• Journal of the Korean Society of Safety
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• v.9 no.1
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• pp.89-94
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• 1994

Two methods, the numerical method of CPQRA and the manual method of IAEA, were used to estimate the effect distance from release and dispersion of toxic materials. The Gaussian plume model which has a weather stability class D with wind velocity of 5m/s was applied to calculate dispersion of toxic materials. Also, probit function were employed to evaluate the human fatality as a result of exposure to toxic gases. Furthermore, concentration of toxic materials corresponding to LC$_{50}$ for 30 min could be determined by setting Pr as 5.0 and solving the probit function. Calculations were conducted by employing chlorine and ammonia as toxic materials because they are not only most commonly used In chemical plants but also very harmful to humans. Calculated results by employing toxic materials indicated that the effect distance from the CPQRA method was between the minimum and maximum distance from the method proposed by IAEA.A.

• Journal of the Korean Institute of Gas
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• v.7 no.1 s.18
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• pp.10-18
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• 2003

Consequence model has been suggested to evaluate consequence of city gas accident considering actual situation. Through event tree analysis(ETA), probable accidents were summarized and listed. Then release rate was calculated both sonic and subsonic conditions. Among city gas accidents, fire damage is the dominant one and mainly discussed; fatality, burning injury, and damage to building were estimated using the consequence model suggested. With an appropriate conditions, calculating total cost by accident was suggested.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.471-478
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• 2020

In this paper, we develop the ground risk model of unmanned aerial vehicle (UAV) operation to quantify the ground risk when the UAV falls to the ground during the intended operation in case of UAV failure. The ground risk is computed by using the UAV failure probability, the probability of impact a person when UAV falls to the ground, the probability of fatality when UAV strikes the person. We mathematically derive each probability to evaluate the ground risk of UAV operation. Also, the population density map, building to land ratio map, car traffic database is used to estimate the number of people exposed to collision with UAV. Finally, we assumed the operations of a UAV with two paths in Daejeon city and evaluate the ground risk of each UAV operations.

• Genomics & Informatics
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• v.20 no.2
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• pp.22.1-22.9
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• 2022

The rise of newer coronavirus disease 2019 (COVID-19) variants has brought a challenge to ending the spread of COVID-19. The variants have a different fatality, morbidity, and transmission rates and affect vaccine efficacy differently. Therefore, the impact of each new variant on the spread of COVID-19 is of interest to governments and scientists. Here, we proposed mathematical SEIQRDVP and SEIQRDV3P models to predict the impact of the Omicron variant on the spread of the COVID-19 situation in South Korea. SEIQEDVP considers one vaccine level at a time while SEIQRDV3P considers three vaccination levels (only one dose received, full doses received, and full doses + booster shots received) simultaneously. The omicron variant's effect was contemplated as a weighted sum of the delta and omicron variants' transmission rate and tuned using a hyperparameter k. Our models' performances were compared with common models like SEIR, SEIQR, and SEIQRDVUP using the root mean square error (RMSE). SEIQRDV3P performed better than the SEIQRDVP model. Without consideration of the variant effect, we don't see a rapid rise in COVID-19 cases and high RMSE values. But, with consideration of the omicron variant, we predicted a continuous rapid rise in COVID-19 cases until maybe herd immunity is developed in the population. Also, the RMSE value for the SEIQRDV3P model decreased by 27.4%. Therefore, modeling the impact of any new risen variant is crucial in determining the trajectory of the spread of COVID-19 and determining policies to be implemented.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.85-96
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• 2023

The number of traffic accidents caused by wet or icy road surface conditions is on the rise every year. Car crashes in such bad road conditions can increase fatalities and serious injuries. Historical data (from the year 2016 to the year 2020) on weather-related traffic accidents show that the fatality rates are fairly high in Korea. This requires accurate prediction and identification of hazardous road conditions. In this study, a forecasting model is developed to predict the chances of traffic accidents that can occur on roads affected by weather and road surface conditions. Multiple deep learning algorithms taking into account AlexNet and 2D-CNN are employed. Data on orthophoto images, automatic weather systems, automated synoptic observing systems, and road surfaces are used for training and testing purposes. The orthophotos images are pre-processed before using them as input data for the modeling process. The procedure involves image segmentation techniques as well as the Z-Curve index. Results indicate that there is an acceptable performance of prediction such as 65% for dry, 46% for moist, and 33% for wet road conditions. The overall accuracy of the model is 53%. The findings of the study may contribute to developing comprehensive measures for enhancing road safety.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.142-148
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• 2023

In Modern days, Self-driving for modern people is an absolute necessity for transportation and many other reasons. Additionally, after the outbreak of COVID-19, driving by oneself is preferred over other means of transportation for the prevention of infection. However, due to the constant exposure to stressful situations and chronic fatigue one experiences from the work or the traffic to and from it, modern drivers often drive under drowsiness which can lead to serious accidents and fatality. To address this problem, we propose a drowsy driving prevention learning model which detects a driver's state of drowsiness. Furthermore, a method to sound a warning message after drowsiness detection is also presented. This is to use MoveNet to quickly and accurately extract the keypoints of the body of the driver and Dense Neural Network(DNN) to train on real-time driving behaviors, which then immediately warns if an abnormal drowsy posture is detected. With this method, we expect reduction in traffic accident and enhancement in overall traffic safety.

• Journal of the Korea Institute of Building Construction
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• v.17 no.2
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• pp.191-197
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• 2017

The safety nature of construction industry differs from that of manufacturing sector. For instance, accident risk level dramatically varies at each phase of construction process. Korean Occupational and Health Safety Act has been regulated OHS expense and it contributed reducing accident risk and enhancing safety culture for many years. However, although current regulation guides to use OHS expense proportionate to construction progress, it still allows late use of the expense. This study was conducted for the purpose of presenting methods of estimating a step-by-step OHS expense rate required at each construction phase. In order to do provide proper OHS expense schedule, it analysed accident risk of each construction phase by sorting out 1439 cases of construction site fatality reports, and proposed a method of generating appropriate OHS expense scheme according to its construction work progress characteristics. Both linear and sigmoidal S-curve model were used for the analysis, and the latter generally requires earlier use of OHS expense. By comparing the estimated OHS expense use schedule with current criteria, more than 27%p early use of OHS expense is required for the prevention of accident.

• Journal of Korean Society of Steel Construction
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• v.15 no.4 s.65
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• pp.341-358
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• 2003

This paper proposed a general formulation of Life-Cycle Cost (LCC) models and LCC effective design system models of steel bridges suitable for practical implementation. An LCC model for the optimum design of steel bridges included initial cost and direct/indirect rehabilitation costs of a steel bridge as well as repair/replacement costs, loss of contents or fatality and injury losses, road user costs, and indirect socioeconomic losses. The new road user cost model and regional socioeconomic losses model were especially considered because of the traffic network. Illustrative design examples of an actual steel box girder and an orthotropic steel deck bridge were discussed to demonstrate the LCC effectiveness of the design of steel bridges. Based on the results of the numerical investigation, the LCC-effective optimum design of steel bridges based on the proposed LCC model was found to lead to a more rational, economical, and safer design compared with the initial cost-optimum design and the conventional code-based design.

• International Journal of Highway Engineering
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• v.10 no.4
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• pp.117-125
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• 2008

Recently, users of bicycles as a green mode are rising sharply, but there are few efforts to increase bicycle safety and to decrease the number of accidents between vehicles and bicycle users. Therefore, this research seeks to improve bicycle safety at intersections by analysing causation factors of bicycle accidents pattern and providing optimal intersection design guidelines. For this study, real bicycle accident data of fifty six occurred in the Incheon metropolitan area in the year of 2005 were collected and field surveys were conducted. In addition, this research developed a bicycle accident pattern model with using multinomial logit model. The model results showed that presence of fatality, presence of traffic islands on the minor road, highway_type, weather, presence of traffic bus_stop on the major road, minor road lane width, victim induce factor are significant for bicycle safety.

• Journal of the Korea Institute of Military Science and Technology
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• v.24 no.3
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• pp.348-355
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• 2021

Hantaan virus(HTNV) causes hemorrhagic fever with renal syndrome(HFRS) with a case fatality rate ranging from <1 to 15 % in human. Hantavax^Ⓡ is a vaccine against the Hantavirus, which has been conditionally approved by the Ministry of Food and Drug Safety(MFDS). However, only 50 % of volunteers had neutralizing antibodies 1 year following the boost. Effective antiviral treatments against HTNV infection are limited. Hantaviruses generally cause asymptomatic infection in adult mice. On the other hand, infection of suckling and newborn mice with hantaviruses causes lethal neurological diesease or persistant infection, which is different from the disease in humans. The development of vaccines and antiviral strategies for HTNV has been partly hampered by the lack of an efficient lethal mouse model to evaluate the efficacy of the candidate vaccines or antivirals. In this report, we established a lethal mouse model for HTNV, which may facilitate in vivo studies on the evaluation of candidate drugs against HTNV. The median lethal dose value of HTNV was calculated by probit analysis of deaths occurring within two weeks. Five groups of ten ICR mice were injected intracranially with serial 2-fold dilutions (from 50 to 3.125 PFU/head) of HTNV. Mice injected with HTNV began to die at 8 days post-infection. The lethal dose required to kill 50 % of the mice (LD₅₀) was calculated to be 2.365 PFU/head.