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The standard approach to speaker verification is to extract cepstral features from the speech spectrum and model them by generative or discriminative techniques. We propose a novel approach where a set of client-specific binary features carrying maximal di ...
Model-based statistical analysis of functional magnetic resonance imaging (fMRI) data relies on the general linear model and statistical hypothesis testing. Due to the large number of intracranial voxels, it is important to deal with the multiple compariso ...
We present a novel technique to detect traffic anomalies based on network flow behavior in different traffic features. Based on the observation that a network has multiple behavior modes, we estimate the modes in each feature component and extract their mo ...
Wyner-Ziv (WZ) video coding is an emerging video coding paradigm based on two major Information Theory results: the Slepian-Wolf and Wyner-Ziv theorems. One of the most interesting and used WZ video coding architectures makes use of a feedback channel (FC) ...
The image identification problem consists in identifying all the equivalent forms of a given reference image. An image is equivalent to the reference image, if the former results from the application of an image operator (or a composition of image operator ...
In Switzerland, the current code for structural concrete published in 2003 privileged an incremental approach for design of new members or for assessment of existing structures with respect to a number of topics (shear, buckling, reinforcement detailing th ...
Because human leukocyte antigen (HLA) associations with various infectious diseases have recently been reported, we examined the role of HLA class I alleles in the development of progressive multifocal leukoencephalopathy (PML) or its outcome in 152 patien ...
We present Netscope, a tomographic technique that infers the loss rates of network links from unicast end-to-end measurements. Netscope uses a novel combination of first- and second-order moments of end-to-end measurements to identify and characterize the ...
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Significance testing is a crucial step in metabolic biomarker recovery from the metabolome-wide latent variables computed by multivariate statistical analysis. In this study we propose an algorithm based on the landscape of the covariance/correlation ratio ...
A classification methodology for the automatic detection of start- and endpoints of chemical and biotechnological reaction systems from spectral reaction data is proposed. In the calibration phase, several batch experiments must be conducted covering the e ...