• Journal of the Korean Institute of Gas
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• v.19 no.3
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• pp.44-48
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• 2015

The equations of hydrocarbon dew points(DT) of the fuel gas mixtures have been derived using the multiple regression analysis. In QSDR(Quantitative Structure Dew-point Relationship), the principal descriptors are CN(average carbon number) and BI(the ratio of the branched isomers). QSDRs studied by changing the pressures of the fuel gas mixtures in the range of 100 kPa ~ 500 kPa are as follows; $$DT(^{\circ}C)=-683.1+1224.98CN-898.01CN^2+308.58CN^3-49.56CN^4+3.02CN^5-12.42BI$$ (at 100 kPa, $$R_{adj}{^2}=0.99$$) (1) $$DT(^{\circ}C)=-745.2+1351.66CN-978.1CN^2+332.7CN^3-52.96CN^4+3.20CN^5-12.84BI$$ (at 200 kPa, $$R_{adj}{^2}=0.99$$) (2) $$DT(^{\circ}C)=-795.4+1457.1CN-1051.1CN^2+357.53CN^3-57.07CN^4+3.46CN^5-13.10BI$$ (at 300 kPa, $$R_{adj}{^2}=0.99$$) (3) $$DT(^{\circ}C)=-868.1+1608.4CN-1156.0CN^2+393.38CN^3-63.06CN^4+3.85CN^5-13.39BI$$ (at 500 kPa, $$R_{adj}{^2}=0.99$$) (4) As the average carbon numbers in the mixed fuel being reduced or the ratio of the branched isomers having a boiling point lower increase, The hydrocarbon dew point becomes lower, The differences between the hydrocarbon-dew points determined by the multiple regression and those calculated by the commercial program, VMGSim are negligible.

• The Journal of Korean Academy of Prosthodontics
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• v.48 no.4
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• pp.287-293
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• 2010

Purpose: This study evaluated the effect of polishing techniques on surface roughness of polymethyl methacrylate (PMMA), as well as the influence of light-cured surface glaze and subsequent brushing on surface roughness. Materials and methods: A total of 60 PMMA specimens ($10{\times}10{\times}5\;mm$) were made and then divided into 6 groups of 10 each according to the polymerization methods (under pressure or atmosphere) and the surface polishing methods (mechanical or chemical polishing) including 2 control groups. The mechanical polishing was performed with the carbide denture bur, rubber points and then pumice and lathe wheel. The chemical polishing was performed by applying a light-cured surface glaze ($Plaquit^{(R)}$; Dreve-Dentamid GmbH). Accura $2000^{(R)}$, a non-contact, non-destructive, optical 3-dimensional surface analysis system, was used to measure the surface roughness (Ra) and 3-dimensional images were acquired. The surface roughness was again measured after ultrasonic tooth brushing in order to evaluate the influence of brushing on the surface roughness. The statistical analysis was performed with Mann-Whitney test and t-test using a 95% level of confidence. Results: The chemically polished group showed a statistically lower mean surface roughness in comparison to the mechanically polished group (P = .0045) and the specimens polymerized under the atmospheric pressure presented a more significant difference (P = .0138). After brushing, all of the groups, except the mechanically polished group, presented rougher surfaces and showed no statistically significant differences between groups. Conclusion: Although the surface roughness increased after brushing, the chemical polishing technique presented an improved surface condition in comparison to the mechanical polishing technique.

• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.415-431
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• 2019

The satellite-viewed cloudiness, a ratio of cloudy pixels to total pixels ($C_{sat,\;prev}$), inevitably differs from the "ground-viewed" cloudiness ($C_{grd}$) due to different viewpoints. Here we develop an algorithm to retrieve the satellite-viewed, but adjusted cloudiness to $C_{grd} (C_{sat,\;adj})$. The key process of the algorithm is to convert the cloudiness projected on the plane surface into the cloudiness on the celestial hemisphere from the observer. For this conversion, the supplementary satellite retrievals such as cloud detection and cloud top pressure are used as they provide locations of cloudy pixels and cloud base height information, respectively. The algorithm is tested for Himawari-8 level 1B data. The $C_{sat,\;adj}$ and $C_{sat,\;prev}$ are retrieved and validated with $C_{grd}$ of SYNOP station over Korea (22 stations) and China (724 stations) during only daytime for the first seven days of every month from July 2016 to June 2017. As results, the mean error of $C_{sat,\;adj}$ (0.61) is less that than that of $C_{sat,\;prev}$ (1.01). The percent of detection for 'Cloudy' scenario of $C_{sat,\;adj}$ (73%) is higher than that of $C_{sat,\;prev}$ (60%) The percent of correction, the accuracy, of $C_{sat,\;adj}$ is 61%, while that of $C_{sat,\;prev}$ is 55% for all seasons. For the December-January-February period when cloudy pixels are readily overestimated, the proportion of correction of $C_{sat,\;adj$ is 60%, while that of $C_{sat,\;prev}$ is 56%. Therefore, we conclude that the present algorithm can effectively get the satellite cloudiness near to the ground-viewed cloudiness.