• Journal of Digital Convergence
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• v.11 no.1
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• pp.381-388
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• 2013

The study was done to identify factors influencing the health risk behavior of the chronic mental illness in the community. A cross-sectional study design was used in this study. The sample was 255 chronic mentally ill persons from D city and C province and who agreed to participate in the study. Data were collected on August-september, 2011 and analyzed using the SPSS/WIN 20. Stress event, insight and depression had significant correlations with health risk behavior. Hierarchial regression analysis showed gender (men), diagnosis (schizophrenia), stress event, insight and depression together explained 24% of variance in health risk behavior. Findings of this study allow a comprehensive understanding of health risk behavior of the chronic mentally ill persons in community. It is necessary to integrated health promotion programs designed for this population should focus on these factors for effective behavioral modification.

• Geotechnical Engineering
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• v.9 no.3
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• pp.67-76
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• 1993

Korea being composed of a number of mountains has been damaged and destroyed in lives and properties by the occurrence of many landslides during the wet seasons. Therefore, it is necessary to study the forecast system and risk analysis for the occurrence of landslides : the rise of groundwater levels due to rainfall is the main cause of landslides. In this paper, the autoregressive models are used to predict the grondwater levls using cases of both time invariant and time -varing autoregressive coefficients. In the former case, AR(1), AR(2), and AR(3) models are selected and their single-valued parameters are estimated to fit them to the observed groundwater level series. In the latter case, modified AR(1) and typical AR(2) models are used as process model and a discrete Kalman Filtering technique is utilized to estimate the parameters which are themselves a function of time. The results show that the real time forecast system using the time-varying autoregressive coefficinets as well as time -invariant AR model is good to predict the groundwater level in hillside slopes and we might get better result if we use the time-hourly rainfall intensity as well as the observed groundwater level.

• Journal of Korean Society of Forest Science
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• v.105 no.4
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• pp.429-434
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• 2016

Slope failures in forest roads often result in social and economic loss as well as environmental damage. This study was carried out to assess susceptibility of slope failures of forest roads in Hongcheon-gun, Gangwon-do where many slope failures occurred after heavy rainfall in 2013 using GIS and logistic regression analysis. The results showed that sandy soil (6.616) in soil texture type had the highest susceptibility to slope failures while medium class (-3.282) in tree diameter showed the lowest susceptibility. A error matrix for both slope failure and non-slope failure area was made and a model was developed showing a classification accuracy of 74.6%. Non-slope failures area in the forest roads were classified mostly in the range of >0.7 which was higher values than the classification criteria (0.5) used by the logistic regression model. It is suggested that considering forest environment and site factors related to forest road failures would improve the accuracy in predicting susceptibility of slope failures.

• Clinical and Experimental Pediatrics
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• v.50 no.7
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• pp.629-635
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• 2007

Purpose : This study was conducted to assess the usefulness of fat-free mass index (FFMI) and fat mass index (FMI) as novel expression methods of body composition in children. Methods : A total of 466 Second grade students-248 boys and 218 girls- from all elementary schools the Gwacheon City underwent anthropometric measures including bioelectrical impedance analysis (BIA) and biochemical tests. The correlation coefficients between obesity indices, including FMI and FFMI, and metabolic risk factors, were assessed. Metabolic risk factors of children with increased FMI were compared with those of children with normal FMI. We compared FMI and FFMI percentile distribution between this study's subjects and the subjects of the Fukuoka body composition study. Results : FMI was lower and FFMI was higher in this study's subjects compared to the subjects of the Fukuoka body composition study. FMI was correlated with other obesity indices and several metabolic risk factors. Metabolic risk was higher in children with increased FMI than in children with normal FMI. Conclusion : FMI and FFMI were useful indicators in comparing difference of body composition among children that had different body size and growth. High FMI was related to increase of metabolic risk in children.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.6
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• pp.822-831
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• 2021

Although programs have been developed to evaluate the risk of dragging anchors, it is practically difficult for VTS(vessel traffic service) operators to calculate and evaluate these risks by obtaining input factors from anchored ships. Therefore, in this study, the gross tonnage (GT) that could be easily obtained from the ship by the VTS operators was set as an independent variable, and linear and nonlinear regression analyses were performed using the input factors as the dependent variables. From comparing the fit of the polynomial model (linear) and power series model (nonlinear), the power series model was evaluated to be more suitable for all input factors in the case of container ships and bulk carriers. However, in the case of tanker ships, the power supply model was suitable for the LBP(length between perpendiculars), width, and draft, and the polynomial model was evaluated to be more suitable for the front wind pressure area, weight of the anchor, equipment number, and height of the hawse pipe from the bottom of the ship. In addition, all other dependent variables, except for the front wind pressure area factor of the tanker ship, showed high degrees of fit with a coefficient of determination (R-squared value) of 0.7 or more. Therefore, among the input factors of the dragging anchor risk assessment program, all factors except the external force, seabed quality, water depth, and amount of anchor chain let out are automatically applied by the regression analysis model formula when only the GT of the ship is provided.

• Environmental and Resource Economics Review
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• v.15 no.2
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• pp.147-175
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• 2006

This paper attempts to incorporate three important factors-perceptions, behavior and valuation-in analysing consumers' responses to health risks from environmental pollutants. Using a survey sample of 500 consumers in the Chonbuk province area, this paper empirically investigated determinants of risk perceptions from using tap water as drinking water. Most consumers were considerably concerned about health risks from drinking tap water. Moreover, those subjective concerns were not random, but were systematically related to individuals' demographic variables such as age, gender, and family size. Those subjective beliefs also influenced respondents' purchase intentions on safer water bottles, in response to a contingent behavior question of presenting two types of water bottles. The technical risk information provided in the survey had significant effects on purchase intentions only when it was interacted with respondents' actual averting practice. In addition, the sample selection effects were present by eliminating respondents who decided not to purchase either of two types of water bottles. The potential selection bias had impacts on the coefficients of the price difference variable, and subsequently the estimates of the price increments for health risk reductions.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.4
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• pp.459-466
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• 2018

Hazardous and Noxious Substances (HNS) are defined as substances that are likely to create a significant impact on human health and marine ecosystem when they are released into the marine environment. Recently, as the volume of HNS transported by ships increases, the rate of leakage accidents also increases. Therefore, research should be conducted to control and monitor sunken materials from the viewpoint of technology development for hazardous material leakage accident response. In this paper, acoustic detection experiments were carried out using HNS substitute materials in order to confirm the possibility of acoustic detection of sunken HNS on the sediment. The castor oil, which has a similar acoustic impedance with chloroform, is used as a substitute. 200 kHz high frequency signals were used to discriminate the reflected signals and measure reflection loss from the interface between water and castor oil. The reflection loss measured is in good agreement with the modeling results, showing a possibility of acoustic detection for sunken HNS.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.5
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• pp.527-534
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• 2019

Several types of mathematical analysis methods are used for port waterway risk assessment based on marine traffic volume. In Korea, a marine traffic congestion model that standardizes the size of the vessels passing through the port waterway is applied to evaluate the risk of the waterway. For example, when marine traffic congestion is high, risk situations such as collisions are likely to occur. However, a scientific review is required to determine if there is a correlation between high density of maritime traffic and a high risk of waterway incidents. In this study, IWRAP Mk2(IALA official recommendation evaluation model) and a marine traffic congestion model were used to analyze the correlation between port waterway risk and marine traffic congestion in the same area. As a result, the linear function of R2 was calculated as 0.943 and it was determined to be significant. The Pearson correlation coefficient was calculated as 0.971, indicating a strong positive correlation. It was confirmed that the port waterway risk and the marine traffic congestion have a strong correlation due to the influence of the common input variables of each model. It is expected that these results will be used in the development of advanced models for the prediction of port waterway risk assessment.

• Environmental and Resource Economics Review
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• v.28 no.3
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• pp.355-383
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• 2019

This study is to investigate whether averting costs for wearing $anti-PM_{10}$ masks and using air purifiers at home to reduce exposure from $PM_{10}$ are influenced by subjective risk perceptions and/or objective $PM_{10}$ concentration levels, whose estimates will be used to measure the willingness to pay for $PM_{10}$ risk reduction. An empirical analysis was conducted on a sample of 1,224 respondents who participated in the web-based survey in the late October of 2017. As we reflect the potential endogeniety bias in the estimation of averting cost functions of using air purifiers, the coefficients of risk perception were differed by 6~7 times. Respondents. subjective risk perceptions were influenced by individuals' knowledge, attitudes and demographic variables, as well as the levels of $PM_{10}$ concentrations in their residential region. The marginal willingness to pay for risk reductions at the mean levels of their risk perceptions were measured at 1,000 won per month from wearing $anti-PM_{10}$ masks and 6,000 won for using air purifiers respectively.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.781-791
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• 2022

It is crucial to provide forest fire risk forecast information to minimize forest fire-related losses. In this research, forecast models of forest fire risk at a mid-range (with lead times up to 7 days) scale were developed considering past, present and future conditions (i.e., forest fire risk, drought, and weather) through random forest machine learning over South Korea. The models were developed using weather forecast data from the Global Data Assessment and Prediction System, historical and current Fire Risk Index (FRI) information, and environmental factors (i.e., elevation, forest fire hazard index, and drought index). Three schemes were examined: scheme 1 using historical values of FRI and drought index, scheme 2 using historical values of FRI only, and scheme 3 using the temporal patterns of FRI and drought index. The models showed high accuracy (Pearson correlation coefficient >0.8, relative root mean square error <10%), regardless of the lead times, resulting in a good agreement with actual forest fire events. The use of the historical FRI itself as an input variable rather than the trend of the historical FRI produced more accurate results, regardless of the drought index used.