• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.794-807
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• 2021

The purpose of this study is to examine the effect of family poverty on the school adjustment of multi-cultural adolescents in Korea. For this purpose, the 7th data of Multi-cultural Adolescents Panel Study(MAPS) was used and the OLS multiple regression models ware applied. to the analyses. From the result of the OLS model analyses, we found out that family poverty affect significantly on the school adjustment of multi-cultural adolescents. Especially, family poverty has the significant negative(-) effects on academic achievement and friend relationships. These results of this study show that family poverty is an important factor influencing the school adjustment of multi-cultural adolescents. And they confirm that family poverty during period of the adolescent has an important meaning and influence on the aspect of school adjustment as to the multi-cultural adolescents. Implications of this study may be that policy attentions are necessary to not only multi-cultural characteristics but also family background such as poverty in oder to improve the school adjustment of the multi-cultural adolescents. In addition, results of this study suggest that more special support and interventions are requested to the multi-cultural adolescents from poverty families who are suffering dual difficulties such as multi-cultural problems and poverty problem.

• Journal of The Korean Digital Architecture Interior Association
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• v.13 no.4
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• pp.51-60
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• 2013

With regard to urban culture this study aims to essential understanding and systematic approach to the culture. The "2012 Seoul Survey" report has been used to find out causality among the related variables. In the first place 'satisfaction of cultural condition' was operationally selected as a dependent variable for regression. For the purpose of controlling the third factors for ceteris paribus effect correlation analysis was previously done between the dependent variable and all other variables respectively, which resulted in two groups of variables: group (1) - 2 variables of very significant correlations(p-value<0.01) and (2) - the other 6 variables of significant correlations(p-value<0.05). Then hierarchical regression was adopted to these 2 groups to analyse statistical significance of independent variables, and multicollinearity(VIF; variance inflation factor). Additionally to OLS robust and bootstrapping regressions were done to confirm the validity of this model specification. At last a regression model specified by group (1) as independent variables(they are 'community spirit caring for women, the disabled, the poor and the old,' 'satisfaction of bicycle riding condition' shows that the variables have statistically significant and substantially strong effect on 'satisfaction of cultural condition.' This finding implies the following understanding; (1) urban festivals are regarded as the main of the urban culture as of now and this results from the low level of today's culture, (2) culture is telling and hearing stories but the influential relationship between urban culture and community spirit on the weak is negative, which says that the cultural perception among citizen is somewhat selfish and far from the essential understanding of the urban culture. In spite of restrictive external validity this finding can be used as a direction for promoting culture and a basis for related policy choice in cities.

• Journal of Korea Water Resources Association
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• v.41 no.9
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• pp.943-958
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• 2008

This study employs Bayesian regression analysis for fitting discharge rating curves. The parameter estimates using the Bayesian regression analysis were compared to ordinary least square method using the t-distribution. In these comparisons, the mean values from the t-distribution and the Bayesian regression are not significantly different. However, the difference between upper and lower limits are remarkably reduced with the Bayesian regression. Therefore, from the point of view of uncertainty analysis, the Bayesian regression is more attractive than the conventional method based on a t-distribution because the data size at the site of interest is typically insufficient to estimate the parameters in rating curve. The merits and demerits of the two types of estimation methods are analyzed through the statistical simulation considering heteroscedasticity. The validation of the Bayesian regression is also performed using real stage-discharge data which were observed at 5 gauges on the Anyangcheon basin. Because the true parameters at 5 gauges are unknown, the quantitative accuracy of the Bayesian regression can not be assessed. However, it can be suggested that the uncertainty in rating curves at 5 gauges be reduced by Bayesian regression.

• The Journal of the Korea Contents Association
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• v.10 no.3
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• pp.315-325
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• 2010

The issues on education as a human capital formation in recent years have been focused for all of the countries with emerging of the knowledge-based economy. The present study compared and analyzed the relationships between the educational investment and national economic growth of ten non-English-speaking OECD countries during 1970-2008, using Ordinary Least Square (OLS) and Seemingly Unrelated Regression Estimation (SURE) as the main analytical methods. Findings indicate that educational investment, R&D investment, and fertility rate were statistically significant in the estimation of the variables related to the human capital formation, and these elements had also positive influence on the national economic growth. The most salient factor was the fertility rate, and the R&D investment and educational investment appeared as the next factors in the national economic growth. In particular, the dimensions in the coefficient of the fertility rate showed 1.8 times of the R&D and 3.5 times of the educational investment, respectively. These results imply that educational investment, R&D investment, and the policies which promote fertility rate should be taken into account for the continuous economic growth of each country.

• Journal of Cadastre & Land InformatiX
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• v.47 no.2
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• pp.19-37
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• 2017

Visible Infrared Imaging Radiometer Suite Day-Night Band (VIIRS-DNB) data provides a much higher capability for observing and quantifying nighttime light (NTL) brightness in comparison with Defense Meteorological Satellite-Operational Linescan System (DMSP-OLS) data. In South Korea, there is little research on the detection of NTL brightness change using VIIRS-DNB data. This study analyzed the spatial distribution and change of NTL brightness between 2013 and 2016 using VIIRS-DNB data, and detected its spatial relation with possible influencing factors using regression models. The intra-year seasonality of NTL brightness in 2016 was also studied by analyzing the deviation and change clusters, as well as the influencing factors. Results are as follows: 1) The higher value of NTL brightness in 2013 and 2016 is concentrated in Seoul and its surrounding cities, which positively correlated with population density and residential areas, economic land use, and other factors; 2) There is a decreasing trend of NTL brightness from 2013 to 2016, which is obvious in Seoul, with the change of population density and area of industrial buildings as the main influencing factors; 3) Areas in Seoul, and some surrounding areas have high deviation of the intra-year NTL brightness, and 71% of the total areas have their highest NTL brightness in January, February, October, November and December; and 4) Change of NTL brightness between summer and winter demonstrated a significantly positive relation with snow cover area change, and a slightly and significantly negative relation with albedo change.

• Journal of Korean Society of Transportation
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• v.32 no.6
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• pp.638-650
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• 2014

The objective of this study is to identify the causes of pedestrian volume path to the destination by investigating the influential levels of regional and planning features in the central area of Seoul. Regional characteristics can be classified from the result of the analysis and through the spatial characteristics of pedestrian volume. For global scale analysis, Ordinary Least Squares (OLS) regression is used for the degree of influence of each characteristics to pedestrian volume. For the local scale, Geographically Weighted Regression (GWR) is used to identify regional influential factors with consideration for spatial differences. The results of OLS indicate that boroughs with transportation facilities, commercial business districts, universities, and planning features with education research facilities and planning facilities have a positive effect on pedestrian volume path to the destination. Correspondingly, transportation hubs and congested areas, commercial and business centers, and university towns and research facilities in the Seoul central area can be identified through the results of GWR. The results of this study can provide information with relevance to existing plans and policies about the importance of regional characteristics and spatial heterogeneity effects on pedestrian volume, as well as significance in the establishment of regional development plans.

• Korean Journal of Social Welfare
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• v.66 no.1
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• pp.251-276
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• 2014

This study scrutinizes the common sense in the field of disability employment that the bigger the size of a firm, the lower the employment rate of people with disabilities. This common sense has been established by conventional cross-tabulation and multiple regression analyses without taking into account possible interactions between the sizes of firms and the industries in which they operate. This study shows that the distribution of the disability employment rate violates the linearity and homoscedasticity assumptions of the OLS. In an effort to find models that explain the data better, this study fits the OLS model, the weighted linear regression model, and the multinomial logit model as well as the path analysis which is meant to examine the relationships between firm size and other variables relevant to disability employment. The result shows that, when an interaction term between firm size and industry is added to the model, firm size does not have any significant effect on disability employment rate for those firms with 100 or more regular employees, to the contrary of the findings of prior studies. It also demonstrates that other factors such as job setting, the extent of helpfulness of disability employment employers perceive, employers' care for disability, and employers' awareness of disability policies may matter more than does firm size. This study proposes that future research and policy implementation for disability employment should pay no less attention to industry and other factors mentioned above than to firm size.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.1
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• pp.49-56
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• 2019

Urban green spaces have been contributing to the improvement of environmental, mental, and physical health for humans. In addition, recent studies showed the potential role of vegetation in reducing the amount of crime in inner-city neighborhoods at the micro-scale level. However, little is known about the positive role of urban green areas in improving urban safety at the regional level. The purpose of this study is to examine the relationship between urban green areas and actual outdoor crime rates, while also considering socio-demographic factors. The study area is the city of Austin, Texas, USA, which consists of 506 block groups. This study utilized socio-demographic factors based on U.S. Census data and vegetation-related factors utilizing GIS and ENVI software. For analyses, the analysis of variance (ANOVA) and an ordinary least square (OLS) regression were utilized. The results from ANOVA showed that yearly crime rates per acre for areas having 0%~25% trees in their neighborhoods were 0.46% and 1.05% higher than those of having 25%~50% and >50% trees in the neighborhoods, respectively. The results from the OLS regression represented that income, NDVI and park rates in neighborhoods were negatively associated with the crime rate per acre, whereas the percentage of minorities and the percentage of teenage school dropouts were positively associated with the crime rate per acre. This study implies that urban green areas may help to improve the safety of urban areas.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.123-132
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• 2014

Inflation uncertainty is known to have deleterious effects on facilities investment by disturbing the corporate decision on the opportunity cost of investment. In this paper, we test the validity of this hypothesis in Korea by estimating the inflation uncertainty with both a time-varing parameter model with GARCH disturbances and the relative price volatility and then, estimate the facilities investment equation which includes those uncertainty indicators. The uncertainty indexes estimated by the above-mentioned methods continue to fluctuate even after the inflation rate has dropped dramatically reflecting the structural changes of Korea's economy since the financial crisis in 1997. As a result of estimation of the investment equation by both OLS and GMM, we find the inflation uncertainty has a negative effect on facilities investment with a statistical significance. Moreover, by means of Markov-switching regression model utilized to verify the non-linearity of this relationship, we draw a conclusion that this negative effect of inflation uncertainty heightens asymmetrically during the downturn periods of business cycle.

• Health Policy and Management
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• v.25 no.3
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• pp.240-251
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• 2015

Background: Dentist's income is quite variable. We investigate the factors underlying the distribution of dental revenue and dentist income. Methods: Financial and structural variables of private dental practices(N=13,967) were examined with 2010 Economic Census microdata which include non-insurance revenue. We conducted quantile regression method(QRM) and ordinary least square(OLS) in treating skewness and heteroskedasticity of distributions. The effective estimation for the upper and lower range of distribution becomes possible by QRM. Results: Mid-career dentists are shown to have higher revenue and income. Male dentists achieve the higher revenue and income than female dentists in all quantiles. Group practices show lower income per owner than solo practices significantly. The revenue and income are increased with increasing size of clinics. The high cost in renting the clinic office is found to have a big positive effect on the revenue but a little positive effect on the income. Interestingly the density of dentists shows negative effect on the lowest quantile of the revenue but positive effect on the highest quantile. The lowest quantile of the revenue in the capital areas have the relatively high revenue. The lowest quantile of the income in metropolitan city show higher income than those in other areas significantly. Conclusion: The suggested QRM is shown to have more effective and efficient tool in finding out determinants of dentists' revenue and income of our concern. The results of this study are expected to be employed for dentists preparing for the opening practices in their organizational settings and locational selections. The distributional efficiency of dental human resources could be accomplished if policy makers guide dentists with this knowledge.