• Proceedings of the Safety Management and Science Conference
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• 2004.05a
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• pp.33-39
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• 2004

The chemical factory deals with dangerous element and more advance, human-error analyzes and becomes effective research for the country and region, this paper analyes the form of work-miss on human-error according to a safety accident for domestic chemical factory from 1999-2002. It include the present contents and raise issues human knowledge, behavior, judgment, sensibility as an important counterplan that makes the safety solution of work miss. For the point of view of human knowledge, it takes color standard for works to be effective in work place. for behavior, the test has been for risk point of work place and infra worker movement, also the workers performed professional work as classify according to work. for judgement, the valuation sheet is reflected to minimize the human -error and the 3rd supervisor does a cross-check audit beforehand. For sensibility, it is applicable for human relations, information, communication by program to the consciousness and an attitude of worker-supervisor.

• Journal of the Korea Safety Management & Science
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• v.24 no.2
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• pp.11-16
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• 2022

When picking up cargo, workers manually load and unload the cargo. Workers have different intensity of work depending on the amount and weight of cargo. In particular, as the intensity of manual work increases, workers are exposed to cumulative traumatic diseases. A manual for picking safety work for workers cargo handling in the distribution center is required. In this study, the worker's picking safety work based on the cargo volume and weight was presented as an experimental design model. Like the research results, the disease begins when the worker feels the number of pains presented by the model.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.23 no.1
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• pp.27-34
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• 2013

Objectives: The purpose of this study is to calculate the worker-DNEL (Derived No Effect Level) values using the REACH guidance and compare the calculated DNELs with existing Korea occupational exposure limits (KOELs) for evaluation of the applicability of the worker-DNELs as provisional occupational exposure limits for chemicals that are not established KOELs in the workplace. Methods: The worker-DNELs for 46 chemicals among 113 hazardous substance requiring management were calculated using the REACH guidance, and a paired t-test was performed to see if there is any statistical difference between two lists (worker-DNELs vs KOELs). The ratios of KOELs over worker-DNELs were also calculated to compare the overall levels of two lists using the geometric means method. Results: The calculated worker-DNELs for 46 chemicals ranged from 0.001 to $329mg/m^3$ (GM= 6.9, GSD = 10.8), and appeared to be a significant difference between the worker-DNELs and the KOELs (p < 0.01). In addition, the ratios of KOELs over worker-DNELs ranged from 0.3 to 394 times (GM = 10.2, GSD = 3.9), indicating that the worker-DNELs were, on average, 27 times lower than the KOELs. Conclusions: Therefore, the study results show that the calculated worker-DNELs can be applied and used as provisional occupational exposure limits in the workplace in order to reduce worker exposures to chemicals and health risks, and manage potential worker exposures based on the precautionary principle through comprehensive chemical risk assessment.

• Safety and Health at Work
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• v.15 no.3
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• pp.373-378
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• 2024

Introduction: Following the Republic of Korea electric power industry site-specific safety management system, this paper proposes a novel safety autonomous platform (SAP) architecture that can automatically and precisely manage on-site safety through ensemble artificial intelligence (AI) models. The ensemble AI model was generated from video information and worker's biometric information as learning data and the estimation results of this model are based on standard operating procedures of the workplace and safety rules. Methods: The ensemble AI model is designed and implemented by the Hadoop ecosystem with Kafka/NiFi, Spark/Hive, HUE, and ELK (Elasticsearch, Logstash, Kibana). Results: The functional evaluation shows that the main function of this SAP architecture was operated successfully. Discussion: The proposed model is confirmed to work well with safety mobility gateways to provide some safety applications.

• Fire Science and Engineering
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• v.33 no.1
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• pp.147-155
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• 2019

This study was a quasi-experimental research of a non-equivalent control group and non-synchronized design for analyzing the effects of fire safety education on care worker trainees. The subjects of the study were care worker trainees of the S Care Worker Institution: 57 trainees with 28 in the experimental group, and 29 in the control group. The research period was from May 21 to June 14, 2018 and the experiments focusing on fire safety education were performed once per week for a total of four times over the research period. The data were then analyzed using a ${\chi}^2-test$ and t-test. The results showed that fire safety education is an effective source of education for increasing the knowledge on fire safety, attitudes towards fire safety, perceived behavioral control on fire safety, behavioral intention on fire safety, and fire safety behavior in addition to being incredibly useful in practicing fire safety behaviors throughout their daily lives. On the other hand, the subjective norms on fire safety did not show any significant differences. Therefore, this paper suggests a follow-up study that should focus on analyzing the effects of the subjective norms on fire safety.

• Proceedings of the Safety Management and Science Conference
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• 2002.11a
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• pp.9-15
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• 2002

There are many and various problems due to an occupational disease. These problems result in serious social problems such as individual and family problem, economical loses of company. The objective of this study is to analyze the worker's consciousness and provide the precautionary measures for prevention of an occupational disease. The samples for this study are chosen from the companies with less than 300 employees under charge of the Kangnung Ministry of Labor during three months (2002. 3. 2 ∼ 2002. 5. 31).

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.987-991
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• 2005

The Aerial platform Truck is widely used for work in high place with the aerial platform. The most important thing is that worker's safety and worker must be able to work with trustworthiness so it needs to be verified its stiffness, deflection of boom, and dynamic condition concerned with a rollover accident. It should have an analytical exactitude because it is directly linked with the worker safety. In this point, we are trying to develop a proper CAE analysis model concerned with a rollover safety, bending stress and deflection for load. The Aerial platform Truck have a dynamic characteristics by load and moving of boom in the work field, so its static and dynamic strength analysis, structural mechanics are very important. Therefore, we evaluate the safety of each boom to calculating its stress, deflection. A computer simulation program is used widely for doing applying calculation of stiffness and structural mechanics, then finally trying to find a optimum design of the Aerial platform Truck.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.3
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• pp.317-331
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• 2023

Objectives: Construction workers are exposed to various hazardous substances simultaneously. However, little is known about the exposure hazards in construction industry. This study was aimed at identifying the risk of exposure hazards among construction workers. Methods: The expert survey (n=29) was conducted, including construction industry health managers (n=11) and work environment monitoring experts (n=18), on exposure probability, intensity and risk of hazardous substances by construction occupations Results: The exposure hazards of 30 construction occupations were identified and summarized through a literature review and expert survey. The most prevalent hazards were in order of noise, awkward posture, heat/cold, crystalline silica, cement/concrete dust, metal fumes, and volatile organic compounds. The hazards with highest risk score(over seven points) at construction occupations were noise(formwork carpenter, concrete finisher, rebar worker, demolition worker, driller/rock blaster), hazardous rays(welder), heat/cold (earthworks, formwork carpenter, rebar worker, concrete placer, scaffolder), awkward posture(bricklayer, caulker/tile setter, rebar worker) and heavy lifting(bricklayer, rebar worker). Among construction workers, the job types with the highest risk of exposure to carcinogens, and in which occupational cancer has been reported, were in order of stonemason, concrete finisher, rock blaster, welder, insulation installer, painter, scaffolder, plant worker and earthworks in order Conclusions: Systematic research and discussion on occupational disease among construction workers and its various hazardous factors are needed to establish job exposure matrix for facilitating standard for promptly processing the workers' compensation.

• Proceedings of the Safety Management and Science Conference
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• 2011.04a
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• pp.29-38
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• 2011

• Journal of the Korean Society of Safety
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• v.34 no.6
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• pp.29-37
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• 2019

Since construction sites are exposed to outdoor environments, working conditions are significantly dangerous. Thus, wearing of the personal protective equipments such as safety helmet is very important for worker safety. However, construction workers are often wearing-off the helmet as inconvenient and uncomportable. As a result, a small mistake may lead to serious accident. For this, checking of wearing safety helmet is important task to safety managers in field. However, due to the limited time and manpower, the checking can not be executed for every individual worker spread over a large construction site. Therefore, if an automatic checking system is provided, field safety management should be performed more effectively and efficiently. In this study, applicability of deep learning based computer vision technology is investigated for automatic checking of wearing safety helmet in construction sites. Faster R-CNN deep learning algorithm for object detection and classification is employed to develop the automatic checking model. Digital camera images captured in real construction site are used to validate the proposed model. Based on the results, it is concluded that the proposed model may effectively be used for automatic checking of wearing safety helmet in construction site.