This study evaluates the occupational accident risks of anchovy boat seine fishery in Korea. Using Bayesian network modeling within the framework of the Formal Safety Assessment (FSA) proposed by the International Maritime Organization (IMO), data from 508 accident compensation claims between 2018 and 2022 were analyzed. Accidents were categorized into processes (sailing, fishing, maintenance, loading/unloading, and catch processing) and risk factors (hull and working environment, fishing gear and equipment, machinery and equipment, weather and external conditions, and processing equipment). The analysis revealed significant risks associated with fishing processes and hull-related factors. Fishing accounted for 36.42% of all accidents with trips/slips being the most frequent type (29.13%). Bayesian network analysis showed that trips/slips accidents during fishing posed the highest risks (0.001100). The risk of fishing operations was 4.60 times higher than sailing and 30.00 times higher than loading/unloading. The findings indicate that risks vary significantly depending on the processes and risk factors involved. As risk assessments mandated by the 2025 revision of Korean fishing safety laws are expected to remain simple and qualitative, this study underscores the necessity of incorporating quantitative approaches to enhance the reliability and effectiveness of safety management practices.

이 논문에서는 근로자의 정신질병과 자해행위로 인해 사망(자살)한 근로자에 대한 재해보상제도의 분석을 통해서 선원법상의 재해보상제도의 개선 방안제시를 목적으로 하고 있다. 특히, 산업재해보상보험법과 선원법의 정신질병과 자해행위로 인해 사망한 근로자 (선원)의 재해보상제도를 비교하고 이와 관련된 판례분석을 통해서 선원법의 개선 방안을 제시하고 있다. 선원법은 선원노동위원회가 직 무외 재해 중 고의성이 인정되었을 경우 요양보상 및 유족보상 등에 대한 선박소유자의 재해보상을 면책하도록 규정하고 있다. 반면에 산업재해보상보험법의 정신질병을 비롯해서 직장 내 괴롭힘으로 인한 스트레스로 발병한 질병에 대해서는 업무상 재해로 인정하고 있다. 또한 고의적인 자해행위로 비롯된 사망이 발생하였다 할지라도 업무와의 상당인과관계가 존재하는 경우 업무상 재해로 인정함으로써 선 원법보다도 유연한 인정 기준을 가지고 근로자의 정신질병과 자해행위에 대한 보상이 이루어지고 있다. 선원법의 특수한 입법목적을 고 려했을 때 육상의 근로자와 동등한 수준으로 선원의 재해보상이 이루어질 수 있도록 입법적 조치가 이루어질 필요성이 있다. 이와 함께 재해의 고의성 여부를 판단하는 선원노동위원회의 전문성을 확보하기 위한 조직 운영 개선이 필요할 것으로 판단된다.

This study quantitatively analyzes risks of industrial incidents to fisher on overseas tuna purse seiners and long liners. A Bayesian network is employed to analyze 478 cases of industrial incidents, comprising 401 cases from purse seiners and 77 cases from long liners, reported from 2019 to 2022. The highest risk of industrial incidents on purse seiners is attributed to diseases. Excluding diseases, risks are the highest during fishing: 5.31 times higher during catch handling, 2.05 times higher during maintenance, and 2.38 times higher during loading and unloading. The risk of industrial incidents caused by the hull is 9.50 times higher than those caused by fishing gear, 4.59 times higher than those caused by machinery, and 3.61 times higher than those caused by the caught fish. Among the types of industrial incidents, slips are the highest: 2.58 times higher than industrial incidents caused by being bump, 3.74 times higher than those caused by hit, and 3.94 times higher than those caused by imbalance and overexertion. For long liners, most industrial incidents are concentrated in diseases, with dental, musculoskeletal, skin, and respiratory diseases being the primary types of industrial incidents identified. This study aims to propose reduction measures for reducing the high-risk form of industrial incidents, specifically slips, and to present health management strategies for preventing diseases among fisher on overseas tuna fishing vessels. By addressing these aspects, this study seeks to contribute to the safety and sustainability of the overseas tuna fishing industry.

This study aims to predict return-to-work outcomes for workers injured in industrial accidents using a TabNet-RUSBoost hybrid model. The study analyzed data from 1,383 workers who had completed recuperation. Key predictors identified include length of recuperation, disability grade, occupation activity, self-efficacy, and socioeconomic status. The model effectively addresses class imbalance and demonstrates superior predictive performance. These findings underscore the importance of a holistic approach, incorporating both medical and psychosocial factors.

우리나라 제조 소기업은 온실가스 고배출 업종이 많고, 산재사망사고 발생 비중이 높아 수출의존도가 높은 국내 제조 소기업에 대한 ESG 이슈 관리가 점차 중요해 질 것이다. 본 연구는 제조 소기업의 저탄소 활동이 현장 작업자의 안전의식과 산업재해에 미치는 영향을 파악하고, 저탄소 활동이 안전, 고용 등의 영역에서 발생하는 부정적 영향을 감소 시켜 기업의 경쟁력을 향상시킬 수 있는 방안을 모색해 보았다. 연구에서는 제조 소기업의 저탄소 활동(저탄소 전략 및 시스템 활동, 온실가스 및 환경오염 분야 활동, 자원 및 에너 지 분야 활동)이 산업안전 인식 향상에 긍정적(+)인 영향을 미치는 것을 확인하고, 저탄소 활동에 참여한 기업들의 산업재해율이 감소하였으며, 매출과 고용이 증가하는 성과가 나 타난 것을 확인하였다. 따라서 정부는 제조 소기업의 저탄소 활동과 산업안전, 고용창출이 연계될 수 있도록 정책적인 지원을 통해 지속가능한 성장을 위한 핵심 경영 전략으로 자리 잡게 해야 한다.

This study employs Bayesian network analysis to quantitatively evaluate the risk of incidents in trap boats, utilizing accident compensation approval data spanning from 2018 to 2022. With a dataset comprising 1,635 incidents, the analysis reveals a mortality risk of approximately 0.011 across the entire trap boat. The study significantly identifies variations in incident risks contingent upon fishing area and fishing processes. Specifically, incidents are approximately 1.22 times more likely to occur in coastal compared to offshore, and the risk during fishing processes outweighs that during maintenance operations by a factor of approximately 23.20. Furthermore, a detailed examination of incident types reveals varying incidence rates. Trip/slip incidents, for instance, are approximately 1.36 times more prevalent than bump/hit incidents, 1.58 times more than stuck incidents, and a substantial 5.17 times more than fall incidents. The study concludes by providing inferred mortality risks for 16 distinct scenarios, incorporating fishing areas, processes, and incident types. This foundational data offers a tailored approach to risk mitigation, enabling proactive measures suited to specific circumstances and occurrence types in the trap boat industry.

The objective of this study was to conduct research and analysis using Group Focus Interview to survey the between construction site workers and managers implementing for the Severe Accident Punishment Act. Focused on measures to improve safety management effectiveness for the effectiveness of establishing a safety management system. A plan to improve the efficient safety management system was presented to 50 construction industrial managers and workers. In order to ensure the industrial accident prevention policies appropriately, it is necessary to be aware of safety obligations for workers as well as business operators. In addition, despite the existence of a commentary on the Serious Accident Punishment Act, confusion in the field still persists, so in the event of a major accidents, the obligation to take safety and health education is strengthened, and effective case education is proposed by teaching actual accident cases suitable for actual working sites. It is necessary to make all training mandatory, and it is necessary to reconsider awareness through writing a daily safety log, awareness of risk factors, etc., and writing down risk information. Above all, at the construction ordering stage, it is necessary to keep the construction safety, request corrections and supplements for problems issues that arise, and consult between the orderer and the construction company about the problems issues. Rather than having only the construction company correct or supplement the safety management plan, the contents should be shared with supervisors and workers to establish a more practical solution. Results of this study will contribute to improving the effectiveness of the serious accident and construction safety management system.

기후변화는 연안지역에 심각한 영향을 미치고 있으며 그 영향이 점점 증가할 것이라고 예상되는 바, 최근 기후변화 적응 및 리스크 평가에 있어 많은 연구들이 취약성과 함께 회복탄력성 개념을 이용하고 있다. 본 연구의 목적은 기후변화 적응을 위한 연안재해 회복탄력성 측정 모형을 개발하는 것이다. 측정 모형 개발에 앞서 연안재해 회복탄력성에 대한 광범위한 문헌검토를 통해 취약성과 회복 탄력성에 대한 조작적 정의와 함께 여러 피드백 메커니즘이 포함된 개념적 프레임워크를 작성하였다. 연안재해 회복탄력성 측정 모형은 네 가지 측정값(MRV, LRV, RTSPV, ND)과 연안재해 회복탄력성 복합 지수(CRI)를 포함하고 있으며, 개발된 지수는 국내 연안침식 사례에 적용되었다. 또한 지수 등급에 따른 지역적 분석이 수행되었다. 연구 결과, 네 가지 회복탄력성 측정값을 통해 각 지점이 가지는 연안침식 회복탄력성의 다양한 특성을 파악할 수 있음을 확인하였다. 연안 회복탄력성 복합 지수의 매핑 결과 서해안 및 남해안 지역에 비해 동해 안 지역들은 연안침식 회복탄력성이 상대적으로 떨어지는 것으로 나타났다. 본 연구의 회복탄력성 측정 모형은 적응 이후의 이행전략에 대한 논의를 제공하는 도구로 활용될 수 있으며, 서로 다른 취약 지역 그룹 간 정책지원에 대한 우선순위를 결정하는 데 이용 가능하다.

This study attempted to provide implications by analyzing the impact of business Owner’s safety commitment on industrial accidents and examining the mediating role of management supervisors’ safety leadership and worker participation. Analysis was conducted on 2,067 manufacturing sites with 20 to 50 employees in the 10th Occupational Safety and Health Survey data. SPSS waw used to secure the reliability of the measurement variable. Hypothesis vertification was carried out after securing the suitability and validity of the structural model using AMOS. The direct impact of three latent variables on industrial accidents was confirmed: the business owner’s safety commitment, the management supervisor’s safety leadership, and the worker participation. The employer’s safety will and the management supervisor’s safety leadership do not directly affect industial accidents, but it has been verified that worker participation has a diret impact on industrial accident reduction. In addition, it has been confirmed that the safety leadership and worker participation of the management. Supervior have a complete mediating effect on the reduction of industrial accidents by mediating with the safety leadership of the management supervior and the participation of the workers. This study analyzed the impact on industrial accidents by dividing the stakeholders constituting the workplace into three classes: business owners, superviors, and workers, but the results suggest that employers and all workers inside the workplace may be organically linked to achieving the goal of reducing industrial accidents. Therefore, in order to establish an autonomous safety management system for safety and health at workerplaces, efforts are needed to reduce industrial accidents in their respective location by forming an organic community among internal stakeholders.

Since 2024, small business are also going to be ruled under the Serious Accident Punishment Act. As the scope of the law expands, the small logistics companies are required to pay more attention on preventing serious accidents on the field. Freight vehicle accidents can cause personnel accidents and cargo accidents which are the two serious accidents that the Serious Accident Punishment Act is trying to prevent. The purpose of this research are to study the factors that cause the serious accidents that happens in the small logistics companies and to suggest preventive. The results of the study shows that fall prevention is the top-priority and then driving experience, safety management, and cargo driving hours. However, the gaps between the evaluation values of each are not huge, which means all the preventives are significant.

Recently, the importance of impact-based forecasting has increased along with the socio-economic impact of severe weather have emerged. As news articles contain unconstructed information closely related to the people’s life, this study developed and evaluated a binary classification algorithm about snowfall damage information by using media articles text mining. We collected news articles during 2009 to 2021 which containing ‘heavy snow’ in its body context and labelled whether each article correspond to specific damage fields such as car accident. To develop a classifier, we proposed a probability-based classifier based on the ratio of the two conditional probabilities, which is defined as I/O Ratio in this study. During the construction process, we also adopted the n-gram approach to consider contextual meaning of each keyword. The accuracy of the classifier was 75%, supporting the possibility of application of news big data to the impact-based forecasting. We expect the performance of the classifier will be improve in the further research as the various training data is accumulated. The result of this study can be readily expanded by applying the same methodology to other disasters in the future. Furthermore, the result of this study can reduce social and economic damage of high impact weather by supporting the establishment of an integrated meteorological decision support system.