Numerical and Computational Strategy for Pressure-Driven Steady-State Simulation of Oilfield Production

Within the TINA (Transient Integrated Network Analysis) research project and in partnership with Total, IFP is developing a new generation of simulation tool for flow assurance studies. This integrated simulation software will be able to perform multiphase simulations from the wellbore to the surface facilities. The purpose of this paper is to define, in a CAPE-OPEN compliant environment, a numerical and computational strategy for solving pressure-driven steady-state simulation problems, i.e. pure simulation and design problems, in the specific context of hydrocarbon production and transport from the wellbore to the surface facilities

Definition of a New Level One Test Case Measurements of Equilibrium Radiation from an Inductively Coupled Plasma in the Near-UV to Near-IR Spectral Region for a Titan-Type N2-CH4 Mixture. Preliminary Results

A test case, using a similar methodology and experimental set-up than previous test case TC5-Level 1 is presented in this paper. An inductively coupled plasma torch, working at atmospheric pressure, is used to create N2-CH4 Titan-like plasma (98%N2 - 2%CH4). The operating frequency and power are 64 MHz and 3 kW respectively. This kind of apparatus allows obtaining plasma in chemical and quasi-thermal equilibrium The spectral measurements cover the [300-800] nm range and are performed inside the induction coil. Each interesting spectrum is calibrated and compared to the line-by-line spectral code SPARTAN used for the simulation of the radiative emission of entry-type plasma. Finally, a discussion is proposed about the nucleation phenomenon which is occurred in the ICP torch with the N2-CH4 plasma. Preliminary studies show the synthesis of nanostructured carbon on the quartz tube.Comment: Radiation of High Temperature Gases in Atmospheric Entry, Heraklion : Greece (2008

Using Statistico-Relational Model for Activity Recognition in Smart Home

International audienceThis paper presents the use of a model which mixes logical knowledge and statistical inference to recognize Activities of Daily Living (ADL) from sensors in a smart home. This model called Markov Logic Network (MLN) has different implementations and we propose to compare three of them, from the widely used Alchemy 1 to the new generic framework DeepDive 2. Finally, we discuss the interest these software products can have for real time activity recognition

Multichannel Automatic Recognition of Voice Command in a Multi-Room Smart Home : an Experiment involving Seniors and Users with Visual Impairment

International audienceVoice command system in multi-room smart homes for assist- ing people in loss of autonomy in their daily activities must face several challenges, one of which being the distant condi- tion which impacts the ASR system performance. This paper presents an approach to improve voice command recognition at the decoding level by using multiple sources and model adap- tation. The method has been tested on data recorded with 11 elderly and visually impaired participants in a real smart home. The results show an error rate of 3.2% in off-line condition and of 13.2% in on-line condition

Les technologies de la parole et du TALN pour l'assistance à domicile des personnes âgées : un rapide tour d'horizon (Quick tour of NLP and speech technologies for ambient assisted living) [in French]

National audiencePour relever le défi du maintien à domicile de la population vieillissante, une des solutions retenues par les pays industrialisés est le développement massif des Technologies de l'Information et de la Communication (TIC). Les TIC représentent une opportunité importante pour améliorer la vie quotidienne des personnes âgées afin qu'elles soient toujours maitresses de leurs choix et qu'elles utilisent la technologie pour continuer à vivre de manière autonome, à apprendre et à s'investir dans la vie sociale. Les technologies du traitement du langage naturelle et de la parole qui se trouvent au cœur de la communication humaine, ont donc un rôle significatif à jouer. Dans cet article nous dressons un tour d'horizon des technologies du TALN et du traitement de la parole actuellement développées dans ce cadre et des verrous ou écueils techniques ou éthiques qui peuvent limiter leur impact

Reconnaissance automatique de la parole distante dans un habitat intelligent : méthodes multi-sources en conditions réalistes (Distant Speech Recognition in a Smart Home : Comparison of Several Multisource ASRs in Realistic Conditions) [in French]

International audienceLe domaine des maisons intelligentes s'est développé dans le but d'améliorer l'assistance aux personnes en perte d'autonomie. La reconnaissance automatique de la parole (RAP) commence à être utilisée, mais reste en retrait par rapport à d'autres technologies. Nous présentons le projet Sweet-Home ayant pour objectif le contrôle de l'environnement domestique par la voix. Plusieurs approches, état de l'art et nouvelles, sont évaluées sur des données enregistrées en conditions réalistes. Le corpus de parole distante, enregistré auprès de 21 locuteurs simule des scénarios intégrant des activités journalières dans un appartement équipé de plusieurs microphones. Les techniques opérant au cours du décodage et utilisant des connaissances a priori permettent d'obtenir des résultats très intéressants par rapport à un système RAP classique

Preliminary Study of Adaptive Decision-Making System for Vocal Command in Smart Home

International audienceIn smart homes, prediction and decision are often defined a priori and require tuning from the user, which can be tedious, and complex. However, these smart homes have the ability to analyze the user behavior and to modify their decisions automatically. We present a preliminary study that tests a decision system from voice command and the user's context, which is modified by reinforcement learning. The system ran on a realistic corpus, which shows the interest of such an adaptation

Étude préliminaire d'une méthode de prise de décision adaptative pour la commande vocale dans un habitat intelligent

International audienceIn smart homes, prediction and decision are often defined a priori and require tuning from the user, which can be tedious, and complex. However, these smart home can demonstrate the ability to analyse the user behavior and so as to modify its decisions automatically. We present a preliminary study that tests a decision system from voice command and context which is modified by reinforcement learning. The system was run on a realistic corpus which shows the interest of such an adaptation.Dans les habitats intelligents, les prédictions et décisions qui sont souvent faites a priori nécessitent de la part de l'utilisateur une configuration qui peut être complexe et fastidieuse. Ces habitats ont pourtant des capacités de perception requises pour analyser le comportement de l'utilisateur et modifier ses décisions automatiquement. Nous présentons une étude préliminaire qui teste un système de décision à partir d'une commande vocale et de son contexte modifié par renforcement. Le système expérimenté sur un corpus réaliste montre le potentiel d'une telle adaptation

Making Context Aware Decision from Uncertain Information in a Smart Home: A Markov Logic Network Approach

International audienceThis research addresses the issue of building home automa- tion systems reactive to voice for improved comfort and autonomy at home. The focus of this paper is on the context-aware decision process which uses a dedicated Markov Logic Network approach to benefit from the formal logical representation of domain knowledge as well as the abil- ity to handle uncertain facts inferred from real sensor data. The approach has been experimented in a real smart home with naive and users with special needs

How affects can perturbe the automatic speech recognition of domotic interactions

International audienceIn Smart Home, the vocal home automation orders, for comfort purposes, or assistive devoted, have been pointed as the more relevant interaction for ambient assisted living. Even if the orders are very strictly formulated, when they are daily used (directed to the smart home, or to a robot mediator), they become often pronounced with various affects. In this paper we have evaluated how some state of the art ASR systems shut down with expressive orders, acted or spontaneous, and how the ASR training with neutral and/or acted and/or spontaneous expressive commands corpus can greatly modify the ASR performances