Publications related to Classes of stochastically switched (blinking) systems

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

Alfio Quarteroni, Francesco Regazzoni, Stefano Pagani

Predicting the evolution of systems with spatio-temporal dynamics in response to external stimuli is essential for scientific progress. Traditional equations-based approaches leverage first principles through the numerical approximation of differential equ ...

Nature Portfolio2024

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

Stability: a search for structure

Wouter Jongeneel

In this thesis we study stability from several viewpoints. After covering the practical importance, the rich history and the ever-growing list of manifestations of stability, we study the following. (i) (Statistical identification of stable dynamical syste ...

EPFL2024

A Method of Moments Estimator for Interacting Particle Systems and their Mean Field Limit

Andrea Zanoni, Grigorios A. Pavliotis

We study the problem of learning unknown parameters in stochastic interacting particle systems with polynomial drift, interaction, and diffusion functions from the path of one single particle in the system. Our estimator is obtained by solving a linear sys ...

Siam Publications2024

The Strong Integral Input-to-State Stability Property in Dynamical Flow Networks

Nils Gustav Nilsson

Dynamical flow networks serve as macroscopic models for, e.g., transportation networks, queuing networks, and distribution networks. While the flow dynamics in such networks follow the conservation of mass on the links, the outflow from each link is often ...

Ieee-Inst Electrical Electronics Engineers Inc2024

The dynamics of unsteady frictional slip pulses

Fabian Barras, Thibault Didier Roch

Self-healing slip pulses are major spatiotemporal failure modes of frictional systems, featuring a characteristic size L(t) and a propagation velocity c(p)(t) (t is time). Here, we develop a theory of slip pulses in realistic rate- and state-dependent fric ...

National Academy of Sciences2023

Higher-order organization of multivariate time series

Enrico Amico, Andrea Santoro

Time series analysis has proven to be a powerful method to characterize several phenomena in biology, neuroscience and economics, and to understand some of their underlying dynamical features. Several methods have been proposed for the analysis of multivar ...

NATURE PORTFOLIO2023

Tumescense monitoring system for diagnosing erectile dysfunction and methods of use

Nikolaos Stergiopoulos, Rodrigo Araujo Fraga Da Silva

Systems and methods for monitoring penile tumescence are provided that overcome the drawbacks of previously known systems by providing a wearable formed of a flexible and elastic tube having a plurality of sensors disposed on or embedded within it, the wea ...

2023

How Words Move Hearts: Interpretable Machine Learning Models of Bias, Engagement, and Influence in Socio-Political Systems

Aswin Suresh

We study socio-political systems in representative democracies. Motivated by problems that affect the proper functioning of the system, we build computational methods to answer research questions regarding the phenomena occurring in them. For each phenomen ...

EPFL2023

Dynamic Linkers Are the Narrow Waist of Operating Systems

Adrien Ghosn, Charly Nicolas Lucien Castes

While software applications, programming languages, and hardware have changed, operating systems have not. Widely-used commodity operating systems are still modeled after the ones designed in the seventies. The accumulated burden of backward compatibility ...

Association for Computing Machinery2023

Learning Physics-Consistent Particle Interactions

David Simon Kammer, Zhichao Han, Olga Fink

Interacting particle systems play a key role in science and engineering. Access to the governing particle interaction law is fundamental for a complete understanding of such systems. However, the inherent system complexity keeps the particle interaction hi ...

Oxford University Press2023

Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems

Colin Neil Jones, Melanie Nicole Zeilinger, Xuan Truong Nghiem, Roland Schwan

Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathematical models developed in scientific and engineering domains. As opposed to ...

IEEE2023

The Case for Performance Interfaces for Hardware Accelerators

George Candea, Aikaterini Argyraki, Rishabh Ramesh Iyer, Jiacheng Ma

While systems designers are increasingly turning to hardware accelerators for performance gains, realizing these gains is painstaking and error-prone. It can take several person-months to determine if a given accelerator is a good fit for a given piece of ...

2023

Remote wide angle view broad wavelength viewing system compatible with D-T operations in JET

Gilles Arnoux, Paulo Giovane Paschoali Pereira Puglia

Imaging diagnostics in Joint European Torus have become essential in the study of plasma wall interactions and the protection of the plasma facing components. During deuterium operations, the location of these diagnostics was at close proximity to the vess ...

2023

Invariant tori in dissipative hyperchaos

Tobias Schneider, Jeremy Peter Parker

One approach to understand the chaotic dynamics of nonlinear dissipative systems is the study of non-chaotic yet dynamically unstable invariant solutions embedded in the system's chaotic attractor. The significance of zero-dimensional unstable fixed points ...

American Institute of Physics2022

Linearization and Identification of Multiple-Attractor Dynamical Systems through Laplacian Eigenmaps

Aude Billard, Bernardo Fichera

Dynamical Systems (DS) are fundamental to the modeling and understanding time evolving phenomena, and have application in physics, biology and control. As determining an analytical description of the dynamics is often difficult, data-driven approaches are ...

Microtome Publishing2022

Spatial Series and Fractal Analysis Associated with Fracture Behaviour of UO2 Ceramic Material

Maria-Alexandra Paun

SEM micrographs of the fracture surface for UO2 ceramic materials have been analysed. In this paper, we introduce some algorithms and develop a computer application based on the time-series method. Utilizing the embedding technique of phase space, the attr ...

MDPI2022

Constructing periodic orbits of high-dimensional chaotic systems by an adjoint-based variational method

Tobias Schneider, Sajjad Azimi, Omid Ashtari

Chaotic dynamics in systems ranging from low-dimensional nonlinear differential equations to high-dimensional spatiotemporal systems including fluid turbulence is supported by nonchaotic, exactly recurring time-periodic solutions of the governing equations ...

2022

Code Generation Approach Supporting Complex System Modeling based on Graph Pattern Matching

Dimitrios Kyritsis, Yan Yan, Jinzhi Lu

Code generation is an effective way to drive the complex system development in model-based systems engineering. Currently, different code generators are developed for different modeling languages to deal with the development of systems with multi-domain. T ...

ELSEVIER2022

Bibliometric Analysis of Model-Based Systems Engineering: Past, Current, and Future

Dimitrios Kyritsis, Yan Yan, Jinzhi Lu

Model-based systems engineering (MBSE) is considered an important approach for understanding multidomain fields and is widely used in complex systems such as aerospace. In this article, a detailed survey of MBSE literature was conducted from its commenceme ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022