Publications associées à An Investigation into Machine Learning Matchmaking for Reused Rubble Concrete Masonry Units (RR-CMU)

Publications associées (5)

Euclid: Searches for strong gravitational lenses using convolutional neural nets in Early Release Observations of the Perseus field

Georges Meylan, Benjamin Yvan Alexandre Clement, Olivia Mueller

The Euclid Wide Survey (EWS) is predicted to find approximately 170 000 galaxy-galaxy strong lenses from its lifetime observation of 14 000 deg2 of the sky. Detecting this many lenses by visual inspection with professional astronomers and citizen scientist ...

2025

Steel stresses and shear forces in reinforcing bars due to dowel action

Aurelio Muttoni, Marko Pejatovic

Reinforcing bars in structural concrete are typically designed to carry axial forces. Nevertheless, due to their bending stiffness, the bars can also carry transverse forces, that are associated with the localized bending mechanism (dowel action) resulting ...

2024

Advanced Acoustic Emission-based SHM for Concrete Structures: Real-Time, High-Precision Imaging of Crack Geometry and Damage Source-type Using Moment Tensor Inversion

Brice Tanguy Alphonse Lecampion, Seyyedmaalek Momeni

In this paper, we introduce a novel automated and high-precision acoustic emission (AE) monitoring algorithm and the software SIMORGH, which is suitable for structural health monitoring (SHM) of civil structures. Initially developed for laboratory-scale hy ...

NDT.net2024

Circular and net-zero opportunities in the management of electronic waste in low- and middle-income countries: the example of Ghana

Klaus Benedikt Schönenberger, Solomzi Makohliso

Low- and middle-income countries suffer from excessive accumulation of electronic waste (e-waste), partly owing to a lack of recycling infrastructure and relevant policy frameworks, which can lead to significant toxic exposure of the surrounding population ...

Routledge Journals, Taylor & Francis Ltd2024

How isotropic kernels perform on simple invariants

Matthieu Wyart, Stefano Spigler, Jonas Paccolat

We investigate how the training curve of isotropic kernel methods depends on the symmetry of the task to be learned, in several settings. (i) We consider a regression task, where the target function is a Gaussian random field that depends only on d(paralle ...

IOP PUBLISHING LTD2021