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Multi-objective genetic algorithm was performed to attain a single set of processing parameters that could produce both the highest light olefin selectivity and yield.
Methods: We acquired high-resolution structural MRI and DSI of the cerebellum in four healthy female subjects at 3T. DSI tractography based on a streamline algorithm was performed to identify the circuits connecting the cerebellar cortex with the deep cerebellar nuclei, selected brainstem nuclei, and the thalamus.
However, the majority-voting-based ensemble learning algorithm was performed to boost the classification results of the pairwise bilinear features in the first-stage ensemble learning.
However, the majority-voting-based ensemble learning algorithm was performed to boost the classification results of the 5-column features in the first-stage ensemble learning.
A heuristic search procedure using the tree bisection/reconnection branch swapping algorithm was performed to find the optimal ML tree topology (with 70,000 rearrangements).
We acquired high-resolution structural MRI and DSI of the cerebellum in four healthy female subjects at 3T. DSI tractography based on a streamline algorithm was performed to identify the circuits connecting the cerebellar cortex with the deep cerebellar nuclei, selected brainstem nuclei, and the thalamus.
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First, a coarse timing offset (CTO) estimation algorithm is performed to estimate the CTO and the inter-transmitter delays.
Optimization by genetic algorithm is performed to determine the characteristics of a bi-layer material minimizing the scattering.
In the first step of the proposed method, the time reversal focusing algorithm is performed to estimate the source locations on the source plane.
To accomplish this, a numerical optimization based on a finite element code and exhaustive search algorithm is performed to seek for the best geometric structure of the ψ-shaped cavity.
Since there are no analytical solutions for other heat transfer laws, the continuous HJB equations are discretized and the dynamic programming (DP) algorithm is performed to obtain the complete numerical solutions of the optimization problem.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com