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Event detection is the first step in event-based non-intrusive load monitoring (NILM) and it can provide useful transient information to identify appliances. However, existing event detection methods with fixed parameters may fail in case…

Signal Processing · Electrical Eng. & Systems 2021-07-26 Lei Yan , Wei Tian , Jiayu Han , Zuyi Li

A chemical reaction mechanism (CRM) is a sequence of molecular-level events involving bond-breaking/forming processes, generating transient intermediates along the reaction pathway as reactants transform into products. Understanding such…

Chemical Physics · Physics 2024-07-16 Ajnabiul Hoque , Manajit Das , Mayank Baranwal , Raghavan B. Sunoj

Various kinetic Monte Carlo algorithms become inefficient when some of the population sizes in a system are large, which gives rise to a large number of reaction events per unit time. Here, we present a new acceleration algorithm based on…

Quantitative Methods · Quantitative Biology 2019-07-24 Yen Ting Lin , Song Feng , William S. Hlavacek

This text presents one of the first successful applications of a rare events method for the study of multistability in a turbulent flow without stochastic energy injection. The trajectories of collapse of turbulence in plane Couette flow,…

Fluid Dynamics · Physics 2021-11-29 Joran Rolland

Accelerator mass spectrometry (AMS) is a widely-used technique with multiple applications, including geology, molecular biology and archeology. In order to achieve a high dynamic range, AMS requires tandem accelerators and large magnets,…

Quantum Physics · Physics 2023-05-23 Radu Ionicioiu

Particle-based shape modeling (PSM) is a family of approaches that automatically quantifies shape variability across anatomical cohorts by positioning particles (pseudo landmarks) on shape surfaces in a consistent configuration. Recent…

Computer Vision and Pattern Recognition · Computer Science 2025-07-11 Hong Xu , Shireen Y. Elhabian

In this work we propose an adaptive multilevel version of subset simulation to estimate the probability of rare events for complex physical systems. Given a sequence of nested failure domains of increasing size, the rare event probability…

Numerical Analysis · Mathematics 2023-12-13 Daniel Elfverson , Robert Scheichl , Simon Weissmann , F. Alejandro DiazDelaO

In this paper, we study a sequential decision-making problem, called Adaptive Sampling for Discovery (ASD). Starting with a large unlabeled dataset, algorithms for ASD adaptively label the points with the goal to maximize the sum of…

Machine Learning · Statistics 2023-01-04 Ziping Xu , Eunjae Shim , Ambuj Tewari , Paul Zimmerman

Variational multiscale (VMS) methods offer a robust framework for handling under-resolved flow scales without resorting to problem-specific turbulence models. Here, we propose and assess a dynamic, term-by-term VMS stabilized formulation…

Fluid Dynamics · Physics 2026-02-06 Diego Escobar , Douglas Pacheco , Alejando Aguirre , Ernesto Castillo

The multi-robot adaptive sampling problem aims at finding trajectories for a team of robots to efficiently sample the phenomenon of interest within a given endurance budget of the robots. In this paper, we propose a robust and scalable…

Robotics · Computer Science 2023-03-02 Lishuo Pan , Sandeep Manjanna , M. Ani Hsieh

In this paper, a new fractional step method is proposed for simulating stiff and nonstiff chemically reacting flows. In stiff cases, a well-known spurious numerical phenomenon, i.e. the incorrect propagation speed of discontinuities, may be…

Computational Physics · Physics 2019-05-01 Jian-Hang Wang , Shucheng Pan , Xiangyu Y. Hu , Nikolaus A. Adams

The development of high-efficiency porous catalyst membranes critically depends on our understanding of where the majority of the chemical conversions occur within the porous structure. This requires mapping of chemical reactions and mass…

The goal of video anomaly detection is tantamount to performing spatio-temporal localization of abnormal events in the video. The multiscale temporal dependencies, visual-semantic heterogeneity, and the scarcity of labeled data exhibited by…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Dezhi An , Wenqiang Liu , Kefan Wang , Zening Chen , Jun Lu , Shengcai Zhang

Stochastic modeling of reaction networks is a framework used to describe the time evolution of many natural and artificial systems, including, biochemical reactive systems at the molecular level, viral kinetics, the spread of epidemic…

Numerical Analysis · Mathematics 2014-06-10 Alvaro Moraes , Raul Tempone , Pedro Vilanova

Annealed Sequential Monte Carlo (ASMC) samplers are special cases of SMC samplers where the sequence of distributions can be embedded in a smooth path of distributions. Using this underlying path and a performance model based on the…

Computation · Statistics 2025-12-03 Saifuddin Syed , Alexandre Bouchard-Côté , Kevin Chern , Arnaud Doucet

The ability to predict accurate thermodynamic and kinetic properties in biomolecular systems is of both scientific and practical utility. While both remain very difficult, predictions of kinetics are particularly difficult because rates, in…

Chemical Physics · Physics 2018-06-13 Yong Wang , Omar Valsson , Pratyush Tiwary , Michele Parrinello , Kresten Lindorff-Larsen

The development of computational models for the numerical simulation of chemically reacting flows operating in the turbulent regime requires the solution of partial differential equations that represent the balance of mass, linear momentum,…

Fluid Dynamics · Physics 2021-06-03 Americo Cunha , Luis Fernando Figueira da Silva

Transitional localised turbulence in shear flows is known to either decay to an absorbing laminar state or proliferate via splitting. The average passage times from one state to the other depend super-exponentially on the Reynolds number…

Fluid Dynamics · Physics 2022-05-12 S. Gomé , L. S. Tuckerman , D. Barkley

First-principles calculations are a cornerstone of modern surface science and heterogeneous catalysis. However, accurate reaction energies and barrier heights are frequently inaccessible due to the approximations demanded by the large…

Materials Science · Physics 2024-02-08 Hong-Zhou Ye , Timothy C. Berkelbach

The adaptive smoothing method (ASM) is a widely used approach for traffic state reconstruction. This article presents a Python implementation of ASM, featuring end-to-end calibration using real-world ground truth data. The calibration is…

Machine Learning · Computer Science 2026-02-03 Junyi Ji , Derek Gloudemans , Gergely Zachár , Matthew Nice , William Barbour , Daniel B. Work
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