• Korean Journal of Childcare and Education
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• v.17 no.5
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• pp.83-103
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• 2021

Objective: This study aimed to develop a longitudinal predictive model that identifies first-grade children who are at risk for ADHD and to investigate the factors that predict the probability of belonging to the at-risk group for ADHD by using machine learning. Methods: The data of 1,445 first-grade children from the 1st, 3rd, 6th, 7th, and 8th waves of the Korean Children's Panel were analyzed. The output factors were the at-risk and non-risk group for ADHD divided by the CBCL DSM-ADHD scale. Prenatal as well as developmental factors during infancy and early childhood were used as input factors. Results: The model that best classifies the at-risk and the non-risk group for ADHD was the LASSO model. The input factors which increased the probability of being in the at-risk group for ADHD were temperament of negative emotionality, communication abilities, gross motor skills, social competences, and academic readiness. Conclusion/Implications: The outcomes indicate that children who showed specific risk indicators during infancy and early childhood are likely to be classified as being at risk for ADHD when entering elementary schools. The results may enable parents and clinicians to identify children with ADHD early by observing early signs and thus provide interventions as early as possible.

• Journal of the Korea Institute of Building Construction
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• v.19 no.1
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• pp.77-86
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• 2019

Due to the increasing demand for and complexity of plant construction projects, unpredictable risk factors are on the consequent increase. For that reason, the quantitative risk analysis is being called for, in order for the development of a risk assessment model using risk indicators for the plant construction projects. This study used the claim payout data collected at a global insurance company to reflect the actual financial losses in plant construction projects as dependent variables in the risk assessment model. In terms of independent variables, the geographic information, i. e., landform, and the construction information including test-run, schedule rate, total cost and duration are adopted. In addition, this study suggests that the regression model containing such independent variables that are statistically significant can be applied to as a foundational guideline for the plant construction project risk analysis during the phase of construction and commissioning.

• 재활복지
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• v.21 no.2
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• pp.1-27
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• 2017

The purpose of this study is to evaluate the level of implementation of the Incheon Strategy and to develop measures for effective implementation. This research method used literature review and monitoring method. The results of the study are summarized as follows: First, 9 key indicators and 7 supplementary indicators, which are classified into implementation and non-implementation, 3 key indicators have been implemented, one indicator has been partially implemented, 5 indicators have not yet been implemented, Also, In the case of supplementary indicators, five were implemented and two were not. Second, the ten target areas are lacking in implementation, but the objective of 7 is to ensure the comprehensive disaster risk reduction and management, the ratification and implementation of the Convention on the Rights of Persons with Disabilities and the harmonization of the Convention with the domestic law, Also, it is analyzed that the level of implementation is in the order of improving the reliability and comparability of the data of goal 8, ensuring gender equality of goal 6 and strengthening the capacity of women. Based on these results, we propose an improvement plan for implementation. First, it is necessary to formulate policy issues and implement measures for the implementation of Incheon Strategy. Second, it is necessary to establish a system to implement and monitor for Incheon strategy. Third, Korean standards for goals and targets, key indicators and supplementary indicators are needed. Fourth, it is necessary to prioritize the target implementation and to take preemptive action. Lastly, it is necessary to educate and publicize for the Incheon strategy.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.191-196
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• 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
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• v.15 no.8
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• pp.5-11
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• 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
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• v.43 no.3
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• pp.264-274
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• 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
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• v.54 no.5
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• pp.489-500
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• 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
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• v.43 no.1
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• pp.19-26
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• 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
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• v.19 no.1
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• pp.81-91
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• 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
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• v.7 no.11
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• pp.717-725
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• 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.