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More importantly, we were able to show that CEnCs delivered by both approaches were able to reverse corneal blindness in a rabbit model of bullous keratopathy as shown by the recovery in corneal thickness in both treatment groups.
In addition, the heuristic approaches were able to perform within 4% of the constraint satisfaction approaches on student data from the classroom, which reflects the intended user population of the software.
All four approaches were able to reduce the training set size required considerably below that suggested by conventional widely used heuristics without significant impact on the accuracy with which the class of interest was classified.
A comparison of predicted model results for mean flow and turbulence with the corresponding experimental data showed that both the LES and RANS approaches were able to predict the main characteristics of the mean flow in the array of cubes reasonably well.
All three optimization approaches were able to improve on the dose distribution of the standard plan.
Nevertheless, except for F12, none of the approaches were able to locate the global optimum within the prescribed tolerance.
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Several approaches are able to provide such observers.
Neither universal or targeted approaches are able to accomplish swift, lasting, and largescale transformative change.
Results demonstrated both approaches being able to achieve excellent adhesion of final coating.
Such approaches are able to provide optimal or quasi-optimal solutions to a plethora of difficult combinatorial optimisation problems.
Intelligent approaches are able to find a sub-optimal (near to optimal) solution for the problem at hand.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com