Sentence examples for distribution of quantity from inspiring English sources

Using the monitoring system, we could obtain purified LiCl crystal with uniform distribution of quantity on 6 crystallization plates and high separation efficiency of over 90% at various cooling conditions.

Finally, we compared the distributions of quantity and percentage of pathway annotations transferred to genes gi (and of known pathway annotations of genes Gj) over all MaxLgi (MaxLGj) and AvgLgi (AvgLGj) levels, respectively.

(3) Oblique shock waves are induced at the intersection of the upper and downstream sections and disturb distributions of quantities in the downstream section.

Power spectral density (PSD) is a function that describes the energy content distribution of a quantity over the frequency range.

We know the distribution of this quantity, namely normal and with the aforementioned variance.

To guarantee the performance of investments, equal distribution of generation quantity for different power units became the primary task of power dispatching, which significantly promoted the development of the power industry under the conditions at that time.

These works mainly concern about how to minimize the posterior expected value of a risk function (i.e., the posterior expected risk), such as using Bayesian rule to update the probability distribution of tag quantity and adjusting the frame size.

The number of edges emanating from a node is the degree of the node and the degree distribution is the distribution of this quantity across the population [ 14].

We note that the subjects chosen within the sample may not necessarily themselves follow a normal distribution as measurement method comparison studies often select subjects that give a wide distribution of the quantity measured rather than some random selection.

BMA is a variable selection approach that takes model uncertainty into account by averaging over the posterior distribution of a quantity of interest based on multiple models, weighted by their posterior model probabilities [ 82, 83].

The propagation of the confidence intervals through to the percentage/probability of exceedance of a threshold is achieved using a Monte-Carlo approach: The parameters of Eq.  2 are randomly sampled (a thousand times) within the bootstrap distribution (95%% confidence interval), and the percentage/probability of exceedance is computed each time giving a distribution of that quantity.