1,856 research outputs found
How Has Hospital Consolidation Affected the Price and Quality of Hospital Care?
Provides an overview of the wave of hospital consolidation in the 1990s and reviews the literature on its effects on the prices, costs, and quality of inpatient care. Analyzes the studies' findings and discusses implications for policy makers
Factor analysis modelling for speaker verification with short utterances
This paper examines combining both relevance MAP and subspace speaker adaptation processes to train GMM speaker models for use in speaker verification systems with a particular focus on short utterance lengths. The subspace speaker adaptation method involves developing a speaker GMM mean supervector as the sum of a speaker-independent prior distribution and a speaker dependent offset constrained to lie within a low-rank subspace, and has been shown to provide improvements in accuracy over ordinary relevance MAP when the amount of training data is limited. It is shown through testing on NIST SRE data that combining the two processes provides speaker models which lead to modest improvements in verification accuracy for limited data situations, in addition to improving the performance of the speaker verification system when a larger amount of available training data is available
Cross likelihood ratio based speaker clustering using eigenvoice models
This paper proposes the use of eigenvoice modeling techniques with the Cross Likelihood Ratio (CLR) as a criterion for speaker clustering within a speaker diarization system. The CLR has previously been shown to be a robust decision criterion for speaker clustering using Gaussian Mixture Models. Recently, eigenvoice modeling techniques have become increasingly popular, due to its ability to adequately represent a speaker based on sparse training data, as well as an improved capture of differences in speaker characteristics. This paper hence proposes that it would be beneficial to capitalize on the advantages of eigenvoice modeling in a CLR framework. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, resulting in a 35.1% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system
On the taxonomic position of Tanacetum funkii (Anthemideae, Compositae)
In order to clarify the taxonomic position of the enigmatic SE Spanish endemic
Tanacetum funkii Sch. Bip. ex Willk., a phylogenetic analysis based on nrDNA
ITS sequence variation of representatives of Anthemideae (Compositae) was
carried out together with morphological analyses of the type material. The
observation of nearly identical (1 bp difference) sequences of ITS1 and ITS2
in T. funkii and Anthemis cotula L., along with the joint possession of a
conical receptacle and subulate receptacular scales, argue for the
conspecificity of these two taxa. As a consequence, T. funkii is transferred
to the genus Anthemis L. and placed in the synonymy of Anthemis cotula, and a
lectotype is designated
Weighted LDA techniques for I-vector based speaker verification
This paper introduces the Weighted Linear Discriminant Analysis (WLDA) technique, based upon the weighted pairwise Fisher criterion, for the purposes of improving i-vector speaker verification in the presence of high intersession variability. By taking advantage of the speaker discriminative information that is available in the distances between pairs of speakers clustered in the development i-vector space, the WLDA technique is shown to provide an improvement in speaker verification performance over traditional Linear Discriminant Analysis (LDA) approaches. A similar approach is also taken to extend the recently developed Source Normalised LDA (SNLDA) into Weighted SNLDA (WSNLDA) which, similarly, shows an improvement in speaker verification performance in both matched and mismatched enrolment/verification conditions. Based upon the results presented within this paper using the NIST 2008 Speaker Recognition Evaluation dataset, we believe that both WLDA and WSNLDA are viable as replacement techniques to improve the performance of LDA and SNLDA-based i-vector speaker verification
Porcelain aorta does not mean inoperability but needs special strategies
Porcelain aorta is not an absolute contraindication for aortic valve and/or coronary bypass grafting but it requires a special strategy and individualized approach to minimize the risk of embolic complications and technical problems during opening and/or closing the aortotomy.
Keywords: Aortic valve replacement; Coronary bypass grafting; Hypothermic circulatory arrest; Porcelain aorta; Xeno-pericardial patc
Optimized imaging using non-rigid registration
The extraordinary improvements of modern imaging devices offer access to data
with unprecedented information content. However, widely used image processing
methodologies fall far short of exploiting the full breadth of information
offered by numerous types of scanning probe, optical, and electron
microscopies. In many applications, it is necessary to keep measurement
intensities below a desired threshold. We propose a methodology for extracting
an increased level of information by processing a series of data sets
suffering, in particular, from high degree of spatial uncertainty caused by
complex multiscale motion during the acquisition process. An important role is
played by a nonrigid pixel-wise registration method that can cope with low
signal-to-noise ratios. This is accompanied by formulating objective quality
measures which replace human intervention and visual inspection in the
processing chain. Scanning transmission electron microscopy of siliceous
zeolite material exhibits the above-mentioned obstructions and therefore serves
as orientation and a test of our procedures
By-passing the Kohn-Sham equations with machine learning
Last year, at least 30,000 scientific papers used the Kohn-Sham scheme of
density functional theory to solve electronic structure problems in a wide
variety of scientific fields, ranging from materials science to biochemistry to
astrophysics. Machine learning holds the promise of learning the kinetic energy
functional via examples, by-passing the need to solve the Kohn-Sham equations.
This should yield substantial savings in computer time, allowing either larger
systems or longer time-scales to be tackled, but attempts to machine-learn this
functional have been limited by the need to find its derivative. The present
work overcomes this difficulty by directly learning the density-potential and
energy-density maps for test systems and various molecules. Both improved
accuracy and lower computational cost with this method are demonstrated by
reproducing DFT energies for a range of molecular geometries generated during
molecular dynamics simulations. Moreover, the methodology could be applied
directly to quantum chemical calculations, allowing construction of density
functionals of quantum-chemical accuracy
An Upper Limit on the Reflected Light from the Planet Orbiting the Star tau Bootis
The planet orbiting tau Boo at a separation of 0.046 AU could produce a
reflected light flux as bright as 1e-4 relative to that of the star. A spectrum
of the system will contain a reflected light component which varies in
amplitude and Doppler-shift as the planet orbits the star. Assuming the
secondary spectrum is primarily the reflected stellar spectrum, we can limit
the relative reflected light flux to be less than 5e-5. This implies an upper
limit of 0.3 for the planetary geometric albedo near 480 nm, assuming a
planetary radius of 1.2 R_Jup. This albedo is significantly less than that of
any of the giant planets of the solar system, and is not consistent with
certain published theoretical predictions.Comment: 5 pages, 1 figure, accepted by ApJ Letter
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