Scalar conservation laws with stochastic forcing

We show that the Cauchy Problem for a randomly forced, periodic multi-dimensional scalar first-order conservation law with additive or multiplicative noise is well-posed: it admits a unique solution, characterized by a kinetic formulation of the problem, which is the limit of the solution of the stochastic parabolic approximation

Diffusion limit for the radiative transfer equation perturbed by a Wiener process

The aim of this paper is the rigorous derivation of a stochastic non-linear diffusion equation from a radiative transfer equation perturbed with a random noise. The proof of the convergence relies on a formal Hilbert expansion and the estimation of the remainder. The Hilbert expansion has to be done up to order 3 to overcome some diffculties caused by the random noise.Comment: 27 page

Long-time behavior in scalar conservation laws

We consider the long-time behavior of the entropy solution of a first-order scalar conservation law on a Riemannian manifold. In the case of the Torus, we show that, under a weak property of genuine non-linearity of the flux, the solution converges to its average value in $L^{p}$, $1\leq p<+\infty$. We give a partial result in the general case

Degenerate parabolic stochastic partial differential equations: Quasilinear case

Debussche A, Hofmanová M, Vovelle J. Degenerate parabolic stochastic partial differential equations: Quasilinear case. The Annals of Probability. 2016;44(3):1916-1955

Privacy, security, legal and technology acceptance requirements for a GDPR compliance platform.

GDPR entered into force in May 2018 for enhancing user data protection. Even though GDPR leads towards a radical change with many advantages for the data subjects it turned out to be a significant challenge. Organizations need to make long and complex changes for the personal data processing activities to become GDPR compliant. Citizens as data subjects are empowered with new rights, which however they need to become aware of and understand. Finally, the role of data protection authorities changes as well as their expectations from organizations. GDPR compliance being a challenging matter for the relevant stakeholders calls for a software platform that can support their needs. The aim of the Data govErnance For supportiNg gDpr (DEFeND) EU Project is to deliver such a platform. To succeed, the platform needs to satisfy legal and privacy requirements, be effective in supporting organizations in GDPR compliance, and provide functionalities that data controllers request for supporting GDPR compliance. Further, it needs to satisfy acceptance requirements, for assuring that its users will embrace and use the platform. In this paper, we describe the process, within the DEFeND EU Project, for eliciting and analyzing requirements for such a complex platform, by involving stakeholders from the banking, energy, health and public administration sectors, and using advanced frameworks for privacy requirements and acceptance requirements. The paper also contributes by providing elicited privacy and acceptance requirements concerning a holistic platform for supporting GDPR compliance

Privacy, security, legal and technology acceptance elicited and consolidated requirements for a GDPR compliance platform

Purpose– General data protection regulation (GDPR) entered into force in May 2018 for enhancing personal data protection. Even though GDPR leads toward many advantages for the data subjects it turned out to be a significant challenge. Organizations need to implement long and complex changes to become GDPR compliant. Data subjects are empowered with new rights, which, however, they need to become aware of. GDPR compliance is a challenging matter for the relevant stakeholders calls for a software platform that can support their needs. The aim of data governance for supporting GDPR (DEFeND) EU project is to deliver such a platform. The purpose of this paper is to describe the process, within the DEFeND EU project, for eliciting and analyzing requirements for such a complex platform. Design/methodology/approach– The platform needs to satisfy legal and privacy requirements and provide functionalities that data controllers request for supporting GDPR compliance. Further, it needs to satisfy acceptance requirements, for assuring that its users will embrace and use the platform. In this paper, the authors describe the methodology for eliciting and analyzing requirements for such a complex platform, by analyzing data attained by stakeholders from different sectors. Findings– The findings provide the process for the DEFeND platform requirements’elicitation and an indicative sample of those. The authors also describe the implementation of a secondary process for consolidating the elicited requirements into a consistent set of platform requirements. Practical implications– The proposed software engineering methodology and data collection tools(i.e. questionnaires) are expected to have a significant impact for software engineers in academia and industry. Social implications– It is reported repeatedly that data controllers face difficulties in complying with theGDPR. The study aims to offer mechanisms and tools that can assist organizations to comply with the GDPR,thus, offering a significant boost toward the European personal data protection objectives. Originality/value– This is the first paper, according to the best of the authors’ knowledge, to provide software requirements for a GDPR compliance platform, including multiple perspectives

La propriété intellectuelle en République populaire de Chine et plus particulièrement le droit des marques – Analyse du point de vue de l'entrepreneur européen

Master [120] en droit, Université catholique de Louvain, 201

Diffusion-approximation in stochastically forced kinetic equations

International audienceWe derive the hydrodynamic limit of a kinetic equation where the interactions in velocity are modeled by a linear operator (Fokker–Planck or linear Boltzmann) and the force in the Vlasov term is a stochastic process with high amplitude and short-range correlation. In the scales and the regime we consider, the hydrodynamic equation is a scalar second-order stochastic partial differential equation. Compared to the deterministic case, we also observe a phenomenon of enhanced diffusion

Invariant measure of scalar first-order conservation laws with stochastic forcing

International audienceUnder an hypothesis of non-degeneracy of the flux, we study the long-time behaviour of periodic scalar first-order conservation laws with stochastic forcing in any space dimension. For sub-cubic fluxes, we show the existence of an invariant measure. Moreover for sub-quadratic fluxes we show uniqueness and ergodicity of the invariant measure. Also, since this invariant measure is supported by Lp for some p small, we are led to generalize to the stochastic case the theory of L1 solutions developed by Chen and Perthame in 2003