• 대한가정학회지
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• 제12권3_4호
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• pp.641-662
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• 1974

The purpose of this study is to present the basic rule on the planning standard menu for the improvement of nutritional school lunch program through analysis of their food habits and daily energy expenditure. 1. The purpose of the school lunch program is to get on adequate diet in quality and quantity through right food habits and nutrition education for the most active growing children. 2. At present time in Korea, school lunch program has not been carried out nutritionaly so that it should be improved immediately. 3. The ratio of the daily diet should be given to the students breakfast 1. lunch 1.1, dinner 1.5, through analysis of their daily energy expenditure by their activity. 4. The result of the analysis of for food habits shows that children like foods which were used at home commonly and dislike foods not commonly used. 5. The basic rule on the planning school lunch menu is presented as follows. 1) The ratio of the aily diet should be given as breakfast 1, lunch 1.1. dinner 1.5, for calories, and minerals and vitamins should be given 1/3 to 2/5 of a daily requirements. 2) It should be selected foods which most children like foods when plan menu for school lunch. 3) Green, yellow vegetables should be given over 50 gm. 4) Milk should be given 180cc.

• Industrial Engineering and Management Systems
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• 제11권4호
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• pp.371-384
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• 2012

This study proposes a multi-level data analysis approach to identify both superficial and latent relationships among variables in the data set obtained from a vocational rehabilitation (VR) services program of people with significant disabilities. At the first layer, data mining and statistical predictive models are used to extract the superficial relationships between dependent and independent variables. To supplement the findings and relationships from the analysis at the first layer, association rule mining algorithms at the second layer are employed to extract additional sets of interesting associative relationships among variables. Finally, nonlinear nonparametric canonical correlation analysis (NLCCA) along with clustering algorithm is employed to identify latent nonlinear relationships. Experimental outputs validate the usefulness of the proposed approach. In particular, the identified latent relationship indicates that disability types (i.e., physical and mental) and severity (i.e., severe, most severe, not severe) have a significant impact on the levels of self-esteem and self-confidence of people with disabilities. The identified superficial and latent relationships can be used to train education program designers and policy developers to maximize the outcomes of VR training programs.

• 디지털융복합연구
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• 제16권6호
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• pp.85-93
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• 2018

대표적인 종단자료 분석방법인 잠재성장모형(Latent Growth Modeling)은 무조건적 모델과 조건적 모델로 구분되는데, 이중 무조건적 모델은 초기값과 기울기를 추정하여 적합도가 높은 모델을 추정해야 한다. 그렇지만 기존 잠재성장모형에는 종단자료의 형태가 단순선형함수 등 특정 함수가 아닐 경우 기울기를 추정하는 체계적인 방법론이 없었다. 본 연구에서는 뮤조건적 모델의 기울기를 추정하는데 연관규칙(Association Rule Mining)의 순차패턴(Sequential Pattern)을 사용하였다. 데이터는 한국고용정보원의 2001년~2006년에 조사한 청년 패널 데이터를 사용하였다. 제안한 방법론은 기존 단순선형함수를 가정할 때와 비교하여 적합도가 상승하는 것을 확인할 수 있었으며, 기울기 추정 과정을 시각화할 수 있는 부수적인 장점이 있었다.

• 한국융합학회논문지
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• 제10권2호
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• pp.217-225
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• 2019

대표적인 종단자료 분석방법인 잠재성장모형(Latent Growth Modeling)은 무조건적 모형과 조건적 모형으로 구분한다. 잠재성장모형의 무조건적 모형 성장궤적은 선형으로 가정하여 분석하는 경우가 많다. 본 연구는 선형 성장궤적으로 가정하여 모형 적합도가 미달하는 경우 연관규칙기법을 이용하여 모형 적합도를 제고하는 방법론을 제안한다. 방법론은 연관규칙 마이닝의 순차패턴(Sequential Pattern)을 사용한다. 이를 위하여 종단자료를 분위별로 나누고, 각 분위에 속한 종단자료의 기간 변화를 산출한 뒤 이를 순차 패턴 화하였다. SPSS AMOS를 이용하여 한국고용정보원의 2001년부터 6년간 조사한 청년 패널 자료로 효과성을 검증하였다. 기존 단순선형함수를 가정할 때와 비교하여 모형 적합도가 상승하는 것을 확인할 수 있었다.

• 대한가정학회지
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• 제32권3호
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• pp.135-146
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• 1994

This study proposed a plan to seek a more practical way of life norm education of today's families on the basis of family rule in the traditional society by comparison between the older generation's family life rule education and college students. The study was made by analysing rules in Chosun Dynasty questionaire nair was drawn up on the basis of it. The subjects of this study were college students of one largest cities and their 800 parents. Collected data was processed by frequency analysis, ANOVA, interrelation and regression which are used through SPSS computer programs, Study results show that acceptance level is higher among the older generation but the necessity of family standare education is urgent beyond the generations. Also people who have lived with grand parents feel more necessity of education family norm. When the education could not be made in families because parents excessive protection examination-centered education, and bad effects of mass media then emphasis has to be made to create life culture which makes family norms to be kept continuously by the education at schools, education culture centers and public facilities.

• 산업공학
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• 제21권2호
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• pp.237-246
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• 2008

In today's competitive global environment, technological innovation is an important issue. Many countries are devising national level strategies to further strengthen industrial capacity in support of innovative companies. South Korea is no exception, and multiple strategies are in place to aid innovative development in the private sector. This study postulates that such national level strategies are applied differently depending on the innovation goal pursued by the service sector in Korea. We use data mining methods to test such research hypothesis. Factor analysis is used for clustering of various service companies, while association rule is used in finding the relationship per each cluster. The results show that national level strategies are underutilized and unequally distributed. This may be attributed to the disparity between the demand and needs of the private sector and the opinion of the government, which lead to underutilized and indistinguishable strategies.

• 산업공학
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• 제19권4호
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• pp.342-354
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• 2006

The purpose of this thesis is to develop the schemes of supporting estimate for marine engines’ factories which are in a general make-to-order style. The marine engines’ factories currently use the method which depends on the past data and experiences handled by the responsible person, which causes inefficiency and inaccuracy in dealing with a huge amount of data. We apply association rule to solving the problems mentioned above. Critical data for analysis is filtered among materials that have been using actual records of performance so far. Secondly, relation with each part of marine engines through filtered data so that the company can estimate cost promptly and precisely if customers with similar components as requested. By proposed method of study estimate support efficient and supported exactly.

• Asian Journal of Innovation and Policy
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• 제8권1호
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• pp.73-96
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• 2019

This study suggests a new approach for identifying core robot tech-nologies based on technological cross-impact. Specifically, the approach applies data mining techniques and multi-criteria decision-making methods to the co-classification information of registered patents on the robots. First, a cross-impact matrix is constructed with the confidence values by applying association rule mining (ARM) to the co-classification information of patents. Analytic network process (ANP) is applied to the co-classification frequency matrix for deriving weights of each robot technology. Then, a technique for order performance by similarity to ideal solution (TOPSIS) is employed to the derived cross-impact matrix and weights for identifying core robot technologies from the overall cross-impact perspective. It is expected that the proposed approach could help robot technology managers to formulate strategy and policy for technology planning of robot area.

• Journal of the Korean Data and Information Science Society
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• 제24권2호
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• pp.267-275
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• 2013

데이터 마이닝 기법들 중에서도 연관성 규칙은 가장 최근에 개발된 기법으로 대용량 데이터베이스에서 각 항목들 간의 관련성을 찾아내며, 두 항목간의 관계를 명확히 수치화함으로써 두 개 이상의 항목간의 관련성을 표시하여 주기 때문에 현장에서 직접 적용이 가능하다. 일반적으로 연관성 규칙 생성 여부를 판단할 때, 각 항목간의 연관성을 반영하는 기준인 지지도, 신뢰도, 향상도 등의 흥미도 측도를 활용하게 된다. 실제적으로 연관성 규칙의 수를 결정하기 위해서는 이들 흥미도 측도들의 평가기준을 정하기 위해 반복적으로 조정 과정을 거쳐야 한다. 본 논문에서는 이러한 문제를 해결하기 위해 연관성 평가기준 모두를 일반적으로 많이 활용되고 있는 비선형 회귀모형에 적용하여 연관성 규칙의 수를 추정하는 방안을 강구하였다. 또한 분산팽창계수를 이용하여 다중공선성 문제를 진단하는 동시에 분산분석 결과와 수정 결정계수를 이용하여 각 모형의 기여도를 비교하여 가장 바람직한 회귀 모형을 구하였다.

• 한국전자거래학회지
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• 제4권1호
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• pp.21-36
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• 1999

Using user monitoring techniques on web, marketing decision makers in cyber shopping malls can gather customer behavior data as well as sales transaction data and customer profiles. In this paper, we present a marketing rule extraction technique for customer behavior analysis in cyber shopping malls, The technique is an application of market basket analysis which is a representative data mining technique for extracting association rules. The market basket analysis technique is applied on a customer behavior log table, which provide association rules about web pages in a cyber shopping mall. The extracted association rules can be used for mall layout design, product packaging, web page link design, and product recommendation. A prototype cyber shopping mall with customer monitoring features and a customer behavior analysis algorithm is implemented using Java Web Server, Servlet, JDBC(Java Database Connectivity), and relational database on windows NT.