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SPar-K: a method to partition NGS signal data

Publications associées (27)

Method for Design Materialization (MDM) for artists, educators and archivists: an introduction

This contribution argues for the potential of Barr, Khaled and Lessard’s Method for Design Materialization (MDM) as a research through design tool that is specifically suited for new media preservation. Building moreover from the ISEA first and second Summ ...

2023

Reinforcement bond performance in 3D concrete printing: Explainable ensemble learning augmented by deep generative adversarial networks

Xianlin Wang

Integrating various reinforcements into 3D concrete printing (3DCP) is an efficient method to satisfy critical requirements for structural applications. This paper explores an explainable ensemble machine learning (EML) method to predict the bond failure m ...

Elsevier2023

Efficient approximation of cardiac mechanics through reduced-order modeling with deep learning-based operator approximation

Alfio Quarteroni, Andrea Manzoni

Reducing the computational time required by high-fidelity, full-order models (FOMs) for the solution of problems in cardiac mechanics is crucial to allow the translation of patient-specific simulations into clinical practice. Indeed, while FOMs, such as th ...

Wiley2023

Measuring electro-adhesion pressure before and after contact

Herbert Shea, Sylvain Thomas Schaller

Electro-adhesion (EA) is a low-power, tunable, fast and reversible electrically-controlled adhesion method, effective on both conducting and insulating objects. Typically, only the electro-adhesive detachment force, i.e., the force required to separate an ...

Nature Portfolio2023

Training Efficient Controllers via Analytic Policy Gradient

Dario Floreano, Davide Scaramuzza, Valentin Wüest

Control design for robotic systems is complex and often requires solving an optimization to follow a trajectory accurately. Online optimization approaches like Model Predictive Control (MPC) have been shown to achieve great tracking performance, but requir ...

New York2023

Nanoindentation of embedded particles

Andreas Mortensen, Alejandra Inés Slagter, Joris Pierre Everaerts

We address the effect of elastic inhomogeneity on elastic modulus and hardness determinations made by depth-sensing indentations performed on individual particles embedded within a matrix of different elastic modulus. Finite element simulations and nanoind ...

SPRINGER HEIDELBERG2023

Computational conceptual design — typological exploration of spatial truss systems through optimization

Corentin Jean Dominique Fivet, Jonas Warmuth, Pierluigi D'Acunto

Exploring a wide range of design options is crucial for every sound conceptual design process. In the conventional structural design workflow, optimization techniques are generally employed to generate well-performing design options. However, focusing only ...

International Association for Shell and Spatial Structures (IASS)2023