Probabilistic representation for solutions of an irregular porous media type equation: the degenerate case

We consider a possibly degenerate porous media type equation over all of $\R^d$ with $d = 1$, with monotone discontinuous coefficients with linear growth and prove a probabilistic representation of its solution in terms of an associated microscopic diffusion. This equation is motivated by some singular behaviour arising in complex self-organized critical systems. The main idea consists in approximating the equation by equations with monotone non-degenerate coefficients and deriving some new analytical properties of the solution

La crise économique et financière impacte-t-elle la mission d'audit légal et de certification des comptes ?

L'article vise à montrer comment le commissaire aux comptes (CAC) doit adapter sa mission à un contexte de crise économique et financière. En effet, le CAC doit mettre en œuvre des diligences spécifiques au contexte économique, puisque certains risques sont ainsi amplifiés, comme ceux tenant à la continuité d'exploitation et à la mauvaise estimation du résultat comptable. En outre, le rapport général du commissaire peut lui aussi être nuancé en raison de l'incertitude pesant sur certains éléments, ce qui peut induire des asymétries d'information. L'analyse théorique de la situation est complétée par une étude de cas portant sur une société située dans un secteur touché par la crise financière actuelle, à savoir la fabrication de matériels électriques de pointe.crise financière ; commissaires aux comptes ; mission générale ; France ; étude de cas ; financial crisis ; auditors ; France ; case study

Revisiting loss-specific training of filter-based MRFs for image restoration

It is now well known that Markov random fields (MRFs) are particularly effective for modeling image priors in low-level vision. Recent years have seen the emergence of two main approaches for learning the parameters in MRFs: (1) probabilistic learning using sampling-based algorithms and (2) loss-specific training based on MAP estimate. After investigating existing training approaches, it turns out that the performance of the loss-specific training has been significantly underestimated in existing work. In this paper, we revisit this approach and use techniques from bi-level optimization to solve it. We show that we can get a substantial gain in the final performance by solving the lower-level problem in the bi-level framework with high accuracy using our newly proposed algorithm. As a result, our trained model is on par with highly specialized image denoising algorithms and clearly outperforms probabilistically trained MRF models. Our findings suggest that for the loss-specific training scheme, solving the lower-level problem with higher accuracy is beneficial. Our trained model comes along with the additional advantage, that inference is extremely efficient. Our GPU-based implementation takes less than 1s to produce state-of-the-art performance.Comment: 10 pages, 2 figures, appear at 35th German Conference, GCPR 2013, Saarbr\"ucken, Germany, September 3-6, 2013. Proceeding

A numerical framework for modelling tire mechanics accounting for composite materials, large strains and frictional contact

Presentation delivered by Alejandro Cornejo from CIMNE during the 17th International Conference on Computational Plasticity, Fundamentals and Applications (COMPLAS) taking place from 5 – 7 of September in Barcelona, Spain.The Fatigue4Light project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 10100684

Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modelling platform: a land data assimilation application over France

The land monitoring service of the European Copernicus programme has developed a set of satellite-based biogeophysical products, including surface soil moisture (SSM) and leaf area index (LAI). This study investigates the impact of joint assimilation of remotely sensed SSM derived from Advanced Scatterometer (ASCAT) backscatter data and the Copernicus Global Land GEOV1 satellite-based LAI product into the the vegetation growth version of the Interactions between Soil Biosphere Atmosphere (ISBA-A-gs) land surface model within the the externalised surface model (SURFEX) modelling platform of Météo-France. The ASCAT data were bias corrected with respect to the model climatology by using a seasonal-based CDF (Cumulative Distribution Function) matching technique. A multivariate multi-scale land data assimilation system (LDAS) based on the extended Kalman Filter (EKF) is used for monitoring the soil moisture, terrestrial vegetation, surface carbon and energy fluxes across the domain of France at a spatial resolution of 8 km. Each model grid box is divided into a number of land covers, each having its own set of prognostic variables. The filter algorithm is designed to provide a distinct analysis for each land cover while using one observation per grid box. The updated values are aggregated by computing a weighted average. <br><br> In this study, it is demonstrated that the assimilation scheme works effectively within the ISBA-A-gs model over a four-year period (2008–2011). The EKF is able to extract useful information from the data signal at the grid scale and distribute the root-zone soil moisture and LAI increments throughout the mosaic structure of the model. The impact of the assimilation on the vegetation phenology and on the water and carbon fluxes varies from one season to another. The spring drought of 2011 is an interesting case study of the potential of the assimilation to improve drought monitoring. A comparison between simulated and in situ soil moisture gathered at the twelve SMOSMANIA (Soil Moisture Observing System–Meteorological Automatic Network Integrated Application) stations shows improved anomaly correlations for eight stations

Fatigue behaviour of Glass-Fiber-Reinforced Polymers Numerical versus experimental characterisation

Presentation delivered by Bàrbara Alcayde from CIMNE during the 17th International Conference on Computational Plasticity, Fundamentals and Applications (COMPLAS) taking place from 5 – 7 of September in Barcelona, Spain.The Fatigue4Light project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 10100684