We performed a cluster sample analysis with a linear mixed-effects model using a reduced maximum-likelihood approach (REML) to evaluate and compare the relatively homogeneous groups and compensate for repeated observations due to the limited donor number.
Equally, it also reduced light hypoglycemia using a clinically specified maximum risk with stochastic forecasting of metabolic variation, as well as significantly reducing clinical workload compared with the current clinical standard protocol at Christchurch Hospital.
In the following, we will show that we can reduce the time required to reach collision free operation by using a smaller maximum contention window, in particular.
We designed each choice set using a maximum of five domains to reduce the cognitive burden on the respondents.
The results showed that solving the problem using HDPA reduced the maximum profit by only 0.28% on average from the solution provided HVRPTW, and the average computational time was also reduced dramatically.
Otherwise, because we form the cluster using a maximum number of shared channels, we reduce the chance of reclustering due to channel occupancy by PUs.
Free parameters were reduced to the K80 model, and α values were determined by using a maximum likelihood approach in PAUP*4.0 (Sinauer Associates, Inc. Publishers, Sunderland, MA, USA).
This program uses a maximum likelihood approach for reducing genotyping errors and provides recommendations for replications at each locus to reach a ≥95% reliability level.
A scalar is used to reduce the maximum conversion efficiency when the VPD is high enough to inhibit photosynthesis.
Under the assumption that the screening test scores follow a bivariate Gaussian distribution, conditional on disease status, we use an iterative, maximum likelihood approach to reduce the bias in the estimates of the mean, variance and correlation.
Depending upon the PEM, scalars such as temperature, VPD and soil moisture are used to reduce the maximum LUE values, e.g. through linear ramp functions [43].
