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In summary, the maximum window size does not appear to significantly limit our ability to detect associations between H and cognitive effort.
(A) boxplots plots showing correlations between individual subject H maps obtained for maximum window size nmax = 50 TR, compared to H maps obtained for shorter nmax.
In order to validate this approach, and determine the robustness of DFA to shorter time-windows, we examined the consistency of findings as a function of maximum window size nmax for the representative SART dataset.
This is demonstrated in the analysis of task difficulty, which was conducted on relatively short blocks of 20TRs, and a subsequent analysis of SART data (Fig. 6), which showed consistent results for a maximum window size nmax ranging from 50 to 20 TRs.
Doubling of the CW stops after the maximum window size CWmax is reached.
Similarly lower value of maximum window size is selected for priority flows and vice versa.
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Maximum window sizes from an overheating perspective were identified that are larger than the optimal window sizes for space heating demand.
Maximum window sizes were tested from 10-50% (in 10% increments) of participants at risk.
The learning agent starts searching for the optimized maximum TCP window size by halving the current maximum TCP window size.
At the maximum number of backoff stages m, the maximum contention window size CW max = CW m = 2 m * CW min. Fig. 1 Markov chain model for the 802.11e backoff process.
(The maximum RLC window size is set to 80 KBytes, the maximum TCP window size is 256 KBytes. NewReno TCP is used).
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Justyna Jupowicz-Kozak
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