Quantifying evapotranspiration fluxes on green roofs: A comparative analysis of observational methods.

Evapotranspiration (ET) is an important process in green stormwater infrastructure (GSI) aiming to reduce urban drainage, to promote cooling and/or to contribute to an urban hydrological balance restoration closer to the natural one. However, on these structures and particularly on green roofs (GR), its evaluation remains challenging and subject to discussion. Estimates of ET by water balance, energy balance, and an ET chamber were performed on five different plots of a full-scale experimental green roof in Trappes (France).

NoiseCapture smartphone application as pedagogical support for education and public awareness.

Teaching science subjects such as acoustics to youth or the general public can be facilitated by illustrating physical phenomena or scientific issues using fun experiences. A few years ago, our team developed a smartphone application named NoiseCapture with the aim of offering to anyone the opportunity to measure their sound environment and to share their geolocated measurements with the community in order to build a collective noise map. Since then, NoiseCapture team members have experimented with numerous interventions in schools or scientific events for the general public based on the app to explain not only societal and environmental issues related to noise but also to teach acoustic notions and to address technical and scientific topics associated with sound measurement.

Multidimensional analyses of the noise impacts of COVID-19 lockdown.

As part of the Agence Nationale de Recherche Caractérisation des ENvironnements SonorEs urbains (Characterization of urban sound environments) project, a questionnaire was sent in January 2019 to households in a 1 km study area in the city of Lorient, France, to which about 318 responded. The main objective of this questionnaire was to collect information about the inhabitants' perception of the sound environments in their neighborhoods, streets, and dwellings. In the same study area, starting mid-2019, about 70 sensors were continuously positioned, and 15 of them were selected for testing sound source recognition models.

Step In, Step Out from the First Lockdown: An Exploration of COVID-19 Perceptions in France and Quebec.

Objective: The objective of this research was to describe and analyze the role of psychological and behavioral factors on perceptions of COVID-19 in France and Quebec at three different times during the pandemic.

Design: We conducted three qualitative and quantitative studies (Study 1 = 255, Study 2 = 230, Study 3 = 143). Participants were asked to evaluate psychological and behavioral measures: at the beginning of lockdown (Study 1), during lockdown (Study 2), and during lockdown exit (Study 3).

Automatic estimation of the sound emergence of wind turbine noise with nonnegative matrix factorization.

In many countries, the acoustic impact of wind farms is often constrained by a curtailment plan to limit their noise, which spreads in their surroundings. To update the plan, on/off cycle measurements are performed to determine the ambient noise (wind turbines in operation) and residual noise (wind turbines shut down), but these shutdown operations are limited in time, which reduces the representativeness of the estimated in situ emergence. Consequently, a machine learning technique, called nonnegative matrix factorization (NMF), is proposed to estimate the sound emergence of wind turbines continuously, i.

Polyphonic training set synthesis improves self-supervised urban sound classification.

Machine listening systems for environmental acoustic monitoring face a shortage of expert annotations to be used as training data. To circumvent this issue, the emerging paradigm of self-supervised learning proposes to pre-train audio classifiers on a task whose ground truth is trivially available. Alternatively, training set synthesis consists in annotating a small corpus of acoustic events of interest, which are then automatically mixed at random to form a larger corpus of polyphonic scenes.

Estimation of all six parameters of Johnson-Champoux-Allard-Lafarge model for acoustical porous materials from impedance tube measurements.

The open porosity of air-saturated acoustical porous materials is estimated from the low-frequency or high-frequency asymptotes of the real part of the dynamic bulk modulus. Combining this technique with the estimation of the static air-flow resistivity from the low-frequency asymptote of the imaginary part of the dynamic mass density and the analytical inversions of the remaining parameters from the dynamic mass density and bulk modulus [methods introduced by Panneton and Olny, J. Acoust.

Sensitivity analysis of a parabolic equation model to ground impedance and surface roughness for wind turbine noise.

Input parameters of outdoor sound prediction models are related to environmental phenomena, such as atmospheric conditions and ground properties, which are variable in both time and space. In order to obtain reliable predictions, it is essential to get information on uncertainties by quantifying the sensitivity of numerical or analytical models to their input parameters, and thus determine the inputs that will be the main source of uncertainties. This paper focuses on ground parameters impact on sound propagation considering wind turbine noise.

PHROG: A Multimodal Feature for Place Recognition.

Long-term place recognition in outdoor environments remains a challenge due to high appearance changes in the environment. The problem becomes even more difficult when the matching between two scenes has to be made with information coming from different visual sources, particularly with different spectral ranges. For instance, an infrared camera is helpful for night vision in combination with a visible camera.

Noise sensitivity and loudness derivative index for urban road traffic noise annoyance computation.

Urban road traffic composed of powered-two-wheelers (PTWs), buses, heavy, and light vehicles is a major source of noise annoyance. In order to assess annoyance models considering different acoustical and non-acoustical factors, a laboratory experiment on short-term annoyance due to urban road traffic noise was conducted. At the end of the experiment, participants were asked to rate their noise sensitivity and to describe the noise sequences they heard.

Measuring the effect of the rainfall on the windshield in terms of visual performance.

Driving through rain results in reduced visual performance, and car designers have proposed countermeasures in order to reduce the impact of rain on driving performance. In this paper, we propose a methodology dedicated to the quantitative estimation of the loss of visual performance due to the falling rain. We have considered the rain falling on the windshield as the main factor which reduces visual performance in driving.