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We find that the relative z-score, derived from the monkey test (Marsaglia and Zaman, 1993) for assessing random number generators (RNGs), helps classify six nucleotide sequence classes into three clusters in decreasing degree of randomness: (1) genome/intergene/intron, (2) mRNA/ncRNA, and (3) repeat.
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Most obviously, there is Schnorr's own conception of randomness (§2.1.2; supplement B.1.2).
To eliminate the impact of randomness, 100 scenarios are generated randomly to run for each experiment.
Matrix (A.7) performs the best for reasons of symmetry and randomness, (A.1).
But for higher randomness, η=0.1, 0.15, and 0.2, DIRL gives poor performance with regard to tracking performance.
Without preliminary information, the best statistical assumption is a uniform distribution over space, corresponding to complete spatial randomness [78].
Researchers have been actively working toward this to minimize the randomness [22, 23] in the key predistribution schemes.
It has been shown that devices detected with signal strength less than -80 dBm are largely due to randomness [19]; thus, we use -80 dBm as cutoff.
It can be seen that for lower randomness, η=0.5, 0.7, and 0.9, RL and Exp3 show very close results for tracking performance.
This is mainly due to the Gardner's TED self-noise arising from data randomness [17] and the additive noise impairment of channel.
One could say that they mark, as it were, the zero point on the scale of randomness.[23] How relevant are these insights to understanding the behaviour of actual systems?
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