• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.3
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• pp.129-141
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• 2019

In recent years, fast growing cities in Korea are showing signs of being vulnerable to more disasters as their population and facilities increase and intensify. In particular, fire is one of the most common disasters in Korea's cities, along with traffic accidents. Therefore, in this study, we analyze what type of factors affect the fire that threatens urban people. Fire data were acquired for 10 years, from 2007 to 2017, in Jinju, Korea. Spatial distribution pattern of fire occurrence in Jinju was assessed through the spatial autocorrelation analysis. First, spatial autocorrelation analysis was carried out to grasp the spatial distribution pattern of fire occurrence in Jinju city. In addition, correlation and multiple regression analysis were used to confirm spatial dependency and abnormality among factors. Based on this, OLS (Ordinary Least Square) regression analysis was performed using space weighting considering fire location and spatial location of each facility. As a result, First, LISA (Local Indicator of Spatial Association) analysis of the occurrence of fire in Jinju shows that the most central commercial area are fire department, industrial area, and residential area. Second, the OLS regression model was analyzed by applying spatial weighting, focusing on the most derived factors of multiple regression analysis, by integrating population and social variables and physical variables. As a result, the second kind of neighborhood living facility showed the highest correlation with the fire occurrence, followed by the following in the order of single house, sales facility, first type of neighborhood living facility, and number of households. The results of this study are expected to be useful for analyzing the fire occurrence factors of each facility in urban areas and establishing fire safety measures.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.27 no.3
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• pp.98-105
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• 2019

In the past 30 years, our aviation demand has been growing continuously. As such, the importance of the demand forecasting field is increasing. In this study, the factors influencing Korea's international air demand were selected, and the international air demand was analyzed, forecasted and reviewed through OLS multiple regression analysis. As a result, passenger demand was affected by GDP per capita, oil price and exchange rate, while cargo demand was affected by GDP per capita and private consumption growth rate. In particular, passenger demand was analyzed to be sensitive to temporary external shocks, and cargo demand was more affected by economic variables than temporary external shocks. Demand forecasting, OLS multiple regression analysis, passenger demand, cargo demand, transient external shocks, economic variables.

• Journal of Korea Technology Innovation Society
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• v.15 no.3
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• pp.586-603
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• 2012

In order to relieve overcrowding, the Korean government has regulated firm's locations in the capital region of Korea. However, the standard of regulation mainly depends on the place of province. Using KIS-Value data of firms that are located Pyeong-taek(the Capital area) or Cheon-an(Non Capital area), in close proximity to each other, we utilize OLS and negative binomial regression models for identifying the difference of firms' management and innovation performance in terms of firms' location difference(regulation difference). Our analysis shows that innovation performance of firms in Cheon-an does better than Pyeong-taek's, but management performance has no gaps between them. This result indicates that the regulation of firm's location has influence on firm's innovation performance. Thus, regulation policy regarding firms' location need to be minutely amended.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.2
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• pp.106-110
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• 2021

In this study, the main factors affecting the number of passengers and cargo volume transported by air between Korea, China and Japan over the past 20 years are to be identified. For the analysis, data from three countries' GDP and per capita as well as exchange rates and international oil prices were used, and OLS multiple regression analysis and fixed effect analysis were performed. As a result of the analysis, both the number of passengers and cargo volume transported by air showed a negative (-) direction for GDP, which represents the country's economic power, and a positive (+) direction, for per capita GDP, which represents income level. And the increase in the exchange rate between China and Japan acted in a positive (+) direction on the increase in the number of passengers, and the effect of oil prices was found to be limited.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.29 no.3
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• pp.111-116
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• 2021

This study aims to identify the representative factors affecting the air trade between the two countries over the past 20 years, targeting China, Korea's largest trading partner for air transport. In the analysis, the two countries' GDP, GDP per capita, and tariff rates, as well as exchange rates, international oil prices, and FTAs were used as variables. For the analysis method, OLS multiple regression analysis was performed, and each was analyzed by dividing the export amount, import amount, and trade amount. As a result of the analysis, China's GDP and Korea's GDP per capita showed a positive (+) direction, an increase in the exchange rate resulted in an increase in the amount of trade, and an increase in the tariff rate resulted in a decrease in the amount of trade. Whether the FTA was concluded or not acted as a factor in increasing the amount of trade between the two countries.

• Journal of the Korean School Mathematics Society
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• v.19 no.2
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• pp.123-151
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• 2016

The purpose of this study is to analyze the existing studies about the effect on private tutoring and EBS broadcasting which is considered as the alternative which was presented by education authorities. And this study attempts to measure the degree of the effects of private tutoring and EBS engagement on mathematics achievement using various quantitative methodologies. T-test and OLS multiple regression indicates some selection-bias which has positive direction compared to the PSM method closed to experimental design. So, it will be required to consider the methodology which measures the exact effect of institution or participation when we conduct the observational studies.

• Korea journal of population studies
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• v.32 no.2
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• pp.115-140
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• 2009

이 연구는 외국인 노동자들의 한국문화에 대한 적응문제를 살펴 보기 위하여 그들이 한국인들에 대하여 가지고 있는 사회적 거리감(social distance)을 분석하고 있다. 사회적 거리감은 인종 간 상호 관계 연구에서 중요한 개념으로 다루어져 왔으며, 특히 사회적응 수준을 드러내는 효과적인 척도로 각광받아왔다. 이 연구는 한국내 외국인 노동자들의 한국인에 대한 사회적 거리감의 결정요인을 규명하려는 목적을 가지고 있다. 서울과 경기 지역에서 수집된 자료에 대한 다중회귀분석(OLS Regression)을 통하여, 이 연구는 서구 사회에서 다수 인종의 사회적 거리감을 효과적으로 설명하는 것으로 판명된 요인들이 한국의 소수 인종인 외국인노동자들에게도적용될수있는가를살펴본다. 구체적으로는 연령, 성, 교육, 종교, 인종과 같은 사회인구학적 변수들과 한국인과의 접촉정도 가사회적 거리감에 유의미한 효과가 있는지 분석된다. 둘째, 이 연구는 외국인 노동자들의 가장 중요한 삶의 공간인 작업장에서의 경험과 관련된 변수들이 사회적 거리감에 대하여 가지는 효과를 탐구한다. 셋째, 구조방정식 모형(Structural Equation Model)의 적용을 통하여, 이 연구는 다중회귀에서 분석된 여러 설명 변수들 간의 복잡한 인과구조를 규명하고, 이들이 사회적 거리감에 미치는 영향을 직접효과, 간접효과, 전체효과로 나누어 살펴본다. 다중회귀분석 결과는 집단 간 사회적 거리감은 사회인구학적 변수들, 한국인들과의 접촉, 작업장 내 경험등 다양한 요인들의 복합적인 결과물이라는 점을 확인해 준다. 특히 분석결과는 작업장에서의 경험과 느낌이 한국 내 외국인 노동자들의 한국인들에 대한사회적거리감형성에결정적이라는사실을보여주는반면, 기존연구에서 효과적인 것으로 판명된 전통적 요인들은 영향력이 미미하다는 점을 말해준다. 한편, 구조방정식 모형을 적용한 분석결과는 한국인 친구들과의 접촉과 이해하기 쉽고 구체적인 노동조건이 사회적 거리감에 직접적으로 영향을 주고 있다는 것을 보여 준다. 한편 추상적인 노동조건은 사회적 거리감에 간접적으로 영향을 미친다. 상사에 대한 평가와 직무만족은 노동조건에 의해 유의미한 영향을 받지만, 한국인 친구와의 접촉과는 관련이 없다. 간단히 말해, 상사에 대한 평가와 직무만족은 노동조건이 사회적거리감에 대하여 가지는 효과를 매개한다. 결론적으로, 구조방정식모형의 분석결과는 작업장 관련 변수들간에 복잡한 인과구조가 존재한다는 점과 작업장 내 경험이 한국인에 대한 사회적 거리감 형성에 가장 중요하다는점을 확인해 준다.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.218-236
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• 2023

This study attempted to analyze the environmental equity of fine dust(PM₁₀) in Daegu using MGWR(Multi-scale Geographically Weighted Regression) and KT(Korea Telecom Corporation) sensor data. Existing national monitoring network data for measuring fine dust are collected at a small number of ground-based stations that are sparsely distributed in a large area. To complement these drawbacks, KT sensor data with a large number of IoT(Internet of Things) stations densely distributed were used in this study. The MGWR model was used to deal with spatial heterogeneity and multi-scale contextual effects in the spatial relationships between fine dust concentration and socioeconomic variables. Results indicate that there existed an environmental inequity by land value and foreigner ratio in the spatial distribution of fine dust in Daegu metropolitan city. Also, the MGWR model showed better the explanatory power than Ordinary Least Square(OLS) and Geographically Weighted Regression(GWR) models in explaining the spatial relationships between the concentration of fine dust and socioeconomic variables. This study demonstrated the potential of KT sensor data as a supplement to the existing national monitoring network data for measuring fine dust.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1457-1469
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• 2017

Private education expenses is one of the key issues in Korea and there have been many discussions about it. Academically, most of previous researches for private education expenses have used multiple regression linear model based on ordinary least squares (OLS) method. However, if the data do not satisfy the basic assumptions of the OLS method such as the normality and homoscedasticity, there is a problem with the reliability of estimations of parameters. In this case, quantile regression model is preferred to OLS model since it does not depend on the assumptions of nonnormality and heteroscedasticity for the data. In the present study, the data from a survey on private education expenses, conducted by Statistics Korea in 2015 has been analyzed for investigation of the impacting factors for private education expenses. Since the data do not satisfy the OLS assumptions, quantile regression model has been employed in Bayesian approach by using gibbs sampling method. The analysis results show that the gender of the student, parent's age, and the time and cost of participating after school are not significant. Household income is positively significant in proportion to the same size for all levels (quantiles) of private education expenses. Spending on private education in Seoul is higher than other regions and the regional difference grows as private education expenditure increases. Total time for private education and student's achievement have positive effect on the lower quantiles than the higher quantiles. Education level of father is positively significant for midium-high quantiles only, but education level of mother is for all but low quantiles. Participating after school is positively significant for the lower quantiles but EBS textbook cost is positively significant for the higher quantiles.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.5
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• pp.105-111
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• 2004

This paper shows that active and reactive power load have significant positive relationship and there exist two types of relationship between them using Test Statistics. In investigating the cross plots at every hour, we found out that from 0 to 8 hours, there relationships are linear, while from 9 to 23 hours, they are two piece-wise linear. Also, reactive power loads was estimated and forecasted using active power load as the explanary variable with OLS (Ordinary Least Squares) regression methods. MAPE (Mean Absolute Percentage Error) for each model is calculated for one-hour ahead forecasting.