• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2023년도 학술발표회
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• pp.161-161
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• 2023

Bias correction of values is a necessary step in downscaling coarse and systematically biased global climate models for use in local climate change impact studies. In addition to univariate bias correction methods, many multivariate methods which correct multiple variables jointly - each with their own mathematical designs - have been developed recently. While some literature have focused on the inter-comparison of these multivariate bias correction methods, none have focused extensively on the effect of diverse configurations (i.e., different combinations of input variables to be corrected) of climate variables, particularly high-dimensional ones, on the ability of the different methods to remove biases in uni- and multivariate statistics. This study evaluates the impact of three configurations (inter-variable, inter-spatial, and full dimensional dependence configurations) on four state-of-the-art multivariate bias correction methods in a national-scale domain over South Korea using a gridded approach. An inter-comparison framework evaluating the performance of the different combinations of configurations and bias correction methods in adjusting various climate variable statistics was created. Precipitation, maximum, and minimum temperatures were corrected across 306 high-resolution (0.2°) grid cells and were evaluated. Results show improvements in most methods in correcting various statistics when implementing high-dimensional configurations. However, some instabilities were observed, likely tied to the mathematical designs of the methods, informing that some multivariate bias correction methods are incompatible with high-dimensional configurations highlighting the potential for further improvements in the field, as well as the importance of proper selection of the correction method specific to the needs of the user.

• 품질경영학회지
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• 제52권2호
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• pp.185-199
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• 2024

Purpose: The improvement of yield and quality in product manufacturing is crucial from the perspective of process management. Controlling key variables within the process is essential for enhancing the quality of the produced items. In this study, we aim to identify key variables influencing product defects and facilitate quality enhancement in CNC machining process using SHAP(SHapley Additive exPlanations) Methods: Firstly, we conduct model training using boosting algorithm-based models such as AdaBoost, GBM, XGBoost, LightGBM, and CatBoost. The CNC machining process data is divided into training data and test data at a ratio 9:1 for model training and test experiments. Subsequently, we select a model with excellent Accuracy and F1-score performance and apply SHAP to extract variables influencing defects in the CNC machining process. Results: By comparing the performances of different models, the selected CatBoost model demonstrated an Accuracy of 97% and an F1-score of 95%. Using Shapley Value, we extract key variables that positively of negatively impact the dependent variable(good/defective product). We identify variables with relatively low importance, suggesting variables that should be prioritized for management. Conclusion: The extraction of key variables using SHAP provides explanatory power distinct from traditional machine learning techniques. This study holds significance in identifying key variables that should be prioritized for management in CNC machining process. It is expected to contribute to enhancing the production quality of the CNC machining process.

• International Journal of Computer Science & Network Security
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• 제22권3호
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• pp.389-395
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• 2022

This quantitative study explored the extent to which convenience enhances professional development (PD) online. The sample of the study consisted of 421 teachers and supervisors. Findings evinced that convenience stimulated online PD. Another salient finding is the absence of significant differences among participants' responses concerning position and gender. Nonetheless, a significant difference exists in the variable of teaching experience. Teachers with more than 26-year experience were motivated to use online PD, which evidently could be attributed to the convenience they had over teachers with fewer years of experience.

• 환경영향평가
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• 제20권6호
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• pp.891-905
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• 2011

Climate vulnerability index is usually defined as a function of the climate exposure, sensitivity, and adaptive capacity, which requires adequate selection of proxy variables of each variable. We selected and used 9 proxy variables related to climate exposure in the literature, and diagnosed the adequacy of them for application in Korean peninsula. The selected proxy variables are: four variables from temperature, three from precipitation, one from wind speed, and one from relative humidity. We collected climate data over both previous year (1981~2010) and future climate scenario (A1B scenario of IPCC SERES) for 2020, 2050, and 2100. We introduced the spatial and temporal diagnostic statistical parameters, and evaluated both spatial and time variabilities in the relative scale. Of 9 proxy variables, effective humidity indicated the most sensitive to climate change temporally with the biggest spatial variability, implying a good proxy variable in diagnostics of climate change vulnerability in Korea. The second most sensitive variable is the frequency of strong wind speed with a decreasing trend, suggesting that it should be used carefully or may not be of broad utility as a proxy variable in Korea. The A1B scenario of future climate in 2020, 2050 and 2100 matches well with the extension of linear trend of observed variables during 1981~2010, indicating that, except for strong wind speed, the selected proxy variables can be effectively used in calculating the vulnerability index for both past and future climate over Korea. Other local variabilities for the past and future climate in association with climate exposure variables are also discussed here.

• 농업과학연구
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• 제50권3호
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• pp.581-591
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• 2023

Domestic processed food exports might increase due to the free trade agreement (FTA) and spread of the Korean Wave, Hallyu. However, the share of the domestic raw materials in the domestic processed food industry is very low at 31.4%, which limits the spillover effect on domestic agriculture. Therefore, we selected frozen dumplings as a representative processed food whose exports are growing rapidly and conducted a multiple regression analysis to examine the effects of Hallyu and FTA variables on the frozen dumpling exports. We tried to link them to an increase in agricultural income through the expansion of demand for the domestic raw materials. This study analyzed tariff indicator as the FTA variable, cosmetics export value indicator as the Hallyu Wave variable, and other variables expected to change the trade environment such as gross domestic product (GDP) and the relative exchange rate by country as the key explanatory variables that affect changes in the trade environment. The analysis showed that the core hypothesis, the Hallyu variable and the FTA variable, have a positive impact on frozen dumpling exports. Frozen dumpling exports are expected to increase as the FTAs and the spread of Hallyu are expected to continue for the foreseeable future. Therefore, we should seek ways to increase the proportion of domestically produced ingredients in the frozen dumplings to spread the economic impact to domestic agriculture. We reviewed previous studies and determined, the price-related factors play a major role in the use of imported ingredients, and that price stability and competitiveness are essential to increase the share of the domestically produced ingredients. Based on these conclusions, we reviewed the current status of food industry-related policies and determined measures needed to expand the use of domestically produced ingredients.

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.109-128
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• 2020

A climate-impact projection usually consists of several stages, and the uncertainty of the projection is known to be quite large. It is necessary to assess how much each stage contributed to the uncertainty. We call an uncertainty quantification method in which relative contribution of each stage can be evaluated as uncertainty decomposition. We propose a new Bayesian model for uncertainty decomposition in climate change impact assessments. The proposed Bayesian model can incorporate uncertainty of natural variability and utilize data in control period. We provide a simple and efficient Gibbs sampling algorithm using the auxiliary variable technique. We compare the proposed method with other existing uncertainty decomposition methods by analyzing streamflow data for Yongdam Dam basin located at Geum River in South Korea.

• Journal of Advanced Marine Engineering and Technology
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• 제41권2호
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• pp.150-155
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• 2017

Many engineering issues are caused because of sloshing phenomena. Numerical solution methods including the computational fluid dynamics (CFD) technique, are used to analyze these sloshing problems. In this study, a numerical technique was used to analyze sloshing impact loads in a prismatic tank under forced horizontal motion. The volume-of-fraction (VOF) method was adopted to model the sloshing flow. Six cases were used to compare the effects of the natural frequencies of a simple rectangular and prismatic tank, with impact pressure on the prismatic tank wall. This study also investigated the variable pressure loads and sloshing phenomena in prismatic tanks when the frequencies were changed. The results showed that the average of the peak pressure value for ${\omega}^{\prime}1=4.24=4.24$ was 22% higher than that of ${\omega}_1=4.6$.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2012년도 추계학술대회 논문집
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• pp.750-755
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• 2012

In this study we conduct the optimal spot-weld layout design of vehicle body structure considering dynamic stiffness and side impact. We conduct both linear static analysis and nonlinear analysis with a baseline model to verify the process. 13 design variables will be selected for the effect analysis. Then, topology optimization is conducted to each selected design variable. The design constraints are formulated to improve the dynamic stiffness and side impact performance. Objective function is to set the density of weld component. Optimal spot-weld layout design are compared with the baseline model to show the improvement.

• Journal of Information Technology Applications and Management
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• 제19권4호
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• pp.171-184
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• 2012

We suggest that cultural differences among nations should have a significant impact upon the exports of Korean broadcasting contents due to the fact that production and consumption of the contents are influenced by their own cultural aspects. Based on Hofstede's cultural dimensions frequently cited in the literature, we perform empirical analysis to identify the impact of cultural dimensions upon the export amounts by investigating four-year export data of Korean broadcasting industry. In our research model, Hofstede's cultural dimensions and GDP per capita are independent variables and a genre of broadcasting contents is used as a moderating variable. We find in our analysis that three cultural dimensions such as individualism, uncertainty avoidance, masculinity significantly affect the export amount but do not find the impact of power distance.

• East Asian Economic Review
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• 제27권1호
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• pp.3-31
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• 2023

Dissemination of information can enhance smallholder farmers' agricultural outcomes and incomes in developing countries. However, the impact evaluation for new information can be inaccurate without considering pre-existing information that the indigenous people have used. This study explores qualitative causal links between existing agricultural information used by Lao smallholder farmers on rice yield and selling price with 180 household data. We categorized the pre-existing information into weather, farming technique, input, intermediate trader, and sales price. The source of each piece of information is used as an instrumental variable to overcome the endogeneity issue between information use and agricultural outcomes. Using farming technique information positively affects rice yields by 57.1% compared to those without that information. Moreover, intermediate trader and crop sales information result in 64.5% and 60.0% higher selling prices than non-user groups. A statistically significant causal relationship exists with agricultural outcomes. The more genuine impact should be measured with a newly updated impact evaluation approach that considers this pre-existing agricultural information.