• Korean Journal of Veterinary Service
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• v.30 no.2
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• pp.197-203
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• 2007

A total of 501 serum samples were selected from blood samples that were submitted to Department of Veterinary Pathology, Kangwon National University from all provinces in Korea from September 2001 to August 2002. Their sera were examined for antibodies to swine influenza virus subtype H1N1 (SlV H1N1) and porcine repro-ductive and respiratory syndrome virus (PRRSV) according to the age of pig, season, and herd size using enzyme-linked immunosorbent assay. The seroprevalence of SIV H1N1, PRRSV, and dual infection were 39.12%, 61.48%, and 25.95%, respectively. The seroprevalence of SIV H1N1 according to herd size was not significant differences (p>0.05). The results showed that the PRRSV infection spread widely in swine herds throughout the country.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1956-1960
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• 2010

최근 이상홍수 및 하천정비 등으로 인해 갈수시 또는 홍수시 하천 모니터링을 위한 기초자료로 유량측정의 필요성이 부각되고 있다. 기존 유량측정 방법은 고비용과 다수의 측정인력이 필요하기 때문에 이를 개선하기 위하여 최근 전자장비를 이용한 비접촉식 유량측정에 대한 연구가 다수 진행 중에 있다. 이 중 간편하고 측정 정확도를 유지할 수 있는 표면영상유속계(SIV, Surface Image Velocimetry)에 대한 연구가 국내외에서 다양하게 이루어지고 있다. 표면영상유속계는 일정 시간 간격을 갖는 두 영상을 분석하여 유속을 계산하기 때문에 수표면이 움직이는 시간보다 두 영상 사이의 시간 간격을 길게 할 경우 잘못된 상관영역을 찾게 되어 유속 측정의 정확도를 떨어뜨릴 수 있다. 이러한 문제점을 개선하기 위해서 영상간의 시간간격 변화에 따른 표면영상유속계의 정확도 분석을 수행하였다. 본 연구에서는 영상간의 시간간격에 따른 표면영상유속계의 정확도 분석을 위해 현장에서 수면 요철이 발생하는 근경 영상을 이용하여 영상내의 수면 움직임의 최소 지속시간을 측정하였다. 측정 결과 대부분의 수면 요철은 0.1 ~ 0.2 초 내에서 발생하였다. 측정 결과 일반 캠코더를 이용하여 초당 최대 30장의 영상을 이용하여 하천 표면유속을 측정한다면 문제가 없을 것으로 판단된다.

• Journal of Korea Water Resources Association
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• v.49 no.6
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• pp.469-480
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• 2016

The present study aims to develop a real-time surface image velocimeter (SIV) using an Android smartphone. It can measure river surface velocity by using its built-in sensors and processors. At first the SIV system figures out the location of the site using the GPS of the phone. It also measures the angles (pitch and roll) of the device by using its orientation sensors to determine the coordinate transform from the real world coordinates to image coordinates. The only parameter to be entered is the height of the phone from the water surface. After setting, the camera of the phone takes a series of images. With the help of OpenCV, and open source computer vision library, we split the frames of the video and analyzed the image frames to get the water surface velocity field. The image processing algorithm, similar to the traditional STIV (Spatio-Temporal Image Velocimeter), was based on a correlation analysis of spatio-temporal images. The SIV system can measure instantaneous velocity field (1 second averaged velocity field) once every 11 seconds. Averaging this instantaneous velocity measurement for sufficient amount of time, we can get an average velocity field. A series of tests performed in an experimental flume showed that the measurement system developed was greatly effective and convenient. The measured results by the system showed a maximum error of 13.9 % and average error less than 10 %, when we compared with the measurements by a traditional propeller velocimeter.

• Journal of Korea Water Resources Association
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• v.41 no.7
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• pp.701-709
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• 2008

Surface Image Velocimetry (SIV) is an instrument to measure water surface velocity by using image processing techniques. It gives us one of the easiest ways to measure water velocity. However, since it requires a set of plane survey data to estimate the velocity, it may give us some kind of misconcept that its usage would be difficult or cumbersome in spite of its handiness. If it has a feature that can estimate the plane survey data easily, it may be treated as like one of the conventional propeller velocimetries and its applicability would be improved so high. The present study is to propose a method to estimate the plane geometry of the physical coordinate with a calibrated camera. With the feature we can half-automatize the estimating procedure for the whole water velocity field. Photogrammetric technique to calculate the plane coordinates of the reference points with a calibrated camera was studied, which has originally studied for long time in the field of computer vision. By applying this technique to SIV, it is possible to estimate the location of reference coordinates for projective transform without plane survey. With this procedure the cumbersome plane survey for the reference points is omitted. One example application of the developed method showed fairly good results with insignificant errors.

• Korean Journal of Veterinary Service
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• v.34 no.4
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• pp.313-320
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• 2011

The purpose of this study was to investigate association with gross lesions and causative pathogens of porcine respiratory disease complex (PRDC) including porcine circovirus type 2 (PCV2), porcine reproductive and respiratory syndrome virus (PRRSV), swine influenza virus (SIV), Mycoplasma hyopneumoniae (MH), Pasteurella multocida (PM), Actinobacillus pleuropneumoniae (APP), Haemophilus parasuis (HP) in slaughtered pigs. A total of 1,200 lung samples were collected randomly from slaughtered pigs in Korea during August of 2010 through July of 2011. The gross lesions were classified according to the six stages (0, 1~10, 11~20, 21~30, 31~40 and ${\geq}41$, unit=%) and 48 samples from each stage were selected to detect viral and bacterial pathogens. The results according to the six stages were 100 (8.3%), 259 (21.6%), 326 (27.2%), 213 (17.8%), 144 (12.0%) and 158 (13.2%) cases, respectively. Prevalence of pneumonia according to season was 87.0~96.7% and the highest prevalence was in spring. In detection of pathogens by PCR, 53 samples were not detected any causative pathogens of PRDC. PCV2, PRRSV, SIV, MH, PM, APP serotype 2, APP serotype 5 and HP were positive in 45.5%, 12.5%, 10.4%, 60.1%, 1.7%, 13.9%, 12.2% and 15.6%, respectively. In co-infection, PCV2-MH was the most detected causative pathogens of PRDC. The detection rate of PCV2 and PRRSV was the highest in spring, of SIV, MH and HP was in winter. The detection rate of APP-2 and APP-5 had no seasonal prevalence. The more severe gross lesions increased, the higher the detection rate showed.

• 전기의세계
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• v.25 no.6
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• pp.65-68
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• 1976

For the RIV characteristics test of power apparatus, an indoor measuring system of radio influence voltage was set up and by means of this measuring unit SIV characteristics on the 7$^{1}$2/" pin-type domestic insulators were examined. According to the test data, RIV values of all the test pieces exceeded the maximum permissible level at 10kV applied voltage. The electrical resistivity of domestic semi-conductive glaze as good as importedone but un-uniformity of coating is turned out to be a main cause of failure.lure.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.467-468
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• 2007

This paper describes characteristics of converters of auxiliary power supply for electric railway vehicles. Auxiliary power supply is called Static Inverter(SIV) which supplied lamps, air conditioning and heat equipments, control systems, etc. Simulation results shows that line No.1 cheon contains low harmonics compared with those of KTX.

• Proceedings of the KSR Conference
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• 2002.10a
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• pp.522-527
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• 2002

This paper proposes 40 [KVA] rated SW(Static Inverter) system for Light Rail Transit. The SIV provide power of a fluorescent light in the car, Air-conditioner, and other equipments. To control output voltage it is used voltage control loop for constant voltage control and simultaneously used current control loop for instantaneous control at load changing. The performance of SW system will be verified by experimental results.

• Proceedings of the KIPE Conference
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• 2018.11a
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• pp.161-162
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• 2018

철도챠량에서 일반적으로 사용되는 상용전원은 보조전원장치(이하 SIV)로 불리는 전력변환장치로부터 공급된다. 본 논문에서는 LLC 공진형 컨버터를 적용하여 스위치의 영전압 스위칭(Zero-Voltage-Switching, ZVS)을 통해 높은 효율을 달성하고, 고속스위칭에 의해 인덕터, 커패시터, 트랜스포머와 같은 소자의 부피를 줄이고 시스템의 효율을 높여 기존의 보조전원장치보다 약 40%이상 소형 경량화가 가능한 보조전원장치에 대한 연구를 소개한다.

• Journal of Environmental Science International
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• v.25 no.6
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• pp.799-815
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• 2016

In this study, according to the reference setting based on the runoff video of 9:00 where the highest water level of 3.94 m has been recorded during the runoff of Cheon-mi Stream in Jeju Island by the attack of Typhoon no. 16 Sanba on September $17^{th}$, 2012, the error rate of long-distance and short-distance velocimetry and real-distance change rate by input error have been calculated and the input range value of reference point by stream has been suggested. In the reference setting process, if a long-distance reference point input error occurs, the real-distance change rate of 0.35 m in the x-axis direction and 1.35 m in y-axis direction is incurred by the subtle input error of 2~11 pixels, and if a short-distance reference point input error occurs, the real-distance change rate of 0.02 m in the x-axis direction and 0.81 m in y-axis direction is incurred by the subtle input error of 1~11 pixels. According to the long-distance reference point setting variable, the velocity error rate showed the range of fluctuation of at least 14.36% to at most 76.06%, and when calculating flux, it showed a great range of fluctuation of at least 20.48% to at most 78.81%.