• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.1
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• pp.60-66
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• 2023

Currently, the maritime industry is focusing on developing technologies that promote autonomy and intelligence, such as smart ships, autonomous ships, and eco-friendly technologies, to enhance ship operational efficiency. Many countries are conducting research on different methods to ensure ship safety while increasing operational efficiency. This study aims to develop a real-time ship operational efficiency analysis model using data analysis methods to address the current limitations of the present technologies in the real-time evaluation of operational efficiency. The model selected ship operational efficiency factors and ship operational condition factors to compare the operational efficiency of the ship with present and classified factors to determine whether the present ship operational efficiency is appropriate. The study involved selecting a target ship, collecting data, preprocessing data, and developing classification models. The results of the research were obtained by determining the improved ship operational efficiency based on the ship operational condition factors to support ship operators.

• Journal of Navigation and Port Research
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• v.40 no.3
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• pp.105-111
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• 2016

In ports of Korea, the marine traffic flow is congested due to a large number of vessels coming in and going out. In order to improve the safety and efficiency of these vesse's movement, South Korea is operating with a Vessel Traffic System, which is monitoring its flow 24-7. However despite these efforts of the VTS (Vessel Traffic System) officers, marine accidents are occurring continuously in their control area. VTS Officers are controlling subjectively based on their experience due to no VTS control guideline of dangerous situation among vessels. On this paper, we listened to Busan VHF channel for 3days and analyzed the message. With collision risk model, We analyzed a moment of risk which officers advise or recommend to vessel in encounter situation, VTSO's career, and day&night.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.59-68
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• 2021

As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

• Journal of the Korean Society of Marine Environment & Safety
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• v.17 no.3
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• pp.227-233
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• 2011

Korea coastal area is highly potential dangerous zone of marine accident due to frequent ship's encounters. VTS center can't identify ship's information because of beyond VHF range. It is also difficult of us to efficiently manage vessel traffic beyond VTS control area, so that it can't prevent marine accident. Presently, korean government is conducting maritime traffic safety assessment according to enlargement of harbor & development of new port but do not have the system which provide danger of information depending on maritime traffic environment with real time. So it is necessary to develop evaluation index which can assess sea risk through the evaluation of maritime traffic environment. In this paper, on the basis of vessel navigator's risk consciousness, we carried out survey & statistical analysis vessel navigator's subjective risk depending on the LOA, crossing situation($045^{\circ}$, $090^{\circ}$, $135^{\circ}$), overtaking, head-on situation, encountering vessel's side, within or outside harbor, speed with other vessel(ex. same, fast or slow), speed difference with other vessel and distance with other vessel & propose basic expression to develop maritime traffic safety evaluation model. And by using this model, we can confirm that this proposing expression is suitable for domestic maritime traffic environment.