1.Introduction Artificial intelligence(AI)is committed to the realization of machine-borne intelligence.The technologies underpinning AI have made huge leaps in the past decade,bringing exciting applications such as l...1.Introduction Artificial intelligence(AI)is committed to the realization of machine-borne intelligence.The technologies underpinning AI have made huge leaps in the past decade,bringing exciting applications such as language understanding,vision recognition,and intelligent digital assistants.However,contemporary AI systems are good at specific predefined tasks and are unable to learn by themselves from data or from experience,intuitive reasoning,and adaptation.展开更多
This work elaborates a fast and robust structural health monitoring scheme for copying with aircraft structural fatigue.The type of noise in structural strain signals is determined by using a statistical analysis meth...This work elaborates a fast and robust structural health monitoring scheme for copying with aircraft structural fatigue.The type of noise in structural strain signals is determined by using a statistical analysis method,which can be regarded as a mixture of Gaussian-like(tiny hairy signals)and impulse-like noise(single signals with anomalous movements in peak and valley areas).Based on this,a least squares filtering method is employed to preprocess strain signals.To precisely eliminate noise or outliers in strain signals,we propose a novel variational model to generate step signals instead of strain ones.Expert judgments are employed to classify the generated signals.Based on the classification labels,whether the aircraft is structurally healthy is accurately judged.By taking the generated step count vectors and labels as an input,a discriminative neural network is proposed to realize automatic signal discrimination.The network output means whether the aircraft structure is healthy or not.Experimental results demonstrate that the proposed scheme is effective and efficient,as well as achieves more satisfactory results than other peers.展开更多
This paper presents an integrated study from fracture propagation modeling to gas flow modeling and a correlation analysis to explore the key controlling factors of intensive volume fracturing.The fracture propagation...This paper presents an integrated study from fracture propagation modeling to gas flow modeling and a correlation analysis to explore the key controlling factors of intensive volume fracturing.The fracture propagation model takes into account the interaction between hydraulic fracture and natural fracture by means of the displacement discontinuity method(DDM)and the Picard iterative method.The shale gas flow considers multiple transport mechanisms,and the flow in the fracture network is handled by the embedded discrete fracture model(EDFM).A series of numerical simulations are conducted to analyze the effects of the cluster number,stage spacing,stress difference coefficient,and natural fracture distribution on the stimulated fracture area,fractal dimension,and cumulative gas production,and their correlation coefficients are obtained.The results show that the most influential factors to the stimulated fracture area are the stress difference ratio,stage spacing,and natural fracture density,while those to the cumulative gas production are the stress difference ratio,natural fracture density,and cluster number.This indicates that the stress condition dominates the gas production,and employing intensive volume fracturing(by properly increasing the cluster number)is beneficial for improving the final cumulative gas production.展开更多
Based on the two-dimensional(2D)three-component first-order velocity-stress equation,the high order staggered mesh finite difference numerical simulation method was used to simulate the elastic and viscoelastic tilted...Based on the two-dimensional(2D)three-component first-order velocity-stress equation,the high order staggered mesh finite difference numerical simulation method was used to simulate the elastic and viscoelastic tilted transversely isotropic(TTI)media.The perfect matched layer(PML)absorption boundary condition was selected to eliminate the boundary effect.The results show that:(①)Under the condition of fixed elastic parameters of elastic TTI medium,when the polarization angle and azimuth are 60°and 45°respectively,the degree of shear wave splitting is significantly greater than the angle of 0°;②The influence of viscoelasticity on TTI medium is mainly reflected in the amplitude.If the quality factor decreases,the attenuation of the seismic wave amplitude increases,causing the waveform to become wider and distorted.If the quality factor increases,the viscoelastic medium becomes closer to elastic medium;③For TTI medium with different polarization angle and azimuth angle in the upper and lower layers,the shear wave can multiple splits at the interface of medium.The symmetry of seismograms is affected by the polarization angle and azimuth angle of TTI medium;④Viscoelasticity has a great influence on reflected wave,transmitted wave and converted wave in the low-velocity model.When the viscoelasticity is strong,the weaker waves may not be shown.展开更多
In this paper,the distributed stochastic model predictive control(MPC)is proposed for the noncooperative game problem of the discrete-time multi-player systems(MPSs)with the undirected Markov jump graph.To reflect the...In this paper,the distributed stochastic model predictive control(MPC)is proposed for the noncooperative game problem of the discrete-time multi-player systems(MPSs)with the undirected Markov jump graph.To reflect the reality,the state and input constraints have been considered along with the external disturbances.An iterative algorithm is designed such that model predictive noncooperative game could converge to the socalledε-Nash equilibrium in a distributed manner.Sufficient conditions are established to guarantee the convergence of the proposed algorithm.In addition,a set of easy-to-check conditions are provided to ensure the mean-square uniform bounded stability of the underlying MPSs.Finally,a numerical example on a group of spacecrafts is studied to verify the effectiveness of the proposed method.展开更多
Polarimetric dehazing is an effective way to enhance the quality of images captured in foggy weather.However,images of essential polarization parameters are vulnerable to noise,and the brightness of dehazed images is ...Polarimetric dehazing is an effective way to enhance the quality of images captured in foggy weather.However,images of essential polarization parameters are vulnerable to noise,and the brightness of dehazed images is usually unstable due to different environmental illuminations.These two weaknesses reveal that current polarimetric dehazing algorithms are not robust enough to deal with different scenarios.This paper proposes a novel,to our knowledge,and robust polarimetric dehazing algorithm to enhance the quality of hazy images,where a low-rank approximation method is used to obtain low-noise polarization parameter images.Besides,in order to improve the brightness stability of the dehazed image and thus keep the image have more details within the standard dynamic range,this study proposes a multiple virtual-exposure fusion(MVEF)scheme to process the dehazed image(usually having a high dynamic range)obtained through polarimetric dehazing.Comparative experiments show that the proposed dehazing algorithm is robust and effective,which can significantly improve overall quality of hazy images captured under different environments.展开更多
Abnormal event detection in crowded scenes is a hot topic in computer vision and information retrieval community. In this paper, we study the problems of detecting anomalous behaviors within the video, and propose a r...Abnormal event detection in crowded scenes is a hot topic in computer vision and information retrieval community. In this paper, we study the problems of detecting anomalous behaviors within the video, and propose a robust collective representation with multi-feature descriptors for abnormal event detection. The proposed method represents different features in an identical representation, in which different features of the same topic will show more common properties. Then, we build the intrinsic relation between different feature descriptors and capture concept drift in the video sequence, which can robustly discriminate between abnormal events and normal events. Experimental results on two benchmark datasets and the comparison with the state-of-the-art methods validate the effectiveness of our method.展开更多
Obtaining multi-source satellite geodesy and ocean observation data to map the high-resolution global digital elevation models(DEMs)is a formidable task at present.The key theoretical and technological obstacles to fi...Obtaining multi-source satellite geodesy and ocean observation data to map the high-resolution global digital elevation models(DEMs)is a formidable task at present.The key theoretical and technological obstacles to fine modeling must be overcome before the geographical ditribution of ocean topography and plate move-ment patterns can be explored.Geodesy.展开更多
With the incredible growth of high-dimensional data such as microarray gene expression data and web blogs from internet, the researchers are desirable to develop new clustering techniques to address the critical probl...With the incredible growth of high-dimensional data such as microarray gene expression data and web blogs from internet, the researchers are desirable to develop new clustering techniques to address the critical problem created by irrelevant dimensions. Properties of Nonnegative Matrix Factorization(NMF) as a clustering method were studied by relating its formulation to other methods such as K-means clustering. In this paper, by introducing clustering indicator constraints on NMF and incorporating manifold regularization to preserve geometric structures,we propose a novel manifold regularized NMF method that can simultaneously learn subspace and do clustering. As a result, our clustering results can directly assign cluster label to data points. Extensive experimental results show that our method outperforms related other methods.展开更多
Water-related optical imaging serves as a crucial tool and method for human beings to understand aquatic environments,develop and utilize water resources,and protect aquatic ecosystems.It offers distinct advantages su...Water-related optical imaging serves as a crucial tool and method for human beings to understand aquatic environments,develop and utilize water resources,and protect aquatic ecosystems.It offers distinct advantages such as intuitive target detection,high imaging resolution,and rich information content.However,due to the absorption and scattering properties of water,water-related optical imaging is often plagued by noise,making the acquisition of clear images a challenging task.展开更多
Water-related optical imaging constitutes a pivotal domain within the field of water-related optics and vision,furnishing essential tools for comprehending the water-related environment,harnessing water resources,and ...Water-related optical imaging constitutes a pivotal domain within the field of water-related optics and vision,furnishing essential tools for comprehending the water-related environment,harnessing water resources,and safeguarding water ecology.Its merits encompass facile target detection,elevated imaging resolution,and copious information content.Nonetheless,the formidable challenge of attaining clear images in water-related environments is challenging due to the water's absorption and scattering properties.Substantial strides have been achieved in recent years through advancements in software and hardware optical imaging and processing techniques.This review offers a comprehensive exploration of the present state of water-related optical imaging,spanning historical,theoretical,and methodological dimensions.A retrospective analysis of the historical evolution of water-related optical imaging is presented,accompanied by a detailed exposition of the operational principles and the latest noteworthy advancements in various categories of water-related optical imaging.Furthermore,a meticulous comparative analysis of these methodologies is undertaken.These approaches not only enhance water-related optical imaging efficacy but also furnish robust support for scientific inquiry and resource exploitation in water-related environments.This review enhances the comprehension of advancements in water-related optical imaging research,acting as a crucial touchpoint for future explorations and innovations.Water-related optical imaging is critical for comprehending marine ecosystems,supporting environmental conservation,and improving industry efficiency.展开更多
文摘1.Introduction Artificial intelligence(AI)is committed to the realization of machine-borne intelligence.The technologies underpinning AI have made huge leaps in the past decade,bringing exciting applications such as language understanding,vision recognition,and intelligent digital assistants.However,contemporary AI systems are good at specific predefined tasks and are unable to learn by themselves from data or from experience,intuitive reasoning,and adaptation.
文摘This work elaborates a fast and robust structural health monitoring scheme for copying with aircraft structural fatigue.The type of noise in structural strain signals is determined by using a statistical analysis method,which can be regarded as a mixture of Gaussian-like(tiny hairy signals)and impulse-like noise(single signals with anomalous movements in peak and valley areas).Based on this,a least squares filtering method is employed to preprocess strain signals.To precisely eliminate noise or outliers in strain signals,we propose a novel variational model to generate step signals instead of strain ones.Expert judgments are employed to classify the generated signals.Based on the classification labels,whether the aircraft is structurally healthy is accurately judged.By taking the generated step count vectors and labels as an input,a discriminative neural network is proposed to realize automatic signal discrimination.The network output means whether the aircraft structure is healthy or not.Experimental results demonstrate that the proposed scheme is effective and efficient,as well as achieves more satisfactory results than other peers.
基金supported by the National Natural Science Foundation of China(Nos.52274038,5203401042174143)+1 种基金the Taishan Scholars Project(No.tsqnz20221140)the Open Fund of State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation(Southwest Petroleum University)of China(No.PLN2020-5)。
文摘This paper presents an integrated study from fracture propagation modeling to gas flow modeling and a correlation analysis to explore the key controlling factors of intensive volume fracturing.The fracture propagation model takes into account the interaction between hydraulic fracture and natural fracture by means of the displacement discontinuity method(DDM)and the Picard iterative method.The shale gas flow considers multiple transport mechanisms,and the flow in the fracture network is handled by the embedded discrete fracture model(EDFM).A series of numerical simulations are conducted to analyze the effects of the cluster number,stage spacing,stress difference coefficient,and natural fracture distribution on the stimulated fracture area,fractal dimension,and cumulative gas production,and their correlation coefficients are obtained.The results show that the most influential factors to the stimulated fracture area are the stress difference ratio,stage spacing,and natural fracture density,while those to the cumulative gas production are the stress difference ratio,natural fracture density,and cluster number.This indicates that the stress condition dominates the gas production,and employing intensive volume fracturing(by properly increasing the cluster number)is beneficial for improving the final cumulative gas production.
基金the National Natural Science Foundation of China(Nos.41974048,41574078,41604039,41604102)the Guangxi Natural Science Foundation of China(Nos.2018GXNSFAA138059,2016GXNSFBA380082 and 2018GXNSFBA050005)+1 种基金Guangxi Science and Technology Base and Talent Project(Gui Kc AD19110057)Guangxi High School Junior Teachers Foundation Funding for capacity improvement projects(No.2019KY0264).
文摘Based on the two-dimensional(2D)three-component first-order velocity-stress equation,the high order staggered mesh finite difference numerical simulation method was used to simulate the elastic and viscoelastic tilted transversely isotropic(TTI)media.The perfect matched layer(PML)absorption boundary condition was selected to eliminate the boundary effect.The results show that:(①)Under the condition of fixed elastic parameters of elastic TTI medium,when the polarization angle and azimuth are 60°and 45°respectively,the degree of shear wave splitting is significantly greater than the angle of 0°;②The influence of viscoelasticity on TTI medium is mainly reflected in the amplitude.If the quality factor decreases,the attenuation of the seismic wave amplitude increases,causing the waveform to become wider and distorted.If the quality factor increases,the viscoelastic medium becomes closer to elastic medium;③For TTI medium with different polarization angle and azimuth angle in the upper and lower layers,the shear wave can multiple splits at the interface of medium.The symmetry of seismograms is affected by the polarization angle and azimuth angle of TTI medium;④Viscoelasticity has a great influence on reflected wave,transmitted wave and converted wave in the low-velocity model.When the viscoelasticity is strong,the weaker waves may not be shown.
基金This work was supported by the National Natural Science Foundation of China(62122063,62073268,U22B2036,11931015)the Young Star of Science and Technology in Shaanxi Province(2020KJXX-078)+1 种基金the National Science Fund for Distinguished Young Scholars(62025602)the XPLORER PRIZE。
文摘In this paper,the distributed stochastic model predictive control(MPC)is proposed for the noncooperative game problem of the discrete-time multi-player systems(MPSs)with the undirected Markov jump graph.To reflect the reality,the state and input constraints have been considered along with the external disturbances.An iterative algorithm is designed such that model predictive noncooperative game could converge to the socalledε-Nash equilibrium in a distributed manner.Sufficient conditions are established to guarantee the convergence of the proposed algorithm.In addition,a set of easy-to-check conditions are provided to ensure the mean-square uniform bounded stability of the underlying MPSs.Finally,a numerical example on a group of spacecrafts is studied to verify the effectiveness of the proposed method.
基金Science and Technology Development Funds of Shaanxi Province(2024QCY-KXJ-179)Natural Science Foundation of Shaanxi Province(2021JM-204,2022JQ-612)Xi'an Scientific and Technological Projects(2020KJRC0013)。
文摘Polarimetric dehazing is an effective way to enhance the quality of images captured in foggy weather.However,images of essential polarization parameters are vulnerable to noise,and the brightness of dehazed images is usually unstable due to different environmental illuminations.These two weaknesses reveal that current polarimetric dehazing algorithms are not robust enough to deal with different scenarios.This paper proposes a novel,to our knowledge,and robust polarimetric dehazing algorithm to enhance the quality of hazy images,where a low-rank approximation method is used to obtain low-noise polarization parameter images.Besides,in order to improve the brightness stability of the dehazed image and thus keep the image have more details within the standard dynamic range,this study proposes a multiple virtual-exposure fusion(MVEF)scheme to process the dehazed image(usually having a high dynamic range)obtained through polarimetric dehazing.Comparative experiments show that the proposed dehazing algorithm is robust and effective,which can significantly improve overall quality of hazy images captured under different environments.
文摘Abnormal event detection in crowded scenes is a hot topic in computer vision and information retrieval community. In this paper, we study the problems of detecting anomalous behaviors within the video, and propose a robust collective representation with multi-feature descriptors for abnormal event detection. The proposed method represents different features in an identical representation, in which different features of the same topic will show more common properties. Then, we build the intrinsic relation between different feature descriptors and capture concept drift in the video sequence, which can robustly discriminate between abnormal events and normal events. Experimental results on two benchmark datasets and the comparison with the state-of-the-art methods validate the effectiveness of our method.
基金supported by the National Key Research and Development Program of China(2020YFA0607900,2020YFA0608003,and 2021YFC3101601)the National Natural Science Foundation of China(42125503 and 42075137)the National Key Scientific and Technological Infrastructure Project‘‘Earth System Science Numerical Simulator Facility”(Earth Lab)。
文摘Obtaining multi-source satellite geodesy and ocean observation data to map the high-resolution global digital elevation models(DEMs)is a formidable task at present.The key theoretical and technological obstacles to fine modeling must be overcome before the geographical ditribution of ocean topography and plate move-ment patterns can be explored.Geodesy.
文摘With the incredible growth of high-dimensional data such as microarray gene expression data and web blogs from internet, the researchers are desirable to develop new clustering techniques to address the critical problem created by irrelevant dimensions. Properties of Nonnegative Matrix Factorization(NMF) as a clustering method were studied by relating its formulation to other methods such as K-means clustering. In this paper, by introducing clustering indicator constraints on NMF and incorporating manifold regularization to preserve geometric structures,we propose a novel manifold regularized NMF method that can simultaneously learn subspace and do clustering. As a result, our clustering results can directly assign cluster label to data points. Extensive experimental results show that our method outperforms related other methods.
文摘Water-related optical imaging serves as a crucial tool and method for human beings to understand aquatic environments,develop and utilize water resources,and protect aquatic ecosystems.It offers distinct advantages such as intuitive target detection,high imaging resolution,and rich information content.However,due to the absorption and scattering properties of water,water-related optical imaging is often plagued by noise,making the acquisition of clear images a challenging task.
基金supported by the National Key Research and Development Program of China(Grant Nos.2022YFC2808000,2022YFC2808003)Fundamental Research Funds for the Central Universities(Grant No.D5000220481)Natural Science Foundation of Shaanxi Province,China(Grant No.2024JC-YBMS-468)。
文摘Water-related optical imaging constitutes a pivotal domain within the field of water-related optics and vision,furnishing essential tools for comprehending the water-related environment,harnessing water resources,and safeguarding water ecology.Its merits encompass facile target detection,elevated imaging resolution,and copious information content.Nonetheless,the formidable challenge of attaining clear images in water-related environments is challenging due to the water's absorption and scattering properties.Substantial strides have been achieved in recent years through advancements in software and hardware optical imaging and processing techniques.This review offers a comprehensive exploration of the present state of water-related optical imaging,spanning historical,theoretical,and methodological dimensions.A retrospective analysis of the historical evolution of water-related optical imaging is presented,accompanied by a detailed exposition of the operational principles and the latest noteworthy advancements in various categories of water-related optical imaging.Furthermore,a meticulous comparative analysis of these methodologies is undertaken.These approaches not only enhance water-related optical imaging efficacy but also furnish robust support for scientific inquiry and resource exploitation in water-related environments.This review enhances the comprehension of advancements in water-related optical imaging research,acting as a crucial touchpoint for future explorations and innovations.Water-related optical imaging is critical for comprehending marine ecosystems,supporting environmental conservation,and improving industry efficiency.
