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Forecasting Intraday Risk Measures using Multiplicative Component GARCH Model and Multimodal Distributions
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Robust estimation of covariance and correlation functions of a stationary multivariate process
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Silicon Nanowires Based Resistors for Bacteria Detection
No full textInternational audienceSilicon nanowires (SiNWs) based resistors used as bacteria sensors are fabricated using the classical silicon technologies. SiNWs are grown by vapor liquid solid (VLS) method using gold as catalyst. Electrodes of the device are made of heavily in-situ doped polycristalline silicon. Results show potential use of the corresponding resistors, with SiNWs as sensitive units, for bacteria detection. Bacteria are preferentially hanged into SiNWs array and electrical resistance of the device decreases due to the presence of bacteria. Such resistors are promising bacteria sensors to monitor contamination in controlled environment for hygiene, fabricated in a simple and low-cost fabrication technology
Separation of Impulsive Blended Seismic Sources Using Orthogonal Matching Pursuit
No full textInternational audienceSimultaneous-source (or blended) seismic data acquisition allows reducing acquisition time, which is beneficial in harsh meteorological environment or when strict environmental regulations are applied. The only draw-back of blended acquisition is the interference (or cross-talk) between signals originating from different seismic sources firing at the same time. Recent advances in processing and imaging allow acceptable handling of the cross-talk, however, specific processing methods adapted for blended data still need to be improved. Whether the deblending step (or separation of signals originating from different sources) is necessary remains an open question, but it is still included in the beginning of most of the simultaneous-source processing sequences. In this paper, we propose a deblending method based on the decomposition of the blended signal into a set of locally coherent features, or seismic events. The information on the source contained in each seismic event is further used for separation. The decomposition is performed using the Orthogonal Matching Pursuit signal decomposition algorithm with a specific parametric dictionary adapted for seismic events and allowing sparse representation of the data. The method shows promising results on synthetic sets of 2D seismic data and is scalable to large datasets of industrial size
Une formulation SAT pour l’apprentissage de modèles de classement multicritères non-compensatoires
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Fluid-flow modeling and stability analysis of communication networks
No full textInternational audienceThis paper deals with a fluid-flow modeling under compartmental representation of a network. The motivating example is a communication network made up of buffers and transmission lines where densities and flows of packets are viewed as macroscopic variables respecting the conservation laws. The main contribution lies in the resulting model. It is a coupled linear hyperbolic partial differential equations (PDEs) with an ordinary differential equation (ODEs) along with a dynamic boundary condition. Input-to-state stability of an optimal equilibrium is analyzed using Lyapunov techniques
Distributed Non-Asymptotic Confidence Region Computation over Sensor Networks
No full textInternational audienceThis paper addresses the distributed computation of exact, non-asymptotic confidence regions for the parameter estimation of a linear model from observations at different nodes of a network of sensors. If a central unit gathers all the data, the sign perturbed sums (SPS) method proposed by Csáji et al. can be used to define guaranteed confidence regions with prescribed confidence levels from a finite number of measurements. SPS requires only mild assumptions on the measurement noise. This work proposes distributed solutions, based on SPS and suited to a wide variety of sensor networks, for distributed in-node evaluation of non-asymptotic confidence regions as defined by SPS. More specifically, a Tagged and Aggregated Sum information diffusion algorithm is introduced, which exploits the specificities of SPS to avoid flooding the network with all measurements provided by the sensors. The performance of the proposed solutions is evaluated in terms of required traffic load, both analytically and experimentally on different network topologies. The best information diffusion strategy among nodes depends on how structured the network is
The Non-stationary Stochastic Multi-armed Bandit Problem
No full textInternational audienceWe consider a variant of the stochastic multi-armed bandit with K arms where the rewards are not assumed to be identically distributed, but are generated by a non-stationary stochastic process. We first study the unique best arm setting when there exists one unique best arm. Second, we study the general switching best arm setting when a best arm switches at some unknown steps. For both settings, we target problem-dependent bounds, instead of the more conservative problem-free bounds. We consider two classical problems: (1) identify a best arm with high probability (best arm identification), for which the performance measure by the sample complexity (number of samples before finding a near-optimal arm). To this end, we naturally extend the definition of sample complexity so that it makes sense in the switching best arm setting, which may be of independent interest. (2) Achieve the smallest cumulative regret (regret minimization) where the regret is measured with respect to the strategy pulling an arm with the best instantaneous mean at each step
Large Deviation Analysis of the CPD Detection Problem Based on Random Tensor Theory
No full textNational audienceLarge Deviation Analysis of the CPD Detection Problem Based on Random Tensor Theor
How to Close the Loop of Platinum from Heavy Vehicles Catalytic Converters?: Framework to Evaluate the Impact of Several Promising Action Levers
No full textInternational audienceThe issue of recovering platinum from catalytic converter of heavy vehicles, arises for economic (high valuable component due to the non-negligible presence of platinum that costs around 30 €/g), environmental (low platinum concentration in mines (below 10 g/t) requires large consumption of energy), social (ore mining conditions are increasingly drastic) and geostrategic (more than 90% of platinum stock is located in South Africa and Russia) reasons. Even if some marginal channels exist, the collection rate of platinum from catalytic converters in Europe is still low (around 50%) while recycling efficiency is high (around 95%). As heavy vehicles are not considered by any end-of-life directive contrary to the automotive sector submitted to ELV directive, the objective of this applied research work is to evaluate the impact of other actions levers to close the loop of heavy vehicles catalytic converters which contain larger amount of platinum than in cars. To date, a number of issues that still need to be tackling to close the loop of platinum have been outlined in literature but there is a lack of operational improvement proposal or simulation to see “what if” scenarios, and therefore evaluate the impact of different changes. Indeed, even though research the on end-of-life management has an extensive literature, there is still lack of in-depth investigation on how to effectively improve the overall end-of-life collection, recovery and efficiency related to platinum from heavy-duty vehicles catalytic converters. Thus, new insights are needed to address and overcome the barriers, systematically analysed in previous state-of-the-art, to an effective circular economy of platinum. In this light, the main objectives of this work are twofold, (i) to construct a methodology that aims at assessing the impact of different actions levers on the road toward the circular economy, (ii) to experience the proposed approach through a significant industrial case study from a manufacturer willing to know how close the loop of their product containing precious raw materials, in order to benefit from economic and environmental spinoffs. Through MFA and SD modeling and simulations, promising actions levers (e.g. re-design to facilitate end-of-life recovery, take-back and remanufacturing offers, product-as-a-service, mandatory recycling rate) will be analyzed. Also, methods of prospective will be used to define relevant and realistic scenarios. The developed approach will assess the contribution of different actions levers in “closing-the-loop” by simultaneously considering environmental and economic parameters. In this paper, we will try to summarize the issues of platinum recovery from end-of-life heavy vehicles, to explain in detail the approach and to present first results of application. The proposed method consists in five steps. First step is about modeling the current situation (defining scope, boundaries of the study, identifying stakeholders, representing value chain). Second step deals with the identification and selection of promising and possible action levers. Third step with scenarios elaborations. Fourth step with simulations realisation. Last step with results analysis and presentation to get feedback from actors. The broader impact of this work will be to provide significant new insights for industrial practitioners about mechanisms to maintain platinum deposit contained in catalytic converter in Europe and therefore to secure supply chain. As such, it will represent a valuable contribution to resource sustainability for European platinum sector in the light of the circular economy