• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.977-985
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• 2012

Data quality and climate forecasting performance deteriorates because of long climate data contaminated by non-climatic factors such as the station relocation or new instrument replacement. For a trusted climate forecast, it is necessary to implement data quality control and test inhomogeneous data. Before the inhomogeneity test, a reference series was created by $d$ index to measure the temperature series relationship between the candidate and surrounding stations. In this study, a inhomogeneity test to each season and climatological station was performed on the daily mean temperatures, daily minimum temperatures and daily maximum temperatures. After comparing two inhomogeneity tests, the traditional and the adjusted SNHT method, we found the adjusted SNHT method was slightly superior to the traditional one.

• Atmosphere
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• v.31 no.5
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• pp.553-562
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• 2021

The long-term trend of surface wind speed in Korea is estimated by correcting wind measurements at 29 KMA weather stations from 1985 to 2019 with physical and statistical homogenization. The anemometer height changes at each station are first adjusted by applying physical homogenization using the power-law wind profile. The statistical homogenization is then applied to the adjusted data. A standard normal homogeneity test (SNHT) is particularly utilized. Approximately 40% of inhomogeneities detected by the SNHT match with the sea-level-height change of each station, indicating that an SNHT is an effective technique for reconciling data inhomogeneity. The long-term trends are compared with homogenized data. Statistically significant negative trends are observed along the coast, while insignificant trends are dominant inland. The mean trend, averaged over all stations, is -0.03 ± 0.07 m s^-1 decade^-1. This insignificant trend is due to a trend change across 2001. A decreasing trend of -0.10 m s^-1 decade^-1 reverses to an increasing trend of 0.03 m s^-1 decade^-1 from 2001. This trend change is consistent with mid-latitude wind change in the Northern hemisphere, indicating that the long-term trend of surface wind speed in Korea is partly determined by large-scale atmospheric circulation.

• Journal of Applied Reliability
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• v.13 no.4
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• pp.273-285
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• 2013

Because process variations have direct influence on yield rate in process industry, it is very important to understand process variations that occur accidentally. In process industry, quality variation due to the activities of process improvement and maintenance and chance effect such as change of work environment and difference in staffs' craftsmanship are mixed with each other, therefore it is difficult to actually detect minute process variations. In this study, objective and rational methods of detection that can detect minute process variations in process industry were designed referring to various methodologies of process management, and they were verified through similar examples.