• Title/Summary/Keyword: Light-Backscattering

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The Scattering Property of EVA/SiO2 Composite Film Formed Micro-aggregation Structure for Roll-to-roll Process (Roll-to-roll 적용 가능한 마이크로 응집 구조를 갖는 EVA/SiO2 복합 필름의 산란 특성)

  • Jo, Kuk Hyun;Yang, Jun Yeong;Lee, Si Woo;Park, Eun Kyoung;Choi, Geun Seok;Song, Ki Won;Kim, Hyo Jung
    • Textile Coloration and Finishing
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    • v.30 no.3
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    • pp.190-198
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    • 2018
  • We fabricated high transmission and high scattering poly(ethylene-co-vinyl acetate)(EVA) films embedding $SiO_2$ nanoparticles to improve outcoupling efficiency in organic display. The 800nm diameter $SiO_2$ nanoparticles aggregated and formed $1.56{\mu}m$ (with ${\pm}0.853{\mu}m$ standard deviation) diameter microparticles in EVA. The total transmission of scattering film was 83.3% on Polyethylene terephthalate(PET), which was higher than reference 82.8% PET substrate. The diffuse transmission and haze of the $SiO_2$ embedded EVA film were 76.1% and 91.4%, respectively. The optimized condition was 1:1 weight ratio of $SiO_2$ nanoparticles to EVA in Tetrahydrofuran(THF) solution. When the ratio of $SiO_2$ was larger than 1, the total transmission decreased by the increase in backscattering of light due to high scattering. With the optimized condition, we could succeed to fabricate a large scale film(35m in length) with a roll-to-roll process.

Dispersion Stability Determination of Saengshik Beverage by Optical Methods (광학적 방법에 의한 생식음료의 분산 안정성 측정)

  • Lee, Ju-Yeon;Mok, Chulkyoon
    • Food Engineering Progress
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    • v.14 no.1
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    • pp.41-48
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    • 2010
  • An optical method was introduced to investigate the dispersion stability of Saengshik beverages (SB) containing 3.7-11.7% Saengshik powder (SP). Time course changes in backscattering light flux (BSLF) from SB were monitored by a Turbiscan. BSLF in the bottom and top layers of SB increased by forming sediment and foam, respectively, while that in the middle layer decreased by clarifying. With SP levels, sedimentation in SB was retarded, but the height of total sedimentation layer was increased. A logarithmic model was developed to fit to the changes in BSLF with time, showing determination coefficients of 0.979-0.988. The levels of SP in SB influenced the migration speed of the clarification front as well as the numbers of separated layers; 2 layers in SB containing 3.7% SP, 3 in 5.7-9.7%, and 4 in 11.7%. Formation of clear layers started after 17-29 min and continued for 22-53 min. The clarification was retarded most in SB containing 7.7% SP, indicating the most stable SP level for the SB preparation.

Waveform Decomposition of Airborne Bathymetric LiDAR by Estimating Potential Peaks (잠재적 피크 추정을 통한 항공수심라이다 웨이브폼 분해)

  • Kim, Hyejin;Lee, Jaebin;Kim, Yongil;Wie, Gwangjae
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1709-1718
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    • 2021
  • The waveform data of the Airborne Bathymetric LiDAR (ABL; LiDAR: Light Detection And Ranging) system provides data with improved accuracy, resolution, and reliability compared to the discrete-return data, and increases the user's control over data processing. Furthermore, we are able to extract additional information about the return signal. Waveform decomposition is a technique that separates each echo from the received waveform with a mixture of water surface and seabed reflections, waterbody backscattering, and various noises. In this study, a new waveform decomposition technique based on a Gaussian model was developed to improve the point extraction performance from the ABL waveform data. In the existing waveform decomposition techniques, the number of decomposed echoes and decomposition performance depend on the peak detection results because they use waveform peaks as initial values. However, in the study, we improved the approximation accuracy of the decomposition model by adding the estimated potential peak candidates to the initial peaks. As a result of an experiment using waveform data obtained from the East Coast from the Seahawk system, the precision of the decomposition model was improved by about 37% based on evaluating RMSE compared to the Gaussian decomposition method.