Publications associées à Accelerating the convergence to a limit cycle in 3D cardiac electromechanical simulations through a data-driven 0D emulator

Publications associées (21)

Search for ηc (2S) → p(p)over-bar and branching fraction measurements of χcJ → p(p)over-bar via ψ(2S) radiative decays

Using (27.12 +/- 0.14) x 10(8) psi(2S) events collected by the BESIII detector operating at BEPCII, we search for the decay eta(c) (2S) -> p (p) over bar via the process psi(2S) -> gamma eta(c)(2S) and only find a signal with a significance of 1.7 sigma. T ...

AMER PHYSICAL SOC2025

Analytical and EZmock covariance validation for the DESI 2024 results

Jiaxi Yu, Daniel Felipe Forero Sanchez

The estimation of uncertainties in cosmological parameters is an important challenge in Large-Scale-Structure (LSS) analyses. For standard analyses such as Baryon Acoustic Oscillations (BAO) and Full-Shape two approaches are usually considered. First: anal ...

2025

CORTEX experiments, Part III: Experimental determination of the zero power transfer function of AKR-2 with reliable uncertainties

Vincent Pierre Lamirand

The transfer function is an important characteristic quantity of a nuclear reactor, since it contains the kinetic parameters. It expresses the response of a nuclear reactor to a disturbance of a certain frequency. If it is determined experimentally, it can ...

2024

Multi-Annual Year-on-Year: Minimising the Uncertainty in Photovoltaic System Performance Loss Rates

Christophe Ballif, Hugo James André Quest

The performance loss rate (PLR) is a key parameter in the assessment of photovoltaic (PV) systems' long-term performance and reliability. Despite the lack of industry-wide consensus and standardised methods for extracting PLR values from field data, the ye ...

2024

A stable loosely-coupled scheme for cardiac electro-fluid-structure interaction

Alfio Quarteroni

We present a loosely coupled scheme for the numerical simulation of the cardiac electrofluid-structure interaction problem, whose solution is typically computationally intensive due to the need to suitably treat the coupling of the different submodels. Our ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

The JPEG AI Standard: Providing Efficient Human and Machine Visual Data Consumption

Touradj Ebrahimi

The Joint Photographic Experts Group (JPEG) AI learning-based image coding system is an ongoing joint standardization effort between International Organization for Standardization (ISO), International Electrotechnical Commission (IEC), and International Te ...

IEEE COMPUTER SOC2023

Distribution Inference Risks: Identifying and Mitigating Sources of Leakage

Robert West, Maxime Jean Julien Peyrard, Valentin Hartmann

A large body of work shows that machine learning (ML) models can leak sensitive or confidential information about their training data. Recently, leakage due to distribution inference (or property inference) attacks is gaining attention. In this attack, the ...

IEEE COMPUTER SOC2023

Human-machine interface for two-dimensional steering control with the auricular muscles

Daniel Jose Lins Leal Pinheiro, Silvestro Micera, Solaiman Shokur

Human-machine interfaces (HMIs) can be used to decode a user's motor intention to control an external device. People that suffer from motor disabilities, such as spinal cord injury, can benefit from the uses of these interfaces. While many solutions can be ...

FRONTIERS MEDIA SA2023

Reducing Aerosol Forcing Uncertainty by Combining Models With Satellite and Within-The-Atmosphere Observations: A Three-Way Street

Athanasios Nenes

Aerosol forcing uncertainty represents the largest climate forcing uncertainty overall. Its magnitude has remained virtually undiminished over the past 20 years despite considerable advances in understanding most of the key contributing elements. Recent wo ...

AMER GEOPHYSICAL UNION2023

Singular quadratic eigenvalue problems: linearization and weak condition numbers

Ivana Sain Glibic, Daniel Kressner

The numerical solution of singular eigenvalue problems is complicated by the fact that small perturbations of the coefficients may have an arbitrarily bad effect on eigenvalue accuracy. However, it has been known for a long time that such perturbations are ...

SPRINGER2023

Directionality-Aware Design of Embroidery Patterns

Zhenyuan Liu

Embroidery is a long-standing and high-quality approach to making logos and images on textiles. Nowadays, it can also be performed via automated machines that weave threads with high spatial accuracy. A characteristic feature of the appearance of the threa ...

2023

A squeezed mechanical oscillator with millisecond quantum decoherence

Tobias Kippenberg, Amir Youssefi, Mahdi Chegnizadeh, Shingo Kono

An enduring challenge in constructing mechanical-oscillator-based hybrid quantum systems is to ensure engineered coupling to an auxiliary degree of freedom and maintain good mechanical isolation from the environment, that is, low quantum decoherence, consi ...

NATURE PORTFOLIO2023

tweedledum: A Compiler Companion for Quantum Computing

Giovanni De Micheli, Bruno Schmitt Antunes

This work presents tweedledum-an extensible open-source library aiming at narrowing the gap between high-level algorithms and physical devices by enhancing the expressive power of existing frameworks. For example, it allows designers to insert classical lo ...

IEEE2022

High-order accurate entropy stable adaptive moving mesh finite difference schemes for special relativistic (magneto)hydrodynamics

Junming Duan

This paper develops high-order accurate entropy stable (ES) adaptive moving mesh finite difference schemes for the two- and three-dimensional special relativistic hydrodynamic (RHD) and magnetohydrodynamic (RMHD) equations, which is the high-order accurate ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2022

FLEET: Online Federated Learning via Staleness Awareness and Performance Prediction

Rachid Guerraoui, Anne-Marie Kermarrec, Rhicheek Patra

Federated learning (FL) is very appealing for its privacy benefits: essentially, a global model is trained with updates computed on mobile devices while keeping the data of users local. Standard FL infrastructures are however designed to have no energy or ...

ASSOC COMPUTING MACHINERY2022

A chance-constraint approach for optimizing Social Engagement-based services

Michel Bierlaire

Social Engagement is a novel business model transforming final users of a service from passive into active components. In this framework, people are contacted by a company and they are asked to perform tasks in exchange for a reward. This arises the compli ...

IEEE2022

A Modular Workflow for Model Building, Analysis, and Parameter Estimation in Systems Biology and Neuroscience

Daniel Keller

Neuroscience incorporates knowledge from a range of scales, from single molecules to brain wide neural networks. Modeling is a valuable tool in understanding processes at a single scale or the interactions between two adjacent scales and researchers use a ...

HUMANA PRESS INC2022

Sparse-RS: A Versatile Framework for Query-Efficient Sparse Black-Box Adversarial Attacks

Nicolas Henri Bernard Flammarion, Maksym Andriushchenko, Francesco Croce

We propose a versatile framework based on random search, Sparse-RS, for score-based sparse targeted and untargeted attacks in the black-box setting. Sparse-RS does not rely on substitute models and achieves state-of-the-art success rate and query efficienc ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2022

U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture Search

Pascal Frossard, Ahmet Caner Yüzügüler, Nikolaos Dimitriadis

Optimizing resource utilization in target platforms is key to achieving high performance during DNN inference. While optimizations have been proposed for inference latency, memory footprint, and energy consumption, prior hardware-aware neural architecture ...

SPRINGER INTERNATIONAL PUBLISHING AG2022

On the transition times in a loss model of wireless networks

Patrick Thiran

SPRINGER2022