• Title/Summary/Keyword: 모드 기여도

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Improvement of an Simultaneous Determination for Clenbuterol and Ractopamine in Livestock Products using LC-MS/MS (LC-MS/MS를 이용한 축산물 중 clenbuterol과 ractopamine의 동시 분석법 개선)

  • Cho, Yoon-Jae;Chae, Young-Sik;Kim, Jae-Young;Kim, Hyung-Soo;Kang, Ilhyun;Do, Jung-Ah;Oh, Jae-Ho;Kwon, Kisung;Chang, Moon-Ik
    • Korean Journal of Food Science and Technology
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    • v.45 no.1
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    • pp.25-33
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    • 2013
  • Clenbuterol and ractopamine, which are ${\beta}$-agonists, have been misused as a growth promoting agent in meat producing animals. Clenbuterol was banned for veterinary drug in Korea because of its problems regarding safety. Due to their adverse effects, such as cardiovascular and central nervous diseases on human health proper control and monitoring should be conducted. The existing analytical method of clenbuterol and ractopamine in the Food code was improved through our present study. The bovine muscle samples were subjected to enzymatic hydrolysis, extracted with ethyl acetate and defatted by hexane-methanol partitioning. A molecular imprinted polymer (MIP) solid phase extraction cartridge was used for clean-up and LC-MS/MS was operated in positive multiple reaction monitoring (MRM). Clenbuterol-$d_9$ and ractopamine-$d_3$ were used as an internal standard. The renewed method was validated according to the CODEX guideline. The limits of quantitation for clenbuterol and ractopamine were 0.2 and 0.5 ${\mu}g/kg$, respectively. The mean recoveries ranged in 104.2-113.5% for clenbuterol and in 107.6-118.1% for ractopamine. The improved method was able to save both time and expenses.

Verification of Kompsat-5 Sigma Naught Equation (다목적실용위성 5호 후방산란계수 방정식 검증)

  • Yang, Dochul;Jeong, Horyung
    • Korean Journal of Remote Sensing
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    • v.34 no.6_3
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    • pp.1457-1468
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    • 2018
  • The sigma naught (${\sigma}^0$) equation is essential to calculate geo-physical properties from Synthetic Aperture Radar (SAR) images for the applications such as ground target identification,surface classification, sea wind speed calculation, and soil moisture estimation. In this paper, we are suggesting new Kompsat-5 (K5) Radar Cross Section (RCS) and ${\sigma}^0$ equations reflecting the final SAR processor update and absolute radiometric calibration in order to increase the application of K5 SAR images. Firstly, we analyzed the accuracy of the K5 RCS equation by using trihedral corner reflectors installed in the Kompsat calibration site in Mongolia. The average difference between the calculated values using RCS equation and the measured values with K5 SAR processor was about $0.2dBm^2$ for Spotlight and Stripmap imaging modes. In addition, the verification of the K5 ${\sigma}^0$ equation was carried out using the TerraSAR-X (TSX) and Sentinel-1A (S-1A) SAR images over Amazon rainforest, where the backscattering characteristics are not significantly affected by the seasonal change. The calculated ${\sigma}^0$ difference between K5 and TSX/S-1A was less than 0.6 dB. Considering the K5 absolute radiometric accuracy requirement, which is 2.0 dB ($1{\sigma}$), the average difference of $0.2dBm^2$ for RCS equation and the maximum difference of 0.6 dB for ${\sigma}^0$ equation show that the accuracies of the suggested equations are relatively high. In the future, the validity of the suggested RCS and ${\sigma}^0$ equations is expected to be verified through the application such as sea wind speed calculation, where quantitative analysis is possible.

Estimation of spatial distribution of snow depth using DInSAR of Sentinel-1 SAR satellite images (Sentinel-1 SAR 위성영상의 위상차분간섭기법(DInSAR)을 이용한 적설심의 공간분포 추정)

  • Park, Heeseong;Chung, Gunhui
    • Journal of Korea Water Resources Association
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    • v.55 no.12
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    • pp.1125-1135
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    • 2022
  • Damages by heavy snow does not occur very often, but when it does, it causes damage to a wide area. To mitigate snow damage, it is necessary to know, in advance, the depth of snow that causes damage in each region. However, snow depths are measured at observatory locations, and it is difficult to understand the spatial distribution of snow depth that causes damage in a region. To understand the spatial distribution of snow depth, the point measurements are interpolated. However, estimating spatial distribution of snow depth is not easy when the number of measured snow depth is small and topographical characteristics such as altitude are not similar. To overcome this limit, satellite images such as Synthetic Aperture Radar (SAR) can be analyzed using Differential Interferometric SAR (DInSAR) method. DInSAR uses two different SAR images measured at two different times, and is generally used to track minor changes in topography. In this study, the spatial distribution of snow depth was estimated by DInSAR analysis using dual polarimetric IW mode C-band SAR data of Sentinel-1B satellite operated by the European Space Agency (ESA). In addition, snow depth was estimated using geostationary satellite Chollian-2 (GK-2A) to compare with the snow depth from DInSAR method. As a result, the accuracy of snow cover estimation in terms with grids was about 0.92% for DInSAR and about 0.71% for GK-2A, indicating high applicability of DInSAR method. Although there were cases of overestimation of the snow depth, sufficient information was provided for estimating the spatial distribution of the snow depth. And this will be helpful in understanding regional damage-causing snow depth.

Report about First Repeated Sectional Measurements of Water Property in the East Sea using Underwater Glider (수중글라이더를 활용한 동해 최초 연속 물성 단면 관측 보고)

  • GYUCHANG LIM;JONGJIN PARK
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.29 no.1
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    • pp.56-76
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    • 2024
  • We for the first time made a successful longest continuous sectional observation in the East Sea by an underwater glider during 95 days from September 18 to December 21 2020 in the Korea along the 106 Line (129.1 °E ~ 131.5 °E at 37.9 °N) of the regular shipboard measurements by the National Institute of Fishery Science (NIFS) and obtained twelve hydrographic sections with high spatiotemporal resolution. The glider was deployed at 129.1 °E in September 18 and conducted 88-days flight from September 19 to December 15 2020, yielding twelve hydrographic sections, and then recovered at 129.2 °E in December 21 after the last 6 days virtual mooring operation. During the total traveled distance of 2550 km, the estimated deviation from the predetermined zonal path had an average RMS distance of 262 m. Based on these high-resolution long-term glider measurements, we conducted a comparative study with the bi-monthly NIFS measurements in terms of spatial and temporal resolutions, and found distinguished features. One is that spatial features of sub-mesoscale such as sub-mesoscale frontal structure and intensified thermocline were detected only in the glider measurements, mainly due to glider's high spatial resolution. The other is the detection of intramonthly variations from the weekly time series of temperature and salinity, which were extracted from glider's continuous sections. Lastly, there were deviations and bias in measurements from both platforms. We argued these deviations in terms of the time scale of variation, the spatial scale of fixed-point observation, and the calibration status of CTD devices of both platforms.