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This is a difficult combinatorial optimisation problem, in which decision variables are discrete and both cost function and constraints are non-linear.
This paper presents a novel formulation for structural topology optimization in which both cost function and constraints are expressed in terms of an implicit design variable the iso-line/surface threshold of a characteristic response function, such as a strain or mutual strain energy density function.
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This suggests that explicit, formal expressions defining cost-efficient measurement allocations may only be obtainable if both cost functions and expressions of statistical performance are mathematically very simple.
It is observed that both the cost function and constraints are quadratic in W and linear in γ.
end{aligned} (6 The approximation process of problem (mathcal {A}) includes the discretization of both the cost function and the controlled integral equation constraint.
Finally, a sensitivity analysis on the main parameters of both the cost function and the control chart is performed using experimental design approach.
The use of MPC allowed the generation of biophysically plausible control signals by tuning both the MPC cost function and the constraints on the controller output.
Hence, after adaptation to the new code, the codon frequencies and code cost are: (13) (14) where the new values are used both in the cost function and the codon frequencies.
In the following 24-parameter aerodynamic design optimization case, a steepest descent optimization (SDO) based on adjoint gradient is conducted, then QP based response surface model is constructed using both the values of cost function and its adjoint gradients with respect to geometry control parameters.
In the combination of higher α and lower β (which clearly means more stimulation overall), we see both a higher average cost function and stronger latency-cost function link.
In this study, the lung and spinal cord were incorporated as OAR in the cost function, and both weights (for lung and spinal cord) were empirically set to 5 by using the training case dataset.
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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