Journal of Korea Entertainment Industry Association
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v.13
no.5
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pp.229-238
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2019
The aim of the research is to investigate relationship between drivers' self-control, driving behavior and driving stress. 180 people who have driver's licence and have experiences in driving in Gwangju and Jeonnam area participated for the research. The survey was conducted from 29th April 2015 to 24th July 2015 and data was analysed to figure out the relationship between drivers' self-control, driving behavior and driving stress. As a result, Firstly, drivers' self-control affected mistakes, violations, errors of driving behavior, and driving environment, traffic regulations, accident control, time pressure of driving stress. It showed a statistical significant difference and the higher drivers' self-control is, the lower sub construct factor of driving behavior and driving stress. Secondly, those factors of drivers' self-control, driving behavior and driving stress were correlated. The result showed the relationship between drivers' self-control, driving behavior and driving stress. It is also possible to utilize the information to prevent car accidents. Finally, it is expected to do research further by expanding the participants into multiple areas of people.
Recently, the risk of snow disasters has been increasing South Korea. The damages of heavy snow were categorized into direct and indirect. Direct damage is usually the collapse of buildings as houses, greenhouse or barns. Indirect damage is various, for example, traffic congestion, traffic acident, drop damage, and so on. In South Korea, direct damage is severe in rural area, mosty collapse of greenhouse or barns. However, indirect damage such as traffic accident is mostly occurred in urban area. Therefore, the regional characteristics should be considered when vulnerability is evaluated. Therefore, in this study, the PSR and DPSIR method were applied by regional scale in South Korea. The PSR evaluation method is divided into pressure, state, and reaction index. however, the DPSIR evaluation method is divided into Driving force, Pressure, State, Impact, and Response index. the DPSIR evaluation method is divided into Driving force, Pressure, State, Impact, and Response index. Data corresponding to each indicator were collected, and the weight was calculated using the entropy method to calculate the snowfall vulnerability index by regional scale in South Korea. Calculated heavy snow damage vulnerabilities from the two methods were compared. The calculated vulnerabilities were validated using the recent snow damage in South Korea from 2018 to 2022. Snow vulnerability index calculated using the DPSIR method showed more reliable results. The results of this study could be utilized as an information to prepare the mitigation of heavy snow damage and to establish an efficient snow removal response system.
Hydrogen energy technology is gaining importance in the era of the Fourth Industrial Revolution, offering military advantages when applied to military vehicles due to its characteristics such as reduced greenhouse gas emissions, noise, and low vibration. Korea's military has initiated the Army Tiger 4.0 plan, focusing on hydrogen application, downsizing, and AI-based smart features. The Ministry of National Defense plans to collaborate with the Ministry of Environment to expand hydrogen charging stations nationwide, anticipating increased deployment of military hydrogen vehicles. However, considering the Jet Fire and VCE(Vapor Cloud Explosion) nature of hydrogen, ensuring safety during installation is crucial. Current military guidelines specify a minimum safety distance of 2m from adjacent buildings for charging stations. Scientific methods have been employed to quantitatively assess the accident damage range of hydrogen, proposing a minimum safety distance beyond the affected area.
A high-fidelity computational fluid dynamics (CFD) analysis was performed using the Large Eddy Simulation (LES) model for the lower plenum of the High-Temperature Test Facility (HTTF), a ¼ scale test facility of the modular high temperature gas-cooled reactor (MHTGR) managed by Oregon State University. In most next-generation nuclear reactors, thermal stress due to thermal striping is one of the risks to be curiously considered. This is also true for HTGRs, especially since the exhaust helium gas temperature is high. In order to evaluate these risks and performance, organizations in the United States led by the OECD NEA are conducting a thermal hydraulic code benchmark for HTGR, and the test facility used for this benchmark is HTTF. HTTF can perform experiments in both normal and accident situations and provide high-quality experimental data. However, it is difficult to provide sufficient data for benchmarking through experiments, and there is a problem with the reliability of CFD analysis results based on Reynolds-averaged Navier-Stokes to analyze thermal hydraulic behavior without verification. To solve this problem, high-fidelity 3-D CFD analysis was performed using the LES model for HTTF. It was also verified that the LES model can properly simulate this jet mixing phenomenon via a unit cell test that provides experimental information. As a result of CFD analysis, the lower the dependency of the sub-grid scale model, the closer to the actual analysis result. In the case of unit cell test CFD analysis and HTTF CFD analysis, the volume-averaged sub-grid scale model dependency was calculated to be 13.0% and 9.16%, respectively. As a result of HTTF analysis, quantitative data of the fluid inside the HTTF lower plenum was provided in this paper. As a result of qualitative analysis, the temperature was highest at the center of the lower plenum, while the temperature fluctuation was highest near the edge of the lower plenum wall. The power spectral density of temperature was analyzed via fast Fourier transform (FFT) for specific points on the center and side of the lower plenum. FFT results did not reveal specific frequency-dominant temperature fluctuations in the center part. It was confirmed that the temperature power spectral density (PSD) at the top increased from the center to the wake. The vortex was visualized using the well-known scalar Q-criterion, and as a result, the closer to the outlet duct, the greater the influence of the mainstream, so that the inflow jet vortex was dissipated and mixed at the top of the lower plenum. Additionally, FFT analysis was performed on the support structure near the corner of the lower plenum with large temperature fluctuations, and as a result, it was confirmed that the temperature fluctuation of the flow did not have a significant effect near the corner wall. In addition, the vortices generated from the lower plenum to the outlet duct were identified in this paper. It is considered that the quantitative and qualitative results presented in this paper will serve as reference data for the benchmark.
This study aimed to provide a solution for improving ship collision alert of the 'accident vulnerable ship monitoring service' among the 'intelligent marine traffic information system' services of the Ministry of Oceans and Fisheries. The current ship collision alert uses a supervised learning (SL) model with survey labels based on large ship-oriented data and its operators. Consequently, the small ship data and the operator's opinion are not reflected in the current collision-supervised learning model, and the effect is insufficient because the alarm is provided from a longer distance than the small ship operator feels. In addition, the supervised learning (SL) method requires a large number of labeled data, and the labeling process requires a lot of resources and time. To overcome these limitations, in this paper, the classification model of collision alerts for small ships using unlabeled data with the semi-supervised learning (SSL) algorithms (Label Propagation and TabNet) was studied. Results of real-time experiments on small ship operators using the classification model of collision alerts showed that the satisfaction of operators increased.
Journal of the Korea Institute of Construction Safety
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v.6
no.1
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pp.19-26
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2024
In this study, we analyzed the status of safety management in industrial sites and fatal accident statistics to identify problems and suggest directions for increasing the utilization of convergence engineering. Current industrial site safety management is passive, formal, and unsystematic, and at the same time, the delivery of information on site safety management is very insufficient. In addition, domestic occupational safety and health education was not systematic and could not be considered effective as it was repeating past education forms. Recently, ICT technology has been introduced throughout the industry, and this study suggests several directions for the introduction of convergence safety engineering. Keke is the organization and operation of school curriculum in a convergent manner. In addition, we proposed a plan to apply VR content and experiential education so that safety management education can be conducted in a practical and realistic manner. Lastly, it was proposed to provide differentiated education by industry and type of work, taking into account the characteristics of various industrial sites. It is expected that the results of this study will be able to emphasize the need for convergence and integrated safety education for those involved in the field of domestic industrial safety management and education.
Journal of The Korean Society of Clinical Toxicology
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v.21
no.2
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pp.92-107
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2023
Purpose: This study investigated the characteristics and treatment outcomes of patients who visited the emergency department due to intoxication and analyzed the impact of the coronavirus disease 2019 (COVID-19) pandemic on their visits. Methods: A retrospective study was conducted using data from the National Emergency Department Information System (NEDIS) on patients who visited the emergency department due to intoxication between January 2014 and December 2020. In total, 277,791 patients were included in the study, and their demographic and clinical data were analyzed. A model was created from 2014 to 2019 and applied to 2020 (i.e., during the COVID-19 pandemic) to conduct a time series analysis distinguishing between unexpected accidents and suicide/self-harm among patients who visited the emergency department. Results: The most common reason for visiting the emergency department was unintentional accidents (48.5%), followed by self-harm/suicide attempts (43.8%). Unexpected accident patients and self-harm/suicide patients showed statistically significant differences in terms of sex, age group, hospitalization rate, and mortality rate. The time series analysis showed a decrease in patients with unexpected accidents during the COVID-19 pandemic, but no change in patients with suicide/self-harm. Conclusion: Depending on the intentionality of the intoxication, significant differences were found in the age group, the substance of intoxication, and the mortality rate. Therefore, future analyses of patients with intoxication should be stratified according to intentionality. In addition, the time series analysis of intentional self-harm/suicide did not show a decrease in 2010 in the number of patients, whereas a decrease was found for unintentional accidents.
The market share of online platform services in the used car market continues to expand. And The used car online platform service provides service users with specifications of vehicles, accident history, inspection details, detailed options, and prices of used cars. SUV vehicle type's share in the domestic automobile market will be more than 50% in 2023, Sales of Hybrid vehicle type are doubled compared to last year. And these vehicle types are also gaining popularity in the used car market. Prior research has proposed a used car price prediction model by executing a Machine Learning model for all vehicles or vehicles by brand. On the other hand, the popularity of SUV and Hybrid vehicles in the domestic market continues to rise, but It was difficult to find a study that proposed a used car price prediction model for these vehicle type. This study selects a used car price prediction model by vehicle type using vehicle specifications and options for Sedans, SUV, and Hybrid vehicles produced by domestic brands. Accordingly, after selecting feature through the Lasso regression model, which is a feature selection, the ensemble model was sequentially executed with the same sampling, and the best model by vehicle type was selected. As a result, the best model for all models was selected as the CBR model, and the contribution and direction of the features were confirmed by visualizing Tree SHAP Value for the best model for each model. The implications of this study are expected to propose a used car price prediction model by vehicle type to sales officials using online platform services, confirm the attribution and direction of features, and help solve problems caused by asymmetry fo information between them.
Journal of Korean Tunnelling and Underground Space Association
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v.26
no.2
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pp.91-111
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2024
Most of utility cable tunnels are constructed utilizing shield TBM as part of the underground transmission line project. The TBM chamber is the only space inside the tunnel that encounters rock and soil, and is the place with the highest frequency of accident exposure, such as collapse and collision accidents. Since there is currently no way to measure the disc cutter wear from outside the chamber, frequent inspection by workers is essential. Accordingly, in this study, in order to prevent safety accidents inside the TBM chamber and expect the effect of shortening the construction period by reducing the number of chamber openings, the concept of disk cutter wear measurement technology was established and a prototype was produced. By considering prior technology and determining that magnetic sensors are most suitable for the excavation environment, wear measurement sensor package were developed integrating magnetic sensors, wireless communication modules, power supply, external casing, and monitoring systems. To verify the performance of the prototype in an actual excavation environment, a full-scale tunnelling test was performed using a 3.6 m EPB shield TBM. Based on the full-scale tests, five prototypes were operated normally among eight prototypes. It was analyzed that sensor measurement, wireless communication, and durability performance were secured within a maximum thrust of 3,000 kN and a rotation speed of 1.5 RPM.
Variable Message Sign (VMS), which provides drivers with direct information about state of traffic congestion and for prevent an accident, is the most effective method among the methods of providing information in Advanced Transportation Management System. Currently establishment and the VMS which is operated foundation lets in Guidelines on the use of Variable message sign (a book of the VMS) of 1999 November the Ministry Construction & Transportation, these contents mean main viewpoint on physical part such as message special quality variable (font, character size and line space, word interval) and position mainly among standard about establishment in general. But, it is true that using without effect verification on the character of VMS display and that using mode of stationary-centered. In this paper, it executed significance test to effort verification on the character of VMS display for more practical and effective information transmission based on the driver viewpoint For the researches; develop 3D-Simulation, select characteristics of driver's visual cognition behavior (the conspicuity, the legibility and the comprehensibility), evaluation each issue (day or night, 80km/h or 100km/h). Especially, that used the Eye Marker Recorder to measure of reading-time (legibility) thus, confirmed objectivity and reduce an observational error. The results showed that the conspicuity is Flashing> Stationary>Scroll. The legibility is not deference that Flashing between stationary form. Also the comprehensibility result showed that Flashing> Stationary>Stroll form.
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