• Journal of Information Technology Applications and Management
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• 제15권1호
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• pp.243-260
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• 2008

To prevent low yields in the semiconductor industry is crucial to the success of that industry. However, to prevent low yields is difficult because of too many factors to affect yield variation and their complex relation in the semiconductor manufacturing process. This study presents a new efficient detection methodology for detecting abnormal yields including high and low yields, which can forecast the yield level of a production unit (namely a lot) based on yield-related feature variables' behaviors. In the methodology, we use C5.0 to identify the yield-related feature variables that are the combination of correlated process variables associated with yield, use SOM (Self-Organizing Map) neural networks to extract and classify significant patterns of past abnormal yield lots and finally use C5.0 to generate classification rules for detecting abnormal yield lot. We illustrate the effectiveness of our methodology using a semiconductor manufacturing company's field data.

• Asia pacific journal of information systems
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• 제5권2호
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• pp.37-50
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• 1995

This study analyzed 89 MIS published in Korea since 1974. The keyword classification scheme proposed by Barki et al. [1993] was employed to classify researched themes of the papers. Research methods and research variables were also examined. The results showed that (1) the Korean MIS research focused on DSS/ES, IS evaluation, IS development and operations, (2) nonempirical studies took 46% of the 89 papers while survey method was frequently used in empirical studies, (3) in empical studies, user-related variables were most frequently included as dependent variable while organization-related variables were most frequently selected as independent variable. Some recommendations for the future MIS research in Korea were suggested.

• 한국의류학회지
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• 제17권4호
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• pp.602-607
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• 1993

Concept of the comfort and fitness becomes a major concern in the basic function of the ready-made clothes. This research was performed to classify and characterize Korean adult males anthropometrically. Sample size was 1290 subjects and their age range was from 19 to 54 years old. Sampling was carried out by the stratified sampling method. 75 variables in total were applied to classify the bodytypes. Data were analyzed by the multivariate method, especially factor and cluster analysis. The high factor loading items extracted by factor analysis were based to determine the variables of the cluster analysis for the similar bodytypes respectively. In the part of the lower body, 14 variables from the data were applied to classify the bodytypes of lower part by Ward's minimum variance method. The group fanning a cluster were subdivided into 5 sets by cross-tabulation extracted by the hierarchical cluster analysis. Type 3 and 4 in lower body were composed of the majority of 53.1% of the subjects. The Korean adult males had relatively well-balanced in lower body.

• International Journal of Internet, Broadcasting and Communication
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• 제14권4호
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• pp.228-239
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• 2022

Many countries around the world using ICT technologies have various technologies to keep pace with the 4th industrial revolution, and various algorithms and systems have been developed accordingly. Among them, many industries and researchers are investing in unmanned automation systems based on AI. At the time when new technology development and algorithms are developed, decision-making by big data analysis applied to AI systems must be equipped with more sophistication. We apply, Pearson's correlation analysis is applied to six independent variables to find out the job satisfaction that office workers feel according to their job characteristics. First, a correlation coefficient is obtained to find out the degree of correlation for each variable. Second, the presence or absence of correlation for each data is verified through hypothesis testing. Third, after visualization processing using the size of the correlation coefficient, the degree of correlation between data is investigated. Fourth, the degree of correlation between variables will be verified based on the correlation coefficient obtained through the experiment and the results of the hypothesis test

• 정보기술응용연구
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• 제3권2호
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• pp.1-24
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• 2001

본 연구는 R사의 대고객 만족도 향상을 위하여 고객관계관리(customer relationship management, CRM)를 수행하기 위한 목적으로 추진되었다. 연구의 주안점은 연구관리 데이터베이스로부터 연구관련 변수들의 패턴 및 상호작용을 고려하여 연구계약기관을 기관별 연 구과제의 연구유형 및 연구비에 대한 분석을 통하여 고객유형별로 분류함으로써 향후 대고객관리의 방향을 설정하기 위한 목적으로 시도되었다. 본 연구에서 의사결정나무 알고리듬을 이용하여 자료를 분석한 결과, 17개의 입력변수 중 내외부 계약기관을 분류하는 데 있어서 중요한 변수로는 연구기간, 제경비, 기술개발비의 3개 변수로 나타났다. 연구결과, R사의 고객은 6개월 이상의 연구기간, 3,000만원 이상의 제경비, 그리고 6,075만원의 기술개발비를 기준으로 연구계약기관이 분류되며, 이 연구관련 변수를 이용하여 대고객과의 연구주제 설정, 연구예산 수립 등의 고객관리방안을 수립할 수 있을 것이다.

• 환경영향평가
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• 제24권1호
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• pp.35-50
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• 2015

본 연구는 비도시지역의 생물종 서식지 보전을 위해 반영할 수 있는 생물종 관련 지표의 개발과 관리지역 세분화 방안을 제시하는데 목적이 있다. 이를 위해 생물종 서식분포를 예측한 후에 예측된 서식분포를 활용하여 종풍부도를 만들고 그 결과를 토지적성평가와 비교를 하였다. 종분포도는 59종을 대상으로 Maxent 모형을 사용하였고 15개의 모형변수(5개 지형변수, 4개 식생변수, 6개 거리변수)를 활용하였다. 예측된 생물종 서식분포를 출현/비출현으로 구분한 후 합산하여 종풍부도를 예측 하였다. 토지적성평가는 평가체계 I에 따라 보전, 농업, 개발적성을 물리적, 지역, 공간적 입지 특성별로 평가하였다. 종풍부도 등급과 토지적성평가 등급과의 비교결과는 1등급은 10.92%, 2등급은 37.10%, 3등급은 34.56%, 4등급은 20.89% 그리고 5등급은 1.73%의 면적 일치도가 나타났다. 보전관리지역으로 분류되는 1등급과 계획관리지역으로 분류되는 5등급의 일치도가 가장 낮았다. 이처럼 계획관리지역으로 분류되어도, 종풍부도를 고려해 보면 많은 계획관리지역이 상대적으로 높은 종풍부도 값을 보여주었다. 관리지역은 생물종 서식지의 핵심지역은 아니지만 경관생태학적 관점에서 주변 서식처, 이동통로 등을 제공하면서 생물다양성 보호에 기여 할 수 있다. 따라서 도시관리계획에서 잠재적 생물종 서식분포를 고려하는 노력이 보다 집중되어야 할 것이다.

• Asian-Australasian Journal of Animal Sciences
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• 제33권7호
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• pp.1202-1208
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• 2020

Objective: The aim of this study was to identify a distribution pattern of meat quality grade (MQG) as a function of carcass yield index (CYI) and the gender of Hanwoo (bull, cow, and steer) to determine the optimum point between both yield and quality. We also attempted to identify how pre- and post-deboning variables affect the gender-specific beef quality of Hanwoo. Methods: A total of 31 deboning variables, consisting of 7 pre-deboning and 24 post-deboning variables from bulls (n = 139), cows (n = 69), and steers (n = 153), were obtained from the National Institute of Animal Science (NIAS) in South Korea. The database was reconstructed to be suitable for a statistical significance test between the CYI and the MQG as well as classification of meat quality. Discriminant function analysis was used for classifying MQG using the deboning parameters of Hanwoo by gender. Results: The means of CYI according to 1+, 1, 2, and 3 of MQG were 68.64±2.02, 68.85±1.94, 68.62±5.88, and 70.99±3.32, respectively. High carcass yield correlated with low-quality grade, while high-quality meat most frequently was obtained from steers. The classification ability of pre-deboning parameters was higher than that of post-deboning parameters. Moisture and the shear force were the common significant parameters in all discriminant functions having a classification accuracy of 80.6%, 71%, and 56.9% for the bull, cow, and steer, respectively. Conclusion: This study provides basic information for predicting the meat quality by gender using pre-deboning variables consistent with the actual grading index.

• Tuberculosis and Respiratory Diseases
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• 제81권4호
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• pp.281-288
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• 2018

Background: There are limited number of studies that investigate clinical variables instead of chronic obstructive lung disease (COPD) management according to Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2017 classification. The aim of the study was to investigate whether there was a difference between GOLD 2017 classification and spirometric stage in clinical variables in patients with COPD. The data of 427 male patients with stable COPD were investigated retrospectively. Methods: Patients were allocated into combined assessment of GOLD 2017 and spirometric stage. Age, amount of smoking, pulmonary function, modified Medical Research Council (mMRC), incremental shuttle walk test (ISWT), Hospital Anxiety-Depression Scale (HADS), St. George's Respiratory Questionnaire (SGRQ), body mass index (BMI), and fat free mass index (FFMI) were recorded. Results: Seventy-three (17%) patients were in group A, 103 (24%) constituted group B, 38 (9%) were included in group C, and 213 (50%) comprised group D according to the combined assessment of GOLD 2017. Twenty-three patients (5%) were in stage 1, 95 (22%) were in stage 2, 149 (35%) were in stage 3, and 160 (38%) were in stage 4 according to spirometric stage. According to GOLD 2017, age, amount of smoking, mMRC, BMI, FFMI, SGRQ, HADS, forced vital capacity, forced expiratory volume in 1 second ($FEV_1$), and ISWT were significantly different between groups. Ages, amount of smoking, FFMI, BMI, HADS of group A were different from B and D. Smiliar values of $FEV_1$ were found in A-C and B-D. A and C had smiliar ISWT. According to spirometric stage, BMI, FFMI of stage 4 were statistically different. mMRC, ISWT, and SGRQ of stages 3 and 4 were different from other stages, amongst themselves. $FEV_1$ was correlated with mMRC, SGRQ, anxiety scores, BMI, FFMI, and ISWT. Conclusion: This study showed that the GOLD ABCD classification might not represent the severity of COPD sufficiently well in terms of lung function or exercise capacity. The combination of both spirometric stage and combined assessment of GOLD 2017 is important, especially for estimating clinical variables.

• Journal of Animal Science and Technology
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• 제54권6호
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• pp.463-469
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• 2012

This study utilized a standardization and cluster analysis technique for the selection and classification of beneficial bacteria. A set of synthetic data consisting of 100 individual variables with three characteristics was created for analysis. The three characteristics assigned to each independent variable were designated to have different numeric scales, averages, and standard deviations. The variables were bacterial isolates at random, and the three characteristics were fermentation products, including cell yield, antioxidant activity of culture, and enzyme production. A standardization method utilizing a standard normal distribution equation to record fermentation yields of each isolate was employed to weight their different numeric scales and deviations. Following transformation, the data set was analyzed by cluster analysis. The Manhattan method for dissimilarity matrix construction along with complete linkage technique, an agglomerative method for hierarchical cluster analysis, was employed using statistical computing program R. A total of 100 isolates were classified into groups A, B, and C. In a comparison of the characteristics of each group, all characteristics in groups A and C were higher than those of group B. Isolates displaying higher cell yield were classified as group A, whereas those isolates showing high antioxidant activity and enzyme production were assigned to group C. The results of the cluster analysis can be useful for the classification of numerous isolates and the preparation of an isolation pool using numerical or statistical tools. The present study suggests that a simple technique can be applied to screen and select beneficial microbes using the freely downloadable statistical computing program R.

• 한국융합학회논문지
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• 제9권10호
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• pp.243-248
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• 2018

노년기의 사회참여는 사회적 상호작용의 기회를 제공하여 삶의 만족감을 고취시키기 때문에 성공적인 노화를 달성하기 위해서 중요하다. 이 연구는 우리나라 지역사회 노인을 대상으로 노년기 사회 활동의 관련요인과 사회 참여를 예측하는 통계적 분류 모형을 구축하였다. 분석 대상은 2015년도 지역사회 건강조사를 완료한 60세 이상 노인 1,864명(남 829명, 여 1,035명)이었다. 결과 변수는 지난 1달 간 사회 활동 경험(있음, 없음)으로 정의하였다. 예측모형은 Classification and Regression Trees(CRT) 알고리즘 기반 의사결정나무모형을 이용하여 구축하였다. 연구결과, 사회참여의 유의미한 분류 변수는 주관적 건강, 이웃과의 만남빈도, 친척과의 만남빈도, 배우자 동거여부이었고, 그 중에서도 가장 우선적으로 관여하는 예측 요인은 주관적 건강수준이었다. 본 연구의 결과를 기초로 도래하는 초고령사회의 성공적인 노화를 대비하기 위해서 노인의 사회 활동에 대한 사회적 관심과 지원이 요구된다.