• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.17-28
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• 2022

This study is to develop the direction of the development of the next-generation mapping of marine information required to develop a base of the utilization localization of maritime production tools. The GIS data-processing products and technologies currently used in the Korea's marine sector depend on external applications which is renewal costs, technical updates, and unreflected characteristics. Meanwhile, the S-100 standard, the next generation hydrographic data model that complements S-57's problems in marine GIS data processing, was adopted as a new marine data standard. This study aims to present the current status and problems of marine GIS technology in Korea and to suggest the development direction of GIS software based on the next generation hydrogrphic data model S-100 standard of IHO(International Hydrographic Organization). S-100-based marine GIS localization technology development and industrial ecosystem development research is expected to scientific decision-making on policy issues that occur with other countries such as marine territory management and development and use of marine resources.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2016.05a
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• pp.299-301
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• 2016

국제수로기구(IHO)는 수로데이터의 상호 운용성 확보 및 활용 증진을 위해 ISO 19100 지리공간 정보 표준을 수로분야로 확장하여 S-100(범용수로데이터모델) 표준을 개발하여 현재 2.0 버전에 이르고 있으며, S-101 차세대 전자해도 표준을 포함하여 전자서지 및 동적 수로정보 등의 다양한 표준을 개발 중이다. 한편, 국제해사기구는 e-Navigation 전략 추진을 위해 전략이행계획(SIP)를 개발하고, e-Nav 정보표준인 CMDS를 S-100 표준을 기반으로 개발하기로 결정 하였으며, 국제항로표지협회는 AtoN, IVEF, AIS-ASM, 측위 인프라에 관한 S-20X 표준개발을 진행하고 있다. 우리나라의 해양조사 및 수로도서지 간행을 담당하고 있는 국립해양조사원은 S-100 표준 기술을 확보하고 국가 수로국으로의 역할 수행을 위해 S-100 수로데이터를 구축할 계획으로 있다. 본 연구에서는 S-100/S-10X 표준개발 현황 및 우리나라의 차세대 전자해도 개발 계획을 검토하고, 해사안전, e-Navigation 및 VTS 분야 관점에서 시사점을 정리 하였다.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.418-420
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• 2020

해양에서의 선박사고 발생 횟수는 매년 꾸준히 증가하고 있다. 한국해양안전심판원에서는 이러한 사례들의 판결을 관련 인력들이 공유할 수 있도록 재결서를 제작하여 발간하고 있다. 그러나 선박사고는 2019년 기준 2,971건이 발생하여, 재결서만으로 관련 인력들이 다양한 사건들의 판례를 익히기엔 어려움이 따른다. 따라서 본 논문에서는 문장 표상 기법을 이용한 다중 작업 학습을 이용하여 선박사고의 사고 유형, 적용되는 법령, 형량을 분류 및 예측하는 실험을 진행하였다. USE, KorBERT 두 가지의 모델을 2010~2019년 재결서 데이터로 학습하여 선박사고의 사고 유형, 적용되는 법령, 형량을 분류 및 예측하였으며 그에 따른 정확도를 비교한 결과, KorBERT 문장 표상을 사용한 분류 모델이 가장 정확도가 높음을 확인했다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.7
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• pp.1305-1310
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• 2007

ePosition is a technology that can provide the spacial position of the earth to the information of ePosition ID through the Internet. It is serving the information of land location based on the Internet using the ePosition technology now, but it needs the service technique which can supply the marine data and the information of maritime position. Moreover, to support the information service of marine position, it needs the ENC linked technique based on S-57 that is an IHO transfer standard for digital hydrographic data. In this paper, therefore, it develops a linkage method for applying and utilizing the ePosition technology to ENC data, and supplements the base technology for applying it to marine related fields. As study method, firstly, this paper analyses ENC data model and structure, and converses for processing ENC file to ePosition data. Lastly, it derives the interconnection method with ePosition database and shows the ePosition service application based on the linked data and its validity.

• Proceedings of KOSOMES biannual meeting
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• 2007.11a
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• pp.193-195
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• 2007

해양생태계로 유입되는 화학물질의 총합적인 평가 및 관리를 위해서는 동 화합물의 해양환경중의 거동 및 운영, 생태계에의 영향, 관리방안에 따른 화학물질의 변화 예측 및 리스크 평가 등을 행할 필요가 있으며, 이를 위하여는 화학물질에 대한 생태계 모델이 유용한 수단이 될 수 있다. 본 연구에서는 여러 화학물질에 적용할 수 있으며, 지역특성, 존재 데이터 상황, 대상 수산물의 특성을 고려하여 여러 상태함수 및 프로세스의 추가와 삭제가 가능한 3차원 생태계 모델(EMT-3D)을 사용하여 해양환경중의 PFCs 관련물질을 대상으로 그 적용성을 검토하였으며, 민감도 분석 및 시나리오 분석을 행하여 영향인자를 판별하고 대안에 따른 영향을 평가하였다.

• The Journal of the Acoustical Society of Korea
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• v.28 no.8
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• pp.740-754
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• 2009

Sound in the ocean is scattered by inhomogeneities of many different kinds, such as the sea surface, the sea bottom, or the randomly distributed bubble layer and school of fish. The total sum of the scattered signals from these scatterers is called reverberation. In order to simulate the reverberation signal precisely, combination of a propagation model with proper scattering models, corresponding to each scattering mechanism, is required. In this article, we develop a reverberation model based on the ray theory easily combined with the existing scattering models. Developed reverberation model uses (1) Chapman-Harris empirical formula and APL-UW model/SSA model for the sea surface scattering. For the sea bottom scattering, it uses (2) Lambert's law and APL-UW model/SSA model. To verify our developed reverberation model, we compare our results with those in Ellis' article and 2006 reverberation workshop. This verified reverberation model SNURM is used to simulate reverberation signal for the neighboring seas of South Korea at mid frequency and the results from model are compared with experimental data in time domain. Through comparison between experiment data and model results, the features of reverberation signal dependent on environment of each sea is investigated and this analysis leads us to select an appropriate scattering function for each area of interest.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.716-717
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• 2017

In this paper, we propose a modeling approach for marine environment monitoring by leveraging open-source software to link IoT and Cloud together. The proposed model can be scale out by employing Apache Hadoop-based time-series database so that it can handle collected data increase with a resource pool of the same computers. It can also support the analyze monitored data of marine environment by visualizing collected data.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.179-180
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• 2020

해상교통을 모의하기 위해서는 주요 요소인 선박운항자의 인적요인에 대한 모델링 필요하며, 현실감 있는 해상교통 상황의 재현 및 예측을 위해 선박운항자 행동양식, 항해전문성, 항해오류 등을 모델링하여 반영하는 것이 필요하다. 본 발표에서는 에이전트 기반의 해상교통 시뮬레이션을 위해서 선박운항자의 충동회피를 위한 행동 분석를 수행했으며, 기초 데이터의 확보를 위해 설문조사를 실시하였다. 설문조사를 통해 분석된 정보를 이용하여 선박 충돌상황에서 선박운항자의 행동과 유사한 에이전트 기반의 항해행동 모델 개발현황을 소개하고자 한다.

• Proceedings of KOSOMES biannual meeting
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• 2017.04a
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• pp.244-244
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• 2017

Recently, A study is actively underway to apply to various industries, which are one of the major changes in the key drivers of the industry 4.0.. The data generated by the ship include various indicators such as the fuel volume, engine power, ground speed, speed, speed, main engine rpm, DFOC, SFOC, and FOC. This paper analyzes the sensitivity of the Gathering data and analyzes the impact energy efficiency of the vessel operation by analyzing the influence among each parameter, using the mathematical models, you create an surrogate model using the math model, comparative analysis of actual measurement data and predictive results were analyzed. Through the use of big data analysis technology, it is possible to identify the sensitivity between the energy efficiency related variables of the ship, The possibility of utilization of fuel efficiency indicators using of the surrogate model is identified.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.4
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• pp.721-732
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• 2024

Species identification of zooplankton is the most basic process in understanding the marine ecosystem and studying global warming. In this study, we propose an convolutional neural network model that can classify females and males of three zooplankton at the species level. First, training data including morphological features is constructed based on microscopic images acquired by researchers. In constructing training data, a data argumentation method that preserves morphological feature information of the target species is applied. Next, we propose a convolutional neural network model in which features can be learned from the constructed learning data. The proposed model minimized the information loss of training image in consideration of high resolution and minimized the number of learning parameters by using the global average polling layer instead of the fully connected layer. In addition, in order to present the generality of the proposed model, the performance was presented based on newly acquired data. Finally, through the visualization of the features extracted from the model, the key features of the classification model were presented.