• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.05a
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• pp.85-86
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• 2019

등부표는 선박이 운항할 때 경제적이고 안전한 항로를 선택할 수 있도록 유도하는 항행 원조 시설로 안전 항해에 매우 중요한 요소이다. 그러나 통항 선박의 추돌사고로 인하여 등부표의 파손 및 유실이 발생하고 있다. 따라서 본 연구에서는 해상교통평가모델을 활용하여 등부표 접촉사고 발생 위험성을 평가하고자 한다. 먼저 항만물동량이 높고, 항로에 등부표가 다수 설치된 부산항을 대상항만으로 선정하고, 부산항의 등부표 접촉사고 현황에 대하여 조사 분석했다. 그리고 부산항의 해상교통량을 기반으로 해상교통평가모델인 IWRAP, PARK Model을 활용하여 등부표 접촉사고 발생의 위험성을 평가했다. 추후에 다양한 해역의 접촉사고 위험성을 평가하고, 미래교통량을 추정 적용하여 등부표 신설 시 안전한 등부표 설치 해역 선정의 기초자료로 활용할 수 있을 것이다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.145-146
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• 2022

물동량 증가로 인하여 부산신항에는 극초대형 컨테이너 선박들이 입항하고 있으며 서컨테이너 부두 건설 사업이 완료되면 부산신항 진출입 항로 내 다양한 조우 상황 발생으로 충돌 위험 상황을 초래할 수 있어 선박 통항 안전성 향상 방안 마련을 위하여 부산신항 내 항만 입출항 현황과 해상교통흐름을 살펴보았으며, AHP 기법을 활용하여 위험요소 및 안전대책 식별로 도출된 안전대책을 기반으로 환경 스트레스 모델을 활용하여 해상교통류 시뮬레이션을 실시하여 각 안전대책의 교통 위험도를 파악하였다. 설문조사 및 시나리오 평가 결과, 선박운항자는 일방통행을 위한 진입금지 해역 설정을 가장 중요하게 생각하였으며, 이는 위험도 경감에 큰 효과가 있을 것으로 예상되었다, 본 연구는 부산신항을 입출항 하는 선박들의 통항 안전성 제고를 위한 안전대책 마련의 기반이 될 수 있을 것이다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2113-2120
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• 2012

The study of automatic monitoring and analysis of marine environment in Korea is not enough. Recently, the marine monitoring technology is actively being studied since the sea is a rich repository of natural resources that is taken notice in the world. In particular, the marine environment data should be collected continuously in order to understand and analyze the marine environment, however the marine environment monitoring is limited in many area yet. The prediction of marine disaster by automatic collecting marine environment data and analyzing the collected data can contribute to minimized the damages with respect to marine pollution of oil spill and fisheries damage by red tide blooms and marine environment upsets. In this paper, we proposed the marine environment monitoring and analysis system model. The proposed system automatically collects the marine environment information for monitoring the marine environment intelligently. Also it predicts the marine disaster by analyzing the collected ocean data.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2017.11a
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• pp.115-116
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• 2017

In this paper, we propose a standardization strategy for next generation electronic navigational chart which can be classified as S-100 Universal Hydrographic Data Model, to accept various requirements arising from various marine information and services as well as support e-navigation service strategies. IMO uses the next generation electronic chart standard, S-100 as Common Maritime Data Structure. It means that a common data model is needed as a key element for realization of e-Navigation and also points out that a new ICT convergence paradigm is needed not only for marine safety but also for maritime information and services. this paper considers he model-based data representation and reference model in order to understand the content and use of the S-100 standard and also considers the interconnectivity and role of the ISO/TC211 standards, which are being used as base standards for profiling to develop S-100 standard. Finally, we look at what standardization items are required for standardization of next generation electronic navigational chart supporting multi-purpose and how they are used mutually.

• Nuclear Engineering and Technology
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• v.23 no.4
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• pp.387-400
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• 1991

An ocean compartment model simulating transport of nuclides by advection due to ocean circulation and intertaction with suspended sediments is developed, by which concentration breakthrough curves of nuclides can be calculated as a function of time. Dividing ocean into arbitrary number of characteristic compartments and performing a balance of mass of nuclides in each ocean compartment, the governing equation for the concentration in the ocean is obtained and a solution by the numerical integration is obtained. The integration method is specially useful for general stiff systems. For transfer coefficients describing advective transport between adjacent compartments by ocean circulation, the ocean turnover time is calculated by a two-dimensional numerical ocean model. To exemplify the compartment model, a reference case calculation for breakthrough curves of three nuclides in low-level radioactive wastes, Tc-99, Cs-137, and Pu-238 released from hypothetical repository under the seabed is carried out with five ocean compartments. Sensitivity analysis studies for some parameters to the concentration breakthrough curves are also made, which indicates that parameters such as ocean turnover time and ocean water volume of compartments have an important effect on the breakthrough curves.

• Journal of Navigation and Port Research
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• v.46 no.3
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• pp.158-167
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• 2022

The International Maritime Organization's e-Navigation strategy introduces new technologies to ships to support easier and safer navigation. To implement the e-Navigation strategy, it was necessary to develop a common data model, that could meet various requirements across all aspects of the maritime information service. The International Hydrographic Organization's S-100 Universal Hydrographic Data Model was selected, as the basis for the standardization of maritime data products. Three S-100 based product specifications for weather information, collectively called "S-41X", are currently under development by the NOAA's Ocean Prediction Center, for use in the Electronic Chart Display and Information System (ECDIS). This paper describes a design of a grid based S-413 data model out of three S-41X product specifications. Other S-100 data products, which support the gridded data format, were considered. To verify the data model, an encoding test was conducted, using the Korean Meteorological Adminstration's numerical prediction model results.

• Proceedings of KOSOMES biannual meeting
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• 2005.11a
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• pp.147-151
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• 2005

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.108-110
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• 2020

본 연구의 목적은 딥러닝 기법의 하나인 인공신경망 모델을 활용하여 선박의 가치평가 모델을 개발하는 것이다. 선박의 가치는 해운시장 변화와 밀접한 관계가 있으며, 경기 변동성이 크고 시장 민감성이 높은 해운시장의 특성상 가치의 불확실성 역시 높게 나타나고 있다. 이러한 선박가치의 중요성에도 불구하고 국내외적으로 선박가치평가의 체계 개선 및 평가모델의 객관성과 신뢰성을 제고시키기 위한 연구는 부족한 실정이다. 따라서 본 연구에서는 딥러닝 방법을 통해 선박의 가치를 산출하는 새로운 평가모델을 제시하고자 한다. 가치평가의 대상은 중고 VLCC선이며, 선행연구를 통해 선박의 가치 변화를 유발하는 주요 요인들을 선별하여 변수를 설정하고 2010년 1월부터 현재까지의 해당 데이터를 확보하였다. 교차검증을 통해 파라미터들을 추정하여 인공신경망의 최적 구조를 식별하고 이에 대한 객관성과 신뢰성을 검증한 결과 인공신경망 모델의 가치평가 정확성이 우수함을 확인하였다. 본 연구는 선박가치평가의 전통적 방법론에서 탈피하여 기계학습 기반의 딥러닝 모델을 활용한 측면에서 독창적인 의미가 있다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.236-238
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• 2015

According to the change of maritime environments and the development of science and technologies unidentified risk factors are created day by day in the world. It is crucial reason for the occurrence of maritime accidents that the unidentified risk factors make unexpected and extra-ordinary cases. Thus prior identification of unidentified risk factors is key issues to prevent maritime accidents. In addition to the identification of risk factors, the identification and classification of ongoing risk factors and evaluation model in the future is also one of key issues to consider unidentified maritime accidents. In this study, we searched on the conventional risks and unidentified risks to find risk control options for new, unidentified and expected risks.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1120-1128
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• 2022

In the event of a marine accident, the longer the exposure time to the sea increases, the faster the chance of survival decreases. However, because the search area of the sea is extremely wide compared to that of land, marine object detection technology based on the sensor mounted on a satellite or an aircraft must be applied rather than ship for an efficient search. The purpose of this study was to rapidly detect an object in the ocean using a hyperspectral image sensor mounted on an aircraft. The image captured by this sensor has a spatial resolution of 8,241 × 1,024, and is a large-capacity data comprising 127 spectra and a resolution of 0.7 m per pixel. In this study, a marine object detection model was developed that combines a seawater identification algorithm using DBSCAN and a density-based land removal algorithm to rapidly analyze large data. When the developed detection model was applied to the hyperspectral image, the performance of analyzing a sea area of about 5 km² within 100 s was confirmed. In addition, to evaluate the detection accuracy of the developed model, hyperspectral images of the Mokpo, Gunsan, and Yeosu regions were taken using an aircraft. As a result, ships in the experimental image could be detected with an accuracy of 90 %. The technology developed in this study is expected to be utilized as important information to support the search and rescue activities of small ships and human life.