Sentence examples for subject to optimize from inspiring English sources

The pattern of these 16 connections was chosen for each subject to optimize the distribution of the active jets under the digits.

Our objective in the current paper is to develop criteria for selecting the number of untreated subjects to match to each treated subject to optimize estimation of treatment effects when M 1 matching is used.

Initially response surface statistical design (Central Composite Design CCDCD) was subjected to optimize the formulation variables of oil-in-water (O/W) nanoemulsions induced by ultrasound.

Early identification of treatment response or non-response in bipolar disorder may be beneficial to subjects to optimize clinical outcome by allowing identification of subjects that are most likely to substantially benefit from therapy.

Then we implement a nonlinear algorithm on a minimal cost multicommodity flow (MCMF) problem to optimize some control policies subject to optimal flows.

In other words, we used what the subject saw to estimate the Bayes-optimal estimate of hidden states over the experiment under a particular set of parameters and used subject responses to optimize the parameters of the perceptual and response models.

We then use Monte Carlo simulations to determine the number of untreated subjects to match to each treated subject in order to optimize estimation of treatment effects.

The objective of the subject work is to optimize different design and operating parameters of the adsorbed natural gas (ANG) system subjected to variable charge and the boundary conditions.

The objective in this study is to optimize the HWT test subject to dry condition to be one potential method in measuring rutting resistance in a laboratory.

We utilize a multi-objective genetic optimization algorithm to optimize security subject to constraints for energy consumption and minimum security level.

However, it proved to be impossible with our data from living subjects: the objective function was difficult to optimize and subject to very large estimation errors.