Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation...Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation if estimation of the spoofer on UAV has continuous observation error.Aiming at this problem,the influence of the spoofer’s state estimation error on spoofing effect and error convergence conditions is theoretically analyzed,and an improved adaptively robust estimation algo-rithm suitable for steady-state linear quadratic estimator is pro-posed.It enables the spoofer’s estimator to reliably estimate UAV status in real time,improves the robustness of the estima-tor in responding to observation errors,and accelerates the con-vergence time of error control.Simulation experiments show that the mean value of normalized innovation squared(NIS)is reduced by 88.5%,and the convergence time of NIS value is reduced by 76.3%,the convergence time of true trajectory error of UAV is reduced by 42.3%,the convergence time of estimated trajectory error of UAV is reduced by 67.4%,the convergence time of estimated trajectory error of the spoofer is reduced by 33.7%,and the convergence time of broadcast trajectory error of the spoofer is reduced by 54.8%when the improved algorithm is used.The improved algorithm can make UAV deviate from pre-set trajectory to spoofing trajectory more effectively and more subtly.展开更多
Quadtree-based Cartesian grid was automatically generated from specified geometry.Adaptive refinements were performed according to geometric parameters and solution of flow field.An altered CCST(curvature corrected sy...Quadtree-based Cartesian grid was automatically generated from specified geometry.Adaptive refinements were performed according to geometric parameters and solution of flow field.An altered CCST(curvature corrected symmetry technique)approach was proposed to apply solid wall boundary conditions. Driven flows in a square cavity and flows around NACA0012airfoil were simulated and compared with the result of published structured grid and stretched Cartesian grid.The results show that solid wall boundary condition are accurately applied by current altered CCST approach,while incompressible/compressible subsonic, transonic and supersonic viscous flows are adequately simulated with adaptively refined Cartesian grid.展开更多
Characteristic Basis Function Method (CBFM) is a novel approach for analyzing the ElectroMagnetic (EM) scattering from electrically large objects. Based on dividing the studied object into small blocks, the CBFM is su...Characteristic Basis Function Method (CBFM) is a novel approach for analyzing the ElectroMagnetic (EM) scattering from electrically large objects. Based on dividing the studied object into small blocks, the CBFM is suitable for parallel computing. In this paper, a static load balance parallel method is presented by combining Message Passing Interface (MPI) with Adaptively Modified CBFM (AMCBFM). In this method, the object geometry is partitioned into distinct blocks, and the serial number of blocks is sent to related nodes according to a certain rule. Every node only needs to calculate the information on local blocks. The obtained results confirm the accuracy and efficiency of the proposed method in speeding up solving large electrical scale problems.展开更多
Titanium hollow blades are characterized with lightweight and high structural strength, which are widely used in advanced aircraft engines nowadays. Superplastic forming/diffusion bonding （SPF/DB） combined with nume...Titanium hollow blades are characterized with lightweight and high structural strength, which are widely used in advanced aircraft engines nowadays. Superplastic forming/diffusion bonding （SPF/DB） combined with numerical control （NC） milling is a major solution for manufacturing titanium hollow blades. Due to the shape deviation caused by multiple heat and pressure cycles in the SPF/DB process, it is hard to manufacture the leading and tailing edges by the milling process. This paper presents a new adaptive machining approach using free-form deformation to solve this problem. The actual SPF/DB shape of a hollow blade was firstly inspected by an on-machine measurement method. The measured point data were matched to the nominal SPF/DB shape with an improved ICP algorithm afterwards, by which the point-pairs between the measurement points and their corresponding points on the nominal SPF/DB shape were established, and the maximum modification amount of the final nominal shape was constrained. Based on the displacements between the point-pairs, an accurate FFD volume was iteratively calculated. By embedding the final nominal shape in the deformation space, a new final shape of the hollow blade was built. Finally, a series of measurement and machining tests was performed, the results of which validated the feasibility of the proposed adaptive machining approach.展开更多
Two kinds of fading filters and their principles are introduced. An adaptive robust filter is given with corresponding principle. The basic abilities of the fading filters and adaptively robust filter in controlling t...Two kinds of fading filters and their principles are introduced. An adaptive robust filter is given with corresponding principle. The basic abilities of the fading filters and adaptively robust filter in controlling the influences of the kinematic model errors are analyzed. A practical example is given. The results of the fading filter and adaptively robust filter are compared and analyzed.展开更多
The ant system algorithm （ASA） has proved to be a novel meta-heuristic algorithm to solve many multivariable problems. In this paper, the earth coverage of satellite constellation is analyzed and a n ＋ 1^ -fold cov...The ant system algorithm （ASA） has proved to be a novel meta-heuristic algorithm to solve many multivariable problems. In this paper, the earth coverage of satellite constellation is analyzed and a n ＋ 1^ -fold coverage rate is put forward to evaluate the coverage performance of a satellite constellation. An optimization model of constellation parameters is established on the basis of the coverage performance. As a newly developed method, ASA can be applied to optimize the constellation parameters. In order to improve the ASA, a rule for adaptive number of ants is proposed, by which the search range is obviously enlarged and the convergence speed increased. Simulation results have shown that the ASA is more quick and efficient than other methodV211.71s.展开更多
Forward-backward algorithm, used by watermark decoder for correcting non-binary synchronization errors, requires to traverse a very large scale trellis in order to achieve the proper posterior probability, leading to ...Forward-backward algorithm, used by watermark decoder for correcting non-binary synchronization errors, requires to traverse a very large scale trellis in order to achieve the proper posterior probability, leading to high computational complexity. In order to reduce the number of the states involved in the computation, an adaptive pruning method for the trellis is proposed. In this scheme, we prune the states which have the low forward-backward quantities below a carefully-chosen threshold. Thus, a wandering trellis with much less states is achieved, which contains most of the states with quite high probability. Simulation results reveal that, with the proper scaling factor, significant complexity reduction in the forward-backward algorithm is achieved at the expense of slight performance degradation.展开更多
Attribute revocation is inevitable and al- so important for Attribute-Based Encryption （ABE） in practice. However, little attention has been paid to this issue, and it retrains one of the rmin obsta-cles for the app...Attribute revocation is inevitable and al- so important for Attribute-Based Encryption （ABE） in practice. However, little attention has been paid to this issue, and it retrains one of the rmin obsta-cles for the application of ABE. Most of existing ABE schemes support attribute revocation work under indirect revocation model such that all the users＇ private keys will be affected when the revo-cation events occur. Though some ABE schemes have realized revocation under direct revocation model such that the revocation list is embedded in the ciphertext and none of the users＇ private keys will be affected by revocation, they mostly focused on the user revocation that revokes the user＇s whole attributes, or they can only be proven to be selectively secure. In this paper, we first define a model of adaptively secure ABE supporting the at- tribute revocation under direct revocation model. Then we propose a Key-Policy ABE （KP-ABE） scheme and a Ciphertext-Policy ABE （CP-ABE） scheme on composite order bilinear groups. Finally, we prove our schemes to be adaptively secure by employing the methodology of dual system eno cryption.展开更多
Adaptive grid methods are established as valuable computational technique in approximating effectively the solutions of problems with boundary or interior layers. In this paper,we present the analysis of an upwind sch...Adaptive grid methods are established as valuable computational technique in approximating effectively the solutions of problems with boundary or interior layers. In this paper,we present the analysis of an upwind scheme for singularly perturbed differential-difference equation on a grid which is formed by equidistributing arc-length monitor function.It is shown that the discrete solution obtained converges uniformly with respect to the perturbation parameter.Numerical experiments illustrate in practice the result of convergence proved theoretically.展开更多
Hybrid laser-MAG welding with real-time adaptive control has been demonstrated.Hybrid welding conditions have been developed to produce ISO 13919-1 class B (stringent) quality butt welds between 8mm thickness steel pl...Hybrid laser-MAG welding with real-time adaptive control has been demonstrated.Hybrid welding conditions have been developed to produce ISO 13919-1 class B (stringent) quality butt welds between 8mm thickness steel plates,using a 5kW 6mm.mrad Yb fibre laser combined with conventional arc welding equipment.A laser vision seam tracking system has enabled a 7-axis robot,manipulating the hybrid welding head,to track butt joints in real time during welding.The laser vision system has also provided information on the variations in joint fit-up,in particular the width of any gaps,or height of any mismatches present.This information has then been used to automatically adjust the robot position or speed,or arc welding parameters,depending on the fit-up detected.In this way,the tolerance of the hybrid process has been augmented,producing stringent quality welds over a wider range of joint fit-up cases than when using fixed conditions alone.展开更多
In order to solve the problems of color bias and visual deviation caused by inaccurate estimation of transmittance and atmospheric light in image defogging,a new algorithm based on multi-scale morphological reconstruc...In order to solve the problems of color bias and visual deviation caused by inaccurate estimation of transmittance and atmospheric light in image defogging,a new algorithm based on multi-scale morphological reconstruction with adaptive transmittance and atmospheric light correction was proposed.Firstly,the algorithm used the open operation under morphological reconstruction to replace the minimum filter operation in the dark channel,and used the morphological edge to set the scale of the open operation structure elements,and constructed a multi-scale open operation fusion dark channel.After morphological noise reduction,the exact initial transmittance was obtained.According to the relationship between brightness and saturation difference and transmittance,an adaptive transmittance correction model was fitted with Gaussian function to correct the initial transmittance of the sky fog map.Then the local atmospheric light was improved according to the image brightness information and morphology closure operation.Finally,the proposed algorithm was combined with the atmospheric scattering model to obtain an accurate fog free image.The experimental results showed that the proposed algorithm was suitable for fog image restoration under various scenes,the restoration effect was good,and the brightness was suitable.展开更多
Adaptive mesh refinement (AMR) is fairly practiced in the context of high-dimensional, mesh-based computational models. However, it is in its infancy in that of low-dimensional, generalized-coordinate-based computatio...Adaptive mesh refinement (AMR) is fairly practiced in the context of high-dimensional, mesh-based computational models. However, it is in its infancy in that of low-dimensional, generalized-coordinate-based computational models such as projection-based reduced-order models. This paper presents a complete framework for projection-based model order reduction (PMOR) of nonlinear problems in the presence of AMR that builds on elements from existing methods and augments them with critical new contributions. In particular, it proposes an analytical algorithm for computing a pseudo-meshless inner product between adapted solution snapshots for the purpose of clustering and PMOR. It exploits hyperreduction—specifically, the energy-conserving sampling and weighting hyperreduction method—to deliver for nonlinear and/or parametric problems the desired computational gains. Most importantly, the proposed framework for PMOR in the presence of AMR capitalizes on the concept of state-local reduced-order bases to make the most of the notion of a supermesh, while achieving computational tractability. Its features are illustrated with CFD applications grounded in AMR and its significance is demonstrated by the reported wall-clock speedup factors.展开更多
A slip-draft embedded control system was designed and developed for an independent developed 2WD(two-wheel drive)electric tractor,to improve the traction efficiency,operation performance and ploughing depth stability ...A slip-draft embedded control system was designed and developed for an independent developed 2WD(two-wheel drive)electric tractor,to improve the traction efficiency,operation performance and ploughing depth stability of the electric tractor.In this system,the battery of electric tractor was innovatively equivalent to the original counterweight of the fuel tractor.And through dynamic analysis of electric tractor during ploughing,the mathematical model of adjusting the center of gravity about draft force and slip rate was established.Then the automatic adjustment of the center of gravity for electric tractor was realized through the adaptive adjustment of battery position.Finally,the system was carried on electric tractor for performance evaluation under different ploughing conditions,the traction efficiency,slip rate and front wheel load of electric tractor were measured and controlled synchronously to make it close to the set range.And the comparative experiments of ploughing operation were carried out under the two modes of adaptive adjustment of center of gravity and fixed center of gravity.The test results showed that,based on the developed control system,the center of gravity of electric tractor can be adjusted in real time according to the complex changes of working conditions.During ploughing operation with adjusting adaptively battery position,the average values of traction efficiency,slip rate,front wheel load and relative error of tillage depth of electric tractor were 64.5%,22.2%,2045.0 N and 2.0%respectively.Which were optimized by 15.0%,29.5%,19.6%and 80.0%respectively,compared with electric tractor with fixed battery position.The slip-draft embedded control system can not only realize the adaptive adjustment of the center of gravity position in the ploughing process of electric tractor,but also improve the traction efficiency and the stability of ploughing depth,which can provide reference for the actual production operation of electric tractor.展开更多
We apply the multiscale basis functions for the singularly perturbed reaction-diffusion problem on adaptively graded meshes,which can provide a good balance between the numerical accuracy and computational cost.The mu...We apply the multiscale basis functions for the singularly perturbed reaction-diffusion problem on adaptively graded meshes,which can provide a good balance between the numerical accuracy and computational cost.The multiscale space is built through standard finite element basis functions enriched with multiscale basis functions.The multiscale basis functions have abilities to capture originally perturbed information in the local problem,as a result our method is capable of reducing the boundary layer errors remarkably on graded meshes,where the layer-adapted meshes are generated by a given parameter.Through numerical experiments we demonstrate that the multiscale method can acquire second order convergence in the L^(2)norm and first order convergence in the energy norm on graded meshes,which is independent ofε.In contrast with the conventional methods,our method is much more accurate and effective.展开更多
When evaluating the performance of distributed software-defined network(SDN)controller architecture in data center networks,the required number of controllers for a given network topology and their location are major ...When evaluating the performance of distributed software-defined network(SDN)controller architecture in data center networks,the required number of controllers for a given network topology and their location are major issues of interest.To address these issues,this study proposes the adaptively adjusting and mapping controllers(AAMcon)to design a stateful data plane.We use the complex network community theory to select a key switch to place the controller which is closer to switches it controls in a subnet.A physically distributed but logically centralized controller pool is built based on the network function virtualization(NFV).And then we propose a fast start/overload avoid algorithm to adaptively adjust the number of controllers according to the demand.We performed an analysis for AAMcon to find the optimal distance between the switch and controller.Finally,experiments show the following results.(1)For the number of controllers,AAMcon can greatly follow the demand;for the placement location of controller,controller can respond to the request of switch with the least distance to minimize the delay between the switch and it.(2)For failure tolerance,AAMcon shows good robustness.(3)AAMcon requires less delay to the network with more significant community structure.In fact,there is an inverse relationship between the community modularity and average distance between the switch and controller,i.e.,the average delay decreases when the community modularity increases.(4)AAMcon can achieve the load balance between the controllers.(5)Compared to DCP-GK and k-critical,AAMcon shows good performance.展开更多
Purpose-The purpose of this study is to develop a hybrid algorithm for segmenting tumor from ultrasound images of the liver.Design/methodology/approach-After collecting the ultrasound images,contrast-limited adaptive ...Purpose-The purpose of this study is to develop a hybrid algorithm for segmenting tumor from ultrasound images of the liver.Design/methodology/approach-After collecting the ultrasound images,contrast-limited adaptive histogram equalization approach(CLAHE)is applied as preprocessing,in order to enhance the visual quality of the images that helps in better segmentation.Then,adaptively regularized kernel-based fuzzy C means(ARKFCM)is used to segment tumor from the enhanced image along with local ternary pattern combined with selective level set approaches.Findings-The proposed segmentation algorithm precisely segments the tumor portions from the enhanced images with lower computation cost.The proposed segmentation algorithm is compared with the existing algorithms and ground truth values in terms of Jaccard coefficient,dice coefficient,precision,Matthews correlation coefficient,f-score and accuracy.The experimental analysis shows that the proposed algorithm achieved 99.18% of accuracy and 92.17% of f-score value,which is better than the existing algorithms.Practical implications-From the experimental analysis,the proposed ARKFCM with enhanced level set algorithm obtained better performance in ultrasound liver tumor segmentation related to graph-based algorithm.However,the proposed algorithm showed 3.11% improvement in dice coefficient compared to graph-based algorithm.Originality/value-The image preprocessing is carried out using CLAHE algorithm.The preprocessed image is segmented by employing selective level set model and Local Ternary Pattern in ARKFCM algorithm.In this research,the proposed algorithm has advantages such as independence of clustering parameters,robustness in preserving the image details and optimal in finding the threshold value that effectively reduces the computational cost.展开更多
Alzheimer’s Disease(AD)is a progressive neurodegenerative disorder that significantly affects cognitive function,making early and accurate diagnosis essential.Traditional Deep Learning(DL)-based approaches often stru...Alzheimer’s Disease(AD)is a progressive neurodegenerative disorder that significantly affects cognitive function,making early and accurate diagnosis essential.Traditional Deep Learning(DL)-based approaches often struggle with low-contrast MRI images,class imbalance,and suboptimal feature extraction.This paper develops a Hybrid DL system that unites MobileNetV2 with adaptive classification methods to boost Alzheimer’s diagnosis by processing MRI scans.Image enhancement is done using Contrast-Limited Adaptive Histogram Equalization(CLAHE)and Enhanced Super-Resolution Generative Adversarial Networks(ESRGAN).A classification robustness enhancement system integrates class weighting techniques and a Matthews Correlation Coefficient(MCC)-based evaluation method into the design.The trained and validated model gives a 98.88%accuracy rate and 0.9614 MCC score.We also performed a 10-fold cross-validation experiment with an average accuracy of 96.52%(±1.51),a loss of 0.1671,and an MCC score of 0.9429 across folds.The proposed framework outperforms the state-of-the-art models with a 98%weighted F1-score while decreasing misdiagnosis results for every AD stage.The model demonstrates apparent separation abilities between AD progression stages according to the results of the confusion matrix analysis.These results validate the effectiveness of hybrid DL models with adaptive preprocessing for early and reliable Alzheimer’s diagnosis,contributing to improved computer-aided diagnosis(CAD)systems in clinical practice.展开更多
In this paper we prove the uniform convergence of the standard multigrid V-cycle algorithm with the Gauss-Seidel relaxation performed only on the new nodes and their "immediate" neighbors for discrete ellipt...In this paper we prove the uniform convergence of the standard multigrid V-cycle algorithm with the Gauss-Seidel relaxation performed only on the new nodes and their "immediate" neighbors for discrete elliptic problems on the adaptively refined finite element meshes using the newest vertex bisection algorithm. The proof depends on sharp estimates on the relationship of local mesh sizes and a new stability estimate for the space decomposition based on the Scott-Zhang interpolation operator. Extensive numerical results are reported, which confirm the theoretical analysis.展开更多
Hierarchical identity-based signature （HIBS） has wide applications in the large network. However,the existing works cannot solve the trade-off between the security and efficiency. The main challenge at present is to...Hierarchical identity-based signature （HIBS） has wide applications in the large network. However,the existing works cannot solve the trade-off between the security and efficiency. The main challenge at present is to construct a high efficient and strong secure HIBS with a low computation cost. In this paper,a new construction of HIBS scheme is proposed. The new scheme achieves the adaptive security which is a strong security in the identity-based cryptography. But our scheme has short public parameters and the private keys size shrinks as the hierarchy depth increases. The signature size is a constant and the cost of verification only requires four bilinear pairings,which are independent of hierarchy depth. Furthermore,under the q-strong computational diffie-Hellman problem （q-SDH） assumption,the scheme is provably secure against existential forgery for adaptive chosen message and identity attack in the standard model.展开更多
A new wavelet-based image denoising algorithm, which exploits the edge information hidden in the corrupted image, is presented. Firstly, a canny-like edge detector identifies the edges in each subband. Secondly, multi...A new wavelet-based image denoising algorithm, which exploits the edge information hidden in the corrupted image, is presented. Firstly, a canny-like edge detector identifies the edges in each subband. Secondly, multiplying the wavelet coefficients in neighboring scales is implemented to suppress the noise while magnifying the edge information, and the result is utilized to exclude the fake edges. The isolated edge pixel is also identified as noise. Unlike the thresholding method, after that we use local window filter in the wavelet domain to remove noise in which the variance estimation is elaborated to utilize the edge intbrmation. This method is adaptive to local image details, and can achieve bet, ter performance than the methods of state of the art.展开更多
基金supported by the State Key Laboratory of Geo-Information Engineering(SKLGIE2022-Z-2-1)the National Natural Science Foundation of China(41674024,42174036).
文摘Once the spoofer has controlled the navigation sys-tem of unmanned aerial vehicle(UAV),it is hard to effectively control the error convergence to meet the threshold condition only by adjusting parameters of estimation if estimation of the spoofer on UAV has continuous observation error.Aiming at this problem,the influence of the spoofer’s state estimation error on spoofing effect and error convergence conditions is theoretically analyzed,and an improved adaptively robust estimation algo-rithm suitable for steady-state linear quadratic estimator is pro-posed.It enables the spoofer’s estimator to reliably estimate UAV status in real time,improves the robustness of the estima-tor in responding to observation errors,and accelerates the con-vergence time of error control.Simulation experiments show that the mean value of normalized innovation squared(NIS)is reduced by 88.5%,and the convergence time of NIS value is reduced by 76.3%,the convergence time of true trajectory error of UAV is reduced by 42.3%,the convergence time of estimated trajectory error of UAV is reduced by 67.4%,the convergence time of estimated trajectory error of the spoofer is reduced by 33.7%,and the convergence time of broadcast trajectory error of the spoofer is reduced by 54.8%when the improved algorithm is used.The improved algorithm can make UAV deviate from pre-set trajectory to spoofing trajectory more effectively and more subtly.
文摘Quadtree-based Cartesian grid was automatically generated from specified geometry.Adaptive refinements were performed according to geometric parameters and solution of flow field.An altered CCST(curvature corrected symmetry technique)approach was proposed to apply solid wall boundary conditions. Driven flows in a square cavity and flows around NACA0012airfoil were simulated and compared with the result of published structured grid and stretched Cartesian grid.The results show that solid wall boundary condition are accurately applied by current altered CCST approach,while incompressible/compressible subsonic, transonic and supersonic viscous flows are adequately simulated with adaptively refined Cartesian grid.
文摘Characteristic Basis Function Method (CBFM) is a novel approach for analyzing the ElectroMagnetic (EM) scattering from electrically large objects. Based on dividing the studied object into small blocks, the CBFM is suitable for parallel computing. In this paper, a static load balance parallel method is presented by combining Message Passing Interface (MPI) with Adaptively Modified CBFM (AMCBFM). In this method, the object geometry is partitioned into distinct blocks, and the serial number of blocks is sent to related nodes according to a certain rule. Every node only needs to calculate the information on local blocks. The obtained results confirm the accuracy and efficiency of the proposed method in speeding up solving large electrical scale problems.
基金the financial supports of the National Natural Science Foundation of China(No.51475233)the Fundamental Research Funds for Central Universities(No.NZ2016107)the Jiangsu Innovation Program for Graduate Education(No.CXLX13_139)
文摘Titanium hollow blades are characterized with lightweight and high structural strength, which are widely used in advanced aircraft engines nowadays. Superplastic forming/diffusion bonding （SPF/DB） combined with numerical control （NC） milling is a major solution for manufacturing titanium hollow blades. Due to the shape deviation caused by multiple heat and pressure cycles in the SPF/DB process, it is hard to manufacture the leading and tailing edges by the milling process. This paper presents a new adaptive machining approach using free-form deformation to solve this problem. The actual SPF/DB shape of a hollow blade was firstly inspected by an on-machine measurement method. The measured point data were matched to the nominal SPF/DB shape with an improved ICP algorithm afterwards, by which the point-pairs between the measurement points and their corresponding points on the nominal SPF/DB shape were established, and the maximum modification amount of the final nominal shape was constrained. Based on the displacements between the point-pairs, an accurate FFD volume was iteratively calculated. By embedding the final nominal shape in the deformation space, a new final shape of the hollow blade was built. Finally, a series of measurement and machining tests was performed, the results of which validated the feasibility of the proposed adaptive machining approach.
基金Supported by the National Natural Science Foundation of China （No.40174009, No.40274002）.
文摘Two kinds of fading filters and their principles are introduced. An adaptive robust filter is given with corresponding principle. The basic abilities of the fading filters and adaptively robust filter in controlling the influences of the kinematic model errors are analyzed. A practical example is given. The results of the fading filter and adaptively robust filter are compared and analyzed.
文摘The ant system algorithm （ASA） has proved to be a novel meta-heuristic algorithm to solve many multivariable problems. In this paper, the earth coverage of satellite constellation is analyzed and a n ＋ 1^ -fold coverage rate is put forward to evaluate the coverage performance of a satellite constellation. An optimization model of constellation parameters is established on the basis of the coverage performance. As a newly developed method, ASA can be applied to optimize the constellation parameters. In order to improve the ASA, a rule for adaptive number of ants is proposed, by which the search range is obviously enlarged and the convergence speed increased. Simulation results have shown that the ASA is more quick and efficient than other methodV211.71s.
基金supported in part by National Natural Science Foundation of China (61101114, 61671324) the Program for New Century Excellent Talents in University (NCET-12-0401)
文摘Forward-backward algorithm, used by watermark decoder for correcting non-binary synchronization errors, requires to traverse a very large scale trellis in order to achieve the proper posterior probability, leading to high computational complexity. In order to reduce the number of the states involved in the computation, an adaptive pruning method for the trellis is proposed. In this scheme, we prune the states which have the low forward-backward quantities below a carefully-chosen threshold. Thus, a wandering trellis with much less states is achieved, which contains most of the states with quite high probability. Simulation results reveal that, with the proper scaling factor, significant complexity reduction in the forward-backward algorithm is achieved at the expense of slight performance degradation.
文摘Attribute revocation is inevitable and al- so important for Attribute-Based Encryption （ABE） in practice. However, little attention has been paid to this issue, and it retrains one of the rmin obsta-cles for the application of ABE. Most of existing ABE schemes support attribute revocation work under indirect revocation model such that all the users＇ private keys will be affected when the revo-cation events occur. Though some ABE schemes have realized revocation under direct revocation model such that the revocation list is embedded in the ciphertext and none of the users＇ private keys will be affected by revocation, they mostly focused on the user revocation that revokes the user＇s whole attributes, or they can only be proven to be selectively secure. In this paper, we first define a model of adaptively secure ABE supporting the at- tribute revocation under direct revocation model. Then we propose a Key-Policy ABE （KP-ABE） scheme and a Ciphertext-Policy ABE （CP-ABE） scheme on composite order bilinear groups. Finally, we prove our schemes to be adaptively secure by employing the methodology of dual system eno cryption.
基金supported by the Department of Science & Technology, Government of India under research grant SR/S4/MS:318/06.
文摘Adaptive grid methods are established as valuable computational technique in approximating effectively the solutions of problems with boundary or interior layers. In this paper,we present the analysis of an upwind scheme for singularly perturbed differential-difference equation on a grid which is formed by equidistributing arc-length monitor function.It is shown that the discrete solution obtained converges uniformly with respect to the perturbation parameter.Numerical experiments illustrate in practice the result of convergence proved theoretically.
基金funding from the European Community's Seventh Framework Programme(FP7/2007-2013)under grant agreement n°222289
文摘Hybrid laser-MAG welding with real-time adaptive control has been demonstrated.Hybrid welding conditions have been developed to produce ISO 13919-1 class B (stringent) quality butt welds between 8mm thickness steel plates,using a 5kW 6mm.mrad Yb fibre laser combined with conventional arc welding equipment.A laser vision seam tracking system has enabled a 7-axis robot,manipulating the hybrid welding head,to track butt joints in real time during welding.The laser vision system has also provided information on the variations in joint fit-up,in particular the width of any gaps,or height of any mismatches present.This information has then been used to automatically adjust the robot position or speed,or arc welding parameters,depending on the fit-up detected.In this way,the tolerance of the hybrid process has been augmented,producing stringent quality welds over a wider range of joint fit-up cases than when using fixed conditions alone.
基金supported by National Natural Science Foundation of China(No.61561030)College Industry Support Plan Project of Gansu Provincial Department of Education(No.2021CYZC-04)Educational Reform Fund of Lanzhou Jiaotong University(No.JG201928)。
文摘In order to solve the problems of color bias and visual deviation caused by inaccurate estimation of transmittance and atmospheric light in image defogging,a new algorithm based on multi-scale morphological reconstruction with adaptive transmittance and atmospheric light correction was proposed.Firstly,the algorithm used the open operation under morphological reconstruction to replace the minimum filter operation in the dark channel,and used the morphological edge to set the scale of the open operation structure elements,and constructed a multi-scale open operation fusion dark channel.After morphological noise reduction,the exact initial transmittance was obtained.According to the relationship between brightness and saturation difference and transmittance,an adaptive transmittance correction model was fitted with Gaussian function to correct the initial transmittance of the sky fog map.Then the local atmospheric light was improved according to the image brightness information and morphology closure operation.Finally,the proposed algorithm was combined with the atmospheric scattering model to obtain an accurate fog free image.The experimental results showed that the proposed algorithm was suitable for fog image restoration under various scenes,the restoration effect was good,and the brightness was suitable.
基金support by the Air Force Office of Scientific Research under Grant No.FA9550-20-1-0358 and Grant No.FA9550-22-1-0004.
文摘Adaptive mesh refinement (AMR) is fairly practiced in the context of high-dimensional, mesh-based computational models. However, it is in its infancy in that of low-dimensional, generalized-coordinate-based computational models such as projection-based reduced-order models. This paper presents a complete framework for projection-based model order reduction (PMOR) of nonlinear problems in the presence of AMR that builds on elements from existing methods and augments them with critical new contributions. In particular, it proposes an analytical algorithm for computing a pseudo-meshless inner product between adapted solution snapshots for the purpose of clustering and PMOR. It exploits hyperreduction—specifically, the energy-conserving sampling and weighting hyperreduction method—to deliver for nonlinear and/or parametric problems the desired computational gains. Most importantly, the proposed framework for PMOR in the presence of AMR capitalizes on the concept of state-local reduced-order bases to make the most of the notion of a supermesh, while achieving computational tractability. Its features are illustrated with CFD applications grounded in AMR and its significance is demonstrated by the reported wall-clock speedup factors.
基金supported by the International cooperation project of Qilu University of Technology(Grant No.QLUTGJHZ2018022).
文摘A slip-draft embedded control system was designed and developed for an independent developed 2WD(two-wheel drive)electric tractor,to improve the traction efficiency,operation performance and ploughing depth stability of the electric tractor.In this system,the battery of electric tractor was innovatively equivalent to the original counterweight of the fuel tractor.And through dynamic analysis of electric tractor during ploughing,the mathematical model of adjusting the center of gravity about draft force and slip rate was established.Then the automatic adjustment of the center of gravity for electric tractor was realized through the adaptive adjustment of battery position.Finally,the system was carried on electric tractor for performance evaluation under different ploughing conditions,the traction efficiency,slip rate and front wheel load of electric tractor were measured and controlled synchronously to make it close to the set range.And the comparative experiments of ploughing operation were carried out under the two modes of adaptive adjustment of center of gravity and fixed center of gravity.The test results showed that,based on the developed control system,the center of gravity of electric tractor can be adjusted in real time according to the complex changes of working conditions.During ploughing operation with adjusting adaptively battery position,the average values of traction efficiency,slip rate,front wheel load and relative error of tillage depth of electric tractor were 64.5%,22.2%,2045.0 N and 2.0%respectively.Which were optimized by 15.0%,29.5%,19.6%and 80.0%respectively,compared with electric tractor with fixed battery position.The slip-draft embedded control system can not only realize the adaptive adjustment of the center of gravity position in the ploughing process of electric tractor,but also improve the traction efficiency and the stability of ploughing depth,which can provide reference for the actual production operation of electric tractor.
基金National Natural Science Foundation of China(Grant No.11301462)University Science Research Project of Jiangsu Province(Grant No.13KJB110030)Yangzhou University Overseas Study Program and New Century Talent Project to Shan Jiang。
文摘We apply the multiscale basis functions for the singularly perturbed reaction-diffusion problem on adaptively graded meshes,which can provide a good balance between the numerical accuracy and computational cost.The multiscale space is built through standard finite element basis functions enriched with multiscale basis functions.The multiscale basis functions have abilities to capture originally perturbed information in the local problem,as a result our method is capable of reducing the boundary layer errors remarkably on graded meshes,where the layer-adapted meshes are generated by a given parameter.Through numerical experiments we demonstrate that the multiscale method can acquire second order convergence in the L^(2)norm and first order convergence in the energy norm on graded meshes,which is independent ofε.In contrast with the conventional methods,our method is much more accurate and effective.
文摘When evaluating the performance of distributed software-defined network(SDN)controller architecture in data center networks,the required number of controllers for a given network topology and their location are major issues of interest.To address these issues,this study proposes the adaptively adjusting and mapping controllers(AAMcon)to design a stateful data plane.We use the complex network community theory to select a key switch to place the controller which is closer to switches it controls in a subnet.A physically distributed but logically centralized controller pool is built based on the network function virtualization(NFV).And then we propose a fast start/overload avoid algorithm to adaptively adjust the number of controllers according to the demand.We performed an analysis for AAMcon to find the optimal distance between the switch and controller.Finally,experiments show the following results.(1)For the number of controllers,AAMcon can greatly follow the demand;for the placement location of controller,controller can respond to the request of switch with the least distance to minimize the delay between the switch and it.(2)For failure tolerance,AAMcon shows good robustness.(3)AAMcon requires less delay to the network with more significant community structure.In fact,there is an inverse relationship between the community modularity and average distance between the switch and controller,i.e.,the average delay decreases when the community modularity increases.(4)AAMcon can achieve the load balance between the controllers.(5)Compared to DCP-GK and k-critical,AAMcon shows good performance.
文摘Purpose-The purpose of this study is to develop a hybrid algorithm for segmenting tumor from ultrasound images of the liver.Design/methodology/approach-After collecting the ultrasound images,contrast-limited adaptive histogram equalization approach(CLAHE)is applied as preprocessing,in order to enhance the visual quality of the images that helps in better segmentation.Then,adaptively regularized kernel-based fuzzy C means(ARKFCM)is used to segment tumor from the enhanced image along with local ternary pattern combined with selective level set approaches.Findings-The proposed segmentation algorithm precisely segments the tumor portions from the enhanced images with lower computation cost.The proposed segmentation algorithm is compared with the existing algorithms and ground truth values in terms of Jaccard coefficient,dice coefficient,precision,Matthews correlation coefficient,f-score and accuracy.The experimental analysis shows that the proposed algorithm achieved 99.18% of accuracy and 92.17% of f-score value,which is better than the existing algorithms.Practical implications-From the experimental analysis,the proposed ARKFCM with enhanced level set algorithm obtained better performance in ultrasound liver tumor segmentation related to graph-based algorithm.However,the proposed algorithm showed 3.11% improvement in dice coefficient compared to graph-based algorithm.Originality/value-The image preprocessing is carried out using CLAHE algorithm.The preprocessed image is segmented by employing selective level set model and Local Ternary Pattern in ARKFCM algorithm.In this research,the proposed algorithm has advantages such as independence of clustering parameters,robustness in preserving the image details and optimal in finding the threshold value that effectively reduces the computational cost.
基金funded by the Deanship of Graduate Studies and Scientific Research at Jouf University under grant No.(DGSSR-2025-02-01295).
文摘Alzheimer’s Disease(AD)is a progressive neurodegenerative disorder that significantly affects cognitive function,making early and accurate diagnosis essential.Traditional Deep Learning(DL)-based approaches often struggle with low-contrast MRI images,class imbalance,and suboptimal feature extraction.This paper develops a Hybrid DL system that unites MobileNetV2 with adaptive classification methods to boost Alzheimer’s diagnosis by processing MRI scans.Image enhancement is done using Contrast-Limited Adaptive Histogram Equalization(CLAHE)and Enhanced Super-Resolution Generative Adversarial Networks(ESRGAN).A classification robustness enhancement system integrates class weighting techniques and a Matthews Correlation Coefficient(MCC)-based evaluation method into the design.The trained and validated model gives a 98.88%accuracy rate and 0.9614 MCC score.We also performed a 10-fold cross-validation experiment with an average accuracy of 96.52%(±1.51),a loss of 0.1671,and an MCC score of 0.9429 across folds.The proposed framework outperforms the state-of-the-art models with a 98%weighted F1-score while decreasing misdiagnosis results for every AD stage.The model demonstrates apparent separation abilities between AD progression stages according to the results of the confusion matrix analysis.These results validate the effectiveness of hybrid DL models with adaptive preprocessing for early and reliable Alzheimer’s diagnosis,contributing to improved computer-aided diagnosis(CAD)systems in clinical practice.
基金The first author was supported in part by the National Natural Science Foundation of China(Grant No.10401016)by the National Basic Research Program(Grant No.2005CB321701)+1 种基金The second author was supported in part by the National Natural Science Foundation of China(Grant No.10025102)by China MOS(Grant No.G1999032802).
文摘In this paper we prove the uniform convergence of the standard multigrid V-cycle algorithm with the Gauss-Seidel relaxation performed only on the new nodes and their "immediate" neighbors for discrete elliptic problems on the adaptively refined finite element meshes using the newest vertex bisection algorithm. The proof depends on sharp estimates on the relationship of local mesh sizes and a new stability estimate for the space decomposition based on the Scott-Zhang interpolation operator. Extensive numerical results are reported, which confirm the theoretical analysis.
基金supported by the National Natural Science Foundation of China (60970119, 60803149)the National Basic Research Program of China (2007CB311201)the Fundamental Research Funds for the Central Universities
文摘Hierarchical identity-based signature （HIBS） has wide applications in the large network. However,the existing works cannot solve the trade-off between the security and efficiency. The main challenge at present is to construct a high efficient and strong secure HIBS with a low computation cost. In this paper,a new construction of HIBS scheme is proposed. The new scheme achieves the adaptive security which is a strong security in the identity-based cryptography. But our scheme has short public parameters and the private keys size shrinks as the hierarchy depth increases. The signature size is a constant and the cost of verification only requires four bilinear pairings,which are independent of hierarchy depth. Furthermore,under the q-strong computational diffie-Hellman problem （q-SDH） assumption,the scheme is provably secure against existential forgery for adaptive chosen message and identity attack in the standard model.
基金This work was supported by the National "863" Pro- gram of China under Grant No. 2004AA119010.
文摘A new wavelet-based image denoising algorithm, which exploits the edge information hidden in the corrupted image, is presented. Firstly, a canny-like edge detector identifies the edges in each subband. Secondly, multiplying the wavelet coefficients in neighboring scales is implemented to suppress the noise while magnifying the edge information, and the result is utilized to exclude the fake edges. The isolated edge pixel is also identified as noise. Unlike the thresholding method, after that we use local window filter in the wavelet domain to remove noise in which the variance estimation is elaborated to utilize the edge intbrmation. This method is adaptive to local image details, and can achieve bet, ter performance than the methods of state of the art.
