Sentence examples for system order detection from inspiring English sources

The AIC system order detection method (Additional file 2) was employed to prune false-positive PPIs to obtain real PPI networks of normal and cancer cells: in other words, we used the reverse engineering method to construct the PPI networks of normal and cancer cells.

The AIC system order detection method (Supplementary Materials S.2) is employed to prune the false positive PPIs to obtain the real PPI networks of normal and cancer cells; that is, we use the so-called reverse engineering method to construct PPI networks of normal and cancer cells.

The AIC system order detection method (Supplementary Materials S.2) was used to prune false-positive PPIs to obtain actual PPI networks of normal and cancer cells; that is, we used the so-called reverse engineering method to construct PPI networks of normal and cancer cells.

The order used by the adversary is the correct system order, p = 25 a Detection ratio for the single-watermark approach.

Finally, we prune away the insignificant regulatory genes by AIC model order detection method in system identification [ 22] to refine the gene regulatory network of inflammatory response to bacterial endotoxin.

Fig. 10 Numeric simulation results using the single- and multi-watermark detection schemes with the same performance loss, different adversary system order, and a window size equal to 200. a Detection ratio regarding single-watermark for systems of order ten.

b Detection ratio regarding multi-watermark for systems of order 25. a Detection ratio function with respect to the single-watermark for systems of order 25 against a parametric cyber-physical adversary using different adversary system order.

b Detection ratio function with respect to the multi-watermark for systems of order 25 against a parametric cyber-physical adversary using different adversary system order.

Since USPs are fully integrated into the health care system in order to avoid detection, they can provide insight into the entire patient experience from start (walking in the front door) to finish (walking out the front door)—and therefore the core set of health care system variables that may affect quality of care, patient activation, patient safety, and patient outcomes more generally.

Therefore in order to train a system for detection of neonatal seizures, it is necessary to know the channels involved in the seizure.

This analysis of eligibility criteria requirements for the Medication Profile has focused on the medication specific data elements that the profile would need to contain in order to support the systems mediated detection of suitable subjects for protocol feasibility testing and patient recruitment.