• Journal of the Society of Cosmetic Scientists of Korea
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• v.47 no.1
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• pp.57-63
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• 2021

In this study, isoscoparin was selected as an indicator component to develop Silene seoulensis extract as a functional cosmetic material, and we developed an analysis method using high performance liquid chromatography (HPLC) for quality control. HPLC was performed on a Unison US-C18 with a gradient elution of 0.05% (v/v) trifluoroacetic acid (TFA) and methanol at a flow rate of 1.0 mL/min at 35 ℃, and the detection wavelength was 330 nm. The HPLC method was performed in accordance with the international conference on harmonization (ICH) guideline (version 4, 2005) of analytical procedures with respect to specificity, precision, accuracy, and linearity. The limits of detection and quantitation were 0.02 and 0.07 mg/mL respectively. Calibration curves showed good linearity (R2 > 0.99988), and the precision of analysis was satisfied (less than 0.46%). In addition, the recovery rate was in the range of 99.10 to 101.61%, it was shown to be accurate. This result indicated that the established HPLC method is very useful for the determination of marker compounds in Silene seoulensis extracts.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.463-473
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• 2021

Recently, United States Geological Survey (USGS) distributed Landsat 8 Collection 2 Level 2 Science Product (L2SP). This paper aims to derive land surface temperature from L2SP and to validate it. Validation is made by comparing the land surface temperature with the one calculated from Landsat 8 Collection 1 Level 1 Terrain Precision (L1TP) and the one from Automated Synoptic Observing System (ASOS). L2SP is calculated from Landsat 8 Collection 2 Level 1 data and it provides land surface temperature to users without processing surface reflectance data. Landsat 8 data from 2018 to 2020 is collected and ground sensor data from eight sites of ASOS are used to evaluate L2SP land surface temperature data. To compare ground sensor data with remotely sensed data, 3×3 grid area data near ASOS station is used. As a result of analysis with ASOS data, L2SP and L1TP land surface temperature shows Pearson correlation coefficient of 0.971 and 0.964, respectively. RMSE (Root Mean Square Error) of two results with ASOS data is 4.029℃, 5.247℃ respectively. This result suggests that L2SP data is more adequate to acquire land surface temperature than L1TP. If seasonal difference and geometric features such as slope are considered, the result would improve.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.17-25
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• 2023

In this paper, we propose a model that can perform human pose estimation through a MobileViT-based model with fewer parameters and faster estimation. The based model demonstrates lightweight performance through a structure that combines features of convolutional neural networks with features of Vision Transformer. Transformer, which is a major mechanism in this study, has become more influential as its based models perform better than convolutional neural network-based models in the field of computer vision. Similarly, in the field of human pose estimation, Vision Transformer-based ViTPose maintains the best performance in all human pose estimation benchmarks such as COCO, OCHuman, and MPII. However, because Vision Transformer has a heavy model structure with a large number of parameters and requires a relatively large amount of computation, it costs users a lot to train the model. Accordingly, the based model overcame the insufficient Inductive Bias calculation problem, which requires a large amount of computation by Vision Transformer, with Local Representation through a convolutional neural network structure. Finally, the proposed model obtained a mean average precision of 0.694 on the MS COCO benchmark with 3.28 GFLOPs and 9.72 million parameters, which are 1/5 and 1/9 the number compared to ViTPose, respectively.

• Journal of the Korean Society of Radiology
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• v.17 no.3
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• pp.423-431
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• 2023

The purpose of this study is to analyze the factors affecting the classification of the severity of contrast media side effects based on the patient's body information using artificial intelligence techniques to be used as basic data to reduce the degree of contrast medium side effects. The data used in this study were 606 examiners who had no contrast medium side effects in the past history survey among 1,235 cases of contrast medium side effects among 58,000 CT scans performed at a general hospital in Seoul. The total data is 606, of which 70% was used as a training set and the remaining 30% was used as a test set for validation. Age, BMI(Body Mass Index), GFR(Glomerular Filtration Rate), BUN(Blood Urea Nitrogen), GGT(Gamma Glutamyl Transgerase), AST(Aspartate Amino Transferase,), and ALT(Alanine Amiono Transferase) features were used as independent variables, and contrast media severity was used as a target variable. AUC(Area under curve), CA(Classification Accuracy), F1, Precision, and Recall were identified through AdaBoost, Tree, Neural network, SVM, and Random foest algorithm. AdaBoost and Random Forest show the highest evaluation index in the classification prediction algorithm. The largest factors in the predictions of all models were GFR, BMI, and GGT. It was found that the difference in the amount of contrast media injected according to renal filtration function and obesity, and the presence or absence of metabolic syndrome affected the severity of contrast medium side effects.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.49 no.4
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• pp.291-298
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• 2023

In this study, a quantitative analysis method was developed using high-performance liquid chromatography (HPLC) to analyze the content of ceramide NP in lotion, cream, and cleanser formulations in cosmetics. The analysis was performed using a C18 column, and the mobile phase was set at a ratio of 70 : 30 for acetonitrile and methanol, the flow rate was set to 0.8 mL/min, and the column temperature was set to 20 ℃. The method was verified by analyzing specificity, linearity, limit of detection, limit of quantitation, accuracy, and precision in accordance with the ICH guidelines. As a result of validating the method, the linearity of the calibration curve was excellent (R² = 0.99984). The accuracy of the lotion, cream, and cleanser formulations was confirmed with a recovery rate ranging from 95.11% to 100.48%. The precision analysis showed a low relative standard deviation (RSD) of less than 0.26%. The limit of detection was 0.902 ㎍/mL, and the limit of quantitation was 2.733 ㎍/mL. Through this quantitative analysis method of ceramide NP applied in cosmetics, it is expected to assist in the quality control of products by enabling measurement even when it is difficult to separate the main peak due to the influence of interfering substances.

• Bulletin of the Korean Chemical Society
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• v.31 no.5
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• pp.1159-1164
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• 2010

Several triterpenoid saponins from root of Pulsatilla koreana Nakai (Ranunculaceae) were studied and their biological activities were reported. It is difficult to analyze triterpenoid saponins using HPLC-UV due to the lack of chromophores. So, evaporative light scattering detection (ELSD) is used as a valuable alternative to UV detection. More recently, a charged aerosol detection (CAD) has been developed to improve the sensitivity and reproducibility of ELSD. In this study, we developed and validated a novel method of high performance liquid chromatography coupled with a charged aerosol detector for the simultaneous determination of four triterpenoid saponins: pulsatilloside E, pulsatilla saponin H, anemoside B4 and cussosaponin C. Analytes were separated by the Supelco Ascentis$^{(R)}$ Express C18 column (4.6 mm ${\times}$ 150 mm, 2.7 ${\mu}m$) with gradient elution of methanol and water at a flow rate of 0.8 mL/min at $30^{\circ}C$. We examined various factors that could affect the sensitivity of the detectors, including various concentrations of additives, the pH of the mobile phase, and the CAD range. Linear calibration curves were obtained within the concentration ranges of 2 - 200 ${\mu}g$/mL for pulsatilloside E, anemoside $B_4$ and cussosaponin C, and 5 - 500 ${\mu}g$/mL for pulsatilla saponin H with correlation coefficient ($R^2$) greater than 0.995. The limit of detection (LOD) and quantification (LOQ) were 0.04 - 0.2 and 2 - 5 ${\mu}g$/mL, respectively. The validity of the developed HPLC-CAD method was confirmed by satisfactory values of linearity, intra- and inter-day accuracy and precision. This method could be successfully applied to quality evaluation, quality control and monitoring of Pulsatilla koreana.

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.668-677
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• 2000

Korean has the characteristics that case postpositions determine the syntactic roles of phrases and a postposition may have more than one meanings. In particular, the adverbial postpositions make translation from Korean to English difficult, because they can have various meanings. In this paper, we describe a method for resolving such semantic ambiguities of Korean adverbial postpositions using decision trees. The training examples for decision tree induction are extracted from a corpus consisting of 0.5 million words, and the semantic roles for adverbial postpositions are classified into 25 classes. The lack of training examples in decision tree induction is overcome by clustering words into classes using a greedy clustering algorithm. The cross validation results show that the presented method achieved 76.2% of precision on the average, which means 26.0% improvement over the method determining the semantic role of an adverbial postposition as the most frequently appearing role.

• Bulletin of the Korean Chemical Society
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• v.33 no.5
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• pp.1681-1685
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• 2012

A sensitive liquid chromatography-tandem mass spectrometric (LC-MS/MS) method was developed to determine valproic acid in human red blood cell (RBC). It is important to measure the drug concentration of the RBC as well as that of the plasma because of drug partitioning for pharmacokinetic and pharmacodynamic study. The method was linear over the dynamic range of 1-100 ${\mu}g$/mL with a correlation coefficient $r$ = 0.9997. The linearity of this method was established from 1 to 100 ${\mu}g$/mL for valproic acid in red blood cell with accuracy and precision within 15% at all concentrations. The intra-run and inter-run assay accuracy and coefficient of variations are all within 15% for all QC samples prepared in plasma and red blood human samples. Then, valproic acid amount by protein precipitation in plasma was quantified by LC-MS/MS mass spectrometry. The distribution ratio of VPA in RBC and plasma was analyzed by clinical samples. Based on measurement of the valproic acid in human red blood cell, this method has been applied to clinical research for study of distribution ratio of valproic acid in blood.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.1
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• pp.46-55
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• 2006

The purpose of this study is a development of an automatic mosaicing for applying to large number of airborne multispectral images, which reduces manual operation by human. 2436 airborne multispectral images were acquired from DuncanTech MS4100 camera with three bands; green, red and near infrared. LIDAR(LIght Detection And Ranging) data and GPS/INS(global positioning system/inertial navigation system) data were collected with the multispectral images. First, the multispectral images were converted to image patterns by unsupervised classification. Their patterns were compared with those of adjacent images to derive relative spatial position between images. Relative spatial positions were derived for 80% of the whole images. Second, it accomplished an automatic mosaicing using GPS/INS data and unsupervised classification. Since the time of GPS/INS data did not synchronized the time of readout images, synchronized GPS/INS data with the time of readout image were selected in consecutive data by comparing unsupervised classified images. This method realized mosaicing automatically for 96% images and RMSE (root mean square error) for the spatial precision of mosaiced images was only 1.44 m by validation with LIDAR data.

• Nutrition Research and Practice
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• v.14 no.6
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• pp.667-678
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• 2020

BACKGROUND/OBJECTIVES: This study aimed to improve portion size estimation aids (PSEAs) used in the nutrition survey of the Korea National Health and Nutrition Examination Survey (KNHANES) and validate the accuracy and precision of the newly developed aids. SUBJECTS/METHODS: We conducted intensive interviews with survey experts in KNHANES and consulted with experts to collect opinions about improvement of PSEAs. Based on the results of the interviews, 5 types of PSEAs (rice bowl, earthen pots, mounds, measuring spoons, and thickness sticks) were newly developed using 3-dimensional (3D) modeling or modification of color or shape. Validation tests were conducted with 96 adults 20 years old or older. For the rice bowl and earthen pots, the participants were asked to select the more similar PSEA in size after being shown the real dishes. For the mounds, measuring spoons, and thickness sticks, the participants were presented with actual plates of food and asked to estimate the given portion sizes using the given PSEAs. RESULTS: The improved 2-dimensional (2D) picture aid for the rice bowl reflecting the size distortion by angle of view using 3D modeling was perceived more closely to the actual size than the current 2D picture (P < 0.001). The change of the color of 2D pictures and 3D models, the change of shape of the measuring spoons, and the 3-dimensionalization of the 2D mounds had no significant improvement in the subjects' perception. CONCLUSIONS: The currently used 2D PSEAs need to be fully redesigned using 3D modeling to improve subjects' perception. However, change of color or shape will not be necessary. For amorphous foods, it is suggested that more evaluation be performed before reaching a final conclusion in the use of PSEAs, or alternative ways to improve accuracy of estimation need to be explored.