University of Paderborn

About: University of Paderborn is a education organization based out in Paderborn, Nordrhein-Westfalen, Germany. It is known for research contribution in the topics: Computer science & Context (language use). The organization has 6684 authors who have published 16929 publications receiving 323154 citations.

A New Class of Weak Solutions of the Navier–Stokes Equations with Nonhomogeneous Data

Abstract: We investigate a class of weak solutions, the so-called very weak solutions, to stationary and nonstationary Navier–Stokes equations in a bounded domain \(\Omega \subseteq \mathbb{R}^{3}\). This notion was introduced by Amann [3], [4] for the nonstationary case with nonhomogeneous boundary data leading to a very large solution class of low regularity. Here we are mainly interested in the investigation of the “largest possible” class of solutions u for the more general problem with arbitrary divergence k = div u, boundary data g = u|∂Ω and an external force f, as weak as possible, but maintaining uniqueness. In principle, we will follow Amann’s approach.

Real-Time Facial Expression Recognition Using a Fuzzy Emotion Model

Abstract: This paper presents the fuzzy video based emotion recognition system VISBER, that allows to analyze facial expressions in video sequences. In order to process images in real-time a tracking mechanism is used for face localization. The fuzzy classification itself analyzes the deformation of a face separately in each image. In contrast to most existing approaches, also blended emotions with varying intensities as proposed by psychologists can be handled. For this purpose we propose a fuzzy emotion model which is generally applicable for also for other emotion recognition solutions. Furthermore, VISBER supports the automatic adaptation to the characteristics of individual human faces by a short training phase that can be done before the emotion recognition starts.

Low Secret Exponent RSA Revisited

Abstract: We present a lattice attack on low exponent RSA with short secret exponent d = Nδ for every δ 0.265. Our method, as well as the method by Boneh and Durfee, is heuristic, since the method is based on Coppersmith's approach for bivariate polynomials. Coppersmith [6] pointed out that this heuristic must fail in some cases. We argue in this paper, that a (practically not interesting) variant of the Boneh/Durfee attack proposed in [4] always fails. Many authors have already stressed the necessity for rigorous proofs of Coppersmith's method in the multivariate case. This is even more evident in light of these results.

Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation

Abstract: In this paper, we present a novel blocking matrix and fixed beamformer design for a generalized sidelobe canceler for speech enhancement in a reverberant enclosure. They are based on a new method for estimating the acoustical transfer function ratios in the presence of stationary noise. The estimation method relies on solving a generalized eigenvalue problem in each frequency bin. An adaptive eigenvector tracking utilizing the power iteration method is employed and shown to achieve a high convergence speed. Simulation results demonstrate that the proposed beamformer leads to better noise and interference reduction and reduced speech distortions compared to other blocking matrix designs from the literature.