Owing to the constraints of depth sensing technology,images acquired by depth cameras are inevitably mixed with various noises.For depth maps presented in gray values,this research proposes a novel denoising model,ter...Owing to the constraints of depth sensing technology,images acquired by depth cameras are inevitably mixed with various noises.For depth maps presented in gray values,this research proposes a novel denoising model,termed graph-based transform(GBT)and dual graph Laplacian regularization(DGLR)(DGLR-GBT).This model specifically aims to remove Gaussian white noise by capitalizing on the nonlocal self-similarity(NSS)and the piecewise smoothness properties intrinsic to depth maps.Within the group sparse coding(GSC)framework,a combination of GBT and DGLR is implemented.Firstly,within each group,the graph is constructed by using estimates of the true values of the averaged blocks instead of the observations.Secondly,the graph Laplacian regular terms are constructed based on rows and columns of similar block groups,respectively.Lastly,the solution is obtained effectively by combining the alternating direction multiplication method(ADMM)with the weighted thresholding method within the domain of GBT.展开更多
In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the...In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the recommended density function by introducing a fifth-degree cubature Kalman filter algorithm to guide particle sampling,which effectively alleviates the problem of particle degradation and significantly improves the estimation accuracy of the filter.However,the 5CPF algorithm exhibits high computational complexity,particularly in scenarios with a large number of particles.Therefore,we propose the extended Kalman filter(EKF)-5CPF algorithm,which employs an EKF to replace the time update step for each particle in the 5CPF.This enhances the algorithm’s real-time capability while maintaining the high precision advantage of the 5CPF algorithm.In addition,we construct bearing-only dual-station and single-motion station target tracking systems,and the filtering performances of 5CPF and EKF-5CPF algorithms under different conditions are analyzed.The results show that both the 5CPF algorithm and EKF-5CPF have strong robustness and can adapt to different noise environments.Furthermore,both algorithms significantly outperform traditional nonlinear filtering algorithms in terms of convergence speed,tracking accuracy,and overall stability.展开更多
In this study, we used the multi-resolution graph-based clustering （MRGC） method for determining the electrofacies （EF） and lithofacies （LF） from well log data obtained from the intraplatform bank gas fields loc...In this study, we used the multi-resolution graph-based clustering （MRGC） method for determining the electrofacies （EF） and lithofacies （LF） from well log data obtained from the intraplatform bank gas fields located in the Amu Darya Basin. The MRGC could automatically determine the optimal number of clusters without prior knowledge about the structure or cluster numbers of the analyzed data set and allowed the users to control the level of detail actually needed to define the EF. Based on the LF identification and successful EF calibration using core data, an MRGC EF partition model including five clusters and a quantitative LF interpretation chart were constructed. The EF clusters 1 to 5 were interpreted as lagoon, anhydrite flat, interbank, low-energy bank, and high-energy bank, and the coincidence rate in the cored interval could reach 85%. We concluded that the MRGC could be accurately applied to predict the LF in non-cored but logged wells. Therefore, continuous EF clusters were partitioned and corresponding LF were characteristics ＆different LF were analyzed interpreted, and the distribution and petrophysical in the framework of sequence stratigraphy.展开更多
A better understanding of the relationship between the structure and functions of urban and suburban spaces is one of the avenues of research still open for geographical information science.The research presented in t...A better understanding of the relationship between the structure and functions of urban and suburban spaces is one of the avenues of research still open for geographical information science.The research presented in this paper develops several graph-based metrics whose objective is to characterize some local and global structural properties that reflect the way the overall building layout can be cross-related to the one of the road layout.Such structural properties are modeled as an aggregation of parcels,buildings,and road networks.We introduce several computational measures(Ratio Minimum Distance,Minimum Ratio Minimum Distance,and Metric Compactness)that respectively evaluate the capability for a given road to be connected with the whole road network.These measures reveal emerging sub-network structures and point out differences between less-connective and moreconnective parts of the network.Based on these local and global properties derived from the topological and graph-based representation,and on building density metrics,this paper proposes an analysis of road and building layouts at different levels of granularity.The metrics developed are applied to a case study in which the derived properties reveal coherent as well as incoherent neighborhoods that illustrate the potential of the approach and the way buildings and roads can be relatively connected in a given urban environment.Overall,and by integrating the parcels and buildings layouts,this approach complements other previous and related works that mainly retain the configurational structure of the urban network as well as morphological studies whose focus is generally limited to the analysis of the building layout.展开更多
Simultaneous localization and mapping(SLAM)is widely used in many robot applications to acquire the unknown environment's map and the robots location.Graph-based SLAM is demonstrated to be effective in large-scale...Simultaneous localization and mapping(SLAM)is widely used in many robot applications to acquire the unknown environment's map and the robots location.Graph-based SLAM is demonstrated to be effective in large-scale scenarios,and it intuitively performs the SLAM as a pose graph.But because of the high data overlap rate,traditional graph-based SLAM is not efficient in some respects,such as real time performance and memory usage.To reduce1 data overlap rate,a graph-based SLAM with distributed submap strategy(DSS)is presented.In its front-end,submap based scan matching is processed and loop closing detection is conducted.Moreover in its back-end,pose graph is updated for global optimization and submap merging.From a series of experiments,it is demonstrated that graph-based SLAM with DSS reduces 51.79%data overlap rate,decreases 39.70%runtime and 24.60%memory usage.The advantages over other low overlap rate method is also proved in runtime,memory usage,accuracy and robustness performance.展开更多
The number of botnet malware attacks on Internet devices has grown at an equivalent rate to the number of Internet devices that are connected to the Internet.Bot detection using machine learning(ML)with flow-based fea...The number of botnet malware attacks on Internet devices has grown at an equivalent rate to the number of Internet devices that are connected to the Internet.Bot detection using machine learning(ML)with flow-based features has been extensively studied in the literature.Existing flow-based detection methods involve significant computational overhead that does not completely capture network communication patterns that might reveal other features ofmalicious hosts.Recently,Graph-Based Bot Detection methods using ML have gained attention to overcome these limitations,as graphs provide a real representation of network communications.The purpose of this study is to build a botnet malware detection system utilizing centrality measures for graph-based botnet detection and ML.We propose BotSward,a graph-based bot detection system that is based on ML.We apply the efficient centrality measures,which are Closeness Centrality(CC),Degree Centrality(CC),and PageRank(PR),and compare them with others used in the state-of-the-art.The efficiency of the proposed method is verified on the available Czech Technical University 13 dataset(CTU-13).The CTU-13 dataset contains 13 real botnet traffic scenarios that are connected to a command-and-control(C&C)channel and that cause malicious actions such as phishing,distributed denial-of-service(DDoS)attacks,spam attacks,etc.BotSward is robust to zero-day attacks,suitable for large-scale datasets,and is intended to produce better accuracy than state-of-the-art techniques.The proposed BotSward solution achieved 99%accuracy in botnet attack detection with a false positive rate as low as 0.0001%.展开更多
Maximizing network lifetime is measured as the primary issue in Mobile Ad-hoc Networks(MANETs).In geographically routing based models,packet transmission seems to be more appropriate in dense circumstances.The involve...Maximizing network lifetime is measured as the primary issue in Mobile Ad-hoc Networks(MANETs).In geographically routing based models,packet transmission seems to be more appropriate in dense circumstances.The involvement of the Heuristic model directly is not appropriate to offer an effectual solution as it becomes NP-hard issues;therefore investigators concentrate on using Meta-heuristic approaches.Dragonfly Optimization(DFO)is an effective meta-heuristic approach to resolve these problems by providing optimal solutions.Moreover,Meta-heuristic approaches(DFO)turn to be slower in convergence problems and need proper computational time while expanding network size.Thus,DFO is adaptively improved as Adaptive Dragonfly Optimization(ADFO)to fit this model and re-formulated using graph-based m-connection establishment(G-𝑚𝑚CE)to overcome computational time and DFO’s convergence based problems,considerably enhancing DFO performance.In(G-𝑚𝑚CE),Connectivity Zone(CZ)is chosen among source to destination in which optimality should be under those connected regions and ADFO is used for effective route establishment in CZ indeed of complete networking model.To measure complementary features of ADFO and(G-𝑚𝑚CE),hybridization of DFO-(G-𝑚𝑚CE)is anticipated over dense circumstances with reduced energy consumption and delay to enhance network lifetime.The simulation was performed in MATLAB environment.展开更多
Active learning in semi-supervised classification involves introducing additional labels for unlabelled data to improve the accuracy of the underlying classifier.A challenge is to identify which points to label to bes...Active learning in semi-supervised classification involves introducing additional labels for unlabelled data to improve the accuracy of the underlying classifier.A challenge is to identify which points to label to best improve performance while limiting the number of new labels."Model Change"active learning quantifies the resulting change incurred in the classifier by introducing the additional label(s).We pair this idea with graph-based semi-supervised learning(SSL)methods,that use the spectrum of the graph Laplacian matrix,which can be truncated to avoid prohibitively large computational and storage costs.We consider a family of convex loss functions for which the acquisition function can be efficiently approximated using the Laplace approximation of the posterior distribution.We show a variety of multiclass examples that illustrate improved performance over prior state-of-art.展开更多
Many cutting-edge methods are now possible in real-time commercial settings and are growing in popularity on cloud platforms.By incorporating new,cutting-edge technologies to a larger extent without using more infrast...Many cutting-edge methods are now possible in real-time commercial settings and are growing in popularity on cloud platforms.By incorporating new,cutting-edge technologies to a larger extent without using more infrastructures,the information technology platform is anticipating a completely new level of devel-opment.The following concepts are proposed in this research paper:1)A reliable authentication method Data replication that is optimised;graph-based data encryp-tion and packing colouring in Redundant Array of Independent Disks(RAID)sto-rage.At the data centre,data is encrypted using crypto keys called Key Streams.These keys are produced using the packing colouring method in the web graph’s jump graph.In order to achieve space efficiency,the replication is carried out on optimised many servers employing packing colours.It would be thought that more connections would provide better authentication.This study provides an innovative architecture with robust security,enhanced authentication,and low cost.展开更多
In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenario...In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenarios with non-Gaussian noise and heavy-tailed outliers.The proposed design modifies the extended Kalman filter(EKF)for the global navigation satellite system(GNSS),integrating the maximum correntropy criterion(MCC)and the variational Bayesian(VB)method.This adaptive algorithm effectively reduces non-line-of-sight(NLOS)reception contamination and improves estimation accuracy,particularly in time-varying GNSS measurements.Experimental results show that the proposed method significantly outperforms conventional approaches in estimation accuracy under heavy-tailed outliers and non-Gaussian noise.By combining MCC with VB approximation for real-time noise covariance estimation using fixed-point iteration,the VBMCEKF achieves superior filtering performance in challenging GNSS conditions.The method’s adaptability and precision make it ideal for improving satellite navigation performance in stochastic environments.展开更多
The integration of surface filtration and catalytic decomposition functions in catalytic bags enables the synergistic removal of multiple pollutants(such as dust,nitrogen oxide,acid gases,and dioxins)in a single react...The integration of surface filtration and catalytic decomposition functions in catalytic bags enables the synergistic removal of multiple pollutants(such as dust,nitrogen oxide,acid gases,and dioxins)in a single reactor,thus effectively reducing the cost and operational difficulties associated with flue gas treatment.In this study,Mn-Ce-Sm-Sn(MCSS)catalysts were prepared and loaded onto hightemperature resistant polyimide(P84)filter through ultrasonic impregnation to create composite catalytic filter.The results demonstrate that the NO conversion rates of the composite catalytic filter consistently achieve above 95%within the temperature range of 160-260℃,with a chlorobenzene T_(90)value of 230℃.The ultrasonic impregnation method effectively loaded the catalyst onto the filter,ensuring high dispersion both on the surface and inside the filter.This increased exposure of catalyst active sites enhances the catalytic activity of the composite catalytic filter.Additionally,increasing the catalyst loading leads to a gradual decrease in permeability,an increase in pressure drops and the long residence time of the flue gas,thereby improving catalytic activity.Compared to ordinary impregnation methods,ultrasonic impregnation improves the bonding strength between the catalyst and filter,as well as the permeability of the composite catalytic filter under the same loading conditions.Overall,this study presents a novel approach to prepare composite catalytic filter for the simultaneous removal of NO and chlorobenzene at low temperatures.展开更多
A medical image encryption is proposed based on the Fisher-Yates scrambling,filter diffusion and S-box substitution.First,chaotic sequence associated with the plaintext is generated by logistic-sine-cosine system,whic...A medical image encryption is proposed based on the Fisher-Yates scrambling,filter diffusion and S-box substitution.First,chaotic sequence associated with the plaintext is generated by logistic-sine-cosine system,which is used for the scrambling,substitution and diffusion processes.The three-dimensional Fisher-Yates scrambling,S-box substitution and diffusion are employed for the first round of encryption.The chaotic sequence is adopted for secondary encryption to scramble the ciphertext obtained in the first round.Then,three-dimensional filter is applied to diffusion for further useful information hiding.The key to the algorithm is generated by the combination of hash value of plaintext image and the input parameters.It improves resisting ability of plaintext attacks.The security analysis shows that the algorithm is effective and efficient.It can resist common attacks.In addition,the good diffusion effect shows that the scheme can solve the differential attacks encountered in the transmission of medical images and has positive implications for future research.展开更多
Fault detection in industrial robot drive systems is a critical aspect of ensuring operational reliability and efficiency.To address the challenge of balancing accuracy and robustness in existing fault detection metho...Fault detection in industrial robot drive systems is a critical aspect of ensuring operational reliability and efficiency.To address the challenge of balancing accuracy and robustness in existing fault detection methods,this paper proposes an enhanced fault detection method based on the unscented Kalman filter(UKF).A comprehensive mathematical model of the brushless DC motor drive system is developed to provide a theoretical foundation for the design of subsequent fault detection methods.The conventional UKF estimation process is detailed,and its limitations in balancing estimation accuracy and robustness are addressed by introducing a dynamic,time-varying boundary layer.To further enhance detection performance,the method incorporates residual analysis using improved z-score and signal-tonoise ratio(SNR)metrics.Numerical simulations under both fault-free and faulty conditions demonstrate that the proposed approach achieves lower root mean square error(RMSE)in fault-free scenarios and provides reliable fault detection.These results highlight the potential of the proposed method to enhance the reliability and robustness of fault detection in industrial robot drive systems.展开更多
The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses ...The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is formulated.Due to the fact that only position information can be measured,a linear Extended State Observer(ESO)is introduced to estimate unknown states and matched disturbances,while a dedicated disturbance observer is constructed to estimate mismatched disturbances.Different from the traditional observer results,the design of the disturbance observer used in this study is carried out under the constraint of output feedback.Furthermore,an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory tracking.To mitigate the inherent differential explosion problem of the traditional backstepping framework,a finite-time stable command filter is incorporated.Simultaneously,considering transient filtering errors,a set of error compensation signals are designed to counter their negative impact effectively.Theoretical analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop system.Additionally,under the specific condition of only time-invariant disturbances in the system,the conclusion of asymptotic stability is established.Finally,the algorithm’s efficacy is validated through comparative experiments.展开更多
Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively r...Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively researched for both aerial and underwater navigation applications.However,many TAN systems that rely on recursive Unmanned Aerial Vehicle(UAV)position estimation methods,such as Extended Kalman Filters(EKF),often face challenges with divergence and instability,particularly in highly non-linear systems.To address these issues,this paper proposes and investigates a hybrid two-stage TAN positioning system for UAVs that utilizes Particle Filter.To enhance the system’s robustness against uncertainties caused by noise and to estimate additional system states,a Fuzzy Particle Filter(FPF)is employed in the first stage.This approach introduces a novel terrain composite feature that enables a fuzzy expert system to analyze terrain non-linearities and dynamically adjust the number of particles in real-time.This design allows the UAV to be efficiently localized in GPS-denied environments while also reducing the computational complexity of the particle filter in real-time applications.In the second stage,an Error State Kalman Filter(ESKF)is implemented to estimate the UAV’s altitude.The ESKF is chosen over the conventional EKF method because it is more suitable for non-linear systems.Simulation results demonstrate that the proposed fuzzy-based terrain composite method achieves high positional accuracy while reducing computational time and memory usage.展开更多
In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utili...In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.展开更多
A novel substrate integrated microstrip to ultra-thin cavity filter transition operating in the W-band is proposed in this letter.The structure is a new method of connecting microstrip circuits and waveguide filters,a...A novel substrate integrated microstrip to ultra-thin cavity filter transition operating in the W-band is proposed in this letter.The structure is a new method of connecting microstrip circuits and waveguide filters,and this new structure enables a planar integrated transition from microstrip lines to ultra-thin cavity filters,thereby reducing the size of the transition structure and achieving miniaturization.The structure includes a conventional tapered microstrip transition structure,which guides the electromagnetic field from the microstrip line to the reduced-height dielectric-filled waveguide,and an air-filled matching cavity which is placed between the dielectric-filled waveguide and the ultra-thin cavity filter.The heights of the microstrip line,the dielectric-filled waveguide and the ultra-thin cavity filter are the same,enabling seamless integration within a planar radio-frequency(RF)circuit.To facilitate testing,mature finline transition structures are integrated at both ends of the microstrip line during fabrications.The simulation results of the fabricated microstrip to ultra-thin cavity filter transition with the finline transition structure,with a passband of 91.5-96.5 GHz,has an insertion loss of less than 1.9 dB and a return loss lower than-20 dB.And the whole structure has also been measured which achieves an insertion loss less than 2.6 dB and a return loss lower than-15 dB within the filter's passband,including the additional insertion loss introduced by the finline transitions.Finally,a W-band compact up-conversion module is designed,and the test results show that after using the proposed structure,the module achieves 95 dBc suppression of the 84 GHz local oscillator.It is also demonstrated that the structure proposed in this letter achieves miniaturization of the system integration without compromising the filter performance.展开更多
Filter capacitors play an important role in altern-ating current(AC)-line filtering for stabilizing voltage,sup-pressing harmonics,and improving power quality.However,traditional aluminum electrolytic capacitors(AECs)...Filter capacitors play an important role in altern-ating current(AC)-line filtering for stabilizing voltage,sup-pressing harmonics,and improving power quality.However,traditional aluminum electrolytic capacitors(AECs)suffer from a large size,short lifespan,low power density,and poor reliability,which limits their use.In contrast,ultrafast supercapacitors(SCs)are ideal for replacing commercial AECs because of their extremely high power densities,fast charging and discharging,and excellent high-frequency re-sponse.We review the design principles and key parameters for ultrafast supercapacitors and summarize research pro-gress in recent years from the aspects of electrode materials,electrolytes,and device configurations.The preparation,structures,and frequency response performance of electrode materials mainly consisting of carbon materials such as graphene and carbon nanotubes,conductive polymers,and transition metal compounds,are focused on.Finally,future research directions for ultrafast SCs are suggested.展开更多
Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter us...Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter used in the conventional repetitive controller(CRC), the complex-coefficient filter causes less change in the phase and amplitude of a signal at the frequencies of the periodic signal, especially at the fundamental frequency, when the two filters have the same cutofffrequency.展开更多
The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions a...The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.展开更多
基金National Natural Science Foundation of China(No.62372100)。
文摘Owing to the constraints of depth sensing technology,images acquired by depth cameras are inevitably mixed with various noises.For depth maps presented in gray values,this research proposes a novel denoising model,termed graph-based transform(GBT)and dual graph Laplacian regularization(DGLR)(DGLR-GBT).This model specifically aims to remove Gaussian white noise by capitalizing on the nonlocal self-similarity(NSS)and the piecewise smoothness properties intrinsic to depth maps.Within the group sparse coding(GSC)framework,a combination of GBT and DGLR is implemented.Firstly,within each group,the graph is constructed by using estimates of the true values of the averaged blocks instead of the observations.Secondly,the graph Laplacian regular terms are constructed based on rows and columns of similar block groups,respectively.Lastly,the solution is obtained effectively by combining the alternating direction multiplication method(ADMM)with the weighted thresholding method within the domain of GBT.
基金Supported by the Guangxi Special Program for Technological Innovation Guidance(No.GuiKeAC25069006).
文摘In this study,a fifth-degree cubature particle filter(5CPF)is proposed to address the limited estimation accuracy in traditional particle filter algorithms for bearings-only tracking(BOT).This algorithm calculates the recommended density function by introducing a fifth-degree cubature Kalman filter algorithm to guide particle sampling,which effectively alleviates the problem of particle degradation and significantly improves the estimation accuracy of the filter.However,the 5CPF algorithm exhibits high computational complexity,particularly in scenarios with a large number of particles.Therefore,we propose the extended Kalman filter(EKF)-5CPF algorithm,which employs an EKF to replace the time update step for each particle in the 5CPF.This enhances the algorithm’s real-time capability while maintaining the high precision advantage of the 5CPF algorithm.In addition,we construct bearing-only dual-station and single-motion station target tracking systems,and the filtering performances of 5CPF and EKF-5CPF algorithms under different conditions are analyzed.The results show that both the 5CPF algorithm and EKF-5CPF have strong robustness and can adapt to different noise environments.Furthermore,both algorithms significantly outperform traditional nonlinear filtering algorithms in terms of convergence speed,tracking accuracy,and overall stability.
基金supported by the National Science and Technology Major Project of China(No.2011ZX05029-003)CNPC Science Research and Technology Development Project,China(No.2013D-0904)
文摘In this study, we used the multi-resolution graph-based clustering （MRGC） method for determining the electrofacies （EF） and lithofacies （LF） from well log data obtained from the intraplatform bank gas fields located in the Amu Darya Basin. The MRGC could automatically determine the optimal number of clusters without prior knowledge about the structure or cluster numbers of the analyzed data set and allowed the users to control the level of detail actually needed to define the EF. Based on the LF identification and successful EF calibration using core data, an MRGC EF partition model including five clusters and a quantitative LF interpretation chart were constructed. The EF clusters 1 to 5 were interpreted as lagoon, anhydrite flat, interbank, low-energy bank, and high-energy bank, and the coincidence rate in the cored interval could reach 85%. We concluded that the MRGC could be accurately applied to predict the LF in non-cored but logged wells. Therefore, continuous EF clusters were partitioned and corresponding LF were characteristics ＆different LF were analyzed interpreted, and the distribution and petrophysical in the framework of sequence stratigraphy.
文摘A better understanding of the relationship between the structure and functions of urban and suburban spaces is one of the avenues of research still open for geographical information science.The research presented in this paper develops several graph-based metrics whose objective is to characterize some local and global structural properties that reflect the way the overall building layout can be cross-related to the one of the road layout.Such structural properties are modeled as an aggregation of parcels,buildings,and road networks.We introduce several computational measures(Ratio Minimum Distance,Minimum Ratio Minimum Distance,and Metric Compactness)that respectively evaluate the capability for a given road to be connected with the whole road network.These measures reveal emerging sub-network structures and point out differences between less-connective and moreconnective parts of the network.Based on these local and global properties derived from the topological and graph-based representation,and on building density metrics,this paper proposes an analysis of road and building layouts at different levels of granularity.The metrics developed are applied to a case study in which the derived properties reveal coherent as well as incoherent neighborhoods that illustrate the potential of the approach and the way buildings and roads can be relatively connected in a given urban environment.Overall,and by integrating the parcels and buildings layouts,this approach complements other previous and related works that mainly retain the configurational structure of the urban network as well as morphological studies whose focus is generally limited to the analysis of the building layout.
基金the Project Fund for Key Discipline of the Shanghai Municipal Education Commission(No.J50104)the Major State Basic Research Development Program of China(No.2017YFB0403500)。
文摘Simultaneous localization and mapping(SLAM)is widely used in many robot applications to acquire the unknown environment's map and the robots location.Graph-based SLAM is demonstrated to be effective in large-scale scenarios,and it intuitively performs the SLAM as a pose graph.But because of the high data overlap rate,traditional graph-based SLAM is not efficient in some respects,such as real time performance and memory usage.To reduce1 data overlap rate,a graph-based SLAM with distributed submap strategy(DSS)is presented.In its front-end,submap based scan matching is processed and loop closing detection is conducted.Moreover in its back-end,pose graph is updated for global optimization and submap merging.From a series of experiments,it is demonstrated that graph-based SLAM with DSS reduces 51.79%data overlap rate,decreases 39.70%runtime and 24.60%memory usage.The advantages over other low overlap rate method is also proved in runtime,memory usage,accuracy and robustness performance.
文摘The number of botnet malware attacks on Internet devices has grown at an equivalent rate to the number of Internet devices that are connected to the Internet.Bot detection using machine learning(ML)with flow-based features has been extensively studied in the literature.Existing flow-based detection methods involve significant computational overhead that does not completely capture network communication patterns that might reveal other features ofmalicious hosts.Recently,Graph-Based Bot Detection methods using ML have gained attention to overcome these limitations,as graphs provide a real representation of network communications.The purpose of this study is to build a botnet malware detection system utilizing centrality measures for graph-based botnet detection and ML.We propose BotSward,a graph-based bot detection system that is based on ML.We apply the efficient centrality measures,which are Closeness Centrality(CC),Degree Centrality(CC),and PageRank(PR),and compare them with others used in the state-of-the-art.The efficiency of the proposed method is verified on the available Czech Technical University 13 dataset(CTU-13).The CTU-13 dataset contains 13 real botnet traffic scenarios that are connected to a command-and-control(C&C)channel and that cause malicious actions such as phishing,distributed denial-of-service(DDoS)attacks,spam attacks,etc.BotSward is robust to zero-day attacks,suitable for large-scale datasets,and is intended to produce better accuracy than state-of-the-art techniques.The proposed BotSward solution achieved 99%accuracy in botnet attack detection with a false positive rate as low as 0.0001%.
文摘Maximizing network lifetime is measured as the primary issue in Mobile Ad-hoc Networks(MANETs).In geographically routing based models,packet transmission seems to be more appropriate in dense circumstances.The involvement of the Heuristic model directly is not appropriate to offer an effectual solution as it becomes NP-hard issues;therefore investigators concentrate on using Meta-heuristic approaches.Dragonfly Optimization(DFO)is an effective meta-heuristic approach to resolve these problems by providing optimal solutions.Moreover,Meta-heuristic approaches(DFO)turn to be slower in convergence problems and need proper computational time while expanding network size.Thus,DFO is adaptively improved as Adaptive Dragonfly Optimization(ADFO)to fit this model and re-formulated using graph-based m-connection establishment(G-𝑚𝑚CE)to overcome computational time and DFO’s convergence based problems,considerably enhancing DFO performance.In(G-𝑚𝑚CE),Connectivity Zone(CZ)is chosen among source to destination in which optimality should be under those connected regions and ADFO is used for effective route establishment in CZ indeed of complete networking model.To measure complementary features of ADFO and(G-𝑚𝑚CE),hybridization of DFO-(G-𝑚𝑚CE)is anticipated over dense circumstances with reduced energy consumption and delay to enhance network lifetime.The simulation was performed in MATLAB environment.
基金supported by the DOD National Defense Science and Engineering Graduate(NDSEG)Research Fellowshipsupported by the NGA under Contract No.HM04762110003.
文摘Active learning in semi-supervised classification involves introducing additional labels for unlabelled data to improve the accuracy of the underlying classifier.A challenge is to identify which points to label to best improve performance while limiting the number of new labels."Model Change"active learning quantifies the resulting change incurred in the classifier by introducing the additional label(s).We pair this idea with graph-based semi-supervised learning(SSL)methods,that use the spectrum of the graph Laplacian matrix,which can be truncated to avoid prohibitively large computational and storage costs.We consider a family of convex loss functions for which the acquisition function can be efficiently approximated using the Laplace approximation of the posterior distribution.We show a variety of multiclass examples that illustrate improved performance over prior state-of-art.
文摘Many cutting-edge methods are now possible in real-time commercial settings and are growing in popularity on cloud platforms.By incorporating new,cutting-edge technologies to a larger extent without using more infrastructures,the information technology platform is anticipating a completely new level of devel-opment.The following concepts are proposed in this research paper:1)A reliable authentication method Data replication that is optimised;graph-based data encryp-tion and packing colouring in Redundant Array of Independent Disks(RAID)sto-rage.At the data centre,data is encrypted using crypto keys called Key Streams.These keys are produced using the packing colouring method in the web graph’s jump graph.In order to achieve space efficiency,the replication is carried out on optimised many servers employing packing colours.It would be thought that more connections would provide better authentication.This study provides an innovative architecture with robust security,enhanced authentication,and low cost.
基金supported by the National Science and Technology Council,Taiwan under grants NSTC 111-2221-E-019-047 and NSTC 112-2221-E-019-030.
文摘In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenarios with non-Gaussian noise and heavy-tailed outliers.The proposed design modifies the extended Kalman filter(EKF)for the global navigation satellite system(GNSS),integrating the maximum correntropy criterion(MCC)and the variational Bayesian(VB)method.This adaptive algorithm effectively reduces non-line-of-sight(NLOS)reception contamination and improves estimation accuracy,particularly in time-varying GNSS measurements.Experimental results show that the proposed method significantly outperforms conventional approaches in estimation accuracy under heavy-tailed outliers and non-Gaussian noise.By combining MCC with VB approximation for real-time noise covariance estimation using fixed-point iteration,the VBMCEKF achieves superior filtering performance in challenging GNSS conditions.The method’s adaptability and precision make it ideal for improving satellite navigation performance in stochastic environments.
基金Project supported by the National Key Research and Development Program of China(2021YFB3500600,2021YFB3500605)Natural Science Foundation of Jiangsu Province(BK20220365)+5 种基金Key R&D Program of Jiangsu Province(BE2022142)Natural Science Foundation of the Jiangsu Higher Education Institutions of China(22KJB610002)Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX23_1419)Science and Technology Plan of Yangzhou(YZ2022030,YZ2023020)the State Key Laboratory of Clean and Efficient Coal-fired Power Generation and Pollution Control(D2022FK098)。
文摘The integration of surface filtration and catalytic decomposition functions in catalytic bags enables the synergistic removal of multiple pollutants(such as dust,nitrogen oxide,acid gases,and dioxins)in a single reactor,thus effectively reducing the cost and operational difficulties associated with flue gas treatment.In this study,Mn-Ce-Sm-Sn(MCSS)catalysts were prepared and loaded onto hightemperature resistant polyimide(P84)filter through ultrasonic impregnation to create composite catalytic filter.The results demonstrate that the NO conversion rates of the composite catalytic filter consistently achieve above 95%within the temperature range of 160-260℃,with a chlorobenzene T_(90)value of 230℃.The ultrasonic impregnation method effectively loaded the catalyst onto the filter,ensuring high dispersion both on the surface and inside the filter.This increased exposure of catalyst active sites enhances the catalytic activity of the composite catalytic filter.Additionally,increasing the catalyst loading leads to a gradual decrease in permeability,an increase in pressure drops and the long residence time of the flue gas,thereby improving catalytic activity.Compared to ordinary impregnation methods,ultrasonic impregnation improves the bonding strength between the catalyst and filter,as well as the permeability of the composite catalytic filter under the same loading conditions.Overall,this study presents a novel approach to prepare composite catalytic filter for the simultaneous removal of NO and chlorobenzene at low temperatures.
文摘A medical image encryption is proposed based on the Fisher-Yates scrambling,filter diffusion and S-box substitution.First,chaotic sequence associated with the plaintext is generated by logistic-sine-cosine system,which is used for the scrambling,substitution and diffusion processes.The three-dimensional Fisher-Yates scrambling,S-box substitution and diffusion are employed for the first round of encryption.The chaotic sequence is adopted for secondary encryption to scramble the ciphertext obtained in the first round.Then,three-dimensional filter is applied to diffusion for further useful information hiding.The key to the algorithm is generated by the combination of hash value of plaintext image and the input parameters.It improves resisting ability of plaintext attacks.The security analysis shows that the algorithm is effective and efficient.It can resist common attacks.In addition,the good diffusion effect shows that the scheme can solve the differential attacks encountered in the transmission of medical images and has positive implications for future research.
基金Supported by the Natural Science Foundation of the Higher Education Institutions of Jiangsu Province(22KJB520012)the Research Project on Higher Education Reform in Jiangsu Province(2023JSJG781)the College Student Innovation and Entrepreneurship Training Program Project(202313571008Z)。
文摘Fault detection in industrial robot drive systems is a critical aspect of ensuring operational reliability and efficiency.To address the challenge of balancing accuracy and robustness in existing fault detection methods,this paper proposes an enhanced fault detection method based on the unscented Kalman filter(UKF).A comprehensive mathematical model of the brushless DC motor drive system is developed to provide a theoretical foundation for the design of subsequent fault detection methods.The conventional UKF estimation process is detailed,and its limitations in balancing estimation accuracy and robustness are addressed by introducing a dynamic,time-varying boundary layer.To further enhance detection performance,the method incorporates residual analysis using improved z-score and signal-tonoise ratio(SNR)metrics.Numerical simulations under both fault-free and faulty conditions demonstrate that the proposed approach achieves lower root mean square error(RMSE)in fault-free scenarios and provides reliable fault detection.These results highlight the potential of the proposed method to enhance the reliability and robustness of fault detection in industrial robot drive systems.
基金supported by the National Key R&D Program of China(No.2021YFB2011300)the Special Funds Project for the Transformation of Scientific and Technological Achievements of Jiangsu Province,China(No.BA2023039)+1 种基金the National Natural Science Foundation of China(No.52075262)the Fundamental Research Funds for the Central Universities,China(No.30922010706).
文摘The output feedback active disturbance rejection control of a valve-controlled cylinder electro-hydraulic servo system is investigated in this paper.First,a comprehensive nonlinear mathematical model that encompasses both matched and mismatched disturbances is formulated.Due to the fact that only position information can be measured,a linear Extended State Observer(ESO)is introduced to estimate unknown states and matched disturbances,while a dedicated disturbance observer is constructed to estimate mismatched disturbances.Different from the traditional observer results,the design of the disturbance observer used in this study is carried out under the constraint of output feedback.Furthermore,an output feedback nonlinear controller is proposed leveraging the aforementioned observers to achieve accurate trajectory tracking.To mitigate the inherent differential explosion problem of the traditional backstepping framework,a finite-time stable command filter is incorporated.Simultaneously,considering transient filtering errors,a set of error compensation signals are designed to counter their negative impact effectively.Theoretical analysis affirms that the proposed control strategy ensures the boundedness of all signals within the closed-loop system.Additionally,under the specific condition of only time-invariant disturbances in the system,the conclusion of asymptotic stability is established.Finally,the algorithm’s efficacy is validated through comparative experiments.
文摘Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is unavailable.In recent years,TAN systems have been extensively researched for both aerial and underwater navigation applications.However,many TAN systems that rely on recursive Unmanned Aerial Vehicle(UAV)position estimation methods,such as Extended Kalman Filters(EKF),often face challenges with divergence and instability,particularly in highly non-linear systems.To address these issues,this paper proposes and investigates a hybrid two-stage TAN positioning system for UAVs that utilizes Particle Filter.To enhance the system’s robustness against uncertainties caused by noise and to estimate additional system states,a Fuzzy Particle Filter(FPF)is employed in the first stage.This approach introduces a novel terrain composite feature that enables a fuzzy expert system to analyze terrain non-linearities and dynamically adjust the number of particles in real-time.This design allows the UAV to be efficiently localized in GPS-denied environments while also reducing the computational complexity of the particle filter in real-time applications.In the second stage,an Error State Kalman Filter(ESKF)is implemented to estimate the UAV’s altitude.The ESKF is chosen over the conventional EKF method because it is more suitable for non-linear systems.Simulation results demonstrate that the proposed fuzzy-based terrain composite method achieves high positional accuracy while reducing computational time and memory usage.
基金supported in part by the National Natural Science Foundation of China(12171124,61933007)the Natural Science Foundation of Heilongjiang Province of China(ZD2022F003)+2 种基金the National High-End Foreign Experts Recruitment Plan of China(G2023012004L)the Royal Society of UKthe Alexander von Humboldt Foundation of Germany
文摘In this paper, the problem of cubature Kalman fusion filtering(CKFF) is addressed for multi-sensor systems under amplify-and-forward(AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.
基金Supported by the Fundamental Research Funds for the Central Universities(ZYGX2021J008)。
文摘A novel substrate integrated microstrip to ultra-thin cavity filter transition operating in the W-band is proposed in this letter.The structure is a new method of connecting microstrip circuits and waveguide filters,and this new structure enables a planar integrated transition from microstrip lines to ultra-thin cavity filters,thereby reducing the size of the transition structure and achieving miniaturization.The structure includes a conventional tapered microstrip transition structure,which guides the electromagnetic field from the microstrip line to the reduced-height dielectric-filled waveguide,and an air-filled matching cavity which is placed between the dielectric-filled waveguide and the ultra-thin cavity filter.The heights of the microstrip line,the dielectric-filled waveguide and the ultra-thin cavity filter are the same,enabling seamless integration within a planar radio-frequency(RF)circuit.To facilitate testing,mature finline transition structures are integrated at both ends of the microstrip line during fabrications.The simulation results of the fabricated microstrip to ultra-thin cavity filter transition with the finline transition structure,with a passband of 91.5-96.5 GHz,has an insertion loss of less than 1.9 dB and a return loss lower than-20 dB.And the whole structure has also been measured which achieves an insertion loss less than 2.6 dB and a return loss lower than-15 dB within the filter's passband,including the additional insertion loss introduced by the finline transitions.Finally,a W-band compact up-conversion module is designed,and the test results show that after using the proposed structure,the module achieves 95 dBc suppression of the 84 GHz local oscillator.It is also demonstrated that the structure proposed in this letter achieves miniaturization of the system integration without compromising the filter performance.
文摘Filter capacitors play an important role in altern-ating current(AC)-line filtering for stabilizing voltage,sup-pressing harmonics,and improving power quality.However,traditional aluminum electrolytic capacitors(AECs)suffer from a large size,short lifespan,low power density,and poor reliability,which limits their use.In contrast,ultrafast supercapacitors(SCs)are ideal for replacing commercial AECs because of their extremely high power densities,fast charging and discharging,and excellent high-frequency re-sponse.We review the design principles and key parameters for ultrafast supercapacitors and summarize research pro-gress in recent years from the aspects of electrode materials,electrolytes,and device configurations.The preparation,structures,and frequency response performance of electrode materials mainly consisting of carbon materials such as graphene and carbon nanotubes,conductive polymers,and transition metal compounds,are focused on.Finally,future research directions for ultrafast SCs are suggested.
基金supported in part by the National Natural Science Foundation of China(61873348,6230 3266,62273200)JSPS(Japan Society for the Promotion of Science) KAKENHI(22H03998,23K25252)
文摘Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter used in the conventional repetitive controller(CRC), the complex-coefficient filter causes less change in the phase and amplitude of a signal at the frequencies of the periodic signal, especially at the fundamental frequency, when the two filters have the same cutofffrequency.
基金supported by the National Natural Science(No.U19A2063)the Jilin Provincial Development Program of Science and Technology (No.20230201080GX)the Jilin Province Education Department Scientific Research Project (No.JJKH20230851KJ)。
文摘The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.
