Modelling the exposure of children to extremely low frequency magnetic fields in the ELFSTAT project

Autor: Bonato, M, Parazzini, M., Chiaramello, E, Fiocchi, S., Le Brusquet, Laurent, Magne, I., Souques, M., Röösli, M, Ravazzani, P
Přispěvatelé: Consiglio Nazionale delle Ricerche, Istituto di Elettronica e di Ingegneria dell’Informazione e delle Telecomunicazioni IEIIT (CNR), Laboratoire des signaux et systèmes (L2S), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Service des études médicales, EDF–Gaz de France (SEM-EDF GDF), EDF (EDF), Epidemiology & Public Health [Basel, Switzerland], Swiss Tropical and Public Health Institute [Basel]-Medical School University of Basel
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: BioEM 2018
BioEM 2018, Jun 2018, Portorož, Slovenia
BioEM2018, Piran, Portoro?, Slovenia, 24-29 June, 2018
info:cnr-pdr/source/autori:M. Bonato, M. Parazzini, E. Chiaramello, S. Fiocchi, L. Le Brusquet, I. Magne, M. Souques, M. Röösli and P. Ravazzani/congresso_nome:BioEM2018/congresso_luogo:Piran, Portoro?, Slovenia/congresso_data:24-29 June, 2018/anno:2018/pagina_da:/pagina_a:/intervallo_pagine
ISSN: 2015-2019
Popis: International audience; ELFSTAT project, founded by the French ANSES (2015-2019, Grant agreement n. 2015/1/202), aims at characterizing children's exposure to extremely low frequency magnetic fields (ELF-MF) in real exposure scenarios using stochastic approaches. In this paper, a stochastic approach for extracting information from dataset of recorded ELF-MF signals is presented. The aim is to obtain a better characterization and description of the phenomenon and to investigate on possible correlations or different features between various data subsets.
Databáze: OpenAIRE