1,421 research outputs found

    Bayesian Programming Multi-Target Tracking: an Automotive Application

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    A prerequisite to the design of future Advanced Driver Assistance Systems for cars is a sensing system providing all the information required for high-level driving assistance tasks. In particular, target tracking is still challenging in urban trafc situations, because of the large number of rapidly maneuvering targets. The goal of this paper is to present an original way to perform target position and velocity, based on the occupancy grid framework. The main interest of this method is to avoid the decision problem of classical multi-target tracking algorithms. Obtained occupancy grids are combined with danger estimation to perform an elementary task of obstacle avoidance with an electric car

    Ultrasound to Enhance a Liquid–Liquid Reaction

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    Liquid–liquid mass transfer with ultrasound was investigated experimentally during the hydrolysis of n-amyl acetate. Power ultrasound is supposed to improve the yield and kinetics of such multiphase chemical reactions thanks to the mechanical effects of cavitation. Indeed, implosion of micro-bubbles at the vicinity of the liquid– liquid interface generates disruption of this surface, and enhances mixing in the liquid around the inclusion, thus improving mass transfer between the two phases. This effect has been demonstrated here on the hydrolysis of n-amyl acetate by sodium hydroxide, a rather slow reaction but influenced by mass transfer; the reaction is carried out in a glass jacketed reactor, 500 mL of volume, equipped with a Rushton turbine and a 20 kHz sonotrode dipping in the solution. The ester is initially pure in the organic dispersed phase, and sodium hydroxide has an initial concentration of 300 mol/m3; one of the products, pentanol partitions between the two phases and the sodium salt stays in the aqueous phase. The initial apparent reaction rate is measured from the record of the conductivity giving the concentration of alkali versus time. The reaction rate was always found to increase when ultrasound is superimposed to mechanical stirring (at 600 rpm), with a positive influence of input power (20 and 50 W). When varying initial concentration (300 and 600 mol/m3), temperature (36 and 45°C) and ultrasound emitter (sonotrode or cuphorn), the benefit of ultrasound over mechanical agitation was systematic. The only case of a weak influence of ultrasound was the sonication of a dense medium, containing 23% of organic phase and impeding the propagation of ultrasound

    The temperature dependence of the isothermal bulk modulus at 1 bar pressure

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    It is well established that the product of the volume coefficient of thermal expansion and the bulk modulus is nearly constant at temperatures higher than the Debye temperature. Using this approximation allows predicting the values of the bulk modulus. The derived analytical solution for the temperature dependence of the isothermal bulk modulus has been applied to ten substances. The good correlations to the experiments indicate that the expression may be useful for substances for which bulk modulus data are lacking

    Geometric and Bayesian models for safe navigation in dynamic environments

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    Autonomous navigation in open and dynamic environments is an important challenge, requiring to solve several difficult research problems located on the cutting edge of the state of the art. Basically, these problems may be classified into three main categories: (a) SLAM in dynamic environments; (b) detection, characterization, and behavior prediction of the potential moving obstacles; and (c) online motion planning and safe navigation decision based on world state predictions. This paper addresses some aspects of these problems and presents our latest approaches and results. The solutions we have implemented are mainly based on the followings paradigms: multiscale world representation of static obstacles based on the wavelet occupancy grid; adaptative clustering for moving obstacle detection inspired on Kohonen networks and the growing neural gas algorithm; and characterization and motion prediction of the observed moving entities using Hidden Markov Models coupled with a novel algorithm for structure and parameter learnin

    Appropriateness of internal digital phantoms for monitoring the stability of the UBIS 5000 quantitative ultrasound device in clinical trials

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    In bone status assessment, proper quality assurance/quality control is crucial since changes due to disease or therapeutic treatment are very small, in the order of 2-5%. Unlike for dual X-ray absorptiometry, quality control procedures have not been extensively developed and validated for quantitative ultrasound technology, limiting its use in longitudinal monitoring. While the challenge of developing an ideal anthropometric phantom is still open, some manufacturers use the concept of the internal digital phantom mimicking human characteristics to check the stability of their device. The objective of the study was to develop a sensitive model of quality control suitable for the correction of QUS patient data. In order to achieve this goal, we simulated a longitudinal device lifetime with both correct and malfunctioning behaviors. Then, we verified the efficiency of digital phantoms in detecting those changes and subsequently established the in vitro/in vivo relationship. This is the first time that an attempt to validate an internal digital phantom has made, and that this type of validation approach is used. The digital phantom (DP) was designed to mimic normal bone (BUAP2) and osteoporotic bone (BUAP1) properties. The DP was studied using the UBIS 5000 ultrasound device (DMS, France). Diverse malfunctions of the UBIS-5000 were simulated. Several series of measurements were performed on both BUAP1 and 2 and on 12 volunteers at each grade of malfunction. The effect of each simulated malfunction on in vivo and in vitro results was presented graphically by plotting the average BUA values against the percentage change from baseline. The change from baseline in BUA was modeled using linear regression, and the in vivo/in vitro ratio was obtained from the model. All experimentations influenced the measure of BUAP1 and 2 as well as the measure of our 12 volunteers. However, the degree of significance varied as a function of the severity of the malfunction, and the results also differed substantially in magnitude between in vivo and in vitro. Indeed, the DP was about 10 times more sensitive to variations of the transfer function than was the in vivo measurement, which is very reassuring. The sensitivity of the digital phantoms was reliable in the determination of simulated malfunctions of the UBIS-5000. The digital phantoms provided an accurate evaluation of the acoustic performance of the scanner, including the fidelity of transducers. In light of these results, the QC approach of the UBIS-5000 will be extremely simple to implement compared with other devices. Indeed, since the digital phantom was automatically measured during every patient measurement, the QC approach could be built on an individual level basis rather than on an average basi

    Probabilistic Grid-based Collision Risk Prediction for Driving Application

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    International audienceIn the recent years, more and more modern cars have been equipped with perception capabilities. One of the key applications of such perception systems is the estimation of a risk of collision. This is necessary for both Advanced Driver Assistance Systems and Autonomous Navigation. Most approach for risk estimation propose to detect and track the dynamic objects in the scene. Then the risk is estimated as a Time To Collision (TTC) by projecting the object's trajectory in the future. In this paper, we propose a new grid-based approach for collision risk prediction, based on the Hybrid-Sampling Bayesian Occupancy Filter framework. The idea is to compute an estimation of the TTC for each cell of the grid, instead of reasoning on objects. This strategy avoids to solve the difficult problem of multi-objects detection and tracking and provides a probabilistic estimation of the risk associated to each TTC value. After promising initial results, we propose in this paper to evaluate the relevance of the method for real on-road applications, by using a real-time implementation of our method in an experimental vehicle

    Experimental two dimensional cellular flames

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    International audienceThe propagation of very unstable cellular flames (also called self-turbulent flames) is studied experimentally in a Hele-Shaw cell. This quasi-two dimensional configuration allows for quantitative image analysis. The dynamics of the premixed flame is controlled in these conditions by the creation or merging of the cusps that appear on the front
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