• Journal of Korean Society of Disaster and Security
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• v.13 no.4
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• pp.75-92
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• 2020

In most cases of the water balance analysis, the return flow ratio for each water supply was uniformly determined and applied, so it has been contained a problem that the volume of available water would be incorrectly calculated. Therefore, sewage and wastewater among the return water were focused in this study and the data-driven model was developed to forecast the outflow from the sewage treatment plant. The forecasting results of LSTM (Long Short-Term Memory), GRU (Gated Recurrent Units), and SVR (Support Vector Regression) models, which are mainly used for forecasting the time series data in most fields, were compared with the observed data to determine the optimal model parameters for forecasting outflow. As a result of applying the model, the root mean square error (RMSE) of the GRU model was smaller than those of the LSTM and SVR models, and the Nash-Sutcliffe coefficient (NSE) was higher than those of others. Thus, it was judged that the GRU model could be the optimal model for forecasting the outflow in sewage treatment plants. However, the forecasting outflow tends to be underestimated and overestimated in extreme sections. Therefore, the additional data for extreme events and reducing the minimum time unit of input data were necessary to enhance the accuracy of forecasting. If the water use of the target site was reviewed and the additional parameters that could reflect seasonal effects were considered, more accurate outflow could be forecasted to be ready for climate variability in near future. And it is expected to use as fundamental resources for establishing a reasonable river water management system based on the forecasting results.

• Journal of Food Hygiene and Safety
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• v.38 no.3
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• pp.89-98
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• 2023

Currently, no guidelines exist regarding the maximum residues of pesticides in edible oil which is a processed food commonly consumed in Korea. This lack of guidelines hinders the evaluation of the safety of edible oil in terms of pesticide contamination. In this study, an analysis method based on heat distillation and GC-MS/MS was established by optimizing the extraction and purification procedure for 68 pesticides. Important variables in the thermal distillation procedure included heating temperature and time, and we found the nitrogen flow rate as a mobile phase and the type of dissolving solvent were not considerably affected. The determination coefficient (R²) of the residual pesticide was 0.99 or higher, and the quantitative limit (LOQ) was 0.01-0.02 mg/L. The average recovery rate (n=5) was 66.1-120.0% and the relative standard deviation was lower than ±10% when 68 pesticides were spiked at concentrations of 0.01-0.02, 0.1, and 0.5 mg/L. In addition, the within-laboratory precision was less than ±11%, meeting the Korea Food and Drug Safety Evaluation Institute's Guidelines on Standard Procedures for Preparing Food Testing Methods (2016). Therefore, the test method developed in this study can be used as a test method for managing the safety of the residual pesticide concentration in edible oil.

• Journal of Korea Water Resources Association
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• v.50 no.7
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• pp.455-465
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• 2017

Understanding of the two-dimensional velocity field is crucial in terms of analyzing various hydrodynamic and fluvial processes in the riverine environments. Until recently, many numerical models have played major roles of providing such velocity field instead of in-situ flow measurements, because there were limitations in instruments and methodologies suitable for efficiently measuring in the broad range of river reaches. In the last decades, however, the advent of modernized instrumentations started to revolutionize the flow measurements. Among others, acoustic Doppler current profilers (ADCPs) became very promising especially for accurately assessing streamflow discharge, and they are also able to provide the detailed velocity field very efficiently. Thus it became possible to capture the velocity field only with field observations. Since most of ADCPs measurements have been mostly conducted in the cross-sectional lines despite their capabilities, it is still required to apply appropriate interpolation methods to obtain dense velocity field as likely as results from numerical simulations. However, anisotropic nature of the meandering river channel could have brought in the difficulties for applying simple spatial interpolation methods for handling dynamic flow velocity vector, since the flow direction continuously changes over the curvature of the channel shape. Without considering anisotropic characteristics in terms of the meandering, therefore, conventional interpolation methods such as IDW and Kriging possibly lead to erroneous results, when they dealt with velocity vectors in the meandering channel. Based on the consecutive ADCP cross-sectional measurements in the meandering river channel. For this purpose, the geographic coordinate with the measured ADCP velocity was converted from the conventional Cartesian coordinate (x, y) to a curvilinear coordinate (s, n). The results from application of A-VIM showed significant improvement in accuracy as much as 41.5% in RMSE.

• Journal of Wetlands Research
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• v.26 no.2
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• pp.147-159
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• 2024

Lack of streamflow observations makes model calibration difficult and limits model performance improvement. Satellite-based remote sensing products offer a new alternative as they can be actively utilized to obtain hydrological data. Recently, several studies have shown that artificial intelligence-based solutions are more appropriate than traditional conceptual and physical models. In this study, a data-driven approach combining various recurrent neural networks and decision tree-based algorithms is proposed, and the utilization of satellite remote sensing information for AI training is investigated. The satellite imagery used in this study is from MODIS and SMAP. The proposed approach is validated using publicly available data from 25 watersheds. Inspired by the traditional regionalization approach, a strategy is adopted to learn one data-driven model by integrating data from all basins, and the potential of the proposed approach is evaluated by using a leave-one-out cross-validation regionalization setting to predict streamflow from different basins with one model. The GRU + Light GBM model was found to be a suitable model combination for target basins and showed good streamflow prediction performance in ungauged basins (The average model efficiency coefficient for predicting daily streamflow in 25 ungauged basins is 0.7187) except for the period when streamflow is very small. The influence of satellite remote sensing information was found to be up to 10%, with the additional application of satellite information having a greater impact on streamflow prediction during low or dry seasons than during wet or normal seasons.

• Tuberculosis and Respiratory Diseases
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• v.45 no.2
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• pp.380-387
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• 1998

Background: Minimal pressure support(PSmin) is a level of pressure support which offset the imposed work of breathing(WOBimp) developed by endotracheal tube and ventilator circuits in pressure support ventilation While the lower applied level of pressure support compared to PSmin could induce respiratory muscle fatigue, the higher level than PSmin could keep respiratory muscle rest resulting in prolongation of weaning period during weaning from mechanical ventilation PSmin has been usually applied in the level of 5~10 cm$H_2O$, but the accurate level of PSmin is difficult to be determinated in individual cases. PSmin is known to be calculated by using the equation of "PSmin = peak inspiratory flow rate during spontaneus ventilation$\times$total ventilatory system resistance", but correlation of calculated PSmin and measured PSmin has not been known. The objects of this study were firstly to assess whether customarily applied pressure support level of 5~10 cm$H_2O$ would be appropriate to offset the imposed work of breathing among the patients under weaning process, and secondly to estimate the correlation between the measured PSmin and calculated PSmin. Method : 1) Measurement of PSmin : Intratracheal pressure changes were measured through Hi-Lo jet tracheal tube (8mm in diameter, Mallinckroft, USA) by using pulmonary monitor(CP-100 pulmonary monitor, Bicore, USA), and then pressure support level of mechanical ventilator were increased until WOBimp was reached to 0.01 J/L or less. Measured PSmin was defined as the lowest pressure to make WOBimp 0.01 J/L or less. 2) Calculation of PSmin : Peak airway pressure(Ppeak), plateau airway pressure(Pplat) and mean inspiratory flow rate of the subjects were measured on volume control mode of mechanical ventilation after sedation. Spontaneous peak inspiratory flow rates were measured on CPAP mode(O cm$H_2O$). Thereafter PSmin was calculated by using the equation "PSmin = peak inspiratory flow rate$\times$R, R = (Ppeak-Pplat)/mean inspiratory flow rate during volume control mode on mechanical ventilation". Results: Sixteen patients who were considered as the candidate for weaning from mechanical ventilation were included in the study. Mean age was 64(${\pm}14$) years, and the mean of total ventilation times was 9(${\pm}4$) days. All patients except one were males. The measured PSmin of the subjects ranged 4.0~12.5cm$H_2O$ in 14 patients. The mean level of PSmin was 7.6(${\pm}2.5\;cmH_2O$) in measured PSmin, 8.6 (${\pm}3.25\;cmH_2O$) in calculated PSmin Correlation between the measured PSmin and the calculated PSmin is significantly high(n=9, r=0.88, p=0.002). The calculated PSmin show a tendancy to be higher than the corresponding measured PSmin in 8 out of 9 subjects(p=0.09). The ratio of measured PSmin/calculated PSmin was 0.81(${\pm}0.05$). Conclusion: Minimal pressure support levels were different in individual cases in the range from 4 to 12.5 cm$H_2O$. Because the equation-driven calculated PSmin showed a good correlation with measured PSmin, the application of equation-driven PSmin would be then appropriate compared with conventional application of 5~10 cm$H_2O$ in patients under difficult weaning process with pressure support ventilation.