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The smart card decrypts C1 using the random value of u. b.
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The first one is an algorithm which finds all possible paths between two random secondary users selected as source node and destination node then returns the hop count of the shortest path between them by using the random values of node location and active state, antenna gain, and channel fading as input data.
The clustering elements are selected from the gene expression database using the random values of an index matrix.
Fits to the data have been obtained using the random phase expressions providing values of the interaction parameter and radius of gyration of the inner block.
Differentially expressed genes for 4T1 samples relative to 67NR and 168FARN samples were determined separately with the Class Comparison program using the random variance model and a p value of 0.0001.
For two-phrase combinations, expected values were calculated using the random model.
The one-tailed P values were estimated using the random permutation method.
Missing values were imputed using the random Forest unsupervised classification algorithm (see online supplementary methods).
Our approach is used the random nonce values to eliminate the transmission and clock synchronization delay time.
The MRF-EM-NMF and EM-NMF algorithms were initialized using the same random values (given as \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\bar{R}$$\end{document} ) and run for 1,500 iterations.
We then estimated the cost per case averted using these random values.
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