• Title/Summary/Keyword: temperature estimation

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Studies of VETH Plot for Standard Design of Evaporative Cooling at Summer Glasshouse (하절기 유리온실의 증발냉각 설계기준을 위한 VETH 선도 연구)

  • Woo, Y.H.;Ahn, Y.K.;Kim, D.E.
    • Journal of Practical Agriculture & Fisheries Research
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    • v.20 no.1
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    • pp.55-66
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    • 2018
  • Judicious control of high temperature is the most important task for the successful intensive-cultivation of vegetables in glasshouses during the hot summer. Estimation of cooling load and wise selection of suitable equipments and facilities based upon the environmental conditions are essential for the efficient temperature control. A series of experiments were carried out to investigate VETH(ventilation, evapotranspiration, temperature and humidity) plot was prepared for the possible practical application in designing some evaporated cooling methods for the following 9 locations; Seoul, Seosan, Taejeon, Pusan, Cheju, Kwangju, Taegu, Chonju, and Chinju.

Distribution of Relative Evapotranspiration Availability using Satellite Data in Daegu Metropolitan (위성 자료를 이용한 대구광역시의 상대적 증발산 효율 분포)

  • Kim, Hae-Dong;Im, Jin-Wook;Lee, Soon-Hwan
    • Journal of the Korean earth science society
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    • v.27 no.6
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    • pp.677-686
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    • 2006
  • Surface evapotranspiration is one of the most important factors to determine the surface energy budget, and its estimation is strongly related with the accuracy of weather forecasting. Surface evapotranspiration over Daegu Metropolitan was estimated using high resolution LANDSAT TM data. The estimation of surface evapotranspiration is based on the relationship between surface radiative temperature and vegetation index provided by a TM sensor. The distribution of NDVI (Normalized Difference of Vegetation Index) corresponds well with that of land-used in Deagu Metropolitan. The temperature of several part of downtown in Deagu metropolitan is lower in comparison with the averaged radiative temperature. This is caused by the high evapotranspiration from dense vegetation like DooRyu Park in Deagu Metropolitan. But, weak evapotranspiration availability is distinguished over the central part of downtown and the difference of evapotranspiration availability on industrial complexes and residential area is also clear.

Life Expectancy Estimation of the Propellants KM10 using High Temperature Acceleration Aging Tests and Stockpile Analysis Test (고온가속노화시험법과 저장분석시험법을 이용한 추진제 KM10의 기대수명 평가)

  • Cho, Ki-Hong;Kim, Eui Yong
    • Korean Chemical Engineering Research
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    • v.48 no.6
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    • pp.695-699
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    • 2010
  • The propellant KM10, a single propellant manufactured from nitrocellulose, was known to cause natural degradation phenomena at long term storage. In this study, the self-life was estimated using high temperature acceleration aging tests and stockpile analysis test. For the life expectancy estimation, Arrhenius equation and Berthelot equation were used in the high temperature acceleration tests, and the first order regression was used in the Stockpile analysis test. The self-life of propellant KM10 using the Arrhenius equation and Berthelot equation showed significantly different results as 43.73, 16.53 years in the high temperature acceleration test, and it showed 42.94 years in the Stockpile analysis test. The value of self-life predicted by Arrhenius equation was reasonable when compared with the result of E. R. Bixon.

Applicability Evaluation of Automated Machine Learning and Deep Neural Networks for Arctic Sea Ice Surface Temperature Estimation (북극 해빙표면온도 산출을 위한 Automated Machine Learning과 Deep Neural Network의 적용성 평가)

  • Sungwoo Park;Noh-Hun Seong;Suyoung Sim;Daeseong Jung;Jongho Woo;Nayeon Kim;Honghee Kim;Kyung-Soo Han
    • Korean Journal of Remote Sensing
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    • v.39 no.6_1
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    • pp.1491-1495
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    • 2023
  • This study utilized automated machine learning (AutoML) to calculate Arctic ice surface temperature (IST). AutoML-derived IST exhibited a strong correlation coefficient (R) of 0.97 and a root mean squared error (RMSE) of 2.51K. Comparative analysis with deep neural network (DNN) models revealed that AutoML IST demonstrated good accuracy, particularly when compared to Moderate Resolution Imaging Spectroradiometer (MODIS) IST and ice mass balance (IMB) buoy IST. These findings underscore the effectiveness of AutoML in enhancing IST estimation accuracy under challenging polar conditions.