This paper studies the problem of the spectral radius of the uniform hypergraph determined by the signless Laplacian matrix.The upper bound of the spectral radius of a uniform hypergraph is obtained by using Rayleigh ...This paper studies the problem of the spectral radius of the uniform hypergraph determined by the signless Laplacian matrix.The upper bound of the spectral radius of a uniform hypergraph is obtained by using Rayleigh principle and the perturbation of the spectral radius under moving the edge operation,and the extremal hypergraphs are characterized for both supertree and unicyclic hypergraphs.The spectral radius of the graph is generalized.展开更多
Due to self-occlusion and high degree of freedom,estimating 3D hand pose from a single RGB image is a great challenging problem.Graph convolutional networks(GCNs)use graphs to describe the physical connection relation...Due to self-occlusion and high degree of freedom,estimating 3D hand pose from a single RGB image is a great challenging problem.Graph convolutional networks(GCNs)use graphs to describe the physical connection relationships between hand joints and improve the accuracy of 3D hand pose regression.However,GCNs cannot effectively describe the relationships between non-adjacent hand joints.Recently,hypergraph convolutional networks(HGCNs)have received much attention as they can describe multi-dimensional relationships between nodes through hyperedges;therefore,this paper proposes a framework for 3D hand pose estimation based on HGCN,which can better extract correlated relationships between adjacent and non-adjacent hand joints.To overcome the shortcomings of predefined hypergraph structures,a kind of dynamic hypergraph convolutional network is proposed,in which hyperedges are constructed dynamically based on hand joint feature similarity.To better explore the local semantic relationships between nodes,a kind of semantic dynamic hypergraph convolution is proposed.The proposed method is evaluated on publicly available benchmark datasets.Qualitative and quantitative experimental results both show that the proposed HGCN and improved methods for 3D hand pose estimation are better than GCN,and achieve state-of-the-art performance compared with existing methods.展开更多
This paper focuses on the problem of traffic flow forecasting,with the aim of forecasting future traffic conditions based on historical traffic data.This problem is typically tackled by utilizing spatio-temporal graph...This paper focuses on the problem of traffic flow forecasting,with the aim of forecasting future traffic conditions based on historical traffic data.This problem is typically tackled by utilizing spatio-temporal graph neural networks to model the intricate spatio-temporal correlations among traffic data.Although these methods have achieved performance improvements,they often suffer from the following limitations:These methods face challenges in modeling high-order correlations between nodes.These methods overlook the interactions between nodes at different scales.To tackle these issues,in this paper,we propose a novel model named multi-scale dynamic hypergraph convolutional network(MSDHGCN)for traffic flow forecasting.Our MSDHGCN can effectively model the dynamic higher-order relationships between nodes at multiple time scales,thereby enhancing the capability for traffic forecasting.Experiments on two real-world datasets demonstrate the effectiveness of the proposed method.展开更多
Graph labeling is the assignment of integers to the vertices,edges,or both,subject to certain conditions.Accordingly,hypergraph labeling is also the assignment of integers to the vertices,edges,or both,subject to cert...Graph labeling is the assignment of integers to the vertices,edges,or both,subject to certain conditions.Accordingly,hypergraph labeling is also the assignment of integers to the vertices,edges,or both,subject to certain conditions.This paper is to generalize the coprime labelings of graph to hypergraph.We give the definition of coprime labelings of hypergraph.By using Rosser-Schoenfeld's inequality and the coprime mapping theorem of Pomerance and Selfridge,we prove that some linear hypergraphs are prime.展开更多
Complex networks play a crucial role in the study of collective behavior,encompassing the analysis of dynamical properties and network topology.In real-world systems,higher-order interactions among multiple entities a...Complex networks play a crucial role in the study of collective behavior,encompassing the analysis of dynamical properties and network topology.In real-world systems,higher-order interactions among multiple entities are widespread and significantly influence collective dynamics.Here,we extend the synchronization alignment function framework to hypergraphs of arbitrary order by leveraging the multi-order Laplacian matrix to encode higher-order interactions.Our findings reveal that the upper bound of synchronous behavior is determined by the maximum eigenvalue of the multi-order Laplacian matrix.Furthermore,we decompose the contribution of each hyperedge to this eigenvalue and utilize it as a basis for designing an eigenvalue-based topology modification algorithm.This algorithm effectively enhances the upper bound of synchronous behavior without altering the total number of higher-order interactions.Our study provides new insights into dynamical optimization and topology tuning in hypergraphs,advancing the understanding of the interplay between higher-order interactions and collective dynamics.展开更多
Direct numerical simulations have been conducted to investigate the evolution process of liquid metal laminar to turbulent flow in a rectangular duct under the influence of a non-uniform magnetic field.The Reynolds nu...Direct numerical simulations have been conducted to investigate the evolution process of liquid metal laminar to turbulent flow in a rectangular duct under the influence of a non-uniform magnetic field.The Reynolds number is Re=6299,and the inlet Hartmann number is Ha=2900,with the magnetic field strength decreasing along the flow direction.The results indicate that the dynamic reversal of the three-dimensional(3D)Lorentz force direction near the inflection point of the magnetic field dominates the flow reconstruction,driving the wall jet acceleration and forming an M-type velocity distribution.Moreover,the high-speed shear layer of the jet triggers Kelvin-Helmholtz instability,resulting in the generation of secondary vortex structures near the parallel layer in the non-uniform magnetic field region.In the cross-section perpendicular to the flow direction,the secondary flow gradually evolves into a four-vortex structure,while the velocity fluctuations and turbulent kinetic energy reach the peak.Based on the characteristics of the vortex rotation direction near the shear layer,the intrinsic mechanism behind the unique bimodal distribution of the root-mean-square of velocity fluctuations in the parallel layers is revealed.Furthermore,by comparing the evolution of turbulence under different magnetic field gradients,it is revealed that the distributions of shear stress,Reynolds stress,and turbulent kinetic energy exhibit significant parameter dependence.The strong 3D magnetohydrodynamic effects at the magnetic field gradientγ=0.6 have an immediate impact on the pressure distribution.The transverse Lorentz force LFz further promotes the fluid to accumulate at the wall,leading to a significant increase in the pressure drop and transverse pressure difference in the flow.展开更多
Hypergraphs can accurately capture complex higher-order relationships,but it is challenging to identify their important nodes.In this paper,an improved PageRank(ImPageRank)algorithm is designed to identify important n...Hypergraphs can accurately capture complex higher-order relationships,but it is challenging to identify their important nodes.In this paper,an improved PageRank(ImPageRank)algorithm is designed to identify important nodes in a directed hypergraph.The algorithm introduces the Jaccard similarity of directed hypergraphs.By comparing the numbers of common neighbors between nodes with the total number of their neighbors,the Jaccard similarity measure takes into account the similarity between nodes that are not directly connected,and can reflect the potential correlation between nodes.An improved susceptible–infected(SI)model in directed hypergraph is proposed,which considers nonlinear propagation mode and more realistic propagation mechanism.In addition,some important node evaluation methods are transferred from undirected hypergraphs and applied to directed hypergraphs.Finally,the ImPageRank algorithm is used to evaluate the performance of the SI model,network robustness and monotonicity.Simulations of real networks demonstrate the excellent performance of the proposed algorithm and provide a powerful framework for identifying important nodes in directed hypergraphs.展开更多
Unlike traditional video cameras,event cameras capture asynchronous event streams in which each event encodes pixel location,triggers’timestamps,and the polarity of brightness changes.In this paper,we introduce a nov...Unlike traditional video cameras,event cameras capture asynchronous event streams in which each event encodes pixel location,triggers’timestamps,and the polarity of brightness changes.In this paper,we introduce a novel hypergraph-based framework for moving object classification.Specifically,we capture moving objects with an event camera,to perceive and collect asynchronous event streams in a high temporal resolution.Unlike stacked event frames,we encode asynchronous event data into a hypergraph,fully mining the high-order correlation of event data,and designing a mixed convolutional hypergraph neural network for training to achieve a more efficient and accurate motion target recognition.The experimental results show that our method has a good performance in moving object classification(e.g.,gait identification).展开更多
Hypergraphs,which encapsulate interactions of higher-order beyond mere pairwise connections,are essential for representing polyadic relationships within complex systems.Consequently,an increasing number of researchers...Hypergraphs,which encapsulate interactions of higher-order beyond mere pairwise connections,are essential for representing polyadic relationships within complex systems.Consequently,an increasing number of researchers are focusing on the centrality problem in hypergraphs.Specifically,researchers are tackling the challenge of utilizing higher-order structures to effectively define centrality metrics.This paper presents a novel approach,LGK,derived from the K-shell decomposition method,which incorporates both global and local perspectives.Empirical evaluations indicate that the LGK method provides several advantages,including reduced time complexity and improved accuracy in identifying critical nodes in hypergraphs.展开更多
Growth of high-quality Nb_(3)Sn thin films for superconducting radiofrequency(SRF)applications using the vapor diffusion method requires a uniform distribution of tin nuclei on the niobium(Nb)surface.This study examin...Growth of high-quality Nb_(3)Sn thin films for superconducting radiofrequency(SRF)applications using the vapor diffusion method requires a uniform distribution of tin nuclei on the niobium(Nb)surface.This study examines the mechanism underlying the observed non-uniform distribution of tin nuclei with tin chloride SnCl_(2).Electron backscatter diffraction(EBSD)analysis was used to examine the correlation between the nucleation behavior and orientation of niobium grains in the substrate.The findings of the density functional theory(DFT)simulation are in good agreement with the experimental results,showing that the non-uniform distribution of tin nuclei is the result of the adsorption energy of SnCl_(2)molecules by varied niobium grain orientations.Further analysis indicated that the surface roughness and grain size of niobium also played significant roles in the nucleation behavior.This study provides valuable insights into enhancing the surface pretreatment of niobium substrates during the growth of Nb_(3)Sn thin films using the vapor diffusion method.展开更多
To thoroughly examine the complex relationships between tire and pavement vibrations,a sophisticated vehicle-pavement coupled system is proposed,incorporating a non-uniform dynamic friction force between the tire and ...To thoroughly examine the complex relationships between tire and pavement vibrations,a sophisticated vehicle-pavement coupled system is proposed,incorporating a non-uniform dynamic friction force between the tire and the pavement.According to the Timoshenko beam theory,a dynamic model of pavement structure with a finite length beam was formulated on a nonlinear Pasternak foundation.To more accurately describe the coupling relationship between the tire and the pavement,and to take into account the vibration state under vehicle-pavement interaction,the load distribution between the tire and the pavement is modeled as a dynamic non-uniform contact.Combined with the classic LuGre tire model,the adhesion between the tire and the pavement is calculated.The Galerkin truncation method is employed to transform the pavement vibration partial differential equation into a finite ordinary differential equation,and the integral expression of the nonlinear foundation beam term is derived using the product to sum formula.By using the Runge-Kutta method,the tire-road coupled system can be numerically calculated,thus determining tire adhesion.This research demonstrates that compared with tire force under the traditional static load distribution,load distribution has a significant influence on adhesion.This study offers valuable insights for pavement structure design and vehicle performance control.展开更多
Cooling system design applicable to more than one photovoltaic(PV)unit may be challenging due to the arrangement and geometry of the modules.Different cooling techniques are provided in this study to regulate the temp...Cooling system design applicable to more than one photovoltaic(PV)unit may be challenging due to the arrangement and geometry of the modules.Different cooling techniques are provided in this study to regulate the temperature of conductive panels that are arranged perpendicular to each other.The model uses two vented cavity systems and one L-shaped channel with ternary nanofluid enhanced non-uniform magnetic field.Their cooling performances and comparative results between different systems are provided.The finite element method is used to conduct a numerical analysis for a range of values of the following:the strength of themagnetic field(Hartmann number(Ha)between 0 and 50),the inclination of the magnetic field(γbetween 0 and 90),and the loading of nanoparticles in the base fluid(ϕbetween 0 and 0.03),taking into account both uniformand non-uniformmagnetic fields.For the L-shaped channel and vented cavities,vortex size is controlled by imposing magnetic field and adjusting its strength.Whether uniform or non-uniform magnetic field is applied affects the cooling performances for different cooling configurations.Temperature drops of the horizontal panel with different magnetic field strengths by using channel cooling,vented cavity-1 and vented cavity-2 systems for uniformmagnetic are 11℃,21.5℃,and 3℃when the reference case of Ha=0 is considered for the same cooling systems.However,they become 9.5℃,13.5℃,and 12.5℃when nonuniform magnetic field is used.In the presence of uniform magnetic field effects and changing its magnitude,the use of cooling channel in vented cavity-1 and vented cavity-2 systems results in temperature drops of 4℃,10.8℃,and 3.8℃for vertical panels.On the other hand,when non-uniform magnetic field effects are present,they become 0.5℃,2.1℃,and 9℃.For L-channel cooling,the average Nu for the horizontal panel is more affected byγ,andNu rises asγrises.With increasing nanoparticle loading of ternary nanofluid,the average panel surface temperature shows a linear drop.For the horizontal panel,the temperature declines for nanofluid at the highest loading are 4℃,10℃,and 12℃as compared to using only base fluid.The values of 5℃,7℃,and 11℃are obtained for the vertical panel.Different cooling systems’performance is estimated using artificial neural networks.The method captures the combined impact of applying non-uniformmagnetic field and nanofluid together on the cooling performancewhile accounting for varied cooling strategies for both panels.展开更多
In low-light image enhancement,prevailing Retinex-based methods often struggle with precise illumina-tion estimation and brightness modulation.This can result in issues such as halo artifacts,blurred edges,and diminis...In low-light image enhancement,prevailing Retinex-based methods often struggle with precise illumina-tion estimation and brightness modulation.This can result in issues such as halo artifacts,blurred edges,and diminished details in bright regions,particularly under non-uniform illumination conditions.We propose an innovative approach that refines low-light images by leveraging an in-depth awareness of local content within the image.By introducing multi-scale effective guided filtering,our method surpasses the limitations of traditional isotropic filters,such as Gaussian filters,in handling non-uniform illumination.It dynamically adjusts regularization parameters in response to local image characteristics and significantly integrates edge perception across different scales.This balanced approach achieves a harmonious blend of smoothing and detail preservation,enabling more accurate illumination estimation.Additionally,we have designed an adaptive gamma correction function that dynamically adjusts the brightness value based on local pixel intensity,further balancing enhancement effects across different brightness levels in the image.Experimental results demonstrate the effectiveness of our proposed method for non-uniform illumination images across various scenarios.It exhibits superior quality and objective evaluation scores compared to existing methods.Our method effectively addresses potential issues that existing methods encounter when processing non-uniform illumination images,producing enhanced images with precise details and natural,vivid colors.展开更多
Traffic flow prediction is a crucial element of intelligent transportation systems.However,accu-rate traffic flow prediction is quite challenging because of its highly nonlinear,complex,and dynam-ic characteristics.To...Traffic flow prediction is a crucial element of intelligent transportation systems.However,accu-rate traffic flow prediction is quite challenging because of its highly nonlinear,complex,and dynam-ic characteristics.To address the difficulties in simultaneously capturing local and global dynamic spatiotemporal correlations in traffic flow,as well as the high time complexity of existing models,a multi-head flow attention-based local-global dynamic hypergraph convolution(MFA-LGDHC)pre-diction model is proposed.which consists of multi-head flow attention(MHFA)mechanism,graph convolution network(GCN),and local-global dynamic hypergraph convolution(LGHC).MHFA is utilized to extract the time dependency of traffic flow and reduce the time complexity of the model.GCN is employed to catch the spatial dependency of traffic flow.LGHC utilizes down-sampling con-volution and isometric convolution to capture the local and global spatial dependencies of traffic flow.And dynamic hypergraph convolution is used to model the dynamic higher-order relationships of the traffic road network.Experimental results indicate that the MFA-LGDHC model outperforms current popular baseline models and exhibits good prediction performance.展开更多
To investigate the influence of non-uniform water distribution on the mechanical properties and failure behavior of red sandstone,we designed five immersion heights and durations to achieve varying non-uniform water d...To investigate the influence of non-uniform water distribution on the mechanical properties and failure behavior of red sandstone,we designed five immersion heights and durations to achieve varying non-uniform water distribution states.Uniaxial compression tests were conducted on red sandstone under these conditions.The effects of non-uniform water distribution on deformation,failure,strength,and energy characteristics of red sandstone were analyzed.The impact of non-uniform water distribution on the intensity of rock failure was discussed,and the failure mechanism under non-uniform water distribution was revealed.The hazards of low immersion heights on underground rock structures were analyzed.The results demonstrate that peak strength and elastic modulus of red sandstone exhibit high sensitivity to immersion height,with reductions of 38%and 23%respectively even at L=1/50H.Water immersion reduces both energy storage capacity and energy dissipation capability of red sandstone.The immersion height and duration influence the failure mode of red sandstone by controlling the migration and separation of dry-wet interfaces.Low immersion height poses significant risks to underground rock structures(e.g.,a 38%strength reduction when L=1/50H),and the concentration degree of water non-uniform distribution is the key factor in assessing the weakening effect of water on rocks.展开更多
The intrusion of obstacles onto railway tracks presents a significant threat to train safety,characterized by sudden and unpredictable occurrences.With China leading the world in high-speed rail mileage,ensuring railw...The intrusion of obstacles onto railway tracks presents a significant threat to train safety,characterized by sudden and unpredictable occurrences.With China leading the world in high-speed rail mileage,ensuring railway security is paramount.The current laser monitoring technologies suffer from high false alarm rates and unreliable intrusion identification.This study addresses these issues by investigating high-resolution laser monitoring technology for railway obstacles,focusing on key parameters such as monitoring range and resolution.We propose an enhanced non-uniform laser scanning method,developing a laser monitoring system that reduces the obstacle false alarm rate to 2.00%,significantly lower than the 20%standard(TJ/GW135-2015).This rate is the best record for laser monitoring systems on China Railway.Our system operates seamlessly in all weather conditions,providing superior accuracy,resolution,and identification efficiency.It is the only 3D LiDAR system certified by the China State Railway Group Co.,Ltd.(Certificate No.[2023]008).Over three years,our system has been deployed at numerous points along various lines managed by the China State Railway Group,accumulating a dataset of 300,000 observations.This extensive deployment has significantly enhanced railway safety.The development and implementation of our railway laser monitoring system represent a substantial advancement in railway safety technology.Its low false alarm rate(2.00%),high accuracy(20 cm×20 cm×20 cm),and robust performance in diverse conditions underscore its potential for widespread adoption,promising to enhance railway safety in China and internationally.展开更多
Array configuration of multiple-input multiple-output （MIMO） radar with non-uniform linear array （NLA） is proposed. Unlike a standard phased-array radar where NLA is used to generate thinner beam patterns, in MIMO...Array configuration of multiple-input multiple-output （MIMO） radar with non-uniform linear array （NLA） is proposed. Unlike a standard phased-array radar where NLA is used to generate thinner beam patterns, in MIMO radar the property of NLA is exploited to get more distinct virtual array elements so as to improve pa- rameter identifiability, which means the maximum number of targets that can be uniquely identified by the radar. A class of NLA called minimum redundancy linear array （MRLA） is employed and a new method to construct large MRLAs is descrihed. The numerical results verify that compared to uniform linear array （ULA） MIMO radars, NLA MIMO radars can retain the same parameter identifiability with fewer physical antennas and achieve larger aperture length and lower Cramer-Rao bound with the same number of the physical antennas.展开更多
To analyze a multibody system composed of non-uniform beam and spring-mass subsystems, the model discretization is carried on by utilizing the finite element method（FEM）, the dynamic model of non-uniform beam is dev...To analyze a multibody system composed of non-uniform beam and spring-mass subsystems, the model discretization is carried on by utilizing the finite element method（FEM）, the dynamic model of non-uniform beam is developed by using the transfer matrix method of multibody system（MS-TMM）, the transfer matrix of non-u- niform beam is derived, and the natural frequencies are computed. Compared with the numerical assembly method （NAM）, the results by MS-TMM have good agreement with the results by FEM, and are better than the results by NAM. When using the high precision method, the global dynamic equations of the complex multibody system are not needed and the orders of involved system matrices are decreased greatly. For the investigation on the re- verse problem of the physical parameter identification of multibody system, MS-TMM and the optimization tech- nology based on genetic algorithms（GAs） are combined and extended. The identification problem is exchanged for an optimization problem, and it is formulated as a global minimum solution of the objective function with respect to natural frequencies of multibody system. At last, the numerical example of non-uniform beam with attach- ments is discussed, and the identification results indicate the feasibility and the effectivity of the proposed aop- proach.展开更多
基金Supported by Natural Science Foundation of HuBei Province(2022CFB299).
文摘This paper studies the problem of the spectral radius of the uniform hypergraph determined by the signless Laplacian matrix.The upper bound of the spectral radius of a uniform hypergraph is obtained by using Rayleigh principle and the perturbation of the spectral radius under moving the edge operation,and the extremal hypergraphs are characterized for both supertree and unicyclic hypergraphs.The spectral radius of the graph is generalized.
基金the National Key Research and Development Program of China(No.2021ZD0111902)the National Natural Science Foundation of China(Nos.62172022 and U21B2038)。
文摘Due to self-occlusion and high degree of freedom,estimating 3D hand pose from a single RGB image is a great challenging problem.Graph convolutional networks(GCNs)use graphs to describe the physical connection relationships between hand joints and improve the accuracy of 3D hand pose regression.However,GCNs cannot effectively describe the relationships between non-adjacent hand joints.Recently,hypergraph convolutional networks(HGCNs)have received much attention as they can describe multi-dimensional relationships between nodes through hyperedges;therefore,this paper proposes a framework for 3D hand pose estimation based on HGCN,which can better extract correlated relationships between adjacent and non-adjacent hand joints.To overcome the shortcomings of predefined hypergraph structures,a kind of dynamic hypergraph convolutional network is proposed,in which hyperedges are constructed dynamically based on hand joint feature similarity.To better explore the local semantic relationships between nodes,a kind of semantic dynamic hypergraph convolution is proposed.The proposed method is evaluated on publicly available benchmark datasets.Qualitative and quantitative experimental results both show that the proposed HGCN and improved methods for 3D hand pose estimation are better than GCN,and achieve state-of-the-art performance compared with existing methods.
基金the National Key Research and Development Program of China(No.2021ZD0112400)。
文摘This paper focuses on the problem of traffic flow forecasting,with the aim of forecasting future traffic conditions based on historical traffic data.This problem is typically tackled by utilizing spatio-temporal graph neural networks to model the intricate spatio-temporal correlations among traffic data.Although these methods have achieved performance improvements,they often suffer from the following limitations:These methods face challenges in modeling high-order correlations between nodes.These methods overlook the interactions between nodes at different scales.To tackle these issues,in this paper,we propose a novel model named multi-scale dynamic hypergraph convolutional network(MSDHGCN)for traffic flow forecasting.Our MSDHGCN can effectively model the dynamic higher-order relationships between nodes at multiple time scales,thereby enhancing the capability for traffic forecasting.Experiments on two real-world datasets demonstrate the effectiveness of the proposed method.
基金Supported by the Natural Science Foundation of Chongqing(CSTB2022NSCQ-MSX0884)。
文摘Graph labeling is the assignment of integers to the vertices,edges,or both,subject to certain conditions.Accordingly,hypergraph labeling is also the assignment of integers to the vertices,edges,or both,subject to certain conditions.This paper is to generalize the coprime labelings of graph to hypergraph.We give the definition of coprime labelings of hypergraph.By using Rosser-Schoenfeld's inequality and the coprime mapping theorem of Pomerance and Selfridge,we prove that some linear hypergraphs are prime.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.12247153,T2293771,and 12247101)the Zhejiang Provincial Natural Science Foundation of China(Grant No.LTGY24A050002)+3 种基金the Sichuan Science and Technology Program(Grant Nos.2024NSFSC1364 and 2023NSFSC1919)the Project of Huzhou Science and Technology Bureau(Grant No.2022YZ29)the UESTCYDRI research start-up(Grant No.U03210066)the New Cornerstone Science Foundation through the Xplorer Prize。
文摘Complex networks play a crucial role in the study of collective behavior,encompassing the analysis of dynamical properties and network topology.In real-world systems,higher-order interactions among multiple entities are widespread and significantly influence collective dynamics.Here,we extend the synchronization alignment function framework to hypergraphs of arbitrary order by leveraging the multi-order Laplacian matrix to encode higher-order interactions.Our findings reveal that the upper bound of synchronous behavior is determined by the maximum eigenvalue of the multi-order Laplacian matrix.Furthermore,we decompose the contribution of each hyperedge to this eigenvalue and utilize it as a basis for designing an eigenvalue-based topology modification algorithm.This algorithm effectively enhances the upper bound of synchronous behavior without altering the total number of higher-order interactions.Our study provides new insights into dynamical optimization and topology tuning in hypergraphs,advancing the understanding of the interplay between higher-order interactions and collective dynamics.
基金supported by the Chinese Academy of Sciences Project for Young Scientists in Basic Research(Grant No.YSBR-087)and the National Key R&D Program of China(Grant No.2022YFA1204100)。
文摘Direct numerical simulations have been conducted to investigate the evolution process of liquid metal laminar to turbulent flow in a rectangular duct under the influence of a non-uniform magnetic field.The Reynolds number is Re=6299,and the inlet Hartmann number is Ha=2900,with the magnetic field strength decreasing along the flow direction.The results indicate that the dynamic reversal of the three-dimensional(3D)Lorentz force direction near the inflection point of the magnetic field dominates the flow reconstruction,driving the wall jet acceleration and forming an M-type velocity distribution.Moreover,the high-speed shear layer of the jet triggers Kelvin-Helmholtz instability,resulting in the generation of secondary vortex structures near the parallel layer in the non-uniform magnetic field region.In the cross-section perpendicular to the flow direction,the secondary flow gradually evolves into a four-vortex structure,while the velocity fluctuations and turbulent kinetic energy reach the peak.Based on the characteristics of the vortex rotation direction near the shear layer,the intrinsic mechanism behind the unique bimodal distribution of the root-mean-square of velocity fluctuations in the parallel layers is revealed.Furthermore,by comparing the evolution of turbulence under different magnetic field gradients,it is revealed that the distributions of shear stress,Reynolds stress,and turbulent kinetic energy exhibit significant parameter dependence.The strong 3D magnetohydrodynamic effects at the magnetic field gradientγ=0.6 have an immediate impact on the pressure distribution.The transverse Lorentz force LFz further promotes the fluid to accumulate at the wall,leading to a significant increase in the pressure drop and transverse pressure difference in the flow.
基金Project supported by the National Natural Science Foundation of China(Grant No.62166010)the Guangxi Natural Science Foundation(Grant No.2023GXNSFAA026087).
文摘Hypergraphs can accurately capture complex higher-order relationships,but it is challenging to identify their important nodes.In this paper,an improved PageRank(ImPageRank)algorithm is designed to identify important nodes in a directed hypergraph.The algorithm introduces the Jaccard similarity of directed hypergraphs.By comparing the numbers of common neighbors between nodes with the total number of their neighbors,the Jaccard similarity measure takes into account the similarity between nodes that are not directly connected,and can reflect the potential correlation between nodes.An improved susceptible–infected(SI)model in directed hypergraph is proposed,which considers nonlinear propagation mode and more realistic propagation mechanism.In addition,some important node evaluation methods are transferred from undirected hypergraphs and applied to directed hypergraphs.Finally,the ImPageRank algorithm is used to evaluate the performance of the SI model,network robustness and monotonicity.Simulations of real networks demonstrate the excellent performance of the proposed algorithm and provide a powerful framework for identifying important nodes in directed hypergraphs.
基金the National Key Research and Development Program of China(No.2021ZD0112400)。
文摘Unlike traditional video cameras,event cameras capture asynchronous event streams in which each event encodes pixel location,triggers’timestamps,and the polarity of brightness changes.In this paper,we introduce a novel hypergraph-based framework for moving object classification.Specifically,we capture moving objects with an event camera,to perceive and collect asynchronous event streams in a high temporal resolution.Unlike stacked event frames,we encode asynchronous event data into a hypergraph,fully mining the high-order correlation of event data,and designing a mixed convolutional hypergraph neural network for training to achieve a more efficient and accurate motion target recognition.The experimental results show that our method has a good performance in moving object classification(e.g.,gait identification).
文摘Hypergraphs,which encapsulate interactions of higher-order beyond mere pairwise connections,are essential for representing polyadic relationships within complex systems.Consequently,an increasing number of researchers are focusing on the centrality problem in hypergraphs.Specifically,researchers are tackling the challenge of utilizing higher-order structures to effectively define centrality metrics.This paper presents a novel approach,LGK,derived from the K-shell decomposition method,which incorporates both global and local perspectives.Empirical evaluations indicate that the LGK method provides several advantages,including reduced time complexity and improved accuracy in identifying critical nodes in hypergraphs.
基金supported by the National Natural Science Foundation of China(No.12175283)Youth Innovation Promotion Association of Chinese Academy of Sciences(2020410)Advanced Energy Science and Technology Guangdong Laboratory(HND20TDSPCD,HND22PTDZD).
文摘Growth of high-quality Nb_(3)Sn thin films for superconducting radiofrequency(SRF)applications using the vapor diffusion method requires a uniform distribution of tin nuclei on the niobium(Nb)surface.This study examines the mechanism underlying the observed non-uniform distribution of tin nuclei with tin chloride SnCl_(2).Electron backscatter diffraction(EBSD)analysis was used to examine the correlation between the nucleation behavior and orientation of niobium grains in the substrate.The findings of the density functional theory(DFT)simulation are in good agreement with the experimental results,showing that the non-uniform distribution of tin nuclei is the result of the adsorption energy of SnCl_(2)molecules by varied niobium grain orientations.Further analysis indicated that the surface roughness and grain size of niobium also played significant roles in the nucleation behavior.This study provides valuable insights into enhancing the surface pretreatment of niobium substrates during the growth of Nb_(3)Sn thin films using the vapor diffusion method.
基金financially supported by the National Natural Science Foundation of China(Grant No.12072204).
文摘To thoroughly examine the complex relationships between tire and pavement vibrations,a sophisticated vehicle-pavement coupled system is proposed,incorporating a non-uniform dynamic friction force between the tire and the pavement.According to the Timoshenko beam theory,a dynamic model of pavement structure with a finite length beam was formulated on a nonlinear Pasternak foundation.To more accurately describe the coupling relationship between the tire and the pavement,and to take into account the vibration state under vehicle-pavement interaction,the load distribution between the tire and the pavement is modeled as a dynamic non-uniform contact.Combined with the classic LuGre tire model,the adhesion between the tire and the pavement is calculated.The Galerkin truncation method is employed to transform the pavement vibration partial differential equation into a finite ordinary differential equation,and the integral expression of the nonlinear foundation beam term is derived using the product to sum formula.By using the Runge-Kutta method,the tire-road coupled system can be numerically calculated,thus determining tire adhesion.This research demonstrates that compared with tire force under the traditional static load distribution,load distribution has a significant influence on adhesion.This study offers valuable insights for pavement structure design and vehicle performance control.
基金funded by the Deanship of Scientific Research and Libraries,Princess Nourah bint Abdulrahman University,through the Program of Research Project Funding after Publication,grant No.(RPFAP-88-1445).
文摘Cooling system design applicable to more than one photovoltaic(PV)unit may be challenging due to the arrangement and geometry of the modules.Different cooling techniques are provided in this study to regulate the temperature of conductive panels that are arranged perpendicular to each other.The model uses two vented cavity systems and one L-shaped channel with ternary nanofluid enhanced non-uniform magnetic field.Their cooling performances and comparative results between different systems are provided.The finite element method is used to conduct a numerical analysis for a range of values of the following:the strength of themagnetic field(Hartmann number(Ha)between 0 and 50),the inclination of the magnetic field(γbetween 0 and 90),and the loading of nanoparticles in the base fluid(ϕbetween 0 and 0.03),taking into account both uniformand non-uniformmagnetic fields.For the L-shaped channel and vented cavities,vortex size is controlled by imposing magnetic field and adjusting its strength.Whether uniform or non-uniform magnetic field is applied affects the cooling performances for different cooling configurations.Temperature drops of the horizontal panel with different magnetic field strengths by using channel cooling,vented cavity-1 and vented cavity-2 systems for uniformmagnetic are 11℃,21.5℃,and 3℃when the reference case of Ha=0 is considered for the same cooling systems.However,they become 9.5℃,13.5℃,and 12.5℃when nonuniform magnetic field is used.In the presence of uniform magnetic field effects and changing its magnitude,the use of cooling channel in vented cavity-1 and vented cavity-2 systems results in temperature drops of 4℃,10.8℃,and 3.8℃for vertical panels.On the other hand,when non-uniform magnetic field effects are present,they become 0.5℃,2.1℃,and 9℃.For L-channel cooling,the average Nu for the horizontal panel is more affected byγ,andNu rises asγrises.With increasing nanoparticle loading of ternary nanofluid,the average panel surface temperature shows a linear drop.For the horizontal panel,the temperature declines for nanofluid at the highest loading are 4℃,10℃,and 12℃as compared to using only base fluid.The values of 5℃,7℃,and 11℃are obtained for the vertical panel.Different cooling systems’performance is estimated using artificial neural networks.The method captures the combined impact of applying non-uniformmagnetic field and nanofluid together on the cooling performancewhile accounting for varied cooling strategies for both panels.
文摘In low-light image enhancement,prevailing Retinex-based methods often struggle with precise illumina-tion estimation and brightness modulation.This can result in issues such as halo artifacts,blurred edges,and diminished details in bright regions,particularly under non-uniform illumination conditions.We propose an innovative approach that refines low-light images by leveraging an in-depth awareness of local content within the image.By introducing multi-scale effective guided filtering,our method surpasses the limitations of traditional isotropic filters,such as Gaussian filters,in handling non-uniform illumination.It dynamically adjusts regularization parameters in response to local image characteristics and significantly integrates edge perception across different scales.This balanced approach achieves a harmonious blend of smoothing and detail preservation,enabling more accurate illumination estimation.Additionally,we have designed an adaptive gamma correction function that dynamically adjusts the brightness value based on local pixel intensity,further balancing enhancement effects across different brightness levels in the image.Experimental results demonstrate the effectiveness of our proposed method for non-uniform illumination images across various scenarios.It exhibits superior quality and objective evaluation scores compared to existing methods.Our method effectively addresses potential issues that existing methods encounter when processing non-uniform illumination images,producing enhanced images with precise details and natural,vivid colors.
基金Supported by the Key R&D Program of Gansu Province(No.23YFGA0063)the Key Talent Project of Gansu Province(No.2024RCXM57,2024RCXM22)the Major Science and Technology Special Program of Gansu Province(No.25ZYJA037).
文摘Traffic flow prediction is a crucial element of intelligent transportation systems.However,accu-rate traffic flow prediction is quite challenging because of its highly nonlinear,complex,and dynam-ic characteristics.To address the difficulties in simultaneously capturing local and global dynamic spatiotemporal correlations in traffic flow,as well as the high time complexity of existing models,a multi-head flow attention-based local-global dynamic hypergraph convolution(MFA-LGDHC)pre-diction model is proposed.which consists of multi-head flow attention(MHFA)mechanism,graph convolution network(GCN),and local-global dynamic hypergraph convolution(LGHC).MHFA is utilized to extract the time dependency of traffic flow and reduce the time complexity of the model.GCN is employed to catch the spatial dependency of traffic flow.LGHC utilizes down-sampling con-volution and isometric convolution to capture the local and global spatial dependencies of traffic flow.And dynamic hypergraph convolution is used to model the dynamic higher-order relationships of the traffic road network.Experimental results indicate that the MFA-LGDHC model outperforms current popular baseline models and exhibits good prediction performance.
基金supported by the National Natural Science Foundation of China(Nos.52474133,52304227,52304091,and 52374095)the Natural Science Foundation of Hunan Province(Nos.2025JJ50316 and 2023JJ40548).
文摘To investigate the influence of non-uniform water distribution on the mechanical properties and failure behavior of red sandstone,we designed five immersion heights and durations to achieve varying non-uniform water distribution states.Uniaxial compression tests were conducted on red sandstone under these conditions.The effects of non-uniform water distribution on deformation,failure,strength,and energy characteristics of red sandstone were analyzed.The impact of non-uniform water distribution on the intensity of rock failure was discussed,and the failure mechanism under non-uniform water distribution was revealed.The hazards of low immersion heights on underground rock structures were analyzed.The results demonstrate that peak strength and elastic modulus of red sandstone exhibit high sensitivity to immersion height,with reductions of 38%and 23%respectively even at L=1/50H.Water immersion reduces both energy storage capacity and energy dissipation capability of red sandstone.The immersion height and duration influence the failure mode of red sandstone by controlling the migration and separation of dry-wet interfaces.Low immersion height poses significant risks to underground rock structures(e.g.,a 38%strength reduction when L=1/50H),and the concentration degree of water non-uniform distribution is the key factor in assessing the weakening effect of water on rocks.
基金financially supported by the National Natural Science Foundation of China(Nos.62275244,62375258,62225507,U2033211,62175230,and 62175232)the CAS Project for Young Scientists in Basic Research(No.YSBR-065)+2 种基金Scientific Instrument Developing Project of the Chinese Academy of Sciences(No.YJKYYQ20200001)National Key R&D Program of China(No.2022YFB3607800,No.2022YFB3605800,and No.2022YFB4601501)Key Program of the Chinese Academy of Sciences(ZDBS-ZRKJZ-TLC018)。
文摘The intrusion of obstacles onto railway tracks presents a significant threat to train safety,characterized by sudden and unpredictable occurrences.With China leading the world in high-speed rail mileage,ensuring railway security is paramount.The current laser monitoring technologies suffer from high false alarm rates and unreliable intrusion identification.This study addresses these issues by investigating high-resolution laser monitoring technology for railway obstacles,focusing on key parameters such as monitoring range and resolution.We propose an enhanced non-uniform laser scanning method,developing a laser monitoring system that reduces the obstacle false alarm rate to 2.00%,significantly lower than the 20%standard(TJ/GW135-2015).This rate is the best record for laser monitoring systems on China Railway.Our system operates seamlessly in all weather conditions,providing superior accuracy,resolution,and identification efficiency.It is the only 3D LiDAR system certified by the China State Railway Group Co.,Ltd.(Certificate No.[2023]008).Over three years,our system has been deployed at numerous points along various lines managed by the China State Railway Group,accumulating a dataset of 300,000 observations.This extensive deployment has significantly enhanced railway safety.The development and implementation of our railway laser monitoring system represent a substantial advancement in railway safety technology.Its low false alarm rate(2.00%),high accuracy(20 cm×20 cm×20 cm),and robust performance in diverse conditions underscore its potential for widespread adoption,promising to enhance railway safety in China and internationally.
基金Supported by the Aeronautic Science Foundation of China(2008ZC52026)the Innovation Foundation of Nanjing University of Aeronautics and Astronautics~~
文摘Array configuration of multiple-input multiple-output （MIMO） radar with non-uniform linear array （NLA） is proposed. Unlike a standard phased-array radar where NLA is used to generate thinner beam patterns, in MIMO radar the property of NLA is exploited to get more distinct virtual array elements so as to improve pa- rameter identifiability, which means the maximum number of targets that can be uniquely identified by the radar. A class of NLA called minimum redundancy linear array （MRLA） is employed and a new method to construct large MRLAs is descrihed. The numerical results verify that compared to uniform linear array （ULA） MIMO radars, NLA MIMO radars can retain the same parameter identifiability with fewer physical antennas and achieve larger aperture length and lower Cramer-Rao bound with the same number of the physical antennas.
基金Supported by the National Natural Science Foundation of China(10902051)the Natural Science Foundation of Jiangsu Province(BK2008046)~~
文摘To analyze a multibody system composed of non-uniform beam and spring-mass subsystems, the model discretization is carried on by utilizing the finite element method（FEM）, the dynamic model of non-uniform beam is developed by using the transfer matrix method of multibody system（MS-TMM）, the transfer matrix of non-u- niform beam is derived, and the natural frequencies are computed. Compared with the numerical assembly method （NAM）, the results by MS-TMM have good agreement with the results by FEM, and are better than the results by NAM. When using the high precision method, the global dynamic equations of the complex multibody system are not needed and the orders of involved system matrices are decreased greatly. For the investigation on the re- verse problem of the physical parameter identification of multibody system, MS-TMM and the optimization tech- nology based on genetic algorithms（GAs） are combined and extended. The identification problem is exchanged for an optimization problem, and it is formulated as a global minimum solution of the objective function with respect to natural frequencies of multibody system. At last, the numerical example of non-uniform beam with attach- ments is discussed, and the identification results indicate the feasibility and the effectivity of the proposed aop- proach.
