• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.118-120
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• 2022

해양수산부와 산업통산자원부가 공동으로 추진하고 있는 자율운항선박 기술개발 프로젝트의 핵심기술은 지능항해시스템, 기관자동화시스템, 성능실증센터 및 실증기술, 운용기술 및 표준화로 나누어지며, 대한민국은 2025년까지 자율운항수준을 대양에서는 IMO Level 3, 연안에서는 IMO Level 2까지 달성하는 것을 목표로 하고 있다. 한편, 삼면이 바다로 둘러싸인 대한민국은 세계물류 이동의 거점임과 동시에 어선 등록 척수가 매년 6만 5년여 척이 넘는 어업이 활성화된 나라이며, 주요 어업 해역인 남해안은 대표적 무역항인 부산항, 광양항 등으로 통하는 항로와 중첩되기 때문에 자율운항선박의 원활한 운항을 위해서는 어업이라는 변수가 반드시 고려되어야 한다. 이 연구에서는 핵심기술 중 지능항해시스템 기술개발과 관련, 어업이 지능항해에 미칠 수 있는 영향을 어구, 어법, 어선으로 분류하여 고찰하였고, 발생 가능한 변수를 줄이기 위한 연구 방향을 제시하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.225-226
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• 2023

선박의 애플리케이션 간에 표준화 되지 않은 데이터를 교환하고 처리를 용이하기 위하여 데이터 구조를 통일화하는 통합 규칙이 필요하다. 이에 ISO 19848 표준안은 선박 내 데이터 교환 및 향후 선상 장비가 인터넷에 직접 연결될 수 있는 사항까지 고려하여 데이터 채널 ID를 Codebook에 따라 지정하도록 제안하고 있다. 우리나라는 '자율운항선박 기술개발'을 통하여 자율운항 시험선을 대상으로 데이터 분류 규칙과 표준화된 Codebook 개발을 진행하고 있으며 이를 한국산업표준 제정하기 위하여 표준화 작업을 진행하고 있다.

• Journal of Digital Convergence
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• v.14 no.7
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• pp.145-154
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• 2016

The purpose of this study was to carry out comparative analysis on the world major liner shipping companies' ship investment strategy using Fuzzy-AHP model. In this study, the ship investment factors were firstly selected by literature review and finally adopted them by in-depth interview with experts who had working experiences over 15 years in the field of shipping business. As suggested in the previous research, the liner shipping companies have been classified into four types such as 'ship investment irrelevant to market trend'(Type1), 'ship investment before market rise'(Type2), 'market decline after participation in excessive orders'(Type3), 'avoidance of ship investment during market rise'(Type4) and the comparative analysis were conducted among four ship investment types. According to the results of analysis, ship investment priority in Type1 was freight rates(0.132), price of used ship(0.121) and fleet(0.103). The priority in Type2 was freight rates(0.134), need for ship owner(0.113) and public funding(0.109). Type3 put its priority in freight rates(0.173), fleet(0.169) and the changes in international circumstances(0.121). Type4 considered freight rates(0.239), fleet(0.232) and oil price(0.150) as its priority.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.3
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• pp.235-239
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• 2016

The capsizing speed of an unstable vessel with a lost restoring moment can be understood as a unique response to an accident situation, and is naturally affected by such parameters as moment of inertia, metacentric height, and transverse damping coefficient of the hull in the case of free roll motion. Additionally, it is supposed that the analysis of capsize accidents can be further simplified when a vessel's leaning velocity is shown to be quite low. Therefore, capsize accidents with low leaning speeds are desirably categorized in view of rescuing strategies, as opposed to fast capsize accidents, since the attitude of the declining hull can be properly estimated, which allows rescuers to have more time for helping accident cases. This study focuses on deriving some analytical equations based on the roll decay ratio parameter, which describes how a hull under a low-speed capsize is related to the situational hull characteristics. The suggested equations are applied to a particular ship to disclose the analytical responses from the model ship. It was confirmed that the results show the general characteristics of slow capsizing ships.

• Journal of Korea Port Economic Association
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• v.28 no.4
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• pp.79-98
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• 2012

There is scant of research regarding the efficiency measurement of the ship management business. This paper aims to analyze the relative efficiency within the Korean Major Ship management corporations, to select the relatively low effective companies, and to suggest the improvement strategies for those. As a research methodology, Data Envelopment Analysis (DEA) applied to the top 20 corporations among Korean and Foreign Shipping Liners in Korea. To draw out the efficiency of targeted terminals, the number of ship managed is used as an input variables while, the number of crews and the total sales are utilized as an output variables. As a result. Haeyoung Maritime services is the most efficient corporations in Foreign Shipping Liners. Among Korean Shipping Liners, Panstar Shipping, Korea Lines, STX marine and Woolim Shipping are relatively efficient corporations which are scored BCC 1.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.43-50
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• 2007

Delay in the process of Information Extraction, IE, is largely due to inability to correctly recognize the user's information requirement of particular search factors. Especially if the wrapper rules are used in a search engine, the search generally fails to classify internet documents properly and efficiently since the application of the same wrapper rules lacks extensibility throughout various types of existing internet document. In case of buying or selling a ship, if the price range, type. place of delivery, inspection site and other information relevant to the sales would be available through the internet for proper retrieval the sales could more readily succeed by using Ontology relating to sales or purchase information and by selectively searching for the desired information through the content based retrieval system. This system proposes to improve various wrapper systems existing throughout different internet sites and to eliminate unnecessary information tagged on the existing internet documents in order to create a more advanced information retrieval system.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1463-1478
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• 2022

Maritime transport accounts for 99.7% of the exports and imports of the Republic of Korea; therefore, developing a vessel monitoring system for efficient operation is of significant interest. Several studies have focused on tracking and monitoring vessel movements based on automatic identification system (AIS) data; however, ships without AIS have limited monitoring and tracking ability. High-resolution optical satellite images can provide the missing layer of information in AIS-based monitoring systems because they can identify non-AIS vessels and small ships over a wide range. Therefore, it is necessary to investigate vessel monitoring and small vessel classification systems using high-resolution optical satellite images. This study examined the possibility of developing ship monitoring systems using Compact Advanced Satellite 500-1 (CAS500-1) satellite images by first training a deep learning model using satellite image data and then performing detection in other images. To determine the effectiveness of the proposed method, the learning data was acquired from ships in the Yellow Sea and its major ports, and the detection model was established using the You Only Look Once (YOLO) algorithm. The ship detection performance was evaluated for a domestic and an international port. The results obtained using the detection model in ships in the anchorage and berth areas were compared with the ship classification information obtained using AIS, and an accuracy of 85.5% and 70% was achieved using domestic and international classification models, respectively. The results indicate that high-resolution satellite images can be used in mooring ships for vessel monitoring. The developed approach can potentially be used in vessel tracking and monitoring systems at major ports around the world if the accuracy of the detection model is improved through continuous learning data construction.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.11a
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• pp.19-21
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• 2018

선원의 행동오류는 해양사고를 야기하는 하나의 직접적인 원인이기 때문에 이를 이해하는 것은 해양사고 예방에 근본이 된다. 선원의 행동오류를 이해하기 위해서는 행동오류를 추정하고 예측할 수 있어야 한다. 본 연구에서는 은닉 마르코브 모델(Hidden Markov Model, HMM)을 이용하여 선원들의 행동오류를 추정하고 예측하였다. 아울러 5가지 선박의 종류 각각에 나타나는 선원들의 행동오류를 서로 비교 분석하였다. 모델에 사용한 데이터는 해양안전심판원의 해양사고 보고서에 기록된 내용을 SRKBB(Skill-, Rule- and Knowledge-Based Behavior) 모델을 기반으로 분류하고 관측 수열을 생성하며 라벨링 작업을 통해서 구축하였다. 구축한 데이터를 적용하여 HMM을 보정하고 파라미터를 획득하여 선원들의 행동오류에 관한 모델을 구축하였다. 실험 결과, 선박 종류별로 선원들의 행동오류의 패턴은 서로 다르고, 이를 통해서 선박종류별 해기사들의 행동오류의 추정과 예측이 가능함을 일차적으로 확인할 수 있었다. 추후 본 연구를 지속 전개하여 해양사고 예방을 위한 인적오류의 저감에 기여할 수 있는 방안을 모색할 에정이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1202-1204
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• 2015

디지털 선박에서는 선박 내의 각종 센서로부터 측정된 디지털 데이터에 대한 정확하고 에너지 효율적인 관리가 필요하다. 본 논문에서는 디지털 선박 내에 다수 개의 센서(온도, 습도, 조도, 음성 센서)를 배치하고 효율적인 입력 스트림 처리를 위해서 슬라이딩 윈도우 기반으로 다중 Support Vector Machine(SVM) 알고리즘을 이용하여 사전 분류(pre-clustering)한 후 요약된 정보를 해쉬 테이블로 관리하는 효율적인 처리 기법을 제안한다. 해쉬 테이블을 이용하여 다차원 스트림 데이터의 저장될 레코드 순서를 빠르게 찾아 저장 및 검색함으로서 처리 속도가 향상되고 메모리에 해쉬 테이블 만을 유지하면 되므로 메모리 사용량이 감소한다. 35,912개의 데이터 집함을 사용하여 실험한 결과 제안 기법의 정확도와 처리 성능이 향상되었다.

• 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.