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We apply some heuristic based on the characteristics of Web service when performing model checking, so verification performance is improved visibly.
This includes the establishment of the types of verification that can be performed and the importance of separating issues, such as functional verification, performance verification, and implementation verification.
We also evaluated the automatic verification performance.
However, we found that correction actually decreases the verification performance.
Rangachari's noise tracking algorithm gave the worst overall verification performance.
HINT supports networking test, protocol verification, performance evaluation, and so forth.
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Theoretically, user-specific quantizers provide better verification performances.
As expected, fusing 3D and intensity information increases verification performances.
Experimental results on the FVC2000 fingerprint and the FRGC face database show reasonably good verification performances.
Experimental results on the FVC2000 and the FRGC database show reasonably good verification performances.
As seen in the tables given above, the proposed algorithm showed better verification performances than the other methods except a few cases for the GMM-UBM method.
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