2 resultados para shearing interference

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Statistical learning can be used to extract the words from continuous speech. Gómez, Bion, and Mehler (Language and Cognitive Processes, 26, 212–223, 2011) proposed an online measure of statistical learning: They superimposed auditory clicks on a continuous artificial speech stream made up of a random succession of trisyllabic nonwords. Participants were instructed to detect these clicks, which could be located either within or between words. The results showed that, over the length of exposure, reaction times (RTs) increased more for within-word than for between-word clicks. This result has been accounted for by means of statistical learning of the between-word boundaries. However, even though statistical learning occurs without an intention to learn, it nevertheless requires attentional resources. Therefore, this process could be affected by a concurrent task such as click detection. In the present study, we evaluated the extent to which the click detection task indeed reflects successful statistical learning. Our results suggest that the emergence of RT differences between within- and between-word click detection is neither systematic nor related to the successful segmentation of the artificial language. Therefore, instead of being an online measure of learning, the click detection task seems to interfere with the extraction of statistical regularities.

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New simpler formulae are derived for the shear of a pair of material elements within the context of infinitesimal strain and finite strain. Also, new formulae are derived for shear stress based on the (symmetric) Cauchy stress and for the rate of shear of a pair of material elements within the rate of strain theory. These formulae are exploited to obtain results and to derive new simpler proofs of familiar classical results. In particular, a very simple short derivation is presented of the classical result of Coulomb and Hopkins on the maximum orthogonal shear stress. © 1992.