Transformer has achieved remarkable results in various fields,including its application in modeling dynamic systems governed by partial differential ***,transformer still face challenges in achieving long-term stable ...
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Transformer has achieved remarkable results in various fields,including its application in modeling dynamic systems governed by partial differential ***,transformer still face challenges in achieving long-term stable predictions for three-dimensional *** this paper,we propose an implicit factorized transformer(IFactFormer)model,which enables stable training at greater depths through implicit iteration over factorized *** is applied to large eddy simulation of three-dimensional homogeneous isotropic turbulence(HIT),and is shown to be more accurate than the FactFormer,Fourier neural operator,and dynamic Smagorinsky model(DSM)in the prediction of the velocity spectra,probability density functions of velocity increments and vorticity,temporal evolutions of velocity and vorticity root-mean-square value and isosurface of the normalized *** can achieve long-term stable predictions of a series of turbulence statistics in ***-thermore,IFactFormer showcases superior computational efficiency compared to the conventional DSM in large eddy simulation.
Online signatures are one of the widely accepted biometrics used for the purpose of authentication and identification. Although there are several approaches and algorithms used in online signature verification systems...
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The most commonly used technique in time-frequency analysis is the short-time Fourier transform. It can be used to determine the spectral components as they change over time by computing the Fourier transform of a win...
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Protein-protein interactions (PPIs) are crucial for various cellular activities and disease development, and modulating PPIs using small molecule inhibitors (PPIIs) has gradually become a promising therapeutic strateg...
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Rapid advancements in deep learning over the past decade have fueled an insatiable demand for efficient and scalable *** offers a promising solution by leveraging the unique properties of ***,conventional neural netwo...
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Rapid advancements in deep learning over the past decade have fueled an insatiable demand for efficient and scalable *** offers a promising solution by leveraging the unique properties of ***,conventional neural network architectures,which typically require dense programmable connections,pose several practical challenges for photonic *** overcome these limitations,we propose and experimentally demonstrate Photonic Neural Cellular Automata(PNCA)for photonic deep learning with sparse *** harnesses the speed and interconnectivity of photonics,as well as the self-organizing nature of cellular automata through local interactions to achieve robust,reliable,and efficient *** utilize linear light interference and parametric nonlinear optics for all-optical computations in a time-multiplexed photonic network to experimentally perform self-organized image *** demonstrate binary(two-class)classification of images using as few as 3 programmable photonic parameters,achieving high experimental accuracy with the ability to also recognize out-ofdistribution *** proposed PNCA approach can be adapted to a wide range of existing photonic hardware and provides a compelling alternative to conventional photonic neural networks by maximizing the advantages of lightbased computing whilst mitigating their practical *** results showcase the potential of PNCA in advancing photonic deep learning and highlights a path for next-generation photonic computers.
Road maintenance is required to maintain roads in good condition. Identifying the type of road damage is one of the steps in road maintenance. There has been research on the detection of types of road damage. However,...
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Machine learning has emerged as a powerful tool for predicting signal range in wireless communication networks, offering significant improvements over conventional models. Traditional methods, such as empirical path l...
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Indonesia has experienced 655 terrorism incidents between 2000 and 2024, leading to numerous casualties. This study aims to enhance understanding of public sentiment on Twitter in response to notable terrorism events,...
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This research introduces a novel methodology for high-accuracy modeling of antenna characteristics. It is centered around a recurrent neural network (RNN) optimized through Bayesian Optimization (BO). The RNN architec...
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In association with economy or jobs Smart City is used to describe a city with a 'smart' industry. That implies especially industries in the fields of information and communication technologies (ICT) as well a...
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