3,101 research outputs found

    A New Look at Onset Transfer in Indo-European Reduplication: Dissimilation of Consonant Clusters

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    This is a revised version of my paper presented in a special session on reduplication at the Fall Conference of Language Research Institute, Hankuk University of Foreign Studies (Nov. 1, 2019).A new typology of onset cluster reduplication is proposed in Indo-European languages on three premises: 1) Partial reduplication in Indo-European copies the onset cluster in toto; 2) The canonical form of Grassmanns Law type of dissimilation occurs between two complex segments that are sufficiently similar; 3) Such dissimilation of complex segments typically occurs preferentially to an obstruent plus resonant (TR) cluster and to a sibilant plus obstruent (ST) cluster only as a generalization of the preferential rule. The analysis shows that, of the four logically possible rule combinations in the reduplication of TR- vs. ST-initial roots, only three actually occur in Indo-European languages. The fourth type, in which an ST cluster is reduced but a TR cluster remains, is excluded, as it violates the preferential order of dissimilation of consonant clusters. This paper also explains why Sanskrit and Old Irish reduce the ST-initial clusters differently. If the ST cluster acts as a complex segment, the more sonorant S drops, as in the Sanskrit perfect stem ta-stambh- prop, but if it acts as a consonant cluster, the less sonorant T drops, as in the Old Irish preterit stem se-scaind- spring off. This analysis offers a more coherent typology than Zukoffs (2017), which does not properly explain the acrossthe- board C2-copying, a pattern predicted to occur by his permutation of constraints, yet unattested in Indo-European languages and universally nonexistent

    Continuous multibiometric authentication for online exam with machine learning

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    Multibiometric authentication has been received great attention over the past decades with the growing demand of a robust authentication system. Continuous authentication system verifies a user continuously once a person is login in order to prevent intruders from the impersonation. In this study, we propose a continuous multibiometric authentication system for the identification of the person during online exam using two modalities, face recognition and keystrokes. Each modality is separately processed to generate matching scores, and the fusion method is performed at the score level to improve the accuracy. The EigenFace and support vector machine (SVM) approach are applied to the facial recognition and keystrokes dynamic accordingly. The matching score calculated from each modality is combined using the classification by the decision tree with the weighted sum after the score is split into three zones of interes
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