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Using the fast Fourier transform makes this algorithm more efficient.
Spheres are used to determine lower levels of detail which makes this algorithm highly suitable for multiple contact collision detection.
Given a real system, we could estimate the optimal parameter according to the data sparsity, which makes this algorithm easy to be applied.
This feature makes this algorithm especially well suited for problems where the data have high density, e.g. in the case of tracking devices working under high-luminosity condition such as those of LHC or super-LHC.
This attribute makes this algorithm suitable for intra-operative real-time treatment planning.
The pyramidal representation in the local model for spatial neighbors makes this algorithm efficient.
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The algorithm is more secure and easy to construct and thus made this algorithm special.
The simplicity and robustness of our tests make this algorithm appealing for object reconstruction.
These recursive operations with few memory requirements make this algorithm easy to implement on our architecture.
We need to make some customizations to make this algorithm more suitable for virtual network embedding problem.
Otherwise go back to step 3. To make this algorithm applicable to ring artifact correction, the entire sinogram image is divided into source and target region.
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CEO of Professional Science Editing for Scientists @ prosciediting.com