Nowadays, software designers attempt to employ design patterns in software design phase, but design patterns may be not used in the implementation phase.
They employ pattern-recognition receptors (PRRs) for sensitive and rapid detection of the potential danger caused by microbes and pests.
Our methodology takes the principle of encapsulation several steps further, by employing patterns not only for the incorporation of security features (via security solution frames), but also for the modeling of threats, and even as part of its process.
TextRunner is extraction pattern-based, but rather than employing patterns tuned to a few selected relations, it uses a range of patterns obtained automatically from a syntactically parsed training corpus, weighted via Bayesian machine learning methods to extract miscellaneous relations sentence-by-sentence from text.
To test this, we performed kinase restricted pattern searches using Scanprosite [47], employing patterns consisting of only the most weighted amino acids from tables 1 and 3 for c-Raf, namely, [IKRV]-[LPR]-[GPR]-[ST]-[AILNPV]-[AGLR]-[AGIKR] and MAP3K8, namely, [FIK]-[AFHKQ]-[AFIKV]-[ST]-[AFGV]-[IKR]-[AHKLW] and found 33 and 6 hits respectively.
It employs pattern recognition receptors (PRRs) to detect a diverse range of pathogen-associated molecular patterns (PAMPs).
Many previous efforts have addressed emotion recognition by employing pattern recognition techniques using segmental and/or supra-segmental information obtained from speech [6, 16 26].
Basically, the system employs pattern-based encoding at the transmitter and a wavelet-preprocessed artificial neural network based decoder at the receiver.
We focus on the pivotal SiGe/Si 001) system employing patterned Si substrates at the micrometre-size scale to address the distribution of threading and misfit dislocations within the heterostructures.
