Sentence examples for detection of mode from inspiring English sources

An interesting result of this work is the detection of mode localization in the "tuned" periodic system, a result with no counterpart in existing theories on linear mode localization.

Then, the basic characteristics of AWCD-MAA on abnormality detection of mode shapes, e.g., crack localization, crack quantification, noise immunity, etc., are investigated based on an analytical crack model of cantilever beams using linear elastic fracture mechanics.

By making the comparison between the in-plane and out-of-plane wave vector components the detection of mode conversion is possible, allowing for superior and reliable damage detection.

Our approach is based on the detection of mode mixing by a test of stationarity on the first IMF, and on the extraction of the part of the first IMF that corresponds to pure noise.

Correct Detection of Mode Effects = true positive detection of mode DIF among items simulated with mode DIF; AUC = area under the ROC curve; CI = 95% confidence interval; IRT = item response theory model used to generate response data and parameters used in CAT; CAT item usage = number of times a given item was administered by CAT divided by 100; * p <.05; ** p <.01.

Incorrect detection of mode effects = False positive identification of DIF due to mode among items not simulated with mode DIF; AUC = area under the ROC curve; CI = 95% confidence interval; IRT = item response theory model used to generate response data and parameters used in CAT; CAT item usage = number of times a given item was administered by CAT divided by 100; * p <.05; ** p <.01.

(a) Accuracy of outlier detection of mode-finder compared to 6D LMS.

In this study, several factors were directly examined with respect to detection of mode-of-administration DIF, including DIF size, percentage of DIF items, and mean difference in trait level between modes, item response model, and analytic procedure.

So, we propose in this section to extend, the detection of a mode m at a pixel position, to a range of modes.

Our approach supports the automated detection of remaining mode confusion problems.

In the proposed approach, three steps are performed on-line: Detection of current mode, Mapping switching and Changing voltage/frequency levels of cores.