• Korean Journal of Radiology
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• v.22 no.3
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• pp.344-353
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• 2021

Objective: The mitotic count of gastrointestinal stromal tumors (GIST) is closely associated with the risk of planting and metastasis. The purpose of this study was to develop a predictive model for the mitotic index of local primary GIST, based on deep learning algorithm. Materials and Methods: Abdominal contrast-enhanced CT images of 148 pathologically confirmed GIST cases were retrospectively collected for the development of a deep learning classification algorithm. The areas of GIST masses on the CT images were retrospectively labelled by an experienced radiologist. The postoperative pathological mitotic count was considered as the gold standard (high mitotic count, > 5/50 high-power fields [HPFs]; low mitotic count, ≤ 5/50 HPFs). A binary classification model was trained on the basis of the VGG16 convolutional neural network, using the CT images with the training set (n = 108), validation set (n = 20), and the test set (n = 20). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated at both, the image level and the patient level. The receiver operating characteristic curves were generated on the basis of the model prediction results and the area under curves (AUCs) were calculated. The risk categories of the tumors were predicted according to the Armed Forces Institute of Pathology criteria. Results: At the image level, the classification prediction results of the mitotic counts in the test cohort were as follows: sensitivity 85.7% (95% confidence interval [CI]: 0.834-0.877), specificity 67.5% (95% CI: 0.636-0.712), PPV 82.1% (95% CI: 0.797-0.843), NPV 73.0% (95% CI: 0.691-0.766), and AUC 0.771 (95% CI: 0.750-0.791). At the patient level, the classification prediction results in the test cohort were as follows: sensitivity 90.0% (95% CI: 0.541-0.995), specificity 70.0% (95% CI: 0.354-0.919), PPV 75.0% (95% CI: 0.428-0.933), NPV 87.5% (95% CI: 0.467-0.993), and AUC 0.800 (95% CI: 0.563-0.943). Conclusion: We developed and preliminarily verified the GIST mitotic count binary prediction model, based on the VGG convolutional neural network. The model displayed a good predictive performance.

• Management & Information Systems Review
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• v.29 no.2
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• pp.1-25
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• 2010

This study attempted to empirically test the determinants of stock returns in Korean stock market applying multi-factor model proposed by Haugen and Baker(1996). Regression models were developed using 16 variables related to liquidity, risk, historical price, price level, and profitability as independent variables and 690 stock monthly returns as dependent variable. For the statistical analysis, the data were collected from the Kis Value database and the tests of forecasting power in this study minimized various possible bias discussed in the literature as possible. The statistical results indicated that: 1) Liquidity, one-month excess return, three-month excess return, PER, ROE, and volatility of total return affect stock returns simultaneously. 2) Liquidity, one-month excess return, three-month excess return, six-month excess return, PSR, PBR, ROE, and EPS have an antecedent influence on stock returns. Meanwhile, realized returns of decile portfolios increase in proportion to predicted returns. This results supported previous study by Haugen and Baker(1996) and indicated that firm-characteristic model can better predict stock returns than CAPM. 3) The firm-characteristic model has better predictive power than Fama-French three-factor model, which indicates that a portfolio constructed based on this model can achieve excess return. This study found that expected return factor models are accurate, which is consistent with other countries' results. There exists a surprising degree of commonality in the factors that are most important in determining the expected returns among different stocks.

• Journal of the Society of Disaster Information
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• v.11 no.1
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• pp.135-147
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• 2015

Recent underground common utility tunnels are underground facilities for jointly accommodating more than 2 kinds of air-conditioning and heating facilities, vacuum dust collector, information processing cables as well as electricity, telecommunications, waterworks, city gas, sewerage system required when citizens live their daily lives and facilities responsible for the central function of the country but it is difficult to cope with fire accidents quickly and hard to enter into common utility tunnels to extinguish a fire due to toxic gases and smoke generated when various cables are burnt. Thus, in the event of a fire, not only the nerve center of the country is paralyzed such as significant property damage and loss of communication etc. but citizen inconveniences are caused. Therefore, noticing that most fires break out by a short circuit due to electrical works and degradation contact due to combustible cables as the main causes of fires in domestic and foreign common utility tunnels fire cases that have occurred so far, the purpose of this paper is to scientifically analyze the behavior of a fire by producing the model of actual common utility tunnels and reproducing the fire. A fire experiment was conducted in a state that line type fixed temperature detector, fire door, connection deluge set and ventilation equipment are installed in underground common utility tunnels and transmission power distribution cables are coated with fire proof paints in a certain section and heating pipes are fire proof covered. As a result, in the case of Type II, the maximum temperature was measured as $932^{\circ}C$ and line type fixed temperature detector displayed the fire location exactly in the receiver at a constant temperature. And transmission power distribution cables painted with fire proof paints in a certain section, the case of Type III, were found not to be fire resistant and fire proof covered heating pipes to be fire resistant for about 30 minutes. Also, fire simulation was carried out by entering fire load during a real fire test and as a result, the maximum temperature is $943^{\circ}C$, almost identical with $932^{\circ}C$ during a real fire test. Therefore, it is considered that fire behaviour can be predicted by conducting fire simulation only with common utility tunnels fire load and result values of heat release rate, height of the smoke layer, concentration of O2, CO, CO2 etc. obtained by simulation are determined to be applied as the values during a real fire experiment. In the future, it is expected that more reliable information on domestic underground common utility tunnels fire accidents can be provided and it will contribute to construction and maintenance repair effectively and systematically by analyzing and accumulating experimental data on domestic underground common utility tunnels fire accidents built in this study and fire cases continuously every year and complementing laws and regulations and administration manuals etc.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.239-251
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• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.6
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• pp.882-889
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• 2022

In this study, to understand the factors influencing the flow change the Tsushima Warm Current (TWC), the correlation between the volume transport the TWC, El Niño Southern Oscillation (ENSO), and Pacific Decadal Oscillation (PDO) was analyzed. A calculation of the monthly volume transport of TWC for 25 years (1993-2018) revealed that the seasonal fluctuation cycle was the largest in summer and smallest in winter. Power spectrum analysis to determine the periodicity of the TWC volume transport, Oceanic Niño Undex (ONI), and PDO indicated that the TWC volume transport peaked at a one year cycle, but ONI and PDO showed no clear cycle. Further, to understand the correlation between the TWC transport volume and ONI and PDO, the coherence estimation method was used for analysis. The coherence of ONI and PDO had a high mutual contribution in long-period fluctuations of three years or more but had low mutual contribution in short-period fluctuations within one year. However, the coherence value between the two factors of the TWC volume transport and PDO was 0.7 in the 0.8-1.2 year cycle, which had a high mutual contribution. Meanwhile, the TWC volume transport and PDO have an inverse correlation between period I (1993-2002) and period III (2010-2018). When the TWC maximum transport volume (2.2 Sv or more) was high, the PDO index showed a negative value below -1.0, and the PDO index showed a positive value when the TWC maximum transport volume was (below 2.2 Sv). Therefore, using long-term PDO index data, changes in the TWC transport volume and water temperature in the East Sea coastal area could be predicted.

• Tuberculosis and Respiratory Diseases
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• v.44 no.1
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• pp.93-103
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• 1997

Background : Malnutrition is a common finding in patients with chronic obstructive pulmonary disease, especially in the emphysema group. Although the mechanism of malnutrition is not confirmed, it is believed to be a relative deficiency caused by hypermetabolism due to increased energy requirements of the respiratory muscles, rather than a dietary deficiency. Malnutrition in chronic obstructive pulmonary disease is not a merely coincidental finding. It is known that the nutritional status correlates with physiologic parameters including pulmonary function, muscular power, and exercise performance, and is one of the important and independent prognostic factors of the disease. Methods : Patients with chronic obstructive pulmonary disease Yongdong Severance Hospital from May, 1995 to March, 1996 and age-matched healthy control group were studied. Survey of nutritional intake, anthropometric measurements and biochemical tests were done to assess nutritional status. Relationship between nutritional status and FEV1 (forced expiratory volume at one second), which was a significant functional parameter, was assessed. Results : 1) The patient group was consisted of 25 males with mean age of 66.1years and FEV1 of $42{\pm}14%$ of predicted values. The control group was consisted of 26 healthy males with normal pulmonary function, whose mean age was 65.0 years. 2) The ratio of calorie intake/calorie requirement per day was $107{\pm}28%$ in the patient group, and $94{\pm}14%$ in the control group, showing a tendency of more nutritional intake in patient group(B=0.06). 3) There were significant differences between the patient group and control group in percent ideal body weight(92.8% vs 101.6%, p=0.024), body mass index($20.0kg/m^2$ VS $21.9kg/m^2$, p=0.015), and handgrip strength(29.0kg vs 34.3kg, p=0.003). However, there were no significant differences in triceps skinfold thickness, mid-arm muscle circumference, albumin, and total lymphocyte count between two groups. Percentage of underweight population was 40%(10/25) in the patient group, and 15%(4/26) in the control group. 4) The percent ideal body weight, triceps skinfold thickness, and mid-arm muscle circumference had significant correlation with FEV1. Conclusion : The patients with chronic obstructive pulmonary disease showed significant depletion in nutritional parameters such as body weight and peripheral muscle strength, while absolute amount of dietary intake was not insufficient. Nutritional parameters were well correlated with FEV1.

• Journal of Biosystems Engineering
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• v.4 no.2
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• pp.65-83
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• 1979

Low-temperature drying systems have been extensively used for drying cereal grain such as shelled corn and wheat. Since the 1973 energy crisis, many researches have been conducted to apply solar energy as supplemental heat to natural air drying systems. However, little research on rough rice drying has been done in this area, especially very little in Korea. In designing a solar drying system, quality loss, airflow requirements, temperature rise of drying air, fan power and energy requirements should be throughly studied. The factors affecting solar drying systems are airflow rate, initial moisture content, the amount of heat added to drying air, fan operation method and the weather conditions. The major objectives of this study were to analyze the effects of the performance factors and determine design parameters such as airflow requirements, optimum bed depth, optimum temperature rise of drying air, fan operation method and collector size. Three hourly observations based on the 4-year weather data in Chuncheon area were used to simulate rough rice drying. The results can be summarized as follows: 1. The results of the statistical analysis indicated that the experimental and predicted values of the temperature rise of the air passing through the collector agreed well. 2. Equilibrium moisture content was affected a little by airflow rate, but affected mainly by the amount of heat added, to drying air. Equilibrium moisture content ranged from 12.2 to 13.2 percent wet basis for the continuous fan operation, from 10.4 to 11.7 percent wet basis for the intermittent fan operation respectively, in range of 1. 6 to 5. 9 degrees Centigrade average temperature rise of drying air. 3. Average moisture content when top layer was dried to 15 percent wet basis ranged from 13.1 to 13.9 percent wet basis for the continuous fan operation, from 11.9 to 13.4 percent wet basis for the intermittent fan operation respectively, in the range of 1.6 to 5.9 degrees Centigrade average temperature rise of drying air and 18 to 24 percent wet basis initial moisture content. The results indicated that grain was overdried with the intermittent fan operation in any range of temperature rise of drying air. Therefore, the continuous fan operation is usually more effective than the intermittent fan operation considering the overdrying. 4. For the continuous fan operation, the average temperature rise of drying air may be limited to 2.2 to 3. 3 degrees Centigrade considering safe storage moisture level of 13.5 to 14 perceut wet basis. 5. Required drying time decrease ranged from 40 to 50 percent each time the airflow rate was doubled and from 3.9 to 4.3 percent approximately for each one degrees Centigrade in average temperature rise of drying air regardless of the fan operation methods. Therefore, the average temperature rise of drying air had a little effect on required drying time. 6. Required drying time increase ranged from 18 to 30 percent approximately for each 2 percent increase in initial moisture content regardless of the fan operation methods, in the range of 18 to 24 percent moisture. 7. The intermittent fan operation showed about 36 to 42 percent decrease in required drying time as compared with the continuous fan operation. 8. Drymatter loss decrease ranged from 34 to 46 percent each time the airflow rate was doubled and from 2 to 3 percent approximately for each one degrees Centigrade in average temperature rise of drying air, regardless of the fan operation methods. Therefore, the average temperature rise of drying air had a little effect on drymatter loss. 9. Drymatter loss increase ranged from 50 to 78 percent approximately for each 2 percent increase in initial moisture content, in the range of 18 to 24 percent moisture. 10. The intermittent fan operation: showed about 40 to 50 percent increase in drymatter loss as compared with the continuous fan operation and the increasing rate was higher at high level of initial moisture and average temperature rise. 11. Year-to-year weather conditions had a little effect on required drying time and drymatter loss. 12. The equations for estimating time required to dry top layer to 16 and 1536 wet basis and drymatter loss were derived as functions of the performance factors. by the least square method. 13. Minimum airflow rates based on 0.5 percent drymatter loss were estimated. Minimum airflow rates for the intermittent fan operation were approximately 1.5 to 1.8 times as much as compared with the continuous fan operation, but a few differences among year-to-year. 14. Required fan horsepower and energy for the intermittent fan operation were 3. 7 and 1. 5 times respectively as much as compared with the continuous fan operation. 15. The continuous fan operation may be more effective than the intermittent fan operation considering overdrying, fan horsepower requirements, and energy use. 16. A method for estimating the required collection area of flat-plate solar collector using average temperature rise and airflow rate was presented.

• Journal of Biosystems Engineering
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• v.4 no.2
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• pp.64-64
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• 1979

Low-temperature drying systems have been extensively used for drying cereal grain such as shelled corn and wheat. Since the 1973 energy crisis, many researches have been conducted to apply solar energy as supplemental heat to natural air drying systems. However, little research on rough rice drying has been done in this area, especially very little in Korea. In designing a solar drying system, quality loss, airflow requirements, temperature rise of drying air, fan power and energy requirements should be throughly studied. The factors affecting solar drying systems are airflow rate, initial moisture content, the amount of heat added to drying air, fan operation method and the weather conditions. The major objectives of this study were to analyze the effects of the performance factors and determine design parameters such as airflow requirements, optimum bed depth, optimum temperature rise of drying air, fan operation method and collector size. Three hourly observations based on the 4-year weather data in Chuncheon area were used to simulate rough rice drying. The results can be summarized as follows: 1. The results of the statistical analysis indicated that the experimental and predicted values of the temperature rise of the air passing through the collector agreed well.2. Equilibrium moisture content was affected a little by airflow rate, but affected mainly by the amount of heat added, to drying air. Equilibrium moisture content ranged from 12.2 to 13.2 percent wet basis for the continuous fan operation, from 10.4 to 11.7 percent wet basis for the intermittent fan operation respectively, in range of 1. 6 to 5. 9 degrees Centigrade average temperature rise of drying air.3. Average moisture content when top layer was dried to 15 percent wet basis ranged from 13.1 to 13.9 percent wet basis for the continuous fan operation, from 11.9 to 13.4 percent wet basis for the intermittent fan operation respectively, in the range of 1.6 to 5.9 degrees Centigrade average temperature rise of drying air and 18 to 24 percent wet basis initial moisture content. The results indicated that grain was overdried with the intermittent fan operation in any range of temperature rise of drying air. Therefore, the continuous fan operation is usually more effective than the intermittent fan operation considering the overdrying.4. For the continuous fan operation, the average temperature rise of drying air may be limited to 2.2 to 3. 3 degrees Centigrade considering safe storage moisture level of 13.5 to 14 perceut wet basis.5. Required drying time decrease ranged from 40 to 50 percent each time the airflow rate was doubled and from 3.9 to 4.3 percent approximately for each one degrees Centigrade in average temperature rise of drying air regardless of the fan operation methods. Therefore, the average temperature rise of drying air had a little effect on required drying time.6. Required drying time increase ranged from 18 to 30 percent approximately for each 2 percent increase in initial moisture content regardless of the fan operation methods, in the range of 18 to 24 percent moisture.7. The intermittent fan operation showed about 36 to 42 percent decrease in required drying time as compared with the continuous fan operation.8. Drymatter loss decrease ranged from 34 to 46 percent each time the airflow rate was doubled and from 2 to 3 percent approximately for each one degrees Centigrade in average temperature rise of drying air, regardless of the fan operation methods. Therefore, the average temperature rise of drying air had a little effect on drymatter loss. 9. Drymatter loss increase ranged from 50 to 78 percent approximately for each 2 percent increase in initial moisture content, in the range of 18 to 24 percent moisture. 10. The intermittent fan operation: showed about 40 to 50 percent increase in drymatter loss as compared with the continuous fan operation and the increasing rate was higher at high level of initial moisture and average temperature rise.11. Year-to-year weather conditions had a little effect on required drying time and drymatter loss.12. The equations for estimating time required to dry top layer to 16 and 1536 wet basis and drymatter loss were derived as functions of the performance factors. by the least square method.13. Minimum airflow rates based on 0.5 percent drymatter loss were estimated.Minimum airflow rates for the intermittent fan operation were approximately 1.5 to 1.8 times as much as compared with the continuous fan operation, but a few differences among year-to-year.14. Required fan horsepower and energy for the intermittent fan operation were3. 7 and 1. 5 times respectively as much as compared with the continuous fan operation.15. The continuous fan operation may be more effective than the intermittent fan operation considering overdrying, fan horsepower requirements, and energy use.16. A method for estimating the required collection area of flat-plate solar collector using average temperature rise and airflow rate was presented.

• Korean Journal of Agricultural Science
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• v.9 no.1
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• pp.357-370
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• 1982

Recent concern regarding price and availability of fossil fuels has spurred the interest in alternative sources for farm crop drying. Among the available options such as biomass energy, wind power, nuclear energy and solar energy etc., the increasing attention is being directed to the utilization of heat from solar energy especially for farm crop drying. Even though solar energy is dispersed over a large land area and only a relatively small amount of energy can be simply collected, the advantages of solar energy is that the energy is free, non-polluting. The study reported here was designed to help supply the informations for the development of simple and relatively inexpensive solar warehouse for farm crop drying and storage. Specifically, the objectives of this study were to determine the performance of the solar collector fabricated, to compare solar supplemented heat drying with natural air drying and to develop a simulation model of temperature in stored grain, which can be used to study the effects due to changes in ambient air temperature. For those above objectives, solar collector was fabricated from available materials. Corrugated steel galvanized sheet, painted flat black, was used as absorbers and clear 0.2mm polyethylene sheet was the cover material. The warehouse for rough rice drying and storage was constructed with concrete block, and the solar collector was used as the roof of warehouse instead of original roofing system of it. The results obtained in this study were as follows: 1. The thermal efficiency of the solar collector was average 26 percent and the overall heat transfer coefficient of the collector was approximately $25kJ/hr.m^2\;^{\circ}K$. 2. Solar heated air was sufficient to dry one cubic meter of rough rice from 23.5 to 15.0 percent in 7 days and natural air was able to dry the same amount of rough rice from 20.0 to 5 percent in l2 days. 3. Drying with solar heat reduced the required drying time to dry the same amount of rough rice into a half compared to natural air drying, but overdrying problems of the bottom layer were so severe that these problems should be thoroughly analyzed. 4. Simulation model of temperature in stored grain was developed and the results of predicted temperature agreed well with test results. 5. Based on those simulated temperature, changes in the grain-temperature were a large at the points of the wallside and the damage of the grain would be severe at the contact area of wall.

• Journal of Distribution Research
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• v.17 no.3
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• pp.59-92
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• 2012

With accumulated research evidence, there is little doubt that leadership behavior is related to a wide variety of positive individual and organizational outcomes. Indeed, leadership behavior has been empirically linked to increased employee satisfaction, organizational commitment, extra effort, turnover intention, organizational citizenship behavior, and overall employee performance. Although leadership behavior has been linked to a number of positive organizational outcomes, research regarding the antecedents of such behavior is limited. Especially there is little research dealing with the antecedents of inter-organizational leadership behavior. This study interests in inter-organizational ethical leadership among marketing channel members. In both the mass media and the academic association, there has been a surge in interest in the ethical and unethical behavior of leaders. Although the corporate scandals in recent years may explain much of the mass media and popular focus, academics' interest has been limited by evidence that ethical leadership behavior is associated with both positive and negative inter-organizational processes and performances. This study tried to contribute to this body of knowledge by examining antecedents of ethical leadership. Ethical leadership is defined "the demonstration of normatively appropriate conduct through personal actions and interpersonal relationships, and the promotion of such conduct to followers through two-way communication, reinforcement, and decision-making." Ethical leaders not only inform individuals of the behefits of ethical behavior and the cost of inappropriate behavior, such leaders also set clear standards and use rewards and fair and balanced punishment to hold followers accountable for their ethical conduct. Despite the assume importance and prominence of ethical leadership among organizations, there are still many questions relating to its antecedents and consequences. One is whether the likelihood of an leading organization being perceived as an ethical leader among other following organizations in marketing channels can be predicted using its characteristics and inter-organizational relationship maintenance skills. Identifying trait and skill antecedents will aid in the development of strategies for selecting and developing ethical leaders and determining the best means to reinforce ethical behaviors. The purpose of this study is to investigate the effects of three categorized variables on ethical leadership of channel leader. To be concrete, this study develops a model of the antecedents of three conceptually distinct forms of channel leader characteristics, such as organizational traits, inter-organizational relationship maintenance strategies, and supplier management strategies, and tests the hypothesized differential effects on ethical leadership of marketing channel leaders. The reason why this study deals with discount store channel is that there is very strong inter-dependence between a discount store and its suppliers. Their strong inter-dependence makes their relationship as the relationship between a leader and suppliers and creates an atmosphere that leadership occur without difficulty. The research model is as follows. For the purpose of empirical testing, 295 respondents of suppliers of discount store channel in Korea were surveyed. The procedures included scale reliability, and discriminant and convergent validity were used to validate measures. Also, the reliability measurements traditionally employed, such as the Cronbach's alpha, were used. All the reliabilities were greater than .70. This study conducted confirmatory factor analyses to assess the validity of our measurements. All items loaded significantly on their respective constructs(with the lowest t-value being 15.2), providing support for convergent validity. We then examined composite reliability and average variance extracted(AVE). The composite reliability of each construct was greater than .70. The AVE of each construct was greater than .50. This study tested research model using Partial Least Square(PLS). The estimation of the structural equation model revealed an acceptable fit of the model to the data($r^2$=.851). Thus, This study concluded that the model fit was considered acceptable. The results of PLS are as follows. The results indicated that conscientiousness, openness, conflict management, social networks, training, fair reward had positive effects on ethical leadership of channel leaders. On the other hand, emotional insecure had negative effect and agreeableness, assurance, and inter-organizational communication had no significant effect on supply chain leadership.