• Journal of the Korean Institute of Intelligent Systems
• /
• v.25 no.2
• /
• pp.191-196
• /
• 2015

There have been many studies on statistical forecasting on firm's performance and stock price by applying various financial indicators such as debt ratio and sales growth rate. Selecting predictors for constructing a prediction model among the various financial indicators is very important for precise prediction. Most of the previous studies applied variable selection algorithms for selecting predictors. However, the variable selection algorithm is considered to be at risk of eliminating certain amount of information from the indicators that were excluded from model construction. Therefore, we propose a firm's performance prediction model which principal component analysis is applied instead of the variable selection algorithm, in order to reduce dimensionality of input variables of the prediction model. In this study, we constructed the proposed prediction model by using financial data of American IT companies to empirically analyze prediction performance of the model.

• Journal of the Korean GEO-environmental Society
• /
• v.15 no.8
• /
• pp.5-11
• /
• 2014

In this study, chemical analysis and ecotoxicity tests of leachate from disposal site for foot-and-mouth disease carcasses (FMD leachate) were conducted to collect fundamental data that will be used to develop environmental risk assessment tools for FMD leachate. For chemical analysis, concentration of $Cl^-$, $NH{_4}{^+}-N$, Korea standard method indicators for detection of leachate released from animal carcasses burial site into groundwater and NRN (Ninhydrin-Reactive Nitrogens), a newly suggested screening test indicator to detect groundwater contamination by FMD leachate, were assessed. For ecotoxicity tests, luminescent bacteria (V. fischeri), micro-algae (P. subcapitata) and water flea (D. magna) were selected as test species. Correlation analysis between the concentration of $Cl^-$, $NH{_4}{^+}-N$, NRN and the toxicity to V. fischeri was performed to identify the better indicators to monitor FMD leachate contamination. From regression analysis, the concentration of the indicators in FMD leachate contaminated sample that induced halfmaximal toxic effect to V. fischeri was evaluated. Results obtained from this study can be applied to assess the risk by FMD leachate and to establish the guideline to manage risk in relation to FMD leachate.

• Journal of the korean academy of Pediatric Dentistry
• /
• v.43 no.3
• /
• pp.264-274
• /
• 2016

It is a trend that carbonated drink intake among adolescents is increasing, which makes young people more vulnerable to dental erosion. However, in Korea, public knowledge about dental erosion is very insufficient. The aim of this study was to investigate the prevalence of dental erosion and to assess its risk indicators among 13-15 years old students in Yangsan, Korea. A total of 1,371 adolescents were examined by one calibrated clinician. Dental erosion was assessed by using the Visual Erosion Dental Examination system. Correlation between their dietary habit, oral hygiene and dental erosion was assessed. The data showed that 676 (49.3%) adolescents had dental erosion. The prevalence of dental erosion was significantly higher in females than in males. The prevalence of tooth erosion in mandible is higher than in maxilla. Dental erosion was generalized to develop mostly on anterior teeth, especially lateral incisor, however, the severity score was highest in canines. Following questionnaire analysis, dental erosion was significantly associated with milk and flavored milk. No other associations were detected. The prevalence of dental erosion in this study is higher than those of previous reports. On the contrary to previously reported studies, the prevalence of dental erosion in females is higher than in males.

• Journal of Nutrition and Health
• /
• v.54 no.5
• /
• pp.489-500
• /
• 2021

Purpose: This study aimed at investigating the nutritional status, nutritional support, and nutritional indicators of critically ill patients on extracorporeal membrane oxygen (ECMO) in intensive care units (ICU). Methods: This descriptive study obtained data from the medical records of 37 patients who were treated using ECMO at a university hospital in Korea. The patients were admitted to the Korea University Anam Hospital ICU with acute or serious damage to vital organs from January 1, 2014 to June 30, 2016. Results: Although 32 patients (86.5%) were at a high risk of malnutrition, 26 patients (70.3%) were considered normal in terms of nutritional status by the nutritionist at the beginning of their ICU stay. However, after two weeks, nine patients had passed away and only one patient maintained normal status. Parenteral nutrition was started first but took 4.25 ± 6.95 days till initiation. Only eight patients (21.6%) were able to meet their requirement for both calories and protein. The group provided with adequate calorie and protein showed significantly longer use of the ECMO and respirator and longer ICU and total hospital stay than their counterparts. Normal levels of serum albumin and protein of the group at low-risk for malnutrition on the day of initiation of ECMO, which were significantly higher than the high-risk group, declined by the last day of ECMO leading to a lack of significant differences between the two groups. Conclusion: Considering that the nutritional indicators of patients deteriorated as the days on ECMO increased, more aggressive nutritional management to ensure adequate nutritional support should be emphasized from the beginning and throughout the ICU stay.

• Journal of Biomedical Engineering Research
• /
• v.43 no.1
• /
• pp.19-26
• /
• 2022

The Comprehensive in vitro Proarrhythmic Assay(CiPA) project was launched for solving the hERG assay problem of being classified as high-risk groups even though they are low-risk drugs due to their high sensitivity. CiPA presented a protocol to predict drug toxicity using physiological data calculated based on the in-silico model. in this study, features calculated through the in-silico model are analyzed for correlation of changing action potential in the near future, and features are verified through predictive performance according to drug datasets. Using the O'Hara Rudy model modified by Dutta et al., Pearson correlation analysis was performed between 13 features(dVm/dtmax, APpeak, APresting, APD90, APD50, APDtri, Ca_peak, Ca_resting, CaD90, CaD50, CaDtri, qNet, qInward) calculated at 100 pacing, and between dVm/d_{tmax_repol} calculated at 1,000 pacing, and linear regression analysis was performed on each of the 12 training drugs, 16 verification drugs, and 28 drugs. Indicators showing high coefficient of determination(R²) in the training drug dataset were qNet 0.93, AP resting 0.83, APDtri 0.78, Ca resting 0.76, dVm/dt_max 0.63, and APD90 0.61. The indicators showing high determinants in the validated drug dataset were APDtri 0.94, APD90 0.92, APD50 0.85, CaD50 0.84, qNet 0.76, and CaD90 0.64. Indicators with high coefficients of determination for all 28 drugs are qNet 0.78, APD90 0.74, and qInward 0.59. The indicators vary in predictive performance depending on the drug dataset, and qNet showed the same high performance of 0.7 or more on the training drug dataset, the verified drug dataset, and the entire drug dataset.

• Environmental Analysis Health and Toxicology
• /
• v.19 no.1
• /
• pp.81-91
• /
• 2004

Although it is suggested that risk -based management plan is needed to manage air pollution effectively, we have no resources enough to evaluate all aspects of substances and set priorities. So we need to develop a logical and easy risk-based priority setting method. However, it if impossible that only one generic system that is consistent with all the use is developed. In this study, we proposed a human health risk based priority-setting method for hazardous air pollutants, and ranked priorities for this method. First of all, after investigating previous chemical ranking and scoring systems, we chose appropriate indicators and logics to goal of this study and made a chemical priority ranking method using these. As results, final scores in priority ranking method were derived for 25 substances, and ethylene oxide, acrylonitrile and vinyl chloride were included in high ranks. In addition, same substances were highly ranked when using default values like when using no default, but the scores of hydrofluoric acid and ryan and compounds were sensitive to default values. This study could be important that priorities were set including toxicity type and quality and local inherent exposure conditions and we can set area-specific management guidelines and survey plans as a screening tool.

• The Journal of Asian Finance, Economics and Business
• /
• v.7 no.11
• /
• pp.717-725
• /
• 2020

The purpose of this paper is to highlight the impact of the performance of private wealth management (PWM) on the growth of retail banking in Indonesia. The variables used are bank's competitiveness, risk management, performance of private wealth management, and growth of retail banking business. The data were collected from 60 respondents from 32 banks over five months, from October 2018 to March 2019. Using partial least square path modeling, the analysis shows that the performance of private wealth management has an impact on the growth of retail banking sector in Indonesia. Bank competitiveness and risk management affect the performance of personal wealth management and have an impact on the growth of the retail banking business. Bank competitiveness is the variable that most influences the performance of private wealth management in Indonesia. This research found that market share is the most significant indicator of bank competitiveness. For risk management, significant indicators are the level of bank confidence, increased bank competitiveness, and the creation of new products. In the performance of the private wealth management variable, the most significant indicator is the revenue fee-based income. For the growth of retail banking business, a clear indicator is profit growth.

• Journal of Korean Public Health Nursing
• /
• v.34 no.3
• /
• pp.416-428
• /
• 2020

Purpose: This study identified socioeconomic factors affecting the health status of Korean adults. Methods: Secondary data from 12,921 adults aged 19 to 64 old in the 7th Korean National Health and Nutrition Examination Survey were used. The participants' health status was measured using the indicators that included health behaviors (smoking, high-risk drinking, strength exercise, and aerobic physical activity) and health outcomes (metabolic syndrome, and subjective health status). Results: For all health behaviors and health outcomes, gender, age, educational level, and income were common affecting factors. Regarding health behaviors, the employment status was related to smoking, high-risk drinking, strength exercise, and aerobic physical activity. The marital status was related to high-risk drinking, strength exercise, and aerobic physical activity. The household type was related to smoking. The residential area was related to smoking, high-risk drinking, and aerobic physical activity. For health outcomes, the household type was related to obesity, and subjective health status; residential area was related to obesity. Conclusion: This study presented basic data for assessing the differences in health status. The characteristics of the affecting factors to health status should be considered, depending on the health behaviors and health outcomes.

• The Journal of Industrial Distribution & Business
• /
• v.13 no.10
• /
• pp.1-8
• /
• 2022

Purpose: Support vector machines (SVMs) ensemble has been proposed to improve classification performance of Credit risk recently. However, currently used fusion strategies do not evaluate the importance degree of the output of individual component SVM classifier when combining the component predictions to the final decision. To deal with this problem, this paper designs a support vector machines (SVMs) ensemble method based on fuzzy integral, which aggregates the outputs of separate component SVMs with importance of each component SVM. Research design, data, and methodology: This paper designs a personal credit risk evaluation index system including 16 indicators and discusses a support vector machines (SVMs) ensemble method based on fuzzy integral for designing a credit risk assessment system to discriminate good creditors from bad ones. This paper randomly selects 1500 sample data of personal loan customers of a commercial bank in China 2015-2020 for simulation experiments. Results: By comparing the experimental result SVMs ensemble with the single SVM, the neural network ensemble, the proposed method outperforms the single SVM, and neural network ensemble in terms of classification accuracy. Conclusions: The results show that the method proposed in this paper has higher classification accuracy than other classification methods, which confirms the feasibility and effectiveness of this method.

• Atmosphere
• /
• v.34 no.2
• /
• pp.107-121
• /
• 2024

In this study, we empirically analyzed the impact of physical risks due to climate change on the soundness and operational performance of the financial industry by combining economics and climatology. Particularly, unlike previous studies, we employed the Seasonal-Trend decomposition using LOESS (STL) method to extract trends of climate-related risk variables and economic-financial variables, conducting a two-stage empirical analysis. In the first stage estimation, we found that the delinquency rate and the Bank for International Settlement (BIS) ratio of commercial banks have significant negative effects on the damage caused by natural disasters, frequency of heavy rainfall, average temperature, and number of typhoons. On the other hand, for insurance companies, the damage from natural disasters, frequency of heavy rainfall, frequency of heavy snowfall, and annual average temperature have significant negative effects on return on assets (ROA) and the risk-based capital ratio (RBC). In the second stage estimation, based on the first stage results, we predicted the soundness and operational performance indicators of commercial banks and insurance companies until 2035. According to the forecast results, the delinquency rate of commercial banks is expected to increase steadily until 2035 under assumption that recent years' trend continues until 2035. It indicates that banks' managerial risk can be seriously worsened from climate change. Also the BIS ratio is expected to decrease which also indicates weakening safety buffer against climate risks over time. Additionally, the ROA of insurance companies is expected to decrease, followed by an increase in the RBC, and then a subsequent decrease.