Demand side management in an integrated electricity market: what are the impacts on generation and environmental concerns ?

International audienceSmart Grid technology appears necessary to succeed in activating the demand through demand side management (DSM) programs. This would in turn improve energy efficiency and achieve environmental targets through controlled consumption. The many pilot projects led worldwide involving smart grids technology, brought quantitative evaluations of DSM measures on electricity load. Efficient DSM instruments must be fine tuned to respond to very specific issues arising from the generation mix, the integration of intermittent energies or the level of outage risks faced during peak period. Efficient DSM strategies are illustrated through a model involving five countries that carry these different features and under the assumptions of isolated and fully interconnected markets. This paper aims at bringing recommendations regarding the instruments that should be implemented to maximize the benefits of smart grids technology and demand response. Finally, it tends to emphasis the issue of homogenized energy efficiency policies, critical in the building of internal energy markets such as the one the European Union is envisioning

Audio Event Detection in Movies using Multiple Audio Words and Contextual Bayesian Networks

International audienceThis article investigates a novel use of the well known audio words representations to detect specific audio events, namely gunshots and explosions, in order to get more robustness towards soundtrack variability in Hollywood movies. An audio stream is processed as a sequence of stationary segments. Each segment is described by one or several audio words obtained by applying product quantization to standard features. Such a representation using multiple audio words constructed via product quantisation is one of the novelties described in this work. Based on this representation, Bayesian networks are used to exploit the contextual information in order to detect audio events. Experiments are performed on a comprehensive set of 15 movies, made publicly available. Results are comparable to the state of the art results obtained on the same dataset but show increased robustness to decision thresholds, however limiting the range of possible operating points in some conditions. Late fusion provides a solution to this issue

De la détection d'évènements sonores violents par SVM dans les films

National audienceThis article studies the behaviour of a state-of-the-art support vector machine audio event detection approach, applied to violent event detection in movies. The events we are trying to detect are screams, gunshots, explosions. Contrary to others studies, we show that the state-of-theart approach does not lead to good results on this task. A study on the repartition of samples into subsets in a cross validation protocol helps explain those results and highlights a generalisation problem due to a polymorphism of considered classes. This polymorphism is demonstrated by the computation the divergence between the samples of the test database and the training database.Cet article étudie le comportement d'une approche classique, à l'état de l'art, pour la détection d'événements sonores par machines à vecteurs supports, appliquée à la détection d'événements violents dans les films. Les événements sonores considérés, liés à la présence de violence, sont les Cris, les Coups de feu et les Explosions. Nous montrons que, contrairement aux résultats d'autres études, l'approche état de l'art ne donne pas de bons résultats sur cette tâche. Une étude sur la répartition des échantillons en sous-ensembles dans un protocole de validation croisée permet d'expliquer ces résultats et met en évidence un problème de généralisation, dû au polymorphisme des classes considérées. Ce polymorphisme est démontré par un calcul de divergence entre les échantillons de la base de test et ceux de la base d'apprentissage

Being the chosen one: social inclusion modulates decisions in the ultimatum game. An ERP study

International audienceIn the present study, participants played a modified ultimatum game simulating a situation of inclusion/exclusion, in which either the participant or a rival could be selected to play as the responder. This selection was made either randomly by a computer (i.e. random pairing mode) or by the proposer (i.e. choice mode), based on physical appearance. Being chosen by the proposer triggered positive reciprocal behavior in participants, who accepted unfair offers more frequently than when they had been selected by the computer. Independently of selection mode, greater P200 amplitudes were found when participants received fair offers than when they received unfair offers and when unfair shares were offered to their rivals rather than to them, suggesting that receiving fair offers or observing a rival's misfortune was rewarding for participants. While participants generally showed more interest in the offers they themselves received (i.e. greater P300 responses to these offers), observing their rivals receive fair shares after the latter had been chosen by the proposer triggered an increase in P300 amplitude likely to ref lect a feeling of envy. This study provides new insights into both the cognitive and affective processes underpinning economic decision making in a context of social inclusion/exclusion

Segmenting Multivariate Time Series of Water Flow : a Prior Tool for Contamination Warning Systems

International audienceDrinking Water Distribution Networks (WDN) are critical infrastructures exposed to the risk of accidental and intentional contaminations. To ensure protection of drinking water, there is an important need to design automatic and secure Early Warning Systems (EWS). Online monitoring of water quality into a WDN is a challenging problem due to the complexity of hydraulic networks. Conventional detection methods deal with specific contaminants and usually assume a stationary state of the WDN meanwhile such problem is hardly addressed when operational conditions are changing. This paper introduces a generic methodology based on a temporal analysis in order to extract prior knowledge for warning detectors. Frequent types of operating period are extracted and for each period, upstream / downstream relationships into the WDN can be found. The procedure is fully data-driven and prevents to use heavy hydraulic-quality simulations during the monitoring stage. In fact, the method can be used as a preprocessing step by any detector in order to help dealing with multiple quality sensors and to avoid false alarms due to operating changes. The proposed approach is illustrated on a large real-world network in France and the experimental results are very promising

Uniform and non-uniform random generation of RNA secondary structures with pseudoknots

International audienceWe give an efficient algorithm to generate random RNA secondary structures with pseudoknots, either uniformly or non uniformly in a controllable fashion. Although we consider a restrictive class of pseudoknots, the class of {\em simple recursive pseudoknots}, it turns out that most of the known real RNA pseudoknotted secondary structures in the biological databases belong to this class

One Click Focus with Eye-in-hand/Eye-to-hand Cooperation

A critical assumption of many multi-view control systems is the initial visibility of the regions of interest from all the views. An initialization step is proposed for a hybrid eye-in-hand/eye-to-hand grasping system to overcome this requirement. In this paper, the object of interest is assumed to be within the eye-to-hand field of view, whereas it may not be within the eye-in-hand one. The object model is unknown and no database is used. The object lies in a complex scene with a cluttered background. A method to automatically focus the object of interest is presented, tested and validated on a multi view robotic system

Uniform and non-uniform random generation of RNA secondary structures with pseudoknots

International audienceWe give an efficient algorithm to generate random RNA secondary structures with pseudoknots, either uniformly or non uniformly in a controllable fashion. Although we consider a restrictive class of pseudoknots, the class of {\em simple recursive pseudoknots}, it turns out that most of the known real RNA pseudoknotted secondary structures in the biological databases belong to this class