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Concept

Parametric equation

Related publications (26)

Code for project entitled "study on conformal antennas, proof of concept prototype for a UAV"

Anja Skrivervik, Yuanyan Su

This code is used for developing the project entitled “Study on conformal antennas, proof of concept prototype for a UAV”, from the aspects of theory, design, and implementation. This code aims to speed up the investigation of an arbitrary phased array ant ...

Zenodo2024

Robust numerical integration on curved polyhedra based on folded decompositions

Annalisa Buffa, Pablo Antolin Sanchez, Xiaodong Wei

We present a novel method to perform numerical integration over curved polyhedra enclosed by high-order parametric surfaces. Such a polyhedron is first decomposed into a set of triangular and/or rectangular pyramids, whose certain faces correspond to the g ...

ELSEVIER SCIENCE SA2022

Alpha-NML Universal Predictors

Michael Christoph Gastpar, Marco Bondaschi

Inspired by Sibson’s alpha-mutual information, we introduce a new parametric class of universal predictors. This class interpolates two well-known predictors, the mixture estimator, that includes the Laplace and the Krichevsky-Trofimov predictors, and the ...

2022

Design and evaluation of digital tools to expand experience in vocational education

Kevin Gonyop Kim

Vocational education and training (VET) is the most popular form of upper-secondary education in Switzerland, with more than two-thirds of the teenagers enrolling in a VET program after finishing their compulsory education. The vast majority of the Swiss V ...

EPFL2022

Parametric Estimation For Functional Autoregressive Processes On The Sphere

Alessia Caponera

The aim of this paper is to define a nonlinear least squares estimator for the spectral parameters of a spherical autoregressive process of order 1 in a parametric setting. Furthermore, we investigate on its asymptotic properties, such as weak consistency ...

2022

Reduced order modelling of nonaffine problems on parameterized NURBS multipatch geometries

Annalisa Buffa, Pablo Antolin Sanchez, Margarita Chasapi

This contribution explores the combined capabilities of reduced basis methods and IsoGeometric Analysis (IGA) in the context of parameterized partial differential equations. The introduction of IGA enables a unified simulation framework based on a single g ...

2022

Synthesis and Analysis of 3D shapes with Geometric Deep Learning in Computer-Aided Engineering

Edoardo Remelli

In this thesis, we advocate that Computer-Aided Engineering could benefit from a Geometric Deep Learning revolution, similarly to the way that Deep Learning revolutionized Computer Vision. To do so, we consider a variety of Computer-Aided Engineering pr ...

EPFL2022

Model order reduction based on functional rational approximants for parametric PDEs with meromorphic structure

Davide Pradovera

Many engineering fields rely on frequency-domain dynamical systems for the mathematical modeling of physical (electrical/mechanical/etc.) structures. With the growing need for more accurate and reliable results, the computational burden incurred by frequen ...

EPFL2021

In vivo macromolecule signals in rat brain 1 H‐MR spectra at 9.4T: Parametrization, spline baseline estimation, and T 2 relaxation times

Cristina Ramona Cudalbu Moldovan, Lijing Xin, Bernard Lanz, Dunja Simicic, Veronika Rackayová

Purpose Reliable detection and fitting of macromolecules (MM) are crucial for accurate quantification of brain short-echo time (TE) 1H-MR spectra. An experimentally acquired single MM spectrum is commonly used. Higher spectral resolution at ultra-high fiel ...

Wiley2021

Shape Reconstruction by Learning Differentiable Surface Representations

Pascal Fua, Mathieu Salzmann, Shaifali Parashar, Jan Bednarík, Erhan Gündogdu

Generative models that produce point clouds have emerged as a powerful tool to represent 3D surfaces, and the best current ones rely on learning an ensemble of parametric representations. Unfortunately, they offer no control over the deformations of the su ...

IEEE2020

Model-informed machine learning for multi-component T2 relaxometry

Jean-Philippe Thiran, Tobias Kober, Meritxell Bach Cuadra, Tom Hilbert, Erick Jorge Canales Rodriguez, Cristina Granziera, Muhamed Barakovic, Marco Pizzolato, Elda Fischi Gomez, Thomas Yu, Gian Franco Piredda

Recovering the distribution from multi-echo magnetic resonance (MR) signals is challenging but has high potential as it provides biomarkers characterizing the tissue micro-structure, such as the myelin water fraction (MWF). In this work, we propose to comb ...

2020

A Low-Parametric Rhombic Microstructure Family for Irregular Lattices

Francis Julian Panetta

New fabrication technologies have significantly decreased the cost of fabrication of shapes with highly complex geometric structure. One important application of complex fine-scale geometric structures is to create variable effective elastic material prope ...

2020

The bias of dark matter tracers: assessing the accuracy of mapping techniques

Cheng Zhao

We present a comparison between approximated methods for the construction of mock catalogues based on the halo-bias mapping technique. To this end, we use as reference a high-resolution N-body simulation of 38403 dark matter particles on a 400 h(-1) Mpc cu ...

OXFORD UNIV PRESS2020

Rigid foldability and mountain-valley crease assignments of square-twist origami pattern

Huijuan Feng

Rigid foldability allows an origami pattern to fold about crease lines without twisting or stretching component panels. It enables folding of rigid materials, facilitating the design of foldable structures. Recent study shows that rigid foldability is affe ...

PERGAMON-ELSEVIER SCIENCE LTD2020

A Dirichlet process mixture model of discrete choice: Comparisons and a case study on preferences for shared automated vehicles

Rico Krüger

This paper i) compares parametric and semi-parametric representations of unobserved heterogeneity in hierarchical Bayesian logit models and ii) applies these methods to infer distributions of willingness to pay for features of shared automated vehicle (SAV ...

2020

Volumetric untrimming: Precise decomposition of trimmed trivariates into tensor products

Pablo Antolin Sanchez

3D objects, modeled using Computer Aided Geometric Design (CAGD) tools, are traditionally represented using a boundary representation (B-rep), and typically use spline functions to parameterize these boundary surfaces. However, recent development in physic ...

2019

Shape Projectors for Landmark-Based Spline Curves

Michaël Unser, Daniel Andreas Schmitter

We present a generic method to construct orthogonal projectors for two-dimensional landmark-based parametric spline curves. We construct vector spaces that define a geometric transformation (e.g., affine, similarity, and scaling) that is applied to a refer ...

IEEE Institute of Electrical and Electronics Engineers2017

An efficient method for fiber bridging traction identification based on the R-curve: Formulation and experimental validation

John Botsis, Joël Cugnoni, Thomas Gmür, Guillaume Frossard

Fiber bridging is one of the main toughening mechanisms in mode I interlaminar and intralaminar fracture of laminated composites. Intact fibers exert closing forces on both faces of the crack, restraining crack propagation. An effective identification proc ...

Elsevier2017

Reconstruction of 3D scattered data via radial basis functions by efficient and robust techniques

Alberto Crivellaro

We propose new algorithms to overcome two of the most constraining limitations of surface reconstruction methods in use. In particular, we focus on the large amount of data characterizing standard acquisitions by scanner and the noise intrinsically introdu ...

Elsevier Science Bv2017

Stress intensity factors for axial semi-elliptical surface cracks and embedded elliptical cracks at longitudinal butt welded joints of steel-lined pressure tunnels and shafts considering weld shape

Anton Schleiss, Pedro Filipe De Almeida Manso, Alexandre Jean Pachoud

When for steel liners of pressure tunnels and shafts high-strength steels are used, welded joints are subject to the risk of hydrogen induced cold-cracking in the base material. Longitudinal butt welded joints are critical regions as they are loaded transv ...

Elsevier2017