It also helps to spell out clear performance standards, so that employees are judged based on how well they are meeting those standards, rather than on subjective — and potentially biased — factors.
However, the resistance bias factor is hard to quantify statistically.
The bias factor (Bf) and accuracy factor (Af) both approached 1.0 for the three surfaces evaluated.
This method is different from the cross-section adjustment method and the bias factor method.
The bias factor dependence on dislocation density and ambient temperature is presented and discussed.
The bias factor negatively affected the recovery of all three size groups almost by same proportion.
In addition, the biasing factor is also considered and the caused influence on system capacity is evaluated.
Consequently, the design obtained using the calibrated resistance factor can still miss βT if the variation in resistance bias factor has been underestimated.
Emphasis is placed on re-calibration of resistance factors at various feasibility robustness levels, with due consideration of the variation in the resistance bias factor.
Sematic features including the center-bias factor and other top-down cues are also applied as the features in the proposed stereoscopic saliency detection method.
The regression model is designed in a way that considers disagreement between raters by a constant biasing factor in measuring the AU intensity values.
