Publications related to Development of a system for part quality prediction and process parameters adjustment in wire electrical discharge machining

Related publications (36)

Controlled learning of pointwise nonlinearities in neural-network-like architectures

Michaël Unser, Alexis Marie Frederic Goujon, Stanislas Ducotterd

We present a general variational framework for the training of freeform nonlinearities in layered computational architectures subject to some slope constraints. The regularization that we add to the traditional training loss penalizes the second-order tota ...

2025

Dependable learning and control through Neural ODEs

Muhammad Zakwan

Neural Networks (NNs), renowned for their universal approximation capabilities, have proven well-suited for parametrizing nonlinear control policies and modeling complex processes from available data. However, several NN architectures are physics-agnostic, ...

EPFL2025

Texture Synthesis using Neural Cellular Automata

Ehsan Pajouheshgar

Self-organization and emergent behavior lie at the core of many natural phenomena, from pattern formation in biological tissues to the collective motion of flocking birds. Harnessing these principles in computational models can unlock powerful approaches f ...

EPFL2025

A ride time-oriented scheduling algorithm for dial-a-ride problems

Nikolaos Geroliminis, Claudia Bongiovanni, Mor Kaspi

This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theor ...

Pergamon-Elsevier Science Ltd2024

Nonlinear two-scale beam simulations accelerated by thermodynamics-informed neural networks

Konstantinos Karapiperis

We introduce an efficient computational framework for the simulation of complex beam networks and architected materials. At its core stands a thermodynamics-informed neural network, which serves as a surrogate material model for the cross-sectional respons ...

2024

Inversing the actuation cycle of dielectric elastomer actuators for a facial prosthesis

Yves Perriard, Yoan René Cyrille Civet, Paolo Germano, Thomas Guillaume Martinez, Stefania Maria Aliki Konstantinidi, Alexis Boegli, Quentin Philippe Mario De Menech

Dielectric Elastomer Actuators (DEAs) are a type of smart material described as compliant capacitors. They show impressive performances as soft actuators, such as a high strain and fast response. Nonetheless, replicating natural muscle function with DEAs h ...

Society of Photo-Optical Instrumentation Engineers (SPIE)2024

DEMO toroidal field coil fast discharge unit integration studies

Roberto Guarino

The Fast Discharge Units (FDUs) of the Superconducting (SC) Toroidal Field (TF) coils in the European demonstration fusion power plant DEMO warrant the machine integrity over its full lifetime against severe failure events, such as SC coil quenches or any ...

Elsevier Science Sa2024

Data from: Optimal blade pitch control for enhanced vertical-axis wind turbine performance

Karen Ann J Mulleners, Sébastien Le Fouest

This directory contains open-source data obtained using a single-bladed H-type vertical-axis wind turbine prototype with individual blade pitching. This data results from the optimisation of the blade's pitching kinematics using a genetic algorithm at two ...

Zenodo2024

Scalable constrained optimization

Maria-Luiza Vladarean

Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...

EPFL2024

Deterministic equivalent and error universality of deep random features learning

Hugo Chao Cui

This manuscript considers the problem of learning a random Gaussian network function using a fully connected network with frozen intermediate layers and trainable readout layer. This problem can be seen as a natural generalization of the widely studied ran ...

2024

Characterization of low-temperature plasmas generated by dielectric barrier discharges for bacterial inactivation

Lorenzo Ibba

Low-temperature plasmas (LTPs) at atmospheric pressure hold great promise for disinfection and sterilization applications. When compared to traditional sterilization technologies like autoclaving, LTPs may offer several benefits, including reduced energy c ...

EPFL2024

Robot Learning using Tensor Networks

Suhan Narayana Shetty

In various robotics applications, the selection of function approximation methods greatly influences the feasibility and computational efficiency of algorithms. Tensor Networks (TNs), also referred to as tensor decomposition techniques, present a versatile ...

EPFL2024

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Philippe Schwaller, Jeff Guo

Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

Amer Chemical Soc2024

Multi-Agent Learning in Contextual Games under Unknown Constraints

Maryam Kamgarpour, Anna Maria Maddux

We consider the problem of learning to play a repeated contextual game with unknown reward and unknown constraints functions. Such games arise in applications where each agent’s action needs to belong to a feasible set, but the feasible set is a priori unk ...

2024

System for predicting a prognosis of the neuropsychological and/or neuropsychiatric status in a subject

Olaf Blanke, Fosco Bernasconi

The present invention relates to systems and methods for predicting a prognosis of the neuropsychological and/or neuropsychiatric status in a subject based on reports of Minor Hallucination (MH) events in combination with electrophysiological data of the s ...

2024

Wind farm power density optimization according to the area size using a novel self-adaptive genetic algorithm

Fernando Porté Agel, Nicolas Otto Kirchner Bossi

This work studies the power density (PD) optimization in wind farms, and its sensitivity to the available area size. A novel genetic algorithm (PDGA) is introduced, which optimizes PD and the turbine layout, by self-adapting to the PD and to the solutions ...

Pergamon-Elsevier Science Ltd2023

Contemporary Logic Synthesis: with an Application to AQFP Circuit Optimization

Siang-Yun Lee

Electronic devices play an irreplaceable role in our lives. With the tightening time to market, exploding demand for computing power, and continuous desire for smaller, faster, less energy-consuming, and lower-cost chips, computer-aided design for electron ...

EPFL2024

Beam homogeneity of caesium seeded SPIDER using a direct beamlet current measurement

Basile Marie Jacques Pouradier Duteil

The ITER Heating Neutral Beam (HNB) source prototype SPIDER (Source for the Production of Ions of Deuterium Extracted from a Radio frequency plasma), hosted at the Neutral Beam Test Facility (NBTF) in Padova, Italy, has recently started operating with evap ...

ELSEVIER SCIENCE SA2023

Optimization of elastic wave propagation in a reconfigurable medium by genetic algorithms with adaptive mutation probability

Romain Christophe Rémy Fleury, Janez Rus

We introduce a reconfigurable medium for the manipulation of elastic propagation properties of Lamb waves. It is based on a shape memory polymer (SMP) with temperature-dependent Young's modulus. Waves are excited by a laser pulse and detected by a laser vi ...

IOP Publishing Ltd2023

A Comparative Analysis of Empirical Copula and Quantile Regression Methods for Probabilistic Load Forecasting

Mario Paolone, Francesco Gerini, Pål Forr Austnes

This paper presents a detailed comparative analysis of two data-driven probabilistic forecasting methods - a density-based Empirical Copula (EC) and a non-parametric Quantile Regression (QR) - in the context of load forecasting for day-ahead market applica ...

IEEE2024