Sentence examples for sensor discrepancy from inspiring English sources

Despite this safety barrier, there was one episode of unexplained asymptomatic hypoglycemia at 0500 h, which could not be attributed to sensor discrepancy or to the MPC advice, because only 0.4 units of insulin was infused over the preceding 6 h.

Moreover, Boyne et al. addressed the issue of random inter-sensor time discrepancies, which were quantitatively similar to physiological time delays, when comparing measurements of two subcutaneous sensors in the same individual [32].

His associates claimed that, with error rates in the 10-20 perange range, discrepancies in sensor results would ultimately have a negative impact on the league's image.

For a well studied acid base reaction, the reaction enthalpy measured using this new heat-flux sensor had only a 5% discrepancy with the standard value, showing the efficiency of the new thin-film device.

Additional calibrations for discrepancy between the sensor and venous glucose were not done.

The MPC algorithm compensated for discrepancies between the sensor and reference glucose level during hypoglycemia by suspending insulin delivery when sensor glucose values fell <80 mg/dL.

In Section 4, the proposed method is evaluated with a realistic application scenario and is analyzed with nonideal problems such as the discrepancy between approximated and actual identification sensor coverage and variance of actual identification sensor coverage.

The reason for this strikingly different behavior is unclear, but one way to resolve this discrepancy is to develop alternative FRET sensors based on a different binding mechanism.

The discrepancy between the actual coverage by the identification sensor and the approximated coverage by the visual sensor may generate cases where the conditions are not satisfied.

We also identify more association problems with the discrepancy between the actual coverage by the identification sensor and the approximated coverage by the visual sensor and present a coverage adjustment scheme using the object dynamics.

Any residual discrepancies between the observed and modelled sensor glucose values are then assumed to be normally distributed with mean zero and with an unknown variance (to be estimated) that also varies between both individuals and calibration periods.