본 연구는 '절망사(Deaths of Despair)' 개념을 적용하여 2018년 ‘고 령사회’에 진입한 이후 2023년까지 노인 자살생각과 관련된 국내의 연구 를 대상으로 노인의 자살생각을 유발하는 위험요인의 효과크기를 메타분 석을 통해 검증하여 노인의 자살생각과 관련된 후속연구의 방향을 제시 하고, 노인 자살을 예방하는 정책적 제안을 하는데 목적이 있다. 연구대 상은 효과크기 변환이 가능하고, 노인의 자살생각을 종속변수로, 자살생 각에 영향을 미치는 위험요인을 독립변수 및 매개변수로 하는 학술지 및 학위논문 64편을 연구대상으로 선정하였다. 분석결과 우울, 인식된 짐스 러움, 좌절된 소속감, 차별경험, 불안, 스트레스, 고독감 7개의 위험요인 을 추출하였으며 전체 효과크기는 0.41로 나타났고, 기존 메타분석 연구 와 다르게 고독감의 효과크기가 가장 컸으며 스트레스, 인식된 짐스러움, 불안, 우울, 차별경험, 좌절된 소속감의 순으로 효과크기가 큰 것으로 나 타났다. 분석 결과를 바탕으로 절망사 개념의 주요 시사점을 중심으로 노인 자살생각의 경감을 위한 대응방안 및 정책적 제안을 제시하였다.

최근 자율주행 차량의 등장으로 인해 기존의 교통 시스템에 많은 변화가 생길 것으로 보이며, 운전자가 주행하던 차량과는 다른 행태로 인해 기존 비자율주행 차량들이 초래하는 고위험 상황의 요인과는 다른 새로운 요인들이 도출될 것으로 보인다. 하지만, 현 시점 국내 에서는 자율주행 차량이 실제로 주행하고 있지 않기 때문에 주행행태를 포함한 데이터 기반의 주요 요인 분석 및 도출에 한계가 있다. 따라서 현 시점에서 자율주행 차량이 혼재하는 환경에서 고위험한 상황을 정의할 수 있는 요인을 도출하기 위해서는 사례 중심의 분석이 필요하다. 따라서 본 연구에서는 기존 국내·외 자율주행차량과 관련된 다양한 논문 사례를 DB화하여 이를 정량적으로 평가할 수 있는 메타 분석(Meta-Analysis) 기법을 통해 향후 자율주행차량이 혼재하는 교통 네트워크에서 안전성을 증진하기 위한 고위험 유발의 주요 요인을 도출하고자 하였다. 본 연구에서 DB화한 논문은 자율주행 차량과 관련된 총 4가지(사고요인, 시나리오, 예측모델, 법규)에 해당 하는 분야로 분류하여 수집하였으며, 2015년부터 2024년 까지 최근 10개년에 해당 되는 사례를 수집하여 분석을 수행하고 주요 요인을 도출하였다. 본 연구의 결과는 향후 자율주행 차량 혼재 시 고위험 상황의 주요 요인들을 바탕으로 각 요인에 기반한 자율주행차량 혼재 시 고위험 상황에 대한 정의를 할 수 있으며, 이러한 고위험 요인들에 의해 도로교통의 안전성이 저해될 수 있는 요인에 대한 사전 예방을 수행할 수 있을 것으로 기대된다.

2020년 국토교통부에서는 ‘결빙 취약구간 평가 세부 배점표’에 의하면, 전국의 고속국도 및 일반국도를 대상으로 결빙 취약 구간 464 개소를 선정하여 관리중에 있다. 그러나 감사원은 2020년 진행한 주요 사회기반시설(도로ㆍ고속철도) 안전관리실태 감사에서 결빙 취 약 구간 선정 시 터널 입출구부 등 결빙위험이 큰 구간이 도로포장 홈파기 대상구간에서 누락된 점을 지적하였다. 이러한 근거로 결 빙에 취약한 터널 입ㆍ출구에서 결빙사고가 우려되는 등 ‘겨울철 도로교통 안전 강화대책’의 실효성이 저하될 가능성이 제시되었다. 또한 본 연구에서 자체적으로 검토한 결과, 4개 특성 12개 항목으로 구성된 ‘결빙 취약구간 평가 세부 배점표’의 도로시설 항목에서 터널, 교량 등 도로시설물의 배점 부여 기준을 확인하기 어려웠으며, 각 도로시설에 대한 정의가 모호하여 평가표의 현장 적용성이 제 한되거나 신뢰도 검증이 부족한 점을 확인하였다. 본 연구에서는 국토교통부에서 제공하는 노드(Node) 및 링크(Link) 기반의 국내 도로망 GIS(Geographic Information System)데이터 에 결빙사고 데이터의 위치정보를 결합하여 고속국도 및 일반국도의 터널 및 교량 등을 포함하는 도로시설물 및 그 주변에서 발생한 결빙사고 이력을 자료화하였다. 최종적으로 도로시설물별 결빙사고 발생 비율 및 사고 심각도(사망자, 부상자 수)에 대한 분석을 통해 도로시설물의 결빙사고 상관 정도와 영향 범위를 파악하였다.

과거 교통에서는 이동의 신속성이 중시되고 자동차의 통행이 우선이었던 반면, 현재는 모든 교통 이용자의 안전한 이동과 보행자가 중요시되는 방향으로 교통정책이 나아가고 있다. 보행자의 안전하고 쾌적한 통행과 교통약자의 이동권의 보장이 강조됨에 따라서, 향 후 교통약자 보호구역의 역할도 확대될 것으로 예상된다. 그러나 교통약자의 안전한 보행 공간 확보와 보행사고 피해의 축소라는 목 적과 달리, 스쿨존 내 사고 등은 지속적으로 발생하고 있는 추세이다. 이에 본 연구에서는 보호구역의 사고 위험을 판단하고 안전성을 분석하고자 하였다. 교통사고의 위험성을 비교하고 사고 예방이 필요한 보호구역을 판단하기 위한 기준으로서 사고 위험도를 정량화 하였다. 서울시 보호구역 내 사고 데이터를 보호구역 구간별 특성 데이터와 결합하여 구간별 사고 건수 및 피해 정도를 자료화하고, 도로 속성을 기준으로 보호구역 구간을 유형화하였다. 보호구역 유형별 사고 발생확률과 평균 피해 정도를 구해 도로의 속성마다 다 른 사고 발생 특성을 반영하였다. 사고 위험도는 사고 발생빈도와 피해 정도를 통해 판단하고자 하였다. 사고 발생빈도는 도로 면적과 발생 건수를 기준으로 하여 산출하였고, 피해 정도는 유형에 따른 사고 발생확률과 발생빈도, 평균 피해 정도를 통해 산출하였다. 위 험도에 대한 정량적 분석모델을 통해 사고 위험이 높다고 판단되는 보호구역과 해당 구간의 특성을 알아보고, 각 행정구역별로 보호 구역에서의 교통사고 위험성을 비교하였다. 이를 통해 사고 위험이 높은 지역과 유형이 무엇이며, 어떠한 특성을 보이는지 파악하여 보호구역 개선 방향을 제시하고자 한다.

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.

As the complexity and uncertainty of international construction projects increase, the importance of risk management capabilities in the construction industry has become more pronounced. Accordingly, Enterprise Risk Management (ERM) has become a widely adopted approach among organizations as a new way for more effective risk management. Despite its growing application, research related to ERM is still in its infancy, and most of the existing studies have been limited to financial industries. Therefore, this study aims to empirically examine the influence of ERM’s core elements on project risk management (PRM) and project performance within construction firms. Our findings indicate that the key ERM components—organization, policy, and culture—significantly enhance PRM processes, underscoring their critical role and importance. Additionally, effective PRM positively affects project outcomes, highlighting its significance for construction companies engaged in international projects. While ERM does not directly impact project performance, it indirectly improves outcomes through enhanced PRM capabilities. It suggests that ERM will contribute to the firm’s performance by improving the firm’s PRM capability through policies and a risk-focused culture corresponding to the adopted ERM organization and system..

Fueled by international efforts towards AI standardization, including those by the European Commission, the United States, and international organizations, this study introduces a AI-driven framework for analyzing advancements in drone technology. Utilizing project data retrieved from the NTIS DB via the “drone” keyword, the framework employs a diverse toolkit of supervised learning methods (Keras MLP, XGboost, LightGBM, and CatBoost) enhanced by BERTopic (natural language analysis tool). This multifaceted approach ensures both comprehensive data quality evaluation and in-depth structural analysis of documents. Furthermore, a 6T-based classification method refines non-applicable data for year-on-year AI analysis, demonstrably improving accuracy as measured by accuracy metric. Utilizing AI’s power, including GPT-4, this research unveils year-on-year trends in emerging keywords and employs them to generate detailed summaries, enabling efficient processing of large text datasets and offering an AI analysis system applicable to policy domains. Notably, this study not only advances methodologies aligned with AI Act standards but also lays the groundwork for responsible AI implementation through analysis of government research and development investments.

The digitization of ship environments has increased the risk of cyberattacks on ships. The smartization and automation of ships are also likely to result in cyber threats. The International Maritime Organization (IMO) has discussed the establishment of regulations at the autonomous level and has revised existing agreements by dividing autonomous ships into four stages, where stages 1 and 2 are for sailors who are boarding ships while stages 3 and 4 are for those not boarding ships. In this study, the level of a smart ship was classified into LEVELs (LVs) 1 to 3 based on the autonomous levels specified by the IMO. Furthermore, a risk assessment for smart ships at various LVs in different risk scenarios was conducted The cyber threats and vulnerabilities of smart ships were analyzed by dividing them into administrative, physical, and technical security; and mitigation measures for each security area were derived. A total of 22 cyber threats were identified for the cyber asset (target system). We inferred that the higher the level of a smart ship, the greater the hyper connectivity and the remote access to operational technology systems; consequently, the greater the attack surface. Therefore, it is necessary to apply mitigation measures using technical security controls in environments with high-level smart ships.

This study aimed to quantitatively analyze the risk using data from 329 safety accidents that occurred in aquaculture fisheries management vessels over the recent five years (2018-2022). For quantitative risk analysis, the Bayesian network proposed by the International Maritime Organization (IMO) was used to analyze the risk level according to the fishing process and cause of safety accidents. Among the work processes, the fishing process was analyzed to have the highest risk, being 12.5 times that of the navigation, 2.7 times that of the maintenance, and 8.8 times that of the loading and unloading. Among the causes of accidents, the hull and working environment showed the highest risk, being 1.7 times that of fishing gear and equipment, 4.7 times that of machinery and equipment, and 9.4 times that of external environment. By quantitatively analyzing the safety accident risks for 64 combinations of these four work processes and four accident causes, this study provided fundamental data to reduce safety accidents occurring in aquaculture fisheries management vessels.

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.

In this study, the AHP (analytic hierarchy process) technique was used to analyze the risk of expected risk factors and fishing possibilities during gillnet fishing within the floating offshore wind farms (floating OWF). For this purpose, the risks that may occur during gillnet fishing within the floating offshore wind farms were defined as collisions, entanglements, and snags. In addition, the risk factors that cause these risks were classified into three upper risk factors and ten sub risk factors, and the three alternatives to gillnet fishing available within the floating OWF were classified and a hierarchy was established. Lastly, a survey was conducted targeting fisheries and marine experts and the response results were analyzed. As a result of the analysis, among the top risk factors, the risk was the greatest when laying fishing gear. The risk of the sub factors for each upper risk was found to be the highest at the berthing (mooring), the final hauling of fishing net, and the laying of the bottom layer net. Based on the alternatives, the average of the integrated risk rankings showed that allowing full navigation/fisheries had the highest risk. As a result of the final ranking analysis of the integrated risk, the overall ranking of allowing navigation/fisheries in areas where bottom layer nets were laid was ranked the first when moving vessels within the floating OWF was analyzed as the lowest integrated risk ranking of the 30th at the ban on navigation/fisheries. Through this, navigation was analyzed to be possible while it was analyzed that the possibility of gillnet fishing within the floating OWF was not high.

The demand for transportation is increasing due to the continuous generation of radioactive wastes. Especially, considering the geographical characteristics of Korea and the location characteristics of nuclear facilities, the demand for maritime transportation is expected to increase. If a sinking accident happens during maritime transportation, radioactive materials can be released into the ocean from radioactive waste transportation containers. Radioactive materials can spread through the ocean currents and have radiological effects on humans. The effect on humans is proportional to the concentration of radioactive materials in the ocean compartment. In order to calculate the concentration of radioactive materials that constantly flow along the ocean current, it is necessary to divide the wide ocean into appropriate compartments and express the transfer processes of radioactive materials between the compartments. Accordingly, this study analyzed various ocean transfer evaluation methodologies of overseas maritime transportation risk codes. MARINRAD, POSEIDON, and LAMER codes were selected to analyze the maritime transfer evaluation methodology. MARINRAD divided the ocean into two types of compartments that water and sediment compartments. And it was assumed that radionuclides are transfered from water to water or from water to sediment. Advection, diffusion, and sedimentation were established as transfer process for radionuclides between compartments. MARINRAD use transfer parameters to evaluate transer processes by advection, diffusion, and sedimentation. Transfer parameters were affected by flow rate, sedimentation rate, sediment porosity, and etc. POSEIDON also divided the ocean into two types that water and sediment compartment, each compartments was detaily divided into three vertical sub-compartment. Advection, diffusion, resuspension, sedimentation, and bioturbation were established as transport processes for radionuclides between compartments. POSEIDON also used transfer parameters for evaluating advection, diffusion, resuspension, sedimentation, and bioturbation. Transfer parameters were affected by suspended sediment rates, sedimentation rates, vertical diffusion coefficients, bioturbation factors, porosity, and etc. LAMER only considered the water compartment. It divided the water compartment into vertical detailed compartments. Diffusion, advection and sedimentation were established as the nuclide transfer processes between the compartments. To evaluated the transfer processes of nuclides for diffusion and advection, LAMER calculated the probability with generating random position vectors for radionuclides’ locations rather than deterministic methods such as MARINRAD’s transfer parameters or POSEIDON’s transfer rates to evaluate transfer processes. The results of this study can be used as a basis for developing radioactive materials’ ocean transfer evaluation model.