Multi-label feature selection(MFS)is a crucial dimensionality reduction technique aimed at identifying informative features associated with multiple labels.However,traditional centralized methods face significant chal...Multi-label feature selection(MFS)is a crucial dimensionality reduction technique aimed at identifying informative features associated with multiple labels.However,traditional centralized methods face significant challenges in privacy-sensitive and distributed settings,often neglecting label dependencies and suffering from low computational efficiency.To address these issues,we introduce a novel framework,Fed-MFSDHBCPSO—federated MFS via dual-layer hybrid breeding cooperative particle swarm optimization algorithm with manifold and sparsity regularization(DHBCPSO-MSR).Leveraging the federated learning paradigm,Fed-MFSDHBCPSO allows clients to perform local feature selection(FS)using DHBCPSO-MSR.Locally selected feature subsets are encrypted with differential privacy(DP)and transmitted to a central server,where they are securely aggregated and refined through secure multi-party computation(SMPC)until global convergence is achieved.Within each client,DHBCPSO-MSR employs a dual-layer FS strategy.The inner layer constructs sample and label similarity graphs,generates Laplacian matrices to capture the manifold structure between samples and labels,and applies L2,1-norm regularization to sparsify the feature subset,yielding an optimized feature weight matrix.The outer layer uses a hybrid breeding cooperative particle swarm optimization algorithm to further refine the feature weight matrix and identify the optimal feature subset.The updated weight matrix is then fed back to the inner layer for further optimization.Comprehensive experiments on multiple real-world multi-label datasets demonstrate that Fed-MFSDHBCPSO consistently outperforms both centralized and federated baseline methods across several key evaluation metrics.展开更多
For positioning a moving target, a maximum intensity projection (MIP) or average intensity projection (AIP) image derived from 4DCT is often used as the reference image which is matched to free breathing cone-beam CT ...For positioning a moving target, a maximum intensity projection (MIP) or average intensity projection (AIP) image derived from 4DCT is often used as the reference image which is matched to free breathing cone-beam CT (FBCBCT) before treatment. This method can be highly accurate if the respiratory motion of the patient is stable. However, a patient’s breathing pattern is often irregular. The purpose of this study is to investigate the effects of irregular respiration on positioning accuracy for a moving target aligned with FBCBCT. Nine patients’ respiratory motion curves were selected to drive a Quasar motion phantom with one embedded cubic and two spherical targets. A 4DCT of the phantom was acquired on a CT scanner (Philips Brilliance 16) equipped with a Varian RPM system. The phase binned 4DCT images and the corresponding MIP and AIP images were transferred into Eclipse for analysis. FBCBCTs of the phantom driven by the same respiratory curves were also acquired on a Varian TrueBeam and fused such that both CBCT and MIP/AIP images share the same target zero positions. The sphere and cube volumes and centroid differences (alignment error) determined by MIP, AIP and FBCBCT images were calculated, respectively. Compared to the volume determined by MIP, the volumes of the cube, large sphere, and small sphere in AIP and FBCBCT images were smaller. The alignment errors for the cube, large sphere and small sphere with center to center matches between MIP and FBCBCT were 2.5 ± 1.8 mm, 2.4 ± 2.1 mm, and 3.8 ± 2.8 mm, and the alignment errors between AIP and FBCBCT were 0.5 ± 1.1 mm, 0.3 ± 0.8 mm, and 1.8 ± 2.0 mm, respectively. AIP images appear to be superior reference images to MIP images. However, irregular respiratory pattern could compromise the positioning accuracy, especially for smaller targets.展开更多
In this paper,various extended contractions are introduced as generalizations of some existing contractions given by Kannan,Ciric,Reich and Gornicki,et al.Then,several meaningful results about asymptotically regular m...In this paper,various extended contractions are introduced as generalizations of some existing contractions given by Kannan,Ciric,Reich and Gornicki,et al.Then,several meaningful results about asymptotically regular mappings in cone metric spaces over Banach algebras are obtained,weakening the completeness of the spaces and the continuity of the mappings.Moreover,some nontrivial examples are showed to verify the innovation of the new concepts and our fxed point theorems.展开更多
The finite volume method was applied to numerically simulate the bottom pressure field induced by regular waves,vehicles in calm water and vehicles in regular waves.The solution of Navier-Stokes(N-S)equations in the v...The finite volume method was applied to numerically simulate the bottom pressure field induced by regular waves,vehicles in calm water and vehicles in regular waves.The solution of Navier-Stokes(N-S)equations in the vicinity of numerical wave tank's boundary was forced towards the wave theoretical solution by incorporating momentum source terms,thereby reducing adverse effects such as wave reflection.Simulations utilizing laminar flow,turbulent flow,and ideal fluid models were all found capable of effectively capturing the waveform and bottom pressure of regular waves,agreeing well with experimental data.In predicting the bottom pressure field of the submerged vehicle,turbulent simulations considering fluid viscosity and boundary layer development provided more accurate predictions for the stern region than inviscid simulations.Due to sphere's diffractive effect,the sphere's bottom pressure field in waves is not a linear superposition of the wave's and the sphere's bottom pressure field.However,a slender submerged vehicle exhibits a weaker diffractive effect on waves,thus the submerged vehicle's bottom pressure field in waves can be approximated as a linear superposition of the wave's and the submerged vehicle's bottom pressure field,which simplifies computation and analysis.展开更多
This paper delves into the baseline design under the baseline parameterization model in experimental design, focusing on the relationship between the K-aberration criterion and the word length pattern (WLP) of regular...This paper delves into the baseline design under the baseline parameterization model in experimental design, focusing on the relationship between the K-aberration criterion and the word length pattern (WLP) of regular two-level designs. The paper provides a detailed analysis of the relationship between K5and the WLP for regular two-level designs with resolution t=3, and proposes corresponding theoretical results. These results not only theoretically reveal the connection between the orthogonal parameterization model and the baseline parameterization model but also provide theoretical support for finding the K-aberration optimal regular two-level baseline designs. It demonstrates how to apply these theories to evaluate and select the optimal experimental designs. In practical applications, experimental designers can utilize the theoretical results of this paper to quickly assess and select regular two-level baseline designs with minimal K-aberration by analyzing the WLP of the experimental design. This allows for the identification of key factors that significantly affect the experimental outcomes without frequently changing the factor levels, thereby maximizing the benefits of the experiment.展开更多
On a compact Riemann surface with finite punctures P_(1),…P_(k),we define toric curves as multivalued,totallyunramified holomorphic maps to P^(n)with monodromy in a maximal torus of PSU(n+1).Toric solutions to SU(n+1...On a compact Riemann surface with finite punctures P_(1),…P_(k),we define toric curves as multivalued,totallyunramified holomorphic maps to P^(n)with monodromy in a maximal torus of PSU(n+1).Toric solutions to SU(n+1)Todasystems on X\{P_(1);…;P_(k)}are recognized by the associated toric curves in.We introduce character n-ensembles as-tuples of meromorphic one-forms with simple poles and purely imaginary periods,generating toric curves on minus finitelymany points.On X,we establish a correspondence between character-ensembles and toric solutions to the SU(n+1)system with finitely many cone singularities.Our approach not only broadens seminal solutions with two conesingularities on the Riemann sphere,as classified by Jost-Wang(Int.Math.Res.Not.,2002,(6):277-290)andLin-Wei-Ye(Invent.Math.,2012,190(1):169-207),but also advances beyond the limits of Lin-Yang-Zhong’s existencetheorems(J.Differential Geom.,2020,114(2):337-391)by introducing a new solution class.展开更多
Toric patch is a kind of rational multisided patch,which is associated with a finite integer lattice points set A.A set of weights is defined which depend on a parameter according to regular decomposition of A.When al...Toric patch is a kind of rational multisided patch,which is associated with a finite integer lattice points set A.A set of weights is defined which depend on a parameter according to regular decomposition of A.When all weights of the patch tend to infinity,we obtain the limiting form of toric patch which is called its regular control surface.The diferent weights may induce the diferent regular control surfaces of the same toric patch.It prompts us to consider that how many regular control surfaces of a toric patch.In this paper,we study the regular decompositions of A by using integer programming method firstly,and then provide the relationship between all regular decompositions of A and corresponding state polytope.Moreover,we present that the number of regular control surfaces of a toric patch associated with A is equal to the number of regular decompositions of A.An algorithm to calculate the number of regular control surfaces of toric patch is provided.The algorithm also presents a method to construct all of the regular control surfaces of a toric patch.At last,the application of proposed result in shape deformation is demonstrated by several examples.展开更多
Geotechnical parameters derived from an intrusive cone penetration test(CPT)are used to asses mechanical properties to inform the design phase of infrastructure projects.However,local,in situ 1D measurements can fail ...Geotechnical parameters derived from an intrusive cone penetration test(CPT)are used to asses mechanical properties to inform the design phase of infrastructure projects.However,local,in situ 1D measurements can fail to capture 3D subsurface variations,which could mean less than optimal design decisions for foundation engineering.By coupling the localised measurements from CPTs with more global 3D measurements derived from geophysical methods,a higher fidelity 3D overview of the subsurface can be obtained.Machine Learning(ML)may offer an effective means to capture all types of geophysical information associated with CPT data at a site scale to build a 2D or 3D ground model.In this paper,we present an ML approach to build a 3D ground model of cone resistance and sleeve friction by combining several CPT measurements with Multichannel Analysis of Surface Waves(MASW)and Electrical Resistivity Tomography(ERT)data on a land site characterisation project in the United Arab Emirates(UAE).To avoid a potential overfitting problem inherent to the use of machine learning and a lack of data at certain locations,we explore the possibility of using a prior Geo-Statistical(GS)approach that attempts to constrain the overfitting process by“artificially”increasing the amount of input data.A sensitivity study is also performed on input features used to train the ML algorithm to better define the optimal combination of input features for the prediction.Our results showed that ERT data were not useful in capturing 3D variations of geotechnical properties compared to Vs due to the geographical location of the site(200 m east from the Oman Gulf)and the possible effect of saline water intrusion.Additionally,we demonstrate that the use of a prior GS phase could be a promising and interesting means to make the prediction of ground properties more robust,especially for this specific case study described in this paper.Looking ahead,better representation of the subsurface can lead to a number of benefits for stakeholders involved in developing assets.Better ground/geotechnical models mean better site calibration of design methods and fewer design assumptions for reliability-based design,creating an opportunity for value engineering in the form of lighter construction without compromising safety,shorter construction timelines,and reduced resource requirements.展开更多
Harrat Lunayyir,a volcanic field in western Saudi Arabia,exhibits diverse geomorphological and topographical features shaped by volcanic,tectonic,and climatic processes.This study integrates field observations,remote ...Harrat Lunayyir,a volcanic field in western Saudi Arabia,exhibits diverse geomorphological and topographical features shaped by volcanic,tectonic,and climatic processes.This study integrates field observations,remote sensing,and GIS analysis to investigate the spatial distribution and relationships between volcanic landforms,lava flows,and topographical variation result obtained is a morphological classification of the cinder cones of Harrat Lunayyir,which can be sub-divided into four types:tephra rings,horseshoe-shaped volcanoes,multiple volcanoes and volcanoes without craters.All of these are monogenetic volcanoes,unlike central volcanoes(stratovolcanoes)which live for tens or hundreds of thousands of years and erupt numerous times.In Harrat Lunayyir,there is a clear dominance of arched horseshoe-shaped volcanoes(58)over ring-shaped cinder cones(10),A1_symmetric cones(circular,uniform cinder cones with a single crater)(32),A2_asymmetric cones(elongated,irregular cones and may feature one or more craters)(8),volcanoes without craters(55)and multiple volcanoes(20).The classification presented in this paper makes it possible to include all morphological types of volcanoes found in the region.This fact also renders the present classification a useful tool to apply in other,both insular and continental volcanic areas to eventually analyze and systematize the study of eruptive edifices with similar traits.Hence,this research will explore the standard physical volcanology literature so as to follow accepted definitions.展开更多
In this study,we present a deterministic convergence analysis of Gated Recurrent Unit(GRU)networks enhanced by a smoothing L_(1)regularization technique.While GRU architectures effectively mitigate gradient vanishing/...In this study,we present a deterministic convergence analysis of Gated Recurrent Unit(GRU)networks enhanced by a smoothing L_(1)regularization technique.While GRU architectures effectively mitigate gradient vanishing/exploding issues in sequential modeling,they remain prone to overfitting,particularly under noisy or limited training data.Traditional L_(1)regularization,despite enforcing sparsity and accelerating optimization,introduces non-differentiable points in the error function,leading to oscillations during training.To address this,we propose a novel smoothing L_(1)regularization framework that replaces the non-differentiable absolute function with a quadratic approximation,ensuring gradient continuity and stabilizing the optimization landscape.Theoretically,we rigorously establish threekey properties of the resulting smoothing L_(1)-regularizedGRU(SL_(1)-GRU)model:(1)monotonic decrease of the error function across iterations,(2)weak convergence characterized by vanishing gradients as iterations approach infinity,and(3)strong convergence of network weights to fixed points under finite conditions.Comprehensive experiments on benchmark datasets-spanning function approximation,classification(KDD Cup 1999 Data,MNIST),and regression tasks(Boston Housing,Energy Efficiency)-demonstrate SL_(1)-GRUs superiority over baseline models(RNN,LSTM,GRU,L_(1)-GRU,L2-GRU).Empirical results reveal that SL_(1)-GRU achieves 1.0%-2.4%higher test accuracy in classification,7.8%-15.4%lower mean squared error in regression compared to unregularized GRU,while reducing training time by 8.7%-20.1%.These outcomes validate the method’s efficacy in balancing computational efficiency and generalization capability,and they strongly corroborate the theoretical calculations.The proposed framework not only resolves the non-differentiability challenge of L_(1)regularization but also provides a theoretical foundation for convergence guarantees in recurrent neural network training.展开更多
We explore some necessary and sufficient conditions for the boundedness of the Forelli-Rudin type operator T on the weighted Lebesgue space associated with tubular domains over the forward light cone.Our approach invo...We explore some necessary and sufficient conditions for the boundedness of the Forelli-Rudin type operator T on the weighted Lebesgue space associated with tubular domains over the forward light cone.Our approach involves conducting precise computations for a series of complex integrals to identify appropriate test functions,and through a detailed analysis of these test functions,we derive the boundedness properties of the operator T.This work is significant in the study of the Bergman projection operators.展开更多
We use the Schrödinger–Newton equation to calculate the regularized self-energy of a particle using a regular self-gravitational and electrostatic potential derived in string T-duality.The particle mass M is no ...We use the Schrödinger–Newton equation to calculate the regularized self-energy of a particle using a regular self-gravitational and electrostatic potential derived in string T-duality.The particle mass M is no longer concentrated into a point but is diluted and described by a quantum-corrected smeared energy density resulting in corrections to the energy of the particle,which is interpreted as a regularized self-energy.We extend our results and find corrections to the relativistic particles using the Klein–Gordon,Proca and Dirac equations.An important finding is that we extract a form of the generalized uncertainty principle(GUP)from the corrected energy.This form of the GUP is shown to depend on the nature of particles;namely,for bosons(spin 0 and spin 1)we obtain a quadratic form of the GUP,while for fermions(spin 1/2)we obtain a linear form.The correlation we find between spin and GUP may offer insights for investigating quantum gravity.展开更多
Currently,the cranes used at sea do not have enough flexibility,efficiency,and safety.Thus,this study proposed a floating multirobot coordinated towing system to meet the demands for offshore towing.Because of the fle...Currently,the cranes used at sea do not have enough flexibility,efficiency,and safety.Thus,this study proposed a floating multirobot coordinated towing system to meet the demands for offshore towing.Because of the flexibility of rope-driven robots,the one-way pulling characteristics of the rope,and the floating characteristics of the base,towing robots are easily overturned.First,the spatial configuration of the towing system was established according to the towing task,and the kinematic model of the towing system was established using the coordinate transformation.Then,the dynamic model of the towing system was established according to the rigid-body dynamics and hydrodynamic theory.Finally,the stability of the towing system was analyzed using the stability cone method.The simulation experiments provide a reference for the practical application of the floating multirobot coordinated towing system,which can improve the stability of towing systems by changing the configuration of the towing robot.展开更多
Absorption compensation is a process involving the exponential amplification of reflection amplitudes.This process amplifies the seismic signal and noise,thereby substantially reducing the signal-tonoise ratio of seis...Absorption compensation is a process involving the exponential amplification of reflection amplitudes.This process amplifies the seismic signal and noise,thereby substantially reducing the signal-tonoise ratio of seismic data.Therefore,this paper proposes a multichannel inversion absorption compensation method based on structure tensor regularization.First,the structure tensor is utilized to extract the spatial inclination of seismic signals,and the spatial prediction filter is designed along the inclination direction.The spatial prediction filter is then introduced into the regularization condition of multichannel inversion absorption compensation,and the absorption compensation is realized under the framework of multichannel inversion theory.The spatial predictability of seismic signals is also introduced into the objective function of absorption compensation inversion.Thus,the inversion system can effectively suppress the noise amplification effect during absorption compensation and improve the recovery accuracy of high-frequency signals.Synthetic and field data tests are conducted to demonstrate the accuracy and effectiveness of the proposed method.展开更多
Energy resolution calibration is crucial for gamma-ray spectral analysis,as measured using a scintillation detector.A locally constrained regularization method was proposed to determine the resolution calibration para...Energy resolution calibration is crucial for gamma-ray spectral analysis,as measured using a scintillation detector.A locally constrained regularization method was proposed to determine the resolution calibration parameters.First,a Monte Carlo simulation model consistent with an actual measurement system was constructed to obtain the energy deposition distribution in the scintillation crystal.Subsequently,the regularization objective function is established based on weighted least squares and additional constraints.Additional constraints were designed using a special weighting scheme based on the incident gamma-ray energies.Subsequently,an intelligent algorithm was introduced to search for the optimal resolution calibration parameters by minimizing the objective function.The most appropriate regularization parameter was determined through mathematical experiments.When the regularization parameter was 30,the calibrated results exhibited the minimum RMSE.Simulations and test pit experiments were conducted to verify the performance of the proposed method.The simulation results demonstrate that the proposed algorithm can determine resolution calibration parameters more accurately than the traditional weighted least squares,and the test pit experimental results show that the R-squares between the calibrated and measured spectra are larger than 0.99.The accurate resolution calibration parameters determined by the proposed method lay the foundation for gamma-ray spectral processing and simulation benchmarking.展开更多
Background:Although Cone reconstruction has been shown to improve biventricular functionover time,postoperative right ventricular dysfunction(RVD)is frequently observed,signiffcantly affectingreoperation and long-term...Background:Although Cone reconstruction has been shown to improve biventricular functionover time,postoperative right ventricular dysfunction(RVD)is frequently observed,signiffcantly affectingreoperation and long-term prognosis.This study aims to identify the predictors for postoperative RVD.Methods:This retrospective cohort study included 51 patients with Ebstein’s anomaly who underwentthe Cone reconstruction.RVD was deffned as right ventricular fractional area change(RV-FAC)lessthan 35%and tricuspid annular plane systolic excursion(TAPSE)less than 17 mm through pre-dischargeechocardiography.Univariate and multivariate analyses were used to analyze the pre-operative predictors.Results:The median age at surgery was 37.7(±15.3)years,RVD was documented in 25 patients(49%)of the51 patients.Patients with RVD had signiffcantly higher right ventricular end-systolic volume index(RVESVi)(p=0.001),right ventricular end-diastolic volume index(RVEDVi)(p=0.03),and septal leaffet displacement(p=0.003).Multivariate analysis conffrmed that septal leaffet displacement was independently associatedwith postoperative RVD(p=0.02).Additionally,RVD was not related to the cardiopulmonary bypass time,ICU stay and total hospital time.Conclusions:This study suggests that preoperative right ventricularejection fraction(RVEF)reduction,severe septal leaffet displacement and signiffcant right ventriculardilatation are key predictors of early postoperative RVD.RVD may exacerbate tricuspid regurgitation,andthis ffnding indicates that predicting RVD may aid in identifying high-risk patients prone to recurrence oftricuspid regurgitation after Cone reconstruction.展开更多
For cone beam computed tomography(CBCT),there has long been a desire to modulate the intensity and distribution of the X-rays to accommodate the patient’s anatomy as the gantry rotates from one projection to another....For cone beam computed tomography(CBCT),there has long been a desire to modulate the intensity and distribution of the X-rays to accommodate the patient’s anatomy as the gantry rotates from one projection to another.This would reduce both image artifacts and radiation dose.However,the current beam modulation setups,such as dynamic bowtie filters,may be too complex for practical use in clinical applications.This study aimed to investigate a simplified dynamic beam filtration strategy for CBCT imaging to reduce image artifacts and radiation dose.In this study,the beam filtration was designed to vary dynamically as the CBCT gantry rotates around the object.Specifically,two distinct components were integrated:the sheet filter part and the bowtie filter part.The dynamic beam filtration setup has two working schemes,one is a combination of dynamic sheet filter and dynamic bowtie filter,denoted as dynamic filterdynamic bowtie(DFDB);the other is a combination of dynamic sheet filter and static bowtie filter,denoted as dynamic filter-static bowtie(DFSB).Numerical imaging experiments were performed for three human body parts:the shoulder,chest,and knee.In addition,the Monte Carlo simulation platform MC-GPU was used to generate the dose distribution maps.Results showed that the proposed DFDB and DFSB beam filtration schemes can significantly reduce the image artifacts and thus improve the CBCT image quality.Depending on the scanned object,the total radiation dose could be reduced by 30%.The proposed simple dynamic beam filtration strategy,especially the DFSB approach,could be beneficial in the future to improve the CBCT image quality with reduced image artifacts and radiation dose.展开更多
Target tracking is an essential task in contemporary computer vision applications.However,its effectiveness is susceptible to model drift,due to the different appearances of targets,which often compromises tracking ro...Target tracking is an essential task in contemporary computer vision applications.However,its effectiveness is susceptible to model drift,due to the different appearances of targets,which often compromises tracking robustness and precision.In this paper,a universally applicable method based on correlation filters is introduced to mitigate model drift in complex scenarios.It employs temporal-confidence samples as a priori to guide the model update process and ensure its precision and consistency over a long period.An improved update mechanism based on the peak side-lobe to peak correlation energy(PSPCE)criterion is proposed,which selects high-confidence samples along the temporal dimension to update temporal-confidence samples.Extensive experiments on various benchmarks demonstrate that the proposed method achieves a competitive performance compared with the state-of-the-art methods.Especially when the target appearance changes significantly,our method is more robust and can achieve a balance between precision and speed.Specifically,on the object tracking benchmark(OTB-100)dataset,compared to the baseline,the tracking precision of our model improves by 8.8%,8.8%,5.1%,5.6%,and 6.9%for background clutter,deformation,occlusion,rotation,and illumination variation,respectively.The results indicate that this proposed method can significantly enhance the robustness and precision of target tracking in dynamic and challenging environments,offering a reliable solution for applications such as real-time monitoring,autonomous driving,and precision guidance.展开更多
Transfer-based Adversarial Attacks(TAAs)can deceive a victim model even without prior knowledge.This is achieved by leveraging the property of adversarial examples.That is,when generated from a surrogate model,they re...Transfer-based Adversarial Attacks(TAAs)can deceive a victim model even without prior knowledge.This is achieved by leveraging the property of adversarial examples.That is,when generated from a surrogate model,they retain their features if applied to other models due to their good transferability.However,adversarial examples often exhibit overfitting,as they are tailored to exploit the particular architecture and feature representation of source models.Consequently,when attempting black-box transfer attacks on different target models,their effectiveness is decreased.To solve this problem,this study proposes an approach based on a Regularized Constrained Feature Layer(RCFL).The proposed method first uses regularization constraints to attenuate the initial examples of low-frequency components.Perturbations are then added to a pre-specified layer of the source model using the back-propagation technique,in order to modify the original adversarial examples.Afterward,a regularized loss function is used to enhance the black-box transferability between different target models.The proposed method is finally tested on the ImageNet,CIFAR-100,and Stanford Car datasets with various target models,The obtained results demonstrate that it achieves a significantly higher transfer-based adversarial attack success rate compared with baseline techniques.展开更多
文摘Multi-label feature selection(MFS)is a crucial dimensionality reduction technique aimed at identifying informative features associated with multiple labels.However,traditional centralized methods face significant challenges in privacy-sensitive and distributed settings,often neglecting label dependencies and suffering from low computational efficiency.To address these issues,we introduce a novel framework,Fed-MFSDHBCPSO—federated MFS via dual-layer hybrid breeding cooperative particle swarm optimization algorithm with manifold and sparsity regularization(DHBCPSO-MSR).Leveraging the federated learning paradigm,Fed-MFSDHBCPSO allows clients to perform local feature selection(FS)using DHBCPSO-MSR.Locally selected feature subsets are encrypted with differential privacy(DP)and transmitted to a central server,where they are securely aggregated and refined through secure multi-party computation(SMPC)until global convergence is achieved.Within each client,DHBCPSO-MSR employs a dual-layer FS strategy.The inner layer constructs sample and label similarity graphs,generates Laplacian matrices to capture the manifold structure between samples and labels,and applies L2,1-norm regularization to sparsify the feature subset,yielding an optimized feature weight matrix.The outer layer uses a hybrid breeding cooperative particle swarm optimization algorithm to further refine the feature weight matrix and identify the optimal feature subset.The updated weight matrix is then fed back to the inner layer for further optimization.Comprehensive experiments on multiple real-world multi-label datasets demonstrate that Fed-MFSDHBCPSO consistently outperforms both centralized and federated baseline methods across several key evaluation metrics.
文摘For positioning a moving target, a maximum intensity projection (MIP) or average intensity projection (AIP) image derived from 4DCT is often used as the reference image which is matched to free breathing cone-beam CT (FBCBCT) before treatment. This method can be highly accurate if the respiratory motion of the patient is stable. However, a patient’s breathing pattern is often irregular. The purpose of this study is to investigate the effects of irregular respiration on positioning accuracy for a moving target aligned with FBCBCT. Nine patients’ respiratory motion curves were selected to drive a Quasar motion phantom with one embedded cubic and two spherical targets. A 4DCT of the phantom was acquired on a CT scanner (Philips Brilliance 16) equipped with a Varian RPM system. The phase binned 4DCT images and the corresponding MIP and AIP images were transferred into Eclipse for analysis. FBCBCTs of the phantom driven by the same respiratory curves were also acquired on a Varian TrueBeam and fused such that both CBCT and MIP/AIP images share the same target zero positions. The sphere and cube volumes and centroid differences (alignment error) determined by MIP, AIP and FBCBCT images were calculated, respectively. Compared to the volume determined by MIP, the volumes of the cube, large sphere, and small sphere in AIP and FBCBCT images were smaller. The alignment errors for the cube, large sphere and small sphere with center to center matches between MIP and FBCBCT were 2.5 ± 1.8 mm, 2.4 ± 2.1 mm, and 3.8 ± 2.8 mm, and the alignment errors between AIP and FBCBCT were 0.5 ± 1.1 mm, 0.3 ± 0.8 mm, and 1.8 ± 2.0 mm, respectively. AIP images appear to be superior reference images to MIP images. However, irregular respiratory pattern could compromise the positioning accuracy, especially for smaller targets.
基金Supported by Yunnan Provincial Reserve Talent Program for Young and Middle-aged Academic and Technical Leaders(202405AC350086)the Special Basic Cooperative Research Programs of Yunnan Provincial Undergraduate Universities’Association(202301BA070001-095,202301BA070001-092)+3 种基金the Natural Science Foundation of Guangdong Province(2023A1515010997)Xingzhao Talent Support ProgramEducation and Teaching Reform Research Project of Zhaotong University(Ztjx202405,Ztjx202403,Ztjx202414)2024 First-class Undergraduate Courses of Zhaotong University(Ztujk202405,Ztujk202404).
文摘In this paper,various extended contractions are introduced as generalizations of some existing contractions given by Kannan,Ciric,Reich and Gornicki,et al.Then,several meaningful results about asymptotically regular mappings in cone metric spaces over Banach algebras are obtained,weakening the completeness of the spaces and the continuity of the mappings.Moreover,some nontrivial examples are showed to verify the innovation of the new concepts and our fxed point theorems.
文摘The finite volume method was applied to numerically simulate the bottom pressure field induced by regular waves,vehicles in calm water and vehicles in regular waves.The solution of Navier-Stokes(N-S)equations in the vicinity of numerical wave tank's boundary was forced towards the wave theoretical solution by incorporating momentum source terms,thereby reducing adverse effects such as wave reflection.Simulations utilizing laminar flow,turbulent flow,and ideal fluid models were all found capable of effectively capturing the waveform and bottom pressure of regular waves,agreeing well with experimental data.In predicting the bottom pressure field of the submerged vehicle,turbulent simulations considering fluid viscosity and boundary layer development provided more accurate predictions for the stern region than inviscid simulations.Due to sphere's diffractive effect,the sphere's bottom pressure field in waves is not a linear superposition of the wave's and the sphere's bottom pressure field.However,a slender submerged vehicle exhibits a weaker diffractive effect on waves,thus the submerged vehicle's bottom pressure field in waves can be approximated as a linear superposition of the wave's and the submerged vehicle's bottom pressure field,which simplifies computation and analysis.
文摘This paper delves into the baseline design under the baseline parameterization model in experimental design, focusing on the relationship between the K-aberration criterion and the word length pattern (WLP) of regular two-level designs. The paper provides a detailed analysis of the relationship between K5and the WLP for regular two-level designs with resolution t=3, and proposes corresponding theoretical results. These results not only theoretically reveal the connection between the orthogonal parameterization model and the baseline parameterization model but also provide theoretical support for finding the K-aberration optimal regular two-level baseline designs. It demonstrates how to apply these theories to evaluate and select the optimal experimental designs. In practical applications, experimental designers can utilize the theoretical results of this paper to quickly assess and select regular two-level baseline designs with minimal K-aberration by analyzing the WLP of the experimental design. This allows for the identification of key factors that significantly affect the experimental outcomes without frequently changing the factor levels, thereby maximizing the benefits of the experiment.
基金supported by the National Natural Science Foundation of China(11931009,12271495,11971450,and 12071449)Anhui Initiative in Quantum Information Technologies(AHY150200)the Project of Stable Support for Youth Team in Basic Research Field,Chinese Academy of Sciences(YSBR-001).
文摘On a compact Riemann surface with finite punctures P_(1),…P_(k),we define toric curves as multivalued,totallyunramified holomorphic maps to P^(n)with monodromy in a maximal torus of PSU(n+1).Toric solutions to SU(n+1)Todasystems on X\{P_(1);…;P_(k)}are recognized by the associated toric curves in.We introduce character n-ensembles as-tuples of meromorphic one-forms with simple poles and purely imaginary periods,generating toric curves on minus finitelymany points.On X,we establish a correspondence between character-ensembles and toric solutions to the SU(n+1)system with finitely many cone singularities.Our approach not only broadens seminal solutions with two conesingularities on the Riemann sphere,as classified by Jost-Wang(Int.Math.Res.Not.,2002,(6):277-290)andLin-Wei-Ye(Invent.Math.,2012,190(1):169-207),but also advances beyond the limits of Lin-Yang-Zhong’s existencetheorems(J.Differential Geom.,2020,114(2):337-391)by introducing a new solution class.
基金Supported by the National Natural Science Foundation of China(12001327,12071057)。
文摘Toric patch is a kind of rational multisided patch,which is associated with a finite integer lattice points set A.A set of weights is defined which depend on a parameter according to regular decomposition of A.When all weights of the patch tend to infinity,we obtain the limiting form of toric patch which is called its regular control surface.The diferent weights may induce the diferent regular control surfaces of the same toric patch.It prompts us to consider that how many regular control surfaces of a toric patch.In this paper,we study the regular decompositions of A by using integer programming method firstly,and then provide the relationship between all regular decompositions of A and corresponding state polytope.Moreover,we present that the number of regular control surfaces of a toric patch associated with A is equal to the number of regular decompositions of A.An algorithm to calculate the number of regular control surfaces of toric patch is provided.The algorithm also presents a method to construct all of the regular control surfaces of a toric patch.At last,the application of proposed result in shape deformation is demonstrated by several examples.
文摘Geotechnical parameters derived from an intrusive cone penetration test(CPT)are used to asses mechanical properties to inform the design phase of infrastructure projects.However,local,in situ 1D measurements can fail to capture 3D subsurface variations,which could mean less than optimal design decisions for foundation engineering.By coupling the localised measurements from CPTs with more global 3D measurements derived from geophysical methods,a higher fidelity 3D overview of the subsurface can be obtained.Machine Learning(ML)may offer an effective means to capture all types of geophysical information associated with CPT data at a site scale to build a 2D or 3D ground model.In this paper,we present an ML approach to build a 3D ground model of cone resistance and sleeve friction by combining several CPT measurements with Multichannel Analysis of Surface Waves(MASW)and Electrical Resistivity Tomography(ERT)data on a land site characterisation project in the United Arab Emirates(UAE).To avoid a potential overfitting problem inherent to the use of machine learning and a lack of data at certain locations,we explore the possibility of using a prior Geo-Statistical(GS)approach that attempts to constrain the overfitting process by“artificially”increasing the amount of input data.A sensitivity study is also performed on input features used to train the ML algorithm to better define the optimal combination of input features for the prediction.Our results showed that ERT data were not useful in capturing 3D variations of geotechnical properties compared to Vs due to the geographical location of the site(200 m east from the Oman Gulf)and the possible effect of saline water intrusion.Additionally,we demonstrate that the use of a prior GS phase could be a promising and interesting means to make the prediction of ground properties more robust,especially for this specific case study described in this paper.Looking ahead,better representation of the subsurface can lead to a number of benefits for stakeholders involved in developing assets.Better ground/geotechnical models mean better site calibration of design methods and fewer design assumptions for reliability-based design,creating an opportunity for value engineering in the form of lighter construction without compromising safety,shorter construction timelines,and reduced resource requirements.
文摘Harrat Lunayyir,a volcanic field in western Saudi Arabia,exhibits diverse geomorphological and topographical features shaped by volcanic,tectonic,and climatic processes.This study integrates field observations,remote sensing,and GIS analysis to investigate the spatial distribution and relationships between volcanic landforms,lava flows,and topographical variation result obtained is a morphological classification of the cinder cones of Harrat Lunayyir,which can be sub-divided into four types:tephra rings,horseshoe-shaped volcanoes,multiple volcanoes and volcanoes without craters.All of these are monogenetic volcanoes,unlike central volcanoes(stratovolcanoes)which live for tens or hundreds of thousands of years and erupt numerous times.In Harrat Lunayyir,there is a clear dominance of arched horseshoe-shaped volcanoes(58)over ring-shaped cinder cones(10),A1_symmetric cones(circular,uniform cinder cones with a single crater)(32),A2_asymmetric cones(elongated,irregular cones and may feature one or more craters)(8),volcanoes without craters(55)and multiple volcanoes(20).The classification presented in this paper makes it possible to include all morphological types of volcanoes found in the region.This fact also renders the present classification a useful tool to apply in other,both insular and continental volcanic areas to eventually analyze and systematize the study of eruptive edifices with similar traits.Hence,this research will explore the standard physical volcanology literature so as to follow accepted definitions.
基金supported by the National Science Fund for Distinguished Young Scholarship(No.62025602)National Natural Science Foundation of China(Nos.U22B2036,11931015)+2 种基金the Fok Ying-Tong Education Foundation China(No.171105)the Fundamental Research Funds for the Central Universities(No.G2024WD0151)in part by the Tencent Foundation and XPLORER PRIZE.
文摘In this study,we present a deterministic convergence analysis of Gated Recurrent Unit(GRU)networks enhanced by a smoothing L_(1)regularization technique.While GRU architectures effectively mitigate gradient vanishing/exploding issues in sequential modeling,they remain prone to overfitting,particularly under noisy or limited training data.Traditional L_(1)regularization,despite enforcing sparsity and accelerating optimization,introduces non-differentiable points in the error function,leading to oscillations during training.To address this,we propose a novel smoothing L_(1)regularization framework that replaces the non-differentiable absolute function with a quadratic approximation,ensuring gradient continuity and stabilizing the optimization landscape.Theoretically,we rigorously establish threekey properties of the resulting smoothing L_(1)-regularizedGRU(SL_(1)-GRU)model:(1)monotonic decrease of the error function across iterations,(2)weak convergence characterized by vanishing gradients as iterations approach infinity,and(3)strong convergence of network weights to fixed points under finite conditions.Comprehensive experiments on benchmark datasets-spanning function approximation,classification(KDD Cup 1999 Data,MNIST),and regression tasks(Boston Housing,Energy Efficiency)-demonstrate SL_(1)-GRUs superiority over baseline models(RNN,LSTM,GRU,L_(1)-GRU,L2-GRU).Empirical results reveal that SL_(1)-GRU achieves 1.0%-2.4%higher test accuracy in classification,7.8%-15.4%lower mean squared error in regression compared to unregularized GRU,while reducing training time by 8.7%-20.1%.These outcomes validate the method’s efficacy in balancing computational efficiency and generalization capability,and they strongly corroborate the theoretical calculations.The proposed framework not only resolves the non-differentiability challenge of L_(1)regularization but also provides a theoretical foundation for convergence guarantees in recurrent neural network training.
基金Liu’s research was supported by the Fundamental Research Funds for the Central Universities,Sun Yat-sen University(31610030)Deng’s research was supported by the NSFC(11971042,12071035)the National Key R&D Program of China(2021YFA1002600).
文摘We explore some necessary and sufficient conditions for the boundedness of the Forelli-Rudin type operator T on the weighted Lebesgue space associated with tubular domains over the forward light cone.Our approach involves conducting precise computations for a series of complex integrals to identify appropriate test functions,and through a detailed analysis of these test functions,we derive the boundedness properties of the operator T.This work is significant in the study of the Bergman projection operators.
文摘We use the Schrödinger–Newton equation to calculate the regularized self-energy of a particle using a regular self-gravitational and electrostatic potential derived in string T-duality.The particle mass M is no longer concentrated into a point but is diluted and described by a quantum-corrected smeared energy density resulting in corrections to the energy of the particle,which is interpreted as a regularized self-energy.We extend our results and find corrections to the relativistic particles using the Klein–Gordon,Proca and Dirac equations.An important finding is that we extract a form of the generalized uncertainty principle(GUP)from the corrected energy.This form of the GUP is shown to depend on the nature of particles;namely,for bosons(spin 0 and spin 1)we obtain a quadratic form of the GUP,while for fermions(spin 1/2)we obtain a linear form.The correlation we find between spin and GUP may offer insights for investigating quantum gravity.
基金Supported by the National Natural Science Foundation of China under Grant No.51965032the Natural Science Foundation of Gansu Province of China under Grant No.22JR5RA319+2 种基金the Excellent Doctoral Student Foundation of Gansu Province of China under Grant No.23JRRA842the Sichuan Province Engineering Technology Research Center of General Aircraft Maintenance under Grant No.GAMRC2023YB05the Key Research and Development Project of Lanzhou Jiaotong University under Grant No.LZJTUZDYF2302.
文摘Currently,the cranes used at sea do not have enough flexibility,efficiency,and safety.Thus,this study proposed a floating multirobot coordinated towing system to meet the demands for offshore towing.Because of the flexibility of rope-driven robots,the one-way pulling characteristics of the rope,and the floating characteristics of the base,towing robots are easily overturned.First,the spatial configuration of the towing system was established according to the towing task,and the kinematic model of the towing system was established using the coordinate transformation.Then,the dynamic model of the towing system was established according to the rigid-body dynamics and hydrodynamic theory.Finally,the stability of the towing system was analyzed using the stability cone method.The simulation experiments provide a reference for the practical application of the floating multirobot coordinated towing system,which can improve the stability of towing systems by changing the configuration of the towing robot.
基金funded by the National Key R&D Program of China(Grant no.2018YFA0702504)the Sinopec research project(P22162).
文摘Absorption compensation is a process involving the exponential amplification of reflection amplitudes.This process amplifies the seismic signal and noise,thereby substantially reducing the signal-tonoise ratio of seismic data.Therefore,this paper proposes a multichannel inversion absorption compensation method based on structure tensor regularization.First,the structure tensor is utilized to extract the spatial inclination of seismic signals,and the spatial prediction filter is designed along the inclination direction.The spatial prediction filter is then introduced into the regularization condition of multichannel inversion absorption compensation,and the absorption compensation is realized under the framework of multichannel inversion theory.The spatial predictability of seismic signals is also introduced into the objective function of absorption compensation inversion.Thus,the inversion system can effectively suppress the noise amplification effect during absorption compensation and improve the recovery accuracy of high-frequency signals.Synthetic and field data tests are conducted to demonstrate the accuracy and effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(No.41804141)。
文摘Energy resolution calibration is crucial for gamma-ray spectral analysis,as measured using a scintillation detector.A locally constrained regularization method was proposed to determine the resolution calibration parameters.First,a Monte Carlo simulation model consistent with an actual measurement system was constructed to obtain the energy deposition distribution in the scintillation crystal.Subsequently,the regularization objective function is established based on weighted least squares and additional constraints.Additional constraints were designed using a special weighting scheme based on the incident gamma-ray energies.Subsequently,an intelligent algorithm was introduced to search for the optimal resolution calibration parameters by minimizing the objective function.The most appropriate regularization parameter was determined through mathematical experiments.When the regularization parameter was 30,the calibrated results exhibited the minimum RMSE.Simulations and test pit experiments were conducted to verify the performance of the proposed method.The simulation results demonstrate that the proposed algorithm can determine resolution calibration parameters more accurately than the traditional weighted least squares,and the test pit experimental results show that the R-squares between the calibrated and measured spectra are larger than 0.99.The accurate resolution calibration parameters determined by the proposed method lay the foundation for gamma-ray spectral processing and simulation benchmarking.
基金funded by E Fund Congenital Heart Disease Medical Talent Cultivation and Education Fund(grant number[2023QT0009])the Science and Technology Planning Project of Guangdong Province(grant number[2023B03J1255]).
文摘Background:Although Cone reconstruction has been shown to improve biventricular functionover time,postoperative right ventricular dysfunction(RVD)is frequently observed,signiffcantly affectingreoperation and long-term prognosis.This study aims to identify the predictors for postoperative RVD.Methods:This retrospective cohort study included 51 patients with Ebstein’s anomaly who underwentthe Cone reconstruction.RVD was deffned as right ventricular fractional area change(RV-FAC)lessthan 35%and tricuspid annular plane systolic excursion(TAPSE)less than 17 mm through pre-dischargeechocardiography.Univariate and multivariate analyses were used to analyze the pre-operative predictors.Results:The median age at surgery was 37.7(±15.3)years,RVD was documented in 25 patients(49%)of the51 patients.Patients with RVD had signiffcantly higher right ventricular end-systolic volume index(RVESVi)(p=0.001),right ventricular end-diastolic volume index(RVEDVi)(p=0.03),and septal leaffet displacement(p=0.003).Multivariate analysis conffrmed that septal leaffet displacement was independently associatedwith postoperative RVD(p=0.02).Additionally,RVD was not related to the cardiopulmonary bypass time,ICU stay and total hospital time.Conclusions:This study suggests that preoperative right ventricularejection fraction(RVEF)reduction,severe septal leaffet displacement and signiffcant right ventriculardilatation are key predictors of early postoperative RVD.RVD may exacerbate tricuspid regurgitation,andthis ffnding indicates that predicting RVD may aid in identifying high-risk patients prone to recurrence oftricuspid regurgitation after Cone reconstruction.
文摘For cone beam computed tomography(CBCT),there has long been a desire to modulate the intensity and distribution of the X-rays to accommodate the patient’s anatomy as the gantry rotates from one projection to another.This would reduce both image artifacts and radiation dose.However,the current beam modulation setups,such as dynamic bowtie filters,may be too complex for practical use in clinical applications.This study aimed to investigate a simplified dynamic beam filtration strategy for CBCT imaging to reduce image artifacts and radiation dose.In this study,the beam filtration was designed to vary dynamically as the CBCT gantry rotates around the object.Specifically,two distinct components were integrated:the sheet filter part and the bowtie filter part.The dynamic beam filtration setup has two working schemes,one is a combination of dynamic sheet filter and dynamic bowtie filter,denoted as dynamic filterdynamic bowtie(DFDB);the other is a combination of dynamic sheet filter and static bowtie filter,denoted as dynamic filter-static bowtie(DFSB).Numerical imaging experiments were performed for three human body parts:the shoulder,chest,and knee.In addition,the Monte Carlo simulation platform MC-GPU was used to generate the dose distribution maps.Results showed that the proposed DFDB and DFSB beam filtration schemes can significantly reduce the image artifacts and thus improve the CBCT image quality.Depending on the scanned object,the total radiation dose could be reduced by 30%.The proposed simple dynamic beam filtration strategy,especially the DFSB approach,could be beneficial in the future to improve the CBCT image quality with reduced image artifacts and radiation dose.
基金supported by the Natural Science Foundation of Sichuan Province of China under Grant No.2025ZNSFSC0522partially supported by the National Natural Science Foundation of China under Grants No.61775030 and No.61571096.
文摘Target tracking is an essential task in contemporary computer vision applications.However,its effectiveness is susceptible to model drift,due to the different appearances of targets,which often compromises tracking robustness and precision.In this paper,a universally applicable method based on correlation filters is introduced to mitigate model drift in complex scenarios.It employs temporal-confidence samples as a priori to guide the model update process and ensure its precision and consistency over a long period.An improved update mechanism based on the peak side-lobe to peak correlation energy(PSPCE)criterion is proposed,which selects high-confidence samples along the temporal dimension to update temporal-confidence samples.Extensive experiments on various benchmarks demonstrate that the proposed method achieves a competitive performance compared with the state-of-the-art methods.Especially when the target appearance changes significantly,our method is more robust and can achieve a balance between precision and speed.Specifically,on the object tracking benchmark(OTB-100)dataset,compared to the baseline,the tracking precision of our model improves by 8.8%,8.8%,5.1%,5.6%,and 6.9%for background clutter,deformation,occlusion,rotation,and illumination variation,respectively.The results indicate that this proposed method can significantly enhance the robustness and precision of target tracking in dynamic and challenging environments,offering a reliable solution for applications such as real-time monitoring,autonomous driving,and precision guidance.
基金supported by the Intelligent Policing Key Laboratory of Sichuan Province(No.ZNJW2022KFZD002)This work was supported by the Scientific and Technological Research Program of Chongqing Municipal Education Commission(Grant Nos.KJQN202302403,KJQN202303111).
文摘Transfer-based Adversarial Attacks(TAAs)can deceive a victim model even without prior knowledge.This is achieved by leveraging the property of adversarial examples.That is,when generated from a surrogate model,they retain their features if applied to other models due to their good transferability.However,adversarial examples often exhibit overfitting,as they are tailored to exploit the particular architecture and feature representation of source models.Consequently,when attempting black-box transfer attacks on different target models,their effectiveness is decreased.To solve this problem,this study proposes an approach based on a Regularized Constrained Feature Layer(RCFL).The proposed method first uses regularization constraints to attenuate the initial examples of low-frequency components.Perturbations are then added to a pre-specified layer of the source model using the back-propagation technique,in order to modify the original adversarial examples.Afterward,a regularized loss function is used to enhance the black-box transferability between different target models.The proposed method is finally tested on the ImageNet,CIFAR-100,and Stanford Car datasets with various target models,The obtained results demonstrate that it achieves a significantly higher transfer-based adversarial attack success rate compared with baseline techniques.
