background: the purpose of this study is to demonstrate the advantages of gradient echo (gre) sequences in the detection and characterization of cerebral venous sinus thrombosis compared to conventional magnetic resonance sequences. methods: a total of 17 patients with cerebral venous thrombosis (cvt) were evaluated using different magnetic resonance imaging (mri) sequences. the mri sequences i...

Monte Carlo simulation is used to obtain estimates of the probability that all weighted scoring rules elect the same winner for large electorates under the impartial culture condition. While this probability is relatively large for three candidate elections (0.535), it decreases significantly as the number of candidates increases. The same general observations are made when considering the prob...

This work is concerned with the development and study of a minimum residual norm subspace method based on the Generalized Conjugate Residual method with inner Orthogonalization (GCRO) method that allows flexible preconditioning and deflated restarting for the solution of non-symmetric or non-Hermitian linear systems. First we recall the main features of Flexible Generalized Minimum Residual wit...

Three models were used to estimate heritabilities for milk yields at different production levels and for different years as twice the regression of daughter residual effects on dam residual effects. The denominator is the residual mean square for dams. The numerator is the difference between the residual term for sum of dam's and daughter's records and sum of residual terms for records of dams ...

The dual weighted residual method (DWR) and its localization for mesh adaptivity applied to elliptic partial differential equations is investigated. The contribution of this paper is twofold: first, we introduce a novel localization technique based on the introduction of a partition of unity. This new technique is very easy to apply, as neither strong residuals nor jumps over element edges are ...

This paper considers residual-based and randomly weighted kernel estimators for innovation densities of nonlinear autoregressive models. The weights are chosen to make use of the information that the innovations have mean zero. Rates of convergence are obtained in weighted L1-norms. These estimators give rise to smoothed and weighted empirical distribution functions and moments. It is shown tha...

In this paper we propose a method for enhancement of speech in the presence of additive noise. The objective is to selectively enhance the high SNR regions in the noisy speech in the temporal and spectral domains, without causing signiicant distortion in the resulting enhanced speech. This is proposed to be done at three diierent levels: (a) At the gross level, by identifying the regions of spe...

In this work we calculate the eigenvalues obtained by preconditioning the discrete Helmholtz operator with Sommerfeld-like boundary conditions on a rectilinear domain, by a related operator with boundary conditions that permit the use of fast solvers. The main innovation is that the eigenvalues for two and three-dimensional domains can be calculated exactly by solving a set of one-dimensional e...

In this paper we show how the properties of integral operators and their approximations are reeected in the performance of the GMRES iteration and how these properties can be used to smooth the GMRES iterates, thereby strengthening the norm in which convergence takes place. The smoothed iteration has very similar properties to Broyden's method and we present some comparisons of the two methods ...