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Online Deep anomaly Detection – ODD
Anomaly detection is a challenge per se. It is unsupervised by nature, as abnormal events are rare, varied, and cumbersome to collect. By exploring deep neural networks for representation learning, the main categories of anomaly detection methods are deep one-class classifiers, autoencoders, generat
Online Security Management and Reliability Toolkit for Water Distribution Networks – SMaRT-OnlineWDN
Water distribution Networks (WDNs) are critical infrastructures that are exposed to deliberate or accidental contamination. Until now, no monitoring system is capable of protecting a WDN in real time. In the immediate future water service utilities that are installing water quantity and quality sens
Operando investigation of chemo-mechanical degradation in sulfide-based solid electrolyte – OpInSolid
All solid-state batteries based on thiosulfate solid electrolyte hold the promise of safer and more energetic batteries, especially once coupled to Li metal anode and high voltage cathodes. Unfortunately, it was demonstrated in the literature that their electrochemical stability window is far from o
Optical Control of the Movement and Organization of Nanoparticles – COME-ON
COME-ON aims at demonstrating controlled light-induced organization of individual nano-sized objects using photomechanically active azo-derivative molecules. Indeed, the cis-trans photoisomerization of such molecules is known to produce huge average mass-transport effects in polymeric hosts. However
OptimAl Transport for MachIne Learning – OATMIL
In our era of steady data deluge, there is no doubt that the design of efficient techniques to extract knowledge from massive data collections or data streams has become a fundamental scientific and technological challenge bearing immense opportunities, both industrial and societal. As such, it is n
Optimal Transport and Image Multiphysics – TOMMI
Interpolating between two images is an old problem from image analysis, which finds applications for example to recover lost or damaged data in experiments films. It is also used in order to determine in which state the studied system could have been at some time when no observations were made. Imag
Optimal Transport: Theory and Applications to cosmological Reconstruction and Image processing – OTARIE
Optimal transport is a mathematical subject connecting the fields of optimization, partial differential equations, and dynamical systems in both finite and infinite dimensions. The basic problem of optimal transport is to find a transport plan that connects two given distributions of mass and minimi
Optimisation des Procédés d'Elaboration par Refusion (Arc-Slag) – OPERAS
The aim of the project OPERAS is the development of numerical models for simulating the ESR (Electro Slag Remelting) and VAR (Vacuum Arc Remelting) processes. Both processes are based on the remelting of a consumable electrode of the required grade and subsequent solidification of the ingot which re
Optimisation of arsenic-rich MIne wastes phytostabilisation strategies: prediction of impacts on water and pollutants bioavailability to plants linked with MicrObial activities – oMIMo
Securing mining residues represents a major environmental challenge. Most metal mines generated waste containing iron and/or sulfur, with arsenic (As) being a common toxic pollutant. Phytostabilization appears to be an appropriate option to minimize the risks linked to the dispersion of particles by
Optimising CNS-targeted neurotensin-peptide-vector conjugates for induction of therapeutic hypothermia – VEC2Brain
Central Nervous System (CNS) diseases are the world’s leading cause of disability. The brain's blood vessels possess unique anatomical and physiological features - collectively known as the blood-brain barrier (BBB) - that substantially limit the delivery of drugs to the nervous tissue. Strategies f
