24,826 research outputs found

    Unsupervised Discovery of Phonological Categories through Supervised Learning of Morphological Rules

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    We describe a case study in the application of {\em symbolic machine learning} techniques for the discovery of linguistic rules and categories. A supervised rule induction algorithm is used to learn to predict the correct diminutive suffix given the phonological representation of Dutch nouns. The system produces rules which are comparable to rules proposed by linguists. Furthermore, in the process of learning this morphological task, the phonemes used are grouped into phonologically relevant categories. We discuss the relevance of our method for linguistics and language technology

    Static and dynamical properties of a supercooled liquid confined in a pore

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    We present the results of a Molecular Dynamics computer simulation of a binary Lennard-Jones liquid confined in a narrow pore. The surface of the pore has an amorphous structure similar to that of the confined liquid. We find that the static properties of the liquid are not affected by the confinement, while the dynamics changes dramatically. By investigating the time and temperature dependence of the intermediate scattering function we show that the dynamics of the particles close to the center of the tube is similar to the one in the bulk, whereas the characteristic relaxation time tau_q(T,rho) of the intermediate scattering function at wavevector q and distance rho from the axis of the pore increases continuously when approaching the wall, leading to an apparent divergence in the vicinity of the wall. This effect is seen for intermediate temperatures down to temperatures close to the glass transition. The rho-dependence of tau_q(T,rho) can be described by an empirical law of the form tau_q(T,\rho)=f_q(T) exp [Delta_q/(rho_p-rho)], where Delta_q and \rho_q are constants, and f_q(T) is the only parameter which shows a significant temperature dependence.Comment: 4 pages of Latex, 4 figures Pari

    Large-N Solution of the Heterotic Weighted Non-Linear Sigma-Model

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    We study a heterotic two-dimensional N=(0,2) gauged non-linear sigma-model whose target space is a weighted complex projective space. We consider the case with N positively and N^~=N_F - N negatively charged fields. This model is believed to give a description of the low-energy physics of a non-Abelian semi-local vortex in a four-dimensional N=2 supersymmetric U(N) gauge theory with N_F > N matter hypermultiplets. The supersymmetry in the latter theory is broken down to N=1 by a mass term for the adjoint fields. We solve the model in the large-N approximation and explore a two-dimensional subset of the mass parameter space for which a discrete Z_{N-N^~} symmetry is preserved. Supersymmetry is generically broken, but it is preserved for special values of the masses where a new branch opens up and the model becomes super-conformal.Comment: 34 pages, 10 figures, references adde
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