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Cruise ships and other naval vessels include automated Internet of Things (IoT)-based evacuation systems for the passengers and crew to assist them in case of emergencies and accidents. The technical challenges of assisting passengers and crew to safety during emergencies include various aspects such as sensor failures, imperfections in the sound or display systems that are used to direct evacuees, the timely selection of optimum evacuation routes for the evacuees, as well as computation and communication delays that may occur in the IoT infrastructure due to intense activities during an emergency. In addition, during an emergency, the evacuees may be confused or in a panic, and may make mistakes in following the directions offered by the evacuation system. Therefore, the purpose of this work is to analyze the effect of two important aspects that can have an adverse effect on the passengers’ evacuation time, namely (a) the computer processing and communication delays, and (b) the errors that may be made by the evacuees in following instructions. The approach we take uses simulation with a representative existing cruise ship model, which dynamically computes the best exit paths for each passenger, with a deadline-driven Adaptive Navigation Strategy (ANS). Our simulation results reveal that delays in the evacuees’ reception of instructions can significantly increase the total time needed for passenger evacuation. In contrast, we observe that passenger behavior errors also affect the evacuation duration, but with less effect on the total time needed to evacuate passengers. These findings demonstrate the importance of the design of passenger evacuation systems in a way that takes into account all realistic features of the ship’s indoor evacuation environment, including the importance of having high-performance data processing and communication systems that will not result in congestion and communication delays. [ABSTRACT FROM AUTHOR]

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Objectives Due to such factors as docking and temperature due to sunshine exposure, overall and partial response and deformation will occur during the construction and maintenance of surface vessels. On the one hand, it will affect the construction accuracy and safety of the hull, and on the other, it will affect the calibration of the relevant maintenance system.Methods In this paper, based on the finite element method, research on the structural response and deformation analysis method of a docking ship is carried out while taking into account the influence of temperature difference caused by sunshine.Results A finite element model is created for the entire hull of a docked surface ship according to the principles of docking block arrangement. According to the measured temperature data, the structural response and deformation prediction of the docked ship under the temperature difference of sunshine is carried out. The calculation results reveal the reason behind the phenomenon of “lotus leaf deformation” in docked vessels.Conclusions The results of this study are of valuable reference value for the calibration of shipborne weapon systems and aviation support systems in a docked state.

Hannah Snell is arguably considered the most famous woman who embarked on warships as a marine in men’s clothes. Astonishingly, she was able to be involved with missions as a seaman for more than four years without anyone discovering her true identity. Although her experiences were portrayed in some magazines, such as Gentlemen’s Magazine and Scots Magazine, and books published in Holland and England, her life entered history as fact through The Female Soldier; Or, The Surprising Life and Adventures of Hannah Snell by Robert Walker, a London newspaper printer. This paper addresses Walker’s first edition as a primary source because it was written after hearing directly from Hanna Snell, which means it can be recognized as being closer to the truth than the expanded edition. I examine the significance of female cross-dressing aboard male-dominated naval ships by analyzing the body of Hannah Snell as depicted in The Female Soldier.

Accurate magnetic-signature prediction is the most challenging task in the path of active magnetic-signature minimization. This article discusses the effect of the change in hull thickness, relative permeability, and radius of the object, considering the detailed understanding of the magnetic signatures. The traditional magnetic experiment-based method using a 12-coil structure is implemented for a double hull vessel. However, the time required and effort involved in predicting the magnetic signature is much higher. Hence, a multiple linear regression-based statistical machine-learning (ML) technique for the magnetic signature prediction is proposed. The nonlinear magnetic behavior of the naval vessel is assumed to be linear, because the hysteresis curve in the range of the earth’s ambient field is linear. Hence, a linear relationship is developed between the magnetic signatures and each component of the ambient earth’s magnetic field. The ML-based model also considers the crosstalk among the longitudinal, athwartship, and vertical signatures. The predicted magnetic signatures using the ML technique and the experiment-based techniques are compared. The ML method is found to be accurate, fast, and precise compared with the laboratory-based method, which has strict and continuous requirements for hardware magnetic facility. This method is very simple to implement and directly contributes to the development of the real-time degaussing current calculation algorithm. [ABSTRACT FROM AUTHOR]

The article examines IRGC’s naval provocations and US government sanctions on Iran to support stabilization in the region and prevent the development of nuclear weapons. Trump’s policy towards Iran is analyzed, taking into account the strengthening or weakening of the country’s unannounced actions. [ABSTRACT FROM AUTHOR]