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
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
In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to ...In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.展开更多
Convex feasibility problems are widely used in image reconstruction,sparse signal recovery,and other areas.This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recovery...Convex feasibility problems are widely used in image reconstruction,sparse signal recovery,and other areas.This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recovery.We rst derive the projection formulas for a vector onto the feasible sets.The centralized circumcentered-reection method is designed to solve the convex feasibility problem.Some numerical experiments demonstrate the feasibility and e ectiveness of the proposed algorithm,showing superior performance compared to conventional alternating projection methods.展开更多
Marine thin plates are susceptible to welding deformation owing to their low structural stiffness.Therefore,the efficient and accurate prediction of welding deformation is essential for improving welding quality.The t...Marine thin plates are susceptible to welding deformation owing to their low structural stiffness.Therefore,the efficient and accurate prediction of welding deformation is essential for improving welding quality.The traditional thermal elastic-plastic finite element method(TEP-FEM)can accurately predict welding deformation.However,its efficiency is low because of the complex nonlinear transient computation,making it difficult to meet the needs of rapid engineering evaluation.To address this challenge,this study proposes an efficient prediction method for welding deformation in marine thin plate butt welds.This method is based on the coupled temperature gradient-thermal strain method(TG-TSM)that integrates inherent strain theory with a shell element finite element model.The proposed method first extracts the distribution pattern and characteristic value of welding-induced inherent strain through TEP-FEM analysis.This strain is then converted into the equivalent thermal load applied to the shell element model for rapid computation.The proposed method-particularly,the gradual temperature gradient-thermal strain method(GTG-TSM)-achieved improved computational efficiency and consistent precision.Furthermore,the proposed method required much less computation time than the traditional TEP-FEM.Thus,this study lays the foundation for future prediction of welding deformation in more complex marine thin plates.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
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
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
Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters accordi...Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.展开更多
To analyze the differences in the transport and distribution of different types of proppants and to address issues such as the short effective support of proppant and poor placement in hydraulically intersecting fract...To analyze the differences in the transport and distribution of different types of proppants and to address issues such as the short effective support of proppant and poor placement in hydraulically intersecting fractures,this study considered the combined impact of geological-engineering factors on conductivity.Using reservoir production parameters and the discrete elementmethod,multispherical proppants were constructed.Additionally,a 3D fracture model,based on the specified conditions of the L block,employed coupled(Computational Fluid Dynamics)CFD-DEM(Discrete ElementMethod)for joint simulations to quantitatively analyze the transport and placement patterns of multispherical proppants in intersecting fractures.Results indicate that turbulent kinetic energy is an intrinsic factor affecting proppant transport.Moreover,the efficiency of placement and migration distance of low-sphericity quartz sand constructed by the DEM in the main fracture are significantly reduced compared to spherical ceramic proppants,with a 27.7%decrease in the volume fraction of the fracture surface,subsequently affecting the placement concentration and damaging fracture conductivity.Compared to small-angle fractures,controlling artificial and natural fractures to expand at angles of 45°to 60°increases the effective support length by approximately 20.6%.During hydraulic fracturing of gas wells,ensuring the fracture support area and post-closure conductivity can be achieved by controlling the sphericity of proppants and adjusting the perforation direction to control the direction of artificial fractures.展开更多
This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standar...This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standard system was established for comprehensive quality evaluation of HTD.There were obvious changes in the physicochemical properties,enzyme activities,and volatile flavor components at different storage periods,which affected the sensory evaluation of HTD to a certain extent.The results of high-throughput sequencing revealed significant microbial diversity,and showed that the bacterial community changed significantly more than did the fungal community.During the storage process,the dominant bacterial genera were Kroppenstedtia and Thermoascus.The correlation between dominant microorganisms and quality indicators highlighted their role in HTD quality.Lactococcus,Candida,Pichia,Paecilomyces,and protease activity played a crucial role in the formation of isovaleraldehyde.Acidic protease activity had the greatest impact on the microbial community.Moisture promoted isobutyric acid generation.Furthermore,the comprehensive quality evaluation standard system was established by the entropy weight method combined with multi-factor fuzzy mathematics.Consequently,this study provides innovative insights for comprehensive quality evaluation of HTD during storage and establishes a groundwork for scientific and rational storage of HTD and quality control of sauce-flavor Baijiu.展开更多
Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this cha...Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this challenge,nonlinear stress boundaries for a numerical model are determined through regression analysis of a series of nonlinear coefficient matrices,which are derived from the bubbling method.Considering the randomness and flexibility of the bubbling method,a parametric study is conducted to determine recommended ranges for these parameters,including the standard deviation(σb)of bubble radii,the non-uniform coefficient matrix number(λ)for nonlinear stress boundaries,and the number(m)and positions of in situ stress measurement points.A model case study provides a reference for the selection of these parameters.Additionally,when the nonlinear in situ stress inversion method is employed,stress distortion inevitably occurs near model boundaries,aligning with the Saint Venant's principle.Two strategies are proposed accordingly:employing a systematic reduction of nonlinear coefficients to achieve high inversion accuracy while minimizing significant stress distortion,and excluding regions with severe stress distortion near the model edges while utilizing the central part of the model for subsequent simulations.These two strategies have been successfully implemented in the nonlinear in situ stress inversion of the Xincheng Gold Mine and have achieved higher inversion accuracy than the linear method.Specifically,the linear and nonlinear inversion methods yield root mean square errors(RMSE)of 4.15 and 3.2,and inversion relative errors(δAve)of 22.08%and 17.55%,respectively.Therefore,the nonlinear inversion method outperforms the traditional multiple linear regression method,even in the presence of a systematic reduction in the nonlinear stress boundaries.展开更多
The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytica...The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytical solutions for free vibration and eigenbuckling of rectangular plates and circular cylindrical shells.By taking the free vibration of rectangular thin plates as an example,this work presents the theoretical framework of the SOV methods in an instructive way,and the bisection–based solution procedures for a group of nonlinear eigenvalue equations.Besides,the explicit equations of nodal lines of the SOV methods are presented,and the relations of nodal line patterns and frequency orders are investigated.It is concluded that the highly accurate SOV methods have the same accuracy for all frequencies,the mode shapes about repeated frequencies can also be precisely captured,and the SOV methods do not have the problem of missing roots as well.展开更多
Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vi...Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vironment and intensify carbon emissions.However,the use of microbially induced calcium carbonate pre-cipitation(MICP)to obtain bio-cement is a novel technique with the potential to induce soil stability,providing a low-carbon,environment-friendly,and sustainable integrated solution for some geotechnical engineering pro-blems in the environment.This paper presents a comprehensive review of the latest progress in soil improvement based on the MICP strategy.It systematically summarizes and overviews the mineralization mechanism,influ-encing factors,improved methods,engineering characteristics,and current field application status of the MICP.Additionally,it also explores the limitations and correspondingly proposes prospective applications via the MICP approach for soil improvement.This review indicates that the utilization of different environmental calcium-based wastes in MICP and combination of materials and MICP are conducive to meeting engineering and market demand.Furthermore,we recommend and encourage global collaborative study and practice with a view to commercializing MICP technique in the future.The current review purports to provide insights for engineers and interdisciplinary researchers,and guidance for future engineering applications.展开更多
Bearing is an indispensable key component in mechanical equipment,and its working state is directly related to the stability and safety of the whole equipment.In recent years,with the rapid development of artificial i...Bearing is an indispensable key component in mechanical equipment,and its working state is directly related to the stability and safety of the whole equipment.In recent years,with the rapid development of artificial intelligence technology,especially the breakthrough of deep learning technology,it provides a new idea for bearing fault diagnosis.Deep learning can automatically learn features from a large amount of data,has a strong nonlinear modeling ability,and can effectively solve the problems existing in traditional methods.Aiming at the key problems in bearing fault diagnosis,this paper studies the fault diagnosis method based on deep learning,which not only provides a new solution for bearing fault diagnosis but also provides a reference for the application of deep learning in other mechanical fault diagnosis fields.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.
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 in part by Natural Science Foundation of Guangxi(2023GXNSFAA026246)in part by the Central Government's Guide to Local Science and Technology Development Fund(GuikeZY23055044)in part by the National Natural Science Foundation of China(62363003)。
文摘In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.
基金Supported by the Natural Science Foundation of Guangxi Province(Grant Nos.2023GXNSFAA026067,2024GXN SFAA010521)the National Natural Science Foundation of China(Nos.12361079,12201149,12261026).
文摘Convex feasibility problems are widely used in image reconstruction,sparse signal recovery,and other areas.This paper is devoted to considering a class of convex feasibility problem arising from sparse signal recovery.We rst derive the projection formulas for a vector onto the feasible sets.The centralized circumcentered-reection method is designed to solve the convex feasibility problem.Some numerical experiments demonstrate the feasibility and e ectiveness of the proposed algorithm,showing superior performance compared to conventional alternating projection methods.
基金Supported by the National Natural Science Foundation of China under Grant No.51975138the High-Tech Ship Scientific Research Project from the Ministry of Industry and Information Technology under Grant No.CJ05N20the National Defense Basic Research Project under Grant No.JCKY2023604C006.
文摘Marine thin plates are susceptible to welding deformation owing to their low structural stiffness.Therefore,the efficient and accurate prediction of welding deformation is essential for improving welding quality.The traditional thermal elastic-plastic finite element method(TEP-FEM)can accurately predict welding deformation.However,its efficiency is low because of the complex nonlinear transient computation,making it difficult to meet the needs of rapid engineering evaluation.To address this challenge,this study proposes an efficient prediction method for welding deformation in marine thin plate butt welds.This method is based on the coupled temperature gradient-thermal strain method(TG-TSM)that integrates inherent strain theory with a shell element finite element model.The proposed method first extracts the distribution pattern and characteristic value of welding-induced inherent strain through TEP-FEM analysis.This strain is then converted into the equivalent thermal load applied to the shell element model for rapid computation.The proposed method-particularly,the gradual temperature gradient-thermal strain method(GTG-TSM)-achieved improved computational efficiency and consistent precision.Furthermore,the proposed method required much less computation time than the traditional TEP-FEM.Thus,this study lays the foundation for future prediction of welding deformation in more complex marine thin plates.
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.
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 Innovation Foundation of Provincial Education Department of Gansu(2024B-005)the Gansu Province National Science Foundation(22YF7GA182)the Fundamental Research Funds for the Central Universities(No.lzujbky2022-kb01)。
文摘Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure.Therefore,it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring(SHM)system,so as to provide a scientific basis for structural damage identification and dynamic model modification.In view of this,this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters.The paper primarily introduces data-driven modal parameter recognition methods(e.g.,time-domain,frequency-domain,and time-frequency-domain methods,etc.),briefly describes damage identification methods based on the variations of modal parameters(e.g.,natural frequency,modal shapes,and curvature modal shapes,etc.)and modal validation methods(e.g.,Stability Diagram and Modal Assurance Criterion,etc.).The current status of the application of artificial intelligence(AI)methods in the direction of modal parameter recognition and damage identification is further discussed.Based on the pre-vious analysis,the main development trends of structural modal parameter recognition and damage identification methods are given to provide scientific references for the optimized design and functional upgrading of SHM systems.
基金funded by the project of the Major Scientific and Technological Projects of CNOOC in the 14th Five-Year Plan(No.KJGG2022-0701)the CNOOC Research Institute(No.2020PFS-03).
文摘To analyze the differences in the transport and distribution of different types of proppants and to address issues such as the short effective support of proppant and poor placement in hydraulically intersecting fractures,this study considered the combined impact of geological-engineering factors on conductivity.Using reservoir production parameters and the discrete elementmethod,multispherical proppants were constructed.Additionally,a 3D fracture model,based on the specified conditions of the L block,employed coupled(Computational Fluid Dynamics)CFD-DEM(Discrete ElementMethod)for joint simulations to quantitatively analyze the transport and placement patterns of multispherical proppants in intersecting fractures.Results indicate that turbulent kinetic energy is an intrinsic factor affecting proppant transport.Moreover,the efficiency of placement and migration distance of low-sphericity quartz sand constructed by the DEM in the main fracture are significantly reduced compared to spherical ceramic proppants,with a 27.7%decrease in the volume fraction of the fracture surface,subsequently affecting the placement concentration and damaging fracture conductivity.Compared to small-angle fractures,controlling artificial and natural fractures to expand at angles of 45°to 60°increases the effective support length by approximately 20.6%.During hydraulic fracturing of gas wells,ensuring the fracture support area and post-closure conductivity can be achieved by controlling the sphericity of proppants and adjusting the perforation direction to control the direction of artificial fractures.
文摘This study investigated the physicochemical properties,enzyme activities,volatile flavor components,microbial communities,and sensory evaluation of high-temperature Daqu(HTD)during the maturation process,and a standard system was established for comprehensive quality evaluation of HTD.There were obvious changes in the physicochemical properties,enzyme activities,and volatile flavor components at different storage periods,which affected the sensory evaluation of HTD to a certain extent.The results of high-throughput sequencing revealed significant microbial diversity,and showed that the bacterial community changed significantly more than did the fungal community.During the storage process,the dominant bacterial genera were Kroppenstedtia and Thermoascus.The correlation between dominant microorganisms and quality indicators highlighted their role in HTD quality.Lactococcus,Candida,Pichia,Paecilomyces,and protease activity played a crucial role in the formation of isovaleraldehyde.Acidic protease activity had the greatest impact on the microbial community.Moisture promoted isobutyric acid generation.Furthermore,the comprehensive quality evaluation standard system was established by the entropy weight method combined with multi-factor fuzzy mathematics.Consequently,this study provides innovative insights for comprehensive quality evaluation of HTD during storage and establishes a groundwork for scientific and rational storage of HTD and quality control of sauce-flavor Baijiu.
基金funded by the National Key R&D Program of China(Grant No.2022YFC2903904)the National Natural Science Foundation of China(Grant Nos.51904057 and U1906208).
文摘Due to the heterogeneity of rock masses and the variability of in situ stress,the traditional linear inversion method is insufficiently accurate to achieve high accuracy of the in situ stress field.To address this challenge,nonlinear stress boundaries for a numerical model are determined through regression analysis of a series of nonlinear coefficient matrices,which are derived from the bubbling method.Considering the randomness and flexibility of the bubbling method,a parametric study is conducted to determine recommended ranges for these parameters,including the standard deviation(σb)of bubble radii,the non-uniform coefficient matrix number(λ)for nonlinear stress boundaries,and the number(m)and positions of in situ stress measurement points.A model case study provides a reference for the selection of these parameters.Additionally,when the nonlinear in situ stress inversion method is employed,stress distortion inevitably occurs near model boundaries,aligning with the Saint Venant's principle.Two strategies are proposed accordingly:employing a systematic reduction of nonlinear coefficients to achieve high inversion accuracy while minimizing significant stress distortion,and excluding regions with severe stress distortion near the model edges while utilizing the central part of the model for subsequent simulations.These two strategies have been successfully implemented in the nonlinear in situ stress inversion of the Xincheng Gold Mine and have achieved higher inversion accuracy than the linear method.Specifically,the linear and nonlinear inversion methods yield root mean square errors(RMSE)of 4.15 and 3.2,and inversion relative errors(δAve)of 22.08%and 17.55%,respectively.Therefore,the nonlinear inversion method outperforms the traditional multiple linear regression method,even in the presence of a systematic reduction in the nonlinear stress boundaries.
基金supported by the National Natural Science Foundation of China(12172023).
文摘The separation-of-variable(SOV)methods,such as the improved SOV method,the variational SOV method,and the extended SOV method,have been proposed by the present authors and coworkers to obtain the closed-form analytical solutions for free vibration and eigenbuckling of rectangular plates and circular cylindrical shells.By taking the free vibration of rectangular thin plates as an example,this work presents the theoretical framework of the SOV methods in an instructive way,and the bisection–based solution procedures for a group of nonlinear eigenvalue equations.Besides,the explicit equations of nodal lines of the SOV methods are presented,and the relations of nodal line patterns and frequency orders are investigated.It is concluded that the highly accurate SOV methods have the same accuracy for all frequencies,the mode shapes about repeated frequencies can also be precisely captured,and the SOV methods do not have the problem of missing roots as well.
基金funded by the National Natural Science Foundation of China(No.41962016)the Natural Science Foundation of NingXia(Nos.2023AAC02023,2023A1218,and 2021AAC02006).
文摘Soil improvement is one of the most important issues in geotechnical engineering practice.The wide application of traditional improvement techniques(cement/chemical materials)are limited due to damage ecological en-vironment and intensify carbon emissions.However,the use of microbially induced calcium carbonate pre-cipitation(MICP)to obtain bio-cement is a novel technique with the potential to induce soil stability,providing a low-carbon,environment-friendly,and sustainable integrated solution for some geotechnical engineering pro-blems in the environment.This paper presents a comprehensive review of the latest progress in soil improvement based on the MICP strategy.It systematically summarizes and overviews the mineralization mechanism,influ-encing factors,improved methods,engineering characteristics,and current field application status of the MICP.Additionally,it also explores the limitations and correspondingly proposes prospective applications via the MICP approach for soil improvement.This review indicates that the utilization of different environmental calcium-based wastes in MICP and combination of materials and MICP are conducive to meeting engineering and market demand.Furthermore,we recommend and encourage global collaborative study and practice with a view to commercializing MICP technique in the future.The current review purports to provide insights for engineers and interdisciplinary researchers,and guidance for future engineering applications.
文摘Bearing is an indispensable key component in mechanical equipment,and its working state is directly related to the stability and safety of the whole equipment.In recent years,with the rapid development of artificial intelligence technology,especially the breakthrough of deep learning technology,it provides a new idea for bearing fault diagnosis.Deep learning can automatically learn features from a large amount of data,has a strong nonlinear modeling ability,and can effectively solve the problems existing in traditional methods.Aiming at the key problems in bearing fault diagnosis,this paper studies the fault diagnosis method based on deep learning,which not only provides a new solution for bearing fault diagnosis but also provides a reference for the application of deep learning in other mechanical fault diagnosis fields.
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.
