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A novel framework has been proposed for optimizing batch cooling crystallization operation.
Distributed dual averaging (DDA) algorithm – inspired by Nesterov's dual averaging algorithm (Xiao 2010; Nesterov 2009) – has been proposed for optimizing convex functions (Duchi & Wainwright 2012).
Other dosing strategies have been proposed for optimizing beta-lactams exposure, these include dose adjustments made specific to interventions, continuous infusion and dosing monograms.
In principle, the goal of a module detection is to find the 'optimal' partition with largest modularity Q or modularity density D. Several methods have been proposed for optimizing Q.
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An evolutionary approach an improved particle swarm optimization is proposed for optimizing such systems.
A novel optimization framework based on a stochastic optimization algorithm is proposed for optimizing batch, semi-batch and non-isothermal evaporative crystallizations.
A stochastic optimization framework is proposed for optimizing semi-batch reactive crystallizations.
In the presented work, a metamodel-based shape optimization methodology is proposed for optimizing shallow-buried blast-loaded underbody structures.
A random search algorithm is proposed for optimizing these models.
A recommendation is proposed for optimizing the deep cryogenic treatment of tool steels.
Here, a fractal branch and bound method (FBB) is proposed for optimizing the stacking sequences.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com