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In this paper, we designed experiments and calculation to optimize the simulation of temperature distribution of light-emitting diode module.
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The experimental data was compared with those of calculations to optimize fuel-scheduling programme.
The central computer receives data from the process computers and performs calculations to optimize the performance of each chemical-processing unit.
We performed a series of calculations to optimize the parameters by maximizing the prediction accuracy.
This paper presents a calculation process to optimize the design of helical extension springs whatever the nature of the specifications.
We decided to adjust the sample size calculation and to optimize the power of the trial given the current study design, resulting in a smaller but more feasible sample size, in the light of possible slow recruitment.
The aims were to produce baseline data which would inform decisions for the main trial design (i.e. population, primary outcome, sample size calculation) and to optimize the robustness of trial processes within the study setting.
Optical design and calculation were employed to optimize the structure using a optimization program.
Then by using a direct optimization approach based on median calculation, which is to optimize each ancestral node in terms of its three or more immediate neighbors, the phylogeny and ancestral genomes could be reconstructed.
The theoretical quantum calculation was used to optimize the spatial distribution of ground state geometry (HOMO) and excited state geometry (LUMO) levels of the molecules.
Before actual applications, several numerical calculations are performed to optimize electrode and insulator sizes, and optimal design is verified by static experiments.
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