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After computer optimization, the resulting schedule is presented in Fig. 14.
After optimization, the resulting puerarin nanoparticles exhibited a good spherical shape, a smooth surface and a narrow particle size distribution, with a mean particle size of 0.19 μm.
Furthermore, with the capability that AIDA has at considering process parameter variations during the optimization, the resulting methodology is able to obtain truly robust circuit designs.
For a wider bandwidth, including more of the spectrum in the optimization, the resulting weighting factors are given by the green and red lines for W=0.04 and 0.08, respectively.
Given a sufficient number of basis functions for the optimization, the resulting SRS can almost exactly match a randomly generated target SRS that is nonzero over the frequency range considered.
However, unlike former studies in the field of robust optimization, the resulting optimization model in the flood risk management problem is nonlinear and discontinuous and leads to an intractable robust counterpart model.
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Since the optimization process is stochastic, the resulting partition varies between realizations of the process.
The resulting optimization value is referred to as the localization score.
Therefore, a global minimum for the resulting optimization problem may not exist.
We find that the resulting optimization problem is a difference of convex (DC) functions.
The resulting convex optimization problem is (33a).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com