• The Journal of Internal Korean Medicine
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• v.35 no.1
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• pp.50-58
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• 2014

Objectives : The aim of this study was to analyze relationship between post-stroke depression (PSD) and cold, heat, deficiency and excess patterns. Methods : Twenty-eight PSD patients were recruited from STROKE center and measured with questionnaires for cold, heat, deficiency and excess patternvalues and saliva for cortisol awakening response (CAR). Saliva samples were collected immediately, 15, 30 and 45 min after awakening. In addition, Beck Depression Inventory (BDI) and Hamilton Depression Rating Scale (HDRS) were conducted for PSD severity. We conducted correlation analysis to find the relationship between cold, heat, deficiency and excess patterns and CAR or BDI and HDRS. Results : Deficiency and excess patterns werepositively correlated with area under the curve with respect to the increase (AUCi), but not with area under the curve with respect to the global (AUCg), in CAR. Furthermore, it was negatively correlated with BDI and HDRS, while cold and heat patterns were not correlated with CAR, BDI and HDRS. Conclusions : In terms of deficiency and excess patterns, the higher the PSD severity, the higher the deficiency and the lower the PSD severity, the higher the excess. However, there was not a significant relationship between PSD and cold and heat patterns.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.374-382
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• 2020

The purpose of this study is to improve the learning speed of an ammunition stockpile reliability classification artificial neural network model by proposing a normalization method that reduces the number of input variables based on the characteristic of Ammunition Stockpile Reliability Program (ASRP) data without loss of classification performance. Ammunition's performance requirements are specified in the Korea Defense Specification (KDS) and Ammunition Stockpile reliability Test Procedure (ASTP). Based on the characteristic of the ASRP data, input variables can be normalized to estimate the lot percent nonconforming or failure rate. To maintain the unitary hypercube condition of the input variables, min-max normalization method is also used. Area Under the ROC Curve (AUC) of general min-max normalization and proposed 2-step normalization is over 0.95 and speed-up for marching learning based on ASRP field data is improved 1.74 ~ 1.99 times depending on the numbers of training data and of hidden layer's node.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.495-509
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• 2015

We study a classification problem of significant differences in the proportion of two groups known as the unbalanced classification problem. It is usually more difficult to classify classes accurately in unbalanced data than balanced data. Most observations are likely to be classified to the bigger group if we apply classification methods to the unbalanced data because it can minimize the misclassification loss. However, this smaller group is misclassified as the larger group problem that can cause a bigger loss in most real applications. We compare several classification methods for the unbalanced data using sampling techniques (up and down sampling). We also check the total loss of different classification methods when the asymmetric loss is applied to simulated and real data. We use the misclassification rate, G-mean, ROC and AUC (area under the curve) for the performance comparison.

• Journal of Veterinary Science
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• v.23 no.5
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• pp.64.1-64.9
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• 2022

Background: Fluralaner is a novel drug belonging to the isoxazoline class that acts on external parasites of domestic animals. It is used systemically via drinking water, especially against red poultry mite in layer chickens. Fluralaner is frequently used in layers infected with D. gallinae. However, no study to date has investigated the effects of feed intake and water hardness. Objectives: This study aimed to investigate the effects of variable water hardness and feed intake on the pharmacokinetic profile of fluralaner. Methods: Layer chickens were divided into four groups (n = 8): fed + purified water (Group 1), feed restricted + purified water (Group 2), feed restricted + hard water (Group 3), and feed restricted + soft water (Group 4). After administering a single dose of the drug with drinking water, the blood samples were collected for 21 days. Fluralaner concentrations in plasma samples were determined by liquid chromatography/tandem mass spectrometry. The maximum plasma concentration (C_max), time to reach maximum plasma concentration (t_max), area under the concentration-time curve values (AUC_0-21d), half-life (t_1/2), and other pharmacokinetic parameters were calculated. Results: Although the highest maximum plasma concentration (C_max) was determined in Group 1 (fed + purified water), no statistically significant difference was found in the C_max, t_max, t_1/2, MRT_{0-inf_obs}, Vz/F_obs, and Cl/F_{_obs} parameters between the experimental groups. Conclusions: It was concluded that the feed intake or water hardness did not change the pharmacokinetic profile of fluralaner in layer chickens. Therefore, fluralaner could be used before or after feeding with the varying water hardness in poultry industry.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.85-85
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• 2020

South Korea experiences few large scale erosion and sedimentation problems, however, there are numerous local sedimentation problems. A reliable and consistent approach to modelling and management for sediment processes are desirable in the country. In this study, field measurements of sediment concentration from 34 alluvial river basins in South Korea were used with the Modified Einstein Procedure (MEP) to determine the total sediment load at the sampling locations. And then the Flow Duration-Sediment Rating Curve (FD-SRC) method was used to estimate the specific degradation for all gauging stations. The specific degradation of most rivers were found to be typically 50-300 tons/㎢·yr. A model tree data mining technique was applied to develop a model for the specific degradation based on various watershed characteristics of each watershed from GIS analysis. The meaningful parameters are: 1) elevation at the middle relative area of the hypsometric curve [m], 2) percentage of wetland and water [%], 3) percentage of urbanized area [%], and 4) Main stream length [km]. The Root Mean Square Error (RMSE) of existing models is in excess of 1,250 tons/㎢·yr and the RMSE of the proposed model with 6 additional validations decreased to 65 tons/㎢·yr. Erosion loss maps from the Revised Universal Soil Loss Equation (RUSLE), satellite images, and aerial photographs were used to delineate the geospatial features affecting erosion and sedimentation. The results of the geospatial analysis clearly shows that the high risk erosion area (hill slopes and construction sites at urbanized area) and sedimentation features (wetlands and agricultural reservoirs). The result of physiographical analysis also indicates that the watershed morphometric characteristic well explain the sediment transport. Sustainable management with the data mining methodologies and geospatial analysis could be helpful to solve various erosion and sedimentation problems under different conditions.

• Biomolecules & Therapeutics
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• v.28 no.4
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• pp.361-369
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• 2020

Tofacitinib, a Janus kinase inhibitor, was developed for the treatment of rheumatoid arthritis. Recently, it has been associated with an increased change in arthritis development in patients with diabetes. Herein, we evaluated the pharmacokinetics of tofacitinib after intravenous (10 mg/kg) and oral (20 mg/kg) administration to rats with streptozotocin-induced diabetes mellitus and control rats. Following intravenous administration of tofacitinib to rats with streptozotocin-induced diabetes mellitus, area under the plasma concentration-time curve from time zero to infinity of tofacitinib was significantly smaller (33.6%) than that of control rats. This might be due to the faster hepatic intrinsic clearance (112%) caused by an increase in the hepatic cytochrome P450 (CYP) 3A1(23) and the faster hepatic blood flow rate in rats with streptozotocin-induced diabetes mellitus than in control rats. Following oral administration, area under the plasma concentration-time curve from time zero to infinity of tofacitinib was also significantly smaller (55.5%) in rats with streptozotocin-induced diabetes mellitus than that in control rats. This might be due to decreased absorption caused by the higher expression of P-glycoprotein and the faster intestinal metabolism caused by the higher expression of intestinal CYP3A1(23), which resulted in the decreased bioavailability of tofacitinib (33.0%) in rats with streptozotocin-induced diabetes mellitus. In summary, our findings indicate that diabetes mellitus affects the absorption and metabolism of tofacitinib, causing faster metabolism and decreased intestinal absorption in rats with streptozotocin-induced diabetes mellitus.

• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.289-294
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• 2020

Peptic ulcer disease is a gastrointestinal disorder caused by Helicobacter pylori infection and the use of nonsteroid anti-inflammatory drugs. While many studies have been conducted to find the risk factors of peptic ulcers, there are no studies on the suggestion of peptic ulcer prediction models for Koreans. Therefore, the purpose of this study is to implement peptic ulcer prediction model using machine learning based on demographic information, obesity information, blood information, and nutritional information for middle-aged and elderly people. For model building, wrapper-based variable selection method and naive Bayes algorithm were used. The classification accuracy of the female prediction model was the area under the receiver operating characteristics curve (AUC) of 0.712, and males showed an AUC of 0.674, which is lower than that of females. These results can be used for prediction and prevention of peptic ulcers in the middle and elderly people.

• Journal of The Geomorphological Association of Korea
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• v.24 no.1
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• pp.77-91
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• 2017

Many debris landforms in the mountains of Korea have formed in the periglacial environment during the last glacial stage when the generation of sediments was active. Because these landforms are generally located on steep slopes and mostly covered by vegetation, however, it is difficult to observe and access them through field investigation. A scientific method is required to reduce the survey range before performing field investigation and to save time and cost. For this purpose, the use of remote sensing and GIS technologies is essential. This study has extracted the potential area of debris landform formation using a fuzzy set model as a mathematical data integration method. The first step was to obtain information about the location of debris landforms and their related factors. This information was verified through field observation and then used to build a database. In the second step, we conducted the fuzzy set modeling to generate a map, which classified the study area based on the possibility of debris formation. We then applied a cross-validation technique in order to evaluate the map. For a quantitative analysis, the calculated potential rate of debris formation was evaluated by plotting SRC(Success Rate Curve) and calculating AUC(Area Under the Curve). The prediction accuracy of the model was found to be 83.1%. We posit that the model is accurate and reliable enough to contribute to efficient field investigation and debris landform management.

• Research in Community and Public Health Nursing
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• v.22 no.3
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• pp.302-314
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• 2011

Purpose: This study aimed to validate instruments to classify the frailty of Korean elderly people in community. Methods: For this study, 632 elders were selected from community-based elderly houses and home visiting registries, and data on frailty were collected using three instruments during November, 2008. The Korean Frail Scale (KFS) was composed of 10 domains with the maximum score of 20. The Edmonton Frail Scale (EFS) had 10 domains with the maximum score of 17. The 25_Japan Frail Scale (25_JFS) was composed of 6 domains with the maximum score of 25. Internal consistency was measured with Cronbach's ${\alpha}$. Sensitivity, specificity and area under the curve (AUC) of ROC were measured to see validity with long.term care insurance grade as a gold standard. Results: The Cronbach's ${\alpha}$ was .72 for KFS, .55 for EFS, and .80 for 25_JFS. Sensitivity, specificity, and AUC were 70.0%, 83.2%, and .83, respectively, at cutting point 10.5 for the KFS, 50.0%, 80.9%, and .66, respectively, at 8.5 for EFS, and 80.0%, 85.9%, and .86, respectively, at 12.5 for 25_JFS. Conclusion: KFS and three JFS showed favorable internal consistency and predictive validity. Further longitudinal studies are recommended to confirm predictive validity.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6327-6330
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• 2013

Haematuria is a common presentation of bladder cancer and requires a full urologic evaluation. This study aimed to develop a scoring system capable of stratifying patients with haematuria into high or low risk groups for having bladder cancer to help clinicians decide which patients need more urgent assessment. This cross-sectional study included all adult patients referred for haematuria and subsequently undergoing full urological evaluation in the years 2001 to 2011. Risk factors with strong association with bladder cancer in the study population were used to design the scoring system. Accuracy was determined by the area under the receiver operating characteristic (ROC) curve. A total of 325 patients with haematuria were included, out of which 70 (21.5%) were diagnosed to have bladder cancer. Significant risk factors associated with bladder cancer were male gender, a history of cigarette smoking and the presence of gross haematuria. A scoring system using 4 clinical parameters as variables was created. The scores ranged between 6 to 14, and a score of 10 and above indicated high risk for having bladder cancer. It was found to have good accuracy with an area under the ROC curve of 80.4%, while the sensitivity and specificity were 90.0% and 55.7%, respectively. The scoring system designed in this study has the potential to help clinicians stratify patients who present with haematuria into high or low r isk for having bladder cancer. This will enable high-risk patients to undergo urologic assessment earlier.