• Particle and aerosol research
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• v.16 no.4
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• pp.131-140
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• 2020

Air pollutants emitted from chimneys of coal-fired power plants are considered to be a major source of fine particulate matter in the atmosphere. In order to manage fine particle in the chimney of a coal-fired power plant, it is necessary to know the concentration of fine particle emitted in real time, but the current system is difficult. In this study, a real-time measurement system for chimney fine particle was developed, and measurements were performed on six coal-fired power plants. Through the measurements, the mass concentration distribution according to the particle size could be secured. All six chimneys showed bimodal distribution, and the count median diameters of each mode were 0.5 and 1.1 ㎛. In addition, it was compared with the gravimetric measurement method, and it was determined that the relative accuracy for PM10 was within 20%, and the value measured using the developed measuring instrument was reliable. Finally, three power plants were continuously measured for one month, and as a result of comparing the concentration of PM10 according to the amount of power generation, it was confirmed that the PM10 discharged from the chimney increased in the form of an exponential function according to the amount of power generation.

• Journal of Food Hygiene and Safety
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• v.36 no.1
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• pp.34-41
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• 2021

The purpose of this research is to improve analysis methods of determining the contents of fatty acids in infant formulas and follow-up formulas. A gas chromatography (GC) method was performed on a GC system coupled to flame ionization detector, with a fused silica capillary column (SP2560, 100 m×0.25 mm, 0.20 ㎛). The method was validated using standard reference material (SRM, NIST 1849a). Performance parameters for method validation such as specificity, linearity, limits of detection (LOD) and quantification (LOQ), accuracy and precision were examined. The linearity of standard solution with correlation coefficient was higher than 0.999 in the range of 0.1-5 mg/mL. The LOD and LOQ were 0.01-0.06 mg/mL and 0.03-0.2 mg/mL, respectively. The recovery using standard reference material was confirmed and the precision was found to be between 0.8% and 2.9% relative standard deviation (RSD). Optimized methods were applied in sample analysis to verify the reliability. All the tested products had acceptable contents of fatty acids compared with component specification for nutrition labeling. The result of this research will provide efficient experimental information and strengthen the management of nutrients in infant formula and follow-up formula.

• Journal of Digital Convergence
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• v.19 no.1
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• pp.475-483
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• 2021

The purpose of this study is to identify the temporal and spatial characteristics of pass accuracy by utilizing the second processing data and official records collected from the 2018 FIFA World Cup Russia video data. For a total of 128 games, the success rate of passes based on the results of the game, passing time, and passing position was two-way ANOVA with repeated measure. The results showed no difference between winning and losing groups, and no interaction effects were found for passing time and location. The difference in passing time was high in the first half, with the highest success rate in the middle of the first half (79.2%) and the middle of the second half (77.9%) in the 15~30 minutes and the 60~75 minutes. Pass success rates were in the order of defense-midfield area (83.9%), midfield-attack area (81.7%), defense area (70.6%) and attack area (61.1%). In conclusion, there was no difference in the passing success rate of the winning and losing teams depending on the characteristics of the relative competitive strength of the World Cup games, and it is believed that follow-up research is needed to analyze the game contents rather than the factors of the winning and losing in the future.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1711-1720
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• 2020

Particulate matter (PM) that has been artificially generated during the recent of rapid industrialization and urbanization moves and disperses according to weather conditions, and adversely affects the human skin and respiratory systems. The purpose of this study is to predict the PM10 concentration in Seoul using meteorological factors as input dataset for multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) models, and compared and evaluated the performance of the models. First, the PM10 concentration data obtained at 39 air quality monitoring sites (AQMS) in Seoul were divided into training and validation dataset (8:2 ratio). The nine meteorological factors (mean, maximum, and minimum temperature, precipitation, average and maximum wind speed, wind direction, yellow dust, and relative humidity), obtained by the automatic weather system (AWS), were composed to input dataset of models. The coefficients of determination (R2) between the observed PM10 concentration and that predicted by the MLR, SVM, and RF models was 0.260, 0.772, and 0.793, respectively, and the RF model best predicted the PM10 concentration. Among the AQMS used for model validation, Gwanak-gu and Gangnam-daero AQMS are relatively close to AWS, and the SVM and RF models were highly accurate according to the model validations. The Jongno-gu AQMS is relatively far from the AWS, but since PM10 concentration for the two adjacent AQMS were used for model training, both models presented high accuracy. By contrast, Yongsan-gu AQMS was relatively far from AQMS and AWS, both models performed poorly.

• Journal of the Korean Society of Radiology
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• v.15 no.4
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• pp.429-435
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• 2021

In intracavitary radiotherapy, incorrect location of the source can cause excessive dose to normal tissue, so it is essential to evaluate the location accuracy of the source. In this study, basic research was performed on digital line dosimeter based on lead (II) oxide (PbO) to improve analog verification method. Therefore, a polycrystalline PbO unit cell dosimeter was manufactured and the measurement performance for Ir-192 sources was evaluated. As a result, the reproducibility satisfies the evaluation criteria of 1.5% with a relative standard deviation of 0.85%. Linearity showed excellent results with a linear coefficient of R² of 0.9998. In the case of distance dependence evaluation, the power function R² showed 0.9855 for PbO and 0.9974 for diode, and the overall average difference was 1.66% for PbO and 2.18% for diode. This study presents the basic detection performance of the polycrystalline PbO dosimeter for the Ir-192 source and can provide basic data in the field of radiation measurement.

• Journal of Food Hygiene and Safety
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• v.36 no.4
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• pp.281-288
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• 2021

This study was conducted to analyze and compare the concentrations of heavy metals in 430 different products of 20 types of herbal medicines available in the domestic market in Korea by Graphite Furnace-Atomic Absorption Spectrometry (GF-AAS) and automated mercury analyzer. The accuracy for lead (Pb), arsenic (As), cadmium (Cd), and mercury (Hg) was in the range 92.67-102.56%, and the precision was 0.21-6.00 relative standard deviation (RSD%), which was in compliance with the Codex acceptable range. Furthermore, the Food Analysis Performance Assessment Scheme (FAPAS) quality control (QC) material showed a recovery range of 96.7-102.0% and 0.33-4.93 RSD%. The average contents (㎍/kg) of Pb, As, Cd, and Hg in herbal medicines were 254.9 (not detected (N.D.)-2,515.2), 171.0 (N.D.-2,465.2), 99.2 (N.D.-797.1), and 6.0 (N.D.-83.6), respectively. Based on the quantitative analysis results, the heavy metal contents of 20 types of herbal medicines distributed in Korea are within the acceptable range according to the standards issued by the Ministry of Food and Drug Safety (MFDS). By using the manufacturer of herbal products as the standard for QC, the Pb, As, Cd, and Hg contents were investigated in the packaging process just before distribution to determine the actual conditions of residual heavy metals in herbal medicines. Thus, these result may contribute to monitoring the QC of herbal medicines distributed in Korea and could provide basic data for supplying safe herbal medicines to the public.

• Journal of Korean Neurosurgical Society
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• v.65 no.1
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• pp.74-83
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• 2022

Objective : Oblique lumbar interbody fusion (OLIF) is a surgical technique that utilizes a large interbody cage to indirectly decompress neural elements. The position of the cage relative to the vertebral body could affect the degree of foraminal decompression. Previous studies determined the position of the cage using plain radiographs, with conflicting results regarding the influence of the position of the cage to the degree of neural foramen decompression. Because of the cage obliquity, computed tomography (CT) has better accuracy than plain radiograph for the measurement of the obliquely inserted cage. The objective of this study is to find the correlation between the position of the OLIF cage with the degree of indirect decompression of foraminal stenosis using CT and magnetic resonance imaging (MRI). Methods : We review imaging of 46 patients who underwent OLIF from L2-L5 for 68 levels. Segmental lordosis (SL) was measured in a plain radiograph. The positions of the cage were measured in CT. Spinal canal cross-sectional area (SCSA), and foraminal crosssectional area (FSCA) measurements using MRI were taken into consideration. Results : Patients' mean age was 69.7 years. SL increases 3.0±5.1 degrees. Significant increases in SCSA (33.3%), FCSA (43.7% on the left and 45.0% on the right foramen) were found (p<0.001). Multiple linear regression analysis shows putting the cage in the more posterior position correlated with more increase of FSCA and decreases SL correction. The position of the cage does not affect the degree of the central spinal canal decompression. Obliquity of the cage does not result in different degrees of foraminal decompression between right and left side neural foramen. Conclusion : Cage position near the posterior part of the vertebral body increases the decompression effect of the neural foramen while putting the cage in the more anterior position correlated with increases SL.

• Journal of Food Hygiene and Safety
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• v.36 no.6
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• pp.474-480
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• 2021

Sodium alginate is the sodium salt of alginic acid, commonly used as a food additive for stabilizing, thickening, and emulsifying properties. A relatively simple and universal analysis method is used to study sodium alginate due to the complex pretreatment process and extended analysis time required during the quantitative method. As for the equipment, HPLC-UVD and Unison US-Phenyl column were used for analysis. For the pretreatment condition, a shaking apparatus was used for extraction at 150 rpm for 180 minutes at room temperature. The calibration curve made from the standard sodium alginate solution in 5 concentration ranges showed that the linearity (R²) is 0.9999 on average. LOD and LOQ showed 3.96 mg/kg and 12.0 mg/kg, respectively. Furthermore, the average intraday and inter-day accuracy (%) and precision (RSD%) were 98.47-103.74% and 1.69-3.08% for seaweed jelly noodle samples and 99.95-105.76% and 0.59-3.63% for sherbet samples, respectively. The relative uncertainty value was appropriate for the CODEX standard with 1.5-7.9%. To evaluate the applicability of the method developed in this study, the sodium alginate concentrations of 103 products were quantified. The result showed that the detection rate is highest from starch vermicelli and instant fried noodles to sugar processed products.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1257-1271
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• 2022

Recently, many Earth observation optical satellites have been developed, as their demands were increasing. Therefore, a rapid preprocessing of satellites became one of the most important problem for an active utilization of satellite images. Satellite image matching is a technique in which two images are transformed and represented in one specific coordinate system. This technique is used for aligning different bands or correcting of relative positions error between two satellite images. In this paper, we propose an automatic image matching method among satellite images with different ground sampling distances (GSDs). Our method is based on improved feature matching and robust estimation of transformation between satellite images. The proposed method consists of five processes: calculation of overlapping area, improved feature detection, feature matching, robust estimation of transformation, and image resampling. For feature detection, we extract overlapping areas and resample them to equalize their GSDs. For feature matching, we used Oriented FAST and rotated BRIEF (ORB) to improve matching performance. We performed image registration experiments with images KOMPSAT-3A and RapidEye. The performance verification of the proposed method was checked in qualitative and quantitative methods. The reprojection errors of image matching were in the range of 1.277 to 1.608 pixels accuracy with respect to the GSD of RapidEye images. Finally, we confirmed the possibility of satellite image matching with heterogeneous GSDs through the proposed method.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.103-126
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• 2021

The purpose of this study is described in detail as follows. First, I would like to define what digital transformation is in the maritime transport sector. Second, it is intended to derive success factors for digital transformation in the maritime transportation field by examining various preceding studies related to digital transformation. Finally, in order to derive priorities for the derived success factors, an AHP analysis model is built and an expert survey is conducted for practical experts in the maritime transportation field. Based on the survey results, we would like to provide guidelines on what factors should be considered first among the success factors of digital transformation in the maritime transportation sector. In this study, in order to derive the priority of success factors for digital transformation in the maritime transportation field, the hierarchical structure was divided into four high-level evaluation items(strategic factors, organizational culture and human factors, technology factors, and environmental factors) and 21 sub-evaluation items. A relative evaluation method of weighting items among AHP(Analytic Hierarchy Process) was applied. AHP analysis of 24 questionnaires with a consistency ratio of 0.1 or less in order to increase the accuracy of information among questionnaires collected through maritime transportation related university professors, research groups, shipping companies, container terminals, and experts engaged in shipping related IT companies was carried out. As a result of the analysis, the priority of the first-tier factors for the success factors of digital transformation in the maritime transport sector was shown in the order of strategic factors, organizational culture and human factors, technology factors, and environmental factors. In addition, when looking at the priorities of 21 detailed items, it was found that the development of new business models, the creation of an active future digital strategy, and the leadership of the chief digital officer were high.