• Title/Summary/Keyword: 전달함수합성

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Comparison of Measured and Calculated Carboxylation Rate, Electron Transfer Rate and Photosynthesis Rate Response to Different Light Intensity and Leaf Temperature in Semi-closed Greenhouse with Carbon Dioxide Fertilization for Tomato Cultivation (반밀폐형 온실 내에서 탄산가스 시비에 따른 광강도와 엽온에 반응한 토마토 잎의 최대 카복실화율, 전자전달율 및 광합성율 실측값과 모델링 방정식에 의한 예측값의 비교)

  • Choi, Eun-Young;Jeong, Young-Ae;An, Seung-Hyun;Jang, Dong-Cheol;Kim, Dae-Hyun;Lee, Dong-Soo;Kwon, Jin-Kyung;Woo, Young-Hoe
    • Journal of Bio-Environment Control
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    • v.30 no.4
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    • pp.401-409
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    • 2021
  • This study aimed to estimate the photosynthetic capacity of tomato plants grown in a semi-closed greenhouse using temperature response models of plant photosynthesis by calculating the ribulose 1,5-bisphosphate carboxylase/oxygenase maximum carboxylation rate (Vcmax), maximum electron transport rate (Jmax), thermal breakdown (high-temperature inhibition), and leaf respiration to predict the optimal conditions of the CO2-controlled greenhouse, for maximizing the photosynthetic rate. Gas exchange measurements for the A-Ci curve response to CO2 level with different light intensities {PAR (Photosynthetically Active Radiation) 200µmol·m-2·s-1 to 1500µmol·m-2·s-1} and leaf temperatures (20℃ to 35℃) were conducted with a portable infrared gas analyzer system. Arrhenius function, net CO2 assimilation (An), thermal breakdown, and daylight leaf respiration (Rd) were also calculated using the modeling equation. Estimated Jmax, An, Arrhenius function value, and thermal breakdown decreased in response to increased leaf temperature (> 30℃), and the optimum leaf temperature for the estimated Jmax was 30℃. The CO2 saturation point of the fifth leaf from the apical region was reached at 600ppm for 200 and 400µmol·m-2·s-1 of PAR, at 800ppm for 600 and 800µmol·m-2·s-1 of PAR, at 1000ppm for 1000µmol of PAR, and at 1500ppm for 1200 and 1500µmol·m-2·s-1 of PAR levels. The results suggest that the optimal conditions of CO2 concentration can be determined, using the photosynthetic model equation, to improve the photosynthetic rates of fruit vegetables grown in greenhouses.

Fabrication of Gd2O2S:Tb fine scintillator film and evaluation of image quality for resolution improvement of X-ray imaging based on CMOS (CMOS 기반 X선 영상의 해상력 향상을 위한 Gd2O2S:Tb 미세형광체 필름 제작 및 영상 질 평가)

  • Kang, Sang-Sik;Choi, Young-Zoon;Jung, Bong-Jae;No, Si-Cheul;Cho, Chan-Hoon;Yoon, In-Chan;Park, Ji-Koon
    • Journal of the Korean Society of Radiology
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    • v.5 no.5
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    • pp.283-287
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    • 2011
  • In this study, fine $Gd_2O_2S$:Tb powder was synthesized by using a low temperature solution-combustion method for a high-resolution digital x-ray imaging detector. From the fabricated phosphor power, the fine scintillator films was fabricated by particle sedimentation method and was investigated the luminescent property. From the experimental results of relative light output as a function of terbium concentration, the highest luminescent efficiency has at 5 wt% Tb concentration, and luminescent intensity decreased rapidly according to quenching effect about higher Tb concentration. Also, the relative light output of $270{\mu}m$-$Gd_2O_2S$:Tb film has 2945 pC/$cm^2$/mR. And light intensity was saturated at higher film thickness. Finally, to evaluate an image acquisition performance of fabricated phosphor, images were obtained by using commercial CMOS sensor and measured the MTF, NPS, and DQE. DQE(0 lp/mm) of fine phosphor film has 37%. But, DQE improvement of fine phosphor film is possible by resolving problem of film fabrication process and has a significant potential in the application of digital radiation imaging system later.

Estimation of Significant Wave Heights from X-Band Radar Based on ANN Using CNN Rainfall Classifier (CNN 강우여부 분류기를 적용한 ANN 기반 X-Band 레이다 유의파고 보정)

  • Kim, Heeyeon;Ahn, Kyungmo;Oh, Chanyeong
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.33 no.3
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    • pp.101-109
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    • 2021
  • Wave observations using a marine X-band radar are conducted by analyzing the backscattered radar signal from sea surfaces. Wave parameters are extracted using Modulation Transfer Function obtained from 3D wave number and frequency spectra which are calculated by 3D FFT of time series of sea surface images (42 images per minute). The accuracy of estimation of the significant wave height is, therefore, critically dependent on the quality of radar images. Wave observations during Typhoon Maysak and Haishen in the summer of 2020 show large errors in the estimation of the significant wave heights. It is because of the deteriorated radar images due to raindrops falling on the sea surface. This paper presents the algorithm developed to increase the accuracy of wave heights estimation from radar images by adopting convolution neural network(CNN) which automatically classify radar images into rain and non-rain cases. Then, an algorithm for deriving the Hs is proposed by creating different ANN models and selectively applying them according to the rain or non-rain cases. The developed algorithm applied to heavy rain cases during typhoons and showed critically improved results.