• Analytical Science and Technology
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• v.18 no.3
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• pp.201-205
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• 2005

Tri-octyl amine (TOA) is used in solvent extraction process for radioactive waste. This compound may be degraded to di-octyl amine (DOA), mono-octyl amine (MOA) by radioactive materials. Amount of TOA, DOA and MOA in TOA must be monitored because they production of these compounds means degradation of which leads to a decrease in the extraction yield. Retention behavior for TOA, DOA and MOA are studied with Phenomenex LUNA-$C_{18}$ ($4.6mm{\times}25cm$) analytical column and $CH_3OH:H_2O$ (50 mmol $CH_3COONH_4$) eluent by liquid chromatography. Optimum condition for these compounds is $CH_3OH:H_2O$ (50 mmol $CH_3COONH_4$) = 85 : 15 ratio. TOA, DOA and MOA compounds is well separated within 20 minute. Dynamic range is $30{\sim}160{\mu}g/mL$ for TOA, $5{\sim}100{\mu}g/mL$ for DOA and $0.1{\sim}5{\mu}g/mL$ for MOA, respectively. The detection limit are $0.1{\mu}g/mL$ for TOA, $1{\mu}g/mL$ for DOA (in SCAN mode) and $0.1{\mu}g/mL$ for MOA (in SIM mode) in this system with $20{\mu}L$ sample loop.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.277-283
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• 2021

Traffic data by vehicle classification are important data used as basic data in various fields such as road and traffic design. Traffic data is collected through permanent and temporary surveys and is provided as an annual average daily traffic (AATD) in the statistical yearbook of road traffic. permanent surveys are collected through traffic collection equipment (AVC), and the AVC consists of a loop sensor that detects traffic volume and a piezo sensor that detects the number of axes. Due to the nature of the buried type of traffic collection equipment, missing data is generated due to failure of detection equipment. In the existing method, it is corrected through historical data and the trend of traffic around the point. However, this method has a disadvantage in that it does not reflect temporal and spatial characteristics and that the existing data used for correction may also be a correction value. In this study, we proposed a method to correct the missing traffic volume by calculating the axis correction coefficient through the accumulated number of axes acquired by using a piezo sensor that can detect the axis of the vehicle. This has the advantage of being able to reflect temporal and spatial characteristics, which are the limitations of the existing methods, and as a result of comparative evaluation, the error rate was derived lower than that of the existing methods. The traffic volume correction system using axis count is judged as a correction method applicable to the field system with a simple algorithm.