In order to solve the model update problem in mean-shift based tracker, a novel mechanism is proposed. Kalman filter is employed to update object model by filtering object kernel-histogram using previous model and cur...In order to solve the model update problem in mean-shift based tracker, a novel mechanism is proposed. Kalman filter is employed to update object model by filtering object kernel-histogram using previous model and current candidate. A self-tuning method is used for adaptively adjust all the parameters of the filters under the analysis of the filtering residuals. In addition, hypothesis testing servers as the criterion for determining whether to accept filtering result. Therefore, the tracker has the ability to handle occlusion so as to avoid over-update. The experimental results show that our method can not only keep up with the object appearance and scale changes but also be robust to occlusion.展开更多
To combat packet loss and realize robust video transmission over Intemet and wireless networks, a new multiple description （MD） video coding method is proposed. In the method, two descriptions for each video frame i...To combat packet loss and realize robust video transmission over Intemet and wireless networks, a new multiple description （MD） video coding method is proposed. In the method, two descriptions for each video frame is first created by group of blocks （GOB） alternation. Motion information is then duplicated in both the descriptions and a process called low quality macroblock update is designed to redundantly encode textures in each frame using standard bit stream syntax. In this way, the output bit streams are standard compliant and better trade-offs between redundancy and single charmel reconstruction distortion are achieved. The proposed method has much better performance than the well-known MD transform coding （MDTC） method both in terms of redundancy rate distortion, and in the packet loss scenario.展开更多
As a crucial process in the coordinated strikes of unmanned aerial vehicles(UAVs), weapon-target assignment is vital for optimizing the allocation of available weapons and effectively exploiting the capabilities of UA...As a crucial process in the coordinated strikes of unmanned aerial vehicles(UAVs), weapon-target assignment is vital for optimizing the allocation of available weapons and effectively exploiting the capabilities of UAVs. Existing weapon-target assignment methods primarily focus on macro cluster constraints while neglecting individual strategy updates. This paper proposes a novel weapon-target assignment method for UAVs based on the multi-strategy threshold public goods game(PGG). By analyzing the concept mapping between weapon-target assignment for UAVs and multi-strategy threshold PGG, a weapon-target assignment model for UAVs based on the multi-strategy threshold PGG is established, which is adaptively complemented by the diverse cooperation-defection strategy library and the utility function based on the threshold mechanism. Additionally, a multi-chain Markov is formulated to quantitatively describe the stochastic evolutionary dynamics, whose evolutionary stable distribution is theoretically derived through the development of a strategy update rule based on preference-based aspiration dynamic. Numerical simulation results validate the feasibility and effectiveness of the proposed method, and the impacts of selection intensity, preference degree and threshold on the evolutionary stable distribution are analyzed. Comparative simulations show that the proposed method outperforms GWO, DE, and NSGA-II, achieving 17.18% higher expected utility than NSGA-II and reducing evolutionary stable times by 25% in large-scale scenario.展开更多
Nowadays,wireless communication devices turn out to be transportable owing to the execution of the current technologies.The antenna is the most important component deployed for communication purposes.The antenna plays...Nowadays,wireless communication devices turn out to be transportable owing to the execution of the current technologies.The antenna is the most important component deployed for communication purposes.The antenna plays an imperative role in receiving and transmitting the signals for any sensor network.Among varied antennas,micro strip fractal antenna(MFA)significantly contributes to increasing antenna gain.This study employs a hybrid optimization method known as the elephant clan updated grey wolf algorithm to introduce an optimized MFA design.This method optimizes antenna characteristics,including directivity and gain.Here,the factors,including length,width,ground plane length,height,and feed offset-X and feed offset-Y,are taken into account to achieve the best performance of gain and directivity.Ultimately,the superiority of the suggested technique over state-of-the-art strategies is calculated for various metrics such as cost and gain.The adopted model converges to a minimal value of 0.2872.Further,the spider monkey optimization(SMO)model accomplishes the worst performance over all other existing models like elephant herding optimization(EHO),grey wolf optimization(GWO),lion algorithm(LA),support vector regressor(SVR),bacterial foraging-particle swarm optimization(BF-PSO)and shark smell optimization(SSO).Effective MFA design is obtained using the suggested strategy regarding various parameters.展开更多
The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time perfor...The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time performance.However,the intricate and unpredictable pedestrian motion patterns lead the INS localization error to significantly diverge with time.This paper aims to enhance the accuracy of zero-velocity interval(ZVI)detection and reduce the heading and altitude drift of foot-mounted INS via deep learning and equation constraint of dual feet.Aiming at the observational noise problem of low-cost inertial sensors,we utilize a denoising autoencoder to automatically eliminate the inherent noise.Aiming at the problem that inaccurate detection of the ZVI detection results in obvious displacement error,we propose a sample-level ZVI detection algorithm based on the U-Net neural network,which effectively solves the problem of mislabeling caused by sliding windows.Aiming at the problem that Zero-Velocity Update(ZUPT)cannot suppress heading and altitude error,we propose a bipedal INS method based on the equation constraint and ellipsoid constraint,which uses foot-to-foot distance as a new observation to correct heading and altitude error.We conduct extensive and well-designed experiments to evaluate the performance of the proposed method.The experimental results indicate that the position error of our proposed method did not exceed 0.83% of the total traveled distance.展开更多
Tracking the fast-moving object in occlusion situations is an important research topic in computer vision. Despite numerous notable contributions have been made in this field,few of them simultaneously incorporate bot...Tracking the fast-moving object in occlusion situations is an important research topic in computer vision. Despite numerous notable contributions have been made in this field,few of them simultaneously incorporate both object's extrinsic features and intrinsic motion patterns into their methodologies,thereby restricting the potential for tracking accuracy improvement. In this paper, on the basis of efficient convolution operators(ECO) model, a speed-accuracy-balanced model is put forward. This model uses the simple correlation filter to track the object in real-time, and adopts the sophisticated deep-learning neural network to extract high-level features to train a more complex filter correcting the tracking mistakes, when the tracking state is judged to be poor. Furthermore, in the context of scenarios involving regular fast-moving, a motion model based on Kalman filter is designed which greatly promotes the tracking stability, because this motion model could predict the object's future location from its previous movement pattern. Additionally,instead of periodically updating our tracking model and training samples, a constrained condition for updating is proposed,which effectively mitigates contamination to the tracker from the background and undesirable samples avoiding model degradation when occlusion happens. From comprehensive experiments, our tracking model obtains better performance than ECO on object tracking benchmark 2015(OTB100), and improves the area under curve(AUC) by about 8% and 32% compared with ECO, in the scenarios of fast-moving and occlusion on our own collected dataset.展开更多
To determine compositions,homogenization pressures and isopleths of CO2-H2O-NaCl fluid inclusions,an improved activity-fugacity model is developed to calculate CO2solubility in aqueous NaCl solutions.The model can pre...To determine compositions,homogenization pressures and isopleths of CO2-H2O-NaCl fluid inclusions,an improved activity-fugacity model is developed to calculate CO2solubility in aqueous NaCl solutions.The model can predict the solubility of CO2in aqueous NaCl solutions from 273 K to 723 K,from1 bar to 1500 bar and from 0 to 4.5 mol kg-1of NaCl,within or close to experimental uncertainties.The average deviation between the solubility predicted展开更多
In order to study the sliding characteristics when the cable is connected with the other rods in the transmission line structures,a linear sliding cable element based on updated Lagrangian formulation and a sliding ca...In order to study the sliding characteristics when the cable is connected with the other rods in the transmission line structures,a linear sliding cable element based on updated Lagrangian formulation and a sliding catenary element considering the out-of-plane stiffness coefficient are put forward.A two-span and a three-span cable structures are taken as examples to verify the sliding cable elements.By comparing the tensions of the two proposed cable elements with the existing research results,the error is less than 1%,which proves the correctness of the proposed elements.The sliding characteristics should be considered in the practical engineering because of the significant difference between the tensions of sliding cable elements and those of cable element without considering sliding.The out-of-plane stiffness coefficient and friction characteristics do not obviously affect the cable tensions.展开更多
Foot-mounted pedestrian navigation system(PNS)is a common solution to pedestrian navigation using micro-electro mechanical system(MEMS)inertial sensors.The inherent problems of inertial navigation system(INS)by the tr...Foot-mounted pedestrian navigation system(PNS)is a common solution to pedestrian navigation using micro-electro mechanical system(MEMS)inertial sensors.The inherent problems of inertial navigation system(INS)by the traditional algorithm,such as the accumulated errors and the lack of observation of heading and altitude information,have become obstacles to the application and development of the PNS.In this paper,we introduce a heuristic heading constraint method.First of all,according to the movement characteristics of human gait,we use the generalized likelihood ratio test(GLRT)detector and introduce a time threshold to classify the human gait,so that we can effectively identify the stationary state of the foot.In addition,based on zero velocity update(ZUPT)and zero angular rate update(ZARU),the cumulative error of the inertial measurement unit(IMU)is limited and corrected,and then a heuristic heading estimation is used to constrain and correct the heading of the pedestrian.After simulation and experiments with low-cost IMU,the method is proved to reduce the localization error of end-point to less than 1%of the total distance,and it has great value in application.展开更多
The decomposition based approach decomposes a multi-objective problem into a series of single objective subproblems, which are optimized along contours towards the ideal point. But non-dominated solutions cannot sprea...The decomposition based approach decomposes a multi-objective problem into a series of single objective subproblems, which are optimized along contours towards the ideal point. But non-dominated solutions cannot spread uniformly, since the Pareto front shows different features, such as concave and convex. To improve the distribution uniformity of non-dominated solutions, a bidirectional decomposition based approach that constructs two search directions is proposed to provide a uniform distribution no matter what features problems have. Since two populations along two search directions show differently on diversity and convergence, an adaptive neighborhood selection approach is presented to choose suitable parents for the offspring generation. In order to avoid the problem of the shrinking search region caused by the close distance of the ideal and nadir points, a reference point update approach is presented. The performance of the proposed algorithm is validated with four state-of-the-art algorithms. Experimental results demonstrate the superiority of the proposed algorithm on all considered test problems.展开更多
An adaptive controller of full state feedback for certain cascade nonlinear systems achieving input-to-state stability with respect to unknown bounded disturbance is designed using backstepping and control Lyapunov fu...An adaptive controller of full state feedback for certain cascade nonlinear systems achieving input-to-state stability with respect to unknown bounded disturbance is designed using backstepping and control Lyapunov function (CLF) techniques. We show that unknown bounded disturbance can be estimated by update laws, which requires less information on unknown disturbance, as a part of stabilizing control. The design method achieves the desired property: global robust stability. Our contribution is illustrated with the example of a disturbed pendulum.展开更多
文摘In order to solve the model update problem in mean-shift based tracker, a novel mechanism is proposed. Kalman filter is employed to update object model by filtering object kernel-histogram using previous model and current candidate. A self-tuning method is used for adaptively adjust all the parameters of the filters under the analysis of the filtering residuals. In addition, hypothesis testing servers as the criterion for determining whether to accept filtering result. Therefore, the tracker has the ability to handle occlusion so as to avoid over-update. The experimental results show that our method can not only keep up with the object appearance and scale changes but also be robust to occlusion.
文摘To combat packet loss and realize robust video transmission over Intemet and wireless networks, a new multiple description （MD） video coding method is proposed. In the method, two descriptions for each video frame is first created by group of blocks （GOB） alternation. Motion information is then duplicated in both the descriptions and a process called low quality macroblock update is designed to redundantly encode textures in each frame using standard bit stream syntax. In this way, the output bit streams are standard compliant and better trade-offs between redundancy and single charmel reconstruction distortion are achieved. The proposed method has much better performance than the well-known MD transform coding （MDTC） method both in terms of redundancy rate distortion, and in the packet loss scenario.
文摘为方便用户使用高级语言开发Oracle应用程序,Oracle提供有高级语言程序接口工具,使用这些工具,用户便可以用高级语言编制包含SQL语言在内的程序,访问Oracle数据库的数据,Pro*C即为O-racle与C语言的程序接口。 在Oracle中Update命令的功能是用来改变指定“表”的字段值,它的一般调用格式如下: Update Table Set Column=Expr Where
基金supported by the National Natural Science Foundation of China (No. 62073267)。
文摘As a crucial process in the coordinated strikes of unmanned aerial vehicles(UAVs), weapon-target assignment is vital for optimizing the allocation of available weapons and effectively exploiting the capabilities of UAVs. Existing weapon-target assignment methods primarily focus on macro cluster constraints while neglecting individual strategy updates. This paper proposes a novel weapon-target assignment method for UAVs based on the multi-strategy threshold public goods game(PGG). By analyzing the concept mapping between weapon-target assignment for UAVs and multi-strategy threshold PGG, a weapon-target assignment model for UAVs based on the multi-strategy threshold PGG is established, which is adaptively complemented by the diverse cooperation-defection strategy library and the utility function based on the threshold mechanism. Additionally, a multi-chain Markov is formulated to quantitatively describe the stochastic evolutionary dynamics, whose evolutionary stable distribution is theoretically derived through the development of a strategy update rule based on preference-based aspiration dynamic. Numerical simulation results validate the feasibility and effectiveness of the proposed method, and the impacts of selection intensity, preference degree and threshold on the evolutionary stable distribution are analyzed. Comparative simulations show that the proposed method outperforms GWO, DE, and NSGA-II, achieving 17.18% higher expected utility than NSGA-II and reducing evolutionary stable times by 25% in large-scale scenario.
文摘Nowadays,wireless communication devices turn out to be transportable owing to the execution of the current technologies.The antenna is the most important component deployed for communication purposes.The antenna plays an imperative role in receiving and transmitting the signals for any sensor network.Among varied antennas,micro strip fractal antenna(MFA)significantly contributes to increasing antenna gain.This study employs a hybrid optimization method known as the elephant clan updated grey wolf algorithm to introduce an optimized MFA design.This method optimizes antenna characteristics,including directivity and gain.Here,the factors,including length,width,ground plane length,height,and feed offset-X and feed offset-Y,are taken into account to achieve the best performance of gain and directivity.Ultimately,the superiority of the suggested technique over state-of-the-art strategies is calculated for various metrics such as cost and gain.The adopted model converges to a minimal value of 0.2872.Further,the spider monkey optimization(SMO)model accomplishes the worst performance over all other existing models like elephant herding optimization(EHO),grey wolf optimization(GWO),lion algorithm(LA),support vector regressor(SVR),bacterial foraging-particle swarm optimization(BF-PSO)and shark smell optimization(SSO).Effective MFA design is obtained using the suggested strategy regarding various parameters.
基金supported in part by National Key Research and Development Program under Grant No.2020YFB1708800China Postdoctoral Science Foundation under Grant No.2021M700385+5 种基金Guang Dong Basic and Applied Basic Research Foundation under Grant No.2021A1515110577Guangdong Key Research and Development Program under Grant No.2020B0101130007Central Guidance on Local Science and Technology Development Fund of Shanxi Province under Grant No.YDZJSX2022B019Fundamental Research Funds for Central Universities under Grant No.FRF-MP-20-37Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities)under Grant No.FRF-IDRY-21-005National Natural Science Foundation of China under Grant No.62002026。
文摘The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time performance.However,the intricate and unpredictable pedestrian motion patterns lead the INS localization error to significantly diverge with time.This paper aims to enhance the accuracy of zero-velocity interval(ZVI)detection and reduce the heading and altitude drift of foot-mounted INS via deep learning and equation constraint of dual feet.Aiming at the observational noise problem of low-cost inertial sensors,we utilize a denoising autoencoder to automatically eliminate the inherent noise.Aiming at the problem that inaccurate detection of the ZVI detection results in obvious displacement error,we propose a sample-level ZVI detection algorithm based on the U-Net neural network,which effectively solves the problem of mislabeling caused by sliding windows.Aiming at the problem that Zero-Velocity Update(ZUPT)cannot suppress heading and altitude error,we propose a bipedal INS method based on the equation constraint and ellipsoid constraint,which uses foot-to-foot distance as a new observation to correct heading and altitude error.We conduct extensive and well-designed experiments to evaluate the performance of the proposed method.The experimental results indicate that the position error of our proposed method did not exceed 0.83% of the total traveled distance.
基金supported by the National Nature Science Foundation of China (62373246,62203299)the Oceanic Interdisciplinary Program of Shanghai Jiao Tong University (SL2022MS008,SL2020ZD206,SL2022MS010)。
文摘Tracking the fast-moving object in occlusion situations is an important research topic in computer vision. Despite numerous notable contributions have been made in this field,few of them simultaneously incorporate both object's extrinsic features and intrinsic motion patterns into their methodologies,thereby restricting the potential for tracking accuracy improvement. In this paper, on the basis of efficient convolution operators(ECO) model, a speed-accuracy-balanced model is put forward. This model uses the simple correlation filter to track the object in real-time, and adopts the sophisticated deep-learning neural network to extract high-level features to train a more complex filter correcting the tracking mistakes, when the tracking state is judged to be poor. Furthermore, in the context of scenarios involving regular fast-moving, a motion model based on Kalman filter is designed which greatly promotes the tracking stability, because this motion model could predict the object's future location from its previous movement pattern. Additionally,instead of periodically updating our tracking model and training samples, a constrained condition for updating is proposed,which effectively mitigates contamination to the tracker from the background and undesirable samples avoiding model degradation when occlusion happens. From comprehensive experiments, our tracking model obtains better performance than ECO on object tracking benchmark 2015(OTB100), and improves the area under curve(AUC) by about 8% and 32% compared with ECO, in the scenarios of fast-moving and occlusion on our own collected dataset.
文摘To determine compositions,homogenization pressures and isopleths of CO2-H2O-NaCl fluid inclusions,an improved activity-fugacity model is developed to calculate CO2solubility in aqueous NaCl solutions.The model can predict the solubility of CO2in aqueous NaCl solutions from 273 K to 723 K,from1 bar to 1500 bar and from 0 to 4.5 mol kg-1of NaCl,within or close to experimental uncertainties.The average deviation between the solubility predicted
基金Project(51308193)supported by the National Natural Science Foundation of ChinaProject(SGKJ[2007]116)supported by the Science and Technology Program of State Grid Corporation of China
文摘In order to study the sliding characteristics when the cable is connected with the other rods in the transmission line structures,a linear sliding cable element based on updated Lagrangian formulation and a sliding catenary element considering the out-of-plane stiffness coefficient are put forward.A two-span and a three-span cable structures are taken as examples to verify the sliding cable elements.By comparing the tensions of the two proposed cable elements with the existing research results,the error is less than 1%,which proves the correctness of the proposed elements.The sliding characteristics should be considered in the practical engineering because of the significant difference between the tensions of sliding cable elements and those of cable element without considering sliding.The out-of-plane stiffness coefficient and friction characteristics do not obviously affect the cable tensions.
基金This work was supported by the National Natural Science Foundation of China(61803278).
文摘Foot-mounted pedestrian navigation system(PNS)is a common solution to pedestrian navigation using micro-electro mechanical system(MEMS)inertial sensors.The inherent problems of inertial navigation system(INS)by the traditional algorithm,such as the accumulated errors and the lack of observation of heading and altitude information,have become obstacles to the application and development of the PNS.In this paper,we introduce a heuristic heading constraint method.First of all,according to the movement characteristics of human gait,we use the generalized likelihood ratio test(GLRT)detector and introduce a time threshold to classify the human gait,so that we can effectively identify the stationary state of the foot.In addition,based on zero velocity update(ZUPT)and zero angular rate update(ZARU),the cumulative error of the inertial measurement unit(IMU)is limited and corrected,and then a heuristic heading estimation is used to constrain and correct the heading of the pedestrian.After simulation and experiments with low-cost IMU,the method is proved to reduce the localization error of end-point to less than 1%of the total distance,and it has great value in application.
文摘The decomposition based approach decomposes a multi-objective problem into a series of single objective subproblems, which are optimized along contours towards the ideal point. But non-dominated solutions cannot spread uniformly, since the Pareto front shows different features, such as concave and convex. To improve the distribution uniformity of non-dominated solutions, a bidirectional decomposition based approach that constructs two search directions is proposed to provide a uniform distribution no matter what features problems have. Since two populations along two search directions show differently on diversity and convergence, an adaptive neighborhood selection approach is presented to choose suitable parents for the offspring generation. In order to avoid the problem of the shrinking search region caused by the close distance of the ideal and nadir points, a reference point update approach is presented. The performance of the proposed algorithm is validated with four state-of-the-art algorithms. Experimental results demonstrate the superiority of the proposed algorithm on all considered test problems.
文摘An adaptive controller of full state feedback for certain cascade nonlinear systems achieving input-to-state stability with respect to unknown bounded disturbance is designed using backstepping and control Lyapunov function (CLF) techniques. We show that unknown bounded disturbance can be estimated by update laws, which requires less information on unknown disturbance, as a part of stabilizing control. The design method achieves the desired property: global robust stability. Our contribution is illustrated with the example of a disturbed pendulum.
