Publications related to Occupational noise

Less Conservatism, Stronger Robustness: Iterative Robust Gain-Scheduled Path Following Control of Autonomous Bus With Unstructured and Changing Dynamics

Path-following control is a critical technology for autonomous vehicles. However, time-varying parameters, parametric uncertainties, external disturbances, and complicated environments significantly challenge autonomous driving. We propose an iterative rob ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Neutron-Gamma Noise Measurements in a Zero-Power Reactor Using Organic Scintillators

Andreas Pautz, Vincent Pierre Lamirand, Oskari Ville Pakari

Noise measurements in light water reactor systems aid in generating validation data for integral point kinetic parameter predictions and generating monitoring parameters for reactor safety and safeguards. The CROCUS zero-power reactor has been used to supp ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Observation of non-reciprocal harmonic conversion in real sounds

Romain Christophe Rémy Fleury, Hervé Lissek, Xinxin Guo

Reciprocity guarantees that in most media, sound transmission is symmetric between two points of space when the location of the source and receiver are interchanged. This fundamental law can be broken in non-linear media, often at the cost of detrimental i ...

2023

WINC: A Wireless IoT Network for Multi-Noise Source Cancellation

Haitham Al Hassanieh, Junfeng Guan, Jiaming Wang

This paper introduces Wireless IoT-based Noise Cancellation (WINC) which defines a framework for leveraging a wireless network of IoT microphones to enhance active noise cancellation in noise-canceling headphones. The IoT microphones forward ambient noise ...

Assoc Computing Machinery2023

Repeated Human Exposure to Semivolatile Organic Compounds by Inhalation: Novel Protocol for a Nonrandomized Study

Florian Frédéric Vincent Breider, Dominique Grandjean, Guillaume Suarez, Myriam Borgatta

Background: Semivolatile organic compounds (SVOCs) comprise several different chemical families used mainly as additives in many everyday products. SVOCs can be released into the air as aerosols and deposit on particulate matter during use by dispersion, e ...

2023

Performance investigation of cameras using HDR sensors for daylight glare evaluations

Jan Wienold, Dong Hyun Kim, Geraldine Cai Ting Quek

This study presents a novel framework for evaluating the luminance measurement capabilities of High Dynamic Range (HDR) sensor cameras in indoor glare conditions. Results indicate that the practical usage range of the CSEM VIP camera is significantly lower ...

International Commission on Illumination2023

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Baiwei Guo

Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...

EPFL2023

Deep learning-based galaxy image deconvolution

Frédéric Courbin, Pascale Jablonka, Jean-Luc Starck, Utsav Akhaury, Kevin Michalewicz

With the onset of large-scale astronomical surveys capturing millions of images, there is an increasing need to develop fast and accurate deconvolution algorithms that generalize well to different images. A powerful and accessible deconvolution method woul ...

FRONTIERS MEDIA SA2022

On the reconstruction of the attenuation function of a return-stroke current from the Fourier Transform of finite-duration measurements

Farhad Rachidi-Haeri, Marcos Rubinstein

A correct representation of the lightning current is crucial when the electromagnetic field radiated to a point of interest has to be computed. Based on the engineering models of Transmission Line type, such representation involves the knowledge of the ret ...

2022

A Noise-Resistant Mixed-Discrete Particle Swarm Optimization Algorithm for the Automatic Design of Robotic Controllers

Alcherio Martinoli, Cyrill Silvan Baumann

The automatic design of well-performing robotic controllers is still an unsolved problem due to the inherently large parameter space and noisy, often hard-to-define performance metrics, especially when sequential tasks need to be accomplished. Distal contr ...

2022

Plasma-based Electroacoustic Actuator for Broadband Sound Absorption

Stanislav Sergeev

Environmental noise, mostly related to human activities, has an immense impact on public health. The development of noise reduction technologies is paramount in addressing this problem. Because of practical and economic reasons, a compact, broadband, light ...

EPFL2022

High accuracy measurement of the prompt neutron decay constant in CROCUS using Gamma Noise and bootstrapped uncertainties

Andreas Pautz, Vincent Pierre Lamirand, Oskari Ville Pakari, Pavel Frajtag, Tom Mager

We experimentally demonstrate the advantages of gamma detection for noise measurements to deter-mine the prompt neutron decay constant a of a nuclear reactor using the power spectral density (PSD) method, coupled to a new uncertainty estimation scheme base ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Synthetic realistic noise-corrupted PPG database and noise generator for the evaluation of PPG denoising and delineation algorithms

David Atienza Alonso, Giulio Masinelli, Adriana Arza Valdes, Fabio Isidoro Tiberio Dell'Agnola

This database is meant to evaluate the performance of denoising and delineation algorithms for PPG signals affected by noise. The noise generator allows applying the algorithms under test to an artificially corrupted reference PPG signal and comparing its ...

2021

Moment approach of the multi-species non-linear Coulomb collision operator adapted to particle-in-cell codes

Laurent Villard, Stephan Brunner, Emmanuel Lanti, Moahan Murugappan, Noé Thomas Elie Ohana, Claudio Gheller

In this article an approximated version of the multi-species, non-linear Coulomb collision operator is derived via the use of a truncated moment expansion of the distribution function to compute the Rosenbluth potentials. The evolution of the distribution ...

2021

A modular functional framework for the design and evaluation of multi-robot navigation

Alcherio Martinoli, Cyrill Silvan Baumann

In this work, we address the design of tightly integrated control, estimation, and allocation algorithms allowing a group of robots to move collectively. For doing so, we leverage a modular framework that allows us to define precisely the needed functional ...

Elsevier2021

The Globalization of an Interaction Ritual Chain: “Clapping for Carers” During the Conflict Against COVID-19

Alexandre André Robert Rigal

Sociologists have long been interested in the theoretical possibility of a universal ritual. Despite a growing number of indicators of world society and globalization, there have not been attempts to observe and analyze the international reach of particula ...

2021

Emittance growth suppression with a multibunch feedback in high-energy hadron colliders: Numerical optimization of the gain and bandwidth

Xavier Buffat, Sondre Vik Furuseth

A transverse feedback system can effectively mitigate the emittance growth caused by injection oscillations and machine noise in hadron beams. However, as its action on the beam depends on beam position measurements of finite accuracy, it introduces additi ...

2021

Compound Admittance Matrix Estimation of Three-phase Untransposed Power Distribution Grids using Synchrophasor Measurements

Jean-Yves Le Boudec, Mario Paolone, Fabrizio Sossan, Rahul Kumar Gupta

The paper considers the problem of estimating the parameters of the compound admittance matrix of three-phase untransposed low-and medium-voltage electrical distribution networks using synchrophasor measurements from phasor measurement units (PMUs). The wo ...

2021

A Distributed Luenberger Observer for Linear State Feedback Systems With Quantized and Rate-Limited Communications

Colin Neil Jones, Andrea Alessandretti, Ye Pu, Francisco Fernandes Castro Rego

This article addresses the problem of simultaneous distributed state estimation, and control of linear systems with linear state feedback, subjected to process, and measurement noise, under the constraints of quantized, and rate-limited network data transm ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Fidelity Estimation Improves Noisy-Image Classification with Pretrained Networks

Sabine Süsstrunk, Majed El Helou, Deblina Bhattacharjee, Xiaoyu Lin

Image classification has significantly improved using deep learning. This is mainly due to convolutional neural networks (CNNs) that are capable of learning rich feature extractors from large datasets. However, most deep learning classification methods are ...

IEEE Institute of Electrical and Electronics Engineers2021