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Parameter prediction methods can avoid experimental effort altogether.

All these three different methods can avoid the assumption of the distribution regularities of unknown overall material parameters appeared in existing papers.

Therefore, such methods can avoid some of the difficulties involved in the pixel and bitstream-based methods[178].

Furthermore, in order to evaluate which methods can avoid large misestimation of the prediction error degree, we used MSE in the experiments.

These two methods can avoid the insufficiency of the traditional two-dimensional model that is used to characterize the relationships between properties and structures, and have clear physical significance and provide rich information about the molecular field energy [26].

Second, EMA methods can avoid biases inherent in retrospective recall of alcohol use or momentary states (e.g., urges, craving, affect).

Furthermore, the heuristic search strategy in Markov blanket methods can avoid the time-consuming training process as in SVM and random forests.

The optical microscopy measurement results show that the present method can avoid both missed detections and false positives.

The solid-state inoculation method can avoid both the intensive labor requirement and costly seed fermenter needed with the latter approach.

This method can avoid the misdiagnosis caused by extracting non-fault features.

This simplified method can avoid the complex computation in SFEM yet achieve good accuracy.

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