• Journal of the Economic Geographical Society of Korea
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• v.17 no.2
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• pp.402-419
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• 2014

This study attempts to investigate the spatial characteristics of private tutoring markets for adults which have been expanded rapidly with labor market changes in Korea. In particular, For the purpose, we examine thoroughly various indies of labor markets and private tutoring markets for adults in Korea in first and then analyze the spatial characteristics. We classify private tutoring institutes for adults into two categories by job-statuses and education levels, and analyze the spatial distribution patterns of the attendants of the classes. In order to understand the spatial characteristic of their distributions, we distinguish whether there exist the spatial autocorrelation or not by applying Moran's I values for each categories in first. We also examine the spatial cluster patterns by Hot spots analysis utilizing $G^*$ statistics. Multiple linear regression models are developed for each category to explain the relationships between the spatial distributions of private tutoring institutes and geographical variables.

• Journal of Korea Water Resources Association
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• v.42 no.6
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• pp.465-480
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• 2009

In this study, single and multiple linear regression model were used to derive the relationship between precipitation and altitude, latitude and longitude in Jejudo. The single linear regression analysis was focused on whether orographic effect was existed in Jejudo by annual average precipitation, and the multiple linear regression analysis on whether orographic effect was applied to each duration and return period of quantile from regional frequency analysis by index flood method. As results of the regression analysis, it shows the relationship between altitude and precipitation strongly form a linear relationship as the length of duration and return period increase. The multiple linear regression precipitation estimates(which used altitude, latitude, and longitude information) were found to be more reasonable than estimates obtained using altitude only or altitude-latitude and altitude-longitude. Especially, as results of spatial distribution analysis by kriging method using GIS, it also provides realistic estimates for precipitation that the precipitation was occurred the southeast region as real climate of Jejudo. However, the accuracy of regression model was decrease which derived a short duration of precipitation or estimated high region precipitation even had long duration. Consequently the other factor caused orographic effect would be needed to estimate precipitation to improve accuracy.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.512-512
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• 2015

시 공간적 관측에서 다양한 원인에 의해 강우 자료에 결측이나 오측이 발생할 수 있다. 강우를 측정하고 자료를 수집 관리하는 측면에서 결측 되거나 오측된 자료를 추정 보완할 필요가 있다. 현재까지 결측 강우 자료를 추정하기 위한 방법으로 결측 지점 인근의 관측소를 이용한 단순 가중 평균치 방법에서부터 복잡한 통계적 기반의 보간 방법에 이르기까지 많은 연구들이 진행되고있다. 본 연구에서는 결측 된 강우 자료를 추정하기 위해 인공 신경망을 이용하여 모형을 구축하고 주변 관측소의 강우자료를 이용해 신경망 학습을 실시하여 적용해 보았으며, 최근 관측의 단위가 짧아지고 있는 점을 고려하여 10분, 30분, 1시간 등 다양한 시간간격의 강우자료를 구축하고 선형회귀모형과 RDS 방법, 신경망 모형을 이용한 방법 등을 적용한 결과를 비교하여 신경망 모형의 적용성을 살펴보았다. 단순한 구조면에서는 기존의 RDS 방법에 대한 적용성이 높은 것으로 판단되었으나, 성능의 개선을 위한 별다른 방법이 없는 반면 신경망 모형은 입력 자료를 다양하게 변환하여 구성하는 경우 성능을 개선하여 적용성이 더 높아 질 수 있는 것으로 판단되었다. 향후 신경망 모형을 이용해 잘못 측정된 강우를 적절히 선별하고 결측된 보완함으로써 관측된 강우 자료의 활용성을 높일 수 있을 것이다.

• 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 Korea Water Resources Association
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• v.53 no.2
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• pp.121-129
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• 2020

The increase of impervious surface and development along the river due to urbanization not only causes an increase in the number of associated flood risk factors but also exacerbates flood damage, leading to difficulties in flood management. Flood control measures should be prioritized based on various geographical information in urban areas. In this study, a probabilistic flood hazard assessment was applied to flood-prone areas near an urban river. Flood hazard maps were alternatively considered and used to describe the expected inundation areas for a given set of predictors such as elevation, slope, runoff curve number, and distance to river. This study proposes a Bayesian logistic regression-based flood risk model that aims to provide a probabilistic risk metric such as population-at-risk (PAR). Finally, the logistic regression model demonstrates the probabilistic flood hazard maps for the entire area.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.3
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• pp.1-12
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• 2016

This study aimed to interpret the fundamental cause of road-kill occurrences and analyzed spatial characteristics of the road-kill locations from Route 44 in Seorak National Park, Korea. Logistic regression analysis was utilized for backward elimination on variables. Seorak National Park Service has constructed GIS-data of 81 road-kill occurrences from 2008 to 2013 and these data were assigned as dependent variables in this study. Considered as independent variables from previous studies and field surveys, vegetation age-class, distance to streams, coverage of fences and retaining walls, and distance to building sites were assigned as road-kill impact factors. The coverage of fences and retaining walls(-1.0135) was shown as the most influential factor whereas vegetation age-class(0.0001) was the least influential among all of the significant factor estimates. Accordingly, the rate of road-kill occurrence can increase as the distance to building sites and stream becomes closer and vegetation age-class becomes higher. The predictive accuracy of road-kill occurrence was shown to be 72.2% as a result of analysis, assuming as partial causes of road-kill occurrences reflecting spatial characteristics. This study can be regarded as beneficial to provide objective basis for spatial decision making including road-kill occurrence mitigation policies and plans in the future.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3B
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• pp.279-289
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• 2006

The reconstruction of low dimension nonlinear behavior from the hydrologic time series has been an active area of research in the last decade. In this study, we present the applications of a powerful state space reconstruction methodology using the method of Support Vector Machines (SVM) to the Great Salt Lake (GSL) volume. SVMs are machine learning systems that use a hypothesis space of linear functions in a Kernel induced higher dimensional feature space. SVMs are optimized by minimizing a bound on a generalized error (risk) measure, rather than just the mean square error over a training set. The utility of this SVM regression approach is demonstrated through applications to the short term forecasts of the biweekly GSL volume. The SVM based reconstruction is used to develop time series forecasts for multiple lead times ranging from the period of two weeks to several months. The reliability of the algorithm in learning and forecasting the dynamics is tested using split sample sensitivity analyses, with a particular interest in forecasting extreme states. Unlike previously reported methodologies, SVMs are able to extract the dynamics using only a few past observed data points (Support Vectors, SV) out of the training examples. Considering statistical measures, the prediction model based on SVM demonstrated encouraging and promising results in a short-term prediction. Thus, the SVM method presented in this study suggests a competitive methodology for the forecast of hydrologic time series.

• Korea Real Estate Review
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• v.28 no.4
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• pp.37-51
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• 2018

The purpose of this paper is to analyze the effects of location factors on sales by restaurant type in the six districts of Seoul (Jongno-gu, Jung-gu, Yeongdeungpo-gu, Gangnam-gu, Seocho-gu, and Songpa-gu). Ordinary least squares (OLS) regression model is selected for four restaurant types whose spatial autocorrelation is not identified, spatial lag model (SLM) is only selected for seafood restaurant, and spatial error model (SEM) is selected for nine other restaurant types. The floating population and the workers of surrounding businesses have generally positive effects on the sales of restaurants. The floating population elasticity of the sales of restaurants are found to be in the descending order of Oriental food, pub, Western food, and traditional food restaurant, and the elasticity of the workers of surrounding businesses are in the descending order of bakery, Oriental food, and Western food restaurant. The spatial multiplier effects are in the descending order of Oriental food, pub, and Western food restaurant. There is a statistically significant sales gap between roast meat, pub, and bakery in Gangnam-gu and those in five other districts. The results of this research can help in starting a restaurant in that they can provide information on the suitability of location by restaurant type.

• Land and Housing Review
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• v.13 no.1
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• pp.1-9
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• 2022

In 1991, the United Nations World Tourism Organization (UNWTO) declared "tourism accessible for all" recommending the practice of the right to enjoy tourism. According to the Ministry of Health and Welfare of Korea (2019), the disabled, who are the most vulnerable in tourism, accounted for 5.1% of the total population, and the number of the elderly over 65 is expected to increase to 20.3% by 2025. In particular, the need for customized policies has been raised as the proportion of disabled people among the elderly aged 65 and over continues to increase. Thus, this study identified the spatial characteristics of Universal Design (UD) tourist destinations considering the tourism vulnerable groups. Administrative units (425 dongs) in Seoul were used as spatial units for analysis. As a research method, first, a spatial model was specified through LM verification, and then spatial regression analysis was performed. As a result of the analysis, the spatial characteristics of UD tourist destinations were found to have positive (+) effects on the number of universally certified businesses, the number of restaurants, and the number of bus stops that were available to the vulnerable. It was confirmed that there are a large number of universal certified businesses, restaurants, and bus stops in dongs with UD tourist destinations. The findings will provide policy implications when promoting the right to enjoy tourism in the future and improving Korean universal design quality.

• Journal of Korean Society of Rural Planning
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• v.23 no.3
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• pp.13-20
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• 2017

본 연구는 가나의 비료 보조금 정책(Fertilizer subsidy program: FSP)의 농업 생산성에 대한 영향을 분석하였다. 가나의 군(district) 지역 수준의 농업 생산량 및 투입요소에 대한 자료를 사용하여, FSP 도입 이전과 FSP 도입 이후의 농업 생산성을 계측하였다. 지역적으로 상이한 수준의 농업 생산성을 반영하기 위한 지리적가중회귀(GWR)모형을 사용하여 계측의 오류를 줄이고 공간이질성을 고려하였다. 추정 결과를 바탕으로 ArcMap을 이용하여 생산성을 지도로 시각화 한 자료를 살펴보면, FSP 도입 이후 농업 생산성이 전반적으로 개선되었으며 그 중에서도 생산성이 크게 향상된 지역을 특정할 수 있다. 이러한 공간적 변화는 FSP의 지역적 할당의 효율성 증진을 위한 의사결정 자료로 이용 가능하며, 국내 ODA 추진기관에서 농업 지도 및 지원을 위해 유용한 정보로 사용할 수 있다.