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The proposed optimization is shown to be globally convergent to the optimal grasping force.
The result of optimization is shown in Fig. 7.
GP-based Bayesian optimization is shown in Algorithm 1.
The nonlinear optimization is shown to be the better way of determination.
Full description of the HSDBC algorithm for n-dimensional optimization is shown in Fig. 1.
The result of the dynamic optimization is shown in Fig. 1.
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The parameters for dynamic VAR planning optimization are shown in Table 2.
Moreover, the system optimization was shown to enhance the performance significantly.
The target molecules used as examples of transformation-driven optimization are shown in Figure 3.
In Table 10, the lowest and highest obtained costs in the Pareto chart of the fluids optimization are shown.
The different results obtained from the heating-load optimization and the heating-load density optimization are shown.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com