The out-of-band (OoB) radiation that can cause serious aerial image deformation on the wafer is reported. In order to check the maximum allowable OoB radiation reflectivity at the extreme ultra-violet (EUV) pellicle, we simulated the effect of OoB radiation and found that the maximum allowable OoB radiation reflectivity at the pellicle should be smaller than 15 % which satisfy our criteria such as aerial image critical dimension (CD), contrast, and normalized image log slope (NILS). We suggested a new multi-stack EUV pellicle that can have high EUV transmission, minimal OoB radiation reflectivity, and enough deep ultra-violet transmission for inspection and alignment of the mask through the EUV pellicle.
Mobbing is not restricted to problem of young people but the bigger recent problem occurs in workspaces. According to reports of ILO and domestic case mobbing in the workplace is increasing more and more numerically from 9.1%('03) to 30.7%('08). These mobbing brings personal and social losses. The proposed algorithm makes it possible to grasp not only current mobbing victims but also potential mobbing victims through user profile and contribute to efficient personnel management.This paper extracts user profile related to mobbing, in a way of selecting seven factors and fifty attributes that are related to this matter. Next, expressing extracting factors as '1' if they are related me or not '0'. And apply similarity function to attributes summation included in factors to calculate similarity between the users. Third, calculate optimizing weight choosing factors included attributes by applying neural network algorithm of SPSS Clementine and through this summation Mobbing-Value(MV) can be calculated . Finally by mapping MV of online social network users to G2 mobbing propensity classification model(4 Groups; Ideal Group of the online social network, Bullies, Aggressive victims, Victims) which is designed in this paper, can grasp mobbing propensity of users, which will contribute to efficient personnel management.
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