강원도 북부의 남북 접경지 3개소(서부-철원, 영서-양구, 영동-고성)에서 2023년 5월 11일부터 10월 12일까지 주요 천공성 해충 분류군인 나무좀아과를 대상으로 시기별 발생 양상 및 4가지 유인제(Ipsenol, Ipsedienol, Alpha-pinene, Monochamol)별 유인되는 종과 개체수를 조사 하였다. 연구결과, 총 26속 45종 7,743개체를 확인하였다. 확인한 종 중, 15종이 모든 조사지역에서 공통적으로 발생하고, 2종(암브로시아나무 좀, 왕녹나무좀)이 모든 조사지에서의 우점종으로 확인되었으며, 4종(오리나무좀, 붉은목나무좀, 여름나무좀, 암브로시아나무좀)이 조사기간(5 월~10월) 중 지속적으로 발생하는 것으로 확인되었다. 지역적으로는 가장 다양한 식물종들로 혼합림을 구성하고 있는 양구지역에서 총 36종 2,840개체가 확인되어 다른 두 조사지에서보다 다양하고 많은 개체가 확인되었다. 각 조사지에서 유인제별 확인한 종수는 유의미한 차이를 보이 지 않았으며 개체수면에서 철원에서는 Monochamol, 양구에서는 Ipsedienol, 고성에서는 Ipsenol 유인제에서 가장 많은 개체가 확인되었다.

The model ship of this study, the Baek-Kyung fisheries training ship of Pukyong National University, has a length between perpendiculars of 85 meters, making it not subject to the IMO maneuverability standards. However, understanding the maneuvering characteristics of the vessel is essential for safe navigation. In this regard, this study was conducted to analyze the results from the sea trials of the model ship conducted in accordance with the IMO maneuverability standards. The results of the turning tests met the standards well while in the zig-zag tests, the first overshoot angle exceeded the standard in the 10°/10° test; however, such results met with a difference of 1.8° in the 20°/20° test. Additionally, using the course-stability discrimination formula, the calculated value was -0.0051, indicating unstable course-stability. The results of the stopping tests met the standards well. It is hoped that the analyzed maneuvering characteristics of the model ship from the study results will contribute to the safety of ship navigation.

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.

We analyzed risk factors of coastal gillnet fishers during fishing process and considered work safety measures to reduce safety accidents during fishing using a UWB (ultra wideband) based positioning system. The static position accuracy of the UWB based positioning system was 45 cm. When entering a port, there is a risk of falling overboard. When casting a net, there was a risk of falling overboard due to being hit by fishing gear or guards, or getting caught in a buoy line or sinker line. When hauling a net, there is a risk of getting caught between fishing gear and net hauler, and the risk of musculoskeletal disorders due to repetitive work over a long period of time. Most safety accidents during work on fishing boats are blamed on human errors of the fisher and skipper, but safety accidents occur due to a mixture of mechanical and equipment factors, work and environmental factors, and management factors in addition to human errors. Therefore, the 4E were presented as countermeasures against the 4M, which are causes of safety accidents, and the proposed measures were used to identify risk factors for operation process, comply with work safety rules, and ensure the wearing of personal protective equipments. We need to reduce safety accidents during work by making it part of our daily routine. These research results can be used in the future for optimal placement of fishing gear and fishing nets in other coastal industries where safety accidents occur frequently.