• Journal of IKEEE
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• v.13 no.2
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• pp.248-252
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• 2009

In this paper, analysis of a noise factor and an effective power strategy for the OLED dc-dc converter are described. One of the main reasons that one may not design the OLED power for dc-dc converter is that OLED's panel noise is composed of FFN(Frame Frequency Noise) and LFN(Line Frequency Noise). Into the bargain, FFN is caused by both the dc-dc (circuit) and driving circuit. It is hard to get rid of FFN, baeause FFN has very little results value for our ears. LFN is adjusted by analog compensation value. Actually, that is more important problem than FFN. It is known that voltage divider for OLED's mode variation is not good for compact power design. In the end, a circuit design for understanding OLED's noise and a novel muti-channel dc-dc converter were presented.

• Journal of fish pathology
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• v.24 no.2
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• pp.47-51
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• 2011

The present study demonstrated lymphocystis disease virus (LCDV) propagation through cytopathic effects (CPE) formation and LCDV detection in olive flounder fin (FFN) cells by polymerase chain reaction (PCR) and fluorescent antibody technique (FAT) methods. Tissue filtrates from the cluster cells produced CPE in FFN cells, which initially cells became enlarged and gradually underwent fusion en masse. Infectivity of culture grown LCDV using the FFN cells reached $10^{2.3}$ $TCID_{50}$/ml at 4 days post infection and the highest titer was measured $10^{6.5}$ $TCID_{50}$/ml at 12 days. The viral DNA was detected in the cell culture supernatants showing CPE and the CPE cells by PCR. Antigen specific strong fluorescence reacting with monoclonal antibody against the virus revealed the presence of viral antigen in the cytoplasm of infected FFN cells. These results suggest that the FFN cell line originated from the olive flounder has a susceptibility of the LCDV.

• Korean Journal of Veterinary Research
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• v.38 no.3
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• pp.581-588
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• 1998

Eight monoclonal antibodies(MAbs) against bovine coronavirus(BCV) were produced and characterized. Three MAbs(1G9, 4H12, 5C1) specific to the S glycoprotein and two HE glycoprotein-specific MAbs(2A5, 5G4) were found to neutralize the BCV in fluorescence focus neutralization(FFN) test. Two HE-specific MAbs from the neutralizing MAbs inhibited the hemagglutinating activity of the BCV. None of the N protein-specific MAbs(1C1, 5A12, 6H1) neutralized the virus infectivity. Bovine coronavirus and mouse hepatitis virus, which belong to group II coronaviruses, were differentiated from other groups of coronaviruses(porcine transmissible gastroenteritis virus, porcine epidemic diarrhea virus, canine coronavirus) by all MAbs in fluorescence antibody test(FA), but not in FFN test.

• Korean Journal of Veterinary Research
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• v.36 no.2
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• pp.395-403
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• 1996

Monoclonal antibodies(MAbs) against field isolates of the bovine rotavirus A strain(G6), V strain(G10) and reference I-801 strain(G8) were produced and characterized. Six MAbs(4C2, 4D9, 5E1, 5E7, 5D5, 3E4) against A strain had neutralizing activity and reacted only with the G6 bovine rotaviruses determined by fluorescence focus neutralization (FFN) test. Otherwise, five neutralizing MAbs(1G2, 2G6, 5E2, 5E12, 5H7) against I-801 strain neutralized the G6 and G8 bovine rotaviruses. Five non-neutralizing MAbs(5F12, 7F12, 5E11, 2A11, 2B12) were VP6-specific and cross-reacted with all bovine and porcine rotaviruses examined by fluorescence antibody(FA) test. None of the MAbs reacted with bovie viral diarrhea virus(BVDV) and bovine coronavirus(BCV) determined by FA and FFN test.

• Korean Journal of Community Nutrition
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• v.1 no.1
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• pp.47-60
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• 1996

This study was carried out to investigate growth performance, energy and protein metabolism of breast and formula fed infants from birth to 3 months postpartum. There were four groups : breast fed(BF) and three formula fed groups(FFM, FFN and FFP). There was no significant difference in the height of infants according to feeding method and formula brands. However, mean weight of FFM was significantly higher than that of FFP and BF at 1 and 3 months postpartum, respectively. Mean head circumference of FFN was lowest among groups. The average intake of breast milk was $781.4{\;}{pm}{\;}119.3m{\ell}/day$ and that of formula was $848.6{\;}{pm}{\;}118.5m{\ell}/day$. Mean apparent digestible energy intakes of formula-fed infants and breast-fed infants during 3months were 568.9 $\pm$146.9 kca1/day and 657.9$\pm$212.8 kca1/day, respectively. The average protein intake of brest-fed and formula-fed infants were 8.3$\pm$1.6g/day and 14.1$\pm$14.1 g/day, respectively. The protein intakes of formula-fed infants were significantly higher than those of breast-fed infants at 1, 2, 3 months. The apparent protein digestibility of breast-fed infants was singnificantly higher compared to formula fed infant. These data suggest that RDA for infants be established and breast feeding be encouraged.

• Structural Engineering and Mechanics
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• v.58 no.3
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• pp.459-473
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• 2016

Various vague and unstructured problems encountered the civil engineering/designers that persuaded by their experiences. One of these problems is the structural failure of the reinforced concrete (RC) building determination. Typically, using the traditional Limit state method is time consuming and complex in designing structures that are optimized in terms of one/many parameters. Recent research has revealed the Artificial Neural Networks potentiality in solving various real life problems. Thus, the current work employed the Multilayer Perceptron Feed-Forward Network (MLP-FFN) classifier to tackle the problem of predicting structural failure of multistoried reinforced concrete buildings via detecting the failure possibility of the multistoried RC building structure in the future. In order to evaluate the proposed method performance, a database of 257 multistoried buildings RC structures has been constructed by professional engineers, from which 150 RC structures were used. From the structural design, fifteen features have been extracted, where nine features of them have been selected to perform the classification process. Various performance measures have been calculated to evaluate the proposed model. The experimental results established satisfactory performance of the proposed model.

• Journal of Environmental Impact Assessment
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• v.18 no.5
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• pp.271-280
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• 2009

The objective of this study is to develop a reliable flow forecasting model based on neural network algorithm in order to provide flow rate at stream sections without flow measurement in Nakdong river. Stream flow rate measured at 8-days interval by Nakdong river environment research center, daily upper dam discharge and precipitation data connecting upstream stage gauge were used in this development. Back propagation neural network and multi-layer with hidden layer that exists between input and output layer are used in model learning and constructing, respectively. Model calibration and verification is conducted based on observed data from 3 station in Nakdong river.

• Economic and Environmental Geology
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• v.53 no.1
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• pp.99-110
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• 2020

It is a global trend to consider contaminated low-permeability zones as one of the primary management targets for the remediation of DNAPL contaminated sites. In addition, studies on the persistence caused by back diffusion of DNAPLs from low-permeability zones have been actively conducted worldwide. On the other hand, the studies for domestic groundwater contamination with the low-permeability zones are insufficient. Therefore, this study introduces the forward and back diffusions of DNAPL through low-permeability zones and suggests the importance of them by reviewing representative previous studies, especially on back diffusion and plume persistence. We proposed six diffusion scenarios and analytical solutions based on various boundary conditions of low-permeability zones. FI (forward diffusion into infinite domain) and BI (back diffusion form infinite domain) scenarios illustrate forward and back diffusion in which the depths of a low-permeability layer are assumed to be infinite. FFN (forward diffusion into finite domain with no flux boundary) and BFN (back diffusion from finite domain with no flux boundary) scenarios describe forward and back diffusion for a finite domain of a low-permeability layer with no flux boundary at the bottom. When the bottom of a low-permeability layer is considered as flux boundary, forward and back diffusion scenarios correspond to FFF (forward diffusion into finite domain with flux boundary) and BFF (back diffusion from finite domain with flux boundary). The scenarios and analytical solutions in this study may contribute to the determination of an efficient remediation method based on site characteristics such as a thickness of low-permeability zones or duration of contamination exposure.

• Journal of fish pathology
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• v.23 no.3
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• pp.335-342
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• 2010

In 2008, mass mortality was observed in paradise fish Macropodus opercularis which was imported from Indonesia. PCR of these fish found positive for megalocytivirus and Mycobacterium sp., while an unidentified virus was culture-isolated using CHSE-214 cells. In the present study, we investigated characterization of the unidentified virus and its pathogenicity to determine whether the virus was the causative agent of the mass mortality of paradise fish. The unidentified virus induced cytopathic effect (CPE) with syncytia in CHSE-214 and other fish cells, BF-2, GF, SSN-1, FSP and FFN. The virus was resistant against treatments with IUdR, chloroform, acidity at pH 3, basicity at pH 11 and high temperature at $56^{\circ}C$ for 3h. By electron microscopy, the viral particles were spherical having a double capsid structure with approximately 65 nm in external diameter. Viral genome was composed of at least 10-segmented RNA with sizes ranging from 0.7 kb to 3.6 kb. Based on these characters, this virus can be classified into family Reoviridae. This reovirus did not cause any mortality in an artificial experiment conducted by injecting the virus to paradise fish. This indicates that the reovirus is not only responsible for the mass mortality of paradise fish in 2008.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.314-318
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• 2009

본 연구의 목적은 강우-유출자료 및 댐 방류량 자료의 비선형적인 특정을 가장 잘 반영할 수 있는 신경망모형을 적용하여 수질정책의 기초자료를 제공하기 위하여 신뢰성 있는 유량자료를 산정하는 모형을 개발하였고 이를 낙동강 유역에 적용하는 것이다. 이를 위해서 낙동강물환경연구소의 8일 측정 유량이 가지는 정확성을 이용하면서 상류 댐의 일 방류량자료와 유역별 강우자료 및 국토해양부 수위관측소의 수위자료를 연계하여 유량을 보간할 수 있는 유량 보간 신경망 모형을 개발하였다. 신경망 모형의 출력값은 낙동강물환경 연구소에서 측정하지 않은 기간에 대하여 유량을 보간할 수 있도록 구성하였으며 신경망 모형의 구조는 입력층과 출력층 사이에 하나의 은닉층이 존재하는 다층 신경망으로 구성하였으며, 학습단계에서는 오류 역전파 알고리듬 학습방법 중 모멘텀법을 사용하였다. 본 연구를 통하여 낙동강 전 유역에 대하여 유량 보간 모형을 적용한 결과 댐 방류량과 강우자료 및 상류 수위 관측소의 유량 자료를 이용한 유량 보간 신경망모형의 일 유량결과의 적용가능성을 검증할 수 있으며, 제시된 모형은 지속적인 수문자료의 질적 향상과 유출패턴의 축적으로 그 성능을 향상시킬 수 있을 것이며 또한 홍수기의 더 정확한 유량예측을 위한 적용사례의 확장 및 SWAT을 이용한 모형의 적용에 대한 연구가 병행되어야 할 것이다.