Publications associées à Real-Time Musculoskeletal Kinematics and Dynamics Analysis Using Marker- and IMU-Based Solutions in Rehabilitation

Anisotropic Adaptive Finite Elements for a p-Laplacian Problem

The p-Laplacian problem -del & sdot; ((mu + |del u|(p-2))del u) = f is considered, where mu is a given positive number. An anisotropic a posteriori residual-based error estimator is presented. The error estimator is shown to be equivalent, up to higher ord ...

Walter De Gruyter Gmbh2024

VDMNav: Software Architecture for Aerodynamically Constrained Navigation on Small Fixed-Wing Drones

Jan Skaloud, Gabriel François Laupré

Navigation of drones is predominantly based on sensor fusion algorithms. Most of these algorithms make use of some form of Bayesian filtering with a majority employing an Extended Kalman Filter (EKF), wherein inertial measurements are fused with a Global N ...

2024

Experimental Validation of a Unified and Linear State Estimation Method for Hybrid AC/DC Microgrids

Mario Paolone, Willem Lambrichts

This paper presents the experimental validation of a linear recursive state estimation (SE) process for hybrid AC/DC microgrids proposed in the authors' previous work. The SE uses a unified and linear measurement model that relies on the use of synchronize ...

IEEE2023

An equilibrated flux a posteriori error estimator for defeaturing problems

Ondine Gabrielle Chanon, Annalisa Buffa, Rafael Vazquez Hernandez, Denise Grappein

An a posteriori error estimator based on an equilibrated flux reconstruction is proposed for defeaturing problems in the context of finite element discretizations. Defeaturing consists in the simplification of a geometry by removing features that are consi ...

2023

Timing and spatial selection bias in rapid extreme event attribution

Anthony Christopher Davison, Ophélia Mireille Anna Miralles

Selection bias may arise when data have been chosen in a way that subsequent analysis does not account for. Such bias can arise in climate event attribution studies that are performed rapidly after a devastating "trigger event'', whose occurrence correspon ...

ELSEVIER2023

Functional estimation of anisotropic covariance and autocovariance operators on the sphere

Victor Panaretos, Julien René Pierre Fageot, Matthieu Martin Jean-André Simeoni, Alessia Caponera

We propose nonparametric estimators for the second-order central moments of possibly anisotropic spherical random fields, within a functional data analysis context. We consider a measurement framework where each random field among an identically distribute ...

2022

Adaptive analysis-aware defeaturing

Ondine Gabrielle Chanon

Removing geometrical details from a complex domain is a classical operation in computer aided design for simulation and manufacturing. This procedure simplifies the meshing process, and it enables faster simulations with less memory requirements. However, ...

EPFL2022

Removing Algorithmic Discrimination (With Minimal Individual Error)

Rachid Guerraoui, El Mahdi El Mhamdi, Le Nguyen Hoang, Alexandre David Olivier Maurer

We address for the first time the problem of correcting group discriminations within a score function, while minimizing the individual error. Each group is described by a probability density function on the set of profiles. We first solve the problem analy ...

2022

GNSS/INS Kalman Filter Integrity Monitoring with Uncertain Time Correlated Error Processes

Omar Garcia Crespillo

Safety-critical navigation applications require that estimation errors be reliably quantified and bounded. Over the last decade, significant effort has been put to guarantee a bounded position estimation by using Global Navigation Satellite Systems (GNSS) ...

EPFL2022

Parametric Estimation For Functional Autoregressive Processes On The Sphere

Alessia Caponera

The aim of this paper is to define a nonlinear least squares estimator for the spectral parameters of a spherical autoregressive process of order 1 in a parametric setting. Furthermore, we investigate on its asymptotic properties, such as weak consistency ...

2022

Analysis of Dampers in Time-Sensitive Networks With Non-Ideal Clocks

Jean-Yves Le Boudec, Ehsan Mohammadpour

Dampers are devices that reduce delay jitter in the context of time-sensitive networks, by delaying packets for the amount written in packet headers. Jitter reduction is required by some real-time applications; beyond this, dampers have the potential to so ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

TimeEvolver: A program for time evolution with improved error bound

Sebastian Zell

We present TimeEvolver, a program for computing time evolution in a generic quantum system. It relies on well-known Krylov subspace techniques to tackle the problem of multiplying the exponential of a large sparse matrix iH, where His the Hamiltonian, with ...

ELSEVIER2022

Online Kinematic and Dynamic Parameter Estimation for Autonomous Surface and Underwater Vehicles

Alcherio Martinoli, Anwar Ahmad Quraishi

One of the main challenges in underwater robot localization is the scarcity of external positioning references. Therefore, accurate inertial localization in between external position updates is crucial for applications such as underwater environmental samp ...

2021

Adaptive Social Learning

Ali H. Sayed, Virginia Bordignon

This work proposes a novel strategy for social learning by introducing the critical feature of adaptation. In social learning, several distributed agents update continually their belief about a phenomenon of interest through: i) direct observation of strea ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Does jackknife scale really matter for accurate large-scale structure covariances?

Ginevra Favole

The jackknife method gives an internal covariance estimate for large-scale structure surveys and allows model-independent errors on cosmological parameters. Using the SDSS-III BOSS CMASS sample, we study how the jackknife size and number of resamplings imp ...

OXFORD UNIV PRESS2021

Euclid : Effects of sample covariance on the number counts of galaxy clusters

Georges Meylan, Richard Massey, Yi Wang

Aims. We investigate the contribution of shot-noise and sample variance to uncertainties in the cosmological parameter constraints inferred from cluster number counts, in the context of the Euclid survey. ...

EDP SCIENCES S A2021

Experimental assessment of traffic density estimation at link and network level with sparse data

Nikolaos Geroliminis, Anna Takayasu

This paper investigates the accuracy of mean density estimation from direct sensing at link and network levels. Different calculation methods are compared depending on sensor type, probe vehicles or loop detectors, and availability to quantify the magnitud ...

TAYLOR & FRANCIS LTD2022

Review of control strategies for lower-limb exoskeletons to assist gait

Mohamed Bouri, Auke Ijspeert, Romain Pierre François Baud, Ali Reza Manzoori

Background Many lower-limb exoskeletons have been developed to assist gait, exhibiting a large range of control methods. The goal of this paper is to review and classify these control strategies, that determine how these devices interact with the user. Met ...

BioMed Central2021

A hierarchical approach to the a posteriori error estimation of isogeometric Kirchhoff plates and Kirchhoff–Love shells

Annalisa Buffa, Pablo Antolin Sanchez, Luca Coradello

This work focuses on the development of a posteriori error estimates for fourth-order, elliptic, partial differential equations. In particular, we propose a novel algorithm to steer an adaptive simulation in the context of Kirchhoff plates and Kirchhoff–Lo ...

2020

Adaptive isogeometric analysis on two-dimensional trimmed domains based on a hierarchical approach

Annalisa Buffa, Pablo Antolin Sanchez, Luca Coradello, Rafael Vazquez Hernandez

The focus of this work is on the development of an error-driven isogeometric framework, capable of automatically performing an adaptive simulation in the context of second- and fourth-order, elliptic partial differential equations defined on two-dimensiona ...

2020