• Economic Analysis
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• v.26 no.4
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• pp.98-136
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• 2020

We empirically investigate the determinants of a firm's exit from exporting, using Korean manufacturing firm-level data for the period from 2006 to 2014. Specifically, we estimate the effects of not only firm-level and industry-level characteristics, but also macroeconomic variables on the probability that a firm stops exporting by applying a Complementary Log-Log Model analysis. The results of our estimation suggest that firm-level heterogeneity, such as workforce size, capital intensity, intangible assets and foreign ownership, industry-level variation, such as the labor displacement rate, and macroeconomic variables, such as domestic demand and world demand, significantly affect the possibility of a firm ceasing exports. Also, we show that market interest rates increase the possibility of an export cessation and that the effects of market interest rates are more pronounced on firms with a higher debt ratio. In the primary exporting industries, the probability of a firm ceasing exports decreases as productivity at the firm rises.

• Journal of Korean Society of Transportation
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• v.5 no.2
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• pp.73-80
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• 1987

Various procedures for evaluation of traffic noise annoyance have been proposed. However, most of the studies of this type are restricted for improving traffic flow. In this paper, a method to predict the road traffic noise is proposed in terms of equivalent continuous A-Weighted sound pressure level (Leq), based on a probability model. First, distribution of the road traffic noise level are investigated. second, the weibull distribution parameters are estimated by using the quantification theory. Finally, a prediction model of the road traffic noise is proposed based on the weibull distribution model The predicted values of the Leq are closely matched the measured data.

• Journal of Korean Society for Quality Management
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• v.14 no.1
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• pp.33-38
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• 1986

This paper deals with probabilistic order level inventory system which the quantity ordered at the end of the scheduling period is dependent on lead times. To find an optimal solution, pearson system of distributions is used to approximate the probability density function of the on-order quantity. An example is solved and sensitivity analysis is performed to examine the relation between lead times and the ordering quantity.

• Journal of the Korean Statistical Society
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• v.36 no.3
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• pp.397-410
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• 2007

For the two groups data from multivariate binomial distribution, we consider a bootstrap approach to inferring the simultaneous confidence level and its standard error of a collection of the dependent confidence intervals for the difference of proportions with an experimentwise error rate at the a level are presented. The bootstrap method is used to estimate the simultaneous confidence probability for the difference of proportions.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.13 no.21
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• pp.25-28
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• 1990

In this paper we consider the one-period inventory model in which it is required to determine the selling quantity which maximizes the probability of realizing a predetermined level of profit L. The Assumptions used in this paper are willing to accept the rel life considerations, which are thestochasic supply, the discounted selling price and the discounted purchasing cost for the over-supply etc.

• Journal of the military operations research society of Korea
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• v.12 no.2
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• pp.22-36
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• 1986

The study is to design optimal aircraft allocation model for sufficing the required level of damage, minimizing attrition cost when the aircrafts attack the enemy's fixed target. When friendly aircraft attacks enemy target, the aircraft will suffer the loss due to the enemy's anti-aircraft weapons and aircraft. For this study, it is required that the probability of target damage by the type of aircraft, level of target damage and attrition cost are computed for the application of this model.

• Journal of Agricultural Extension & Community Development
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• v.19 no.3
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• pp.527-550
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• 2012

This study is aimed to compare individualism and collectivism propensity of married immigrant women in a Korean rural area. By result of comparison on nationality, the level of collectivism was higher than it of individualism in every country, but the level of collectivism among the countries was no significant difference. The level of individualism among the countries was difference significantly, and the level of individualism of Chinese is most high but it of Japanese is most low. By logistic regression analysis the probability to be involved in the group that level of individualism is high was heightened as respondent have no religion or their's satisfaction on rural life increase. The level of horizontal propensity was higher than it of vertical propensity both individualism and collectivism. But the result of comparison on nationality, difference between horizontal and vertical propensity was no significant. Besides of these results, practical implications were discussed.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.11
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• pp.668-674
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• 2003

The electric marketplace is in the midst of major changes designed to promote competition. No longer vertically integrated with guaranteed customers and suppliers, electric generators and distributors will have to compete to sell and buy electricity. Unit commitment (UC) in such a competitive environment is not the same as the traditional one anymore. The objective of UC is not to minimize production cost as before but to find the solution that produces a maximum profit for a generation firm. This paper presents a hi-level formulation that decomposes the UC game into a generation-decision game (first level game) and a state(on/off)-decision game (second level game). Derivation that the first-level game has a pure Cournot Nash equilibrium(NE) helps to solve the second-level game. In case of having a mixed NE in the second-level game, this paper chooses a pure strategy having maximum probability in the mixed strategy in order to obviate the probabilistic on/off state which may be infeasible. Simulation results shows that proposed method gives the adequate UC solutions corresponding to a NE.

• The Journal of the Acoustical Society of Korea
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• v.26 no.2E
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• pp.56-62
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• 2007

This paper presents the automatic music emotion classification on acoustic data. A three-level structure is developed. The low-level extracts the timbre and rhythm features. The middle-level estimates the indication functions that represent the emotion probability of a single analysis unit. The high-level predicts the emotion result based on the indication function values. Experiments are carried out on 695 homogeneous music pieces labeled with four emotions, including pleasant, calm, sad, and excited. Three machine learning methods, GMM, MLP, and SVM, are compared on the high-level. The best result of 90.16% is obtained by MLP method.

• Ocean Systems Engineering
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• v.7 no.4
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• pp.319-328
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• 2017

Higher prediction efficacy is a very challenging task in any field of engineering. Due to global warming, there is a considerable increase in the global sea level. Through this work, an attempt has been made to find the sea level variability due to climate change impact at Haldia Port, India. Different statistical downscaling techniques are available and through this paper authors are intending to compare and illustrate the performances of three regression models. The models: Wavelet Neural Network (WNN), Minimax Probability Machine Regression (MPMR), Feed-Forward Neural Network (FFNN) are used for projecting the sea level variability due to climate change at Haldia Port, India. Model performance indices like PI, RMSE, NSE, MAPE, RSR etc were evaluated to get a clear picture on the model accuracy. All the indices are pointing towards the outperformance of WNN in projecting the sea level variability. The findings suggest a strong recommendation for ensembled models especially wavelet decomposed neural network to improve projecting efficiency in any time series modeling.