John Jongdae Jin

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The Atmospheric Chemistry Experiment-Fourier Transform Spectrometer (ACE-FTS) aboard the Canadian satellite SCISAT (launched in August 2003) was designed to investigate the composition of the upper troposphere, stratosphere, and mesosphere. ACE-FTS utilizes solar occultation to measure temperature and pressure as well as vertical profiles of over thirty(More)
From January to March 2005, the Atmospheric Chemistry Experiment high resolution Fourier transform spectrometer (ACE-FTS) on SCISAT-1 measured many of the changes occurring in the Arctic (50–80 N) lower stratosphere under very cold winter conditions. Here we focus on the partitioning between the inorganic chlorine reservoirs HCl and ClONO2 and their(More)
This paper presents extensive validation analyses of ozone observations from the Atmospheric Chemistry Experiment (ACE) satellite instruments: the ACE Fourier Transform Spectrometer (ACE-FTS) and the Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (ACE-MAESTRO) instrument. 5 The ACE satellite instruments(More)
Partitioning between the inorganic chlorine reservoirs HCl and ClONO2 during the Arctic winter 2005 from the ACE-FTS G. Dufour, R. Nassar, C. D. Boone, R. Skelton, K. A. Walker, P. F. Bernath, C. P. Rinsland, K. Semeniuk, J. J. Jin, J. C. McConnell, and G. L. Manney Department of Chemistry, University of Waterloo, Ontario, Canada NASA Langley Research(More)
The purpose of this study is to compare the forecasting performance of a neural network (NN) model and a time-series (SARIMA) model in Korean Stock Exchange. In particular, we investigate whether the back-propagation neural network (BPNN)model outperforms the seasonal autoregressive integrated moving average (SARIMA) model in forecasting the Korea Composite(More)
In this study, we forecast Korean Stock Price Index using historical weekly KOSPI data and three forecasting models such as back-propagation neural network model (BPNN), a Bayesian Chiao's model (BC), and a seasonal autoregressive integrated moving average model (SARIMA). KOSPI are forecasted over three different periods. (i.e., short-term, mid-term, &(More)
AIM To study the chemical composition of Tripterygium wilfordii Hook.f. METHODS Column chromatography was used to separate the chemical constituents. UV, IR, MS, HRMS, 1HNMR, 13CNMR (COM and OFR), 1H-1H COSY, 1H-13C COSY, 2D-NOESY and 1H-13C COLOC were used to determine the structures of the isolated constituents. RESULTS Two sesquiterpene alkaloids(More)
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