• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.2
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• pp.361-367
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• 2019

Ramp metering is a traffic management technique that reduces the congestion of Expressway by controlling vehicles entering the highway. It is widely used outside the country, and Korea is also operating in seven sites (Seoul Ring Expressway). Ramp metering has the advantage of reducing congestion of Expressway, but there are disadvantages, as queuing occurs because vehicles are waiting for ramp, and the ramp queue affects adjacent roads at rush hour. To solve this problem, we improved the ramp metering algorithm to reduce the metering rate more spaces on ramp and to increase the metering rate less spaces. In order to evaluate this, the combined evaluation index was used and it was found that the result satisfied the equity and efficiency at the same time.

• Journal of Digital Convergence
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• v.17 no.1
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• pp.55-62
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• 2019

This study analyzed the relationship between housing price, purchase price, Gini coefficient, interest rate, and the employment, considering that the change in housing price was an important factor influencing macroeconomic variables and income inequality. The panel VAR model was constructed considering the panel data, and the Granger causality, Impulse response and Variance dispersion analysis were performed. As a result, when compared to before and after the global financial crisis, it was shown that the rent price had an effect on income inequality, but in the following period, both the rent price and the selling price affected the income inequality. And that it has a large impact on inequality. In addition, the causality between income inequality and employment rate, interest rate, and tax rate was confirmed. Therefore, it is expected that it will be a desirable policy to mitigate income inequality considering the influence of policy variables for economic activation including government real estate policy.

• The Journal of Korean Society for School & Community Health Education
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• v.20 no.1
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• pp.69-84
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• 2019

Objectives: The purpose of this study is to examine change in adolescent depression across time and to determine the relation between individual and neighborhood socioeconomic status (SES) and depression. Methods: This study employed multilevel latent growth analysis using longitudinal data from Korea Children and Youth Panel Survey. A sample of this study consists of 2,351 adolescents who were in first grade of middle school in 2010. Results: Results showed that both initial level and downward trajectory of depression varied significantly across individuals as well as across neighborhoods. On the individual level, self-rated economic condition(b=-0.203, p<.001) was related to the initial level of depression. Adolescents whose father had a high educational level(b=0.028, p<.001) or whose mother had a low educational level(b=-0.022, p=.011) had lower rates of decline in adolescent depression. On the neighborhood level, neighborhood deprivation index (b=0.003, p=.019) and gini coefficient(b=0.124, p=.040) were associated with lower rates of decline in depression. Conclusions: Low SES in adolescence is correlated with worse mental health, especially depression. Social disparities in depression likely originate before adulthood. The findings argue for the importance of understanding depression in adolescence from a multilevel or ecological framework.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.295-303
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• 2021

The relevance of the research is due to the fact that the issue of poverty is one of the most acute social problems of the beginning of the third millennium. The phenomenon of poverty is widespread in third world countries as well as it is observed in relatively developed countries. Poverty rates in Latin America are threatening. Consequently, the issue of social and economic inequality in these countries has become extremely acute. The purpose of the research: to identify the causes of poverty and social inequality and substantiate the main directions of poverty reduction in third world countries. The research methods: comparative analysis; index method; systematization; grouping; generalization. Results. The classification of the causes of poverty has been carried out and the directions of its overcoming in the countries of Latin America on groups of indicators have been defined, namely: 1) political; 2) economic; 3) demographic; 4) regional-geographical; 5) social; 6) qualification; 7) personal. Based on the Net Domestic Product indicator, a comparison of economic indicators of the studied countries has been carried out. It has been revealed that from 1990 to 2018 income inequality increased in 52 of 119 countries studied, and decreased in 57 states. Inequality has increased in the world's most populous countries, particularly China and India. In general, countries with growing inequality are home to more than two-thirds (71%) of the world's population. Trends in the distribution of income in the world have been investigated by applying the Gini index, the high level of which is observed in Latin America (Colombia 48,9%, Panama 46,1%, Chile and Mexico 45,9%). The forecast of the impact of the Covid-19 pandemic on this issue has been outlined; the ways of its impact on the economies of the countries have been studied. As a result of the study, the main directions and mechanisms of the strategy for poverty reduction and social inequality in the third world countries have been identified. The implementation of the poverty reduction strategy presented in this academic paper may have a positive impact on the economic situation of the population of Latin American countries.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.711-721
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• 2021

In this paper, we propose the method of adjusting thresholds using impurity indices in classification analysis on imbalanced data. Suppose the minority category is Positive and the majority category is Negative for the imbalanced binomial data. When categories are determined based on the commonly used 0.5 basis, the specificity tends to be high in unbalanced data while the sensitivity is relatively low. Increasing sensitivity is important when proper classification of objects in minority categories is relatively important. We explore how to increase sensitivity through adjusting thresholds. Existing studies have adjusted thresholds based on measures such as G-Mean and F1-score, but in this paper, we propose a method to select optimal thresholds using the chi-square statistic of CHAID, the Gini index of CART, and the entropy of C4.5. We also introduce how to get a possible unique value when multiple optimal thresholds are obtained. Empirical analysis shows what improvements have been made compared to the results based on 0.5 through classification performance metrics.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.2
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• pp.64-77
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• 2021

The purpose of this study is to examine the spatial distribution of highly educated human capital and to identify key factors affecting their spatial distribution. We analyzed the spatial concentration and inequality using Gini's coefficient and exploratory spatial data analysis and identified the economic and amenity factors to affect the spatial concentration of highly educated human capital using spatial regression model. The findings show that the spatial pattern of highly educated human capital is concentrated, imbalanced, and clustered in Capital region and part of Chungcheong and Gangwon region. The spatial concentration were more affected by economic factor than by amenity factors. This study provides some implication on the regional economic strategies to attract the human capital.

• Physical Therapy Korea
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• v.30 no.2
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• pp.102-109
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• 2023

Background: While efforts have been made to differentiate fall risk in older adults using wearable devices and clinical methodologies, technologies are still infancy. We applied a decision tree (DT) algorithm using inertial measurement unit (IMU) sensor data and clinical measurements to generate high performance classification models of fall risk of older adults. Objects: This study aims to develop a classification model of fall risk using IMU data and clinical measurements in older adults. Methods: Twenty-six older adults were assessed and categorized into high and low fall risk groups. IMU sensor data were obtained while walking from each group, and features were extracted to be used for a DT algorithm with the Gini index (DT1) and the Entropy index (DT2), which generated classification models to differentiate high and low fall risk groups. Model's performance was compared and presented with accuracy, sensitivity, and specificity. Results: Accuracy, sensitivity and specificity were 77.8%, 80.0%, and 66.7%, respectively, for DT1; and 72.2%, 91.7%, and 33.3%, respectively, for DT2. Conclusion: Our results suggest that the fall risk classification using IMU sensor data obtained during gait has potentials to be developed for practical use. Different machine learning techniques involving larger data set should be warranted for future research and development.

• Korean Journal of Social Welfare Studies
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• v.41 no.3
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• pp.185-212
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• 2010

This study simulates the effects of basic income on income redistribution in Korea, and compares the redistribution effects of basic income models with the effect of the current welfare system. Using the Korea Welfare Panel Study(2008), absolute/relative poverty rate, poverty gap ratio, gini coefficients are measured. As a result of simulation, the basic income models reduced poverty more effectively than the current system. And among the three basic income models, the basic income model combined with flat-rate tax reduced poverty more effectively. And the basic income model combined with progressive tax reduced inequality more effectively. The results of the study reported in this paper confirm the paradox of redistribution which suggest that the effect of universal welfare program on redistribution is the most noticeable.

• Korean Journal of Social Welfare Studies
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• v.40 no.1
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• pp.261-296
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• 2009

I constructed the 2003 Korean 'social accounting matrix'(SAM) to analyze the multipliers of total demand for each economic activity. I find that the relative magnitude of the influence of the welfare policy to the national economy measured by input-output production multipliers tends to be underestimated compared to SAM multipliers. This is because the total demand multipliers of SAM include the private sector effects, which is not considered in the input-output model. The result also support that income inflows in public service areas including education, health and social work, generate gains in the relative income of households.

• Journal of the Economic Geographical Society of Korea
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• v.26 no.3
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• pp.310-323
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• 2023

Urbanization and income distribution issues are global interest, and the results of studies on the impact of urbanization on income inequality are different for each country and period. This study analyzes the impact of urbanization on income inequality using regional data from 2000-2021. In particular, serial correlation, spatial dependence, and common factor effects of the Gini coefficient are confirmed and analyzed through a dynamic spatial panel regression model. As a result, urbanization has a positive effect on reducing income inequality. Therefore, it is necessary to continuously promote regional urbanization to improve the income distribution problem. Areas with already high urbanization rates should reduce income inequality by narrowing the wage gap by expanding training opportunities for low-skilled workers, and need to come up with measures to prevent counter-urbanization.