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In order to calculate the overall PSNR between the original and the approximated set of images, we make the individual images into collages, as the one shown in Figure 1b, and compute the similarity between the original and approximated collages.
To derive a good approximated set of non-dominated points for convex multi-objective MINLPs, we propose a heuristic based on a branch-and-bound algorithm.
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By introducing an approximation based on Jacobian elliptic functions we derive an approximate set of two nonlinear integro-differential modulation equations that govern the time evolution of the amplitude and phase of the motion of the attachment.
We develop a tabu search algorithm in order to generate an approximate set of efficient solutions.
It presented an approximate set of scanned data points with a simple curves or surfaces.
An approximate set of feasible solutions called the initial population are utilized to initialize the genetic algorithm.
Nevertheless, it should be noted that the idea is to generate an approximate set of clusters which are corrected by visual inspection prior to training the models (as they form training data for the classifiers).
For estimating r bp, we use the back-link set as the approximate set of co-complexed proteins, while for r pp, we use the reciprocal set.
MODENA explores the approximate set of weak Pareto optimal solutions in the objective function space of 2 objective functions, a structure stability score and structure similarity score.
The key point here is to construct an approximate set of co-complexed proteins for each bait protein directly from AP-MS data.
Since it is difficult to obtain the complete set of weak Pareto optimal solutions, we explored the approximate set of weak Pareto optimal solutions in the RNA inverse problem by using a framework of MOGA.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com