• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.30 no.4
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• pp.364-375
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• 2020

Objectives: The purpose of this study is to suggest a direction for consumer-oriented curriculum development by analyzing the priorities of subjects and their preference for educational methods. Methods: The participants included 773 management supervisors and education practitioners in the workplace, and a survey was conducted from April 17 to August 30, 2019. Frequency analysis, t-test, Borich's Needs Analysis, and Locus for Focus Model analysis were performed using Microsoft Excel 2019 and IBM SPSS 21.0. Results: The highest perceived priorities for education subjects were as follows: ① 'CPR and First Aid Practice' and 'Occupational Disaster Prevention and First Aid Basics' in the manufacturing industry; and ② 'Emotional Labor and Job Stress Prevention', 'Occupational Disaster Prevention and First Aid basics, and 'Musculoskeletal Disorder Prevention' in the service industry. 'Collective education' was the most preferred method of education. 'School-type' was preferred for the seating arrangement, and the proper number of trainees was considered to be about 30. Respondents said the contents of the education was a top priority when they applied for education, and curriculum and appropriate textbooks should be considered in calculating the cost of education. Conclusions: Practical subjects and subjects related to major hazards by industry were required for management supervisor education. It was proposed in this study that the contents and operating methods of education be changed so that workers can easily comprehend essential subjects such as the Occupational Safety and Health Act. In conclusion, it is necessary to design the curriculum and apply educational methods suitable for each subject's characteristics in consideration of the priorities for subjects reflected in the needs of trainees.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.18-25
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• 2021

In many developed countries, such as South Korea, efficiently maintaining the aging infrastructures is an important issue. Currently, inspectors visually inspect the infrastructure for maintenance needs, but this method is inefficient due to its high costs, long logistic times, and hazards to the inspectors. Thus, in this paper, a novel crack inspection approach for concrete bridges is proposed using integrated image processing techniques. The proposed approach consists of four steps: (1) training a deep learning model to automatically detect cracks on concrete bridges, (2) acquiring in-situ images using a drone, (3) generating orthomosaic images based on 3D modeling, and (4) detecting cracks on the orthmosaic image using the trained deep learning model. Cascade Mask R-CNN, a state-of-the-art instance segmentation deep learning model, was trained with 3235 crack images that included 2415 hard negative images. We selected the Tancheon overpass, located in Seoul, South Korea, as a testbed for the proposed approach, and we captured images of pier 34-37 and slab 34-36 using a commercial drone. Agisoft Metashape was utilized as a 3D model generation program to generate an orthomosaic of the captured images. We applied the proposed approach to four orthomosaic images that displayed the front, back, left, and right sides of pier 37. Using pixel-level precision referencing visual inspection of the captured images, we evaluated the trained Cascade Mask R-CNN's crack detection performance. At the coping of the front side of pier 37, the model obtained its best precision: 94.34%. It achieved an average precision of 72.93% for the orthomosaics of the four sides of the pier. The test results show that this proposed approach for crack detection can be a suitable alternative to the conventional visual inspection method.

• Journal of the Korean Society of Safety
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• v.36 no.4
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• pp.71-79
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• 2021

In this study, a real-scale fuel-cell room of volume 1.36 m³ is constructed to confirm the explosion characteristics of hydrogen-air mixture gas in a hydrogen-powered house. A volume concentration of 40% is applied in the fuel-cell room as the worst-case scenario to examine the most severe accident possible, and two types of doors (made of plastic sheet and wood) are fabricated to observe their effects on the overpressure and impulse. The peak overpressure and impulse based on distance from the ignition source are experimentally observed and assessed. The maximum and minimum overpressures with a plastic-sheet door are about 20 and 6.7 kPa and those with a wooden door are about 46 and 13 kPa at distances of 1 and 5 m from the ignition source, respectively. The ranges of impulses for distances of 1-5 m from the ignition source are about 82-28 Pa·s with a plastic-sheet door and 101-28 Pa·s with a wooden door. The amount of damage to people, buildings, and property due to the peak overpressure and impulse is presented to determine the safe distance; accordingly, the safe distance to prevent harm to humans is about 5 m based on the 'injuries' class, but the structural damage was not serious.

• Architectural research
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• v.24 no.2
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• pp.21-27
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• 2022

For the past decade, South Korea had experienced catastrophic building fires, which resulted in consider-ably high number of casualties. This motivated research to develop fire-safe wall assemblies. In this study Fire Risk Analysis (FRA) is conducted as part of the project designing phase to ensure fire safety of the final product. Traditional approach was to consider fire performance at the end of the designing stage, when PASS/FAIL fire test results are required to be submitted to the Authority Having Jurisdiction (AHJ). By applying a fire risk analysis to guide the designing phase, overall fire safety of a wall assembly can be achieved more systematically as conducting FRA allows designers to clearly identify elements that are more vulnerable to fire and simply replace them with other practical options. Severity of fire risk is determined by considering the fire hazards of a wall assembly such as the exterior layer, insulation, vertical connectivity, and external ignition sources (e.g., photovoltaic panels). Frequency of fire risk is assessed based on the factors affecting fire likelihood, which are air cavity and fire-stopping applied in the design, and random design changes occurring during on-site construction. Fire risk matrix is proposed based on these fire risk factors and efforts to reduce the fire risk level associated with the wall assembly are given by systematically assessing the fire risk factors identified from fire risk analysis. Current study demonstrates how fire risk analysis can be applied to develop fire-safe walls by reducing the relevant fire risks- both severity and frequency.

• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.665-675
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• 2022

The safety problems of giant hydraulic structures such as dams caused by terrorist attacks, earthquakes, and wars often have an important impact on a country's economy and people's livelihood. For the national defense department, timely and effective assessment of damage to or impending damage to dams and other structures is an important issue related to the safety of people's lives and property. In the field of damage assessment and vulnerability analysis, it is usually necessary to give the damage assessment results within a few minutes to determine the physical damage (crack length, crater size, etc.) and functional damage (decreased power generation capacity, dam stability descent, etc.), so that other defense and security departments can take corresponding measures to control potential other hazards. Although traditional numerical calculation methods can accurately calculate the crack length and crater size under certain combat conditions, it usually takes a long time and is not suitable for rapid damage assessment. In order to solve similar problems, this article combines simulation calculation methods with machine learning technology interdisciplinary. First, the common concrete gravity dam shape was selected as the simulation calculation object, and XFEM (Extended Finite Element Method) was used to simulate and calculate 19 cracks with different initial positions. Then, an LSTM (Long-Short Term Memory) machine learning model was established. 15 crack paths were selected as the training set and others were set for test. At last, the LSTM model was trained by the training set, and the prediction results on the crack path were compared with the test set. The results show that this method can be used to predict the crack propagation path rapidly and accurately. In general, this article explores the application of machine learning related technologies in the field of mechanics. It has broad application prospects in the fields of damage assessment and vulnerability analysis.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.319-326
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• 2024

Construction projects account for a significant proportion of workplace hazards globally. While construction cost reports typically emphasize direct accident costs such as treatment expenses, nursing care costs, or disability benefits, indirect factors like work interruption loss costs or consolation costs are frequently overlooked, because it is relatively difficult to estimate those factors in advance. Recognizing and accurately estimating the indirect costs factors associated with construction accidents would not only shed light on the monetary impact these incidents have on overall project costs but also would enable to estimate the total accident cost in advance. The current study seeks to identify factors influencing indirect costs, which ultimately govern the total accident cost, through a data mining approach. A survey was conducted in domestic construction companies, resulting in a dataset of 1038 accident records collected from construction sites. First, statistical analysis was performed to uncover characteristics and patterns of factors affecting construction accident costs from both direct and indirect perspectives. Later, this study proposes four distinct machine learning (ML) models, comparing their performances in predicting the total accident cost (including indirect costs) in advance. Additionally, this research sheds light on an important issue in construction data analysis, which is the scarcity of data in a particular class, by applying random oversampling and random undersampling techniques. The suggested framework can assist practitioners and management in estimating construction accident costs and identifying the relevant attributes that impact accidents at the construction site for future practices.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.34 no.3
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• pp.262-278
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• 2024

Objectives: To investigate the work environment measurement (WEM) status and concentration levels of substances with short-term exposure limits (STEL) among special management substances. Methods: Data from the past 5 years of WEM for 6 substances (1,2-dichloropropane (1,2-DCP), 1,3-butadiene, benzene, trichloroethylene (TCE), perchloroethylene (PCE) and sulfuric acid) were analyzed. The number of samples and concentration level of STEL and 8-hour TWA (time weighted average) were compared. Results: The number of STEL measurement for 1,3-butadiene, benzene, and sulfuric acid was less than 1% of the number of TWA measurement samples, while TCE, 1,2-DCP, and PCE, which are mainly used for cleaning metals, were relatively high, at 16.1%, 5.6%, and 2.2%, respectively. When comparing the concentrations of STEL with TWA on the same STEL measured workers (STEL-matched TWA), STEL concentrations were 2.8, 3.1, 2.6, 2.6 and 40.5 times higher than TWA as 1,2-DCP, benzene, TCE, PCE, and sulfuric acid. When comparing the concentration of STEL-matched TWA with the total TWA, STEL-matched TWA was 3.4, 8, 1.4, 2.0, 8.6 and 0.7 times higher for 1,2-DCP, benzene, 1,3-butadiene, TCE, PCE, and sulfuric acid, respectively. Conclusions: This study found that the workers performing irregular tasks may be exposed to higher concentrations of hazardous substances than regular workers. It is necessary to strengthen short-term exposure measurement, even for substances which STEL have not been set.

• Journal of Food Hygiene and Safety
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• v.28 no.4
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• pp.324-329
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• 2013

This study investigated and evaluated contamination levels of bacteria on tomatoes at farms stage to evaluate potential hazards associated with fresh tomatoes. A total of 170 samples, 90 samples from 5 sampling sites from 18 farms and 80 samples from 1 sampling site from 4 farms every month for four months, were analyzed to enumerate aerobic bacterial counts, coliforms, E. coli, Bacillus cereus, Staphylococcus aureus, Escherichia coli, E. coli O157:H7, Salmonella spp., and Listeria monocytogenes. Aerobic bacterial counts ranged from 0.48 to 6.15 Log CFU/g, with the lowest and the highest bacterial cell counts recorded for A site and E site, respectively. Thirty five percent of the samples from the E site contained more than 2 Log CFU/g. Six samples (6.6%) of 90 samples contained B. cereus less than 1 Log CFU/g. In addition, the contamination level of indicator bacteria and B. cereus in tomatoes were higher on March than on April, May and June (P < 0.05). S. aureus, E. coli, E. coli O157:H7, Salmonella spp. and L. monocytogenes were not detected in the tomato samples. The microbial contamination levels of tomatoes determined in this study may be used as the data for microbiological risk assessment.

• Journal of Food Hygiene and Safety
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• v.14 no.4
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• pp.397-407
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• 1999

A survey was conducted to investigate the attitudes of the food specialist to the food developed by gene recombination. The mail survey was distributed to 1,400 food specialists and received 464, a response rate of 33.1%. Respondents were asked about knowledge, concerns of potential hazards, purchasing and labeling of the gene recombination foods. Most respondents (98.7%) have some knowledge on the gene recombination foods. 91.3% of respondents recognized necessity of gene recombination technology. However, they also point out its potential hazards (80.9%). The groups with less knowledge showed their increased worry on the hazard in comparison with ones of having more knowledge(p<0.01). The result indicated that there was negative relationship between knowledge and worry on the gene recombination foods. The groups with more knowledge showed their increased purchasing on gene recombination foods in comparison with ones of having less knowledge(p<0.01). The result indicated that there was positive relation-ship between their purchase intent for gene recombination foods and knowledge. 68.4% of respondents showed their interest on purchasing the gene recombination foods. In this group, most of them (44.9%) has on condition that low cost (27.0%). In addition, they also have not use the foods for their children (17.9%) if they buy it. Most respondents (85.3%) want labeling on the gene recombination foods.

• The Korean Journal of Air & Space Law and Policy
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• v.33 no.2
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• pp.345-366
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• 2018

Article 37 of the International Convention on Civil Aviation requires that rules should be adopted to keep in compliance with international standards and recommended practices established by ICAO. As SARPs are revised annually, each ICAO Member State needs to reflect the new content in its national aviation Acts in a timely manner. In recent years, data-driven international standards have been developed because of the important roles of aviation safety data and information-based legislation in accident prevention based on human factors. The Safety Management System and crew Fatigue Risk Management Systems were reviewed as examples of the result of data-driven rulemaking. The safety management system was adopted in 2013 with the introduction of Annex 19 and Chapter 5 of the relevant manual describes safety data collection and analysis systems. Through analysis of safety data and information, decision makers can make informed data-driven decisions. The Republic of Korea introduced Safety Management System in accordance with Article 58 of the Aviation Safety Act for all airlines, maintenance companies, and airport corporations. To support the SMS, both mandatory reporting and voluntary safety reporting systems need to be in place. Up until now, the standard of administrative penal dispensation for violations of the safety management system has been very weak. Various regulations have been developed and implemented in the United States and Europe for the proper legislation of the safety management system. In the wake of the crash of the Colgan aircraft, the US Aviation Safety Committee recommended the US Federal Aviation Administration to establish a system that can identify and manage pilot fatigue hazards. In 2010, a notice of proposed rulemaking was issued by the Federal Aviation Administration and in 2011, the final rule was passed. The legislation was applied to help differentiate risk based on flight according to factors such as the pilot's duty starting time, the availability of the auxiliary crew, and the class of the rest facility. Numerous amounts data and information were analyzed during the rulemaking process, and reflected in the resultant regulations. A cost-benefit analysis, based on the data of the previous 10 year period, was conducted before the final legislation was reached and it was concluded that the cost benefits are positive. The Republic of Korea also currently has a clause on aviation safety legislation related to crew fatigue risk, where an airline can choose either to conform to the traditional flight time limitation standard or fatigue risk management system. In the United States, specifically for the purpose of data-driven rulemaking, the Airline Rulemaking Committee was formed, and operates in this capacity. Considering the advantageous results of the ARC in the US, and the D4S in Europe, this is a system that should definitely be introduced in Korea as well. A cost-benefit analysis is necessary, and can serve to strengthen the resulting legislation. In order to improve the effectiveness of data-based legislation, it is necessary to have reinforcement of experts and through them prepare a more detailed checklist of relevant variables.