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Standard error was evaluated through the 95% confidence interval.
Tolerance to error was evaluated through the objective tasks completion scenarios.
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Accordingly, the local error was evaluated.
Experiment result shows that complex surface profile error is evaluated effectively through the proposed algorithm.
The predictive error caused by model uncertainty was evaluated through analysis of the variability of the model performance and parameters.
The coded bit-error rate (BER) performance of the proposed detection algorithm was evaluated through simulations of a MIMO system employing four transmit and four receive antennas.
Model performance was evaluated through 10,000 bootstrapped simulations, producing a mean absolute error (MAE) of 3.0 m for canopy height estimation over 30 m pixels of SRTM data.
The method was evaluated through human validation.
Fibrosis was evaluated through Sirius red staining.
Pyknosis was evaluated through DAPI stain.
Clinical severity was evaluated through HbA1c measurement.
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