Sentence examples for pose the optimization from inspiring English sources

We can now pose the optimization problem for genetic screens as follows: what is the F2-to-F1 screening ratio that minimizes the amount of work needed to screen a required number of mutagenized F1 animals, nreq.

Hence, our minimal cost problem can be expressed as (7) min C T E, E ˙ S. T. ∫ t 0 t F E t dt = E ¯ If we let F = α 1 E + α 2 E 2 + α 3 E ˙ + μ 2 and G =  E, then we can pose the optimization problem stated in Eq. (7) in a more familiar form.

The approach presented relies on (1) adopting a general modeling framework for metabolic networks: the Generalized Mass Action (GMA) representation; (2) posing the optimization task as a non-convex nonlinear programming (NLP) problem; and (3) devising an efficient solution method for globally optimizing the resulting NLP that embeds a GMA model of the metabolic network.

Therefore, the technique is highly dependent on the initial guess of the pose for the optimization which is typically specified manually.

However, the force-field-based score has a very high binding energy on and near the native pose, and the optimization on the force-field-based score results in the change of the orientation of the ligand.

Once the global stiffness and inertia matrices are obtained upon assembling all modules of the subsystems, two constrained optimization techniques are first employed: the fixed pose optimization and the global optimization inside a cube.

This further complicates the optimization problem and poses the challenge of finding the optimal dimensions for which gold nanoshells of a fixed absorption efficiency exhibit the lowest scattering.

A loop closing algorithm is then proposed based on the sequence of magnetic measurement and applied to the pose graph optimization.

The objective of pose graph optimization is to estimate the robot trajectory from the constraints of relative pose measurements.

These algorithms are associated with the method of normalized functions, are based on a combination of formal and heuristic procedures, and allow one to obtain quasi-optimal solutions after a small number of steps, thus overcoming the computational complexity posed the NP-completeness of discrete optimization problems.

Four sets of data are collected, and we compute the position estimation errors in X, Y and Z axes, respectively, by each tag. Figure 8 presents the errors distribution and the final pose with nonlinear optimization process.