Pronostic de défaillances : Maîtrise de l'erreur de prédiction.

International audienceLe travail rapporté ici traite globalement de la spécification et du développement d'un système de pronostic de défaillances. De ce point de vue, beaucoup de développements visant la proposition de méthodes de prévision existent dans la littérature. La majorité d'entre elles portent sur la construction de modèles capables de minimiser l'erreur de prédiction d'une situation future. Cependant, peu traitent de la maitrise de cette erreur. C'est ce qui fait l'objet de ce papier et pour lequel nous proposons d'exploiter le système ANFIS (système d'inférence floue paramétré par apprentissage neuronal). Après avoir positionné l'activité de pronostic dans le cadre de la maintenance industrielle, nous présentons le réseau ANFIS. Nous étudions les pistes permettant de maîtriser l'erreur de prédiction d'un tel système, notamment lors de la phase d'apprentissage (optimisation des paramètres du réseau). Les éléments théoriques nécessaires à cette analyse sont décrits, une nouvelle fonction de coût est proposée et l'influence de celle-ci sur les performances du réseau est discutée. Nous illustrons l'ensemble sur un benchmark. La modification proposée permet de réduire la phase d'apprentissage du système de pronostic

Toward a validation process for model based safety analysis

Today, Model Based processes become more and more widespread to achieve the analysis of a system. However, there is no formal testing approach to ensure that the formal model is compliant with the real system. In the paper, we choose to study AltaRica model. We present a general process to well construct and validate an AltaRica formal model. The focus is made on this validation phase, i.e. verifying the compliance between the model and the real system. For it, the proposed process recommends to build a specification for the AltaRica model. Then, the validation process is transformed to a classical verification problem between an implementation and a specification

Toward a methodology for the AltaRica modelling of multi-physical systems

Numerous works deal with the use of the formal language AltaRica to improve the safety as-sessment process of industrial systems. In this context, the paper aims at describing and applying a common methodology to model physical systems. The example of a mechanical system and a hydro-mechanical system will be taken

Molecular Characterization of a Streptococcus gallolyticus Genomic Island Encoding a Pilus Involved in Endocarditis

Background. Streptococcus gallolyticus is a causative agent of infective endocarditis associated with colon cancer. Genome sequence of strain UCN34 revealed the existence of 3 pilus loci (pil1, pil2, and pil3). Pili are long filamentous structures playing a key role as adhesive organelles in many pathogens. The pil1 locus encodes 2 LPXTG proteins (Gallo2178 and Gallo2179) and 1 sortase C (Gallo2177). Gallo2179 displaying a functional collagen-binding domain was referred to as the adhesin, whereas Gallo2178 was designated as the major pilin. Methods. S. gallolyticus UCN34, Pil1+ and Pil1−, expressing various levels of pil1, and recombinant Lactococcus lactis strains, constitutively expressing pil1, were studied. Polyclonal antibodies raised against the putative pilin subunits Gallo2178 and Gallo2179 were used in immunoblotting and immunogold electron microscopy. The role of pil1 was tested in a rat model of endocarditis. Results. We showed that the pil1 locus (gallo2179-78-77) forms an operon differentially expressed among S. gallolyticus strains. Short pilus appendages were identified both on the surface of S. gallolyticus UCN34 and recombinant L. lactis-expressing pil1. We demonstrated that Pil1 pilus is involved in binding to collagen, biofilm formation, and virulence in experimental endocarditis. Conclusions. This study identifies Pil1 as the first virulence factor characterized in S. gallolyticu

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

L'expérience de consommation des sportifs chez les 18-34 ans : la crédibilité des marques de sport/Case study

Négociation et Management Commercia

Classification of MODIS Time Series with Dense Bag-of-Temporal-SIFT-Words: Application to Cropland Mapping in the Brazilian Amazon

Mapping croplands is a challenging problem in a context of climate change and evolving agricultural calendars. Classification based on MODIS vegetation index time series is performed in order to map crop types in the Brazilian state of Mato Grosso. We used the recently developed Dense Bag-of-Temporal-SIFT-Words algorithm, which is able to capture temporal locality of the data. It allows the accurate detection of around 70% of the agricultural areas. It leads to better classification rates than a baseline algorithm, discriminating more accurately classes with similar profiles

Resistance of morphological and behavioral sexual traits of the palmate newt (Lissotriton helveticus) to bacterial lipopolysaccharide treatment

International audienceInfectious diseases are considered as a significant factor in the global decline of amphibians. In some vertebrates, the assessment of the individual sexual traits can be useful for assessment of their health status and immunocompetence due to trade-off between them and investment in the immune system. Our aim here was to determine whether the trade-off between the expression of sexual morphological and behavioral traits and investment in the immune system is present in an urodele, the Palmate newt (Lissotriton helveticus). The groups of males were injected by solutions of proinflammatory agent, lipopolysaccharide (LPS) from Escherichia coli serotype O:55:B5, at dosages toxic to vertebrates (2 and 10 mg/kg of body mass) or by saline solution only (control groups). They were subsequently measured for variations in body condition and expression of both morphological (filament length, hind-foot-web, crest) and behavioral (courtship frequency) sexual traits. The injection of either LPS or saline solution did not cause any adverse effect on health in any male of all groups. No significant differences in any of the sexual traits were observed between two groups of males injected by LPS and control groups of males indicating the absence of a trade-off between immune response and expression of sexual traits. Our result suggests that measuring morphological or behavioral sexual traits may not be a useful method for monitoring emergence of infectious diseases in the palmate newt

Nonlinear Time-Series Adaptation for Land Cover Classification

International audienceAutomatic land cover classification from satellite image time series is of paramount relevance to assess vegetation and crop status, with important implications in agriculture, biofuels and food. However, due to the high cost and human resources needed to characterize and classify land cover through field campaigns, a recurrent limiting factor is the lack of available labeled data. On top of this, the bio-geo-physical variables exhibit particular temporal structures that need to be exploited. Land cover classification based on image time series is very complex because of the data manifold distortions through time. We propose the use of the kernel manifold alignment (KEMA) method for domain adaptation of remote sensing time series before classification. KEMA is nonlinear, semi-supervised, and reduces to solve a simple generalized eigenproblem. We give empirical evidence of performance through classification of biophysical (LAI, fAPAR, FVC, NDVI) time series at a global scale