Location choice with longitudinal WiFi data

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Publications associées (31)

New particle formation event detection with Mask R-CNN

Lubna Dada, Xinyang Li

Atmospheric new particle formation (NPF) is an important source of climate-relevant aerosol particles which has been observed at many locations globally. To study this phenomenon, the first step is to identify whether an NPF event occurs or not on a given ...

Copernicus Publications2022

Ten seconds of my nights: Exploring methods to measure brightness, loudness and attendance and their associations with alcohol use from video clips

Daniel Gatica-Perez, Skanda Muralidhar, Lakmal Buddika Meegahapola

Introduction Most evidence on associations between alcohol use behaviors and the characteristics of its social and physical context is based on self-reports from study participants and, thus, only account for their subjective impressions of the situation. ...

2021

Sparsely Observed Functional Time Series: Theory and Applications

Tomas Rubin

Functional time series is a temporally ordered sequence of not necessarily independent random curves. While the statistical analysis of such data has been traditionally carried out under the assumption of completely observed functional data, it may well ha ...

EPFL2021

Validating model-based data interpretation methods for quantification of reserve capacity

Ian Smith, Sai Ganesh Sarvotham Pai

Optimal performance of civil infrastructure is an important aspect of liveable cities. A judicious combination of physics-based models with monitoring data in a validated methodology that accounts for uncertainties is explored in this paper. This methodolo ...

2021

The Imitation Game: Algorithm Selection by Exploiting Black-Box Recommenders

Rachid Guerraoui, Georgios Damaskinos

Cross-validation is commonly used to select the recommendation algorithms that will generalize best on yet unknown data. Yet, in many situations the available dataset used for cross-validation is scarce and the selected algorithm might not be the best suit ...

Springer2021

L-mode plasmas analyses and current ramp-up predictions for a JT-60SA hybrid scenario

Timothy Goodman, Javier García Hernández, Matteo Vallar

In this work, L-mode analyses are performed in order to assess a modeling framework for the prediction of electron cyclotron resonant heating (ECRH) -assisted current ramp-up phases for JT-60SA tokamak hybrid scenario #4-2. We compare two turbulence transp ...

IOP PUBLISHING LTD2021

Algorithms for Walking Speed Estimation Using a Lower-Back-Worn Inertial Sensor: A Cross-Validation on Speed Ranges

Kamiar Aminian, Anisoara Ionescu, Abolfazl Soltani

Walking/gait speed is a key measure for daily mobility characterization. To date, various studies have attempted to design algorithms to estimate walking speed using an inertial sensor worn on the lower back, which is considered as a proper location for ac ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Disparity Between Batches as a Signal for Early Stopping

Patrick Thiran, Mahsa Forouzesh

We propose a metric for evaluating the generalization ability of deep neural networks trained with mini-batch gradient descent. Our metric, called gradient disparity, is the l2 norm distance between the gradient vectors of two mini-batches drawn from the t ...

Springer2021

Laser-induced liquid micro-jets for drug delivery

Jan Krizek

Jet injection devices have been studied and developed for transdermal drug delivery to avoid the use of needles. Such contact-less devices provide several advantages such as better dose control, lateral and depth localisation, lower collateral damage than ...

EPFL2021

Two mixed finite element formulations for the weak imposition of the Neumann boundary conditions for the Darcy flow

Erik Burman, Riccardo Puppi

We propose two different discrete formulations for the weak imposition of the Neumann boundary conditions of the Darcy flow. The Raviart-Thomas mixed finite element on both triangular and quadrilateral meshes is considered for both methods. One is a consis ...

Walter De Gruyter2021

Determining 1D fast-ion velocity distribution functions from ion cyclotron emission data using deep neural networks

Ambrogio Fasoli, Marcelo Baquero Ruiz

The relationship between simulated ion cyclotron emission (ICE) signals s and the corresponding 1D velocity distribution function f(upsilon(perpendicular to)) of the fast ions triggering the ICE is modeled using a two-layer deep neural network. The network ...

2021

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