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arXiv 2023年

作者： Fan, Alex Xiao, Xingshuo Washington, Peter Department of Statistics Stanford University StanfordCA United States Institute of Computational Math and Engineering Stanford University StanfordCA United States Information and Computer Science University of Hawai’i at Manoa HonoluluHI United States

Fairness in deep learning models trained with high-dimensional inputs and subjective labels remains a complex and understudied area. Facial emotion recognition, a domain where datasets are often racially imbalanced, can lead to models that yield disparate outcomes across racial groups. This study focuses on analyzing racial bias by sub-sampling training sets with varied racial distributions and assessing test performance across these simulations. Our findings indicate that smaller datasets with posed faces improve on both fairness and performance metrics as the simulations approach racial balance. Notably, the F1-score increases by 27.2% points, and demographic parity increases by 15.7% points on average across the simulations. However, in larger datasets with greater facial variation, fairness metrics generally remain constant, suggesting that racial balance by itself is insufficient to achieve parity in test performance across different racial groups. © 2023, CC BY.

关键词： Emotion Recognition

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HelioCubed: A High Order Inner Heliosphere Simulation Code with a Mapped Cubed Sphere Grid and Adaptive Mesh Refinement 16

HelioCubed: A High Order Inner Heliosphere Simulation Code w...

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16th International Conference on Numerical Modeling of Space Plasma Flows, ASTRONUM 2024

作者： Singh, Talwinder Colella, Phillip Van-Straalen, Brian Bozhart, Chris Pogorelov, Nikolai V. Department of Physics & Astronomy Georgia State University AtlantaGA30303 United States Applied Numerical Algorithms Group Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Electrical Engineering and Computer Science Department University of California Berkeley BerkeleyCA94720 United States Department of Space Science The University of Alabama in Huntsville HuntsvilleAL35805 United States Center for Space Plasma and Aeronomic Research The University of Alabama in Huntsville HuntsvilleAL35805 United States

We present the HelioCubed, a high-order magnetohydrodynamic (MHD) code designed for modeling the inner heliosphere. The code is designed to achieve 4th order accuracy both in space and in time. In addition, HelioCubed can perform simulations on mapped grids, such as those based on cubed spheres, which makes it possible to overcome stability limitations caused by the geometrical singularity at the polar axis of a spherical grid, thus enabling substantially larger time steps. HelioCubed has been developed using the high-level Proto library, ensures performance portability across CPU and GPU architectures, and supports back-end implementations, e.g., CUDA, HIP, OpenMP, and MPI. The code is compatible with the HDF5 library, which facilitates seamless data handling for simulations and boundary conditions derived from semi-empirical and MHD models of the solar corona. While presenting the results of preliminary simulations, we demonstrate that our simulations are indeed performed with 4th order of accuracy. Our approach ensures that HelioCubed solves the MHD equations preserving the radial flow to machine round-off error even on cubed-sphere grids. Solar wind simulations are performed using the boundary conditions provided by the Wang-Sheeley-Arge coronal model of the ambient solar wind. It also allows us to to simulate coronal mass ejections using observation-driven flux rope models. These capabilities make HelioCubed a versatile and powerful tool to advance heliophysics research and space weather forecasting. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Mesh generation

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Collision detection and response approaches for computer muscle modelling

Collision detection and response approaches for computer mus...

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IEEE International Scientific Conference on Informatics

作者： Ondrej Havlicek Martin Cervenka Josef Kohout Department of Computer Science and Engineering Faculty of Applied Sciences University of West Bohemia Pilsen Czech Republic NTIS - New Technologies for the Information Society Faculty of Applied Sciences University of West Bohemia Pilsen Czech Republic

computer muscle modelling is used for many pur-poses, from injury recovery and treatment of chronic diseases to disease prediction. These predictions often involve computing the muscle's internal forces to determine further how fast something may happen (e.g. how quickly the muscle joint wears out). During the simulation of such a model, collisions of soft and rigid bodies inevitably occur. This paper tests various state-of-the-art collision handling methods: voxelisation, one using Signed Distance Fields and one based on Bounding Volume Hierarchies. These methods are tested in the context of muscle modelling with the previously proposed position-based dynamics approach. Compared to the other options, using the Discregrid library for Signed Distance Field generation shows the best results, mainly due to its accuracy to the speed of execution ratio. In contrast to the current system, visually pleasant improvements are significant.

关键词： Solid modeling Analytical models Computational modeling Muscles Predictive models Libraries Informatics

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A SUCCESSIVE TWO-STAGE METHOD FOR SPARSE GENERALIZED EIGENVALUE PROBLEMS

arXiv

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arXiv 2023年

作者： Li, Qia Liao, Jianmin Shen, Lixin Zhang, Na School of Computer Science and Engineering Guangdong Province Key Laboratory of Computational Science Sun Yat-sen University Guangdong Province Guangzhou510275 China Department of Mathematics Syracuse University SyracuseNY13244 United States Department of Applied Mathematics College of Mathematics and Informatics South China Agricultural University Guangdong Province Guangzhou510642 China

The Sparse Generalized Eigenvalue Problem (sGEP), a pervasive challenge in statistical learning methods including sparse principal component analysis, sparse Fisher's discriminant analysis, and sparse canonical correlation analysis, presents significant computational complexity due to its NP-hardness. The primary aim of sGEP is to derive a sparse vector approximation of the largest generalized eigenvector, effectively posing this as a sparse optimization problem. Conventional algorithms for sGEP, however, often succumb to local optima and exhibit significant dependency on initial points. This predicament necessitates a more refined approach to avoid local optima and achieve an improved solution in terms of sGEP's objective value, which we address in this paper through a novel successive two-stage method. The first stage of this method incorporates an algorithm for sGEP capable of yielding a stationary point from any initial point. The subsequent stage refines this stationary point by adjusting its support, resulting in a point with an enhanced objective value relative to the original stationary point. This support adjustment is achieved through a novel procedure we have named support alteration. The final point derived from the second stage then serves as the initial point for the algorithm in the first stage, creating a cyclical process that continues until a predetermined stopping criterion is satisfied. We also provide a comprehensive convergence analysis of this process. Through extensive experimentation under various settings, our method has demonstrated significant improvements in the objective value of sGEP compared to existing methodologies, underscoring its potential as a valuable tool in statistical learning and *** Codes 90C26, 90C32, 90C59, 90C90 Copyright © 2023, The Authors. All rights reserved.

关键词： Principal component analysis

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Using Ultrasound to Probe the Supercooled Liquid Region of Bulk Metallic Glasses

SSRN

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SSRN 2023年

作者： Stevens, Rebecca Serrano, Joseph C. Quine, Cullen M. Johnson, William L. Conner, Robert D. College of Engineering and Computer Science California State University NorthridgeCA91330 United States Department of Chemistry and Biochemistry California State University NorthridgeCA91330 United States Department of Materials Science and Applied Physics California Institute of Technology PasadenaCA91125 United States National Renewable Energy Laboratory United States

Understanding the properties of the supercooled liquid in bulk metallic glasses (BMG) is vital for developing a theoretical framework to guide researchers searching for new alloys with high glass forming ability (GFA) and for the practical application of BMGs in forming and casting operations. Here we report on an effective method to measure the shear wave speed of two BMG alloys of differing fragility in the supercooled liquid. The measured wave speed were used to calculate their shear modulus, G(T), viscosity and fragility in a region between 106 – 1012 Pa-s. Viscosity and fragility was analyzed using the cooperative-shear model (CSM), and compared to results predicted by the Vogel-Fulcher-Tammann (VFT) and Cohen-Grest models and published results. GFA was calculated and compared to published results using methods developed by Senkov and Na et. al. Results show good agreement with published data and the CSM model. © 2023, The Authors. All rights reserved.

关键词： Ultrasonics

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Inverse Design with Dynamic Mode Decomposition

arXiv

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arXiv 2025年

作者： Zhu, Yunpeng Cheng, Liangliang Jing, Anping Huo, Hanyu Lang, Ziqiang Zhang, Bo Kutz, J. Nathan School of Engineering and Material Science Queen Mary University of London LondonE1 4NS United Kingdom ENTEG Faculty of Science and Engineering University of Groningen Groningen9747 AG Netherlands School of Mechanical Engineering Ningxia University Yinchuan750021 China School of Chemistry and Material Science University of Science and Technology of China Hefei230026 China School of Electrical and Electronic Engineering The University of Sheffield SheffieldS10 2TN United Kingdom Department of Applied Mathematics and Electrical and Computer Engineering University of Washington SeattleWA United States

We introduce a computationally efficient method for the automation of inverse design in science and engineering. Based on simple least-square regression, the underlying dynamic mode decomposition algorithm can be used to construct a low-rank subspace spanning multiple experiments in parameter space. The proposed inverse design dynamic mode composition (ID-DMD) algorithm leverages the computed low-dimensional subspace to enable fast digital design and optimization on laptop-level computing, including the potential to prescribe the dynamics themselves. Moreover, the method is robust to noise, physically interpretable, and can provide uncertainty quantification metrics. The architecture can also efficiently scale to large-scale design problems using randomized algorithms in the ID-DMD. The simplicity of the method and its implementation are highly attractive in practice, and the ID-DMD has been demonstrated to be an order of magnitude more accurate than competing methods while simultaneously being 3-5 orders faster on challenging engineering design problems ranging from structural vibrations to fluid dynamics. Due to its speed, robustness, interpretability, and ease-of-use, ID-DMD in comparison with other leading machine learning methods represents a significant advancement in data-driven methods for inverse design and optimization, promising a paradigm shift in how to approach inverse design in *** Codes 37M05, 37M10, 37M21 Copyright © 2025, The Authors. All rights reserved.

关键词： Dynamic mode decomposition

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On the relevance of lift force modelling in turbulent wall flows with small inertial particles

arXiv

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arXiv 2024年

作者： Gao, Wei Shi, Pengyu Parsani, Matteo Costa, Pedro Mechanical Engineering Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Applied Mathematics and Computational Science Computer Electrical and Mathematical Science and Engineering Division Extreme Computing Research Center King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Université de Toulouse CNRS Toulouse France Helmholtz-Zentrum Dresden – Rossendorf Institute of Fluid Dynamics Dresden01328 Germany Process & Energy Department TU Delft Leeghwaterstraat 39 Delft2628 CB Netherlands

In particle-laden turbulent wall flows, lift forces can influence the near-wall turbulence. This has been recently observed in particle-resolved simulations, which, however, are too expensive to be used in upscaled models. Instead, point-particle simulations have been the method of choice to simulate the dynamics of these flows during the last decades. While this approach is simpler, cheaper, and physically sound for small inertial particles in turbulence, some issues remain. In the present work, we address challenges associated with lift force modelling in turbulent wall flows and the impact of lift forces in the near-wall flow. We performed direct numerical simulations (DNS) of small inertial point particles in turbulent channel flow for fixed Stokes number and mass loading while varying the particle size. Our results show that the particle dynamics in the buffer region, causing the apparent particle-to-fluid slip velocity to vanish, raises major challenges for accurately modelling lift forces. While our results confirm that lift forces have little influence on particle dynamics for sufficiently small particle sizes, for inner-scaled diameters of order one and beyond, lift forces become quite important near the wall. The different particle dynamics under lift forces results in the modulation of streamwise momentum transport in the near-wall region. We analyze this lift-induced turbulence modulation for different lift force models, and the results indicate that realistic models are critical for particle-modelled simulations to correctly predict turbulence modulation by particles in the near-wall region. © 2024, CC BY.

关键词： Wall flow

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Enhancing COVID-19 vaccination and medication distribution routing strategies in rural regions of Morocco: A comparative metaheuristics analysis

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Informatics in Medicine Unlocked 2024年 46卷

作者： Mzili, Toufik Mzili, Ilyass Riffi, Mohammed Essaid Kurdi, Mohamed Ali, Ali Hasan Pamucar, Dragan Abualigah, Laith Department of Computer Science Faculty of Science Chouaib Doukkali University EI Jadida Morocco Department of Business Management Al-imam University College Balad Iraq Department of Computer Science Faculty of Economics and Management Hasan 1st University Settat Morocco Faculty of Informatics Engineering Idlib University Idlib Syrian Arab Republic Institute of Mathematics University of Debrecen Pf. 400 Debrecen H-4002 Hungary College of Engineering Technology National University of Science and Technology Dhi Qar 64001 Iraq Technical Engineering College Al-Ayen University Dhi Qar 64001 Iraq Department of Operations Research and Statistics Faculty of Organizational Sciences University of Belgrade Belgrade Serbia College of Engineering Yuan Ze University Taiwan Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan MEU Research Unit Middle East University Amman 11831 Jordan Applied science research center Applied science private university Amman 11931 Jordan

The optimization of the vaccination campaign and medication distribution in rural regions of Morocco conducted by the Ministry of Health can be significantly improved by employing metaheuristic algorithms in conjunction with a tour planning system. This research proposes the utilization of six metaheuristic algorithms: genetic algorithm, rat swarm optimization, whale optimization, spotted hyena optimizer, penguins search optimization, and particle swarm optimization, to determine the most efficient routes for equipped trucks carrying vaccines and medications. These algorithms consider critical field constraints, such as operating hours of vaccination centers, vaccine availability, and distances between centers while minimizing the overall journey duration. In addition, a comprehensive tour planning system is integrated into the optimization framework accounting for transportation costs such as fuel expenses and truck maintenance costs. By incorporating these factors, the Ministry of Health aims to achieve the maximum efficiency while minimizing the financial burden associated with the vaccination campaign in rural areas. The integration of metaheuristics and the tour planning system presents a robust and data-driven solution for the Ministry of Health to enhance the effectiveness of their vaccination and medication distribution campaigns in rural regions of Morocco. This approach not only minimizes costs but also improves overall efficiency by ensuring timely access to vaccines and medications for the rural population. The findings of this research contribute to the growing body of knowledge in the field of healthcare logistics optimization and provide valuable insights for policymakers and practitioners involved in similar campaigns worldwide. © 2024 The Authors

关键词： Healthcare logistics Medication distribution Metaheuristics Route optimization Tour planning system Transportation Vaccination campaign

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Cross-Game Generalization Approaches for General Video Game Playing using Deep Reinforcement Learning 2

Cross-Game Generalization Approaches for General Video Game ...

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2nd International Conference on Smart Electronics and Communication, ICOSEC 2021

作者： Ojha, Rajesh Kumar Rao, S Janardhana Goel, Pankaj Srivastava, Sandeep Kumar, K. Hareesh Prasad, Chitturi Sri Sri University Faculty of Science Odisha Cuttack753001 India Koneru Lakshmaiah Education Foundation Department of CSE AP Vaddeswaram522502 India GL Bajaj Institute of Technology Management Department of Applied Science and Humanities UP Greater Noida201306 India Galgotias University School of Computer Science Engineering UP Greater Noida201306 India Seshadri Rao Gudlavalleru Engineering College Department of CSE AP Gudlavalleru521356 India Koneru Lakshmaiah Education Foundation Department of CSE Department of CSE AP Vaddeswaram522502 India

ISBN: (纸本)9781665433686

This paper presents a number of novel approaches to help facilitate Deep Reinforcement Learning (DRL) for Neural Networks based agents in the domain of General Video Game Playing (GVGP). Using common processing methods, the NN can retain a fixed predetermined input and output shape while having the flexibility to play a variety of games. Training can also be made more efficient via reward normalization. Our results show that these modifications negligibly impact the learning time and performance of the model when testedupon games in the GVGAI framework. Furthermore analysis of these approaches within the parameters of the GVGAI learning competition was also performed. This research work attempts to use the adaptations presented to train an agent thatwill compete in the CEC2019 GVGAI Learning Competition. © 2021 IEEE.

关键词： Reinforcement learning

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On a Cyclometric Modification of the Chua System

On a Cyclometric Modification of the Chua System

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International IEEE Conference and Workshop: Óbuda on Electrical and Power engineering (CANDO-EPE)

作者： Bálint Nagy Antal Joós Attila Kovari Department of Mathematics Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Department of Natural Sciences Kandó Kálmán Faculty of Electrical Engineering Institute of Electrophysics Obuda University Budapest Hungary Department of Applied Quantitative Methods Faculty of Finance and Accountancy Budapest Business University Budapest Hungary Kandó Kálmán Faculty of Electrical Engineering Institute of Electronics and Communication Systems Obuda University Budapest Hungary Faculty of Computer Science Institute of Digital Technology Eszterházy Károly Catholic University Eger Hungary Department of Natural Sciences Institute of Engineering University of Dunaújváros Dunaujvaros Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemét Hungary

Chaos is not only a unique chapter in the theory of dynamical systems but also a useful one with many applications in the field of communications. In this work a cyclometric modification of the well-known example of chaotic systems, the modified differential equations describing the behavior of the Chua-circuit is investigated. The results obtained can be applied in the encryption methods of the implementation of different communication channels like machine-machine or cognitive one.

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