The damped Helmholtz-Duffing oscillator is a topic of great interest in many different fields of study due to its complex dynamics.By transitioning from conventional continuous differential equations to their fractal ...The damped Helmholtz-Duffing oscillator is a topic of great interest in many different fields of study due to its complex dynamics.By transitioning from conventional continuous differential equations to their fractal counterparts,one gains insights into the system's response under new mathematical frameworks.This paper presents a novel method for converting standard continuous differential equations into their fractal equivalents.This conversion occurs after the nonlinear system is transformed into its linear equivalent.Numerical analyses show that there are several resonance sites in the fractal system,which differ from the one resonance point found in the continuous system.One important finding is that the fractal system loses some of its stabilizing power when decaying behavior is transformed into a diffuse pattern.Interestingly,a decrease in the fractal order in resonance settings shows a stabilizing impact,highlighting the dynamics'complexity inside fractal systems.This endeavor to convert to fractals is a revolutionary technique that is being employed for the first time.展开更多
This paper presents a new transformer based multilevel inverter, with a novel pulse width modulation scheme to achieve seven-level inverter output voltage. The proposed inverter switching pattern consists of three fun...This paper presents a new transformer based multilevel inverter, with a novel pulse width modulation scheme to achieve seven-level inverter output voltage. The proposed inverter switching pattern consists of three fundamental frequency sinusoidal reference signals with an offset value, and one high frequency triangular carrier signal. This switching scheme has been implemented using an 8-bit Xilinx SPARTAN-3E field programmable gate array based controller. In addition, the state space model of the proposed inverter is developed. The significant features of the proposed topology are: reduction of the power switch count and the gate drive power supply unit, the provision of a galvanic isolation between load and sources by a centre tap transformer. An exhaustive comparison has been made of the existing multilevel inverter topologies and the proposed topology. The performances of the proposed topology with resistive, resistive-inductive loads are simulated in a MATLAB environment and validated experimentally on a laboratory prototype.展开更多
Long-term traffic flow prediction is a crucial component of intelligent transportation systems within intelligent networks,requiring predictive models that balance accuracy with low-latency and lightweight computation...Long-term traffic flow prediction is a crucial component of intelligent transportation systems within intelligent networks,requiring predictive models that balance accuracy with low-latency and lightweight computation to optimize trafficmanagement and enhance urban mobility and sustainability.However,traditional predictivemodels struggle to capture long-term temporal dependencies and are computationally intensive,limiting their practicality in real-time.Moreover,many approaches overlook the periodic characteristics inherent in traffic data,further impacting performance.To address these challenges,we introduce ST-MambaGCN,a State-Space-Based Spatio-Temporal Graph Convolution Network.Unlike conventionalmodels,ST-MambaGCN replaces the temporal attention layer withMamba,a state-space model that efficiently captures long-term dependencies with near-linear computational complexity.The model combines Chebyshev polynomial-based graph convolutional networks(GCN)to explore spatial correlations.Additionally,we incorporate a multi-temporal feature capture mechanism,where the final integrated features are generated through the Hadamard product based on learnable parameters.This mechanism explicitly models shortterm,daily,and weekly traffic patterns to enhance the network’s awareness of traffic periodicity.Extensive experiments on the PeMS04 and PeMS08 datasets demonstrate that ST-MambaGCN significantly outperforms existing benchmarks,offering substantial improvements in both prediction accuracy and computational efficiency for long-term traffic flow prediction.展开更多
Ship pipe route design(SPRD)is one of the most complex and timeconsuming processes in ship detail design.Currently,there are many researches on the optimization of ship pipe routes,but there is still a lack of effecti...Ship pipe route design(SPRD)is one of the most complex and timeconsuming processes in ship detail design.Currently,there are many researches on the optimization of ship pipe routes,but there is still a lack of effective and convenient methods to build the pipe routing space.In order to solve this problem,a piping space modeling method for SPRD is proposed.This method is based on stereo lithographic(STL)file which is commonly used in data exchange,and it can convert the initial space model built in 3D-CAD software into the data model required by the pipe routing algorithms.For the application purpose,a piping space modeling utility(PSMU)is developed with Python and OpenGL,promoting the development of practical pipe routing system.Finally,the feasibility and practicability of the proposed method are verified by the experiment on the piping space of an actual ship fuel system.展开更多
This paper analyzes the global competitive landscape of smartphone technological innovation capacity using the latent semantic indexing(LSI)and the vector space model(VSM).It integrates the theory of technological eco...This paper analyzes the global competitive landscape of smartphone technological innovation capacity using the latent semantic indexing(LSI)and the vector space model(VSM).It integrates the theory of technological ecological niches and evaluates four key dimensions:patent quality,energy efficiency engineering,technological modules,and intelligent computing power.The findings reveal that USA has established strong technological barriers through standard-essential patents(SEPs)in wireless communication and integrated circuits.In contrast,Chinese mainland firms rely heavily on fundamental technologies.Qualcomm Inc.in USA and Taiwan Semiconductor Manufacturing Company(TSMC)in Chineses Taiwan have built a comprehensive patent porfolio in energy efficiency engineering.While Chinese mainland faces challenges in advancing dynamic frequency modulation algorithms and high-end manufacturing processes.Huawei Inc.in Chinese mainland leads in 5G module technology but struggles with ecosystem collaboration.Semiconductor manufacturing and radio frequency(RF)components still rely on external suppliers.This highlights the urgent need for innovation in new materials and open'source architectures.To enhance intelligent computing power,Chinese mainland firms must address coordination challenges.They should adopt scenario-driven technological strategies and build a comprehensive ecosystem that includes hardware,operating systems,and developer networks.展开更多
With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-...With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-consuming and labor-intensive,but they also struggle to provide consistent,high-precision detection and realtime monitoring of pavement surface defects.To overcome these limitations,we propose an Automatic Recognition of PavementDefect(ARPD)algorithm,which leverages unmanned aerial vehicle(UAV)-based aerial imagery to automate the inspection process.The ARPD framework incorporates a backbone network based on the Selective State Space Model(S3M),which is designed to capture long-range temporal dependencies.This enables effective modeling of dynamic correlations among redundant and often repetitive structures commonly found in road imagery.Furthermore,a neck structure based on Semantics and Detail Infusion(SDI)is introduced to guide cross-scale feature fusion.The SDI module enhances the integration of low-level spatial details with high-level semantic cues,thereby improving feature expressiveness and defect localization accuracy.Experimental evaluations demonstrate that theARPDalgorithm achieves a mean average precision(mAP)of 86.1%on a custom-labeled pavement defect dataset,outperforming the state-of-the-art YOLOv11 segmentation model.The algorithm also maintains strong generalization ability on public datasets.These results confirm that ARPD is well-suited for diverse real-world applications in intelligent,large-scale highway defect monitoring and maintenance planning.展开更多
Accurately recognizing driver distraction is critical for preventing traffic accidents,yet current detection models face two persistent challenges.First,distractions are often fine-grained,involving subtle cues such a...Accurately recognizing driver distraction is critical for preventing traffic accidents,yet current detection models face two persistent challenges.First,distractions are often fine-grained,involving subtle cues such as brief eye closures or partial yawns,which are easily missed by conventional detectors.Second,in real-world scenarios,drivers frequently exhibit overlapping behaviors,such as simultaneously holding a cup,closing their eyes,and yawning,leading tomultiple detection boxes and degradedmodel performance.Existing approaches fail to robustly address these complexities,resulting in limited reliability in safety critical applications.To overcome these pain points,we propose YOLO-Drive,a novel framework that enhances YOLO-based driver monitoring with EfficientViM and Polarized Spectral–Spatial Attention(PSSA)modules.Efficient ViMprovides lightweight yet powerful global–local feature extraction,enabling accurate recognition of subtle driver states.PSSA further amplifies discriminative features across spatial and spectral domains,ensuring robust separation of concurrent distraction cues.By explicitly modeling fine-grained and overlapping behaviors,our approach delivers significant improvements in both precision and robustness.Extensive experiments on benchmark driver distraction datasets demonstrate that YOLO-Drive consistently out-performs stateof-the-art models,achieving higher detection accuracy while maintaining real-time efficiency.These results validate YOLO-Drive as a practical and reliable solution for advanced driver monitoring systems,addressing long-standing challenges of subtle cue recognition and multi-cue distraction detection.展开更多
A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information ...A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information comprehensibly.Firstly,the influencing factors of the "cause nodes" were studied,and then the pre-selection "cause nodes" procedure which utilizes the Pearson correlation coefficient to evaluate the relevancy of the traffic data was introduced.Finally,only the most relevant data were collected to compose the space time model.The experimental results with the actual data demonstrate that the model performs better than other three models.展开更多
In this paper,an analysis for ill conditioning problem in subspace identifcation method is provided.The subspace identifcation technique presents a satisfactory robustness in the parameter estimation of process model ...In this paper,an analysis for ill conditioning problem in subspace identifcation method is provided.The subspace identifcation technique presents a satisfactory robustness in the parameter estimation of process model which performs control.As a frst step,the main geometric and mathematical tools used in subspace identifcation are briefly presented.In the second step,the problem of analyzing ill-conditioning matrices in the subspace identifcation method is considered.To illustrate this situation,a simulation study of an example is introduced to show the ill-conditioning in subspace identifcation.Algorithms numerical subspace state space system identifcation(N4SID)and multivariable output error state space model identifcation(MOESP)are considered to study,the parameters estimation while using the induction motor model,in simulation(Matlab environment).Finally,we show the inadequacy of the oblique projection and validate the efectiveness of the orthogonal projection approach which is needed in ill-conditioning;a real application dealing with induction motor parameters estimation has been experimented.The obtained results proved that the algorithm based on orthogonal projection MOESP,overcomes the situation of ill-conditioning in the Hankel s block,and thereby improving the estimation of parameters.展开更多
Multistation machining process is widely applied in contemporary manufacturing environment. Modeling of variation propagation in multistation machining process is one of the most important research scenarios. Due to t...Multistation machining process is widely applied in contemporary manufacturing environment. Modeling of variation propagation in multistation machining process is one of the most important research scenarios. Due to the existence of multiple variation streams, it is challenging to model and analyze variation propagation in a multi-station system. Current approaches to error modeling for multistation machining process are not explicit enough for error control and ensuring final product quality. In this paper, a mathematic model to depict the part dimensional variation of the complex multistation manufacturing process is formulated. A linear state space dimensional error propagation equation is established through kinematics analysis of the influence of locating parameter variations and locating datum variations on dimensional errors, so the dimensional error accumulation and transformation within the multistation process are quantitatively described. A systematic procedure to build the model is presented, which enhances the way to determine the variation sources in complex machining systems. A simple two-dimensional example is used to illustrate the proposed procedures. Finally, an industrial case of multistation machining part in a manufacturing shop is given to testify the validation and practicability of the method. The proposed analytical model is essential to quality control and improvement for multistation systems in machining quality forecasting and design optimization.展开更多
Formal state space models of quantum control systems are deduced and a scheme to establish formal state space models via quantization could been obtained for quantum control systems is proposed. State evolution of qua...Formal state space models of quantum control systems are deduced and a scheme to establish formal state space models via quantization could been obtained for quantum control systems is proposed. State evolution of quantum control systems must accord with Schrdinger equations, so it is foremost to obtain Hamiltonian operators of systems. There are corresponding relations between operators of quantum systems and corresponding physical quantities of classical systems, such as momentum, energy and Hamiltonian, so Schrdinger equation models of corresponding quantum control systems via quantization could been obtained from classical control systems, and then establish formal state space models through the suitable transformation from Schrdinger equations for these quantum control systems. This method provides a new kind of path for modeling in quantum control.展开更多
The fixture layout is crucial to assure the product quality in a multistation assembly process （MAP）. A well-designed fixture layout will make the final product＇s variability be insensitive to the fixture variation...The fixture layout is crucial to assure the product quality in a multistation assembly process （MAP）. A well-designed fixture layout will make the final product＇s variability be insensitive to the fixture variation inputs. As the basis of the fixture layout design, the design criterion plays an important role in the effectiveness of a solution and the optimization efficiency. In this paper, an effective and efficient design criterion is proposed for the fixture layout with a fixed reference point （FRP） in an MAP. First of all, a state space model for the individual port＇s variation propagation and accumulation is developed, which is the mathematical foundation of the proposed criterion. Then, based on this model, a novel design criterion used to evaluate the performance of the fixture layout is proposed for the fixture layout with an FRP. Finally, a method extracted from the proposed design criterion is developed for quick fixture layout design. A four-station assembly process is used to validate the effectiveness and efficiency of the proposed models and methods.展开更多
A new analytical method is proposed to analyze the force acting on a rectangular oscillating buoy due to linear waves.In the method a new analytical expression for the diffraction velocity potential is obtained first ...A new analytical method is proposed to analyze the force acting on a rectangular oscillating buoy due to linear waves.In the method a new analytical expression for the diffraction velocity potential is obtained first by use of theeigenfunction expansion method and then the wave excitation force is calculated by use of the known incident wavepotential and the diffraction potential. Compared with the classical analytical method, it can be seen that the presentmethod is simpler for a two-dimensional problem due to the comparable effort needed for the computation ofdiffraction potential and for that of radiated potential. To verify the correctness of the method, a classical example inthe reference is recomputed and the obtained results are in good accordance with those by use of other methods,which shows that the present method is correct.展开更多
To overcome the drawbacks of current modelling method for aircraft engine state space model,a new method is introduced.The form of state space model is derived by using Talyor series to expand the nonlinear model that...To overcome the drawbacks of current modelling method for aircraft engine state space model,a new method is introduced.The form of state space model is derived by using Talyor series to expand the nonlinear model that is implicit equations and involves many iterations.A partial derivative calculation method for iterations is developed to handle the influence of iterations on parameters.The derivative calculation and the aerothermodynamics calculations are combined in the component level model with fixed number Newton-Raphson(N-R)iterations.Mathematical derivation and simulations show the convergence ability of proposed method.Simulations show that comparing with the linear parameter varying model and centered difference based state space model,much higher accuracy of proposed online modelling method is achieved.The accuracy of the state space model built by proposed method can be maintained when the step amplitudes of inputs are within 2%,and the responses of the state space model can match those of the component level model when each input steps larger amplitudes.In addition,an online verification was carried out to show the capability of modelling at any operating point and that state space model can predict future outputs accurately.Thus,the effectiveness of the proposed method is demonstrated.展开更多
This paper deals with a state model identification of a gas turbine used for gas transport, using a subspace approach of the state space model. This method provides a reliable and robust state representation of the mo...This paper deals with a state model identification of a gas turbine used for gas transport, using a subspace approach of the state space model. This method provides a reliable and robust state representation of the model, taking advantage of its benefits in the control, monitoring, and supervision of this machine. The model for each variable is set so that the state matrices associated with the gas turbine model are determined from their real input/output data. The comparison of the obtained identification results with those of the actual turbine operation serves to validate the proposed model in this work. This numerical algorithm of the subspace identification method is full of information and more accurate in terms of residual modeling error, and expresses a very high level of confidence in the identified turbine system dynamics. Hence, the controllability and observability tests of turbine operation for different input/output variables allowed to validate the real-time operating stability of the turbine.展开更多
Reliability analysis based on equipment's performance degradation characteristics is one of the significant research areas in reliability research. Nowadays, many researches are carried on multi-sample analysis. B...Reliability analysis based on equipment's performance degradation characteristics is one of the significant research areas in reliability research. Nowadays, many researches are carried on multi-sample analysis. But it is limited for a single equipment reliability prediction. Therefore, the method of reliability prediction based on state space model(SSM) is proposed in this research. Feature energy of the monitored signals is extracted with the wavelet packet analysis and the associated frequency band energy with online monitored data. Then,degradation feature is improved by moving average filtering processing taken as input pair model parameter of SSM to be estimated. In the end, state space predicting model of degradation index is established. The probability density distribution of the degradation index is predicted, and the degree of reliability is calculated. A real testing example of bearing is used to demonstrate the rationality and effectiveness of this method. It is a useful method for single sample reliability prediction.展开更多
A state space model(SSM) is derived for quantum-dot semiconductor optical amplifiers(QD-SOAs).Rate equations of QD-SOA are formulated in the form of state update equations,where average occupation probabilities along ...A state space model(SSM) is derived for quantum-dot semiconductor optical amplifiers(QD-SOAs).Rate equations of QD-SOA are formulated in the form of state update equations,where average occupation probabilities along QD-SOA cavity are considered as state variables of the system.Simulations show that SSM calculates QD-SOA′s static and dynamic characteristics with high accuracy.展开更多
Dimensional control is one of the most important challenges in the shipbuilding industry. In order to predict assembly dimensional variation in hull flat block construction, a variation stream model based on state spa...Dimensional control is one of the most important challenges in the shipbuilding industry. In order to predict assembly dimensional variation in hull flat block construction, a variation stream model based on state space was presented in this paper which can be further applied to accuracy control in shipbuilding. Part accumulative error, locating error, and welding deformation were taken into consideration in this model, and variation propagation mechanisms and the accumulative rule in the assembly process were analyzed. Then, a model was developed to describe the variation propagation throughout the assembly process. Finally, an example of fiat block construction from an actual shipyard was given. The result shows that this method is effective and useful.展开更多
Granular computing is a very hot research field in recent years. In our previous work an algebraic quotient space model was proposed,where the quotient structure could not be deduced if the granulation was based on an...Granular computing is a very hot research field in recent years. In our previous work an algebraic quotient space model was proposed,where the quotient structure could not be deduced if the granulation was based on an equivalence relation. In this paper,definitions were given and formulas of the lower quotient congruence and upper quotient congruence were calculated to roughly represent the quotient structure. Then the accuracy and roughness were defined to measure the quotient structure in quantification. Finally,a numerical example was given to demonstrate that the rough representation and measuring methods are efficient and applicable. The work has greatly enriched the algebraic quotient space model and granular computing theory.展开更多
This paper studies the problem of the space station short-term mission planning, which aims to allocate the executing time of missions effectively, schedule the corresponding resources reasonably and arrange the time ...This paper studies the problem of the space station short-term mission planning, which aims to allocate the executing time of missions effectively, schedule the corresponding resources reasonably and arrange the time of the astronauts properly. A domain model is developed by using the ontology theory to describe the concepts, constraints and relations of the planning domain formally, abstractly and normatively. A method based on time iteration is adopted to solve the short-term planning problem. Meanwhile, the resolving strategies are proposed to resolve different kinds of conflicts induced by the constraints of power, heat, resource, astronaut and relationship. The proposed approach is evaluated in a test case with fifteen missions, thirteen resources and three astronauts. The results show that the developed domain ontology model is reasonable, and the time iteration method using the proposed resolving strategies can successfully obtain the plan satisfying all considered constraints.展开更多
文摘The damped Helmholtz-Duffing oscillator is a topic of great interest in many different fields of study due to its complex dynamics.By transitioning from conventional continuous differential equations to their fractal counterparts,one gains insights into the system's response under new mathematical frameworks.This paper presents a novel method for converting standard continuous differential equations into their fractal equivalents.This conversion occurs after the nonlinear system is transformed into its linear equivalent.Numerical analyses show that there are several resonance sites in the fractal system,which differ from the one resonance point found in the continuous system.One important finding is that the fractal system loses some of its stabilizing power when decaying behavior is transformed into a diffuse pattern.Interestingly,a decrease in the fractal order in resonance settings shows a stabilizing impact,highlighting the dynamics'complexity inside fractal systems.This endeavor to convert to fractals is a revolutionary technique that is being employed for the first time.
文摘This paper presents a new transformer based multilevel inverter, with a novel pulse width modulation scheme to achieve seven-level inverter output voltage. The proposed inverter switching pattern consists of three fundamental frequency sinusoidal reference signals with an offset value, and one high frequency triangular carrier signal. This switching scheme has been implemented using an 8-bit Xilinx SPARTAN-3E field programmable gate array based controller. In addition, the state space model of the proposed inverter is developed. The significant features of the proposed topology are: reduction of the power switch count and the gate drive power supply unit, the provision of a galvanic isolation between load and sources by a centre tap transformer. An exhaustive comparison has been made of the existing multilevel inverter topologies and the proposed topology. The performances of the proposed topology with resistive, resistive-inductive loads are simulated in a MATLAB environment and validated experimentally on a laboratory prototype.
基金supported byNationalNatural Science Foundation of China,GrantNo.62402046the Beijing Forestry University Science and Technology Innovation Project under Grant No.BLX202358.
文摘Long-term traffic flow prediction is a crucial component of intelligent transportation systems within intelligent networks,requiring predictive models that balance accuracy with low-latency and lightweight computation to optimize trafficmanagement and enhance urban mobility and sustainability.However,traditional predictivemodels struggle to capture long-term temporal dependencies and are computationally intensive,limiting their practicality in real-time.Moreover,many approaches overlook the periodic characteristics inherent in traffic data,further impacting performance.To address these challenges,we introduce ST-MambaGCN,a State-Space-Based Spatio-Temporal Graph Convolution Network.Unlike conventionalmodels,ST-MambaGCN replaces the temporal attention layer withMamba,a state-space model that efficiently captures long-term dependencies with near-linear computational complexity.The model combines Chebyshev polynomial-based graph convolutional networks(GCN)to explore spatial correlations.Additionally,we incorporate a multi-temporal feature capture mechanism,where the final integrated features are generated through the Hadamard product based on learnable parameters.This mechanism explicitly models shortterm,daily,and weekly traffic patterns to enhance the network’s awareness of traffic periodicity.Extensive experiments on the PeMS04 and PeMS08 datasets demonstrate that ST-MambaGCN significantly outperforms existing benchmarks,offering substantial improvements in both prediction accuracy and computational efficiency for long-term traffic flow prediction.
基金the Doctoral Scientific Research Foundation ofLiaoning Province(Grant No.2019-BS-061)the Basic Research Foundation of EducationDepartment of Liaoning Province(Grant No.2019-JYT-07).
文摘Ship pipe route design(SPRD)is one of the most complex and timeconsuming processes in ship detail design.Currently,there are many researches on the optimization of ship pipe routes,but there is still a lack of effective and convenient methods to build the pipe routing space.In order to solve this problem,a piping space modeling method for SPRD is proposed.This method is based on stereo lithographic(STL)file which is commonly used in data exchange,and it can convert the initial space model built in 3D-CAD software into the data model required by the pipe routing algorithms.For the application purpose,a piping space modeling utility(PSMU)is developed with Python and OpenGL,promoting the development of practical pipe routing system.Finally,the feasibility and practicability of the proposed method are verified by the experiment on the piping space of an actual ship fuel system.
基金supported in part by the National Social Science Foundation of China(No.20BGL203).
文摘This paper analyzes the global competitive landscape of smartphone technological innovation capacity using the latent semantic indexing(LSI)and the vector space model(VSM).It integrates the theory of technological ecological niches and evaluates four key dimensions:patent quality,energy efficiency engineering,technological modules,and intelligent computing power.The findings reveal that USA has established strong technological barriers through standard-essential patents(SEPs)in wireless communication and integrated circuits.In contrast,Chinese mainland firms rely heavily on fundamental technologies.Qualcomm Inc.in USA and Taiwan Semiconductor Manufacturing Company(TSMC)in Chineses Taiwan have built a comprehensive patent porfolio in energy efficiency engineering.While Chinese mainland faces challenges in advancing dynamic frequency modulation algorithms and high-end manufacturing processes.Huawei Inc.in Chinese mainland leads in 5G module technology but struggles with ecosystem collaboration.Semiconductor manufacturing and radio frequency(RF)components still rely on external suppliers.This highlights the urgent need for innovation in new materials and open'source architectures.To enhance intelligent computing power,Chinese mainland firms must address coordination challenges.They should adopt scenario-driven technological strategies and build a comprehensive ecosystem that includes hardware,operating systems,and developer networks.
基金supported in part by the Technical Service for the Development and Application of an Intelligent Visual Management Platformfor Expressway Construction Progress Based on BIM Technology(grant NO.JKYZLX-2023-09)in partby the Technical Service for the Development of an Early Warning Model in the Research and Application of Key Technologies for Tunnel Operation Safety Monitoring and Early Warning Based on Digital Twin(grant NO.JK-S02-ZNGS-202412-JISHU-FA-0035)sponsored by Yunnan Transportation Science Research Institute Co.,Ltd.
文摘With the rapid development of transportation infrastructure,ensuring road safety through timely and accurate highway inspection has become increasingly critical.Traditional manual inspection methods are not only time-consuming and labor-intensive,but they also struggle to provide consistent,high-precision detection and realtime monitoring of pavement surface defects.To overcome these limitations,we propose an Automatic Recognition of PavementDefect(ARPD)algorithm,which leverages unmanned aerial vehicle(UAV)-based aerial imagery to automate the inspection process.The ARPD framework incorporates a backbone network based on the Selective State Space Model(S3M),which is designed to capture long-range temporal dependencies.This enables effective modeling of dynamic correlations among redundant and often repetitive structures commonly found in road imagery.Furthermore,a neck structure based on Semantics and Detail Infusion(SDI)is introduced to guide cross-scale feature fusion.The SDI module enhances the integration of low-level spatial details with high-level semantic cues,thereby improving feature expressiveness and defect localization accuracy.Experimental evaluations demonstrate that theARPDalgorithm achieves a mean average precision(mAP)of 86.1%on a custom-labeled pavement defect dataset,outperforming the state-of-the-art YOLOv11 segmentation model.The algorithm also maintains strong generalization ability on public datasets.These results confirm that ARPD is well-suited for diverse real-world applications in intelligent,large-scale highway defect monitoring and maintenance planning.
基金funded by the Guangzhou Development Zone Science and Technology Project(2023GH02)the University of Macao(MYRG2022-00271-FST)research grants by the Science and Technology Development Fund of Macao(0032/2022/A)and(0019/2025/RIB1).
文摘Accurately recognizing driver distraction is critical for preventing traffic accidents,yet current detection models face two persistent challenges.First,distractions are often fine-grained,involving subtle cues such as brief eye closures or partial yawns,which are easily missed by conventional detectors.Second,in real-world scenarios,drivers frequently exhibit overlapping behaviors,such as simultaneously holding a cup,closing their eyes,and yawning,leading tomultiple detection boxes and degradedmodel performance.Existing approaches fail to robustly address these complexities,resulting in limited reliability in safety critical applications.To overcome these pain points,we propose YOLO-Drive,a novel framework that enhances YOLO-based driver monitoring with EfficientViM and Polarized Spectral–Spatial Attention(PSSA)modules.Efficient ViMprovides lightweight yet powerful global–local feature extraction,enabling accurate recognition of subtle driver states.PSSA further amplifies discriminative features across spatial and spectral domains,ensuring robust separation of concurrent distraction cues.By explicitly modeling fine-grained and overlapping behaviors,our approach delivers significant improvements in both precision and robustness.Extensive experiments on benchmark driver distraction datasets demonstrate that YOLO-Drive consistently out-performs stateof-the-art models,achieving higher detection accuracy while maintaining real-time efficiency.These results validate YOLO-Drive as a practical and reliable solution for advanced driver monitoring systems,addressing long-standing challenges of subtle cue recognition and multi-cue distraction detection.
基金Project(D101106049710005) supported by the Beijing Science Foundation Program,ChinaProject(61104164) supported by the National Natural Science Foundation,China
文摘A pre-selection space time model was proposed to estimate the traffic condition at poor-data-detector,especially non-detector locations.The space time model is better to integrate the spatial and temporal information comprehensibly.Firstly,the influencing factors of the "cause nodes" were studied,and then the pre-selection "cause nodes" procedure which utilizes the Pearson correlation coefficient to evaluate the relevancy of the traffic data was introduced.Finally,only the most relevant data were collected to compose the space time model.The experimental results with the actual data demonstrate that the model performs better than other three models.
基金supported by the Ministry of Higher Education and Scientific Research of Tunisia
文摘In this paper,an analysis for ill conditioning problem in subspace identifcation method is provided.The subspace identifcation technique presents a satisfactory robustness in the parameter estimation of process model which performs control.As a frst step,the main geometric and mathematical tools used in subspace identifcation are briefly presented.In the second step,the problem of analyzing ill-conditioning matrices in the subspace identifcation method is considered.To illustrate this situation,a simulation study of an example is introduced to show the ill-conditioning in subspace identifcation.Algorithms numerical subspace state space system identifcation(N4SID)and multivariable output error state space model identifcation(MOESP)are considered to study,the parameters estimation while using the induction motor model,in simulation(Matlab environment).Finally,we show the inadequacy of the oblique projection and validate the efectiveness of the orthogonal projection approach which is needed in ill-conditioning;a real application dealing with induction motor parameters estimation has been experimented.The obtained results proved that the algorithm based on orthogonal projection MOESP,overcomes the situation of ill-conditioning in the Hankel s block,and thereby improving the estimation of parameters.
基金supported by National Department Fundamental Research Foundation of China (Grant No. B222090014)National Department Technology Fundatmental Foundaiton of China (Grant No. C172009C001)
文摘Multistation machining process is widely applied in contemporary manufacturing environment. Modeling of variation propagation in multistation machining process is one of the most important research scenarios. Due to the existence of multiple variation streams, it is challenging to model and analyze variation propagation in a multi-station system. Current approaches to error modeling for multistation machining process are not explicit enough for error control and ensuring final product quality. In this paper, a mathematic model to depict the part dimensional variation of the complex multistation manufacturing process is formulated. A linear state space dimensional error propagation equation is established through kinematics analysis of the influence of locating parameter variations and locating datum variations on dimensional errors, so the dimensional error accumulation and transformation within the multistation process are quantitatively described. A systematic procedure to build the model is presented, which enhances the way to determine the variation sources in complex machining systems. A simple two-dimensional example is used to illustrate the proposed procedures. Finally, an industrial case of multistation machining part in a manufacturing shop is given to testify the validation and practicability of the method. The proposed analytical model is essential to quality control and improvement for multistation systems in machining quality forecasting and design optimization.
文摘Formal state space models of quantum control systems are deduced and a scheme to establish formal state space models via quantization could been obtained for quantum control systems is proposed. State evolution of quantum control systems must accord with Schrdinger equations, so it is foremost to obtain Hamiltonian operators of systems. There are corresponding relations between operators of quantum systems and corresponding physical quantities of classical systems, such as momentum, energy and Hamiltonian, so Schrdinger equation models of corresponding quantum control systems via quantization could been obtained from classical control systems, and then establish formal state space models through the suitable transformation from Schrdinger equations for these quantum control systems. This method provides a new kind of path for modeling in quantum control.
基金National Nature Science Foundation of China(No.71201025)Specialized Research Fund for the Doctoral Program of Higher Education,China(No.20110092120007)Jiangsu Key Laboratory of Equipments Detection and Control,China(No.JSKLEDC201215)
文摘The fixture layout is crucial to assure the product quality in a multistation assembly process （MAP）. A well-designed fixture layout will make the final product＇s variability be insensitive to the fixture variation inputs. As the basis of the fixture layout design, the design criterion plays an important role in the effectiveness of a solution and the optimization efficiency. In this paper, an effective and efficient design criterion is proposed for the fixture layout with a fixed reference point （FRP） in an MAP. First of all, a state space model for the individual port＇s variation propagation and accumulation is developed, which is the mathematical foundation of the proposed criterion. Then, based on this model, a novel design criterion used to evaluate the performance of the fixture layout is proposed for the fixture layout with an FRP. Finally, a method extracted from the proposed design criterion is developed for quick fixture layout design. A four-station assembly process is used to validate the effectiveness and efficiency of the proposed models and methods.
基金This work Was supported by the High Tech Research and Development(863)Program of China under Grant No.2003AA5 16010the Chinese Academy of Science Pilot Project of the National Knowledge Innovation Program under Grant No.KGCX2-SW-305Chinese National Science Fund for Distinguished Young Scholars under Grant No.50125924.
文摘A new analytical method is proposed to analyze the force acting on a rectangular oscillating buoy due to linear waves.In the method a new analytical expression for the diffraction velocity potential is obtained first by use of theeigenfunction expansion method and then the wave excitation force is calculated by use of the known incident wavepotential and the diffraction potential. Compared with the classical analytical method, it can be seen that the presentmethod is simpler for a two-dimensional problem due to the comparable effort needed for the computation ofdiffraction potential and for that of radiated potential. To verify the correctness of the method, a classical example inthe reference is recomputed and the obtained results are in good accordance with those by use of other methods,which shows that the present method is correct.
基金supported by the Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(No.KYCX180315)。
文摘To overcome the drawbacks of current modelling method for aircraft engine state space model,a new method is introduced.The form of state space model is derived by using Talyor series to expand the nonlinear model that is implicit equations and involves many iterations.A partial derivative calculation method for iterations is developed to handle the influence of iterations on parameters.The derivative calculation and the aerothermodynamics calculations are combined in the component level model with fixed number Newton-Raphson(N-R)iterations.Mathematical derivation and simulations show the convergence ability of proposed method.Simulations show that comparing with the linear parameter varying model and centered difference based state space model,much higher accuracy of proposed online modelling method is achieved.The accuracy of the state space model built by proposed method can be maintained when the step amplitudes of inputs are within 2%,and the responses of the state space model can match those of the component level model when each input steps larger amplitudes.In addition,an online verification was carried out to show the capability of modelling at any operating point and that state space model can predict future outputs accurately.Thus,the effectiveness of the proposed method is demonstrated.
文摘This paper deals with a state model identification of a gas turbine used for gas transport, using a subspace approach of the state space model. This method provides a reliable and robust state representation of the model, taking advantage of its benefits in the control, monitoring, and supervision of this machine. The model for each variable is set so that the state matrices associated with the gas turbine model are determined from their real input/output data. The comparison of the obtained identification results with those of the actual turbine operation serves to validate the proposed model in this work. This numerical algorithm of the subspace identification method is full of information and more accurate in terms of residual modeling error, and expresses a very high level of confidence in the identified turbine system dynamics. Hence, the controllability and observability tests of turbine operation for different input/output variables allowed to validate the real-time operating stability of the turbine.
基金the National Science and Technology Major Project of China(No.2013ZX04012071)the National Natural Science Foundation of China(No.51175057)
文摘Reliability analysis based on equipment's performance degradation characteristics is one of the significant research areas in reliability research. Nowadays, many researches are carried on multi-sample analysis. But it is limited for a single equipment reliability prediction. Therefore, the method of reliability prediction based on state space model(SSM) is proposed in this research. Feature energy of the monitored signals is extracted with the wavelet packet analysis and the associated frequency band energy with online monitored data. Then,degradation feature is improved by moving average filtering processing taken as input pair model parameter of SSM to be estimated. In the end, state space predicting model of degradation index is established. The probability density distribution of the degradation index is predicted, and the degree of reliability is calculated. A real testing example of bearing is used to demonstrate the rationality and effectiveness of this method. It is a useful method for single sample reliability prediction.
文摘A state space model(SSM) is derived for quantum-dot semiconductor optical amplifiers(QD-SOAs).Rate equations of QD-SOA are formulated in the form of state update equations,where average occupation probabilities along QD-SOA cavity are considered as state variables of the system.Simulations show that SSM calculates QD-SOA′s static and dynamic characteristics with high accuracy.
基金Supported by the National Science Foundation of China （Granted No.70872076） and Science Innovation Action Planning of Shanghai 2011 （No.11dz1121803）.
文摘Dimensional control is one of the most important challenges in the shipbuilding industry. In order to predict assembly dimensional variation in hull flat block construction, a variation stream model based on state space was presented in this paper which can be further applied to accuracy control in shipbuilding. Part accumulative error, locating error, and welding deformation were taken into consideration in this model, and variation propagation mechanisms and the accumulative rule in the assembly process were analyzed. Then, a model was developed to describe the variation propagation throughout the assembly process. Finally, an example of fiat block construction from an actual shipyard was given. The result shows that this method is effective and useful.
基金Supported by the National Natural Science Foundation of China(No.61772031)the Special Energy Saving Foundation of Changsha,Hunan Province in 2017
文摘Granular computing is a very hot research field in recent years. In our previous work an algebraic quotient space model was proposed,where the quotient structure could not be deduced if the granulation was based on an equivalence relation. In this paper,definitions were given and formulas of the lower quotient congruence and upper quotient congruence were calculated to roughly represent the quotient structure. Then the accuracy and roughness were defined to measure the quotient structure in quantification. Finally,a numerical example was given to demonstrate that the rough representation and measuring methods are efficient and applicable. The work has greatly enriched the algebraic quotient space model and granular computing theory.
基金supported by the National Natural Science Foundation of China(11402295)the Science Project of National University of Defense Technology(JC14-01-05)the Hunan Provincial Natural Science Foundation of China(2015JJ3020)
文摘This paper studies the problem of the space station short-term mission planning, which aims to allocate the executing time of missions effectively, schedule the corresponding resources reasonably and arrange the time of the astronauts properly. A domain model is developed by using the ontology theory to describe the concepts, constraints and relations of the planning domain formally, abstractly and normatively. A method based on time iteration is adopted to solve the short-term planning problem. Meanwhile, the resolving strategies are proposed to resolve different kinds of conflicts induced by the constraints of power, heat, resource, astronaut and relationship. The proposed approach is evaluated in a test case with fifteen missions, thirteen resources and three astronauts. The results show that the developed domain ontology model is reasonable, and the time iteration method using the proposed resolving strategies can successfully obtain the plan satisfying all considered constraints.
