매지연에는 부정적 경험과 후회회피가 정(+)의 영향요인으로 나타났다. 결제단계 지연에는 시간압박성, 구매변경 가능성, 부정적 경험 및 후회회피가, 장바구니 포기에는 시간압박성과 부정적 경험, 후회회피가 정(+)의 영향을 미치고 있었다. 둘째, 전반적인 구매지연과 결제단계 지연에는 정보, 선호 및 심리불확실성이, 장바구니 포기에는 정보 및 심리 불확실성이 정(+)의 영향을 미치고 있었다. 본 연구는 인터넷 소비자의 구매지연행동의 상황적 요인과 지각된 불확실성을 분석함으로써 인터넷 분야 연구의 이론 확장 및 다양화에 기여하였고, 인터넷 쇼핑몰의 고객관리와 마케팅 전략에 유용한 자료를 제공한 의의가 있다.

• 한국자동차공학회논문집
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• 제14권5호
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• pp.65-72
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• 2006

In new generation vehicle technologies, a fuel cell vehicle becomes more important, by virtue of their emission merits. In addition, a fuel cell is considered as a major source to generate the electricity for vehicles in near future. This paper focuses on modeling of not only an electric vehicle and but also a fuel cell vehicle to estimate performances. And an EV cart is manufactured to verify the modeling. Speed, voltage, and current of the vehicle and modeling are compared to estimate them at acceleration test and driving mode test. The estimations are also compared with the data of the Ballard Nexa fuel cell stack. In order to investigate a fuel cell based vehicle, motor and fuel cell models are integrated in a electric vehicle model. The characteristics of individual components are also integrated. Calculated fuel cell equations show good agreements with test results. In the fuel cell vehicle simulation, maximum speed and hydrogen fuel consumption are estimated. Even though there is no experimental data from vehicle tests, the vehicle simulation showed physically-acceptable vehicle characteristics.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1474-1479
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• 2004

In this paper, the design of the network system using the CAN and the analysis of effects of time delay in the system are presented. A conventional implementation technique induces many problems because of the amount and complexity of wiring and maintenance problems. The network system reduces these problems, but it cause another problem; time delay. Time delay in a sampling time does not have much effects on the system, but time delay over the sampling time changes the control frequency and ended up makes the system unstable. It is verified that time delay between each parts has different effects on the entire system. The results from this paper will be a base for studying algorithms to reduce effects of time delay in the system using the CAN.

• 한국가구학회지
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• 제19권1호
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• pp.33-43
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• 2008

This study intended to explore trends of furniture sold in general merchandise stores such as Lotte mart, E-mart, GSmart, Home ever, and Home plus, which are run by conglomerates in Korea. Through internet, related books and papers, interviews with the mart-related people, styles, items, prices, manufacturers, and materials of furniture well sold in the marts were researched and analyzed qualitatively. As the result of the analysis, the furniture expressed the scale to be able to put in the cart of the marts, knock-down and folding structure to be easy to disassemble, pack, and move, low prices below one hundred thousand won, the light materials like plastic, aluminum and the more MDF than hard wood. Each item was made of PB reflecting lower prices of 10 to 20 percentage for the consumer.

• Journal of the Korean Data and Information Science Society
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• 제18권1호
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• pp.1-10
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• 2007

In this paper, we focus on churn analysis for the first successful candidates in the entrance examination on 2006 year using Clementine, data mining tool. The goal of this study is to apply decision tree including C5.0 and CART algorithms, neural network and logistic regression techniques to predict a successful candidate churn. And we analyze the churning and nochurning successful candidates and why the successful candidates churn and which successful candidates are most likely to churn in the future using data from entrance examination data of K university on 2006 year.

• Journal of Acupuncture Research
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• 제29권5호
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• pp.61-74
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• 2012

Objectives : This study is perfomed for preparation of oriental medicine clinical guidelines for drawing up the standards of oriental medicine demonstration and diagnosis classification about the knee pain. Methods : Statistical analysis about Crane's-knee wind(鶴膝風), arthralgia syndrome(痺症), knee injury(膝傷), gout arthritis(痛風), Youk jeol poung(歷節風) classified experts' opinions about knee pain patients by Delphi method is conducted by using oriental medicine diagnosis questionnaire. The result was classified by using linear discriminant analysis(LDA), diagonal linear discriminant analysis(DLDA), diagonal quadratic discriminant analysis(DQDA), K-nearest neighbor classification(KNN), classification and regression trees(CART), support vector machines(SVM). Results : The results are summarized as follows. 1. The result analyzed by using LDA has a hit rate of 81.65% in comparison with the original diagnosis. 2. The result analyzed by using DLDA has a hit rate of 63.3% in comparison with the original diagnosis. 3. The result analyzed by using DQDA has a hit rate of 65.14% in comparison with the original diagnosis. 4. The result analyzed by using KNN has a hit rate of 74.31% in comparison with the original diagnosis. 5. The result analyzed by using CART has a hit rate of 75.23% in comparison with the original diagnosis when the test of selected 13 significant questions based on analysis of variance was performed. 6. The result analyzed by using SVM has a hit rate of 87.16% in comparison with the original diagnosis. Conclusions : Statistical analysis using oriental medicine diagnosis questionnaire on knee pain generally turned out to have a significant result.