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Search Results: 1 - 10 of 6714 matches for " Tom Pustelnik "
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Performance of the QuickVue Influenza A+B Rapid Test for Pandemic H1N1 (2009) Virus Infection in Adults
Wolfgang Poeppl, Harald Herkner, Heinz Burgmann, Tom Pustelnik, Gerhard Mooseder, Theresia Popow-Kraupp, Monika Redlberger-Fritz
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0028089
Abstract: To investigate the diagnostic accuracy of the QuickVue? Influenza A+B rapid test we conducted a prospective observational study in which this rapid test was compared with a real-time reverse transcription polymerase chain reaction (RT-PCR) for pandemic influenza A H1N1 (2009) infection in Austrian adults. The sensitivity, specificity, and positive and negative predictive values of the QuickVue test compared with the RT-PCR were 26% (95% CI 18–35), 98% (95% CI 92–100), 94% (95% CI 80–99) and 50% (95% CI 42–58), respectively. The prevalence of pandemic H1N1 (2009) virus infection among the 209 patients included in the study was 57%. Our data suggest that a positive QuickVue test provides considerable information for the diagnosis of pandemic influenza A H1N1 (2009) virus infection in young adults but that a negative QuickVue test result should, if relevant for patient management or public health measures, be verified using PCR.
Removal of a Degraded Concrete Layer with Emphasis on the Surface Optimization Before Application of Repair Material
Eva Janurova,Jan Pustelnik,Libor Hlavac
Advances in Electrical and Electronic Engineering , 2012,
Abstract: This contribution is concerned with the modelling of destructive effects of a high-velocity water jet, used as a tool for preparation of surfaces during reconstructions, on a degraded layer of concrete. The destruction action of a water jet on model material surfaces with artificially prepared degraded layers was studied both theoretically and experimentally. The tests were designed so their results could be consequently used for breaking of concrete during repairs of concrete constructions damaged by gaseous carbon and sulphur oxides, water during phase changes and chemical defrosting substances. The result is the determination of evaluation methodology of degraded and subsequently finished concrete surfaces.
Nested iterative algorithms for convex constrained image recovery problems
Caroline Chaux,Jean-Christophe Pesquet,Nelly Pustelnik
Mathematics , 2008,
Abstract: The objective of this paper is to develop methods for solving image recovery problems subject to constraints on the solution. More precisely, we will be interested in problems which can be formulated as the minimization over a closed convex constraint set of the sum of two convex functions f and g, where f may be non-smooth and g is differentiable with a Lipschitz-continuous gradient. To reach this goal, we derive two types of algorithms that combine forward-backward and Douglas-Rachford iterations. The weak convergence of the proposed algorithms is proved. In the case when the Lipschitz-continuity property of the gradient of g is not satisfied, we also show that, under some assumptions, it remains possible to apply these methods to the considered optimization problem by making use of a quadratic extension technique. The effectiveness of the algorithms is demonstrated for two wavelet-based image restoration problems involving a signal-dependent Gaussian noise and a Poisson noise, respectively.
Parallel Proximal Algorithm for Image Restoration Using Hybrid Regularization -- Extended Version
Nelly Pustelnik,Caroline Chaux,Jean-Christophe Pesquet
Mathematics , 2009,
Abstract: Regularization approaches have demonstrated their effectiveness for solving ill-posed problems. However, in the context of variational restoration methods, a challenging question remains, which is how to find a good regularizer. While total variation introduces staircase effects, wavelet domain regularization brings other artefacts, e.g. ringing. However, a compromise can be found by introducing a hybrid regularization including several terms non necessarily acting in the same domain (e.g. spatial and wavelet transform domains). We adopt a convex optimization framework where the criterion to be minimized is split in the sum of more than two terms. For spatial domain regularization, isotropic or anisotropic total variation definitions using various gradient filters are considered. An accelerated version of the Parallel ProXimal Algorithm is proposed to perform the minimization. Some difficulties in the computation of the proximity operators involved in this algorithm are also addressed in this paper. Numerical experiments performed in the context of Poisson data recovery, show the good behavior of the algorithm as well as promising results concerning the use of hybrid regularization techniques.
On-the-fly Approximation of Multivariate Total Variation Minimization
Jordan Frecon,Nelly Pustelnik,Patrice Abry,Laurent Condat
Mathematics , 2015,
Abstract: In the context of change-point detection, addressed by Total Variation minimization strategies, an efficient on-the-fly algorithm has been designed leading to exact solutions for univariate data. In this contribution, an extension of such an on-the-fly strategy to multivariate data is investigated. The proposed algorithm relies on the local validation of the Karush-Kuhn-Tucker conditions on the dual problem. Showing that the non-local nature of the multivariate setting precludes to obtain an exact on-the-fly solution, we devise an on-the-fly algorithm delivering an approximate solution, whose quality is controlled by a practitioner-tunable parameter, acting as a trade-off between quality and computational cost. Performance assessment shows that high quality solutions are obtained on-the-fly while benefiting of computational costs several orders of magnitude lower than standard iterative procedures. The proposed algorithm thus provides practitioners with an efficient multivariate change-point detection on-the-fly procedure.
Relaxing Tight Frame Condition in Parallel Proximal Methods for Signal Restoration
Nelly Pustelnik,Jean-Christophe Pesquet,Caroline Chaux
Computer Science , 2011, DOI: 10.1109/TSP.2011.2173684
Abstract: A fruitful approach for solving signal deconvolution problems consists of resorting to a frame-based convex variational formulation. In this context, parallel proximal algorithms and related alternating direction methods of multipliers have become popular optimization techniques to approximate iteratively the desired solution. Until now, in most of these methods, either Lipschitz differentiability properties or tight frame representations were assumed. In this paper, it is shown that it is possible to relax these assumptions by considering a class of non necessarily tight frame representations, thus offering the possibility of addressing a broader class of signal restoration problems. In particular, it is possible to use non necessarily maximally decimated filter banks with perfect reconstruction, which are common tools in digital signal processing. The proposed approach allows us to solve both frame analysis and frame synthesis problems for various noise distributions. In our simulations, it is applied to the deconvolution of data corrupted with Poisson noise or Laplacian noise by using (non-tight) discrete dual-tree wavelet representations and filter bank structures.
Local regularity, wavelet leaders and total variation based procedures for texture segmentation
Nelly Pustelnik,Herwig Wendt,Patrice Abry,Nicolas Dobigeon
Computer Science , 2015,
Abstract: Texture segmentation constitutes a standard image processing task, crucial to many applications. The originality of the present approach resides in the combination of three key ingredients: First, texture characterization relies on the concept of local regularity; Second, estimation of local regularity is based on new multi scale quantities referred to as wavelet leaders; Third, segmentation from local regularity faces a fundamental bias variance trade-off: In nature, local regularity estimation shows high variability that impairs the detection of changes, while a posteriori smoothing of regularity estimates precludes from locating correctly changes. Instead, the present contribution proposes several variational problem formulations based on total variation and proximal resolutions that effectively circumvent this trade-off. Performances of the proposed procedures are quantified and compared on synthetic as well as real-world textures.
What’s Wrong with Requirements Specification? An Analysis of the Fundamental Failings of Conventional Thinking about Software Requirements, and Some Suggestions for Getting it Right  [PDF]
Tom Gilb
Journal of Software Engineering and Applications (JSEA) , 2010, DOI: 10.4236/jsea.2010.39096
Abstract: We know many of our IT projects fail and disappoint. The poor state of requirements methods and practice is frequently stated as a factor for IT project failure. In this paper, I discuss what I believe is the fundamental cause: we think like programmers, not engineers and managers. We do not concentrate on value delivery, but instead on functions, on use-cases and on code delivery. Further, management is not taking its responsibility to make things better. In this paper, ten practical key principles are proposed, which aim to improve the quality of requirements specification.
Internal Resource Audit for Strategists—A Proposal  [PDF]
Tom Connor
iBusiness (IB) , 2011, DOI: 10.4236/ib.2011.33038
Abstract: It is the purpose of this article to suggest a structured approach to internal resource audit, which, whilst of necessity general-purpose in design, would be capable of adaptation to particular company cases. Consequently this paper does not aim at theory development, but to make a conceptual contribution to the art and practice of management. It will, however, offer some criticism of current theory from a management perspective.
2-D Prony-Huang Transform: A New Tool for 2-D Spectral Analysis
Jérémy Schmitt,Nelly Pustelnik,Pierre Borgnat,Patrick Flandrin,Laurent Condat
Physics , 2014, DOI: 10.1109/TIP.2014.2363000
Abstract: This work proposes an extension of the 1-D Hilbert Huang transform for the analysis of images. The proposed method consists in (i) adaptively decomposing an image into oscillating parts called intrinsic mode functions (IMFs) using a mode decomposition procedure, and (ii) providing a local spectral analysis of the obtained IMFs in order to get the local amplitudes, frequencies, and orientations. For the decomposition step, we propose two robust 2-D mode decompositions based on non-smooth convex optimization: a "Genuine 2-D" approach, that constrains the local extrema of the IMFs, and a "Pseudo 2-D" approach, which constrains separately the extrema of lines, columns, and diagonals. The spectral analysis step is based on Prony annihilation property that is applied on small square patches of the IMFs. The resulting 2-D Prony-Huang transform is validated on simulated and real data.
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