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An optimization of the flapping kinematics of the wing has been led, in order to maximize the mean lift and thus the payload.
The "optimum" codebook design criterion is to maximize the mean squared inner product (MSIP) of the beamforming vector and the codebook vectors.
To deal with uncertain parameters effectively, a novel multi-objective robust possibilistic programming approach is developed which is able to maximize the mean value of supply chain performance and control the optimality as well as feasibility robustness.
The theoretical approach applied an engineering bio-thermodynamic approach recently developed in order to obtain a physical mathematical model that calculated the frequency of the field able to maximize the mean entropy changes as a function of cellular parameters.
One of the objective functions is the maximization of the MOS-based utility, according to which the rate adaptation is done to maximize the mean MOS (mean user-perceived quality).
We expect descriptive representative conformers may minimize the mean of the squared distance of the clique within clusters (MSQw) and to maximize the mean of the squared distance of the clique between the clusters (MSQb).
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Drawing on IP in language learning more specifically, we aimed to maximize the means through which opportunities for attentional manipulation (Skehan 1998) could take place.
We determine the number of cells to be scanned for maximizing the mean user throughput within this setting.
Thus, we were interested in finding ideal intervals for the tested parameters that could simultaneously minimize the mean quantization error, while maximizing the mean neuron utility.
So we can conclude the least energy solutions of system (1.1) concentrate at a point of the boundary, which maximizes the mean curvature of the boundary of Ω.
We conclude that the least energy solutions of the system concentrate at the point of boundary, which maximizes the mean curvature of ∂ Ω.
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