In this article, we examined what has contributed to the worsening income inequality and poverty between 1996 and 2011 in South Korea. We used a rank-preserving exchange method and a conditional reweighting method to assess the roles of family behaviors—including female labor force participation and family structure—characteristics of household heads, and men’s earnings. The results showed that the change in men’s earnings was a dominant factor in accounting for the increasing income inequality and poverty. The change in age and education among household heads also contributed significantly to the worsening income distribution. The change in family structure mainly affected the income disparity among lower-income families and increased poverty. The rise in women’s labor force participation improved the income distribution but not considerably. The distributional roles of family have not worked to prevent or reverse the worsening income distribution in the past few decades in South Korea.
Principal component analysis (PCA) was modified for real-time applications and applied to the end-point detection of small open area SiO 2 plasma etching. Typically, the end point of plasma etching is determined from a few manually selected wavelengths. Determining the end point of the plasma etching using this approach is quite a challenge when the exposed open area is less than several percent. To increase the sensitivity, information was extracted from the entire spectra of 2755 signals in the range of 200-1100 nm, using a PCA algorithm. In this study, the PCA algorithm was modified to allow real-time applications of end-point detection. The loading vector was determined from the model wafer, and the score vector was determined using the real-time data of the target wafer to reduce the processing time. This algorithm was tested for the small open area of SiO 2 etching of a 200 ms sampling period, using the entire optical emission spectra, through a comparison with a defined signal-to-noise ratio. The results were compared with the conventional single wavelength signals of SiF (440.2 nm), CO (482.5 nm), and Si (505.6 nm). The end-point detection of 0.4%-0.8% SiO 2 open area was achieved using the suggested algorithm, while the single wavelength showed limitations in the open areas above a few percent. The sensitivity was also increased by a factor of 2.15, compared to the signal-to-noise ratio of the single wavelength method.
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