Sentence examples for detecting the variance from inspiring English sources

Before designing the ANNs required for change point estimation in the process variability, a three-layered perceptron ANN was applied for detecting the variance shifts and identifying quality characteristics responsible for the out-of-control states.

In this paper, first we use an artificial neural network (ANN -based method in the literANN -baseddetecting the variance shifts as well as diagnosing the sources of variation in the methodarintheattribute processes.

In the first module, we aim to detect the variance shifts and diagnose quality characteristics responsible for out-of-control signals.

In our system, the three-dimensional (3D) object space is segmented into some distinct discrete sampling cells, and pyroelectric infrared (PIR) sensors are employed to detect the variance of the thermal flux within these cells.

This is consistent with high reproducibility across replicates and indicates that our quantitative bioinformatics approach has sufficient precision to detect the biological variance, which manifests as a much wider SD for the latter population.

The proposed approach uses a Markov chain approach to compute the statistical performance, and uses a statistical design model to design DSVSI ¯¯¯X and s charts for detecting the mean shift and variance increase.

No significant difference was detected in the variance between the four forest types with different dominant woody species.

A slight systematic difference was detected in the variance, standard deviation of the triplicates and dynamic range.

27 Although inter-relations between factors were found, no collinearity was detected as the variance inflation factor was never greater than 1.9.

After the beginning of TEA, pancreatic microcirculation improved in Group 1 (TEA) and a significant time-by-treatment interaction was detected in the variance analysis for repeated measurements (P <0.001).

Concerning the tissue oxygenation, a significant time-by-treatment interaction was detected in the variance analysis for repeated measurements (P <0.001) and when comparing the areas under the curve during the treatment interval a significantly better tissue oxygenation was found in Group 1 (Group 1 (TEA) 215 ± 64 in comparison to Group 2 (Control) 138 ± 90; P = 0.007).