• Journal of Ecology and Environment
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• v.45 no.1
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• pp.10-16
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• 2021

Background: Ranavirus is an emerging infectious disease which has been linked to mass mortality events in various amphibian species. In this study, we document the first mass mortality event of an adult population of Dybowski's brown frogs (Rana dybowskii), in 2017, within a mountain valley in South Korea. Results: We confirmed the presence of ranavirus from all collected frogs (n = 22) via PCR and obtained the 500 bp major capsid protein (MCP) sequence from 13 individuals. The identified MCP sequence highly resembled Frog virus 3 (FV3) and was the same haplotype of a previously identified viral sequence collected from Huanren brown frog (R. huanrenensis) tadpoles in South Korea. Human habitat alteration, by recent erosion control works, may be partially responsible for this mass mortality event. Conclusion: We document the first mass mortality event in a wild Korean population of R. dybowskii. We also suggest, to determine if ranavirus infection is a threat to amphibians, government officials and researchers should develop continuous, country-wide, ranavirus monitoring programs of Korean amphibian populations.

• Nuclear Engineering and Technology
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• v.56 no.2
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• pp.558-567
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• 2024

Diagnostic support systems are being researched to assist operators in identifying and responding to abnormal events in a nuclear power plant. Most studies to date have considered single abnormal events only, for which it is relatively straightforward to obtain data to train the deep learning model of the diagnostic support system. However, cases in which multiple abnormal events occur must also be considered, for which obtaining training data becomes difficult due to the large number of combinations of possible abnormal events. This study proposes an approach to maintain diagnostic performance for multiple abnormal events by training a deep learning model with data on single abnormal events only. The proposed approach is applied to an existing algorithm that can perform feature selection and multi-label classification. We choose an extremely randomized trees classifier to select dedicated monitoring parameters for target abnormal events. In diagnosing each event occurrence independently, two-channel convolutional neural networks are employed as sub-models. The algorithm was tested in a case study with various scenarios, including single and multiple abnormal events. Results demonstrated that the proposed approach maintained diagnostic performance for 15 single abnormal events and significantly improved performance for 105 multiple abnormal events compared to the base model.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.341-344
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• 2004

발전소에서 운전 중인 발전 설비의 장비 및 기계의 동작, 감시, 진단은 매우 중요한 일이다. 발전소의 이상 감지를 위해 상태 모니터링이 사용되며, 이상이 발생되었을 때 고장의 원인을 분석하고 적절한 조치를 계획하기 위한 이상 진단 과정을 따르게 된다. 본 논문에서는 산업 현장에서 기기들의 운전시에 발생하는 기기 발생 음을 획득하여 정상/비정상을 판정하기 위한 알고리듬에 대하여 연구하였다. 사운드 감시(Sound Monitoring) 기술은 관측된 신호를 acoustic event로 분류하는 것과 분류된 이벤트를 정상 또는 비정상으로 구분하는 두 가지 과정으로 진행할 수 있다. 기존의 기술들은 주파수 분석과 패턴 인식의 방법으로 간단하게 적용되어 왔으며, 본 논문에서는 K-means clustering 알고리듬을 이용하여 사운드를 acoustic event로 분류하고 분류된 사운드를 정상 또는 비정상으로 구분하는 알고리듬을 개발하였다.

• Asian Journal of Atmospheric Environment
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• v.4 no.1
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• pp.20-25
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• 2010

The gaseous $^{222}Rn$ concentration at the level of clouds was estimated by using the wet scavenging model of its decay products with the observed data of environmental radiation at the ground. And the origin of the $^{222}Rn$ was also discussed. The estimation was done for a precipitation event on Dec. 26-27, 2003, when a large increase of the radiation was observed in Tokai-mura in Ibaraki, Japan. From a backward trajectory analysis, the origin of $^{222}Rn$ atoms for that event was traced back to the northeastern part of China, and it was expected that the large amount of $^{222}Rn$ emitted in the northeastern part of China was transported to Tokai-mura by the Eurasian continental air mass.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.141-142
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• 2006

In this paper, DSPOCS(Digital Switchgear Panel Operation and Control Solution) is designed, which is the intelligent inference operation and control solution of substation based on IED. DSPOCS is designed as a scheduled monitoring and control task and a real-time alarm inference task, and is interlinked with BRES in the required case. The intelligent alarm inference task consists of the alarm knowledge generation part and the real-time pattern matching part The alarm knowledge generation part generates automatically alarm knowledge from DB and saves it in alarm KB. On the other hand, the pattern matching part inferences the real-time event by comparing the real-time event information furnished from IEDs of substation with the patterns of the saved alarm knowledge base.

• Journal of Information Technology Applications and Management
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• v.27 no.6
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• pp.117-139
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• 2020

This research analyzes the factors that affect the consumers' participation of the internet-only banks, and suggests effective financial sales strategies and methods to attract more users. Through prior research review and interviews with experts, the factors affecting the consumers to sign up for the internet banks are identified. The actual user data from the internet banks are used for the analysis, providing more systematic and credible results. The research shows that social media buzz positively affects the user growth, proving Granger Causality relation of increasing social media buzz on K Bank increases K Bank users. The research also shows that marketing activities noticeably impacts K Bank's positive user growth. On the other hand, the event of Kakao Bank's grand opening shows negative effect. The results from the research validates the need for periodical monitoring process of social media buzz. Moreover, the research proves that the integrated analysis of social media buzz and marketing effect is also essential.

• Journal of Semiconductor Engineering
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• v.1 no.3
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• pp.81-87
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• 2020

An instrumentation amplifier (IA) and an analog-to-digital converter (ADC) are essential circuit blocks for accurate and robust sensor readout systems. This paper introduces recent advances in radiation-hardening by design (RHBD) techniques applied for the sensor readout integrated circuits (IC), e.g., the three-op-amp IA and the successive-approximation register (SAR) ADC, operating against total ionizing dose (TID) and singe event effect (SEE) in harsh radiation environments. The radiation-hardened IA utilized TID monitoring and adaptive reference control to compensate for transistor parameter variations due to radiation effects. The radiation-hardened SAR ADC adopts delay-based double-feedback flip-flops to prevent soft errors which flips the data bits. Radiation-hardened IA and ADC were verified through compact model simulation, and fabricated CMOS chips were measured in radiation facilities to confirm their radiation tolerance.

• Proceedings of the KSRS Conference
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• v.2
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• pp.856-859
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• 2006

In river with bar, the characteristics of its physical conditions have a close relationship with bar morphology. In this paper, a monitoring approach of bar transformation in the Han River Estuary is presented using RADARSAT/SAR Images. The estuary is divided into North and South Korea and its area is blocked by CCL(Civil Control Line). Satellite remote sensing, therefore, is uniquely suited to monitoring bar transformation. Based on SAR signatures for bars, bar transformation is investigated from 2000 to 2005, and monitoring of suspended-silt transportations from terrestrial runoff is tried to understand the morphology during the events of severe rain storm. SAR data did not reveal clearly the bar locations because of most of data acquisitions during high tides from 6.8 m to 9.0 m. Even though the problem, it could be said that in the estuary vegetated area and natural levees are developed well, but bars and shifted after an event like a flood. It is also showed that suspended solids such as silt transported through the estuary could contribute highly to a sedimentation environment around Incheon.

• Journal of Radiation Protection and Research
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• v.19 no.2
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• pp.147-156
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• 1994

On-line gamma monitoring system around KAERI-site was set up to monitor the radiation fluctuations in environment. Data on gamma exposure rates measured by the ionication chamber in the monitoring posts are transmitted to a computer of central control station with. radio telemetry transmission modem and monitored in real time. Radio telemetry transmission system is economical and reliable on handling and storing of data. This monitroing system can triger an early warning system in the event of abnormal radiation levels.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.25 no.8
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• pp.553-558
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• 2015

This paper aims at making a dedicated vibration monitoring and diagnosis framework for 3MW WTG(wind turbine generator). Within the scope of the research, vibration data of WTG drive train are used and WTG operating conditions are involved for dividing the vibration data class which included transient and steady state vibration signals. We separate two health detections which are CHD(continuous health detection) and EHD(event health detection). CHD has function of early detection and continuous monitoring. EHD makes the use of finding vibration values of fault components effectively by spectrum matrix subsystem. We proposed framework and showed application for 3MW WTG in a practical point of view.