Characterization of a radial cylindrical spring using an electromechanical test bench

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Publications associées (31)

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Soumaya Elkantassi

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. ...

EPFL2023

Automated neuron tracking inside moving and deforming C. elegans using deep learning and targeted augmentation

Sahand Jamal Rahi, Kseniia Korchagina

Reading out neuronal activity from three-dimensional (3D) functional imaging requires segmenting and tracking individual neurons. This is challenging in behaving animals if the brain moves and deforms. The traditional approach is to train a convolutional n ...

Nature Portfolio2023

Automated music composition and generation system and method

Florian François Colombo

An automated music composition and generation system for automatically harmonizing digital pieces of music using an automated music composition and generation engine for multi-voice music harmonization, including a system-user interface configured to input ...

2023

lifex-ep: a robust and efficient software for cardiac electrophysiology simulations

Alfio Quarteroni, Francesco Regazzoni, Marco Fedele, Stefano Pagani

Background: Simulating the cardiac function requires the numerical solution of multi-physics and multi-scale mathematical models. This underscores the need for streamlined, accurate, and high-performance computational tools. Despite the dedicated endeavors ...

BMC2023

Epidemic Learning: Boosting Decentralized Learning with Randomized Communication

Rachid Guerraoui, Anne-Marie Kermarrec, Sadegh Farhadkhani, Rafael Pereira Pires, Rishi Sharma, Marinus Abraham de Vos

We present Epidemic Learning ( EL ), a simple yet powerful decentralized learning (DL) algorithm that leverages changing communication topologies to achieve faster model convergence compared to conventional DL approaches. At each round of EL, each node sen ...

2023

A study of the K^(+) → π^(0)e^(+)νγ decay

Alessandro Mapelli, Radoslav Marchevski, Alina Kleimenova

A sample of 1.3 x 10^(5) K^(+) → π^(0)e^(+)νγ candidates with less than 1% background was collected by the NA62 experiment at the CERN SPS in 2017-2018. Branching fraction measurements are obtained at percent relative precision in three restricted kinemati ...

Springer Nature2023

Encoding and Decoding Narratives: Datafication and Alternative Access Models for Audiovisual Archives

Yuchen Yang

Situated in the intersection of audiovisual archives, computational methods, and immersive interactions, this work probes the increasingly important accessibility issues from a two-fold approach. Firstly, the work proposes an ontological data model to hand ...

ACM2023

Epigenome-wide DNA methylation in externalizing behaviours: A review and combined analysis

Maria del Carmen Sandi Perez, Mandy Meijer

DNA methylation (DNAm) is one of the most frequently studied epigenetic mechanisms facilitating the interplay of genomic and environmental factors, which can contribute to externalizing behaviours and related psychiatric disorders. Previous epigenome-wide ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Identification of typical district configurations: A two-step global sensitivity analysis framework

François Maréchal, Jonas Schnidrig, Cédric Terrier

The recent geopolitical conflicts in Europe highlighted the sensibility of the current energy system to the volatility of energy carrier prices. In the prospect of defining robust energy system configurations to ensure energy supply stability, it is necess ...

2023

Harmonization of multi-scanner in vivo magnetic resonance spectroscopy: ENIGMA consortium task group considerations

Cristina Ramona Cudalbu

Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging technique that allows for the measurement of brain metabolites that has demonstrated utility in diagnosing and characterizing a broad range of neurological diseases. Its impa ...

FRONTIERS MEDIA SA2023

Center-aware Adversarial Augmentation for Single Domain Generalization

Mathieu Salzmann, Zhiye Wang

Domain generalization (DG) aims to learn a model from multiple training (i.e., source) domains that can generalize well to the unseen test (i.e., target) data coming from a different distribution. Single domain generalization (SingleDG) has recently emerge ...

IEEE COMPUTER SOC2023

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