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arXiv 2024年

作者： Santiago, Paulo Roberto Pereira Chinaglia, Abel Gonçalves Flanagan, Kira Bedo, Bruno L.S. Mochida, Ligia Yumi Aceros, Juan Bononi, Aline Cesar, Guilherme Manna Biomechanics and Motor Control Laboratory School of Physical Education and Sport USP Brazil Graduate Program in Rehabilitation and Functional Performance Medical School USP Brazil Technology and Sports Performance Analysis Laboratory School of Physical Education USP Brazil Laboratory of Applied Biomechanics and Engineering Brooks College of Health UNF United States Department of Physical Therapy Brooks College of Health UNF United States College of Computing Engineering and Construction UNF United States Municipal Pharmacy Ribeirão Preto Brazil

Human movement analysis is crucial in health and sports biomechanics for understanding physical performance, guiding rehabilitation, and preventing injuries. However, existing tools are often proprietary, expensive, and function as "black boxes", limiting user control and customization. This paper introduces vailá—Versatile Anarcho Integrated Liberation Ánalysis in Multimodal Toolbox—an open-source, Python-based platform designed to enhance human movement analysis by integrating data from multiple biomechanical systems. vailá supports data from diverse sources, including retroreflective motion capture systems, inertial measurement units (IMUs), markerless video capture technology, electromyography (EMG), force plates, and GPS/GNSS systems, enabling comprehensive analysis of movement patterns. Developed entirely in Python 3.11.9, which offers improved efficiency and long-term support, and featuring a straightforward installation process, vailá is accessible to users without extensive programming experience. In this paper, we also present several workflow examples that demonstrate how vailá allows the rapid processing of large batches of data, independent of the type of collection method. This flexibility is especially valuable in research scenarios where unexpected data collection challenges arise, ensuring no valuable data point is lost. We demonstrate the application of vailá in analyzing sit-to-stand movements in pediatric disability, showcasing its capability to provide deeper insights even with unexpected movement patterns. By fostering a collaborative and open environment, vailá encourages users to innovate, customize, and freely explore their analysis needs, potentially contributing to the advancement of rehabilitation strategies and performance optimization. For more details in GitHub repository: https://***/vaila-multimodaltoolbox/vaila and the online documentation: https://*** Codes 92C10, 68U10, 65D18, 65K10 © 2024, CC BY-SA.

关键词： Electromyography

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Non-Hermitian lattice fermions in the 2D Gross-Neveu-Yukawa model

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Physical Review D 2024年第3期110卷 034502-034502页

作者： Xingyu Guo Chen-Te Ma Hui Zhang Key Laboratory of Atomic and Subatomic Structure and Quantum Control (MOE) Guangdong Basic Research Center of Excellence for Structure and Fundamental Interactions of Matter Institute of Quantum Matter South China Normal University Department of Physics and Astronomy Iowa State University Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University Asia Pacific Center for Theoretical Physics Pohang University of Science and Technology School of Physics and Telecommunication Engineering South China Normal University The Laboratory for Quantum Gravity and Strings Department of Mathematics and Applied Mathematics University of Cape Town Physics Department Center for Exploration of Energy and Matter Indiana University

We work the lattice fermions and non-Hermitian formulation in the 2D Gross-Neveu-Yukawa (GNY) model and demonstrate the numerical implementation for two flavors by the hybrid Monte Carlo. Our approach has a notable advantage in dealing with chiral symmetry on a lattice by avoiding the Nielsen-Ninomiya theorem, due to the nonsymmetrized finite-difference operator. We restore the hypercubic symmetry by averaging over all possible orientations with the proper continuum limit. Our study is the first simulation for the interacting fermion formulated in a non-Hermitian way. We compare the numerical solution with the one-loop resummation. The resummation results matches with the numerical solution in ⟨ϕ⟩, ⟨ϕ2⟩, ⟨Tr(ψ¯1ψ1+ψ¯2ψ2)/2⟩, and ⟨Tr(ψ¯1ψ1+ψ¯2ψ2)ϕ/2⟩. We also used the one-loop resummation to provide the renormalization group flow and asymptotic safety in the 2D GNY model.

关键词： Nonperturbative effects in field theory Perturbation theory Chiral symmetry Hybrid Monte Carlo algorithm Lattice field theory

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Machine learning framework for computing the most probable paths of stochastic dynamical systems

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Physical Review E 2021年第1期103卷 012124-012124页

作者： Yang Li Jinqiao Duan Xianbin Liu State Key Laboratory of Mechanics and Control of Mechanical Structures College of Aerospace Engineering Nanjing University of Aeronautics and Astronautics 29 Yudao Street Nanjing 210016 China Department of Applied Mathematics College of Computing Illinois Institute of Technology Chicago Illinois 60616 USA

The emergence of transition phenomena between metastable states induced by noise plays a fundamental role in a broad range of nonlinear systems. The computation of the most probable paths is a key issue to understanding the mechanism of transition behaviors. The shooting method is a common technique for this purpose to solve the Euler-Lagrange equation for the associated action functional, while losing its efficacy in high-dimensional systems. In the present work, we develop a machine learning framework to compute the most probable paths in the sense of Onsager-Machlup action functional theory. Specifically, we reformulate the boundary value problem of a Hamiltonian system and design a neural network to remedy the shortcomings of the shooting method. The successful applications of our algorithms to several prototypical examples demonstrate its efficacy and accuracy for stochastic systems with both (Gaussian) Brownian noise and (non-Gaussian) Lévy noise. This approach is effective in exploring the internal mechanisms of rare events triggered by random fluctuations in various scientific fields.

关键词： Diffusion Fluctuations & noise Neuronal networks

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ADER Methods for Hyperbolic Equations with a Time-Reconstruction Solver for the Generalized Riemann Problem: the Scalar Case

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Communications on applied Mathematics and Computation 2020年第3期2卷 369-402页

作者： R.Demattè V.A.Titarev G.I.Montecinos E.F.Toro Department of Aerospace Science and Technology Politecnico di MilanoMilanItaly Dorodnicyn Computing Center Federal Research Center Computer Science and ControlRussianAcademy of SciencesMoscowRussia Departamento de Ciencias Naturales y Tecnología Universidad de AysénCoyhaiqueChile Laboratory of Applied Mathematics DICAMUniversity of TrentoTrentoItaly

The ADER approach to solve hyperbolic equations to very high order of accuracy has seen explosive developments in the last few years,including both methodological aspects as well as very ambitious *** spite of methodological progress,the issues of efficiency and ease of implementation of the solution of the associated generalized Riemann problem(GRP)remain the centre of attention in the ADER *** the original formulation of ADER schemes,the proposed solution procedure for the GRP was based on(i)Taylor series expansion of the solution in time right at the element interface,(ii)subsequent application of the Cauchy-Kowalewskaya procedure to convert time derivatives to functionals of space derivatives,and(iii)solution of classical Riemann problems for high-order spatial derivatives to complete the Taylor series *** realistic problems the Cauchy-Kowalewskaya procedure requires the use of symbolic manipulators and being rather cumbersome its replacement or simplification is highly *** this paper we propose a new class of solvers for the GRP that avoid the Cauchy-Kowalewskaya procedure and result in simpler ADER *** is achieved by exploiting the history of the numerical solution that makes it possible to devise a time-reconstruction procedure at the element *** relying on a time Taylor series expansion of the solution at the interface,the time derivatives are then easily calculated from the time-reconstruction *** resulting schemes are called ADER-TR.A thorough study of the linear stability properties of the linear version of the schemes is carried out using the von Neumann method,thus deducing linear stability ***,via careful numerical experiments,we deduce stability regions for the corresponding non-linear *** examples using the present simplified schemes of fifth and seventh order of accuracy in space and time show that these compare favourably with conventional ADER ***

关键词： Hyperbolic equations Finite volume ADER methods Generalized Riemann problem(GRP) Time-reconstruction(TR)

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Stochastic Virtual Battery Modeling of Uncertain Electrical Loads Using Variational Autoencoder

Stochastic Virtual Battery Modeling of Uncertain Electrical ...

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American control Conference

作者： Indrasis Chakraborty Sai Pushpak Nandanoori Soumya Kundu Karanjit Kalsi Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore CA USA Optimization and Control Group Pacific Northwest National Laboratory Richland WA USA

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

Effective utilization of flexible loads for grid services, while satisfying end-user preferences and constraints, requires an accurate estimation of the aggregated predictive flexibility offered by the electrical loads. Virtual battery (VB) models are often used to quantify the predictive flexibility in thermostatic loads (e.g. residential air-conditioners, electric water-heaters), which model the temporal evolution of a (virtual) energy state via a first order dynamics including self-dissipation rate, and power and energy capacities as parameters. Uncertainties and lack of information regarding end-usage and equipment models render deterministic VB models impractical. In this paper, we introduce the notion of stochastic VB models, and propose a variational autoencoder-based deep learning algorithm to identify the probability distribution of the VB model parameters. Using available sensors and meters data, the proposed algorithm generates not only point estimates of the VB parameters, but also confidence intervals around those values. Effectiveness of the proposed frameworks is demonstrated on a collection of electric water-heater loads, whose operation is driven by uncertain water usage profiles.

关键词： Load modeling Energy states Uncertainty Atmospheric modeling Predictive models Stochastic processes Batteries

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Rate-Splitting for Cell-Free Massive MIMO: Performance Analysis and Generative AI Approach

arXiv

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arXiv 2024年

作者： Zheng, Jiakang Zhang, Jiayi Du, Hongyang Zhang, Ruichen Niyato, Dusit Dobre, Octavia A. Ai, Bo The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China The Department of Electrical and Electronic Engineering University of Hong Kong Pok Fu Lam Hong Kong The College of Computing and Data Science Nanyang Technological University Singapore Faculty of Engineering and Applied Science Memorial University Canada The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-speed Railway System China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen China

Cell-free (CF) massive multiple-input multiple-output (MIMO) provides a ubiquitous coverage to user equipments (UEs) but it is also susceptible to interference. Rate-splitting (RS) effectively extracts data by decoding interference, yet its effectiveness is limited by the weakest UE. In this paper, we investigate an RS-based CF massive MIMO system, which combines strengths and mitigates weaknesses of both approaches. Considering imperfect channel state information (CSI) resulting from both pilot contamination and noise, we derive a closed-form expression for the sum spectral efficiency (SE) of the RS-based CF massive MIMO system under a spatially correlated Rician channel. Moreover, we propose low-complexity heuristic algorithms based on statistical CSI for power-splitting of common messages and power-control of private messages, and genetic algorithm is adopted as a solution for upper bound performance. Furthermore, we formulate a joint optimization problem, aiming to maximize the sum SE of the RS-based CF massive MIMO system by optimizing the power-splitting factor and power-control coefficient. Importantly, we improve a generative AI (GAI) algorithm to address this complex and non-convexity problem by using a diffusion model to obtain solutions. Simulation results demonstrate its effectiveness and practicality in mitigating interference, especially in dynamic environments. Copyright © 2024, The Authors. All rights reserved.

关键词： Genetic algorithms

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Quantum Entanglement Based on Two-Photon Joint Subtraction from Two-Mode Squeezed Vacuum States

Quantum Entanglement Based on Two-Photon Joint Subtraction f...

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OptoElectronics and Communications Conference, OECC

作者： Hongbin Song Heyu Huang Hao Liu Ai Zhou Guofeng Zhang Hidehiro Yonezawa The General Education Division and Guangdong Key Laboratory of Optoelectronic Materials and Chips and Shenzhen Key Lab of Semiconductor Lasers The Chinese University of Hong Kong Shenzhen Shenzhen China School of Materials Science and Engineering and National Engineering Research Center of Fiber Optic Sensing Technology and Networks Wuhan University of Technology Wuhan China National Engineering Research Center of Fiber Optic Sensing Technology and Networks Wuhan University of Technology Wuhan China Department of Applied Mathematics The Hong Kong Polytechnic University Hongkong China Optical Quantum Control Research Team RIKEN Center for Quantum Computing Saitama Japan

We present and analyze the quantum entanglement generated from two-photon joint subtraction from two-mode squeezed vacuum states (TMSV). Larger entanglement negativity than single-photon jointly subtracted TMSV, photo... 详细信息

ISBN: (数字)9798350308396

ISBN: (纸本)9798350308402

关键词： Protocols Correlation Quantum entanglement Simulation Elementary particle vacuum Quantum networks Photonics

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A Hybrid Adaptive Filter for Head Tracking in Augmented Reality (AR)-based Flight Simulators

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IEEE Transactions on Computers 2025年

作者： Nwobodo, Onyeka J. Kuaban, Godlove Suila Nkemeni, Valery Wereszczynski, Kamil Cyran, Krzysztof A. Silesian University of Technology Department of Computer Graphics Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Gliwice Poland Polish Academy of Sciences Institute of Theoretical and Applied Informatics Poland University of Buea Laboratory of Electrical Engineering and Computing Faculty of Engineering and Technology Buea Cameroon

This paper presents a novel approach for head tracking in augmented reality (AR) flight simulators using an adaptive fusion of Kalman and particle filters. This fusion dynamically balances the strengths of both algorithms, leveraging Kalman filters for computational efficiency and particle filters for handling non-linearities based on real-time factors such as sensor noise and head movement patterns. Our method demonstrates superior tracking precision and reduced latency, making it particularly effective for immersive pilot training in AR-based flight simulations. While focused on flight simulation, our approach holds high potential for broader applications in other AR and virtual reality (VR) environments where precise, real-time head tracking is crucial. These results provide actionable design guidance for developers optimizing tracking systems in environments that require fast response times and high accuracy. Future extensions of this research could explore the generalization of our approach across diverse AR applications, including human-computer interaction (HCI), medical simulations, and gaming. © 1968-2012 IEEE.

关键词： Flight simulators

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Stochastic virtual battery modeling of uncertain electrical loads using variational autoencoder

arXiv

引用

arXiv 2020年

作者： Chakraborty, Indrasis Nandanoori, Sai Pushpak Kundu, Soumya Kalsi, Karanjit Center for Applied Scientific Computing Lawrence Livermore National Laboratory LivermoreCA94550 United States Optimization and Control Group Pacific Northwest National Laboratory RichlandWA99352 United States

Effective utilization of flexible loads for grid services, while satisfying end-user preferences and constraints, requires an accurate estimation of the aggregated predictive flexibility offered by the electrical loads. Virtual battery (VB) models are often used to quantify the predictive flexibility in thermostatic loads (e.g. residential air-conditioners, electric water-heaters), which model the temporal evolution of a (virtual) energy state via a first order dynamics including selfdissipation rate, and power and energy capacities as parameters. Uncertainties and lack of information regarding endusage and equipment models render deterministic VB models impractical. In this paper, we introduce the notion of stochastic VB models, and propose a variational autoencoder-based deep learning algorithm to identify the probability distribution of the VB model parameters. Using available sensors and meters data, the proposed algorithm generates not only point estimates of the VB parameters, but also confidence intervals around those values. Effectiveness of the proposed frameworks is demonstrated on a collection of electric water-heater loads, whose operation is driven by uncertain water usage profiles. Copyright © 2020, The Authors. All rights reserved.

关键词： Stochastic models

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Point cloud-based registration and image fusion between cardiac SPECT MPI and CTA

arXiv

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arXiv 2024年

作者： Shaojie, Tang Penpen, Miao Xingyu, Gao Yu, Zhong Dantong, Zhu Haixing, Wen Zhihui, Xu Qiuyue, Wei Hongping, Yao Xin, Huang Rui, Gao Chen, Zhao Weihua, Zhou School of Automation Xi’an University of Posts and Telecommunications Shaanxi Xi’an710121 China Xi'an Key Laboratory of Advanced Control and Intelligent Process Shaanxi Xi’an710121 China Second Clinical Medical School of Nanjing Medical University Jiangsu Nanjing210011 China Department of Cardiology The First Affiliated Hospital of Nanjing Medical University Jiangsu Nanjing210000 China Department of Pharmacy The First Affiliated Hospital of Xi’an Jiaotong University Shaanxi Xi’an710061 China Department of Cardiology The First Affiliated Hospital of Xi’an Jiaotong University Shaanxi Xi’an710061 China Department of Nuclear Medicine The First Affiliated Hospital of Xi’an Jiaotong University Shaanxi Xi’an710061 China Department of Computer Science Kennesaw State University MariettaGA30060 United States Department of Applied Computing Center for Biocomputing and Digital Health Institute of Computing and Cybersystems Health Research Institute Michigan Technological University HoughtonMI49931 United States

A method was proposed for the point cloud-based registration and image fusion between cardiac single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) and cardiac computed tomography angiograms (CTA). Firstly, the left ventricle (LV) epicardial regions (LVERs) in SPECT and CTA images were segmented by using different U-Net neural networks trained to generate the point clouds of the LV epicardial contours (LVECs). Secondly, according to the characteristics of cardiac anatomy, the special points of anterior and posterior interventricular grooves (APIGs) were manually marked in both SPECT and CTA image volumes. Thirdly, we developed an in-house program for coarsely registering the special points of APIGs to ensure a correct cardiac orientation alignment between SPECT and CTA images. Fourthly, we employed ICP, SICP or CPD algorithm to achieve a fine registration for the point clouds (together with the special points of APIGs) of the LV epicardial surfaces (LVERs) in SPECT and CTA images. Finally, the image fusion between SPECT and CTA was realized after the fine registration. The experimental results showed that the cardiac orientation was aligned well and the mean distance error of the optimal registration method (CPD with affine transform) was consistently less than 3 mm. The proposed method could effectively fuse the structures from cardiac CTA and SPECT functional images, and demonstrated a potential in assisting in accurate diagnosis of cardiac diseases by combining complementary advantages of the two imaging modalities. © 2024, CC BY.

关键词： Image fusion

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