Publication

Assessment of a recent tribocorrosion model for wear of metal-on-metal hip joints: Comparison between model predictions and simulator results

Publications associées (30)

Spatially adaptive machine learning models for predicting water quality in Hong Kong

Water quality prediction in the spatially heterogeneous environment is challenging as the importance of water quality parameters (WQPs) and the performance of prediction models may vary across space. Thus, this study proposed spatially adaptive machine lea ...

ELSEVIER2023

Single-arm diagnostic electrocardiography with printed graphene on wearable textiles

Ata Jedari Golparvar

Stimulated by the COVID-19 outbreak, the global healthcare industry better acknowledges the necessity of innovating novel methods for remote healthcare monitoring and treating patients outside clinics. Here we report the development of two different types ...

ELSEVIER SCIENCE SA2023

Data-driven modeling of beam loss in the LHC

Tatiana Pieloni, Michael Schenk, Loïc Thomas Davies Coyle, Ekaterina Krymova

In the Large Hadron Collider, the beam losses are continuously measured for machine protection. By design, most of the particle losses occur in the collimation system, where the particles with high oscilla-tion amplitudes or large momentum error are scrape ...

FRONTIERS MEDIA SA2023

Modeling the origins of adhesive wear across scales

Son-Jonathan Pham-Ba

Friction and wear occur at every interface between solid materials. In the design of mechanical devices, it is desirable to be able to quantify and control the amount of friction and wear, as well as predict their evolution with time. ``Tribology'' is the ...

EPFL2022

Polyethylene wear of dual mobility cups: a comparative analysis based on patient-specific finite element modeling

Alexandre Terrier, Matthieu Boubat, Ehsan Sarshari

Purpose Concerns remain about potential increased wear with dual mobility cups related to the multiple articulations involved in this specific design of implant. This finite element analysis study aimed to compare polyethylene (PE) wear between dual mobili ...

SPRINGER2022

Are socially-aware trajectory prediction models really socially-aware?

Alexandre Massoud Alahi, Seyed Mohsen Moosavi Dezfooli, Saeed Saadatnejad, Mohammadhossein Bahari, Pedram Khorsandi

Our transportation field has recently witnessed an arms race of neural network-based trajectory predictors. While these predictors are at the core of many applications such as autonomous navigation or pedestrian flow simulations, their adversarial robustne ...

2022

Effect of wear particles and roughness on nanoscale friction

Jean-François Molinari, Enrico Milanese, Tobias Brink

Frictional contacts lead to the formation of a surface layer called the third body, consisting of wear particles and structures resulting from their agglomerates. Its behavior and properties at the nanoscale control the macroscopic tribological performance ...

2022

Failure and success of the spectral bias prediction for Laplace Kernel Ridge Regression: the case of low-dimensional data

Matthieu Wyart, Umberto Maria Tomasini, Antonio Sclocchi

Recently, several theories including the replica method made predictions for the generalization error of Kernel Ridge Regression. In some regimes, they predict that the method has a 'spectral bias': decomposing the true function f* on the eigenbasis of the ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2022

Putting Temperature into the Equation: Development and Validation of Algorithms to Distinguish Non-Wearing from Inactivity and Sleep in Wearable Sensors

Kamiar Aminian, Anisoara Ionescu, Sara Pagnamenta

Long-term monitoring of real-life physical activity (PA) using wearable devices is increasingly used in clinical and epidemiological studies. The quality of the recorded data is an important issue, as unreliable data may negatively affect the outcome measu ...

MDPI2022

Towards real-world biomechanical analysis of performance and functional capacity using wearable sensors

Salil Apte

Today, wearable heart rate monitors are an integral part of runners' training sessions, with heart rate data routinely used to assess effort intensity and stress on the body. As athletes translate their physical capacity into performance on the field throu ...

EPFL2022