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Preferable substrate(s) for most candidate ROs could be predicted using the RHObase substrate prediction module (Fig. 4).

QoS of a system operating over fading channels can be predicted using the outage probability metric.

Cutting force, tool life and many other performance measures can be predicted using the proposed methodology.

Crystallizer performance can be predicted using the population balance concept, along with kinetic and solubility data.

These require several design parameters, which can be predicted using the correlations.

A shift in the peak position can be predicted using the Erhenfest formula.

The crack locations could be predicted using the Tsai Wu failure criterion.

In other words, missing values do not depend on the missing data, yet can be predicted using the observed data.

The degradation of the speech sample can be predicted using the PESQ algorithm with subjective opinion score.

The direct monetary costs of administration can be predicted using the algorithm developed by Tetteh and Morris [4].

Clearly, when the maximum flexural crack width is less than 1.0 mm, it can be predicted using the selected specifications.

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