• 한국시뮬레이션학회논문지
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• 제23권4호
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• pp.189-195
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• 2014

본 논문에서는 장소와 시간의 제약을 받지 않는 클라우드 컴퓨팅 도입 의사 결정 모델링에 대한 연구를 진행하였다. 연구에서는 65명의 응답자에게 수집 된 패널데이터와 데이터마이닝 방법 중 하나인 CART(회귀분류나무)를 사용하여 의사결정 모델을 구축하였다. 모델링에는 2단계로 진행되는데 첫 번째 단계에서는 패널데이터를 사용하여 도입 의사를 결정하는데 영향을 미치는 문항들을 선택하고 2 번째 단계에서는 선택된 문항을 사용하여 도입 의사 결정 모델을 구축하였다. 문항 선택을 통하여 설문지 수집 문항수를 25개에서 5개로 줄일 수 있어 응답자에게 빠른 답변을 얻을 수 있고 데이터의 사이즈가 작기 때문에 모델 구축 시간을 줄일 수 있는 장점을 보여주었다.

• Child Health Nursing Research
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• 제29권1호
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• pp.60-71
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• 2023

Purpose: This study aimed to identify factors affecting the mental health status of children from multicultural families in South Korea. Methods: This study was based on Dahlgren and Whitehead's (1991) rainbow model as a conceptual framework and used data from the second phase of the multicultural adolescents panel study conducted by the National Youth Policy Institute. Multiple logistic regression analysis was performed using SPSS version 26.0, with p<.05 considered to indicate statistical significance. Results: In the final model, stress (odds ratio [OR]=0.53, p<.001), life satisfaction (OR=2.09, p=.004), self-esteem (OR=1.73, p=.032), and peer support (OR=1.46, p=.019) affected the mental health status of children from multicultural families. The living and working conditions and general socioeconomic, cultural, and environmental conditions did not significantly influence the mental health status of children from multicultural families in the final model. Conclusion: As components of Dahlgren and Whitehead's model, individual hereditary and lifestyle factors, as well as social and community networks, affected the mental health status of children from multicultural families. Therefore, in order to improve the mental health of children from multicultural families, efforts are needed to alleviate their stress, increase life satisfaction and self-esteem, and strengthen their social support.

• 반도체디스플레이기술학회지
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• 제21권1호
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• pp.17-21
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• 2022

In the case of the manufacturing industry that produces high-tech components such as semiconductors and large flat panel displays, the manufacturing space is made into a cleanroom to increase product yield and reliability, and various environmental factors have been managed to maintain the environment. Among them, airborne particle is a representative management item enough to be the standard for actual cleanroom grade, and a sequential particle monitoring system is usually used as one parts of the FMS (Fab or Facility monitoring system). However, this method has a problem in that the measurement efficiency decreases as the length of the sampling tube increases. In this study, in order to solve this problem, a multiple regression model was created. This model can correct the measurement error due to the decrease in efficiency by sampling tube length.

• 응용통계연구
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• 제30권6호
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• pp.957-981
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• 2017

관측되지 않는 효과 또는 고정효과로 설명할 수 없는 분산 구조가 포함되어 정확한 모수 추정이 어려운 경우 체계적인 분석을 위해 일반화 선형 모형은 임의효과가 포함된 일반화 선형 혼합 모형으로 확장되었다. 본 연구에서는 일반화 선형 모형 중에서도 이분적인 반응변수를 다루는 로지스틱 회귀모형에 임의효과를 포함한 최대 우도 추정 방법을 설명한다. 그중에서도 라플라스 근사법, 가우스-에르미트 구적법, 적응 가우스-에르미트 구적법 그리고 유사가능도 우도에 대한 최대우도 추정법을 자세히 알아본다. 또한 제안한 방법을 사용하여 한국 복지 패널 데이터에서 정신건강과 생활만족도가 자원봉사활동에 미치는 영향에 대해 분석한다.

• 농촌계획
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• 제24권1호
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• pp.61-66
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• 2018

The purpose of this study is to identify the factors related to the heavy rain damage and to identify effect of repair and improvement for irrigation facilities on heavy rain damages. The results of the analysis are as follows. First, the imbalance of precipitation became worse over time from using the coefficient of variation. Second, the analysis using Spearman correlation coefficient shows positive relationship between heavy rain damage amount and precipitation amount, and negative correlation between heavy rain damage amount and repair and improvement for irrigation facilities cost. Third, the analysis of the panel regression model shows that the negative impact of the repair and improvement for irrigation facilities cost on the heavy rain damage, which means that the increase of the repair and improvement for irrigation facilities cost can reduce the heavy rain damage.

• Communications for Statistical Applications and Methods
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• 제28권5호
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• pp.447-462
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• 2021

In insurance, the surrender rate is an important variable that threatens the sustainability of insurers and determines the profitability of the contract. Unlike other actuarial assumptions that determine the cash flow of an insurance contract, however, it is characterized by endogenous variables such as people's economic, social, and subjective decisions. Therefore, a microscopic approach is required to identify and analyze the factors that determine the lapse rate. Specifically, micro-level characteristics including the individual, demographic, microeconomic, and household characteristics of policyholders are necessary for the analysis. In this study, we select panel survey data of Korean Retirement Income Study (KReIS) with many diverse dimensions to determine which variables have a decisive effect on the lapse and apply the lasso regularized regression model to analyze it empirically. As the data contain many missing values, they are imputed using the random forest method. Among the household variables, we find that the non-existence of old dependents, the existence of young dependents, and employed family members increase the surrender rate. Among the individual variables, divorce, non-urban residential areas, apartment type of housing, non-ownership of homes, and bad relationship with siblings increase the lapse rate. Finally, among the financial variables, low income, low expenditure, the existence of children that incur child care expenditure, not expecting to bequest from spouse, not holding public health insurance, and expecting to benefit from a retirement pension increase the lapse rate. Some of these findings are consistent with those in the literature.

• 융합경영연구
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• 제7권2호
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• pp.1-5
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• 2019

Purpose - Along with the rise of foreign investments in the Korean stock market, there has been a variety of studies on their influence. The conflicting findings on the question of information asymmetry of foreign investors among existing literatures appear to be a result of mixture of research method problems, what information is defined as being comparable, individual business levels, or the entire stock market. This paper empirically investigates what factors contribute to foreign investments in firms in the Korean stock market. Research design, data, and Methodology - Samples are constructed by manufacturing firms listed on the stock market of Korea as well as those who settle accounts in December from 2001 to 2018. Financial institutions are excluded from the sample as their accounting procedures, governance and regulations differ. This study adopted the panel regression model to assess the sample construction including yearly and cross-sectional data. Result - This paper find that firms' R&D, dividends, size give significant positive impact to foreign investment, whereas debt gives significant negative impact to foreign investment. This relationship does not change when the samples are divided before and after the 2008 global financial crisis. Conclusion - This results support the literatures that foreign investors favor firms lowering their information asymmetry.

• 무역학회지
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• 제47권3호
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• pp.157-175
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• 2022

This study calculates agglomeration indices of manufacturing specialization and diversification in different regions of South Korea. Two types of agglomeration indices are introduced into the spatial durbin model (SDM) to analyzes the effects of manufacturing agglomeration in Korea on CO₂ emission intensity. The subjects of this study are 17 regions of South Korea , and the research period is from 2013 to 2019. This study also uses partial differential to analyze the direct and spillover effect of specialization and diversification agglomeration on CO₂ emission intensity. From the perspective of direct effect, the results reveal that specialization agglomeration is an important factor contributing to Korea's CO₂ emissions. However, diversification agglomeration has an obvious CO₂ emission reduction effect. From the perspective of spillover effect, this study finds that specialization agglomeration in one region can also contribute to CO₂ emissions in nearby regions. However, the development of diversification agglomeration in one region can have CO₂ emission reduction spillover effect on neighboring regions.

• Asian-Australasian Journal of Animal Sciences
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• 제8권5호
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• pp.505-513
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• 1995

The major factors affecting productivity on daily farms in Queensland, Australia, were determined using the stepwise linear regression approach. The data were obtained from a survey conducted on the total population of daily farms in Queensland in 1987. These data were divided into six major dailying regions. The technique was applied using 12 independent variables believed by a panel of experienced research and extension personnel to exert the most influence on milk production. The regression equations were all significant (p < 0.001) with the percentage coefficients of determination ranging from 62 to 76% for equations developed using' total farm milk: production as the dependent variable. Three of the variables affecting total farm milk: production were found to be common to all six regions. These were; the amount of supplementary energy fed, the area set aside to irrigate winter feed and the size of the area used for dailying. Higher production farms appeared to be more efficient in that they consistently produced milk production levels higher than those estimated from the regression equation for their region. Other methods of analysis including robust regression and non linear regression techniques were unsuccessful in overcoming this problem and allowing development of a model appropriate for farms at all levels of production.

• 디지털산업정보학회논문지
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• 제6권4호
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• pp.297-305
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• 2010

Employment number by areas is composed of various factors for groups and time series. In this paper, we use the panel data for finding various variables and using this, we analyzed the factors that is major influence to employment number by areas. For analysis we looked at employment number by areas, the region for analysis consist of seven groups, that is, the metropolitan city(such as Busan, Daegu, Incheon, Gwangiu, Daejeon, Ulsan.) and Seoul. Analyzing period be formed over a 63 time points(2005.01.- 2010.03). We examined the data in relation to the employment number by occupational job, unemployment rate, monthly household income, preceding business composite index, consumer price index, composite stock price index. In looking at the factors which determine employment number by areas job, evidence was produced supporting the hypothesis that there is a significant negative relationship between unemployment rate and monthly household income the consumer price index. The consumer price index and composite stock price index are significant positive relationship, preceding business composite index is positive relationship, it are not significant variables in terms of employment number by areas job.