• Land and Housing Review
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• v.14 no.2
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• pp.19-34
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• 2023

The proportion of single-person households has been steadily increasing, and the young account for the highest proportion at 35.9% among all single-person households. However, research on young single-person households has been relatively recent. Research on single-person households has mostly focused on all single-person households or elderly single-person households, and comparative research between different age groups is lacking. Therefore, this study categorizes all single-person households into young, middle-aged, and elderly groups to investigate the differences in the factors that affect their residential satisfaction and to analyze how these residential environment factors affect life satisfaction through the mediating effect of residential satisfaction. The 2020 Seoul Survey Urban Policy Index Survey data were analyzed using a structural equation model to investigate the impact of each factor. First, a finding is that various residential environment factors directly affect residential satisfaction and life satisfaction. Next, it was found that residential satisfaction directly affects life satisfaction in the models of young and middle-aged single-person households. Through this, it was confirmed that there are differences in residential environment factors that affect residential satisfaction and that residential satisfaction plays an important mediating role. Finally, it was found that the factors that affect the residential and life satisfaction of young single-person households are more diverse compared to other age groups. This study provides policy implications that age group differences should be considered first in order to improve the residential and life satisfaction of single-person households. In particular, for young single-person households, it is necessary to consider more diverse alternatives to improve their residential and life satisfaction.

• The Korean Journal of Physiology and Pharmacology
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• v.12 no.2
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• pp.83-87
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• 2008

The fyn-related kinase (FRK) belongs to the tyrosine kinase family of protein kinases. Recent studies have shown that Frk affects pancreatic beta cell number during embryogenesis and promotes beta cell cytotoxic signals in response to streptozotocin. To investigate the genetic association between FRK polymorphisms and the risk of obesity in Korean population, single nucleotide polymorphisms (SNPs) in the FRK gene region were selected and analyzed. The body mass index (BMI) was calculated, and biochemical data (systolic blood pressure, diastolic blood pressure, hemoglobin A1C, triglyceride, total cholesterol, high density lipoprotein, and low density lipoprotein) of blood sample from each subject were also measured. One hundred fifty five healthy control and 204 overweight/obesity subjects were recruited. Genotype frequencies of six SNPs [rs6568920 (+8391G>A), rs3756772 (+56780A>G), rs3798234 (+75687C>T), rs9384970 (+68506G>A), rs1933739 (+72978G>A), and rs9400883 (+75809A>G)] in the FRK gene were determined by Affymetrix Targeted Genotyping Chip data. According to the classification of Korean Society for the Study of Obesity, control (BMI 18 to < 23) and overweight/obesity (BMI$\geq$23) subjects were recruited. For the analysis of genetic data, EM algorithm, SNPStats, Haploview, HapAnalyzer, SNPAnalyzer, and Helixtree programs were used. Multiple logistic regression analysis (codominant, dominant, and recessive models) was performed. Age and gender as covariates were adjusted. For biochemical data, Student's t test was used. The mean value of BMI in the control and overweigh/obesity groups was 21.1${\pm}$1.2 (mean${\pm}$SD) and 25.6${\pm}$2.0, respectively. All biochemical data of the overweight/obesity group were statistically significance, compared with the control group. Among six SNPs, two linkage disequilibrium (LD) blocks were discovered. One block consisted of rs1933739 and rs9400883, and the other comprised rs3756772 and rs3798234. One SNP (rs9384970, +68506G>A) showed an association with overweight/obesity in the codominant model (p=0.03). Interestingly, the AA genotype distribution in the overweight/obesity group (n=7, 3.5%) was higher than those in the control group (n=1, 0.6%), which is not found in either Japanese or Chinese subjects. Therefore, the AA genotype of rs9384970 may be a risk factor for development of obesity in Korean population. The results suggest that FRK may be associated with overweight/obesity in Korean population.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.105-129
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• 2020

This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

• Korean Journal of Soil Science and Fertilizer
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• v.32 no.2
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• pp.95-108
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• 1999

Field experiments were conducted in the 101 tobacco fields(51 fields in 1985 and 50 fields in 1986) of chief tobacco producing counties of Chungbuk province(Jincheon, Eumseong, Goesan, and Joongweon counties), Chungnam province(Cheonweon county), and Kyongbuk province (Cheongdo, Seongju, and Andong counties) for two years from 1985 to 1986 in order to evaluate soil fertility using chemical properties and soil map database. Pot experiments also on the same soils were conducted and the results were compared to those of field experiments. The yield of tobacco in the plots of no fertilization was considered as a basic factor representing the soil fertility and was evaluated by nineteen independent variables, that was 9 chemical properties and 10 soil map databases. These independent variables were classified into two groups, 11 quantitative indexes and 9 qualitative indexes, and were analyzed by multiple linear regression(MLR) of SAS by REG and GLM models. The yield of tobacco in the plot of no fertilization showed high variations, e.g. the difference between minimum and maximum yields was about 5.0-5.5 times in the pot experiment and 8.2-14.9 times in the field experiment. The indexes indicating close link between yield of tobacco and soil chemical indexes, was selected but it was not well matched by the years or between pot and field experiments. Also, the standardized partial regression coefficients of quantitative indexes for the yield of field were less than 1.0, suggesting that it is difficult to develop an available single index for the evaluation of soil fertility. Evaluation for the soil fertility of field by MLR was better than that of single regression and it was gradually improved by adding chemical properties, quantitative indexes, and qualitative indexes of soil map. For example, the coefficient of determination ($R^2$) of MLR for the yield of 1985 was increased to 0.422 with chemical indexes, 0.503 by addition of quantitative indexes, and 0.633 by the additional adding of qualitative indexes of soil map, compared to 0.244 of single index, $NO_3-N$ content of soil. Consequently, it is assumed that this approach by MLR with quantitative and qualitative indexes including chemical properties and soil map databases was available as an evaluation model of soil fertility for tobacco field.

• Steel and Composite Structures
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• v.34 no.1
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• pp.123-139
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• 2020

The tube outward local buckling of Concrete-Filled Steel Tube (CFST) beam under high compression stress is still considered a critical problem, especially for steel tubes with a slender section compared to semi-compact and compact sections. In this study, the flexural performance of stiffened slender cold-formed square tube beams filled with normal concrete was investigated. Fourteen (14) simply supported CFST specimens were tested under static bending loads, stiffened with different shapes and numbers of steel stiffeners that were provided at the inner sides of the tubes. Additional finite element (FE) CFST models were developed to further investigate the influence of using internal stiffeners with varied thickness. The results of tests and FE analyses indicated that the onset of local buckling, that occurs at the top half of the stiffened CFST beam's cross-section at mid-span was substantially restricted to a smaller region. Generally, it was also observed that, due to increased steel area provided by the stiffeners, the bending capacity, flexural stiffness and energy absorption index of the stiffened beams were significantly improved. The average bending capacity and the initial flexural stiffness of the stiffened specimens for the various shapes, single stiffener situations have increased of about 25% and 39%, respectively. These improvements went up to 45% and 60%, for the double stiffeners situations. Moreover, the bending capacity and the flexural stiffness values obtained from the experimental tests and FE analyses validated well with the values computed from equations of the existing standards.

• Journal of Ginseng Research
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• v.41 no.3
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• pp.233-239
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• 2017

Background: Nephrotoxicity is the major side effect in cisplatin chemotherapy. Previously, we reported that the ginsenosides Rk3 and Rh4 reduced cisplatin toxicity on porcine renal proximal epithelial tubular cells (LLC-PK1). Here, we aimed to evaluate the protective effect of ginsenosides Rk3 and Rh4 on kidney function and elucidate their antioxidant effect using in vitro and in vivo models of cisplatin-induced acute renal failure. Methods: An enriched mixture of ginsenosides Rk3 and Rh4 (KG-KH; 49.3% and 43.1%, respectively) was purified from sun ginseng (heat processed Panax ginseng). Cytotoxicity was induced by treatment of $20{\mu}M$ cisplatin to LLC-PK1 cells and rat model of acute renal failure was generated by single intraperitoneal injection of 5 mg/kg cisplatin. Protective effects were assessed by determining cell viability, reactive oxygen species generation, blood urea nitrogen, serum creatinine, antioxidant enzyme activity, and histopathological examination. Results: The in vitro assay demonstrated that KG-KH ($50{\mu}g/mL$) significantly increased cell viability (4.6-fold), superoxide dismutase activity (2.8-fold), and glutathione reductase activity (1.5-fold), but reduced reactive oxygen species generation (56%) compared to cisplatin control cells. KG-KH (6 mg/kg, per os) also significantly inhibited renal edema (87% kidney index) and dysfunction (71.4% blood urea nitrogen, 67.4% creatinine) compared to cisplatin control rats. Of note, KG-KH significantly recovered the kidney levels of catalase (1.2-fold) and superoxide dismutase (1.5-fold). Conclusion: Considering the oxidative injury as an early trigger of cisplatin nephrotoxicity, our findings suggest that ginsenosides Rk3 and Rh4 protect the kidney from cisplatin-induced oxidative injury and help to recover renal function by restoring intrinsic antioxidant defenses.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.5
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• pp.248-254
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• 2001

The traction power demand highly varies with time and train positions and the traction load is a large-capacity current at single phase converted from 3-phase power system. Subsequently, each phase current converted from 3-phase power system cannot be maintained in balance any longer and thus the traction load can bring about imbalance in three-phase voltage. Therefore, the exact assessment of voltage unbalance must be carried out preferentially as well as load forecast at stages of designing and planning for electric railway system. The evaluation of unbalance voltage in areas, such as electric railway depots should be a prerequisite with more accuracy. The conventional researches on voltage unbalance have dealt with connection schemes of the transformers used in ac AT-fed electric railroads system and induced formulas to briefly evaluate voltage unbalance in the system(3). These formulas are still being used widely due to their easy applicabilities on voltage unbalance evaluation. Meanwhile, they don't take into account detailed characteristics of ac AT-fed electric railroads system, being founded on some assumptions. Accordingly. accuracy still remains in question. This paper proposes a new method to more effectively estimate voltage unbalance index. In this method, numerous diverted circuits in electric railway depots are categorized in three components and each component is defined as a two-port network model. The equivalent circuit for the entire power supply system is also described into a two-port network model by making parallel and/or series connections of these components. Efficiency and accuracy in voltage unbalance calculation as well can be promoted by simplifying the circuits into two-port network models.

• Journal of the Korea Society for Simulation
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• v.26 no.3
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• pp.1-11
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• 2017

Blast injuries in a compartment are investigated, and the effects of obstacles on blast injury are particularly analyzed by comparing injuries in the compartments with or without protruding obstacles inside. Even if blast pressure profile tends to be complicated in a confined space unlike in open field, it can be obtained in a relatively short time by using some empirical fast running models for simple confined spaces. However, a finite element method should be employed to obtain blast pressure profiles in a case with obstacles in confined spaces, because the obstacles heavily disturb blast waves. On the other hand, Axelsson SDOF(Single degree of freedom) model and ASII(Adjusted severity of injury index) injury level are employed to estimate blast injury in compartments, because the usual pressure-impulse injury criterion based on the ideal Friedlander waves in open the field cannot be applied to personnel in a confined space due to complexity of blast waves inside. In cases with obstacles, chest wall velocity was reduced by 26 to 76 percent(%) and the personnel injury in the compartment caused by blast was also reduced.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.1-10
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• 2022

Vegetables such as cabbage are greatly affected by natural disasters, so price fluctuations increase due to disasters such as heavy rain and disease, which affects the farm economy. Various efforts have been made to predict the price of agricultural products to solve this problem, but it is difficult to predict extreme price prediction fluctuations. In this study, cabbage prices were analyzed using the ensemble Voting technique, a method of determining the final prediction results through various classifiers by combining a single classifier. In addition, the results were compared with LSTM, a time series analysis method, and XGBoost and RandomForest, a boosting technique. Daily data was used for price data, and weather information and price index that affect cabbage prices were used. As a result of the study, the RMSE value showing the difference between the actual value and the predicted value is about 236. It is expected that this study can be used to select other time series analysis research models such as predicting agricultural product prices

• Journal of Periodontal and Implant Science
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• v.53 no.3
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• pp.184-193
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• 2023

Purpose: The present study was designed to compare the incidence of periodontitis according to menopausal status and to investigate the possible effect of hormone replacement therapy (HRT) on periodontitis in postmenopausal women using a common data model (CDM) at a single institution. Methods: This study involved retrospective cohort data of 950,751 patients from a 20-year database (2001 to 2020) of Ewha Womans University Mokdong Hospital converted to the Observational Medical Outcomes Partnership CDM. One-way analysis of variance models and the χ² test were used to analyze the statistical differences in patient characteristics among groups. A time-dependent Cox regression analysis was used to calculate hazard ratios and 95% confidence intervals, and P values less than 0.05 were considered to indicate statistical significance. Results: Of the 29,729 patients, 1,307 patients were diagnosed with periodontitis and 28,422 patients were not. Periodontitis was significantly more common among postmenopausal patients regardless of HRT status than among the non-menopausal group (P<0.05). Time-dependent Cox regression analysis showed that the postmenopausal patients had a significantly higher chance of having periodontitis than non-menopausal patients (P<0.05), but after adjustment for age, body mass index, and smoking status, the difference between the non-menopausal and post-menopausal HRT-treated groups was insignificant (P=0.140). Conclusions: Postmenopausal women had a significantly greater risk of periodontitis than non-menopausal women. Additionally, the use of HRT in postmenopausal women could reduce the incidence of periodontitis.