• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1071-1079
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• 2020

For integrated water management, it is essential to secure basic data such as the amount of agricultural water intake. The river water intake through the intake weir is carried out through the agricultural irrigation canal, and a method for measuring the quantity of water intake is required to suit the characteristics of the measuring points. In this study, the accuracy of the calculated flow data was determined by applying a microwave water surface current meter. The microwave water surface current meter is a method of calculating surface velocity using doppler effect, which is mainly used in high-velocities situations such as flood. Surface velocity is difficult to represent the average velocity of the entire section at low dicharges or high wind speeds, it is considered to be low in continuous utilization throughout the year, and it is necessary to verify whether the measurement using an microwave water surface curren meter is appropriate in agricultural irrigation canal. The data measured with an microwave water surface curren meter were compared with the actual flow data to calculate the intake data in agricultural irrigation canal. In agricultural irrigation canal, the low-level discharge calculated using an microwave water surface current meter at a minimum velocity of about 0.3 m/s and a minimum discharge of about 1.0 m3/s or higher was found to have a high tendency and accuracy compared to the standard discharge, especially when the high discharge was high. Although effective results can be obtained in terms of quantity at low discharge, it is deemed that subsequent studies are needed to calculate the average discharge of the cross section at low discharge, given that the trend of data is unstable. Through this study, it is suggested that it is appropriate to calculate the amount of water intake through the microwave water surface current meter in artificial waterways with a certain discharge or higher, so it is expected to be widely distributed as a method for measuring river water intake.

• Journal of Food Hygiene and Safety
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• v.36 no.1
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• pp.68-76
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• 2021

Foodborne outbreaks frequently occur worldwide and result in huge economic losses. It is the therefore important to estimate the costs associated with foodborne diseases to minimize the economic damage. At the same time, it is difficult to accurately estimate the economic loss from foodborne disease due to a wide variety of cost components. In Korea, there are a limited number of analytical studies attempting to estimate such costs. In this study we investigated the components of economic cost used in foreign countries to better estimate the cost of foodborne disease in Korea. Seven recent studies investigated the cost components used to estimate the cost of foodborne disease in humans. This study categorized the economic loss into four types of cost: direct costs, indirect costs, food business costs, and government administration costs. The healthcare costs most often included were medical (outpatient) and hospital costs (inpatient). However, these cost components should be selected according to the systems and budgets of medical services by country. For non-healthcare costs, several other studies considered transportation costs to the hospital as an exception to the cost of inpatient care. So, further discussion is needed on whether to consider inpatient care costs. Among the indirect costs, premature mortality, lost productivity, lost leisure time, and lost quality of life/pain, grief and suffering costs were considered, but the opportunity costs for hospital visits were not considered in any of the above studies. As with healthcare costs, government administration costs should also be considered appropriate cost components due to the difference in government budget systems, for example. Our findings will provide fundamental information for economic analysis associated with foodborne diseases to improve food safety policy in Korea.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.1
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• pp.1-12
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• 2021

To investigate the effect of freshwater discharge on the seawater circulation in the semi-closed harbor, a 3-D hydrodynamic model was applied to the International Ferry Terminal (IFT). The model run is conducted for 45 days (from May 15 to June 30, 2020), and the reproducibility of the model for time-spatial variability of current velocity and salinity was verified by comparison with model results and observation data. There are two sources of freshwater towards inside of the IFT: Han River and water reservoir located in the eastern part of IFT. In residual current velocity results, the two-layer circulation (the seaward flow near surface and the landward flow near bottom)derived from the horizontal salinity gradient in only considering the discharge from a Han River is more developed than that considering both the Han River and water reservoir. This suggests that the impact of freshwater from the reservoir is greater in the IFT areas than that from a Han River. Additionally, the two-layer circulation is stronger in the IFT located in southern part than Incheon South Port located in northern part. This process is formed by the interaction between tidal current propagating into the port and freshwater discharge from a water reservoir, and flow with a low salinity (near 0 psu) is delivered into the IFT. This low salinity distribution reinforces the horizontal stratification in front of the IFT, and maintains a two-layer circulation. Therefore, local sources of freshwater input are considered to estimate for mass transport process associated with the seawater circulation within the harbor and It is necessary to perform a numerical model according to the real-time freshwater flow rate discharged.

• Clean Technology
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• v.27 no.1
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• pp.9-16
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• 2021

Since the active matrix organic light-emitting diode (AMOLED) encapsulation process is very vulnerable to moisture and oxygen, high-purity nitrogen with minimal moisture and oxygen must be used. In this study, a copper-based catalyst used to remove oxygen from nitrogen in the AMOLED encapsulation process was optimized. Two-component and three-component catalysts composed of CuO, Al2O3, or ZnO were prepared through a co-precipitation method. The prepared catalysts were characterized by using BET, XRD, TPR, and XRF analysis. In order to verify the oxygen removal performance of the catalyst, several catalytic reactions were conducted in a fixed bed reactor, and the corresponding oxygen contents were measured through an oxygen analyzer. In addition, reusability of the catalysts was proven through repetitive regeneration. The properties and oxygen removal capacity of the catalysts prepared with CuO and Al2O3 ratios of 6 : 4, 7 : 3, and 8 : 2 were compared. The number of active sites of the catalyst with a ratio of CuO and Al2O3 of 8 : 2 was the highest among the 2-component catalysts. Moreover, the reducibility of the catalyst with a ratio of CuO and Al2O3 of 8 : 2 was the best as it had the highest CuO dispersion. As a result, the oxygen removal ability of the catalyst with a ratio of CuO and Al2O3 of 8 : 2 was the best among the 2-component catalysts. The best oxygen removal capacity was obtained when 2wt% of ZnO was added to the sub-optimized catalyst (i.e., CuO : Al2O3 = 8 : 2) probably due to its outstanding reducibility. Furthermore, the optimized catalyst kept its performance during a couple of regeneration tests.

• Science of Emotion and Sensibility
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• v.24 no.4
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• pp.139-148
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• 2021

This study aimed to verify how a multisensory storytelling-based activity-based intervention affects social interaction in children with cerebral palsy. As a quasi-experimental investigation, this study used a single-blind, two-group pre-post test design. This study comprised 24 children aged 7 to 8 y who had been diagnosed with spastic cerebral palsy and were classified as having GMFCS stages I to III. Twelve children were randomly assigned to experimental and control groups, with neither the children nor their guardians knowing which group they were placed in. The group program comprised 16 sessions of 60 min each, twice a week for eight weeks. The experimental group engaged in an activity-centered intervention centered on multisensory storytelling, whereas the control group engaged in structured physical activity. The activities were assessed using the peer relations skills scale to determine the extent to which social interaction had changed prior to and during the child's intervention. The SPSS 25.0 for Windows (IBM Corp, USA) application was used to analyze the data, and the significance level (α) for statistical verification was set to 0.05. Furthermore, the Wilcoxon Signed-Rank and Mann-Whitney U tests were used to assess the differences in social interaction between the experimental and control groups. Significant differences were observed in the total of the peer relationship skill scale and cooperation and empathy areas of the subtest in the intragroup change of the peer relationship skill scale between the experimental and control groups. However, the experimental group demonstrated a significant difference in the initiative area, whereas the control group demonstrated no significant difference. A significant difference was observed in the amount of change between the two groups in the initiative area and total of the subtest of peer relationship skills but no significant difference in the collaboration and empathy areas. We gave a multisensory storytelling-based activity-based intervention based on multisensory storytelling to children with cerebral palsy and saw a significant improvement in peer relationship skills. It may be proposed as an effective intervention strategy for children with cerebral palsy who struggle with social contact.

• Korean Journal of Cognitive Science
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• v.33 no.1
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• pp.51-75
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• 2022

Transcranial direct current stimulation (tDCS) is a non-invasive brain stimulation that is able to alter neuronal activity in particular brain regions. Many studies have researched how tDCS modulates neuronal activity and reorganizes neural networks. However it is difficult to conclude the effect of brain stimulation because the studies are heterogeneous with respect to the stimulation parameter as well as individual difference. It is not fully in agreement with the effects of brain stimulation. In particular few studies have researched the reason of variability of brain stimulation in response to time so far. The study investigated individual variability of brain stimulation based on circadian rhythm and chronotype. Participants were divided into two groups which are morning type and evening type. The experiment was conducted by Zoom meeting which is video meeting programs. Participants were sent experiment tool which are Muse(EEG device), tdcs device, cell phone and cell phone holder after manuals for experimental equipment were explained. Participants were required to make a phone in frount of a camera so that experimenter can monitor online EEG data. Two participants who was difficult to use experimental devices experimented in a laboratory setting where experimenter set up devices. For all participants the accuracy of 98% was achieved by SVM using leave one out cross validation in classification in the the effects of morning stimulation and the evening stimulation. For morning type, the accuracy of 92% and 96% was achieved in classification in the morning stimulation and the evening stimulation. For evening type, it was 94% accuracy in classification for the effect of brain stimulation in the morning and the evening. Feature importance was different both in classification in the morning stimulation and the evening stimulation for morning type and evening type. Results indicated that the effect of brain stimulation can be explained with brain state and trait. Our study results noted that the tDCS protocol for target state is manipulated by individual differences as well as target state.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1095-1105
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• 2021

The advancement of dam operation is further required due to the upcoming rainy season, typhoons, or torrential rains. Besides, physical models based on specific rules may sometimes have limitations in controlling the release discharge of dam due to inherent uncertainty and complex factors. This study aims to forecast the water level of the nearest station to the dam multi-timestep-ahead and evaluate the availability when it makes a decision for a release discharge of dam based on LSTM (Long Short-Term Memory) of deep learning. The LSTM model was trained and tested on eight data sets with a 1-hour temporal resolution, including primary data used in the dam operation and downstream water level station data about 13 years (2009~2021). The trained model forecasted the water level time series divided by the six lead times: 1, 3, 6, 9, 12, 18-hours, and compared and analyzed with the observed data. As a result, the prediction results of the 1-hour ahead exhibited the best performance for all cases with an average accuracy of MAE of 0.01m, RMSE of 0.015 m, and NSE of 0.99, respectively. In addition, as the lead time increases, the predictive performance of the model tends to decrease slightly. The model may similarly estimate and reliably predicts the temporal pattern of the observed water level. Thus, it is judged that the LSTM model could produce predictive data by extracting the characteristics of complex hydrological non-linear data and can be used to determine the amount of release discharge from the dam when simulating the operation of the dam.

• Korean Chemical Engineering Research
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• v.60 no.4
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• pp.535-543
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• 2022

A CPFD (Computational particle fluid dynamics) model of solar fluidized bed receiver of silicon carbide (SiC: average d_p=123 ㎛) particles was established, and the model was verified by comparing the simulation and experimental results to analyze the effect of particle behavior on the performance of the receiver. The relationship between the heat-absorbing performance and the particles behavior in the receiver was analyzed by simulating their behavior near bed surface, which is difficult to access experimentally. The CPFD simulation results showed good agreement with the experimental values on the solids holdup and its standard deviation under experimental condition in bed and freeboard regions. The local solid holdups near the bed surface, where particles primarily absorb solar heat energy and transfer it to the inside of the bed, showed a non-uniform distribution with a relatively low value at the center related with the bubble behavior in the bed. The local solid holdup increased the axial and radial non-uniformity in the freeboard region with the gas velocity, which explains well that the increase in the RSD (Relative standard deviation) of pressure drop across the freeboard region is responsible for the loss of solar energy reflected by the entrained particles in the particle receiver. The simulation results of local gas and particle velocities with gas velocity confirmed that the local particle behavior in the fluidized bed are closely related to the bubble behavior characterized by the properties of the Geldart B particles. The temperature difference of the fluidizing gas passing through the receiver per irradiance (∆T/I_DNI) was highly correlated with the RSD of the pressure drop across the bed surface and the freeboard regions. The CPFD simulation results can be used to improve the performance of the particle receiver through local particle behavior analysis.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

• Journal of Appropriate Technology
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• v.6 no.2
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• pp.174-182
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• 2020

The permissible limit of ammonia concentration in drinking water recommended by the World Health Organization (WHO) is 1.5 mg/L. However, in the case of groundwater in Kathmandu, Nepal, the concentration of ammonia fluctuates dramatically from 0 to 120 mg/L at different locations and groundwater depths (Chapagain et al., 2010). Such a high concentration of ammonia causes aesthetic problems in drinking water, such as bad taste and odor; hence, prior treatment is required. In Kathmandu, half of the population utilizes groundwater, which is also employed for drinking water, but owing to a lack of knowledge of household water filters, residents of Kathmandu tend to depend greatly on commercially available jar water than on the installation of a proper household filtration method. Thus, in our study, we employed adsorption and reverse osmosis (RO) as two of the most viable decentralized/household treatment options to address the issue of high contamination of ammonia in drinking water. We evaluated their performances from technical and the economic perspectives using synthetically prepared groundwater at varying ammonia concentrations (50 mg/L and 15 mg/L). Consequently, it was found that adsorption via ion exchange (IE) resin was a comparatively better ammonia removal technology than RO, with 100% ammonia removal even after regeneration; the removal by RO was limited to up to 90%. Furthermore, our study suggests that IE is the most suitable ammonia removal technology for places with lower water consumption (< 50 L/day), whereas RO seemed to be a cost-effective technology for places with higher water consumption, where the daily water demand exceeds 50 L/day. Lastly, these assessments suggest that installing a suitable household treatment system would be more efficient and sustainable from both technical and economic points of view than purchasing commercially bottled water.