• Journal of Wetlands Research
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• v.24 no.4
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• pp.345-353
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• 2022

A wastewater treatment plant (WWTP) is a major gateway for the engineered nano-particles (ENPs) entering the water bodies. However existing studies have reported that many WWTPs exceed the No Observed Effective Concentration (NOEC) for ENPs in the effluent and thus they need to be designed or operated to more effectively control ENPs. Understanding and predicting ENPs behaviors in the unit and \the whole process of a WWTP should be the key first step to develop strategies for controlling ENPs using a WWTP. This study aims to provide a modeling tool for predicting behaviors and removal efficiencies of ENPs in a WWTP associated with process characteristics and major operating conditions. In the developed model, four unit processes for water treatment (primary clarifier, bioreactor, secondary clarifier, and tertiary treatment unit) were considered. Additionally the model simulates the sludge treatment system as a single process that integrates multiple unit processes including thickeners, digesters, and dewatering units. The simulated ENP was nano-sized TiO₂, (nano-TiO₂) assuming that its behavior in a WWTP is dominated by the attachment with suspendid solids (SS), while dissolution and transformation are insignificant. The attachment mechanism of nano-TiO₂ to SS was incorporated into the model equations using the apparent solid-liquid partition coefficient (Kd) under the equilibrium assumption between solid and liquid phase, and a steady state condition of nano-TiO₂ was assumed. Furthermore, an MS Excel-based user interface was developed to provide user-friendly environment for the nano-TiO₂ removal efficiency calculations. Using the developed model, a preliminary simulation was conducted to examine how the solid retention time (SRT), a major operating variable affects the removal efficiency of nano-TiO₂ particles in a WWTP.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.515-530
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• 2021

This study is to estimate soil moisture (SM) using Sentinel-1A/B C-band SAR (synthetic aperture radar) images and Multiple Linear Regression Model(MLRM) in the Yongdam-Dam watershed of South Korea. Both the Sentinel-1A and -1B images (6 days interval and 10 m resolution) were collected for 5 years from 2015 to 2019. The geometric, radiometric, and noise corrections were performed using the SNAP (SentiNel Application Platform) software and converted to backscattering coefficient of VV and VH polarization. The in-situ SM data measured at 6 locations using TDR were used to validate the estimated SM results. The 5 days antecedent precipitation data were also collected to overcome the estimation difficulty for the vegetated area not reaching the ground. The MLRM modeling was performed using yearly data and seasonal data set, and correlation analysis was performed according to the number of the independent variable. The estimated SM was verified with observed SM using the coefficient of determination (R²) and the root mean square error (RMSE). As a result of SM modeling using only BSC in the grass area, R² was 0.13 and RMSE was 4.83%. When 5 days of antecedent precipitation data was used, R² was 0.37 and RMSE was 4.11%. With the use of dry days and seasonal regression equation to reflect the decrease pattern and seasonal variability of SM, the correlation increased significantly with R² of 0.69 and RMSE of 2.88%.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.49-62
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• 2023

Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• Clean Technology
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• v.29 no.4
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• pp.255-261
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• 2023

Power semiconductors are semiconductors used for power conversion, transformation, distribution, and control. Recently, the global demand for high-voltage power semiconductors is increasing across various industrial fields, and optimization research on high-voltage IGBT components is urgently needed in these industries. For high-voltage IGBT development, setting the resistance value of the wafer and optimizing key unit processes are major variables in the electrical characteristics of the finished chip. Furthermore, the securing process and optimization of the technology to support high breakdown voltage is also important. Etching is a process of transferring the pattern of the mask circuit in the photolithography process to the wafer and removing unnecessary parts at the bottom of the photoresist film. Ion implantation is a process of injecting impurities along with thermal diffusion technology into the wafer substrate during the semiconductor manufacturing process. This process helps achieve a certain conductivity. In this study, dry etching and wet etching were controlled during field ring etching, which is an important process for forming a ring structure that supports the 3.3 kV breakdown voltage of IGBT, in order to analyze four conditions and form a stable body junction depth to secure the breakdown voltage. The field ring ion implantation process was optimized based on the TEG design by dividing it into four conditions. The wet etching 1-step method was advantageous in terms of process and work efficiency, and the ring pattern ion implantation conditions showed a doping concentration of 9.0E13 and an energy of 120 keV. The p-ion implantation conditions were optimized at a doping concentration of 6.5E13 and an energy of 80 keV, and the p+ ion implantation conditions were optimized at a doping concentration of 3.0E15 and an energy of 160 keV.

• Health Policy and Management
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• v.34 no.1
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• pp.48-58
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• 2024

Background: The purpose of this study was to investigate the association between external medical service use and the characteristics of Chungcheongnam-do patients. We aimed to provide evidence of external medical service use enhance the healthcare delivery system in Chungcheongnam-do. Methods: We used the Health Insurance Cohort DB 2.0 of 2016-2019, and 2,570,439 patients were included in the study. Multivariate logistic regression and multinomial logistic regression were used to identify the association between external medical service use and each patient characteristic. Generalized linear model was used to identify the association between medical costs and external medical service use area. Results: During the study period, 32.2% of inpatients and 12.5% of outpatients had external medical service use in Chungcheongnam-do. In comparison to patients living in Cheonan and Asan, the odds ratio (OR) for external medical services use was higher across all regions. Specifically, hospitalized patients from Gyeryong, Nonsan, and Geumsan (OR, 116.817) and Gongju, Buyeo, and Cheongyang (OR, 72.931) demonstrated extremely high likelihood of external medical service use in the Daejeon area. Furthermore, compared to medical expenses incurred within Chungcheongnam-do, patients with external medical service use in the capitol area (outpatient=17.01%, inpatients=22.11%) and Daejeon area (outpatient=16.63%, inpatients=15.41%) spent more on healthcare services. Conclusion: This study found the evidence of external medical service use among Chungcheongnam-do patients. Further study should be conducted taking into account variables including satisfaction of local medical services, different types of patient diseases, and others. The study's findings may serve as a foundation for policy proposals aimed at ensuring the financial stability of our health insurance system, ensuring the efficient delivery of medical care, and localization of medical care.