Sentence examples for distributions variability from inspiring English sources

Based on a set of carefully designed experiments and analyses, we have concluded that variability in virtual topologies' hop-distance distributions, variability in network traffic distributions, and pattern matching between distance and traffic matrices are major factors in determining the effectiveness of optimal node assignments.

Model refinement with regard to i.v. Pop-PBPK models offer an opportunity to examine the effects of CL and distribution variability in the absence of absorption, a notoriously variable process.

A sensitivity analysis is performed on one case study to evaluate the distribution of the response variable from each method in the presence of parameter and initial seed distribution variability.

Scale independent fractal attributes may be useful for characterizing intrinsic particle-size distribution variability.

Compared to a single paired-plate capacitance sensor, the ECT system also provided images, through its tomography function, that displayed permittivity distribution variability throughout bulk biomass samples.

It is an open problem because of ambiguous boundaries, large variation in intensity distribution, variability of liver geometry from patient to patient and presence of noise.

Modern computer based systems are characterized by several complexity dimensions: a non-exhaustive list includes scale, architecture, distribution, variability, flexibility, dynamics, workloads, time constraints, dependability, availability, security, performances.

They had analyzed the extensive distribution, variability and diversity of helitrons in the maize genome.

The exact distribution is overdispersed relative to the binomial distribution: variability in the exact distribution is larger than in the binomial distribution.

Different absorption (first-order and first-order with lag-time absorption), distribution (one-, two-, and three-compartment distribution), variability (between-subject variability) and residual error (additive, proportional, and combined additive and proportional errors on log-transformed data) models were considered.

The MDC, derived using the sample distribution, variability, and test-retest reliability of the APSA subscales, indicate whether a difference between baseline and a follow up visit represents a true difference in cognitive impairment.