Méthode rationnelle de classement d\u27une bibliothèque

« Document numérisé pour l\u27ENSSIB » - Ce traité de Pierre Boursier vise au premier chef les collectionneurs et les amateurs de livres. L\u27auteur commence par un inventaire des classements adoptés par cette catégorie du lectorat. Après avoir exposé les défauts de chacun de ces modes de classement, il présente la méthode chronologique comme la plus adaptée pour ce type de bibliothèque. Sa méthode consiste à regrouper les livres par formats et à les classer en fonction de la date de naissance de leur auteur. Afin de faciliter les recherches, il recommande la constitution d\u27un catalogue sur fiches par auteurs classées chronologiquement mais aussi un système de rangement physique particulier. Il souligne les avantages de son système, mais évoque aussi les objections qui lui ont été faites à ce propos. Il conclut néanmoins sur la supériorité de sa méthode sur les autres. Son objectif reste d\u27en faire des adeptes. L\u27intérêt de ce document est principalement d\u27ordre historique et technique, permettant d\u27apprécier les différents modes de classement existants à l\u27époque en matière de bibliothèque privée

Sparsity Driven People Localization with a Heterogeneous Network of Cameras

This paper addresses the problem of localizing people in low and high density crowds with a network of heterogeneous cameras. The problem is recast as a linear inverse problem. It relies on deducing the discretized occupancy vector of people on the ground, from the noisy binary silhouettes observed as foreground pixels in each camera. This inverse problem is regularized by imposing a sparse occupancy vector, i.e., made of few non-zero elements, while a particular dictionary of silhouettes linearly maps these non-empty grid locations to the multiple silhouettes viewed by the cameras network. The proposed framework is (i) generic to any scene of people, i.e., people are located in low and high density crowds, (ii) scalable to any number of cameras and already working with a single camera, (iii) unconstrained by the scene surface to be monitored, and (iv) versatile with respect to the camera's geometry, e.g., planar or omnidirectional. Qualitative and quantitative results are presented on the APIDIS and the PETS 2009 Benchmark datasets. The proposed algorithm successfully detects people occluding each other given severely degraded extracted features, while outperforming state-of-the-art people localization technique

Compressed sensing for radio interferometry: spread spectrum imaging techniques

We consider the problem of reconstruction of astrophysical signals probed by radio interferometers with baselines bearing a non-negligible component in the pointing direction. The visibilities measured essentially identify with a noisy and incomplete Fourier coverage of the product of the planar signals with a linear chirp modulation. We analyze the related spread spectrum phenomenon and suggest its universality relative to the sparsity dictionary, in terms of the achievable quality of reconstruction through the Basis Pursuit problem. The present manuscript represents a summary of recent work by the authors

A Sparsity Constrained Inverse Problem to Locate People in a Network of Cameras

A novel approach is presented to locate dense crowd of people in a network of fixed cameras given the severely degraded background subtracted silhouettes. The problem is formulated as a sparsity constrained inverse problem using an adaptive dictionary constructed on- line. The framework has no constraint on the number of cameras neither on the surface to be monitored. Even with a single camera, partially occluded and grouped people are correctly detected and segmented. Qualitative results are presented in indoor and outdoor scenes

Sparsity Driven People Localization with a Heterogeneous Network of Cameras

In this paper, we propose to study the problem of localization of a dense set of people with a network of heterogeneous cameras. We propose to recast the problem as a linear inverse problem. The proposed framework is generic to any scene, scalable in the number of cameras and versatile with respect to their geometry, e.g. planar or omnidirectional. It relies on deducing an \emph {occupancy vector}, i.e. the discretized occupancy of people on the ground, from the noisy binary silhouettes observed as foreground pixels in each camera. This inverse problem is regularized by imposing a sparse occupancy vector, i.e. made of few non- zero elements, while a particular dictionary of silhouettes linearly maps these non-empty grid locations to the multiple silhouettes viewed by the cameras network. This constitutes a linearization of the problem, where non- linearities, such as occlusions, are treated as additional noise on the observed silhouettes. Mathematically, we express the final inverse problem either as Basis Pursuit DeNoise or Lasso convex optimization programs. The sparsity measure is reinforced by iteratively re-weighting the $\ell_1$-norm of the occupancy vector for better approximating its $\ell_0$ ``norm'', and a new kind of ``repulsive'' sparsity is used to adapt further the Lasso procedure to the occupancy reconstruction. Practically, an adaptive sampling process is proposed to reduce the computation cost and monitor a large occupancy area. Qualitative and quantitative results are presented on a basketball game. The proposed algorithm successfully detects people occluding each other given severely degraded extracted features, while outperforming state-of-the-art people localization techniques

Sport Players Detection and Tracking With a Mixed Network of Planar and Omnidirectional Cameras

A generic approach is presented to detect and track people with a network of fixed and omnidirectional cameras given severely degraded foreground silhouettes. The problem is formulated as a sparsity constrained inverse problem. A dictionary made of atoms representing the presence of a person at a given location is used within the problem formulation. A re- weighted scheme is considered to better approximate the sparsity prior. Although the framework is generic to any scene, the focus of this paper is to evaluate the strength of the proposed approach on a basketball game. The main challenges come from the players' behavior, their similar appearance, and the mutual occlusions present in the views. In addition, the extracted foreground silhouettes are severely degraded due to the polished floor reflecting the players, and the strong shadow present in the scene. We present qualitative and quantitative results with the APIDIS dataset as part of the ICDSC sport challenge

Rituximab Efficacy during a Refractory Polyarteritis Nodosa Flare

Polyarteritis nodosa (PAN) is a systemic vasculitis whose severe forms are treated with glucocorticoids and cyclophosphamide. Refractory patients are exposed to many complications, notably accelerated atherosclerosis. We report a case report of 71-year-old man followed for polyarteritis nodosa refractory to glucocorticoids and cyclosphosphamide. Systemic vasculitis relapses are followed to accelerated atherosclerosis: severe ischemic lesions led to amputation of lower limbs. Remission of refractory PAN is obtained with rituximab. Disappearance of biological inflammatory is allowed to regression of ischemic lesions in upper limbs. In this situation, we recommend a systematic vascular work-up for patients suffered from refractory vasculitis. On the other hand, therapeutic trials are needed to determine the real efficacy and place of rituximab in the treatment of polyarteritis nodosa

Development of an in Vitro Rat Intestine Segmental Perfusion Model to Investigate Permeability and Predict Oral Fraction Absorbed

Purpose: The aims of the study are to develop and evaluate an in vitro rat intestine segmental perfusion model for the prediction of the oral fraction absorbed of compounds and to assess the ability of the model to study intestinal metabolism. Methods: The system consisted of a perfusion cell with a rat intestinal segment and three perfusion circulations (donor, receiver, and rinsing circulation). Lucifer yellow (LY) was applied as internal standard together with test compounds in the donor circulation. To validate the model, the permeability of eight noncongeneric passively absorbed drugs was determined. Intestinal N-demethylation of verapamil into norverapamil was followed in the donor and receiver circulations by high-performance liquid chromatography analysis. Results: The in vitro model allowed ranking of the tested compounds according to their in vivo absorption potential. The Spearman's correlation coefficient between the oral fraction absorbed in humans and the ratio of permeation coefficient of test compound to the permeation coefficient of LY within the same experiment was 0.98 (P < 0.01). Moreover, intestinal N-demethylation of verapamil, its permeation, and the permeation of its metabolite norverapamil could be assessed in parallel. Conclusions: Up to six permeation kinetics can be obtained per rat, and the method has shown to be a valuable tool to estimate human oral absorptio

Comparison of accuracy of fibrosis degree classifications by liver biopsy and non-invasive tests in chronic hepatitis C

<p>Abstract</p> <p>Background</p> <p>Non-invasive tests have been constructed and evaluated mainly for binary diagnoses such as significant fibrosis. Recently, detailed fibrosis classifications for several non-invasive tests have been developed, but their accuracy has not been thoroughly evaluated in comparison to liver biopsy, especially in clinical practice and for Fibroscan. Therefore, the main aim of the present study was to evaluate the accuracy of detailed fibrosis classifications available for non-invasive tests and liver biopsy. The secondary aim was to validate these accuracies in independent populations.</p> <p>Methods</p> <p>Four HCV populations provided 2,068 patients with liver biopsy, four different pathologist skill-levels and non-invasive tests. Results were expressed as percentages of correctly classified patients.</p> <p>Results</p> <p>In population #1 including 205 patients and comparing liver biopsy (reference: consensus reading by two experts) and blood tests, Metavir fibrosis (F_M) stage accuracy was 64.4% in local pathologists vs. 82.2% (p < 10^-3) in single expert pathologist. Significant discrepancy (≥ 2F_Mvs reference histological result) rates were: Fibrotest: 17.2%, FibroMeter^2G: 5.6%, local pathologists: 4.9%, FibroMeter^3G: 0.5%, expert pathologist: 0% (p < 10^-3). In population #2 including 1,056 patients and comparing blood tests, the discrepancy scores, taking into account the error magnitude, of detailed fibrosis classification were significantly different between FibroMeter^2G(0.30 ± 0.55) and FibroMeter^3G(0.14 ± 0.37, p < 10^-3) or Fibrotest (0.84 ± 0.80, p < 10^-3). In population #3 (and #4) including 458 (359) patients and comparing blood tests and Fibroscan, accuracies of detailed fibrosis classification were, respectively: Fibrotest: 42.5% (33.5%), Fibroscan: 64.9% (50.7%), FibroMeter^2G: 68.7% (68.2%), FibroMeter^3G: 77.1% (83.4%), p < 10^-3(p < 10^-3). Significant discrepancy (≥ 2 F_M) rates were, respectively: Fibrotest: 21.3% (22.2%), Fibroscan: 12.9% (12.3%), FibroMeter^2G: 5.7% (6.0%), FibroMeter^3G: 0.9% (0.9%), p < 10^-3(p < 10^-3).</p> <p>Conclusions</p> <p>The accuracy in detailed fibrosis classification of the best-performing blood test outperforms liver biopsy read by a local pathologist, i.e., in clinical practice; however, the classification precision is apparently lesser. This detailed classification accuracy is much lower than that of significant fibrosis with Fibroscan and even Fibrotest but higher with FibroMeter^3G. FibroMeter classification accuracy was significantly higher than those of other non-invasive tests. Finally, for hepatitis C evaluation in clinical practice, fibrosis degree can be evaluated using an accurate blood test.</p

TV-Regularized Generation of Planar Images from Omnicams

This paper addresses the problem of mapping images between different vision sensors. Such a mapping could be modeled as a sampling problem that has to encompass the change of geometry between the two sensors and the specific discretization of the real scene observed by the two different imaging systems. We formulate the problem in a general framework that can be cast as a minimization regularized problem with a linear operator, that applies to any image geometry. We then focus on the particular problem of the generation of planar images from omnidirectional images, in any viewing direction and for any size and resolution. In this regularized approach, the fidelity term is expressed in the original omnicam geometry and the regularization is based on Total Variation (TV) solved here with proximal methods. Experimental results demonstrate the superiority of this approach with respect to alternative schemes based on linear interpolation or TV inpainting