• 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.

• KDI Journal of Economic Policy
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• v.39 no.2
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• pp.25-51
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• 2017

This paper employs an Overlapping Generations Model to quantify the impacts of Korea's demographic transition toward an older population on the total output growth rate. The model incorporates the projected population through 2060 according by Statistics Korea. The effects of the low fertility and increased life expectancy rates are studied. The model is considered suitable for analyzing the effects of demographic changes on the Korean economy. Under the assumption that the TFP growth rate will not slow considerably in the future, remaining at 1.3% per annum, the gross output growth rate of the Korean economy is projected to slow to 1.1% per annum in the 2050s, from 4.0% in the 2000s. The shrinking workforce due to the decline in fertility plays a significant role in the deceleration of the Korean economy. The increased life expectancy rate is expected to mitigate the negative effect, but the magnitude of its effect is found to be limited.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.212-220
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• 2024

When a typhoon or natural disaster occurs, a significant number of orchard fruits fall. This has a great impact on the income of farmers. In this paper, we introduce an AI-based method to enhance low-quality raw images. Specifically, we focus on apple images, which are being used as AI training data. In this paper, we utilize both a basic program and an artificial intelligence model to conduct a general image process that determines the number of apples in an apple tree image. Our objective is to evaluate high and low performance based on the close proximity of the result to the actual number. The artificial intelligence models utilized in this study include the Convolutional Neural Network (CNN), VGG16, and RandomForest models, as well as a model utilizing traditional image processing techniques. The study found that 49 red apple fruits out of a total of 87 were identified in the apple tree image, resulting in a 62% hit rate after the general image process. The VGG16 model identified 61, corresponding to 88%, while the RandomForest model identified 32, corresponding to 83%. The CNN model identified 54, resulting in a 95% confirmation rate. Therefore, we aim to select an artificial intelligence model with outstanding performance and use a real-time object separation method employing artificial function and image processing techniques to identify orchard fruits. This application can notably enhance the income and convenience of orchard farmers.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.37-42
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• 1997

Off-line feed rate scheduling is an advanced methodology to automatically determine optimum feed rates for the optimization of NC code. However, the present feed rate scheduling systems have lim~tations to generate the optimized NC codes because they use the material removal rate or non-generalized cutting force model. In this paper, a feed rate scheduling system based on an improved cutting force model that can predrct cutting forces exactly in general machining was presented. Original blocks of NC code were divided to small ones with the modified feed rates to adjust the peak value of cutting forces to a constant vale. The characteristic of acceleration and deceleration for a given machrne tool was considered when off-line feed rate scheduhng was performed. Software for the NC code optimization was developed and applied to pocket machining simulation.

• Journal of Radiation Protection and Research
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• v.34 no.4
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• pp.155-164
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• 2009

In this paper, we used computerized glow curve deconvolution (CGCD) software with several models for the simulation of a TL glow curve which was used for analysis. By using the general approximation plus model, parameters values of the glow curve were analyzed and compared with the other models parameters (general approximation, mixed order kinetics, general order kinetics). The LiF:Mg,Cu,Si and the LiF:Mg,Cu,P material were used for the glow curve analysis. And we based on figure of merits (FOM) which was the goodness of the fitting that was monitored through the value between analysis model and TLD materials. The ideal value of FOM is 0 which represents a perfect fit. The main glow peak makes the most effect of radiation dose assessment of TLD materials. The main peak of the LiF:Mg,Cu,Si materials has a intensity rate 80.76% of the whole TL glow intensity, and that of LiF:Mg,Cu,P materials has a intensity rate 68.07% of the whole TL glow intensity. The activation energy of LiF:Mg,Cu,Si was analyzed as 2.39 eV by result of the general approximation plus(GAP) model. In the case of mixed order kinetics (MOK), the activation energy was analyzed as 2.29 eV. The activation energy was analyzed as 2.38 eV by the general order kinetics (GOK) model. In the case of LiF:Mg,Cu,P TLD, the activation energy was analyzed as 2.39 eV by result of the GAP model. In the case of MOK, the activation energy was analyzed as 2.55 eV. The activation energy was analyzed as 2.51 eV by the GOK model. The R value means different ratio of retrapping-recombination. The R value of LiF:Mg,Cu,Si TLD main peak analyzed as $1.12\times10^{-6}$ and $\alpha$ value analyzed as $1.0\times10^{-3}$. The R of LiF:Mg,Cu,P TLD analyzed as $7.91\times10^{-4}$, the $\alpha$ value means different ratio of initial thermally trapped electron density-initial trapped electron density (include thermally disconnected trap electrons density). The $\alpha$ value was analyzed as $9.17\times10^{-1}$ which was the difference from LiF:Mg,Cu,Si TLD. The deep trap electron density of LiF:Mg,Cu,Si was higher than the deep trap electron density of LiF:Mg,Cu,P.

• Nuclear Engineering and Technology
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• v.29 no.2
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• pp.99-109
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• 1997

A dynamic model for hydrogen generation by Fuel-Coolant Interactions(FCI) is developed with separate models for each FCI stage, coarse mixing and stratification. The model includes the physical concept of FCI, semi-empirical heat and mass transfer correlation and the concentration diffusion equation with the general non-zero boundary condition. The calculated amount of hydrogen, which is mainly generated in stratification, is compared with the FITS experiments. The model developed in this study shows a good agreement within a range of 10 % fuel oxidation rate and predicts the controlled mechanism of the chemical reaction very well. And this model predicts more accurately than the previous works. It is shown from the sensitivity study that the higher initial temperature of fuel particle is, the larger the reaction rate is. Up to 2700 K of temperature of the particle, the reaction rate increases rapid, which can lead to metal ignition.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.3
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• pp.49-57
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• 2010

We extended a general attack tree to apply cyber attack model for network vulnerability analysis. We defined an extended cyber attack tree (E-CAT) which extends the general attack tree by associating each node of the tree with a transition of attack that could have contributed to the cyber attack. The E-CAT resolved the limitation that a general attack tree can not express complex and sophisticate attacks. Firstly, the Boolean expression can simply express attack scenario with symbols and codes. Secondary, An Attack Generation Probability is used to select attack method in an attack tree. A CONDITION-composition can express new and modified attack transition which a aeneral attack tree can not express. The E-CAT is possible to have attack's flexibility and improve attack success rate when it is applied to cyber attack model.

• Journal of the Korea Safety Management & Science
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• v.2 no.2
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• pp.71-83
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• 2000

This paper presents accelerated life tests for Type I censoring data under probabilistic stresses. Probabilistic stress, $S_j$, is the random variable for stress influenced by test environments, test equipments, sampling devices and use conditions. The hazard rate, ,$theta_j$, is the random variable of environments and the function of probabilistic stress. Also it is assumed that the general stress distribution is uniform, the life distribution for the given hazard rate, $\theta$, is exponential and inverse power law model holds. In this paper, we obtained maximum likelihood estimators of model parameters and the mean life in use stress condition.

• Transactions of the Korean Society of Automotive Engineers
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• v.3 no.5
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• pp.17-23
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• 1995

A numerical analysis on engine coolant is made by the use of FVM based general purpose 3 dimensional Navier-Stokes solver, TURB-3D. Numerical solutions are verified by comparison with the experimental data of Lotus model. The results show a good qualitative as well as quantitative comparison. Coolant flow rate control is attempted through adjusting the cross section area of passage base on the results of an original coolant passage. It is concluded from the results that the flow rate control is possible as attempted, and thus can be used in the real engine design.

• Korea Journal of Hospital Management
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• v.10 no.1
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• pp.71-92
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• 2005

The purpose of this study is to analyze the efficiency in management of general hospitals and investigate the major factors on efficiency. Specifically, the management of each general hospital is evaluated by using Data Envelopment Analysis(DEA) technique which is a nonparametric statistical method for measurement of efficiency. Then, the influencing factors are investigated through analyses of Decision-Tree Model and Tobit Regression. The target hospitals were general hospitals in which bed sizes are between 200 and 500 among a total of 276 general hospitals. The main data of financial indicators were collected from 48 hospitals, and it was analyzed by using two statistical models. For Model I, three input and two output variables were used for efficiency evaluation. In particular, three input variables were the number of medical doctors, the number of paramedical personnel, and the bed size. And, two output variables were the numbers of inpatients and outpatients per year, adjusted by bed-size. The results of DEA analysis showed that only seven out of 48 hospitals(15%) turned out to be efficient. The decision-tree analysis also showed that there were six significant influencing factors for Model I. Six factors for Model I were Bed Occupancy Rate, Cost per Adjusted Inpatient, New Visit Ratio of Outpatients, Retired Ratio, Net Profit to Gross Revenues, Net Profit to Total Assets. In addition, the management efficiency of hospital is proved to increase as profit and patient-induced indicators increase and cost-related indicators decrease, by the Tobit regression model of independent variables derived from the decision-tree analysis. This study may be contributable to the development of analytic methodology regarding the efficiency of hospital management in that it suggests the synthetic measures by utilizing DEA model instead of suggesting simple ratio-analyzing results.