• Journal of IKEEE
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• v.24 no.4
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• pp.1069-1073
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• 2020

This paper presents the performance analysis of a long-range marine communication system developed for monitoring the fishing gears. LoRa based buoys were developed to monitor fishing gears. The buoy sends its coordinates along with other relevant information to the central monitoring station via a gateway. During the experiment, a up to 30 km of communication between a buoy and a gateway was successfully tested.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.7
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• pp.1026-1031
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• 2002

In this Paper, We analysed the technical characteristics of a automatic identification system that will introduce in aviation and marine radio stations. IMO's Marine Safety Committee approved revision of chapter V of the Safety of Life at Sea(SOLAS) Convention in 73rd meeting. According to this, AIS will become a mandatory carriage requirement by 01 July 2002. AIS as a surveillance system continuously receives its own position from the GNSS and then repeatedly broadcasts it on a W:.u data link for avoiding traffic conflicts and possible disasters. VHF data link is organized so that a specified number of time slots make up a repeatable frame. Each radio station can autonomously allocate and deallocate slots within the frame using selection algorithm which is called SOTDMA(Self-Organized Time Division Multiple Access). The results can be an aid in the continued of understanding technical characteristics for AIS as a broad surveillance system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.187-191
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• 2002

In this paper, We analysed the technical characteristics of a automatic identification system that will introduce in aviation and marine radio stations. IMO's Marine Safety Committee approved revision of chapter V of the Safety of Life at Sea(SOLAS) Convention in 73rd meeting. According to this, AIS will become a mandatory carriage requirement by 01 July 2002. AIS as a surveillance system continuously receives its own position from the GNSS and then repeatedly broadcasts it on a VHF data link for avoiding traffic conflicts and possible disasters. VHF data link is organized so that a specified number of time slots make up a repeatable frame. Each radio station can autonomously allocate and deallocate slots within the frame using selection algorithm which is called SOTDMA(Self-Organized Time Division Multiple Access). The results can be an aid in the continued of understanding technical characteristics for AIS as a broad surveillance system.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.322-330
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• 2021

In modern aquaculture, mass mortality is a very important issue that determines the success of aquaculture business. If a fish disease is not detected at an early stage in the farm, the disease spreads quickly because the farm is a closed environment. Therefore, early detection of diseases is crucial to prevent mass mortality of fish raised in farms. Recently deep learning-based automatic identification of fish diseases has been widely used, but there are many difficulties in identifying objects due to insufficient images of fish diseases. Therefore, this paper suggests a method to generate a large number of fish disease images by synthesizing normal images and disease images using SinGAN deep learning model in order to to solve the lack of fish disease images. We generate images from the three most frequently occurring Paralichthys Olivaceus diseases such as Scuticociliatida, Vibriosis, and Lymphocytosis and compare them with the original image. In this study, a total of 330 sheets of scutica disease, 110 sheets of vibrioemia, and 110 sheets of limphosis were made by synthesizing 10 disease patterns with 11 normal halibut images, and 1,320 images were produced by quadrupling the images.

• The Journal of the Acoustical Society of Korea
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• v.14 no.3
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• pp.71-81
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• 1995

In this paper, feature vector extraction methods and classification algorithms for the automatic classification of transient signals in underwater are discussed. A feature vector extraction method using wavelet transform, which shows good performance with small number of coefficients, is proposed and compared with the existing classical methods. For the automatic classification, artificial neural networks such as multilayer perceptron (MLP), radial basis function (RBF), and MLP-Class are utilized, where those neural networks as well as extracted feature vectors are combined to improve the performance and reliability of the proposed algorithm. It is confirmed by computer simulation with Traco's standard transient data set I and simulated data that the proposed feature vector extraction method and classification algorithm perform well, assuming that the energy of a given transient signal is sufficiently larger than that of a ambient noise, that there are the finite number of noise sources, and that there does not exist noise sources more than two simultaneously.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.11
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• pp.1063-1069
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• 2011

NCTR(Non-Cooperative Target Recognition) and ATR(Automatic Target Recognition) are methodologies to identify military targets using radar, optical, and infrared images. Among them, a strategy to recognize ground targets using synthetic aperature radar(SAR) images is called SAR ATR. In general, SAR ATR consists of three sequential stages: detection, discrimination and classification. In this paper, a modification of the polar mapping classifier(PMC) to identify inverse SAR(ISAR) images has been made in order to apply it to SAR ATR. In addition, a preprocessing scheme can mitigate the effect from the clutter, and information on the shadow is employed to improve the classification accuracy.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.73-75
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• 2022

본 논문에서는 자율운항선박의 예측 가능한 운항 경로 상에 잠재된 비상상황을 인식하기 위하여 운항 해역의 항적 정보를 활용한 방안과 이를 기반으로 충돌 위험과 같은 비상위험을 식별하는 프레임워크를 설계하였다. 설계한 프레임워크는 크게 항적 특성 분석 모듈, 항로예측 모듈, 위험 식별 모듈로 구성된다. 항적 특성 분석 모듈에서는 자율운항선박의 운항 해역에 관한 선박들의 항적 정보를 활용하기 위하여, 대상 VTS 관제 영역 내에서 취합된 누적 선박자동식별장치(AIS) 데이터를 이용하여 선박의 항적 특성을 분석하여 데이터베이스(DB)를 생성하였다. 그리고 운항 경로 예측 모듈에서는 누적된 항적 정보와 자율운항선박의 현재 운항 정보를 기반으로 특정 시간 동안의 운항 경로를 예측하기 위한 학습 네트워크 모델을 구성하였다. 마지막으로, 위험 식별 모듈에서는 예측한 운항 경로 상에 최근접점과 최근접점 거리 정보를 이용하여 충돌 위험 가능성이 있는 충돌위험영역을 식별하였다. 설계한 프레임워크는 자율운항선박의 육상 관제소에서 원격 제어를 통해 위험상황을 인지하고 회피할 수 있는 정보를 제공할 수 있음을 실제 항적 데이터를 활용하여 그 결과를 검증하였다.

• Review of KIISC
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• v.24 no.2
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• pp.56-62
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• 2014

최근 건조되고 있는 선박에는 안전 운항을 위하여 엔진제어시스템, 선박자동항법장치, 선박자동식별장치, CCTV 등의 전자장치들이 선박네트워크로 연결되어 있으며, 위성을 통하여 선박의 엔진상태 등의 선박 운항정보를 실시간으로 원격지에서 모니터링 할 수 있다. 선박의 내부와 외부통신 체계는 대체로 폐쇄적인 네트워크로 구성되어 있으나, 선박고유식별번호, 선박명, 선박종류, 항로, 목적항, 입항예정일, 화물종류 등의 선박의 주요 정보를 전송하는 선박자동식별장치는 무선 VHF로 전송되고, 선원은 개인용 컴퓨터를 이용하여 인터넷에 접속이 가능하기 때문에 선박 정보의 해킹 또는 바이러스에 취약해질 수 있다. 컴퓨터 바이러스 또는 해킹 등의 외부 칩입으로 인하여 선박항해시스템의 오류가 발생할 가능성이 높아지고 있다. 본 논문에서는 선박통합네트워크에서 제어네트워크의 표준화 동향과 정보보호 기술의 필요성에 대하여 기술한다.

• Journal of Advanced Navigation Technology
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• v.25 no.5
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• pp.397-402
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• 2021

The real-name electric fishing gear system is one of the important policy capable to build 'abundant fishing ground' and to protect marine environment. And, fishing gear automatic-identification system is one of IoT services that can implement above-mentioned policy by using communication such as low power wide area (LPWA) and multi-sensing techniques. Fishing gear automatic -identification system can gather the location data and lost/hold data from electric buoy floated in sea and can provide them to fishermen and monitoring center in land. We have developed the communication modules and electric buoy consisted of fishing gear automatic-identification system. In this paper, we report the test results of communication distance between electric buoy and wireless node installed in fish boat and location error of electric buoy. It is confirmed that line of sight (LOS) distance between electric buoy and wireless node is obtained to be 62 km, which is two times of the desired value, and location error is obtained to be CEP 1 m, which is smaller than the desired value of CEP 5 m. Therefore, it is expected that service area and accuracy of the developed fishing gear automatic-identification system is more extended.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.1
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• pp.63-68
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• 2018

Recently, safety accidents that occur in laboratories have occurred in various forms, so that a system that can reduce safety accidents in laboratories is required. The existing system identifies the danger situation according to the change of the temperature and the humidity, but the type of the danger situation is not known and the operation of the device is manually performed. Therefore, in this paper, we propose a system that identifies the danger situation of a reagent cabinet using multiple sensors and automatically operates the device. The internal environment of the reagent cabinet is measured in real time through the sensors and the sensor data is used to identify the danger situation. Also, when a danger situation is identified, the appropriate device is selected and operated automatically. In this way, identification of the danger situation of the reagent cabinet and automatic operation of the device will reduce the safety accidents occurring in the reagent cabinet.