Publications associées à On the Use of Extents for Process Monitoring and Fault Diagnosis

Publications associées (25)

Extensions of Peer Prediction Incentive Mechanisms

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

EPFL2024

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Romain Christophe Rémy Fleury, Janez Rus

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

2024

Learning Transformations To Reduce the Geometric Shift in Object Detection

Mathieu Salzmann, Martin Pierre Engilberge, Vidit Vidit

The performance of modern object detectors drops when the test distribution differs from the training one. Most of the methods that address this focus on object appearance changes caused by, e.g., different illumination conditions, or gaps between syntheti ...

Ieee Computer Soc2023

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Boi Faltings, Panayiotis Danassis, Ljubomir Rokvic

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

2023

incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment

Boi Faltings, Naman Goel

A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...

2023

A comprehensive review of digital twin-part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives

Olga Fink

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision- and policy-making, and more, by comprehensively m ...

SPRINGER2023

Gait Phase Estimation in Steady Walking: A Comparative Study of Methods Based on the Phase Portrait of the Hip Angle

Mohamed Bouri, Auke Ijspeert, Ali Reza Manzoori

Accurate real-time estimation of the gait phase (GP) is crucial for many control methods in exoskeletons and prostheses. A class of approaches to GP estimation construct the phase portrait of a segment or joint angle, and use the normalized polar angle of ...

IEEE Xplore2023

Keep Sensors in Check: Disentangling Country-Level Generalization Issues in Mobile Sensor-Based Models with Diversity Scores

Daniel Gatica-Perez, Lakmal Buddika Meegahapola

Machine learning models trained with passive sensor data from mobile devices can be used to perform various inferences pertaining to activity recognition, context awareness, and health and well-being. Prior work has improved inference performance through t ...

Assoc Computing Machinery2023

Scaling behavior of bedload transport: what if Bagnold was right?

Christophe Ancey

There is a paradox in the relationship between bedload transport rates and flow variables: laboratory and field studies have reported on how bedload transport rates depend on flow variables through a power law, but none of the empirical laws fitted to the ...

2023

Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science

Henry Markram, Henry Genet, Alejandra Garcia Rojas Martinez, Sean Lewis Hill, Huanxiang Lu, Mohameth François Sy, Samuel Claude Kerrien, Michaël Fernand Paul Dupont, Silvia Rosario Jimenez Tejeda, Bogdan Roman, Ian Lavriushev, Anna-Kristin Kaufmann, Didac Montero Mendez, Wojciech Adam Wajerowicz, Pierre-Alexandre Fonta, Kenneth William Pirman, Julien Antonin Machon, Jonathan Raël Lurie, Dhanesh Neela Mana, Natalia Stafeeva, Alexander Désiré Ulbrich, Carolina Johanna Elisabeth Lindqvist

Modern data-driven science often consists of iterative cycles of data discovery, acquisition, preparation, analysis, model building and validation leading to knowledge discovery as well as dissemination at scale. The unique challenges of building and simul ...

2023

Robust discrete choice models with t-distributed kernel errors

Michel Bierlaire

Outliers in discrete choice response data may result from misclassification and misreporting of the response variable and from choice behaviour that is inconsistent with modelling assumptions (e.g. random utility maximisation). In the presence of outliers, ...

2023

Making Computer Vision Models Robust and Adaptive

Shuqing Teresa Yeo

Visual perception is indispensable for many real-world applications. However, perception models deployed in the real world will encounter numerous and unpredictable distribution shifts, for example, changes in geographic locations, motion blur, and adverse ...

EPFL2023

A comprehensive review of digital twin - part 1: modeling and twinning enabling technologies

Olga Fink

As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision and policy making, and more, by comprehensively mo ...

SPRINGER2022

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

Cost-Based Decision Support System: A Dynamic Cost Estimation of Key Performance Indicators in Manufacturing

Dimitrios Kyritsis, Foivos Psarommatis Giannakopoulos

An attempt is made to translate five generic key performance indicators (KPIs) into a continuous real-time cost function in a batch order-based manufacturing environment. The challenge of controlling and optimizing resource utilization, production efficien ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Data-driven and Safe Networked Control with Applications to Microgrids

Mustafa Sahin Turan

Today, automatic control is integrated into a wide spectrum of real-world systems such as electrical grids and transportation networks. Many of these systems comprise numerous interconnected agents, perform safety-critical operations, or generate large amo ...

EPFL2022

Equivariant Diffusion for Molecule Generation in 3D

Clément Arthur Yvon Vignac

This work introduces a diffusion model for molecule generation in 3D that is equivariant to Euclidean transformations. Our E(3) Equivariant Diffusion Model (EDM) learns to denoise a diffusion process with an equivariant network that jointly operates on bot ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2022

Numerical investigation on the volute cutwater for pumps running in turbine mode

Elena Vagnoni, Alessandro Morabito

The hydropower sector has recently raised the interest in pump as turbine (PaT) that can be a valid trade-off between capital cost and performance in micro-scale installations. Nevertheless, the modest efficiency of PaTs often restricts their exploitation. ...

Pergamon-Elsevier Science Ltd2021

Preprocessing Antarctic Weather Station (AWS) data in python

Michael Lehning, Franziska Gerber

There are many sources providing atmospheric weather station data for the Antarctic continent. However, variable naming, timestamps and data types are highly variable between the different sources. The published python code intends to make processing of di ...

Zenodo2022

A generic methodology and a digital twin for zero defect manufacturing (ZDM) performance mapping towards design for ZDM

Foivos Psarommatis Giannakopoulos

Over recent years, the manufacturing industry has seen constant growth and change. From one side, it has been affected by the fourth industrial revolution (Industry 4.0). From the other side, it has had to enhance its ability to meet higher customer expect ...

2021