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In dense anchorage areas, the challenge of navigation for Unmanned Surface Vehicles (USVs) is particularly pronounced, especially regarding path safety and economy. A Risk-Aware Path Optimization Algorithm (RAPO) is proposed to enhance the safety and efficiency of USV navigating in anchorage areas. The algorithm incorporates risk assessment based on the A* algorithm to generate an optimized path and employs a Dual-Phase Smoothing Strategy to ensure path smoothness. First, the anchorage area is spatially separated using a Voronoi polygon, the RAPO algorithm includes a grid risk function, derived from the ship domain and Gaussian influence function, in the path evaluation criteria, directing USV to successfully bypass high-risk areas and as a result. Then the DPSS is used to decrease path turning points and boost path continuity, which in turn improves path economy. Simulation results demonstrate that this method significantly reduces the path length and the number of turning points, enhancing USV navigation safety in anchorage areas.

Crew members aboard international voyage ships are susceptible to imported acute respiratory infections, leading to clusters of outbreaks that pose challenges to the health of crew members. The aim of the proposed study was to optimize a plan for the quarantine process and rescue measures in response to a coronavirus disease 2019 (COVID-19) outbreak at sea to provide policy guidance for the prevention and control of severe infectious diseases on international voyage ships. Here, we described the baseline characteristics of international voyage ships and crew members entering Zhoushan Port from 2020 to 2022 and analyzed the factors influencing the incidence rate of COVID-19 among crew members. There were 161 COVID-19 cases among cargo ships entering Zhoushan Port by sea, with an average incidence rate of 16.00% (95% CI: 13.73%-18.27%). The incidence rate of COVID-19 was significantly higher among crew members with replacement, long voyage, and those who stayed at multiple anchorages or stayed for a long time. The risk of COVID-19 infection for crew members staying at more than 4 anchorage was the highest, which was 2.667 (95% CI: 1.857-3.830) times that of crew members staying at less than 4 anchorage. We developed and refined the workflow for a public health assistance plan for outbreaks at sea on the basis of our experience with several COVID-19 outbreaks on international voyage ships. The workflow includes fundamental requirements, sampling and testing methods, personnel transfer procedures, medical waste disposal guidelines, and disinfection procedures for affected ships. Our public health assistance plan can be applied to other international voyage ships for which urgent public health assistance is needed during sudden infectious disease outbreaks.

EU Naval Force can confirm that the Malaysian flagged Motor Vessel MV Albedo, held by armed pirates at an anchorage close to the Somali Coast, has sunk in rough seas.

A containership which was owned by defunct Hong Sheng Gai Tai Shipping, , has started leaking oil after being stranded near Kinmen of Taiwan. The vessel was blown off anchorage near Xiamen by a storm and has yet to be towed back. According to the environmental protection department, the vessel is carrying 25 tons of …

A containership which was owned by defunct Hong Sheng Gai Tai Shipping, , has started leaking oil after being stranded near Kinmen of Taiwan. The vessel was blown off anchorage near Xiamen by a storm and has yet to be towed back. According to the environmental protection department, the vessel is carrying 25 tons of …

Preparing for invasive species in the BERING Sea.

In maritime logistics optimization, considerable research efforts are focused on the extraction of deep behavioral characteristics from comprehensive shipping data to discern patterns in maritime vessel behavior. The effective linkage of these characteristics with maritime infrastructure, such as berths, is critical for the enhancement of ship navigation systems. This endeavor is paramount not only as a research focus within maritime information science but also for the progression of intelligent maritime systems. Traditional methodologies have primarily emphasized the analysis of navigational paths of vessels without an extensive consideration of the geographical dynamics between ships and port infrastructure. However, the introduction of knowledge graphs has enabled the integration of disparate data sources, facilitating new insights that propel the development of intelligent maritime systems. This manuscript presents a novel framework using knowledge graph technology for profound analysis of maritime data. Utilizing automatic identification system (AIS) data alongside spatial information from port facilities, the framework forms semantic triplet connections among ships, anchorages, berths, and waterways. This enables the semantic modeling of maritime behaviors, offering precise identification of ships through their diverse semantic information. Moreover, by exploiting the semantic relations between ships and berths, a reverse semantic knowledge graph for berths is constructed, which is specifically tailored to ship type, size, and category. The manuscript critically evaluates a range of graph embedding techniques, dimensionality reduction methods, and classification strategies through experimental frameworks to determine the most efficacious methodologies. The findings reveal that the maritime knowledge graph significantly enhances the semantic understanding of unmanned maritime equipment, thereby improving decision-making capabilities. Additionally, it establish

Alaska boat captain arrested for drunken driving.