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Articles by H. Kim
Total Records ( 2 ) for H. Kim
  M Gillen and H. Kim
 

Older single women are disproportionately vulnerable to poverty. Using data from the 2002 and 2004 waves of the Health and Retirement Study of 5,799 women age 65 or older, this study investigated the effect of change in income sources by recent spousal loss on poverty transition. The focus is on (a) the effect of widowhood on income source change and (b) how such change affects poverty transition of recently widowed older women. Findings indicate that widowhood greatly decreases income from every source. Specifically, a $10 increase in social security benefits decreased the probability of poverty transition for recently widowed older women by 67.2%. These findings call for reconsidering social security survivor benefit rules and women's education with regard to financial security in retirement.

  Md. Atiqur Rahman Ahad , J. Tan , H. Kim and S. shikawa
  Problem statement: In template-based motion recognition approaches, feature sets are computed from the template for classification. Hu invariants are widely employed for this purpose since its inception. However, development of lower-dimensional feature vector sets is required for faster computation along with robust recognition. The concept of reduced size of Hu moment is really interesting. From its inception, seven higher orders Hu moments have been employed by many researchers without considering why seven and why not less numbers. Approach: In this study, we analyzed with various feature sets with different number of Hu moments and rationalized that based on the characteristics of central moments, it is not necessary to employ all the seven moments in every applications and, in that way, we can reduce the computational cost and make it faster. Results: Based on various feature vectors sets, it is evident that we can use lower dimensional feature vectors for our Directional Motion History Image (DMHI) method and other methods. Conclusion: Therefore, we can conclude that we do not need all seven invariants, rather 1st two or three invariants seem enough-as we are not reproducing the image. Higher invariants are noisy and hence can be ignored. The 0th order moment for Energy images provide enough information about the mass area and hence, no need to calculate the other seven invariants.
 
 
 
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