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Here, we use a modified algorithm for acceleration, which avoids the recursive searching process.
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Darvishzadeh and Bhanu [14] present a framework to use a modified PSO MPSOO) algorithm in a multiple robot system for search task in real-world environments.
In this methodology, we use a modified genetic algorithm (MGA) to optimize the parameters of the MRL perceptron, as well as to select an optimal input feature subset of the used databases, aiming at a higher accuracy level for SDCE problems.
In this article, we use a modified bubble sorting algorithm to rearrange SU order.
Our approach is fundamentally different from theirs: we use a modified addition chain algorithm in which the multiplication is truncated to varying number of digits at various steps, followed by a self-tester that validates the truncation.
After finding CALs for each read, we use a modified local alignment algorithm previously described for color space reads by Homer et al.[17] and Rumble et al. [23].
We need to use a modified dynamic programming algorithm where the phased haplotypes also need to be taken into consideration for the MEC since we initially have placed them.
We use a modified relative value iteration algorithm to solve the ITH problem [31].
We propose to use a modified version of the binary search algorithm [ 21] to find p1 and, furthermore, to compute κ p using (4).
We use a modified version of the Variable Projection algorithm implemented by LeVeque (http://www.netlib.org/opt/varpro) adjusted such that the memory requirements scale linearly rather than quadratically with the number of pixels.
Project Ara will use a modified version of Android L, developed in collaboration with Linaro.
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