• Journal of Navigation and Port Research
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• v.29 no.1 s.97
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• pp.23-28
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• 2005

The signal in wireless multi-path channel is affected by fading and ISI because of high data rate transmission, so the signal has the high error rate. The present modulation and demodulation method of DSRC system can not expect sufficient for providing data service over 1 Mbps, so the channel equalization and advanced modulation and demodulation methods are required. OFDM is generally known as an effective technique for high data rate transmission system, since it can prevent ISI by inserting a guard interval. However, a guard interval longer than channel delay spread has to be used in each OFDM symbol period, thus resulting a considerable loss in the efficiency of channel utilization Therefore the equalizer is necessary to cancel ISI to accommodate advanced ITS service with higher bit rate and longer channel delay spread condition In this paper, the channel equalizer for the OFDM -DSRC system was designed and its performance in a multi-path fading environment was evaluated with computer simulation.

• Journal of Navigation and Port Research
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• v.34 no.10
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• pp.763-768
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• 2010

Today the light of mankind since the dawn of mankind and that they were living "lives" on the huge influence across space is a dynamic energy. Because of this, when all human beings with the light and you can feel more comfortable with a stable mind to the beauty and the pursuit of happiness is to have instincts. In this paper, a fuzzy control system using a combination of external environmental factors, respectively, the conversion of quantitative uncertainty information into the LED lighting is designed to express algorithms, available in indoor circadian control circuit was designed and fabricated LED. Factor in the external environment temperature, humidity, and light intensity values to the controller through the sensor to accept these values and the optimal values for lighting the fuzzy control algorithm is converted into human emotion to feel comfortable to express through the dimming control LED lighting.

• Journal of Navigation and Port Research
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• v.41 no.6
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• pp.381-388
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• 2017

Recently, renewed attention for technological applications within the maritime industry has taken place, particularly regarding unmanned vessels. There has been a lot of interest about the number of projects aiming at testing the operational feasibility of unmanned vessels, particularly in relation to technological, safety and security issues. Nevertheless, no studies have investigated this issue from the point of view of seafarers towards unmanned vessels; this paper aims at filling this gap. Data has been collected through a survey questionnaire. A Pearson correlational coefficient has been used to test the correlation between some of the variables. The results show that more than half of the respondents indicated that unmanned vessels do not contribute to an increase in accidents at sea. In addition, seafarers believe unmanned vessels will not be operational in the near future, with most of the respondents indicating a 10-20 year time frame. Thirdly, most of the respondents(both officers and ratings).

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.75-80
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• 2005

Because there are only a limited number of means of action that are available for the master to pursue in the event of flooding, onboard decision support system has been required The majority of systems activated during a flooding emergency (such as watertight and semi-watertight doors, bulkhead valves, dewatering pumps etc.) almost exclusively aim to restore a sufficiently high level of subdivision to prevent flooding from spreading through the ship. Even though assuming the flooding scenario is not catastrophic, the use of ballast tanks can be an additional and very effective tool to ensure both prevention of flooding spreading and also improve ship stability. This paper describes an optimization algorithm devised to choose the set of ballast tanks that should be filled in order to achieve an optimal response to a flooding accident.

• Journal of the Korea Society for Simulation
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• v.25 no.4
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• pp.127-135
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• 2016

Even thought modernized marine navigation devices help navigators, marine accidents has been often occurred and ship collision is one of the main types of the accidents. Various studies on the assessment method of collision risk have been reported, and studies using fuzzy theory are remarkable for the reason that reflect linguistic and ambiguous criteria for real situations. In these studies, collision risks were assessed on the assumption that the current state of navigation ship would be maintained. However, navigators ignore or turn off frequent alarms caused by the devices predicting collision risk, because they think that they can avoid the collisions in the most of situations. This paper proposes a model of predicting ship collision risk considering the general patterns of collision avoidance, and the approach is based on fuzzy inference and discrete event system specification (DEVS) formalism.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2020.11a
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• pp.54-55
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• 2020

In 4th Industrial Revolution, technologies such as artificial intelligence, Internet of Things, and Big data are closely related to the maritime industry, which led to the birth of autonomous vessels. Due to the technical characteristics of the current vessel, the speed cannot be suddenly lowered, so complex communication such as the help of a tug boat, boarding of a pilot, and control of the vessel at the onshore control center is required to berth at the port. In this study, clustering analysis was used to resolve how to establish control criteria for vessels to enter port when autonomous vessels are operating. K-Means clustering was used to quantitatively stage the arrival pattern based on the accumulated AIS(Automatic Identification System) data of the incoming vessel, and the arrival phase using SOG(Speed over Ground), COG(Course over Ground), and ROT(Rate of Turn) Was divided into six phase.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.110-110
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• 2022

본 연구는 자율운항 선박의 원격 고장 진단 기법 개발의 일부로 수행되었다. 특히, 엔진 연료 계통 장비로부터 계측된 시계열 데이터로부터 상태 진단을 위한 알고리즘 구현 결과를 제시하였다. 엔진 연료 펌프와 청정기를 가진 육상 실험 장비로부터 진동 시계열 데이터 계측하였으며, 이상 감지, 고장 분류 및 고장 예측이 가능한 심층 학습(Deep Learning) 및 기계 학습(Machine Learning) 알고리즘을 구현하였다. 육상 실험 장비에 고장 유형 별로 인위적인 고장을 발생시켜 특징적인 진동 신호를 계측하여, 인공 지능 학습에 이용하였다. 계측된 신호 데이터는 선행 발생한 사건의 신호가 후행 사건에 영향을 미치는 특성을 가지고 있으므로, 시계열에 내포된 고장 상태는 시간 간의 선후 종속성을 반영할 수 있는 학습 알고리즘을 제시하였다. 고장 사건의 시간 종속성을 반영할 수 있도록 순환(Recurrent) 계열의 RNN(Recurrent Neural Networks), LSTM(Long Short-Term Memory models)의 모델과 합성곱 연산 (Convolution Neural Network)을 기반으로 하는 Conv1D 모델을 적용하여 예측 정확성을 비교하였다. 특히, 합성곱 계열의 RNN LSTM 모델이 고차원의 순차적 자연어 언어 처리에 장점을 보이는 모델임을 착안하여, 신호의 시간 종속성을 학습에 반영할 수 있는 합성곱 계열의 Conv1 알고리즘을 고장 예측에 사용하였다. 또한 기계 학습 모델의 효율성을 감안하여 XGBoost를 추가로 적용하여 고장 예측을 시도하였다. 최종적으로 연료 펌프와 청정기의 진동 신호로부터 Conv1D 모델과 XGBoost 모델의 고장 예측 성능 결과를 비교하였다

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.204-205
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• 2023

This study studied a prediction model for sending collision alarms for small fishing boats based on semi-supervised learning(SSL). The supervised learning (SL) method requires a large number of labeled data, but the labeling process takes a lot of resources and time. This study used service data collected through a data pipeline linked to 'intelligent maritime traffic information service' and data collected from real-sea experiment. The model accuracy was improved as a result of learning not only real-sea experiment data with labeling determined based on actual user satisfaction but also service data without label determined together.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.104-105
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• 2023

해양 관측과 위성 원격탐사를 이용하여 시공간적으로 다양하게 변하는 생태 어장 환경 및 선박 관련 자료를 획득할 수 있다. 이번 연구의 주요 목적은 야간 불빛 위성 자료를 이용하여 광범위한 해역에 대한 어선의 위치 분포를 파악하는 딥러닝 기반 모델을 제안하는 것이다. 제안한 모델의 정확성을 평가하기 위해 야간 조업 어선의 위치를 포함하고 있는 AIS(Automatic Identification System) 정보와 상호 비교 평가 하였다. 이를 위해, 먼저 AIS 자료를 획득 및 분석하는 방법을 소개한다. 해양안전종합시스템(General Information Center on Maritime Safety & Security, GICOMS)으로부터 제공받은 AIS 자료는 동적정보와 정적정보로 나뉜다. 동적 정보는 일별 자료로 구분되어있으며, 이 정보에는 해상이동업무식별번호(Maritime Mobile Service Identity, MMSI), 선박의 시간, 위도, 경도, 속력(Speed over Ground, SOG), 실침로(Course over Ground, COG), 선수방향(Heading) 등이 포함되어 있다. 정적정보는 1개의 파일로 구성되어 있으며, 선박명, 선종 코드, IMO Number, 호출부호, 제원(DimA, DimB, DimC, Dim D), 홀수, 추정 톤수 등이 포함되어 있다. 이번 연구에서는 선박의 정보에서 어선의 정보를 추출하여 비교 자료로 사용하였으며, 위성 자료는 구름의 영향이 없는 깨끗한 날짜의 영상 자료를 선별하여 사용하였다. 야간 불빛 위성 자료, 구름 정보 등을 이용하여 야간 조업 어선의 불빛을 감지하는 심층신경망(Deep Neural Network; DNN) 기반 모델을 제안하였다. 본 연구의결과는 야간 어선의 분포를 감시하고 한반도 인근 어장을 보호하는데 기여할 것으로 기대된다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.362-365
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• 2022

With the development of the 4th industrial revolution technology, smartization in various fields is accelerating. The shipping and logistics industry is also promoting smartization by combining advanced new technologies such as digital twin, Internet of Things, and artificial intelligence. In Korea, the Ministry of Maritime Affairs and Fisheries is promoting a strategy to spread the smart shipping logistics system in line with the changing global shipping logistics trend, and through this, it is creating a foundation for smart shipping logistics. This study aims to present the concept of a communication tool that recognizes the importance of communication between each logistics entity and exchanges opinions between logistics entities in a virtual digital twin environment to cope with the changing shipping logistics process. In addition, for the development of these communication tools, this study derive a software design model, including architecture.