• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.953-966
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• 2022

Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.502-517
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• 2022

As the use of TBM increases, research has recently increased to to analyze TBM data with machine learning techniques to predict the exchange cycle of disc cutters, and predict the advance rate of TBM. In this study, a regression prediction of disc cutte wear of slurry shield TBM site was made by combining machine learning based on the machine data and the geotechnical data obtained during the excavation. The data were divided into 7:3 for training and testing the prediction of disc cutter wear, and the hyper-parameters are optimized by cross-validated grid-search over a parameter grid. As a result, gradient boosting based on the ensemble model showed good performance with a determination coefficient of 0.852 and a root-mean-square-error of 3.111 and especially excellent results in fit times along with learning performance. Based on the results, it is judged that the suitability of the prediction model using data including mechanical data and geotechnical information is high. In addition, research is needed to increase the diversity of ground conditions and the amount of disc cutter data.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.48 no.4
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• pp.321-330
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• 2022

This study attempted to establish an optimal multi-compound simultaneous analysis method that can secure reliable results for 15 - preservatives, 2 - sun screens and 1 - antioxidants of cosmetics using HPLC-PDA. Since the potential of hydrogen (pH) in the mobile phase affects the acid dissociation constant (pKa) of the preservatives, and the peak retention time shift and area change were observed. The peak separation condition was established by adjusting the pH to 0.1% H₃PO₄ addition (mL) when preparing the mobile phase. As a results of method validation, the linearity correlation coefficient (R²) of above 0.999 were obtained, and accuracy 87.9 ~ 101.1%, 0.1 ~ 7.6% precision for two types of cosmetics (cream and shampoo). It was found that the limit of detection (LOD) was 0.1 ~ 0.2 mg/kg and the limit of quantitation (LOQ) was 2.0 ~ 4.0 mg/kg. In addition, it was possible to simultaneously separate p-anisic acid, a natural compound that was difficult to separate in HPLC due to the small difference from methylparaben, a synthetic preservatives. Through this study, it will be effectively used to secure quality control and safety for compound that need restrictions on use cosmetics.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.149-161
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• 2022

Because the speed limit affects moving speed, it is closely related to traffic accidents as well as traffic flow. The existing speed limit calculation methods consider various engineering factors such as lanes, intersection spacing, driveways, crosswalks, 85 percentile speed, land uses, and roadway geometric characteristics etc. However, it can be said that the engineering analysis is insufficient because the traffic impact analysis considering traffic volume is not carried out. In addition, only 85 percentile speed, which is the spot speed, does not reflect the characteristics of the traffic flow on the road. In this paper, the effect of the speed limit change on the moving speed and the travel speed was analyzed in detail accordinr to the variation of intersection spacing and traffic volume. And by using the results, we proposed a speed limit calculation method that maintains the same service level as before the speed limit change, thereby increasing the speed improvement effect and reducing the difference between moving speed and travel speed. In addition, a variable speed limit operation method according to the change in traffic volume was also suggested. This method is expected to be effective in terms of safety by reducing the speed difference, which affects the severity of traffic accidents, while securing the speed improvement effect, and increasing the speed limit compliance rate of drivers by operating the speed limit that reflects the speed change due to the variation of traffic volume.

• The Journal of Engineering Geology
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• v.33 no.1
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• pp.69-83
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• 2023

Forest fires increase the risk of subsequent soil erosion and mass movement in burned areas, even under rainfall conditions below landslide alert thresholds, by destroying plants and vegetation and causing changes to soil properties. These effects of forest fires can alter runoff in burned areas by altering soil composition, component minerals, soil water repellency, soil mass stability, and soil fabric. Heat from forest fires not only burns shallow organic matter and plants but also spreads below the surface, affecting soil constituents including minerals. This study analyzed X-ray diffraction and physical properties of topsoil and subsoil obtained from both burned and non-burned areas to identify the composition and distribution of clay minerals in the soil. Small amounts of mullite, analcite, and hematite were identified in burned soils. Vermiculite and mixed-layer illite/vermiculite (I/V) were found in topsoil samples from burned areas but not in those from non-burned areas. These findings show changes in soil mineral composition caused by forest fires. Expansive clay minerals increase the volume of soil during rainfall, degrading the structural stability of slopes. Clay minerals generated in soil in burned areas are therefore likely to affect the long-term stability of slopes in mountainous areas.

• Korean Journal of Ecology and Environment
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• v.55 no.2
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• pp.111-119
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• 2022

The occurrence of cyanobacterial blooming and the contaminant sources were analyzed in the downstream of Jecheon Stream, a tributary of Chungju Reservoir. The concentrations of chlorophyll a at the Myungseo Fishing Point (GPS; 37°03'25.5"N, 128°03'13.6"E) were 399.2 and 184.8 mg m^-3 on October 18, 2015 and September 25, 2016, respectively, and the concentrations of total microcystins, a cyanobacterial toxin mainly produced by Microcystis, were 124.09 and 79.71 ㎍ L^-1, respectively. The occurrence of cyanobacterial blooming at the downstream of Jecheon Stream was closely related to the water level of Chungju Reservoir. The cyanobacterial blooming occurred after the increase of water level in Chungju Reservoir, when the water body stagnated. As a result of analyzing National Water Quality Monitoring Data of the upper region of Jecheon Stream, the main source of pollutant was Jangpyeong Stream, the tributary of Jecheon Stream, and the discharge water from Jecheon Wastewater Treatment Plant located in Jangpyeong Stream was considered to be the most important source of contaminant.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.321-335
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• 2023

Monitoring sediment loads in natural rivers is the key process in river engineering, but it is costly and dangerous. In practice, suspended loads are directly measured, and total loads, which is a summation of suspended loads and bed loads, are estimated. This study proposes a real-time sediment discharge monitoring system using the horizontal acoustic Doppler current profiler (H-ADCP) and support vector regression (SVR). The proposed system is comprised of the SVR model for suspended sediment concentration (SVR-SSC) and for total loads (SVR-Q_TL), respectively. SVR-SSC estimates SSC and SVR-Q_TL mimics the modified Einstein procedure. The grid search with K-fold cross validation (Grid-CV) and the recursive feature elimination (RFE) were employed to determine SVR's hyperparameters and input variables. The two SVR models showed reasonable cross-validation scores (R²) with 0.885 (SVR-SSC) and 0.860 (SVR-Q_TL). During the time-series sediment load monitoring period, we successfully detected various sediment transport phenomena in natural streams, such as hysteresis loops and sensitive sediment fluctuations. The newly proposed sediment monitoring system depends only on the gauged features by H-ADCP without additional assumptions in hydraulic variables (e.g., friction slope and suspended sediment size distribution). This method can be applied to any ADCP-installed discharge monitoring station economically and is expected to enhance temporal resolution in sediment monitoring.

• Journal of the Korean Institute of Gas
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• v.27 no.2
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• pp.71-78
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• 2023

In general, electric submersible pumps (ESPs), which have an average life of 1.0 to 1.5 years, experience a decrease in performance and a reduction in life of the pump depending on oil and gas reservoir characteristics and operating conditions in wells. As the result, the failure of ESP causes high well workover costs due to retrieval and installation, and additional costs due to shut down. In this study, a flow loop system was designed and established to predict the life of ESP in long­term operation of oil and gas wells, and the life cycle data of ESP from the time of installation to the time of failure was acquired and analyzed. Among the data acquired from the system, flow rate, inlet and outlet temperature and pressure, and the data of the vibrator installed on the outside of ESP were analyzed, and then the performance status according to long-term operation was classified into five stages: normal, advice I, advice II, maintenance, and failed. Through the experiments, it was found that there was a difference in the data trend by stage during the long­term operation of the ESP, and then the condition of the ESP was diagnosed and the failure of the pump was predicted according to the operating time. The results derived from this study can be used to develop a failure prediction program and data analysis algorithm for monitoring the condition of ESPs operated in oil and gas wells.

• Journal of Service Research and Studies
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• v.11 no.2
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• pp.118-130
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• 2021

This study designs and validates a greenhouse complex environmental control algorithm with a multi-phase processing scheme that can combine and control actuators according to the degree of change in the greenhouse environment. The composite environmental control system is a system in which the complex environmental controller analyzes the information detected by sensors and operates appropriately actuators to maintain the crop growth environment. A composite environmental controller directs control devices driving actuators through a composite environmental control algorithm, which calculates the values necessary for the operation of the control devices. Most existing algorithms carry out control procedures on a single phase by iteration cycle, which can cause abnormal changes in the greenhouse environment due to errors in output. The proposed algorithm distributes control procedures over multiple phases: environmental control, environmental control, and device operation, and every iteration cycle, detects environmental changes in the environmental control phase first, and then combines control devices that can control the environment in the environmental control phase, and finally, performs the controls to derive the actuators in the device operation phase. The proposed algorithm is designed based on the analysis of the relationship between greenhouse environmental elements and control devices deriving actuators. According to verification analysis, the multi-phase processing scheme provides room to modify or supplement the setting value and enables the control devices to reflect changes in the associated environmental components.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.817-823
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• 2023

Manufacturing plants face the challenge of reducing energy use in response to climate change. Reducing energy consumption can be seen as one of the most important issues, such as reducing production costs and improving efficiency. Among manufacturing industries, the increase in energy consumption in the food industry is gradually increasing along with the improvement of the standard of living and the increase in population. In order to save energy in food processing plants, it is important to identify and analyze energy consumption characteristics in energy-consuming processes. Prior to this, it is necessary to monitor and analyze existing energy consumption to derive reduction measures. In this study, a small and medium-sized food processing plant producing processed meat products was used as a case study to identify and analyze the energy consumption structure at typical cycle/stage level of the batch heating process. From this, we tried to establish realistic and quantitative goals that can be obtained under individual process operating conditions. The results of this study will be used as basic data for the development of diffusion and pervasive energy saving FEMS technology for common core processes of food factories of small and medium-sized enterprises in the future.