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This algorithm was one of the firsts to achieve linear pattern matching efficiency, taking only O(N) time to scan a string of size N. Notwithstanding, it results in a randomized algorithm, since h(P) = h(S[ i.. i + L - 1]) does not constitute a guarantee that P = S[ i.. i + L - 1] and so, an additional check is needed to verify if P = S[ i.. i + L - 1].
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The node does not know which old key in the chain is used by the base station for encrypting the recovery information (since it neither knows the number of packets it has missed, nor the number chosen by the base station); consequently the decryption in step that uses the node's stored key may be unsuccessful (i.e., yield nonsense), and step is needed to verify this by checking the contained hash.
More work will be needed to verify that impression.
Obviously, further studies are needed to verify these hypotheses.
Further work would be needed to verify this.
Future studies will be needed to verify this hypothesis.
However, further studies are needed to verify this finding.
This information may be needed to verify your identity.
However, as the complexity of scientific codes increases, extra checks are needed to monitor impacts to dependent models and to verify system constraints.
However, further reliability checks of the CDAT with more coders conducted with more science classroom discourse are needed to further verify the reliability.
Recently, I needed to verify New York's exact size for an article I was writing.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.
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CEO of Professional Science Editing for Scientists @ prosciediting.com