• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.761-774
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• 2022

Accurate hydrologic prediction is essential to analyze the effects of drought, flood, and climate change on flow rates, water quality, and ecosystems. Disentangling the uncertainty of the hydrological model is one of the important issues in hydrology and water resources research. Hydrologic data assimilation (DA), a technique that updates the status or parameters of a hydrological model to produce the most likely estimates of the initial conditions of the model, is one of the ways to minimize uncertainty in hydrological simulations and improve predictive accuracy. In this study, the two ensemble-based sequential DA techniques, ensemble Kalman filter, and particle filter are comparatively analyzed for the daily discharge simulation at the Yongdam catchment using airGRdatassim. The results showed that the values of Kling-Gupta efficiency (KGE) were improved from 0.799 in the open loop simulation to 0.826 in the ensemble Kalman filter and to 0.933 in the particle filter. In addition, we analyzed the effects of hyper-parameters related to the data assimilation methods such as precipitation and potential evaporation forcing error parameters and selection of perturbed and updated states. For the case of forcing error conditions, the particle filter was superior to the ensemble in terms of the KGE index. The size of the optimal forcing noise was relatively smaller in the particle filter compared to the ensemble Kalman filter. In addition, with more state variables included in the updating step, performance of data assimilation improved, implicating that adequate selection of updating states can be considered as a hyper-parameter. The simulation experiments in this study implied that DA hyper-parameters needed to be carefully optimized to exploit the potential of DA methods.

• Journal of the Korean Society of Radiology
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• v.15 no.6
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• pp.781-788
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• 2021

Due to the high sensitivity to radiation, excessive exposure needs to be prevented by accurately measuring the dose irradiated to the skin during radiation therapy. Although clinical trials use dosimeters such as film, OSLD, TLD, glass dosimeter, etc. to measure skin dose, these dosimeters have difficulty in accurate dosimetry on skin curves. In this study, to solve these problems, we developed a skin dosimeter that can be attached according to human flexion and evaluated its response characteristics. For the manufacture of the dosimeter, lead oxide (PbO) with high atomic number (Z_Pb: 82, Z_O: 8) and density (9.53 g/cm³) and silicon binders that can bend according to human flexion were used. In the case of a dosimeter made of PbO material, the performance degradation has been prevented by using parylene and others due to the presence of degradation due to oxidation, but the previously used parylene is affected by bending, so a new form of passive layer was produced and applied to the skin dosimeter. The characteristic evaluation of the skin dosimeter was evaluated by analyzing SEM, reproducibility, and linearity. Through SEM analysis, bending was evaluated, reproducibility and linearity at 6 MeV energy were evaluated, and applicability was assessed with a skin dosimeter. As a result of observing the dosimeter surface through SEM analysis, the parylene passive layer PbO dosimeter with the positive layer raised to the parylene produced cracks on the surface when bent. On the other hand, no crack was observed in the silicon passive layer PbO dosimeter, which was raised to silicon passive layer. In the reproducibility measurement results, the RSD of the silicon passive layer PbO dosimeter was 1.47% which satisfied the evaluation criteria RSD 1.5% and the linearity evaluation results showed the R² value of 0.9990, which satisfied the evaluation criteria R² 9990. The silicon passive layer PbO dosimeter was evaluated to be applicable to skin dosimeters by demonstrating high signal stability, precision, and accuracy in reproducibility and linearity, without cracking due to bending.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1615-1633
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• 2023

Sargassum horneri is one of the floating algae in the sea, which breeds in large quantities in the Yellow Sea and East China Sea and then flows into the coast of Republic of Korea, causing various problems such as destroying the environment and damaging fish farms. In order to effectively prevent damage and preserve the coastal environment, the development of Sargassum horneri detection algorithms using satellite-based remote sensing technology has been actively developed. However, incorrect detection information causes an increase in the moving distance of ships collecting Sargassum horneri and confusion in the response of related local governments or institutions,so it is very important to minimize false detections when producing Sargassum horneri spatial information. This study applied technology to automatically remove false detection results using the GOCI-II-based Sargassum horneri detection algorithm of the National Ocean Satellite Center (NOSC) of the Korea Hydrographic and Oceanography Agency (KHOA). Based on the results of analyzing the causes of major false detection results, it includes a process of removing linear and sporadic false detections and green algae that occurs in large quantities along the coast of China in spring and summer by considering them as false detections. The technology to automatically remove false detection was applied to the dates when Sargassum horneri occurred from February 24 to June 25, 2022. Visual assessment results were generated using mid-resolution satellite images, qualitative and quantitative evaluations were performed. Linear false detection results were completely removed, and most of the sporadic and green algae false detection results that affected the distribution were removed. Even after the automatic false detection removal process, it was possible to confirm the distribution area of Sargassum horneri compared to the visual assessment results, and the accuracy and precision calculated using the binary classification model averaged 97.73% and 95.4%, respectively. Recall value was very low at 29.03%, which is presumed to be due to the effect of Sargassum horneri movement due to the observation time discrepancy between GOCI-II and mid-resolution satellite images, differences in spatial resolution, location deviation by orthocorrection, and cloud masking. The results of this study's removal of false detections of Sargassum horneri can determine the spatial distribution status in near real-time, but there are limitations in accurately estimating biomass. Therefore, continuous research on upgrading the Sargassum horneri monitoring system must be conducted to use it as data for establishing future Sargassum horneri response plans.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1109-1123
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• 2020

In South Korea with forest as a major land cover class (over 60% of the country), many wildfires occur every year. Wildfires weaken the shear strength of the soil, forming a layer of soil that is vulnerable to landslides. It is important to identify the severity of a wildfire as well as the burned area to sustainably manage the forest. Although satellite remote sensing has been widely used to map wildfire severity, it is often difficult to determine the severity using only the temporal change of satellite-derived indices such as Normalized Difference Vegetation Index (NDVI) and Normalized Burn Ratio (NBR). In this study, we proposed an approach for determining wildfire severity based on machine learning through the synergistic use of Sentinel-1A Synthetic Aperture Radar-C data and Sentinel-2A Multi Spectral Instrument data. Three wildfire cases-Samcheok in May 2017, Gangreung·Donghae in April 2019, and Gosung·Sokcho in April 2019-were used for developing wildfire severity mapping models with three machine learning algorithms (i.e., Random Forest, Logistic Regression, and Support Vector Machine). The results showed that the random forest model yielded the best performance, resulting in an overall accuracy of 82.3%. The cross-site validation to examine the spatiotemporal transferability of the machine learning models showed that the models were highly sensitive to temporal differences between the training and validation sites, especially in the early growing season. This implies that a more robust model with high spatiotemporal transferability can be developed when more wildfire cases with different seasons and areas are added in the future.

• Journal of Food Hygiene and Safety
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• v.33 no.4
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• pp.289-295
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• 2018

The aim of this study was to develop and validate an analytical method for determining the presence of wogonin, quercetin, and quercetin-3-O-glucuronide in extracts of Nelumbo nucifera, Morus alba L., and Raphanus sativus mixtures. We evaluated the specificity, linearity, precision, accuracy, limit of detection (LOD), and limit of quantification (LOQ) of analytical methods for wogonin, quercetin, and quercetin-3-O-glucuronide using high performance liquid chromatography. Our result showed that the correlation coefficients of the calibration curve for wogonin, quercetin, and quercetin-3-O-glucuronide were 0.9999. The LOD for wogonin, quercetin, and quercetin-3-O-glucuronide ranged from 0.09 to 0.16 and those for the LOQ ranged from 0.26 to $0.48{\mu}g/mL$. The inter-day and intra-day precision values of wogonin, quercetin, and quercetin-3-O-glucuronide ranged from 0.74 to 1.87 and from 0.28 to 1.12%, respectively. The inter-day and intra-day accuracies were 99.96~115.88% and 99.73~114.81%, respectively. Therefore, the analytical method was validated for the detection of wogonin, quercetin, and quercetin-3-O-glucuronide in extracts of Nelumbo nucifera, Morus alba L., and Raphanus sativus mixtures.

• Tuberculosis and Respiratory Diseases
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• v.62 no.4
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• pp.276-283
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• 2007

Background: A national health care initiative recommends routine spirometry screening of all smokers over age 45 or patients with respiratory symptoms. In response to the recommendation, new, simple, and inexpensive desktop spirometers for the purpose of promoting widespread spirometric screening were marketed. The performance of these spirometers was evaluated in vivo testing with healthy subjects. However, the clinical setting allows spirometric assessment of various pathologic combinations of flow and volume. Objective: The aim of this study was to compare the accuracy of a desktop spirometer to a standard laboratory spirometer, in a clinical setting with pathologic pulmonary function. Method: In a health check-up center, where screening pulmonary funct test was performed using the HI-801 spirometer. Subjects who revealed the ventilation defect in screening spirometry, performed the spirometry again using the standard Vmax spectra 22d spirometer in a tertiary care hospital pulmonary function laboratory. Pulmonary function test with both spirometer was performed according to the guidelines of the American Thoracic Society. Results: 109 patients were enrolled. Pulmonary function measurements (FVC, $FEV_1$, PEFR, FEF25%-75%) from the HI-801 correlated closely (r=0.94, 0.93, 0.81, 0.84, respectively) with those performed with the Vmax spectra 22d and showed the good limits of agreement and differences between the 2 devices; FVC +0.35 L, $FEV_1$ +0.16 L, PEFR +1.85 L/s, FEF25%-75%-0.13 L/s. With the exception of $FEV_1$, FEF25%-75%, these differences were significant(p<0.05) but small. Conclusion: The HI-801 spirometer is comparable to the standard laboratory spirometer, Vmax spectra 22d, with high accurary for $FEV_1$ and FVC and acceptable differences for clinical use.

• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.9
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• pp.1091-1096
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• 2017

The aim of this study was the validation of a modified analytical method for determination of oxypaeoniflorin and paeoniflorin in Moutan Cortex Radicis extract. For validation of the analytical method, we modified established analytical methods and validated improvement. For validation, the specificity, linearity, precision, accuracy, limit of detection (LOD), and limit of quantification of oxypaeoniflorin and paeoniflorin were measured by high performance liquid chromatography. The results show that the correlation coefficients of the calibration curve for oxypaeoniflorin and paeoniflorin were 1.0000 and 0.9998, respectively. The LOD for oxypaeoniflorin and paeoniflorin were $0.23{\mu}g/mL$ and $0.25{\mu}g/mL$, respectively. The inter-day and intra-day precision values of oxypaeoniflorin and paeoniflorin were 0.70~3.19% and 1.74~2.43%, and 0.32~0.92% and 0.62~2.28%, respectively. The inter-day and intra-day accuracies of oxypaeoniflorin and paeoniflorin were 98.33~102.11% and 97.72~118.12%, and 98.44~101.56% and 97.10~112.00%, respectively. Therefore, the analytical method was validated for the detection of oxypaeoniflorin and paeoniflorin in Moutan Cortex Radicis.

• Journal of Food Hygiene and Safety
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• v.37 no.3
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• pp.143-148
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• 2022

This study was to investigate an analytical method for determining dieckol content in Ecklonia stolonifera extract. According to the guidelines of International Conference on Harmonization. Method validation was performed by measuring the specificity, linearity, precision, accuracy, limit of detection (LOD), and limit of quantification (LOQ) of dieckol using high-performance liquid chromatography-photodiode array. The results showed that the correlation coefficient of calibration curve (R²) for dieckol was 0.9997. The LOD and LOQ for dieckol were 0.18 and 0.56 ㎍/mL, respectively. The intra- and inter-day precision values of dieckol were approximately 1.58-4.39% and 1.37-4.64%, respectively. Moreover, intra- and inter-day accuracies of dieckol were approximately 96.91-102.33% and 98.41-105.71%, respectively. Thus, we successfully validated the analytical method for estimating dieckol content in E. stolonifera extract.

• Journal of Food Hygiene and Safety
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• v.39 no.2
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• pp.72-82
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• 2024

This study aimed to develop a scientifically and systematically standardized xylooligosaccharide analytical method that can be applied to products with various formulations. The analysis method was conducted using HPLC with Cadenza C₁₈ column, involving pre-column derivatization with 1-phenyl-3-methyl-5-pyrazoline (PMP) and UV detection at 254 nm. The xylooligosaccharide content was analyzed by converting xylooligosaccharide into xylose through acid hydrolysis. The pre-treated methods were compared and evaluated by varying sonication time, acid hydrolysis time, and concentration. Optimal equipment conditions were achieved with a mobile phase consisting of 20 mM potassium phosphate buffer (pH 6)-acetonitrile (78:22, v/v) through isocratic elution at a flow rate of 0.5 mL/min (254 nm). Furthermore, we validated the advanced standardized analysis method to support the suitability of the proposed analytical procedure such as specificity, linearity, detection limits (LOD), quantitative limits (LOQ), accuracy, and precision. The standardized analysis method is now in use for monitoring relevant health-functional food products available in the market. Our results have demonstrated that the standardized analysis method is expected to enhance the reliability of quality control for healthy functional foods containing xylooligosaccharide.

• Analytical Science and Technology
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• v.33 no.3
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• pp.151-158
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• 2020

Alcohol, which can easily be obtained in the same way as ordinary beverages, is harmful enough to cause death due to excessive drinking and chronic alcohol intake, so it is important to maintain a proper amount of drinking and healthy drinking habits. In addition, the incidence of behavioral disturbances and impaired judgments that can be caused by chronic alcohol drinking of more than adequate amounts of alcohol is also significant. Accordingly it is very useful for forensic science to check whether the person involved is drunken or is alcoholism state in various accidents. Currently, in Korea, alcohol consumption is determined by detecting the level of alcohol or alcohol metabolism 'ethyl glucuronide (EtG)' in blood or urine samples. However, analysis of alcohol or EtG in blood or urine can only provide information about the current state of alcohol consumption because of a narrow window of detection time. Therefore, it is important to analyze the EtG as a long-term direct alcohol metabolite bio-marker in human hair and to investigate relationship between alcohol consumption and EtG concentration for the evaluation of chronic ethanol consumption. In this study, we established an analytical method for the detection of EtG in Korean hair efficiently and validated selectivity, linearity, limits of detection (LOD), limits of quantification (LOQ), matrix effect, recovery, process efficiency, accuracy and precision using liquid chromatography tandem mass spectrometry (LC-MS/MS). In addition, the assay performance was evaluated in Korean social drinker's hair and the postmortem hair of a chronic alcoholism. The results of this study can be useful in monitoring the alcohol abuse of Korean in clinical cases and legal procedures related to custody and provide a useful tool to evaluate postmortem diagnosis of alcoholic ketoacidosis in forensics.