• Journal of muscle and joint health
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• v.17 no.2
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• pp.203-211
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• 2010

Purpose: We aimed to test the validity of the EQ-5D (Euro-Quality of Life-5 Dimension), a brief and simple instrument, in measuring health related quality of life in the patients with osteoarthritis. Methods: 183 participants attending the education programs for osteoarthritis patients at the Health Centers located in Seoul and Gyunggi province area during the periods of June to December in 2009 were interviewed with the EQ-5D and KWOMAC (Korean version of Western Ontario and McMaster Scale). The data were analysed with Spearman correlation coefficents and t-test by using of SPSS/WIN 12.0 version. Results: There was a negative correlation between knee pain, stiffness and difficulty in usual activity of sub category items of KWOMAC and EQ-5Dindex, while there was no correlation between these categories and EQ-VAS. Moreover, as a result of comparing the score of physical function measured by KWOMAC according to the severity degree of the EQ-5Dindex, the group of advanced stage having moderate and severe symptoms reported significantly higher scores of physical function than those of groups having no health problems. Conclusion: The EQ-5D is an acceptable and valid instrument for measuring health-related quality of life in patients with osteoarthritis.

• Journal of Pharmaceutical Investigation
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• v.34 no.6
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• pp.521-527
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• 2004

Cimetidine is a histamine $H_2-receptor$ antagonist, used for the treatment of endoscopically or radiographically comfirmed duodenal ulcer, pathologic GI hypersecretory conditions, and active, benign and gastric ulcer. Simple method for determining cimetidine in human plasma has been developed and validated. The analytical procedure for cimetidine showed a linear relationship in the concentration ranges from $0.05\;to\;5\;{\mu}g/ml$. Coefficient of variance (CV, %) for intraday and interday validation and relative error (RE, %) were less than ${\pm}15%$. Based on this analytical method, the bioequivalence of two cimetidine 400 mg tablets, reference (Tagamet 400 mg) and test drug (Sinil CIMETIDINE 400 mg) was evaluated according to the guidelines set by the Korea Food and Drug Administration (KFDA). Release of cimetidine from the tablets in vitro was tested using KP VIII Apparatus II with various dissolution media (pH 1.2, 4.0, 6.8 buffer solutions and water). Twenty-four healthy volunteers, $21.38{\pm}1.86$ years in age and $68.71{\pm}8.68\;kg$ in body weight, were divided into two groups and a randomized $2{\times}2$ cross-over study was performed. After oral administration of a tablet containing 400 mg of cimetidine, blood samples were taken at predetermined time intervals and concentrations of cimetidine in plasma were determined using HPLC equipped with UV detector. The dissolution profiles of the two tablet formulations were very similar at all dissolution media. In addition, pharmacokinetic parameters such as $AUC_t$ and $C_{max}$ were calculated and ANOVA was employed for the statistical analysis of parameters. The results were revealed that the differences in $AUC_t$ and $C_{max}$ between the two tablets were 4.17 % and 0.97% respectively. At 90% confidence intervals, the differences in these parameters were also within ${\pm}20%$. All of the above mentioned parameters have met the criteria of KFDA guidelines for bioequivalence, indicating that the test drug tablet (Sinil CIMETIDINE tablet) is bioequivalent to Tagamet 400 mg tablet.

• The Korean Journal of Pesticide Science
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• v.6 no.3
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• pp.209-217
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• 2002

Two different QSAR methods, the comparative molecular similarity indices analyses (CoMSIA) and hologram quantitative structure activity relationship (HQSAR) are studied for the fungicidal activities ($pI_{50}$) of 2-N-benzyl-5-phenoxy-3-isothiazolone derivatives against sensitive (SPC: 95CC7105) and resisitive (RPC: 95CC7303) phytophthora blight fungus (Phytaphthora capsici). According to the findings from these QSAR investigation, the cross-validation value, $q^2$ and Pearson correlation coefficient, $r^2$ in the two methods were CoMSIA: RPC; $q^2=0.675,\;r^2=0.942$, SPC; $q^2=0.350,\;r^2=0.876$ and HQSAR: RPC; $q^2=0.519,\;r^2=0.869$, SPC; $q^2=0.483,\;r^2=0.990$, respectively. Therefore, the two models of comparative statistical significance were obtained. From the CoMSIA contour maps, the important factors for selective fungicidal activity against RPC are to be expected that the lower hydrophobic and not bulkiness substituent as hydrogen bonding acceptor have to introduce to meta and para-position (C1-C6) on the phenoxy moiety. And the results of prediction suggest that HQSAR method showed higher fungicidal activity than CoMSIA method.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.423-440
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• 2007

Although various models have been developed to establish the enterprise credit scoring, no model has utilized the enterprise human resource so far. The purpose of this study was to build an enterprise credit scoring model using enterprise human resource factors. The data to measure the enterprise credit score were made by the first-year research material of HCCP was used to investigate the enterprise human resource and 2004 Credit Rating Score generated from KIS-Credit Scoring Model. The independent variables were chosen among questionnaires of HCCP based on Mclagan(1989)'s HR wheel model, and the credit score of Korean Information Service was used for the dependent variables. The statistical method used for data analysis was logistic regression. As a result of constructing a model, 22 variables were selected. To see these specifically by each large area, 6 variables in human resource development(HRD) area, 15 in human resource management(HRM) area, and 1 in the other area were chosen. As a consequence of 10 fold cross validation, misclassification rate and G-mean were 30.81 and 68.27 respectively. Decile having the highest response rate was bigger than the one having the lowest response rate by 6.08 times, and had a tendency to decrease. Therefore, the result of study showed that the proposed model was appropriate to measure enterprise credit score using enterprise human resource variables.

• Biomolecules & Therapeutics
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• v.6 no.2
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• pp.219-224
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• 1998

The bioequivalence of two clarithromvcin products was evaluated with 16 normal male volunteers (age 23-28 yr, body weight 57.5-75.517g) following single oral dose. Test product was ReYon Clarithromycin tablets (ReYon Pharm. Corp., Korea) and reference product was Klarici $d_{R}$ tablets (Abbott Korea). Both products contain 250 mg of clarithromucin. One tablet of the test or the reference product was administered to the volunteers, respectively, by randomized two period cross-over study (2$\times$2 Latin square method). The determination of clarithromycin was accomplished using a modified agar well diffusion bioassay. As a result of the assay validation, the quantification of clarithromycin in human serum by this technique was possible down to 0.03$\mu$g/ml using 100$\mu$l of serum. The coefficient of variation (C.V.) was less than 10%. Average drug concentrations at each sampling time and pharmacokinetic parameters calculated were not significantly different between two products P>0.05); the area under the curve to last sampling time (24 hr) (AU $Co_{24hr}$ (8.10$\pm$ 1.26 vs 8.22$\pm$ 1.627g . hr/ml), AUC from time zero to infinite (AU $Co_{\infty}$) (8.61 $\pm$ 1.28 vs 8.84$\pm$ 1.71 $\mu$g . hr/ml), maximum plasma concentration ( $C_{msx}$) (0.87$\pm$0.22 vs 0.88$\pm$0.19 $\mu$g/ml) and time to maximum plasma concentration ( $T_{max}$) (2.69 $\pm$0.48 vs 2.56$\pm$ 0.51 hr). The differences of mean AU $Co_{24h}$, $C_{msx}$ and $T_{msx}$ between the two products (1.44, 1.39, and 4.65%, respectively) were less than 20%. The power (1-$\beta$) and treatment difference ($\Delta$) for AU $Co_{24hr}$, and $C_{max}$ were more than 0.8 and less than 0.2, respectivly. Although the power for $T_{max}$ was under 0.8, $T_{max}$. of the two products was not significantly different each other (p>0.05). These results suggest that the bioavailability of ReYon Clarithromycin tablets is not significantly different from that of Klarici $d_{R}$ tablets. Therefore, two products are bioequivalent based on the current results. results.sults.sults.s.s.s.s.s.s.s.

• Korean Journal of Remote Sensing
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• v.25 no.4
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• pp.311-320
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• 2009

This study was carried out to estimate forest biomass and to produce forest biomass thematic map for Muju county by combining field data from the 5$^{th}$ National Forest Inventory (2006-2007) and satellite data. For estimating forest biomass, two methods were examined using a Landsat TM-5(taken on April 28th, 2005) and field data: multi-variant regression modeling and t-Nearest Neighbor (k-NN) technique. Estimates of forest biomass by the two methods were compared by a cross-validation technique. The results showed that the two methods provide comparatively accurate estimation with similar RMSE (63.75$\sim$67.26ton/ha) and mean bias ($\pm$1ton/ha). However, it is concluded that the k-NN method for estimating forest biomass is superior in terms of estimation efficiency to the regression model. The total forest biomass of the study site is estimated 8.4 million ton, or 149 ton/ha by the k-NN technique.

• Korean Journal of Remote Sensing
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• v.11 no.3
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• pp.33-47
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• 1995

The representation of point-observed environmental variables in Geographic Information Systems(GIS) has often been inadequate to meet the need of regional-scale ecological and environmental applications. To create a map of continuous surface that would represent more reliable spatial variations for these applications, I present three spatial estimation methods. Using a secondary variable of the proximity to coast line together with rainfall acidity data collected at the 63 acid rain monitoring stations in Korea, average rainfall acidity map was cteated using co-kriging. For comparison, two other commonly used interpolation methods (inverse distance weighting and kriging) were also applied to rainfall acidity data without reference to the secondary variable. These estimation methods were evaluated by both visual assessments of the output maps and the quantitative comparison of error measures that were obtained from cross validation. The co-kriging method produced a rainfall acidity map that showed noticeable improvement in repoducing the inherent spatial pattern as well as provided lower statistical error as compared to the methods using only the primary variable.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.97-117
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• 2021

Predicting term deposit subscriptions is one of representative financial marketing in banks, and banks can build a prediction model using various customer information. In order to improve the classification accuracy for term deposit subscriptions, many studies have been conducted based on machine learning techniques. However, even if these models can achieve satisfactory performance, utilizing them is not an easy task in the industry when their decision-making process is not adequately explained. To address this issue, this paper proposes an explainable scheme for term deposit subscription forecasting. For this, we first construct several classification models using decision tree-based ensemble learning methods, which yield excellent performance in tabular data, such as random forest, gradient boosting machine (GBM), extreme gradient boosting (XGB), and light gradient boosting machine (LightGBM). We then analyze their classification performance in depth through 10-fold cross-validation. After that, we provide the rationale for interpreting the influence of customer information and the decision-making process by applying Shapley additive explanation (SHAP), an explainable artificial intelligence technique, to the best classification model. To verify the practicality and validity of our scheme, experiments were conducted with the bank marketing dataset provided by Kaggle; we applied the SHAP to the GBM and LightGBM models, respectively, according to different dataset configurations and then performed their analysis and visualization for explainable term deposit subscriptions.

• Journal of Conservation Science
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• v.37 no.5
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• pp.411-425
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• 2021

The Stupa of State Preceptor Jigwang from Beopcheonsa Temple Site in Wonju (National Treasure) is a representative stupa of the Goryeo Dynasty, with outstanding Buddhist carvings and splendid patterns, clearly indicating its honoree and year of construction. However, it was destroyed by bombing during the Korean War (1950-1953) and repaired and restored with cement and reinforcing bars in 1957. The surface condition of the original stone shows long-term deterioration due to the m ortar used in past restorations. In order to identify the exact causes of deterioration, the m ortar and surface contaminants on the original stone were analyzed. Portlandite, calcite, ettringite, and gypsum from the mortar were identified, and its ongoing deterioration was observed through pH measurements and the neutralization reaction test. Analysis of surface contaminants identified calcite and gypsum, both poorly water-soluble substances, and their growth in volume among rock-forming minerals was observed by microscopy. Based on those results, semi-quantitative analysis of Ca and S contents significantly influencing the formation of salt crystals was conducted using P-XRF to analyze the basis of surface deterioration, and cross-validation was performed by comparing the body stone affected by the mortar and the upper stylobate stone unaffected by the mortar. Results indicate that the elements are directly involved in the surface deterioration of the body stone.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1149-1161
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• 2021

With a trend of the utilization of computer vision for satellite images, cloud detection using deep learning also attracts attention recently. In this study, we conducted a U-Net cloud detection modeling using SPARCS (Spatial Procedures for Automated Removal of Cloud and Shadow) Cloud Dataset with the image data augmentation and carried out 10-fold cross-validation for an objective assessment of the model. Asthe result of the blind test for 1800 datasets with 512 by 512 pixels, relatively high performance with the accuracy of 0.821, the precision of 0.847, the recall of 0.821, the F1-score of 0.831, and the IoU (Intersection over Union) of 0.723. Although 14.5% of actual cloud shadows were misclassified as land, and 19.7% of actual clouds were misidentified as land, this can be overcome by increasing the quality and quantity of label datasets. Moreover, a state-of-the-art DeepLab V3+ model and the NAS (Neural Architecture Search) optimization technique can help the cloud detection for CAS500 (Compact Advanced Satellite 500) in South Korea.