Sentence examples for error difference from inspiring English sources

To measure error and validate the controller in the implemented system, we grew S. cerevisiae in duplicate at four different ODs and quantified the average, maximum, and 95th percentile tracking error (difference between set OD and measured OD) over a period of 22 h.

The root mean square (RMS) error difference between the two models and measured station data were calculated.

Individual training day analyses also indicated a significant group effect in error difference (T2 T1) on Day 2 (F[1,13] = 6.824, p = 0.0215, ANOVA) relative to sham (Fig. 2h, right).

The feature set comprising of prediction error, difference between the median value and the center pixel; the median value in the kernel under operation has been used during this study.

Similar to the SDV and sham groups, the CCK-SAP group was also impaired in this task relative to SAP controls, with repeated-measures ANOVA analyses of average error difference (T2 T1) revealing a significant group main effect across the 5 training days (F[1,13] = 8.66, p = 0.0114) (Fig. 2h, left).

For Barnes maze, analyses included all groups (sham, SDV, SAP, and CCK-SAP) and revealed that (1) dorsal HPC BDNF levels are negatively correlated with average error difference (T2 T1) (F[1,28] = 4.211, R2 = 0.1307, p = 0.0496) and (2) dorsal HPC DCX levels showed a trend toward significant correlation with Barnes performance (F[1,29] = 3.546, R2 = 0.1089, p = 0.0698).

The root-mean-square (RMS) error differences for a few selected stations are presented in this paper.

Based on the error differences, the result obtained justifies the potential of the NN technique for the predictions of M 3000 F2 values on a global scale.

No significant error differences were observed between the trained versus untrained limbs, although model parameter values were significantly altered with training.

Any interaction or error differences did not reach statistical significance (F < 1).

These comparable sets will be very close numerically, although not identical because of round-off error differences between the two parity generation processes.