• Journal of Ocean Engineering and Technology
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• v.24 no.1
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• pp.178-184
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• 2010

Today, there has been a decrease in international shipping because of the weakening in global economies. Therefore, shipowners are thinking more about Floating Production Storage and Offloading (FPSO), which can perform functions related to the transporting, storage, and tracking of crude oil from oil wells. Given the huge expense of these special ships, shipowners require workers who can solve problems quickly and secure sustainable production functions in this age of globalization. Furthermore, it is important to design, construct, and maintain facilities so that a ship remains in operation over a long term. This paper discusses a system that uses knowledge-based AR to help workers improve their understanding and deal with pipeline equipment problems safely. In addition, it displays a 3CAD model and status information for products to improve their recognition on the FPSO that they intend to inspect. At the same time, the system works quickly and offers solutions for dangerous circumstances or malfunctions. It thus helps to maintain the functionality of the FPSO throughout its life-cycle.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.4 no.1
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• pp.18-24
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• 1999

The satellite image acquired by RADARSAT SAR on August 15, 1996 reveals internal waves in north coastal waters of Cheju Island. It is indicated from the image data, the tidal elevation data, and the bottom topography data, the internal waves seem to be generated by interaction between shallow bottom and tidal currents travelling in the stratified water in the summer time during the tidal changeovers from ebb to flood. The internal waves generated in such condition show patterns of trains of solitons. Probable amplitude of observed solitons is calculated using estimation of the soliton wave length from SAR image data and K-dV equation. Detection of the internal waves is very significant not only to military strategist for underwater maneuvers such as operation of submarines, but also to physical and biological oceanographers. Temporal and spatial variation of the internal waves are needed to be measured by simultaneous in-situ field study together with SAR to examine the nature of these internal waves.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6B
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• pp.859-866
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• 2010

Digital vessels can occur large a disaster at sea because vessels in fire and collision in case of certain unforeseen circumstances. In this paper, We propose digital vessel context monitoring system through risk analysis. We propose environment information analysis system using wireless sensor that have to acquire marine environment and context of marine digital vessel. For conducting simulation, we chose 300 data sets to train the neural network. As a result, we obtained about 96% accuracy for fire risk context and we obtained 88.7% accuracy for body of vessel risk context. To improve the accuracy of the system, we implement a FEC (Forward Error Correction) block. We implemented digital vessel context monitoring system that transmitted to diagnosis result in CDMA.

• Smart Media Journal
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• v.5 no.1
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• pp.130-136
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• 2016

In this paper, the real time monitoring system for the abnormal state of marine algae does not detect the plankton which may directly cause the red tide or the water bloom. But checks both oxygen reduction and nitrogen reduction in water, which indicates the characteristics of zooplankton and phytoplankton respectively, and this system makes a module that monitors in real time the temperature and the illumination of the water, which are indirect factors, with sensors placed in and outside the water, and this module transmits signals periodically at specific intervals to a sever that builds up data base, and the data collected in these ways will be analyzed and compared with the standard data from Ministry of Oceans and Fisheries, and then these data will be made the adequate form of information to be provided to the users as visual information, thus, this system intends to make a red tide and water bloom monitoring system tailored for individual fish farm businesses that has local characteristics and can quickly operate outside working hours, which differs from the existing wide area detecting and monitoring systems.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.8 no.2
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• pp.132-137
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• 2003

Observations of internal waves in the southwest coastal waters of Korea have been made using a mooring measurement and satellite SAR together. From May 28 to May 30 in 2002, thermistor chains with RCM and ADCP mooring measurements were carried out at 10 kin west of Ocheong-Do, together with a CTD field sur-vey on the surrounding waters. Also, a SAR image was acquired on May 29 at 06:53. The data from the in-situ measurement show several internal wave packets passing through the mooring point and the SAR image reveals numbers of internal wave packets distributed around the point. Temporal and spatial characteristics of internal waves in the southwest coastal waters were analyzed using the data from mooring measurement, SAR image, and the K-dv equation. The internal waves are important phenomena in terms of physical oceanography and military as well as marine biology. They should be considered as one of important features in the southwest coastal waters in summer.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.127-134
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• 2021

In this study, an anomaly detection (AD) algorithm was implemented to detect the failure of a marine air compressor. A lab-scale experiment was designed to produce fault datasets (time-series electric current measurements) for 10 failure modes of the air compressor. The results demonstrated that the temporal pattern of the datasets showed periodicity with a different period, depending on the failure mode. An AD model with a convolutional autoencoder was developed and trained based on a normal operation dataset. The reconstruction error was used as the threshold for AD. The reconstruction error was noted to be dependent on the AD model and hyperparameter tuning. The AD model was applied to the synthetic dataset, which comprised both normal and abnormal conditions of the air compressor for validation. The AD model exhibited good detection performance on anomalies showing periodicity but poor performance on anomalies resulting from subtle load changes in the motor.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.111-119
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• 2024

In this paper, we propose a big data platform that can collect information from various sources collected at ocean. Currently operating ocean-related big data platforms are focused on storing and sharing created data, and each data provider is responsible for data collection and preprocessing. There are high costs and inefficiencies in collecting and integrating data in a marine environment using communication networks that are poor compared to those on land, making it difficult to implement related infrastructure. In particular, in fields that require real-time data collection and analysis, such as weather information, radar and sensor data, a number of issues must be considered compared to land-based systems, such as data security, characteristics of organizations and ships, and data collection costs, in addition to communication network issues. First, this paper defines these problems and presents solutions. In order to design a big data platform that reflects this, we first propose a data source, hierarchical MEC, and data flow structure, and then present an overall platform structure that integrates them all.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.79-88
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• 2009

The objective of this study is to develop the new vehicle classification algorithm and minimize classification errors. The existing vehicle classification algorithm collects data from loop and piezo sensors according to the specification("Vehicle classification guide for traffic volume survey" 2006) given by the Ministry of Land, Transport and Maritime Affairs. The new vehicle classification system collects the vehicle length, distance between axles, axle type, wheel-base and tire type to minimize classification error. The main difference of new system is the "Wandering" sensor which is capable of measuring the wheel-base and tire type(single or dual). The wandering sensor obtains the wheel-base and tire type by detecting both left and right tire imprint. Verification tests were completed with the total traffic volume of 762,420 vehicles in a month for the new vehicle classification algorithm. Among them, 47 vehicles(0.006%) were not classified within 12 vehicle types. This results proves very high level of classification accuracy for the new system. Using the new vehicle classification algorithm will improve the accuracy and it can be broadly applicable to the road planning, design, and management. It can also upgrade the level of traffic research for the road and transportation infrastructure.

• Journal of IKEEE
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• v.23 no.2
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• pp.743-746
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• 2019

In this paper we proposed a new ocean radiation automatic monitoring system. The proposed system has the following characteristics: First, using NaI + PVT mixed detectors, the response speed is fast and precision analysis is possible. Second, the application of temperature compensation algorithm to scintillator-type sensors does not require additional cooling devices and enables stable operation in the changing ocean environment. Third, since cooling system is not needed, electricity consumption is low, and electricity can be supplied reliably by utilizing solar energy, which can be installed at the observation deck of ocean environment. Fourth, using GPS and wireless communications, accurate location information and real-time data transmission function for measurement areas enables immediate warning response in the event of nuclear accidents such as those involving neighboring countries. The results tested by the authorized testing agency to assess the performance of the proposed system were measured in the range of $5{\mu}Sv/h$ to 15mSv/h, which is the highest level in the world, and the accuracy was determined to be ${\pm}8.1%$, making normal operation below the international standard ${\pm}15%$. The internal environmental grade (waterproof) was achieved, and the rate of variation was measured within 5% at operating temperature of $-20^{\circ}C$ to $50^{\circ}C$ and stability was verified. Since the measured value change rate was measured within 10% after the vibration test, it was confirmed that there will be no change in the measured value due to vibration in the ocean environment caused by waves.

• Journal of the Korean earth science society
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• v.42 no.6
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• pp.623-631
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• 2021

The increased transport of marine hazardous and noxious substances (HNS) has resulted in frequent HNS spill accidents domestically and internationally. There are about 6,000 species of HNS internationally, and most of them have toxic properties. When an accidental HNS spill occurs, it can destroys the marine ecosystem and can damage life and property due to explosion and fire. Constructing a spectral library of HNS according to wavelength and developing a detection algorithm would help prepare for accidents. In this study, a ground HNS spill experiment was conducted in France. The toluene spectrum was determined through hyperspectral sensor measurements. HNS present in the hyperspectral images were detected by applying the spectral mixture algorithm. Preprocessing principal component analysis (PCA) removed noise and performed dimensional compression. The endmember spectra of toluene and seawater were extracted through the N-FINDR technique. By calculating the abundance fraction of toluene and seawater based on the spectrum, the detection accuracy of HNS in all pixels was presented as a probability. The probability was compared with radiance images at a wavelength of 418.15 nm to select abundance fractions with maximum detection accuracy. The accuracy exceeded 99% at a ratio of approximately 42%. Response to marine spills of HNS are presently impeded by the restricted access to the site because of high risk of exposure to toxic compounds. The present experimental and detection results could help estimate the area of contamination with HNS based on hyperspectral remote sensing.