Smoothness Sample Clauses
Smoothness. After final compaction, treat the stabilized surface with a light application or flushing of water and roll with pneumatic-tired roller to create a close and uniform surface. The pneumatic roller should be fitted with a water spray system and apply light mist to tires while rolling;
Smoothness. We say that an (n, t, r)q-RSS is – m-smooth if for any s ∈ Fq, A ⊂ [n] with |A| ≤ m, any c output by Share(s), and n−|A| any c˜ such that c˜A = cA, c˜¯ ←$ F , for all PPT A it holds that | Pr[1 ← A(1 , Reconstruct(c˜))] − Pr[1 ← A(1 , u)]| is negligible in λ, where the probability is taken over the random coins of A and Reconstruct and u ←$ Fq. – m-smooth on random secrets if it is m-smooth for randomly chosen s ←$ Fq and the Definition 4 (Strong t-privacy). We say that an (n, t, r)q-RSS has strong t-privacy, if for any s ∈ Fq, A ⊂ [n] with |A| ≤ t, the projection cA of c ←$ uniformly randomly in F|A|. Share(s) is distributed Note that strong t-privacy implies t-privacy. The opposite does not necessarily hold. (To see that the opposite might not hold, imagine a Share algorithm creating shares that start with “I’m a share!”). Also note that, in case of random errors occuring, as long as there are fewer then t undisturbed shares, a strong t-private scheme actually hides the locations (and with this also the number) of errors.