• Journal of radiological science and technology
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• v.38 no.3
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• pp.245-252
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• 2015

To obtain the best SNR (signal to noise ratio) due to changes in CTDI (computed tomography dose index) made for the purpose of setting the optimum image obtained by reducing the dose in abdominal CT. Abdominal CT scans of 59 patients a $400-499cm^2$ (n = 12), $500-599cm^2$ (n = 21), $600-699cm^2$ (n = 17), $700-799cm^2$ (n = 9) were separated by four groups and the effective dose was used in the Excel to get the area of the patient using the ImageJ program. Patients of CTDI, DLP, SNR, the effective dose were analyzed. Abdominal CT area was increased to 13 mGy in CTDI is 7.3 mGy, DLP to 732 in $394.4mGy{\cdot}cm$, also effective dose was 5.9 mSv increase in 11mSv. SNR is 15 dB was maintained at 12.7. CTDI according to the average of the abdominal area of 8.9 mGy, the average of the DLP was $481.54mGy{\cdot}cm$, the effective dose is calculated to be 7.2 mSV. Effective dose was calculated by multiplying the load factor of DLP in the abdomen showed no statistically significant difference of (p < .05), there was a significant difference in SNR (p > . 05). To improve image quality of abdominal CT scan image in consideration of the CTDI according to the volume of the patient it should be able to reduce the radiation exposure of the patients.

• Journal of Climate Change Research
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• v.5 no.1
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• pp.71-81
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• 2014

Using the Eddy Covariance technique, we analyzed seasonal variation in net ecosystem $CO_2$ exchange (NEE) and investigated the effects of environmental factors and aboveground biomass of rice on the $CO_2$ fluxes in a rice-barley double cropping paddy field of Gimje, Korea. Quality control and gap-filling were conducted before this investigation of the effects. The results have been showed that NEE, gross primary production (GPP), and ecosystem respiration (Re) during the rice growing period were -215.6, 763.9, and $548.3g\;C\;m^{-2}$, respectively. Relation between NEE and net radiation (Rn) could be described by a quadratic equation, and about 65 % of variation in NEE was explained by changes in Rn. On the other hand, an exponential function relating Re to soil temperature accounted for approximately 43 % of variation in Re under the flooded condition of paddy field. Aboveground biomass showed significant linear relationships with NEE ($r^2=0.93$), GPP ($r^2=0.96$), and Re ($r^2=0.95$), respectively.