• Proceedings of the Korean Radioactive Waste Society Conference
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• 2005.11b
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• pp.149-155
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• 2005

The $ACP^1$ is under development for effective management of spent fuel by converting $UO_2$ into U-metal. For demonstration of this process, $\alpha-\gamma$ type new hotcell was built in the $IMEF^2$ basement. To secure against radiation hazard, this facility needs radiation monitoring system which will observe the entire operating area before the hotcell and service area at back of it. This system consists of 7 parts; Area Monitor for $\gamma$-ray, Room Air Monitor for particulate and iodine in both area, Hotcell Monitor for hotcell inside high radiation and rear door interlock, Duct Monitor for particulate of outlet ventilation, Iodine Monitor for iodine of outlet duct, CCTV for watching workers and material movement, Server for management of whole monitoring system. After installation and test of this, radiation monitoring system will be expected to assist the successful ACP demonstration.

• Journal of Navigation and Port Research
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• v.33 no.9
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• pp.609-614
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• 2009

The traffic of tug/barges which are carrying construction materials, large plants for harbor development, or offshore structures has recently increased in the coast of Korea. The west and south coast of Korea are always congested due to a lot of islands and traffic concentration. Specially tug/barges have higher probability of marine accidents due to their bad maneuverability than others. Considering the operational circumstance and maneuverability, this study was to develop a wide-area monitoring and control system for tug/barges in the coastal area of Korea. The system was made in the form of three program modules i.e. navigation analysis program module, monitoring and control program module, database module. And seven functions were programmed to monitor and control the tug/barges efficiently. These are ship information search, tug/barge information and track management, designated area and safe navigation zone management, fairway management, accident data management, warning of danger, safety information management.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.1-10
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• 2018

Wide-area monitoring of tree-related high impedance fault (THIF) efficiently contributes to increase reliability of large-scaled network, since the failure to early location of them may results in critical lines tripping and consequently large blackouts. In the first place, this wide-area monitoring of THIF requires managing the placement of sensors across large power grid network according to THIF detection objective. For this purpose, current paper presents a framework in which sensors are distributed according to a predetermined risk map. The proposed risk map determines the possibility of THIF occurrence on every branch in a power network, based on electrical conductivity of trees and their positions to power lines which extracted from spectral data. The obtained possibility value can be considered as a weight coefficient assigned to each branch in sensor placement problem. The next step after sensors deployment is to on-line monitor based on moving data window. In this on-line process, the received data window is evaluated for obtaining a correlation between low frequency and high frequency components of signal. If obtained correlation follows a specified pattern, received signal is considered as a THIF. Thereafter, if several faulted section candidates are found by deployed sensors, the most likely location is chosen from the list of candidates based on predetermined THIF risk map.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.776-785
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• 2011

Since the Internet-based real-time Global Positioning System(GPS) synchronized widearea power system frequency monitoring network (FNET) was proposed in 2001, it has been monitoring the power system frequency in interconnected United States power systems and numerous interesting behaviors have been observed, including frequency excursion propagation. We address the consistency of a frequency excursion detection order of frequency disturbance recorders in FNET in relation to the same generation trip, as well as the ability to recreate by power systems dynamic simulation. We also propose a new method, as an application of FNET measurement, to locate a tripped generator using power systems dynamic simulation and wide-area frequency measurement. The simulation database of all the possible trips of generators in the interconnected power systems is created using the off-line power systems dynamic simulation. When FNET detects a sudden drop in the monitoring frequency, which is most likely due to a generation trip in power systems, the proposed algorithm locates a tripped generator by finding the best matching case of the measured frequency excursion in the simulation database in terms of the frequency drop detection order and the time of monitoring points.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.838-844
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• 2012

This paper proposes the effective monitoring method for marine engine system, which is implemented based upon Controller Area Network (CAN). As the marine engine monitoring system requires various kind of information, a lot of sensor nodes are distributed to several places. The CAN supports huge numbers of message IDs for the sensor nodes and provides a stable communication channel in a wide area such as a 12,000 TEU container ship. Since the CAN is priority-based communication system, some of hard real-time messages like alarm messages which are time-critical to the operation of the vessel cannot be communicated within the dead-time. Therefore it is desirable to distinguish the bandwidth of the CAN for static state messages and transition-state messages not to be harmful to the engine operations. Using the features of message arbitration ability of the CAN, it is proposed in this paper that the bandwidth allocation is dynamically adjusted to cope with the increment of input signal to improve the performance of monitoring system. Effectiveness and validity of the proposed scheme have been demonstrated through real experiments.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.153-153
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• 2012

Endpoint detection with plasma impedance monitoring and self-plasma optical emission spectroscopy is demonstrated for dielectric layers etching processes. For in-situ detecting endpoint, optical-emission spectroscopy (OES) is used for in-situ endpoint detection for plasma etching. However, the sensitivity of OES is decreased if polymer is deposited on viewport or the proportion of exposed area on the wafer is too small. To overcome these problems, the endpoint was determined by impedance signal variation from I-V monitoring (VI probe) and self-plasma optical emission spectroscopy. In addition, modified principal component analysis was applied to enhance sensitivity for small area etching. As a result, the sensitivity of this method is increased about twice better than that of OES. From plasma impedance monitoring and self-plasma optical emission spectroscopy, properties of plasma and chamber are analyzed, and real-time endpoint detection is achieved.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.6
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• pp.89-96
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• 2021

In this study, a deep-learning image analysis model was established and validated for AI-based monitoring of the tidal flat ecosystem for marine protected creatures Ocypode stimpsoni and their habitat. The data in the study was constructed using an unmanned aerial vehicle, and the U-net model was applied for the deep learning model. The accuracy of deep learning model learning results was about 0.76 and about 0.8 each for the Ocypode stimpsoni and their burrow whose accuracy was higher. Analyzing the distribution of crabs and burrows by putting orthomosaic images of the entire study area to the learned deep learning model, it was confirmed that 1,943 Ocypode stimpsoni and 2,807 burrow were distributed in the study area. Through this study, the possibility of using the deep learning image analysis technology for monitoring the tidal ecosystem was confirmed. And it is expected that it can be used in the tidal ecosystem monitoring field by expanding the monitoring sites and target species in the future.

• Journal of Wetlands Research
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• v.19 no.4
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• pp.515-522
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• 2017

This study investigated the runoff characteristics containing NPS pollutants in urban areas and estimated the optimal number of storm events to be monitored. 13 residential areas, 8 commercial areas, 9 transportation areas and 11 industrial areas were selected to be monitored located in urban areas. Monitoring was performed from 2008 to 2016 with a total of 632 rainfall events. As a result, it was found that commercial area needs priority NPS management compared to other landuses because the commercial area has high runoff coefficient and NPS pollutant EMC compared with other landuses. The annual monitoring frequency for each landuse was estimated to be 11 to 14 times for industrial area, 12 to 14 times for transportation area, 11 to 13 times for commercial area and 22 to 25 times for residential area. Even with the use of accumulated monitoring data for several years, there is still high probability of uncertainty due to high error in some pollutant items, and it is necessary to establish monitoring know-how and data accumulation to reduce errors by continuous monitoring.

• Journal of the Korean earth science society
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• v.31 no.5
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• pp.465-474
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• 2010

Real-time rainfall monitoring is of great practical importance over the highly populated Indochina area, which is prone to natural disasters, in particular in association with rainfall. With the goal of d etermining near real-time half-hourlyrain estimates from satellite, the three-layer, artificial neural networks (ANN) approach was used to train the brightness temperatures at 6.7, 11, and $12-{\mu}m$ channels of the Japanese geostationary satellite MTSAT against passive microwavebased rain rates from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and TRMM Precipitation Radar (PR) data for the June-September 2005 period. The developed model was applied to the MTSAT data for the June-September 2006 period. The results demonstrate that the developed algorithm is comparable to the PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks) results and can be used for flood monitoring across the Indochina area on a half-hourly time scale.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.302-303
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• 2011

Smart WAMAC (Wide Area Monitoring And Control) System, which supplements control function with the function of WAMS(Wide Area Monitoring System), is an intelligent system not only monitoring the wide area but controlling the power equipment according to defined procedure. This paper presents WAMAC system architecture for hierarchical Infra and considerations to design and implement.