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The paper presents a new approach to spotting a particular sound (keyword) in an acoustic stream. The approach is based on hierarchical processing where equally-sampled posterior probabilities of phoneme classes are estimated first, followed by matched fil ...
We build wavelet-like functions based on a parametrized family of pseudo-differential operators Lv that satisfy some admissibility and scalability conditions. The shifts of the generalized B-splines, which are localized versions of the Green func ...
In this paper, we discuss a framework for the distributed compression of vector sources, based on our previous work on distributed transform coding. In particular, our goal is to develop a strategy of first applying a suitable distributed Karhunen-Loeve tr ...
We present a comprehensive first-principles study of the ballistic transport properties of low-dimensional nanostructures such as linear chains of atoms (Al, C) and carbon nanotubes in the presence of defects. An approach is introduced where quantum conduc ...
In this paper we present the design and evaluate the performance of an autonomic workflow execution engine. Although there exist many distributed workflow engines, in practice, it remains a difficult problem to deploy such systems in an optimal configurati ...
Gene therapy by use of integrating vectors carrying therapeutic transgene sequences offers the potential for a permanent cure of genetic diseases by stable vector insertion into the patients' chromosomes. However, three cases of T cell lymphoproliferative ...
This thesis is dedicated to the study of a new framework linking image segmentation and shape recognition processes in the image processing domain. Image segmentation process aims at separating an image into homogenous regions, the homogeneity measure depe ...
We consider the following integer feasibility problem: Given positive integer numbers a0, a1,&mellip;,an with gcd(a1,&mellip;,an) = 1 and a = (a1,&mellip;,an), does there exist a ...
This paper presents an application of the general sample-to-object approach to the problem of invariant image classification. The approach results in defining new SVM kernels based on tangent vectors that take into account prior information on known invari ...
We derive a nonlinear stabilized Galerkin approximation of the Laplace operator for which we prove a discrete maximum principle on arbitrary meshes and for arbitrary space dimension without resorting to the well-known acute condition or generalizations the ...
