• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.34-48
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• 2019

The purpose of this study was two-fold; first, to develop safety performance functions (SPF) using transportation-related big data for all types of roads in Korea were developed, Second, to provide basic information to develop measures for relatively dangerous roads by evaluating the safety grade for various roads based on it. The coordinates of traffic accident data are used to match roads across the country based on the national standard node and link system. As independent variables, this study effort uses link length, the number of traffic volume data from ViewT established by the Korea Transport Research Institute, and the number of dangerous driving behaviors based on the digital tachograph system installed on commercial vehicles. Based on the methodology and result of analysis used in this study, it is expected that the transportation safety improvement projects can be properly selected, and the effects can be clearly monitored and quantified.

• Journal of the Society of Disaster Information
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• v.14 no.4
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• pp.480-491
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• 2018

Purpose : This study aims to suggest social support composed of organizational support and managerial support would be systematically managed to enhance Disaster Operations Management at Seoul Emergency Operations Center. Method : Emotional labor was used as an independent variable, and organizational commitment was used as a dependent variable to analyze the mediating effects of social support. Results : First, in the aspect of organizational support, the objective evaluation of disaster situation management, disaster situation management emotional labor reduction education and training program development, monitoring of disaster situation management, quality improvement and work imbalance mitigation of firefighters, and emergency coordination managers are needed for systematic work management for emotional labor settlement. Secondly, it is necessary to select competent firefighters in the level of managerial support, to prepare healing measures for structured phased emotional labor for firefighters, and to have counseling competency for managers for emotional labor firefighting officers. Conclusion : In order to improve disaster management ability, education and training programs should be developed to improve organizational commitment based on social support.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.32 no.6
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• pp.251-261
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• 2022

This paper describes the finite element analysis and die design change of spring retainer forging process to reduce the cold forging load and plastic forming stress concentration. Plastic deformation analysis was carried out in order to understand the forming process of workpieces and elastic stress analysis of the die set was performed in order to get basic data for the die fatigue life estimation. Cold forging die design was set up to each process with different four types analysis progressing, the upper and lower dies shapes with combination of fillets and chamfers shapes of cold forging dies. This study suggested optimal cold forging die geometry to reduce cold forging load. The design parameters of fillets and chamfers are selected geometry were selected to apply optimization with the DoE (design of experiment) and Taguchi method. DoE and Taguchi method was performed to optimize the workpiece preform shape for spring retainer forging process, it was possible to expect an increase in cold forging die life due to the 20 percentage forging load reduction.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.147-155
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• 2022

In this study, we developed a system to dynamically balance a daily stock portfolio and performed trading simulations using gradient boosting and genetic algorithms. We collected various stock market data from stocks listed on the KOSPI and KOSDAQ markets, including investor-specific transaction data. Subsequently, we indexed the data as a preprocessing step, and used feature engineering to modify and generate variables for training. First, we experimentally compared the performance of three popular gradient boosting algorithms in terms of accuracy, precision, recall, and F1-score, including XGBoost, LightGBM, and CatBoost. Based on the results, in a second experiment, we used a LightGBM model trained on the collected data along with genetic algorithms to predict and select stocks with a high daily probability of profit. We also conducted simulations of trading during the period of the testing data to analyze the performance of the proposed approach compared with the KOSPI and KOSDAQ indices in terms of the CAGR (Compound Annual Growth Rate), MDD (Maximum Draw Down), Sharpe ratio, and volatility. The results showed that the proposed strategies outperformed those employed by the Korean stock market in terms of all performance metrics. Moreover, our proposed LightGBM model with a genetic algorithm exhibited competitive performance in predicting stock price movements.

• Journal of the Korean Society of Radiology
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• v.17 no.5
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• pp.751-759
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• 2023

Breast ultrasonography is difficult to image in fatty breasts and to find micro-calcification, but the discovery of micro-calcification is very important for breast cancer screening. Among the color Doppler artifact of ultrasound, twinkle artifact mainly occur on strong reflectors such as stones or calcification in images, and evaluation methods using them are clinically being used. In this study, we are conducting experiments on the color Doppler settings of ultrasound equipment, such as repetition frequency, ensemble, persist, wall filtering, smoothing, linear density, and dissociation value, by producing a breast simulation phantom using the largest amount of calcium phosphate among breast implants. The purpose of this study was to improve the contrast of twinkle artifact in breast ultrasound examinations and to maximize their use in clinical practice. As a result, the pulse repetition frequency occurred in the range of 3.6 kHz to 7.2 kHz, and did not occur above 10.5 kHz. For ensembles, twinkle artifact occurred in all sizes of calcification under low conditions, and in threshold settings, the twinkle artifact increased slightly only under 80 to 100 conditions, and did not occur in 1 mm size calcification. Persist, wall filter, smoothing, and line density settings did not have much meaning in the setting variable because conditions did not increase by condition, and pulse repetition frequency, ensemble, and thresholds had the greatest impact on the twinkling artifact image. This study is expected to help examiners select optimal conditions to effectively increase twinkle artifact by adjusting color Doppler settings.

• Information Systems Review
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• v.23 no.4
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• pp.1-22
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• 2021

In the newly encountered economy caused by the Corona virus Disease-19, remote transaction becomes a new normal that disrupt traditional economic order. In the middle of the disruption, mobile tech is placed and remote finance on mobile is highly noticed and considered as an infra-tech to support the new ecology, In mobile finance. remote payment is becoming the most common service and personal identification on it is critical to operate the new service. There are various means of remotely identifying a person. Recently the use of biometric information is increasing. In this study, a correlation analysis was conducted on factors that effects to biometrics usage and the intention to use in remote personal identification. Variables for critical factor in the remote identification were classified into 4 groups such as Performance expectancy, Effort expectancy, Social influence, and Security. The empirical analysis based on the Unified Theory of Acceptance and Use of Technology (UTAUT) was conducted. The relationship between variables and the intention to use is also analyzed. In the study, stepwise regression analysis was conducted four times in which variables were adjusted in individual stage. As a result, the analysis suggests that performance expectancy, effort expectancy, social influence, security have positive effects for intention to use. Additionally, effort expectancy and security have moderating effects to intention to use depends on biometric authentication experience. The analysis has shown positive effect of variables grouped on the intention to use them. It also suggests that the intention to use biometric authentication will quickly grow. This study is expected to make a contribution to utilize and improve the use of biometric information in mobile payment.

• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.274-280
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• 2024

Machine learning techniques utilizing neural networks have been employed in various fields such as disease gene discovery and diagnosis, drug development, and prediction of drug-induced liver injury. Disease features can be investigated by molecular information of DNA. In this study, we developed a neural network to predict the length of DNA and the number of DNA species in mixture solution which are representative molecular information of DNA. In order to address the time-consuming limitations of gel electrophoresis as conventional analysis, we analyzed the dynamic data of a microfluidic concentrating device. The dynamic data were reconstructed into a spatiotemporal map, which reduced the computational cost required for training and prediction. We employed a convolutional neural network to enhance the accuracy to analyze the spatiotemporal map. As a result, we successfully performed single DNA length prediction as single-variable regression, simultaneous prediction of multiple DNA lengths as multivariable regression, and prediction of the number of DNA species in mixture as binary classification. Additionally, based on the composition of training data, we proposed a solution to resolve the problem of prediction bias. By utilizing this study, it would be effectively performed that medical diagnosis using optical measurement such as liquid biopsy of cell-free DNA, cancer diagnosis, etc.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.5
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• pp.13-21
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• 2014

This study generated regression models to quantify storage and annual uptake of carbon from five native landscape tree species through a direct harvesting method, and established essential information to estimate carbon reduction effects from urban greenspaces. Tree species for the study included the Chionanthus retusus, Prunus armeniaca, Abies holophylla, Cornus officinalis, and Taxus cuspidata, which are usually planted in cities of middle Korea, but for which no information on carbon reduction is available. Ten tree individuals for each species were sampled reflecting various stem diameter sizes at a given interval. The study measured biomass for each part including the roots of sample trees to compute total carbon storage per tree. The annual carbon uptake per tree was quantified by analyzing the radial growth rates of stem samples at breast height or ground level. Regression models were developed using diameter at breast height (dbh) or ground level (dg) as an independent variable to easily estimate storage and annual uptake of carbon per tree for each species. All the regression models showed high fitness with $r^2$ values of 0.92~0.99. Storage and annual uptake of carbon from a tree with dbh of 10 cm were greatest with C. retusus (20.0 kg and 5.9 kg/yr, respectively), followed by P. armeniaca (17.5 kg and 4.5 kg/yr) and A. holophylla (13.2kg and 1.8 kg/yr) in order. A C. officinalis tree and T. cuspidata tree with dg of 10 cm stored 9.3 and 6.3 kg of carbon and annually sequestered 3.2 and 0.6 kg, respectively. The above-mentioned carbon storage equaled the amount of carbon emitted from gasoline consumption of about 23~35 L for C. retusus, P. armeniaca, and A. holophylla, and 11~16 L for C. officinalis and T. cuspidata. A tree with the diameter size of 10 cm annually offset carbon emissions from gasoline use of about 6~10 L for C. retusus, P. armeniaca, and C. officinalis, and 1~3 L for A. holophylla and T. cuspidata. The study breaks new ground to easily quantify biomass and carbon reduction for the tree species by overcoming difficulties in direct cutting and root digging of urban landscape trees.

• KDI Journal of Economic Policy
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• v.30 no.2
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• pp.185-223
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• 2008

This paper considers a heterogeneous agent dynamic general equilibrium model and analyzes effects of an increase in labor income tax rate on labor market and the aggregate variables in Korea. The fiscal policy regarding how the government uses the additional tax revenue may take the two forms: 1) general transfer and 2) earned income tax credit (EITC). The model features are as follows: 1) Workers are heterogeneous in their productivity. 2)Labor is indivisible, hence the analysis focuses on the variation in labor supply through the extensive margin in response to a change in fiscal policy. 3) The incomplete markets are introduced, so individual workers can not perfectly insure themselves against risks related to stochastic changes in income or employment status. 4) The model is of general equilibrium, hence it is equiped to analyze the feedback effect of changes in aggregate variables on individual workers' decisions. In the case of general transfer policy, the government equally distributes the additional tax revenue to all workers regardless of their employment states. Under this policy, an increase in the labor income tax rate dampens work incentives of individual workers so that the aggregate employment rate decreases by 1% compared with the benchmark economy. In the case of EITC policy, only employed workers whose labor incomes are below a certain EITC ceiling are eligible for the EITC benefits. Unlike the general transfer policy, the EITC induces low-income workers to participate the labor market to be eligible for EITC benefits. Hence, the aggregate employment rate may increase by 2.7% at the maximum. As the EITC ceiling increases, too many workers can collect the EITC but the benefits per worker becomes too little so that the increase in employment rate is negligible. By and large, this study demonstrates that EITC may effectively raise the aggregate employment rate, and that it can be a useful policy tool in response to the decrease in the labor force due to population aging as observed in Korea recently.

• Journal of the Korean Institute of Landscape Architecture
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• v.37 no.1
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• pp.18-27
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• 2009

The purpose of this study is to understand the scale of temperature change following large-scale urban developments in paddy fields to present possible measures to preserve suburban area paddy fields and to lower the scale of temperature increase after developing paddy fields in urban areas. The study was conducted in Bupyeong and Bucheon of Incheon Metropolitan City. The satellite image($1989{\sim}2000$) before and after the development of old paddy fields were used to analyze the land surface temperature changes according to the land use types. Building coverage, green coverage, non-permeable pavement coverage, and floor area ratio(FAR) were selected as the factors that influence urban temperature changes and the temperature estimation model was constructed by using correlation and regression analyses. The before and after satellite images of Bupyeong and Bucheon were classified into forests, greens and plantations, paddy fields, unused lands, and urban areas. The results indicate that most of the paddy fields that existed in the center of Bupyeong and Bucheon were converted into unused lands which were undergoing construction to become new urban areas. The difference between the surface temperatures of May 17th, 1989 and May 7th, 2000 was analyzed to reveal that most land converted from paddy fields to unused lands or urban areas saw an increase in surface temperature. Han River was used as a comparison to analyze the average surface temperature changes($1989{\sim}2000$) in former paddy fields. The scale of temperature changes were: $+1.6697^{\circ}C$ in urban parks; $+2.5503^{\circ}C$ in residential zones; $+2.9479^{\circ}C$ on public lands, $+3.0385^{\circ}C$ in commercial zones, and $+3.1803^{\circ}C$ in educational zones. The correlation between building coverage, green coverage, non-permeable pavement coverage, or floor area ratio(FAR) and surface temperature increases was also analyzed. The green coverage to temperature increases, but building coverage, non-permeable pavement coverage, and floor area ratio(FAR) had no statistically significant temperature increases. The factors that influence urban temperature changes were set up as independent variables and the surface temperature changes as dependent variables to construct a surface temperature change model for the land use types of former paddy fields. As a result of regression analysis, green coverage was selected as the most significant independent variable. According to regression analysis, if farmland is converted into an urban area, a temperature increase of $+3.889^{\circ}C$ is anticipated with 0% green coverage. The temperature saw a decrease of $-0.43^{\circ}C$ with every 10% increase of green coverage.