• Journal of the Korean Society of Safety
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• v.37 no.2
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• pp.1-9
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• 2022

Most factories deal with toxic or flammable chemicals in their industrial processes. These hazardous substances pose a risk of leakage due to accidents, such as fire and explosion. In the event of chemical release, massive casualties and property damage can result; hence, quantitative risk prediction and assessment are necessary. Several methods are available for evaluating chemical dispersion in the atmosphere, and most analyses are considered neutral in dispersion models and under far-field wind condition. The foregoing assumption renders a model valid only after a considerable time has elapsed from the moment chemicals are released or dispersed from a source. Hence, an initial dispersion model is required to assess risk quantitatively and predict the extent of damage because the most dangerous locations are those near a leak source. In this study, the dispersion model for initial consequence analysis was developed with three-dimensional unsteady advective diffusion equation. In this expression, instantaneous leakage is assumed as a puff, and wind velocity is considered as a coordinate transform in the solution. To minimize the buoyant force, ethane is used as leaked fuel, and two different diffusion coefficients are introduced. The calculated concentration field with a molecular diffusion coefficient shows a moving circular iso-line in the horizontal plane. The maximum concentration decreases as time progresses and distance increases. In the case of using a coefficient for turbulent diffusion, the dispersion along the wind velocity direction is enhanced, and an elliptic iso-contour line is found. The result yielded by a widely used commercial program, ALOHA, was compared with the end point of the lower explosion limit. In the future, we plan to build a more accurate and general initial risk assessment model by considering the turbulence diffusion and buoyancy effect on dispersion.

• Physical Therapy Korea
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• v.27 no.2
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• pp.140-148
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• 2020

Background: Scapular winging (SW) could be caused by tightness or weakness of the periscapular muscles. Although data mining techniques are useful in classifying or predicting risk of musculoskeletal disorder, predictive models for risk of musculoskeletal disorder using the results of clinical test or quantitative data are scarce. Objects: This study aimed to (1) investigate the difference between young women with and without SW, (2) establish a predictive model for presence of SW, and (3) determine the cutoff value of each variable for predicting the risk of SW using the decision tree method. Methods: Fifty young female subjects participated in this study. To classify the presence of SW as the outcome variable, scapular protractor strength, elbow flexor strength, shoulder internal rotation, and whether the scapula is in the dominant or nondominant side were determined. Results: The classification tree selected scapular protractor strength, shoulder internal rotation range of motion, and whether the scapula is in the dominant or nondominant side as predictor variables. The classification tree model correctly classified 78.79% (p = 0.02) of the training data set. The accuracy obtained by the classification tree on the test data set was 82.35% (p = 0.04). Conclusion: The classification tree showed acceptable accuracy (82.35%) and high specificity (95.65%) but low sensitivity (54.55%). Based on the predictive model in this study, we suggested that 20% of body weight in scapular protractor strength is a meaningful cutoff value for presence of SW.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.7
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• pp.3009-3014
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• 2015

The epidermal growth factor (EGF) may play a pathological role in hepatocellular carcinoma (HCC). However, the conclusions of published reports on the relationship between the EGF $61^*A/G$ polymorphism and HCC risk remain controversial. To derive a more precise estimation we performed a meta-analysis based on 14 studies that together included 2,506 cases and 4,386 controls. PubMed, EMBASE, Web of Knowledge and the Chinese National Knowledge Infrastructure (CNKI) databases were used to retrieve articles up to August 1, 2014. The crude odds ratios (ORs) with 95% confidence intervals (95%CIs) were calculated to evaluate the association. Meta-analysis results showed a significant association between the EGF $61^*A/G$ polymorphism and HCC risk in all four genetic models (allele model: OR=1.25, 95%CI=1.12-1.40; dominant model: OR=1.32, 95%CI=1.14-1.54; recessive model: OR=1.33, 95%CI=1.12-1.58; ho-mozygous model: OR=1.59, 95%CI=1.33-1.90). Moreover, significant associations were observed when stratified by ethnicity, source of controls, etiology and genotype methods. Thus, this meta-analysis suggests that the G-allele of the EGF $61^*A/G$ polymorphism is associated with an increased risk of HCC, especially in Asians and Caucasians, without influence from the source of controls or etiological diversity. Further studies with larger population sizes are needed to confirm these results.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.2249-2252
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• 2012

Objective: Methylenetetrahydrofolate reductase (MTHFR) gene polymorphisms have been reported to be associated with pancreatic cancer, but the published studies had yielded inconsistent results.We therefore performed the present meta-analysis. Methods: A search of Google scholar, PubMed, Cochrane Library and CNKI databases before April 2012 was conducted to summarize associations of MTHFR polymorphisms with pancreatic cancer risk. Assessment was with odds ratios (ORs) and 95% confidence intervals (CIs). Publication bias were also calculated. Results: Four relative studies on MTHFR gene polymorphisms (C667T and A1298C) were involved in this meta-analysis. Overall, C667T(TT vs. CC : OR = 1.61, 95%CI = 0.78 - 3.34; TT vs. CT : OR = 1.41, 95%CI = 0.88-2.25; dominant model: OR = 0.68, 95%CI = 0.40-1.17; recessive model: OR = 0.82, 95%CI = 0.52-1.30) and A1298C(CC vs. AA:OR=1.01, 95%CI=0.47-2.17; CC vs. AC: OR=0.99,95%CI=0.46-2.14; dominant model: OR=1.01, 95%CI = 0.47-2.20; recessive model: OR = 1.01, 95%CI = 0.80-1.26) did not increase pancreatic cancer risk. Conclusion: This meta-analysis indicated that MTHFR polymorphisms (C667T and A1298C) were not associated with pancreatic cancer risk.

• Journal of Navigation and Port Research
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• v.36 no.1
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• pp.9-14
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• 2012

Maritime security incidents by pirates and by terrorists increase, but maritime incidents investigation models are limited to figure out the maritime security incidents. This paper provides the analysis model for maritime security incidents. To develop this analysis model, this categorizes five threat factors, the ship, the cargo type, port system, human factor, information flow system, makes the risk assessment matrix to quantify the risk related to threat factors and classifies four priority categories of risk assessment matrix. Also, this model makes from the frameworks which include a variety of security initiatives implementing in stakeholder levels like international organizations, individual governments, shipping companies, and the ship. Therefore, this paper develops the Analysis for Maritime Security Management model based on various security initiatives responding to the stakeholder levels of maritime security management and top-bottom/bottom-up decision trees, and shows the validity through verifying the real maritime security incident of M/V Petro Ranger.

• Computers and Concrete
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• v.19 no.3
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• pp.305-313
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• 2017

A robust finite element based reinforced concrete bridge deck corrosion initiation model is applied for time-dependent probabilistic sensitivity analysis. The model is focused on uncertainties in the governing parameters that include variation of high performance concrete (HPC) diffusion coefficients, concrete cover depth, surface chloride concentration, holidays in reinforcements, coatings and critical chloride threshold level in several steel reinforcements. The corrosion initiation risk is expressed in the form of probability over intended life span of the bridge deck. Conducted study shows the time-dependent sensitivity analysis to evaluate the significance of governing parameters on chloride ingress rate, various steel reinforcement protection and the corrosion initiation likelihood. Results from this probabilistic analysis provide better insight into the effect of input parameters variation on the estimate of the corrosion initiation risk for the design of concrete structures in harsh chloride environments.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.1769-1772
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• 2013

A case-control study of the association of miR-499A>G rs3746444 with risk of hepatocellular carcinoma (HCC)was conducted. Patients with HCC and healthy control subjects were recruited for genotyping of miR-499A>G using duplex polymerase-chain-reaction with confronting-two-pair primer(PCR-RFLP) analysis. The MiR-499 GG genotype was associated with a decreased risk of HCC as compared with the miR-499 AA genotype (adjusted OR=0.74, 95%CI=0.24-0.96). Similarly, the GG genotype showed a 0.45-fold decreased HCC risk in a recessive model. The MiR-499 G allele was significantly associated with decreased risk of HCC among patients infected with HBV in a dominant model (OR=0.09, 95%CI= 0.02-0.29). In conclusion, the MiR-499A>G rs3746444 polymorphism is associated with HCC risk in the Chinese population, and may be useful predictive marker for CAD susceptibility.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7515-7520
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• 2014

Many studies have indicated possible associations between a polymorphism of adiponectin receptor 1 (ADIPOR1) rs1342387 and risk of cancer, but contradictory results have been reported. The main aim of this study was to draw a reliable conclusion about the relationship between the rs1342387 polymorphism and cancer incidence, by conducting a literature search of Pubmed, Embase, Wanfang and Cochrane libraries. Eleven studies including 3, 738 cases and 4, 748 controls were identified in this meta-analysis. The ADIPOR1 rs1342387 polymorphism was associated with risk of colorectal cancer for all genetic comparison models (GG vs AA, OR: 1.44, 95%CI: 1.21-1.70; G carriers vs A carriers, OR: 1.23, 95%CI: 1.11-1.36; dominant model, OR: 1.28, 95%CI: 1.10-1.49 and recessive model, OR: 1.31, 95%CI: 1.12-1.55). Stratified by ethnicity, the rs1342387 polymorphism was significantly associated with risk of colorectal cancer in Asian ancestry for all genetic comparison models (GG vs AA, OR: 1.56, 95%CI: 1.26-1.92; G carriers vs. A carriers OR: 1.30, 95%CI: 1.18-1.43; dominant model OR: 1.31, 95%CI: 1.08-1.60 and recessive model OR: 1.44, 95%CI: 1.26-1.64), but not in Caucasian or mixed (Caucasian mainly) groups. In summary, the ADIPOR1 rs1342387 polymorphism is significantly associated with risk of colorectal cancer among individuals of Asian ancestry.

• Earthquakes and Structures
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• v.18 no.1
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• pp.73-82
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• 2020

With the coal mining depth increasing, both stress and gas pressure rapidly enhance, causing coal and gas outburst risk to become more complex and severe. The conventional method for prediction of coal and gas outburst adopts one prediction index and corresponding critical value to forecast and cannot reflect all the factors impacting coal and gas outburst, thus it is characteristic of false and missing forecasts and poor accuracy. For the reason, based on analyses of both the prediction indicators and the factors impacting coal and gas outburst at the test site, this work carefully selected 6 prediction indicators such as the index of gas desorption from drill cuttings Δh₂, the amount of drill cuttings S, gas content W, the gas initial diffusion velocity index ΔP, the intensity of electromagnetic radiation E and its number of pulse N, constructed the Bayes discriminant analysis (BDA) index system, studied the BDA-based multi-index comprehensive model for forecast of coal and gas outburst risk, and used the established discriminant model to conduct coal and gas outburst prediction. Results showed that the BDA - based multi-index comprehensive model for prediction of coal and gas outburst has an 100% of prediction accuracy, without wrong and omitted predictions, can also accurately forecast the outburst risk even for the low indicators outburst. The prediction method set up by this study has a broad application prospect in the prediction of coal and gas outburst risk.

• The Journal of Engineering Geology
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• v.30 no.4
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• pp.663-671
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• 2020

Recently, there have been many natural disasters in Korea, not only in forest areas but also in urban areas, and the national requirements for them are increasing. In particular, there is no pre-disaster information system that can systematically manage the collapse of the slope of the national highway. In this study, big data analysis was conducted on the factors causing slope collapse based on the detailed investigation report on the slope collapse of national roads in Gangwon-do and Gyeongsang-do areas managed by the Cut Slope Management System (CSMS) and the basic survey of slope failures. Based on the analysis results, a slope collapse risk prediction model was established through Adaboost, a classification-based machine learning model, reflecting the collapse slope location and weather information. It also developed a visualization map for the risk of slope collapse, which is a visualization program, to show that it can be used for preemptive disaster prevention measures by identifying the risk of slope due to changes in weather conditions.