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This last characteristic is of particular interest, as large-scale real-world applications have the potential to require large amounts of computation.
Gapped extension generally requires large amounts of computation time; therefore, most homology search algorithms perform an ungapped extension before a gapped extension.
In addition, due to the large amounts of computation in this study, we only compared three detection algorithms, so the evaluation of other algorithms needed to be further carried out.
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In these devices, motion-compensated temporally predictive coding with motion estimation (ME) not only contributes the most to the coding efficiency of modern video encoder designs [1], but also requires large amounts of computations as well as data bandwidth (BW) [2].
W-CMSR consumes large amount of computation time although its computational efficiency is not affected by the signal bandwidth.
Since this conversion process requires a large amount of computation, this algorithm has low computational efficiency.
Nevertheless, the GVFF mechanism requires a large amount of computation.
This kind of technology requires a large amount of computation for specific scenarios.
Both cases require a large amount of computation to brute-force search the complete space.
For example, AHP requires a relatively large amount of computation and TOPSIS determines the criteria weights subjectively.
In the BH algorithm, a large amount of computation is needed when calculating fitness function values of all stars.
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