• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.3
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• pp.253-258
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• 2015

The purpose of this study is to find suitable probability distribution function of complex distribution data like multimodal. Normal distribution is broadly used to assume probability distribution function. However, complex distribution data like multimodal are very hard to be estimated by using normal distribution function only, and there might be errors when other distribution functions including normal distribution function are used. In this study, we experimented to find fit probability distribution function in multimodal area, by using AIS(Automatic Identification System) observation data gathered in Mokpo port for a year of 2013. By using chi-squared statistic, gaussian mixture model(GMM) is the fittest model rather than other distribution functions, such as extreme value, generalized extreme value, logistic, and normal distribution. GMM was found to the fit model regard to multimodal data of maritime traffic flow distribution. Probability density function for collision probability and traffic flow distribution will be calculated much precisely in the future.

• Journal of Korea Port Economic Association
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• v.34 no.1
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• pp.65-80
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• 2018

This paper attempts to estimate GHG emissions, primarily $CO_2$ ship emissions, at the port of Incheon in October 2014. This study employed a bottom-up approach based on Automatic Identification System (AIS) data to estimate the total amount of fuel consumption and the total amount of $CO_2$ emission produced as a result of fuel combustion. Using a sample of 330 ships operating at the port of Incheon in Korea, the total amount of $CO_2$ gases emitted from ships in October 2014 were estimated to be 164693.06 tons, with estimated total fuel consumption of 51953.64 tons. General cargo ships were most common type of ships, but they were less polluting compared to passenger ships. The detailed emission estimates by ship type revealed that passenger ships were the most polluting ships (81409.6 tons of emissions), followed by tugboats (37248.4 tons), cargo ships (32154.6 tons), ships used for other activities (9039.1 tons), chemical tankers (4027.06 tons), and fishing ships (814.048 tons), respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1195-1202
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• 2016

Recently, a lot of studies that applying the big data technology to various fields, are progressing actively. In the maritime domain, the big data is the meaningful information which makes and gathers by the navigation and communication equipment from the many ships on the ocean. Also, importance of the maritime safety is emphasized, because maritime accidents are rising with increasing of maritime traffic. To support prevention of maritime accidents, in this paper, we developed a vessel traffic display and statistic system based on AIS messages from the many vessels of maritime. Also, to verify the developed system, we conducted tests for vessel track display function and vessel traffic statistic function based on two test scenarios. Therefore, we verified the effectiveness of the developed system for vessel tracks display, abnormal navigation patterns, checking failure of AIS equipments and maritime traffic statistic analyses.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.190-197
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• 2020

Recently there was an incident that military radars, coastal CCTVs and other surveillance equipment captured a small rubber boat smuggling a group of illegal immigrants into South Korea, but guards on duty failed to notice it until after they reached the shore and fled. After that, the detection of such vessels before it reach to the Korean shore has emerged as an important issue to be solved. In the fields of marine navigation, Automatic Identification System (AIS) is widely equipped in vessels, and the vessels incessantly transmits its position information. In this paper, we propose a method of automatically identifying abnormally behaving vessels with AIS using convolutional autoencoder (CAE). Vessel anomaly detection can be referred to as the process of detecting its trajectory that significantly deviated from the majority of the trajectories. In this method, the normal vessel trajectory is gridded as an image, and CAE are trained with images from historical normal vessel trajectories to reconstruct the input image. Features of normal trajectories are captured into weights in CAE. As a result, images of the trajectories of abnormal behaving vessels are poorly reconstructed and end up with large reconstruction errors. We show how correctly the model detects simulated abnormal trajectories shifted a few pixel from normal trajectories. Since the proposed model identifies abnormally behaving ships using actual AIS data, it is expected to contribute to the strengthening of security level when it is applied to various maritime surveillance systems.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.16-21
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• 2014

In recent, the maritime traffic has increased with an increase in international trading volumes and the growing popularity of marine leisure activities. As increasing of maritime traffic, marine accidents happened continually and there are possibilities of accidents at sea. According to the analysis of marine accidents, most accidents occurred by human error of seafarers. To reduce the accidents by human error, the various assistance system for assist seafarers have been proposed. It is required to real-time data management method for applying to real-time system, but most proposed assistance system used off-line data for analysis. In this paper, we aim to build a navigation supporting system for providing safety information to deck officer with data of AIS(Automatic Identification System) and ARPA Radar(Automatic Radar Plotting Aids Radar), and proposed a management algorithm for real-time ship information with blackboard system and verified the validity.

• Journal of the Korean Society for Marine Environment & Energy
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• v.16 no.1
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• pp.1-8
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• 2013

This study focuses on a ship detection and tracking method using Frequency Modulated Continuous Wave (FMCW) radar used for horizontal surveillance. In general, FMCW radar can play an important role in maritime surveillance, because it has many advantages such as low warm-up time, low power consumption, and its all weather performance. In this paper, we introduce an effective method for data and signal processing of ship's detecting and tracking using the X-band radar. Ships information was extracted using an image-based processing method such as the land masking and morphological filtering with a threshold for a cycle data merged from raw data (spoke data). After that, ships was tracked using search-window that is ship's expected rectangle area in the next frame considering expected maximum speed (19 kts) and interval time (5 sec). By using this method, the tracking results for most of the moving object tracking was successful and those results were compared with AIS (Automatic Identification System) for ships position. Therefore, it can be said that the practical application of this detection and tracking method using FMCW radar improve the maritime safety as well as expand the surveillance coverage cost-effectively. Algorithm improvements are required for an enhancement of small ship detection and tracking technique in the future.

• Journal of the Korean Institute of Navigation
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• v.24 no.5
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• pp.435-441
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• 2000

This paper deals with the development of RACOM(Radar Signal Detecting ＆ Processing Computer). RACOM is a radar display system specially designed for radar scan conversion, signal processing and PCI radar image display. RACOM contains two components； i )RSP(Radar Signal Processor) board which is a PCI based board for receiving video, trigger, heading & bearing signals from radar scanner ＆ tranceiver units and processing these signals to generate high resolution radar image, and ⅱ）Applications which perform ordinary radar display functions such as EBL, VRM and so on. Since RACOM is designed to meet a wide variety of specifications(type of output signal from tranceiver unit), to record radar images and to distribute those images in real time to everywhere in a networked environment, it can be applicable to AIS(Automatic Identification System) and VDR(Voyage Data Recorder).

• Journal of the Korean Institute of Navigation
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• v.22 no.1
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• pp.31-49
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• 1998

The technology of navigational instruments and the profession of going to sea have entered a time of dramatic change. A paradigm shift is taking place which will eventually make the industry unrecognizable to those who first went to sea only twenty years ago. This change is most emphatically seen in three areas: Automatic Identification System(AIS), Electronic Chart Display and Information System(ECDIS), and Voyage Data Recoreder(VDR). In order to make these new instruments to be fitted on board commerical ships, international requirements for enhacing the safety of navigation on the world's waterways, the Chapter V of International Convention for the Safety of Life at sea, 1974 as ameded(hereinafter referred to as "SOLAS"), are being also changed.o changed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.159-162
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• 2007

최근 통신 기술의 발달로 육상이동통신 기술을 해상 및 항공에 확대하려는 시도가 꾸준히 진행되고 있다. 해상 및 항공 통신은 인명 안전을 위한 통신으로 국제 기구에 의해서 최우선적인 보호를 받아 왔다. 그러나 통신 기술의 급속한 발전으로 해상 및 항공 통신망은 기존 음성 위주의 통신망에서 멀티미디어를 처리할 수 있는 디지틀망으로의 전환이 시급히 필요하게 되었다. 해상통신의 경우에는 디지틀 통신 방식을 이용하는 DSC(Digital Selective Calling), AIS(Automatic Identification System) 등을 이미 도입해서 운용 중에 있으며 다른 시스템으로의 확대가 진행 중에 있다. SOLAS 선박뿐 만 아니라 비 SOLAS(Safety Of Life At Sea) 선박들도 디지틀 통신을 활용하면 항행 안전에 매우 도움이 될 것이다. 최근에 ITU-R에서는 VHF(Very High Frequency) 대역에서 데이터 및 이메일 등을 송수신하기 위한 데이터 통신시스템 기술에 대한 논의가 진행 중에 있다. 본고에서는 이 VHF대역 데이터시스템에 대한 기술적 특성을 분석하고 향후 해상통신에서의 디지틀 기술이 도입된 후 전개될 해상통신망에 대해서 기술하였다.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.313-320
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• 2022

The light buoy installed on the sea is always flexible, because it is affected by the weather as well as passing vessels. The position of the light buoy can be cached through the AtoN AIS (Automatic Identification System) and RTU (Remote Terminal Unit). This study analyzed the position data of the light buoys for the last five years (2017-2021), as well as the distribution of the light buoys within the maximum separated position. As a result, there was a basic error of 17.9% in the position data. Additionally, the separated position error of 197 light buoys to be analyzed was 70.64%, and the AtoN RTU was worse than the AtoN AIS by equipment. On the other hand, as a result of the plotting the position data of the light buoy, it was classified into four types. The most common percussion center type, the percussion center dichotomous type in which the position is divided into two zones based on the chimney, the central movement type with a fluctuating center, and the drag type, in which the position is deviated from the center for a certain period. Except for Type-1, the type was determined according to the position at which the light buoy was installed. This study is the first to analyze the position data of the light buoy, and it is expected that it will contribute to the improvement of the quality of the position data of the light buoy.