• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.328-330
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• 2003

The land cover of burned area has changed dramatically since Daxinganling forest fire in Northeastern China during May 6 ? June 4, 1987. This research focused on determining the burn severity and assessment of forest recovery. Burned severity was classified into three levels from June 1987 Landsat TM data acquired just after the fire. A regression model was established between the forest canopy closure from 1999 forest stand map and the NDVI values from June 2000 Landsat ETM+ data. The map of canopy closure was got according to the regression model. And vegetation cover was classified into four types according to forest closure density. The change matrix was built using the classified map of burn severity and vegetation recovery. Then the change conversions of every forest type were analyzed. Results from this research indicate: forest recovery status is well in most of burned scars; and vegetation change detection can be accomplished using postclassification comparison method.

• Child Health Nursing Research
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• v.29 no.2
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• pp.149-160
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• 2023

Purpose: Based on the health belief model and theory of planned behavior, this study investigated how age group (adolescence and emerging adulthood) moderated the relative effects of perceived susceptibility, perceived severity, and subjective norms on preventive behavior against coronavirus disease 2019 (COVID-19). Methods: This secondary data analysis utilized data from adolescents (n=272) and emerging adults (n=239). Hierarchical multiple regression analysis was performed to test the moderating effect of age group on the relationships among variables. Results: Higher perceived susceptibility (β=.21, p<.001), perceived severity (β=.14, p=.002), subjective norms (friends) (β=.26, p<.001), subjective norms (parents) (β=.44, p<.001), and subjective norms (schools) (β=.28, p<.001) enhanced COVID-19 preventive behaviors. Moderated regression analysis showed that subjective norms (friends and school) impacted preventive behavior in adolescents more than in emerging adults. Conclusion: Given the need to increase perceived susceptibility and severity among adolescents and emerging adults, these findings provide baseline data for designing effective COVID-19 prevention interventions that consider the developmental characteristics of different age groups. Interventions by health centers at universities can strengthen COVID-19 preventive behavior among emerging adults. As adolescents are influenced by friends, their peer roles must be strengthened to enhance adherence to COVID-19 preventive guidelines.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.113-119
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• 2022

In software fault prediction, a multi classification model that predicts the fault severity category of a module can be much more useful than a binary classification model that simply predicts the presence or absence of faults. A small number of severity-based fault prediction models have been proposed, but no classifier using deep learning techniques has been proposed. In this paper, we construct MLP models with 3 or 5 hidden layers, and they have a structure with a fixed or variable number of hidden layer nodes. As a result of the model evaluation experiment, MLP-based deep learning models shows significantly better performance in both Accuracy and AUC than MLPs, which showed the best performance among models that did not use deep learning. In particular, the model structure with 3 hidden layers, 32 batch size, and 64 nodes shows the best performance.

• Journal of the Korean Society of Safety
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• v.27 no.4
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• pp.108-114
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• 2012

Traffic Accident Merging Index(TAMI) is developed for TMACS(Traffic Safety Information Management Complex System). TAMI is calculated by combining 'Severity Index' and 'Frequency'. This paper suggest the accurate TAMI prediction model by time series forecasting. Preventing the traffic accident by accurately predicting it in advance can greatly improve road traffic safety. Searches the model which minimizes the error of 230 local self-governing groups. TAMI of 2007~2009 years data predicts TAMI of 2010. And TAMI of 2010 compares an actual index and a prediction index. And the error is minimized the constant where selects. Exponential Smoothing model was selected. And smoothing constant was decided with 0.59. TAMI Forecasting model provides traffic next year safety information of the local government.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.12-28
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• 2019

Road geometry is one of the many factors that cause crashes, but the effect on traffic accident depends on weather conditions even under the same road geometry. This study identifies the variables affecting the crash severity by matching the highway accident data and weather data for 14 years from 2001 to 2014. A hierarchical ordered Logit model is used to reflect the effects of road geometry and weather condition interactions on crash severity, as well as the correlation between individual crashes in a region. Among the hierarchical models, we apply a random intercept model including interaction variables between road geometry and weather condition and a random coefficient model including regional weather characteristics as upper-level variables. As a result, it is confirmed that the effects of toll, ramp, downhill slope of 3% or more, and concrete barrier on the crash severity vary depending on weather conditions. It also shows that the combined effects of road geometry and weather conditions may not be linear depending on rainfall or snowfall levels. Finally, we suggest safety improvement measures based on the results of this study, which are expected to reduce the severity of traffic accidents in the future.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.4910-4918
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• 2013

This study aims to design a Severity-Adjusted LOS(Length of Stay) Model in order to efficiently manage LOS of AMI(Acute Myocardial Infarction) patients. We designed a Severity-Adjusted LOS Model with using data-mining methods(multiple regression analysis, decision trees, and neural network) which covered 6,074 AMI patients who showed the diagnosis of I21 from 2004-2009 Korean National Hospital Discharge in-depth Injury Survey. A decision tree model was chosen for the final model that produced superior results. This study discovered that the execution of CABG, status at discharge(alive or dead), comorbidity index, etc. were major factors affecting a Sevirity-Adjustment of LOS of AMI patients. The difference between real LOS and adjusted LOS resulted from hospital location and bed size. The efficient management of LOS of AMI patients requires that we need to perform various activities after identifying differentiating factors. These factors can be specified by applying each hospital's data into this newly designed Severity-Adjusted LOS Model.

• Journal of Korean Academy of Nursing
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• v.45 no.1
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• pp.97-106
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• 2015

Purpose: This study was done to develop and test a structural model for caregiving experience including caregiving satisfaction and caregiving strain in families providing care for family members with a mental disorder. Methods: The Stress-appraisal-coping model was used as the conceptual framework and the structural equation model to confirm the path that explains what and how variables affect caregiving experience in these families. In this hypothesis model, exogenous variables were optimism, severity of illness and uncertainty. The endogenous variables were self efficacy, social support, caregiving satisfaction and caregiving strain. Data were collected using structured questionnaires. Results: Optimism and caregiving self-efficacy had significant direct and indirect effects on caregiving satisfaction. Optimism, severity of illness and uncertainty had significant direct and indirect effects on caregiving strain. The modified path model explained effects of optimism on caregiving self-efficacy with social support in the path structure as a mediator. Also, there were direct and indirect effects of optimism and uncertainty on caregiving satisfaction with social support and caregiving self-efficacy in the path structure as a mediators. Conclusion: Results suggest the need to improve caregiving self-efficacy of these families, establish support systems such as a mental health professional support programs for caregiving self-efficacy. Optimism, severity of illness and uncertainty perceived by families need to be considered in the development of support programs in order to increase their effectiveness.

• Journal of Korean Academy of Nursing
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• v.52 no.3
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• pp.308-323
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• 2022

Purpose: This study aimed to construct and test a predictive model for the quality of life (QOL) in mothers of children with developmental disabilities (DB). The hypothesized model included severity of illness, distress, uncertainty, self-help, and parenting efficacy as influencing factors, QOL as a consequence based on the Braden's Self-Help Model. Methods: The data were collected through a direct and online surveys from 206 mothers in 8 locations, including welfare or daycare centers, developmental treatment centers, and The Parents' Coalition for the Disabled located in two provinces of Korea. Data were analysed using SPSS/WIN 23.0 and AMOS 21.0 program. Results: The fit indices of the predictive model satisfied recommended levels; 𝛘² = 165.79 (p < .001), normed 𝛘² (𝛘²/df) = 2.44, RMR = .04, RMSEA = .08, GFI = .90, AGFI = .85, NFI = .91, TLI = .93, CFI = .95. Among the variables, distress (β = - .46, p < .001), parenting efficacy (β = .22, p < .001), and self-help (β = .17, p = .018) had direct effects on QOL. Severity of illness (β = - .61, p = .010) and uncertainty (β = - .08, p = .014) showed indirect effects. The explanatory power of variables was 61.0%. Conclusion: The study results confirm the utility of Braden's Self-Help Model. They provide a theoretical basis for improving QOL in mothers of children with DB. Nursing intervention strategies that can relieve mothers' distress and uncertainty related to disease and enhance parenting efficacy and self-help behavior should be considered.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.6
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• pp.133-144
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• 2012

This study focused on estimating influential factors of traffic accidents and analyzing traffic accident severity of elderly and non elderly using traffic accident data. In order to reclassify elderly and non elderly traffic accident by a statistical method from entire traffic accident data, multiple discriminant analysis was applied. Also ordered logit model was applied for analyzing traffic accident severities using traffic accident severities as an independent variable and transportation facilities, road conditions and human characteristics as dependent variables. As results of the comparison between elderly and non elderly traffic accident, the traffic accident severity was affected by the age, types of traffic accidents, human characteristics and road conditions as well. Also, transportation facilities and road conditions affected to more elderly traffic accident than non elderly. Therefore, traffic accident severity would be decreased with the improvement of transportation facilities and road conditions for the elderly.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.917-923
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• 2018

In recent, technological advancement including a vehicle black box (VBB) has led to reducing such underreporting issues and errors of crash data. The objective of this study is to analyze the injury severity of cyclists on taxi-to-two wheeler crashes based on the accurate crash data collected from the VBB in taxi. This study defined the two wheelers as bicycle and motorcycle. To perform this study, we used the VBB data collected from taxis operating in Incheon, South Korea for a two-year period (2010-2011). An ordered probit model was applied to analyze the injury severity in crashes. As a result, new injury severity factors were found: increase of the crash speed of taxi, damage of crash-involved vehicles (i.e., taxi and/or two wheeler), not standing of cyclists after crash, and second or third impact of cyclists after first crash.