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Concept

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Publications associées (29)

Computation of sensitivity coefficients in fixed source simulations with SERPENT2

Andreas Pautz, Mathieu Hursin

Within the scope of the implementation of a nuclear data pipeline aiming at producing the best possible evaluated nuclear data files, a major point is the production of relevant sensitivity coefficients when including integral benchmark information. Thanks ...

Elsevier Science Sa2024

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Jean-Paul Richard Kneib, Emma Elizabeth Tolley, Michele Bianco, Tianyue Chen

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Oxford Univ Press2024

Capsizing due to friction-induced twist in the failure of stopper knots

Pedro Miguel Nunes Pereira de Almeida Reis, Paul Johanns

We investigate the failure mechanism of stopper knots, with a particular focus on the figure -8 knot as a representative example. Stopper knots are widely used in climbing, sailing, racket stringing, and sewing to maintain tension in ropes, strings, or thr ...

Elsevier2024

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Seyedbehzad Bozorgtabar

Informative sample selection in an active learning (AL) setting helps a machine learning system attain optimum performance with minimum labeled samples, thus reducing annotation costs and boosting performance of computer-aided diagnosis systems in the pres ...

Elsevier2024

High-precision optical magnetometry using Nitrogen Vacancies in CVD diamond

Hossein Babashah

Sensing weak magnetic fields is a topic of great importance in basic science and technology due to its wide range of applications. In this context, solid-state and nanoscale quantum sensors are poised to revolutionize the sensing platforms due to their ult ...

EPFL2023

Bootstrapping for Approximate Homomorphic Encryption with Negligible Failure-Probability by Using Sparse-Secret Encapsulation

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Jean-Philippe Léonard Bossuat

Bootstrapping parameters for the approximate homomorphic-encryption scheme of Cheon et al., CKKS (Asiacrypt 17), are usually instantiated using sparse secrets to be efficient. However, using sparse secrets constrains the range of practical parameters withi ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

Mixed-precision explicit stabilized Runge-Kutta methods for single- and multi-scale differential equations

Giacomo Rosilho De Souza

Mixed-precision algorithms combine low-and high-precision computations in order to benefit from the performance gains of reduced-precision without sacrificing accuracy. In this work, we design mixed-precision Runge-Kutta-Chebyshev (RKC) methods, where high ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

Precise determination of the low-energy electronuclear Hamiltonian of LiY1-xHoxF4

Sandrine Gerber, Gabriel Aeppli, Michael Müller

The insulating rare-earth magnet LiY1-xHoxF4 has received great attention because a laboratory field applied perpendicular to its crystallographic c axis converts the low-energy electronic spin Hamiltonian into the (dilute) transverse field Ising model. Th ...

2022

Removing Algorithmic Discrimination (With Minimal Individual Error)

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

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

Kernel Density Estimation of Electromyographic Signals and Ensemble Learning for Highly Accurate Classification of a Large Set of Hand/Wrist Motions

Parviz Ghaderi

The performance of myoelectric control highly depends on the features extracted from surface electromyographic (sEMG) signals. We propose three new sEMG features based on the kernel density estimation. The trimmed mean of density (TMD), the entropy of dens ...

FRONTIERS MEDIA SA2022

Monitoring weekly progress of front crawl swimmers using IMU-based performance evaluation goal metrics

Kamiar Aminian, Farzin Dadashi, Fabien Massé, Mahdi Hamidi Rad

Technical evaluation of swimming performance is an essential factor in preparing elite swimmers for their competitions. Inertial measurement units (IMUs) have attracted much attention recently because they can provide coaches with a detailed analysis of sw ...

FRONTIERS MEDIA SA2022

Une approche computationnelle du cadastre napoléonien de Venise

Frédéric Kaplan, Isabella Di Lenardo, Raphaël Barman, Federica Pardini

At the beginning of the 19th century, the Napoleonic administration introduced a new standardised description system to give an objective account of the form and functions of the city of Venice. The cadastre, deployed on a European scale, was offering for ...

2021

Pedestrian intention prediction: A convolutional bottom-up multi-task approach

Alexandre Massoud Alahi, Taylor Ferdinand Mordan

The ability to predict pedestrian behaviour is crucial for road safety, traffic management systems, Advanced Driver Assistance Systems (ADAS), and more broadly autonomous vehicles. We present a vision-based system that simultaneously locates where pedestri ...

2021

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

A platform for experimental precision medicine: The extended BXD mouse family

Johan Auwerx, Evan Graehl Williams

The challenge of precision medicine is to model complex interactions among DNA variants, phenotypes, development, environments, and treatments. We address this challenge by expanding the BXD family of mice to 140 fully isogenic strains, creating a uniquely ...

CELL PRESS2021

Development and evaluation of galaxy shape measurement algorithms for radio interferometric data

Vasileios Angelopoulos

The purpose of this Thesis is to develop, test, and characterize different models attempting to tackle the problem of measurement of galaxy shapes applied in interferometric observations. Shape measurement is a tool for estimating the underlying shear due ...

EPFL2021

Millisecond lattice gasification for high-density CO2- and O2-sieving nanopores in single-layer graphene

Emad Oveisi, Kumar Varoon Agrawal, Mounir Driss Mensi, Luis Francisco Villalobos Vazquez de la Parra, Shiqi Huang, Mostapha Dakhchoune, Shaoxian Li, Deepu Joseph Babu, Marina Micari

Etching single-layer graphene to incorporate a high pore density with sub-angstrom precision in molecular differentiation is critical to realize the promising high-flux separation of similar-sized gas molecules, e.g., CO2 from N2. However, rapid etching ki ...

2021

Evaluating salient object detection in natural images with multiple objects having multi-level saliency

Sabine Süsstrunk, Gökhan Yildirim

Salient object detection is evaluated using binary ground truth (GT) with the labels being salient object class and background. In this study, the authors corroborate based on three subjective experiments on a novel image dataset that objects in natural im ...

2020

Chirok: a post-refinement tool to analyse absolute structure

Philip Pattison

Chirok is software for a post-refinement test of the absolute structure. The software allows a user to calculate a distribution of the measure of chirality based on intensity quotients and linked to the Flack parameter. The distribution is fitted by a set ...

2020

Integrating the Finite Element Method with a Data-Driven Approach for Dam Displacement Prediction

Zhenzhu Meng

Both numerical simulations and data-driven methods have been applied in dam's displacement modeling. For monitored displacement data-driven methods, the physical mechanism and structural correlations were rarely discussed. In order to take the spatial and ...

2020