Background and Objectives:The perception of sound in the vertical plane supports spatial hearing by enabling listeners to detect sources located above and below.Sounds originating from both the front and back elevatio...Background and Objectives:The perception of sound in the vertical plane supports spatial hearing by enabling listeners to detect sources located above and below.Sounds originating from both the front and back elevations along the mid-sagittal plane further contribute to a three-dimensional auditory experience.This study aimed to characterize the variability in vertical sound localization abilities among normal-hearing(NH)individuals using spatialized audio.Materials and Methods:Fifty-one NH participants(aged 18 to 35 years)completed three vertical localization tasks under headphones as part of a single-group,within-subject experimental study.These tasks included two-plane identification:(1)top-down localization,(2)front-back localization,and one discrimination task in the front plane.Hierarchical Cluster Analysis(HCA)was employed to identify distinct patterns in spatial localization profiles specific to the vertical-median plane.Fisher's Discriminant Function Analysis(FDA)was used to validate the accuracy of HCA and estimate classification error.Results:HCA revealed three distinct listener clusters:(1)cluster 1 with good performance across all three tasks,(2)cluster 2 with selective impairment in top-bottom identification,and(3)cluster 3 with selective deficits in front-back identification.FDA validated group membership of the clusters identified by the HCA,with a prediction accuracy of 98%.Conclusions:Individuals with clinically NH exhibited three distinct vertical localization profiles:uniform performers,those impaired in top-bottom identification,and those impaired in front-back identification.These profiles may be linked to the interplay between acoustic and non-acoustic perceptual factors.展开更多
This paper proposes a tamper detection technique for semi-fragile watermarking using Quantizationbased Discrete Cosine Transform(DCT)for tamper localization.In this study,the proposed embedding strategy is investigate...This paper proposes a tamper detection technique for semi-fragile watermarking using Quantizationbased Discrete Cosine Transform(DCT)for tamper localization.In this study,the proposed embedding strategy is investigated by experimental tests over the diagonal order of the DCT coefficients.The cover image is divided into non-overlapping blocks of size 8×8 pixels.The DCT is applied to each block,and the coefficients are arranged using a zig-zag pattern within the block.In this study,the low-frequency coefficients are selected to examine the impact of the imperceptibility score and tamper detection accuracy.High accuracy of tamper detection can be achieved by checking the surrounding blocks to determine whether the corresponding block has been tampered with.The proposed tamper detection is tested under various malicious,incidental,and hybrid attacks(both incidental and malicious attacks).The experimental results demonstrate that the proposed technique achieves a Peak-Signal-to-Noise Ratio(PSNR)value of 41.2318 dB,an average Structural Similarity Index Measure(SSIM)value of 0.9768.The proposed scheme is also evaluated against malicious attacks such as copy-move,object deletion,object manipulation,and collage attacks.The proposed scheme can detect the malicious attack localization under various tampering rates.In addition,the proposed scheme can still detect tampered pixels under a hybrid attack,such as a combination ofmalicious and incidental attacks,with an average accuracy of 96.44%.展开更多
The acquisition of position information of legitimate users and jammers plays an important role in the emerging non-geostationary synchronous orbit(NGSO)satellite communications.In this paper,we study the multi-signal...The acquisition of position information of legitimate users and jammers plays an important role in the emerging non-geostationary synchronous orbit(NGSO)satellite communications.In this paper,we study the multi-signal localization problem in an uplink NGSO satellite communication system.We propose an onboard localization scheme based on multiple observations from the satellite,together with the geometric constraints of the satellite postions,the signal positions,the attitude of the satellite,and the angle-of-arrival(AoAs)of the signals.We develop a massage-passing algorithm,termed the Bayesian blind multi-signal localization(BMSL),to jointly estimate the AoAs and the signal positions.The Cramér-Rao lower bound(CRLB)is derived to characterize the fundamental performance limit of the considered localization problem.Simulation results show that the proposed BMSL algorithm can perform close to the derived CRLB and significantly outperforms its counterpart algorithms.展开更多
The stator of the maglev track plays a crucial role in the operation of the maglev system.Currently,the efficiency of maglev track inspection is limited by several factors,including the large span of elevated structur...The stator of the maglev track plays a crucial role in the operation of the maglev system.Currently,the efficiency of maglev track inspection is limited by several factors,including the large span of elevated structures,manual visual inspection,short inspection window times,and limited GPS positioning accuracy.To address these issues,this paper proposes a deep learning-based method for detecting and locating stator surface damage.This study establishes a maglev track stator surface image dataset,trains different object detection models,and compares their performance.Ultimately,YOLO and ByteTrack object tracking algorithms were chosen as the basic framework and enhanced to achieve automatic identification of high-speed maglev track stator surface damage images and track and count stator surface localization feature images.By matching the identified damaged images with their corresponding stator segment and beam segment sequence numbers,the location of the damage is pinpointed to the corresponding stator segment,enabling rapid and accurate identification and localization of complex damage to the maglev track stator surface.展开更多
Granular materials exhibit complex macroscopic mechanical behaviors closely related to their microscalemicrostructural features.Traditional macroscopic phenomenological elasto-plastic models,however,usually have compl...Granular materials exhibit complex macroscopic mechanical behaviors closely related to their microscalemicrostructural features.Traditional macroscopic phenomenological elasto-plastic models,however,usually have complex formulations and lack explicit relations to these microstructural features.To avoid these limitations,this study proposes a micromechanics-based softening hyperelastic model for granular materials,integrating softening hyperelasticity withmicrostructural insights to capture strain softening,critical state,and strain localization behaviors.The model has two key advantages:(1)a clear conceptualization,straightforward formulation,and ease of numerical implementation(via Abaqus UMAT subroutine in this study);(2)explicit incorporation of micro-scale features(e.g.,contact stiffness,particle size,porosity)to reveal their influences on macroscopic responses.An isotropic directional distribution density of contacts and three specific microstructures are considered,and their softening hyperelastic constitutive modulus tensors are explicitly derived.By introducing a softening factor and critical failure energy density,the model can describe geomaterial behaviors,simulating residual strength,X-shaped shear bands,and strain localization evolution.Numerical validations in comparison with themacro-scale hyperelastic model,Abaqus Drucker-Prager model,and the experiment confirm its accuracy.Parametric studies reveal critical dependencies:a normal to tangential contact stiffness ratio of 2-8(depending on stiffness magnitude),an internal length of 2-4 mm to ensure shear band formation,and a critical failure energy density(≤10 kJ/m^(3))to trigger strain softening and localization.Influences of the specific microstructures on strain localization and softening are investigated.The model also shows mesh independence due to the introduction of an internal length.The model’s applicability is further demonstrated by slope stability analysis,capturing slip surface evolution,and load-displacement characteristics.This study develops a robust microstructure-aware hyperelastic framework to describe the mechanical behaviors of granular materials,providing multiscale insights for geotechnical engineering applications.展开更多
Reconfigurable intelligent surfaces(RISs)not only assist communication but also help the localization of user equipment(UE).This study focuses on indoor localization of UE with a single access point(AP)and multiple RI...Reconfigurable intelligent surfaces(RISs)not only assist communication but also help the localization of user equipment(UE).This study focuses on indoor localization of UE with a single access point(AP)and multiple RISs.First,we propose a two-stage channel estimation scheme where RIS phase shifts are tuned to obtain multiple channel soundings.In the first stage,the newtonized orthogonal matching pursuit algorithm extracts the parameters of multiple paths from the received signals.Then,the LOS path and RISreflected paths are identified.In the second stage,the estimated path gains of RIS-reflected paths with different phase shifts are utilized to determine the angle of arrival(AOA)at the RIS by obtaining the angular pseudo spectrum.Consequently,by taking the AP and RISs as reference points,the linear least squares estimator can locate UE with the estimated AOAs.Simulation results show that the proposed algorithm can realize centimeter-level localization accuracy in the discussed scenarios.Moreover,the higher accuracy of pseudo spectrum,a larger number of channel soundings,and a larger number of reference points can realize higher localization accuracy of UE.展开更多
In ultrasonic non-destructive testing of high-temperature industrial equipment,sound velocity drift induced by non-uniform temperature fields can severely compromise defect localization accuracy.Conventional approache...In ultrasonic non-destructive testing of high-temperature industrial equipment,sound velocity drift induced by non-uniform temperature fields can severely compromise defect localization accuracy.Conventional approaches that rely on room-temperature sound velocities introduce systematic errors,potentially leading to misjudgment of safety-critical components.Two primary challenges hinder current methods:first,it is difficult to monitor real-time changes in sound velocity distribution within a thermal gradient;second,traditional uniform-temperature correction models fail to capture the nonlinear dependence of material properties on temperature and their effect on ultrasonic velocity fields.Here,we propose a defect localization correction method based on multiphysics coupling.A two-dimensional coupled heat transfer–wave propagation model is established in COMSOL,and a one-dimensional steady-state heat transfer condition is used to design a numerical pulse–echo experiment in 1020 steel.Temperature-dependent material properties are incorporated,and the intrinsic relationship between sound velocity and temperature is derived,confirming consistency with classical theories.To account for gradient temperature fields,a micro-element integration algorithm discretizes the propagation path into segments,each associated with a locally computed temperature from the steady-state heat conduction solution.Defect positions are dynamically corrected through cumulative displacement along the propagation path.By integrating heat conduction and elastic wave propagation in a multiphysics framework,this method overcomes the limitations of uniform-temperature assumptions.The micro-element integration approach enables dynamic tracking of spatially varying sound velocities,offering a robust strategy to enhance ultrasonic testing accuracy in high-temperature industrial environments.展开更多
The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to indus...The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to industrial robots.Particle Swarm Optimization may frequently suffer from local optima and inaccuracies in identifying the geometric parameters,which are necessary for applications requiring high-accuracy performances.The proposed approach integrates pheromone-based learning of ACO with the D-H method of developing an error model;hence,the global search effectiveness together with the convergence accuracy is further improved.Comparison studies of the hybrid PSO-ACO algorithm show higher precision and effectiveness in the optimization of geometric error parameters compared to the traditional methods.This is a remarkable reduction of localization errors,thus yielding accuracy and reliability in industrial robotic systems,as the results show.This approach improves performance in those applications that demand high geometric calibration by reducing the geometric error.The paper provides an overview of input for developing robotics and automation,giving importance to precision in industrial engineering.The proposed hybrid methodology is a good way to enhance the working accuracy and effectiveness of industrial robots and shall enable their wide application to complex tasks that require a high degree of accuracy.展开更多
Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accu...Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.展开更多
The fast growth of mobile autonomous machines from traditional equipment to unmanned autonomous vehicles has fueled the demand for accurate and reliable localization solutions in diverse application domains.Ultra Wide...The fast growth of mobile autonomous machines from traditional equipment to unmanned autonomous vehicles has fueled the demand for accurate and reliable localization solutions in diverse application domains.Ultra Wide Band(UWB)technology has emerged as a promising candidate for addressing this need,offering high precision,immunity to multipath interference,and robust performance in challenging environments.In this comprehensive survey,we systematically explore UWB-based localization for mobile autonomous machines,spanning from fundamental principles to future trends.To the best of our knowledge,this review paper stands as the pioneer in systematically dissecting the algorithms of UWB-based localization for mobile autonomous machines,covering a spectrum from bottom-ranging schemes to advanced sensor fusion,error mitigation,and optimization techniques.By synthesizing existing knowledge,evaluating current methodologies,and highlighting future trends,this review aims to catalyze progress and innovation in the field,unlocking new opportunities for mobile autonomous machine applications across diverse industries and domains.Thus,it serves as a valuable resource for researchers,practitioners,and stakeholders interested in advancing the state-of-the-art UWB-based localization for mobile autonomous machines.展开更多
Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environ...Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant challenge.To address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data registration.Specifically,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less efficient.Meanwhile,visual texture information complements LiDAR-Visual localization by providing additional contextual details.By incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of localization.This approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.展开更多
This work presents a method for the three-dimensional localization of individual shallow NV center in diamond,leveraging the near-field quenching effect of a gold tip.Our experimental setup involves the use of an atom...This work presents a method for the three-dimensional localization of individual shallow NV center in diamond,leveraging the near-field quenching effect of a gold tip.Our experimental setup involves the use of an atomic force microscope to precisely move the gold tip close to the NV center,while simultaneously employing a home-made confocal microscope to monitor the fluorescence of the NV center.This approach allows for lateral super-resolution,achieving a full width at half maximum(FWHM)of 38.0 nm and a location uncertainty of 0.7 nm.Additionally,we show the potential of this method for determining the depth of the NV centers.We also attempt to determine the depth of the NV centers in combination with finite-difference time-domain(FDTD)simulations.Compared to other depth determination methods,this approach allows for simultaneous lateral and longitudinal localization of individual NV centers,and holds promise for facilitating manipulation of the local environment surrounding the NV center.展开更多
Automatic Dependent Surveillance-Broadcast(ADS-B)technology,with its open signal sharing,faces substantial security risks from false signals and spoofing attacks when broadcasting Unmanned Aerial Vehicle(UAV)informati...Automatic Dependent Surveillance-Broadcast(ADS-B)technology,with its open signal sharing,faces substantial security risks from false signals and spoofing attacks when broadcasting Unmanned Aerial Vehicle(UAV)information.This paper proposes a security position verification technique based on Multilateration(MLAT)to detect false signals,ensuring UAV safety and reliable airspace operations.First,the proposed method estimates the current position of the UAV by calculating the Time Difference of Arrival(TDOA),Time Sum of Arrival(TSOA),and Angle of Arrival(AOA)information.Then,this estimated position is compared with the ADS-B message to eliminate false UAV signals.Furthermore,a localization model based on TDOA/TSOA/AOA is established by utilizing reliable reference sources for base station time synchronization.Additionally,an improved Chan-Taylor algorithm is developed,incorporating the Constrained Weighted Least Squares(CWLS)method to initialize UAV position calculations.Finally,a false signal detection method is proposed to distinguish between true and false positioning targets.Numerical simulation results indicate that,at a positioning error threshold of 150 m,the improved Chan-Taylor algorithm based on TDOA/TSOA/AOA achieves 100%accuracy coverage,significantly enhancing localization precision.And the proposed false signal detection method achieves a detection accuracy rate of at least 90%within a 50-meter error range.展开更多
We present one family of general analytical solutions for the generalized nonlinear Schr?dinger equation with time-space modulation via the method of a combination of the Darboux transformation and similarity transfor...We present one family of general analytical solutions for the generalized nonlinear Schr?dinger equation with time-space modulation via the method of a combination of the Darboux transformation and similarity transformation. Nonlinear waves on different localized and periodic backgrounds depending on the corresponding nonlinearity modulations are obtained. In particular, we demonstrate the existence and property of localized modes on a doubleperiodic background under a special designed optical lattice potential. Our results may raise the possibility of related experiments and potential applications in nonlinear optics and Bose–Einstein condensates.展开更多
Indian Railways have been the largest people moving transport infrastructure in India.Over the years the systems and trains have been upgraded resulting in both better passenger amenities and reduction in travel time....Indian Railways have been the largest people moving transport infrastructure in India.Over the years the systems and trains have been upgraded resulting in both better passenger amenities and reduction in travel time.The newest addition is the Vande Bharat Express,a semi-high-speed train that was introduced in India in 2019.The train currently runs between 10 routes and has brought significant changes to India’s railway network.This article explores the introduction of Vande Bharat Express trains in India and its effects on the country’s interstation time-space shrinkage using cartographic techniques.The cartographic techniques like stepwise multidimensional scaling and interpolation using the distance cartogram plugin in QGIS are mainly used for generating the time-space maps for various speeds.The limitations of these techniques and the methods to overcome those limitations are also explored in this article.展开更多
This paper is devoted to investigating the spreading speed of a time-space periodic epidemic model with vital dynamics and standard incidence in discrete media. We establish the existence of the leftward and rightward...This paper is devoted to investigating the spreading speed of a time-space periodic epidemic model with vital dynamics and standard incidence in discrete media. We establish the existence of the leftward and rightward spreading speeds for the infective individuals, which can be used to estimate how fast the disease spreads. To overcome the difficulty arising from the lack of comparison principle for such time-space periodic nonmonotone systems, our proof is mainly based on constructing a series of scalar time-space periodic equations, establishing the spreading speeds for such auxiliary equations and using comparison methods. It may be the first work to study the spreading speed for time-space periodic non-monotone systems.展开更多
Seismic anisotropy has been extensively acknowledged as a crucial element that influences the wave propagation characteristic during wavefield simulation,inversion and imaging.Transversely isotropy(TI)and orthorhombic...Seismic anisotropy has been extensively acknowledged as a crucial element that influences the wave propagation characteristic during wavefield simulation,inversion and imaging.Transversely isotropy(TI)and orthorhombic anisotropy(OA)are two typical categories of anisotropic media in exploration geophysics.In comparison of the elastic wave equations in both TI and OA media,pseudo-acoustic wave equations(PWEs)based on the acoustic assumption can markedly reduce computational cost and complexity.However,the presently available PWEs may experience SV-wave contamination and instability when anisotropic parameters cannot satisfy the approximated condition.Exploiting pure-mode wave equations can effectively resolve the above-mentioned issues and generate pure P-wave events without any artifacts.To further improve the computational accuracy and efficiency,we develop two novel pure qP-wave equations(PPEs)and illustrate the corresponding numerical solutions in the timespace domain for 3D tilted TI(TTI)and tilted OA(TOA)media.First,the rational polynomials are adopted to estimate the exact pure qP-wave dispersion relations,which contain complicated pseudo-differential operators with irrational forms.The polynomial coefficients are produced by applying a linear optimization algorithm to minimize the objective function difference between the expansion formula and the exact one.Then,the developed optimized PPEs are efficiently implemented using the finite-difference(FD)method in the time-space domain by introducing a scalar operator,which can help avoid the problem of spectral-based algorithms and other calculation burdens.Structures of the new equations are concise and corresponding implementation processes are straightforward.Phase velocity analyses indicate that our proposed optimized equations can lead to reliable approximation results.3D synthetic examples demonstrate that our proposed FD-based PPEs can produce accurate and stable P-wave responses,and effectively describe the wavefield features in complicated TTI and TOA media.展开更多
This paper investigates the mechanisms underlying the localization of Buddhism among the Kalmyks during Tsarist rule.It identifies and analyzes three interconnected processes:(1)the evolving framework of Tsarist polic...This paper investigates the mechanisms underlying the localization of Buddhism among the Kalmyks during Tsarist rule.It identifies and analyzes three interconnected processes:(1)the evolving framework of Tsarist policies aimed at administrative integration and religious regulation;(2)Kalmyk adaptive strategies,particularly the development of unique institutional responses(Supreme Lama election,Chief Bagshi,Dayanqi,and Temple Adherent systems)to navigate state constraints;and(3)spontaneous processes of cultural hybridity are manifested in material culture(e.g.,the Khoshut temple)and religious narratives(e.g.,Ulyanov’s reinvention of prophecies in Prophecies of Buddha).Utilizing the concept of“conjuncture practice”to frame these interactions,the study demonstrates how localization operated through a combination of regulatory pressure,community-level adaptation,and cultural synthesis,ultimately forging a distinct Kalmyk Buddhist expression within the imperial context.展开更多
Bio-inspired visual systems have garnered significant attention in robotics owing to their energy efficiency,rapid dynamic response,and environmental adaptability.Among these,event cameras-bio-inspired sensors that as...Bio-inspired visual systems have garnered significant attention in robotics owing to their energy efficiency,rapid dynamic response,and environmental adaptability.Among these,event cameras-bio-inspired sensors that asynchronously report pixel-level brightness changes called’events’,stand out because of their ability to capture dynamic changes with minimal energy consumption,making them suitable for challenging conditions,such as low light or high-speed motion.However,current mapping and localization methods for event cameras depend primarily on point and line features,which struggle in sparse or low-feature environments and are unsuitable for static or slow-motion scenarios.We addressed these challenges by proposing a bio-inspired vision mapping and localization method using active LED markers(ALMs)combined with reprojection error optimization and asynchronous Kalman fusion.Our approach replaces traditional features with ALMs,thereby enabling accurate tracking under dynamic and low-feature conditions.The global mapping accuracy significantly improved by minimizing the reprojection error,with corner errors reduced from 16.8 cm to 3.1 cm after 400 iterations.The asynchronous Kalman fusion of multiple camera pose estimations from ALMs ensures precise localization with a high temporal efficiency.This method achieved a mean translation error of 0.078 m and a rotational error of 5.411°while evaluating dynamic motion.In addition,the method supported an output rate of 4.5 kHz while maintaining high localization accuracy in UAV spiral flight experiments.These results demonstrate the potential of the proposed approach for real-time robot localization in challenging environments.展开更多
文摘Background and Objectives:The perception of sound in the vertical plane supports spatial hearing by enabling listeners to detect sources located above and below.Sounds originating from both the front and back elevations along the mid-sagittal plane further contribute to a three-dimensional auditory experience.This study aimed to characterize the variability in vertical sound localization abilities among normal-hearing(NH)individuals using spatialized audio.Materials and Methods:Fifty-one NH participants(aged 18 to 35 years)completed three vertical localization tasks under headphones as part of a single-group,within-subject experimental study.These tasks included two-plane identification:(1)top-down localization,(2)front-back localization,and one discrimination task in the front plane.Hierarchical Cluster Analysis(HCA)was employed to identify distinct patterns in spatial localization profiles specific to the vertical-median plane.Fisher's Discriminant Function Analysis(FDA)was used to validate the accuracy of HCA and estimate classification error.Results:HCA revealed three distinct listener clusters:(1)cluster 1 with good performance across all three tasks,(2)cluster 2 with selective impairment in top-bottom identification,and(3)cluster 3 with selective deficits in front-back identification.FDA validated group membership of the clusters identified by the HCA,with a prediction accuracy of 98%.Conclusions:Individuals with clinically NH exhibited three distinct vertical localization profiles:uniform performers,those impaired in top-bottom identification,and those impaired in front-back identification.These profiles may be linked to the interplay between acoustic and non-acoustic perceptual factors.
基金funded by Ministry of Higher Education Malaysia through Universiti Malaysia Pahang Al-Sultan Abdullah under Internal Research Grant(RDU233003).
文摘This paper proposes a tamper detection technique for semi-fragile watermarking using Quantizationbased Discrete Cosine Transform(DCT)for tamper localization.In this study,the proposed embedding strategy is investigated by experimental tests over the diagonal order of the DCT coefficients.The cover image is divided into non-overlapping blocks of size 8×8 pixels.The DCT is applied to each block,and the coefficients are arranged using a zig-zag pattern within the block.In this study,the low-frequency coefficients are selected to examine the impact of the imperceptibility score and tamper detection accuracy.High accuracy of tamper detection can be achieved by checking the surrounding blocks to determine whether the corresponding block has been tampered with.The proposed tamper detection is tested under various malicious,incidental,and hybrid attacks(both incidental and malicious attacks).The experimental results demonstrate that the proposed technique achieves a Peak-Signal-to-Noise Ratio(PSNR)value of 41.2318 dB,an average Structural Similarity Index Measure(SSIM)value of 0.9768.The proposed scheme is also evaluated against malicious attacks such as copy-move,object deletion,object manipulation,and collage attacks.The proposed scheme can detect the malicious attack localization under various tampering rates.In addition,the proposed scheme can still detect tampered pixels under a hybrid attack,such as a combination ofmalicious and incidental attacks,with an average accuracy of 96.44%.
基金National Key R&D Program of China under Grants 2021YFB2900404the National Natural Science Foundation of China under Grants 62371098。
文摘The acquisition of position information of legitimate users and jammers plays an important role in the emerging non-geostationary synchronous orbit(NGSO)satellite communications.In this paper,we study the multi-signal localization problem in an uplink NGSO satellite communication system.We propose an onboard localization scheme based on multiple observations from the satellite,together with the geometric constraints of the satellite postions,the signal positions,the attitude of the satellite,and the angle-of-arrival(AoAs)of the signals.We develop a massage-passing algorithm,termed the Bayesian blind multi-signal localization(BMSL),to jointly estimate the AoAs and the signal positions.The Cramér-Rao lower bound(CRLB)is derived to characterize the fundamental performance limit of the considered localization problem.Simulation results show that the proposed BMSL algorithm can perform close to the derived CRLB and significantly outperforms its counterpart algorithms.
基金supported in part by the National Natural Science Foundation of China under Grant 52432012in part by the Shanghai Science and Technology Project with 25ZR1402508。
文摘The stator of the maglev track plays a crucial role in the operation of the maglev system.Currently,the efficiency of maglev track inspection is limited by several factors,including the large span of elevated structures,manual visual inspection,short inspection window times,and limited GPS positioning accuracy.To address these issues,this paper proposes a deep learning-based method for detecting and locating stator surface damage.This study establishes a maglev track stator surface image dataset,trains different object detection models,and compares their performance.Ultimately,YOLO and ByteTrack object tracking algorithms were chosen as the basic framework and enhanced to achieve automatic identification of high-speed maglev track stator surface damage images and track and count stator surface localization feature images.By matching the identified damaged images with their corresponding stator segment and beam segment sequence numbers,the location of the damage is pinpointed to the corresponding stator segment,enabling rapid and accurate identification and localization of complex damage to the maglev track stator surface.
基金supported by the National Natural Science Foundation of China through grant numbers 12002245 and 12172263the Science and Technology Research Program of Chongqing Municipal Education Commission through grant number KJQN202300742+1 种基金the National Natural Science Foundation of ChongqingMunicipality through grant number CSTB2025NSCQ-GPX0841Chongqing Jiaotong University through grant number F1220038.
文摘Granular materials exhibit complex macroscopic mechanical behaviors closely related to their microscalemicrostructural features.Traditional macroscopic phenomenological elasto-plastic models,however,usually have complex formulations and lack explicit relations to these microstructural features.To avoid these limitations,this study proposes a micromechanics-based softening hyperelastic model for granular materials,integrating softening hyperelasticity withmicrostructural insights to capture strain softening,critical state,and strain localization behaviors.The model has two key advantages:(1)a clear conceptualization,straightforward formulation,and ease of numerical implementation(via Abaqus UMAT subroutine in this study);(2)explicit incorporation of micro-scale features(e.g.,contact stiffness,particle size,porosity)to reveal their influences on macroscopic responses.An isotropic directional distribution density of contacts and three specific microstructures are considered,and their softening hyperelastic constitutive modulus tensors are explicitly derived.By introducing a softening factor and critical failure energy density,the model can describe geomaterial behaviors,simulating residual strength,X-shaped shear bands,and strain localization evolution.Numerical validations in comparison with themacro-scale hyperelastic model,Abaqus Drucker-Prager model,and the experiment confirm its accuracy.Parametric studies reveal critical dependencies:a normal to tangential contact stiffness ratio of 2-8(depending on stiffness magnitude),an internal length of 2-4 mm to ensure shear band formation,and a critical failure energy density(≤10 kJ/m^(3))to trigger strain softening and localization.Influences of the specific microstructures on strain localization and softening are investigated.The model also shows mesh independence due to the introduction of an internal length.The model’s applicability is further demonstrated by slope stability analysis,capturing slip surface evolution,and load-displacement characteristics.This study develops a robust microstructure-aware hyperelastic framework to describe the mechanical behaviors of granular materials,providing multiscale insights for geotechnical engineering applications.
基金supported in part by the Fundamental Research Funds for the Central Universities under Grant 2242022k60004in part by the National Natural Science Foundation of China(NSFC)under Grants 62261160576,624B2036,W2421087,62422105+1 种基金in part by the Young Elite Scientists Sponsorship Program by CAST 2022QNRC001,and the“Zhishan”Scholars Programs of Southeast Universityin part by the Key Technologies R&D Program of Jiangsu(Prospective and Key Technologies for Industry)under Grants BE2023022,BE2023022-1 and BE2023022-2.
文摘Reconfigurable intelligent surfaces(RISs)not only assist communication but also help the localization of user equipment(UE).This study focuses on indoor localization of UE with a single access point(AP)and multiple RISs.First,we propose a two-stage channel estimation scheme where RIS phase shifts are tuned to obtain multiple channel soundings.In the first stage,the newtonized orthogonal matching pursuit algorithm extracts the parameters of multiple paths from the received signals.Then,the LOS path and RISreflected paths are identified.In the second stage,the estimated path gains of RIS-reflected paths with different phase shifts are utilized to determine the angle of arrival(AOA)at the RIS by obtaining the angular pseudo spectrum.Consequently,by taking the AP and RISs as reference points,the linear least squares estimator can locate UE with the estimated AOAs.Simulation results show that the proposed algorithm can realize centimeter-level localization accuracy in the discussed scenarios.Moreover,the higher accuracy of pseudo spectrum,a larger number of channel soundings,and a larger number of reference points can realize higher localization accuracy of UE.
基金supported by the following projects:National Natural Science Foundation of China[U24A20135]Science and Technology Program of the State Administration for Market Regulation[2024MK016]+9 种基金Basic Scientific Research Fund Project for Higher Education Institutions of Inner Mongolia(2024YXXS057)Key Project of Natural Science Foundation of Inner Mongolia[2023ZD12]2023 Inner Mongolia Autonomous Region Key R&D and Achievement Transformation Program[2023YFHH0090]Natural Science Foundation of Inner Mongolia[2022MS05006]Talent Development Fund of Inner Mongolia Autonomous RegionFundamental Research Funds for Universities[2023RCTD012]Fundamental Research Funds for Universities[2023QNJS075]Inner Mongolia Autonomous Region Postgraduate Research Innovation Project[KC2024053B]Fundamental Research Funds for Universities[2024YXXS012]Open Project of the National Key Laboratory of Special Vehicle Design and Manufacturing Integration Technology[GZ2023KF012].
文摘In ultrasonic non-destructive testing of high-temperature industrial equipment,sound velocity drift induced by non-uniform temperature fields can severely compromise defect localization accuracy.Conventional approaches that rely on room-temperature sound velocities introduce systematic errors,potentially leading to misjudgment of safety-critical components.Two primary challenges hinder current methods:first,it is difficult to monitor real-time changes in sound velocity distribution within a thermal gradient;second,traditional uniform-temperature correction models fail to capture the nonlinear dependence of material properties on temperature and their effect on ultrasonic velocity fields.Here,we propose a defect localization correction method based on multiphysics coupling.A two-dimensional coupled heat transfer–wave propagation model is established in COMSOL,and a one-dimensional steady-state heat transfer condition is used to design a numerical pulse–echo experiment in 1020 steel.Temperature-dependent material properties are incorporated,and the intrinsic relationship between sound velocity and temperature is derived,confirming consistency with classical theories.To account for gradient temperature fields,a micro-element integration algorithm discretizes the propagation path into segments,each associated with a locally computed temperature from the steady-state heat conduction solution.Defect positions are dynamically corrected through cumulative displacement along the propagation path.By integrating heat conduction and elastic wave propagation in a multiphysics framework,this method overcomes the limitations of uniform-temperature assumptions.The micro-element integration approach enables dynamic tracking of spatially varying sound velocities,offering a robust strategy to enhance ultrasonic testing accuracy in high-temperature industrial environments.
文摘The proposed hybrid optimization algorithm integrates particle swarm optimizatio(PSO)with Ant Colony Optimization(ACO)to improve a number of pitfalls within PSO methods traditionally considered and/or applied to industrial robots.Particle Swarm Optimization may frequently suffer from local optima and inaccuracies in identifying the geometric parameters,which are necessary for applications requiring high-accuracy performances.The proposed approach integrates pheromone-based learning of ACO with the D-H method of developing an error model;hence,the global search effectiveness together with the convergence accuracy is further improved.Comparison studies of the hybrid PSO-ACO algorithm show higher precision and effectiveness in the optimization of geometric error parameters compared to the traditional methods.This is a remarkable reduction of localization errors,thus yielding accuracy and reliability in industrial robotic systems,as the results show.This approach improves performance in those applications that demand high geometric calibration by reducing the geometric error.The paper provides an overview of input for developing robotics and automation,giving importance to precision in industrial engineering.The proposed hybrid methodology is a good way to enhance the working accuracy and effectiveness of industrial robots and shall enable their wide application to complex tasks that require a high degree of accuracy.
基金funded by the Youth Fund of the National Natural Science Foundation of China(Grant No.42261070).
文摘Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.
文摘The fast growth of mobile autonomous machines from traditional equipment to unmanned autonomous vehicles has fueled the demand for accurate and reliable localization solutions in diverse application domains.Ultra Wide Band(UWB)technology has emerged as a promising candidate for addressing this need,offering high precision,immunity to multipath interference,and robust performance in challenging environments.In this comprehensive survey,we systematically explore UWB-based localization for mobile autonomous machines,spanning from fundamental principles to future trends.To the best of our knowledge,this review paper stands as the pioneer in systematically dissecting the algorithms of UWB-based localization for mobile autonomous machines,covering a spectrum from bottom-ranging schemes to advanced sensor fusion,error mitigation,and optimization techniques.By synthesizing existing knowledge,evaluating current methodologies,and highlighting future trends,this review aims to catalyze progress and innovation in the field,unlocking new opportunities for mobile autonomous machine applications across diverse industries and domains.Thus,it serves as a valuable resource for researchers,practitioners,and stakeholders interested in advancing the state-of-the-art UWB-based localization for mobile autonomous machines.
基金supported by the project“GEF9874:Strengthening Coordinated Approaches to Reduce Invasive Alien Species(lAS)Threats to Globally Significant Agrobiodiversity and Agroecosystems in China”funding from the Excellent Talent Training Funding Project in Dongcheng District,Beijing,with project number 2024-dchrcpyzz-9.
文摘Ecological monitoring vehicles are equipped with a range of sensors and monitoring devices designed to gather data on ecological and environmental factors.These vehicles are crucial in various fields,including environmental science research,ecological and environmental monitoring projects,disaster response,and emergency management.A key method employed in these vehicles for achieving high-precision positioning is LiDAR(lightlaser detection and ranging)-Visual Simultaneous Localization and Mapping(SLAM).However,maintaining highprecision localization in complex scenarios,such as degraded environments or when dynamic objects are present,remains a significant challenge.To address this issue,we integrate both semantic and texture information from LiDAR and cameras to enhance the robustness and efficiency of data registration.Specifically,semantic information simplifies the modeling of scene elements,reducing the reliance on dense point clouds,which can be less efficient.Meanwhile,visual texture information complements LiDAR-Visual localization by providing additional contextual details.By incorporating semantic and texture details frompaired images and point clouds,we significantly improve the quality of data association,thereby increasing the success rate of localization.This approach not only enhances the operational capabilities of ecological monitoring vehicles in complex environments but also contributes to improving the overall efficiency and effectiveness of ecological monitoring and environmental protection efforts.
基金supported by the National Natural Science Foundation of China(T2325023,92265204,12104447)the National Key R&D Program of China(2023YFF0718400)+1 种基金the Innovation Program for Quantum Science and Technology(2021ZD0302200)the Fundamental Research Funds for the Central Universities。
文摘This work presents a method for the three-dimensional localization of individual shallow NV center in diamond,leveraging the near-field quenching effect of a gold tip.Our experimental setup involves the use of an atomic force microscope to precisely move the gold tip close to the NV center,while simultaneously employing a home-made confocal microscope to monitor the fluorescence of the NV center.This approach allows for lateral super-resolution,achieving a full width at half maximum(FWHM)of 38.0 nm and a location uncertainty of 0.7 nm.Additionally,we show the potential of this method for determining the depth of the NV centers.We also attempt to determine the depth of the NV centers in combination with finite-difference time-domain(FDTD)simulations.Compared to other depth determination methods,this approach allows for simultaneous lateral and longitudinal localization of individual NV centers,and holds promise for facilitating manipulation of the local environment surrounding the NV center.
基金supported by the National Natural Science Foundation of China(Nos.U2441250,62301380,and 62231027)Natural Science Basic Research Program of Shaanxi,China(2024JC-JCQN-63)+3 种基金the Key Research and Development Program of Shaanxi,China(No.2023-YBGY-249)the Guangxi Key Research and Development Program,China(No.2022AB46002)the China Postdoctoral Science Foundation(No.2022M722504 and 2024T170696)the Innovation Capability Support Program of Shaanxi,China(No.2024RS-CXTD-01).
文摘Automatic Dependent Surveillance-Broadcast(ADS-B)technology,with its open signal sharing,faces substantial security risks from false signals and spoofing attacks when broadcasting Unmanned Aerial Vehicle(UAV)information.This paper proposes a security position verification technique based on Multilateration(MLAT)to detect false signals,ensuring UAV safety and reliable airspace operations.First,the proposed method estimates the current position of the UAV by calculating the Time Difference of Arrival(TDOA),Time Sum of Arrival(TSOA),and Angle of Arrival(AOA)information.Then,this estimated position is compared with the ADS-B message to eliminate false UAV signals.Furthermore,a localization model based on TDOA/TSOA/AOA is established by utilizing reliable reference sources for base station time synchronization.Additionally,an improved Chan-Taylor algorithm is developed,incorporating the Constrained Weighted Least Squares(CWLS)method to initialize UAV position calculations.Finally,a false signal detection method is proposed to distinguish between true and false positioning targets.Numerical simulation results indicate that,at a positioning error threshold of 150 m,the improved Chan-Taylor algorithm based on TDOA/TSOA/AOA achieves 100%accuracy coverage,significantly enhancing localization precision.And the proposed false signal detection method achieves a detection accuracy rate of at least 90%within a 50-meter error range.
基金Supported by the National Natural Science Foundation of China under Grant Nos.11475135 and 11547302
文摘We present one family of general analytical solutions for the generalized nonlinear Schr?dinger equation with time-space modulation via the method of a combination of the Darboux transformation and similarity transformation. Nonlinear waves on different localized and periodic backgrounds depending on the corresponding nonlinearity modulations are obtained. In particular, we demonstrate the existence and property of localized modes on a doubleperiodic background under a special designed optical lattice potential. Our results may raise the possibility of related experiments and potential applications in nonlinear optics and Bose–Einstein condensates.
文摘Indian Railways have been the largest people moving transport infrastructure in India.Over the years the systems and trains have been upgraded resulting in both better passenger amenities and reduction in travel time.The newest addition is the Vande Bharat Express,a semi-high-speed train that was introduced in India in 2019.The train currently runs between 10 routes and has brought significant changes to India’s railway network.This article explores the introduction of Vande Bharat Express trains in India and its effects on the country’s interstation time-space shrinkage using cartographic techniques.The cartographic techniques like stepwise multidimensional scaling and interpolation using the distance cartogram plugin in QGIS are mainly used for generating the time-space maps for various speeds.The limitations of these techniques and the methods to overcome those limitations are also explored in this article.
基金supported by the Natural Science Basic Research Program of Shanxi(Grant No.2024JC-YBMS-025)the Innovation Capability Support Program of Shanxi(Grant No.2024RS-CXTD-88)。
文摘This paper is devoted to investigating the spreading speed of a time-space periodic epidemic model with vital dynamics and standard incidence in discrete media. We establish the existence of the leftward and rightward spreading speeds for the infective individuals, which can be used to estimate how fast the disease spreads. To overcome the difficulty arising from the lack of comparison principle for such time-space periodic nonmonotone systems, our proof is mainly based on constructing a series of scalar time-space periodic equations, establishing the spreading speeds for such auxiliary equations and using comparison methods. It may be the first work to study the spreading speed for time-space periodic non-monotone systems.
基金supported by the National Key R&D Program of China(2021YFA0716902)National Natural Science Foundation of China(NSFC)under contract number 42374149 and 42004119National Science and Technology Major Project(2024ZD1002907)。
文摘Seismic anisotropy has been extensively acknowledged as a crucial element that influences the wave propagation characteristic during wavefield simulation,inversion and imaging.Transversely isotropy(TI)and orthorhombic anisotropy(OA)are two typical categories of anisotropic media in exploration geophysics.In comparison of the elastic wave equations in both TI and OA media,pseudo-acoustic wave equations(PWEs)based on the acoustic assumption can markedly reduce computational cost and complexity.However,the presently available PWEs may experience SV-wave contamination and instability when anisotropic parameters cannot satisfy the approximated condition.Exploiting pure-mode wave equations can effectively resolve the above-mentioned issues and generate pure P-wave events without any artifacts.To further improve the computational accuracy and efficiency,we develop two novel pure qP-wave equations(PPEs)and illustrate the corresponding numerical solutions in the timespace domain for 3D tilted TI(TTI)and tilted OA(TOA)media.First,the rational polynomials are adopted to estimate the exact pure qP-wave dispersion relations,which contain complicated pseudo-differential operators with irrational forms.The polynomial coefficients are produced by applying a linear optimization algorithm to minimize the objective function difference between the expansion formula and the exact one.Then,the developed optimized PPEs are efficiently implemented using the finite-difference(FD)method in the time-space domain by introducing a scalar operator,which can help avoid the problem of spectral-based algorithms and other calculation burdens.Structures of the new equations are concise and corresponding implementation processes are straightforward.Phase velocity analyses indicate that our proposed optimized equations can lead to reliable approximation results.3D synthetic examples demonstrate that our proposed FD-based PPEs can produce accurate and stable P-wave responses,and effectively describe the wavefield features in complicated TTI and TOA media.
文摘This paper investigates the mechanisms underlying the localization of Buddhism among the Kalmyks during Tsarist rule.It identifies and analyzes three interconnected processes:(1)the evolving framework of Tsarist policies aimed at administrative integration and religious regulation;(2)Kalmyk adaptive strategies,particularly the development of unique institutional responses(Supreme Lama election,Chief Bagshi,Dayanqi,and Temple Adherent systems)to navigate state constraints;and(3)spontaneous processes of cultural hybridity are manifested in material culture(e.g.,the Khoshut temple)and religious narratives(e.g.,Ulyanov’s reinvention of prophecies in Prophecies of Buddha).Utilizing the concept of“conjuncture practice”to frame these interactions,the study demonstrates how localization operated through a combination of regulatory pressure,community-level adaptation,and cultural synthesis,ultimately forging a distinct Kalmyk Buddhist expression within the imperial context.
基金Supported by Beijing Natural Science Foundation(Grant No.L231004)Young Elite Scientists Sponsorship Program by CAST(Grant No.2022QNRC001)+2 种基金Fundamental Research Funds for the Central Universities(Grant No.2025JBMC039)National Key Research and Development Program(Grant No.2022YFC2805200)National Natural Science Foundation of China(Grant No.52371338).
文摘Bio-inspired visual systems have garnered significant attention in robotics owing to their energy efficiency,rapid dynamic response,and environmental adaptability.Among these,event cameras-bio-inspired sensors that asynchronously report pixel-level brightness changes called’events’,stand out because of their ability to capture dynamic changes with minimal energy consumption,making them suitable for challenging conditions,such as low light or high-speed motion.However,current mapping and localization methods for event cameras depend primarily on point and line features,which struggle in sparse or low-feature environments and are unsuitable for static or slow-motion scenarios.We addressed these challenges by proposing a bio-inspired vision mapping and localization method using active LED markers(ALMs)combined with reprojection error optimization and asynchronous Kalman fusion.Our approach replaces traditional features with ALMs,thereby enabling accurate tracking under dynamic and low-feature conditions.The global mapping accuracy significantly improved by minimizing the reprojection error,with corner errors reduced from 16.8 cm to 3.1 cm after 400 iterations.The asynchronous Kalman fusion of multiple camera pose estimations from ALMs ensures precise localization with a high temporal efficiency.This method achieved a mean translation error of 0.078 m and a rotational error of 5.411°while evaluating dynamic motion.In addition,the method supported an output rate of 4.5 kHz while maintaining high localization accuracy in UAV spiral flight experiments.These results demonstrate the potential of the proposed approach for real-time robot localization in challenging environments.
