Sandy cobble soil exhibits pronounced heterogeneity.The assessment of the uncertainty surrounding its properties is crucial for the analysis of settlement characteristics resulting from volume loss during shield tunne...Sandy cobble soil exhibits pronounced heterogeneity.The assessment of the uncertainty surrounding its properties is crucial for the analysis of settlement characteristics resulting from volume loss during shield tunnelling.In this study,a series of probabilistic analyses of surface and subsurface settlements was conducted considering the spatial variability of the friction angle and reference stiffness modulus,under different volumetric block proportions(Pv)and tunnel volume loss rates(ηt).The non-intrusive random finite difference method was used to investigate the probabilistic characteristics of maximum surface settlement,width of subsurface settlement trough,maximum subsurface settlement,and subsurface soil volume loss rate through Monte Carlo simulations.Additionally,a comparison between stochastic and deterministic analysis results is presented to underscore the significance of probabilistic analysis.Parametric analyses were subsequently conducted to investigate the impacts of the key input parameters in random fields on the settlement characteristics.The results indicate that scenarios with higher Pv or greaterηt result in a higher dispersion of stochastic analysis results.Neglecting the spatial variability of soil properties and relying solely on the mean values of material parameters for deterministic analysis may result in an underestimation of surface and subsurface settlements.From a probabilistic perspective,deterministic analysis alone may prove inadequate in accurately capturing the volumetric deformation mode of the soil above the tunnel crown,potentially affecting the prediction of subsurface settlement.展开更多
Multimodal sentiment analysis aims to understand emotions from text,speech,and video data.However,current methods often overlook the dominant role of text and suffer from feature loss during integration.Given the vary...Multimodal sentiment analysis aims to understand emotions from text,speech,and video data.However,current methods often overlook the dominant role of text and suffer from feature loss during integration.Given the varying importance of each modality across different contexts,a central and pressing challenge in multimodal sentiment analysis lies in maximizing the use of rich intra-modal features while minimizing information loss during the fusion process.In response to these critical limitations,we propose a novel framework that integrates spatial position encoding and fusion embedding modules to address these issues.In our model,text is treated as the core modality,while speech and video features are selectively incorporated through a unique position-aware fusion process.The spatial position encoding strategy preserves the internal structural information of speech and visual modalities,enabling the model to capture localized intra-modal dependencies that are often overlooked.This design enhances the richness and discriminative power of the fused representation,enabling more accurate and context-aware sentiment prediction.Finally,we conduct comprehensive evaluations on two widely recognized standard datasets in the field—CMU-MOSI and CMU-MOSEI to validate the performance of the proposed model.The experimental results demonstrate that our model exhibits good performance and effectiveness for sentiment analysis tasks.展开更多
The conventional linear time-frequency analysis method cannot achieve high resolution and energy focusing in the time and frequency dimensions at the same time,especially in the low frequency region.In order to improv...The conventional linear time-frequency analysis method cannot achieve high resolution and energy focusing in the time and frequency dimensions at the same time,especially in the low frequency region.In order to improve the resolution of the linear time-frequency analysis method in the low-frequency region,we have proposed a W transform method,in which the instantaneous frequency is introduced as a parameter into the linear transformation,and the analysis time window is constructed which matches the instantaneous frequency of the seismic data.In this paper,the W transform method is compared with the Wigner-Ville distribution(WVD),a typical nonlinear time-frequency analysis method.The WVD method that shows the energy distribution in the time-frequency domain clearly indicates the gravitational center of time and the gravitational center of frequency of a wavelet,while the time-frequency spectrum of the W transform also has a clear gravitational center of energy focusing,because the instantaneous frequency corresponding to any time position is introduced as the transformation parameter.Therefore,the W transform can be benchmarked directly by the WVD method.We summarize the development of the W transform and three improved methods in recent years,and elaborate on the evolution of the standard W transform,the chirp-modulated W transform,the fractional-order W transform,and the linear canonical W transform.Through three application examples of W transform in fluvial sand body identification and reservoir prediction,it is verified that W transform can improve the resolution and energy focusing of time-frequency spectra.展开更多
With the increasingly complex and changeable electromagnetic environment,wireless communication systems are facing jamming and abnormal signal injection,which significantly affects the normal operation of a communicat...With the increasingly complex and changeable electromagnetic environment,wireless communication systems are facing jamming and abnormal signal injection,which significantly affects the normal operation of a communication system.In particular,the abnormal signals may emulate the normal signals,which makes it very challenging for abnormal signal recognition.In this paper,we propose a new abnormal signal recognition scheme,which combines time-frequency analysis with deep learning to effectively identify synthetic abnormal communication signals.Firstly,we emulate synthetic abnormal communication signals including seven jamming patterns.Then,we model an abnormal communication signals recognition system based on the communication protocol between the transmitter and the receiver.To improve the performance,we convert the original signal into the time-frequency spectrogram to develop an image classification algorithm.Simulation results demonstrate that the proposed method can effectively recognize the abnormal signals under various parameter configurations,even under low signal-to-noise ratio(SNR)and low jamming-to-signal ratio(JSR)conditions.展开更多
A new scheme of super-resolution optical fluctuation imaging(SOFI)is proposed to broaden its application in the high-order cumulant reconstruction by optimizing blinking characteristics,eliminating noise in raw data a...A new scheme of super-resolution optical fluctuation imaging(SOFI)is proposed to broaden its application in the high-order cumulant reconstruction by optimizing blinking characteristics,eliminating noise in raw data and applying multi-resolution analysis in cumulant reconstruction.A motor-driven rotating mask optical modulation system is designed to adjust the excitation lightfield and allows for fast deployment.Active-modulated fluorescence fluctuation superresolution microscopy with multi-resolution analysis(AMF-MRA-SOFI)demonstrates enhanced resolution ability and reconstruction quality in experiments performed on sample of conventional dyes,achieving a resolution of 100 nm in the fourth order compared to conventional SOFI reconstruction.Furthermore,our approach combining expansion super-resolution achieved a resolution at-57 nm.展开更多
Seepage refers to the flow of water through porous materials.This phenomenon has a crucial role in dam,slope,excavation,tunnel,and well design.Performing seepage analysis usually is a challenging task,as one must cope...Seepage refers to the flow of water through porous materials.This phenomenon has a crucial role in dam,slope,excavation,tunnel,and well design.Performing seepage analysis usually is a challenging task,as one must cope with the uncertainty associated with the parameters such as the hydraulic conductivity in the horizontal and vertical directions that drive this phenomenon.However,at the same time,the data on horizontal and vertical hydraulic conductivities are typically scarce in spatial resolution.In this context,so-called non-traditional approaches for uncertainty quantification(such as intervals and fuzzy variables)offer an interesting alternative to classical probabilistic methods,since they have been shown to be quite effective when limited information on the governing parameters of a phenomenon is available.Therefore,the main contribution of this study is the development of a framework for conducting seepage analysis in saturated soils,where uncertainty associated with hydraulic conductivity is characterized using fuzzy fields.This method to characterize uncertainty extends interval fields towards the domain of fuzzy numbers.In fact,it is illustrated that fuzzy fields are an effective tool for capturing uncertainties with a spatial component,since they allow one to account for available physical measurements.A case study in confined saturated soil shows that with the proposed framework,it is possible to quantify the uncertainty associated with seepage flow,exit gradient,and uplift force effectively.展开更多
Purpose–This paper investigates how high-speed rail(HSR)influences socioeconomic inequality by providing the first systematic bibliometric review of research trends,methodological approaches and thematic structures.I...Purpose–This paper investigates how high-speed rail(HSR)influences socioeconomic inequality by providing the first systematic bibliometric review of research trends,methodological approaches and thematic structures.It examines whether HSR fosters balanced regional development or reinforces spatial disparities.Design/methodology/approach–Using the Bibliometrix R package,237 records were retrieved from the Web of Science(1985–2024).Citation indicators,keyword co-occurrence and collaboration networks were combined with natural language processing(NLP)to classify studies by territorial scale,methodology,economic variables and inequality outcomes.Findings–The paper offers the first structured overview of how the literature conceptualizes the link between HSR and inequality.It highlights persistent gaps–scarcity of city-level analyses,limited socioeconomic indicators and reliance on Chinese case studies–providing a foundation for more comparative and interdisciplinary research.Originality/value–This paper contributes by offering a structured overview of how the literature has conceptualized and measured the relationship between HSR and inequality.By identifying persistent research gaps–such as the scarcity of city-level analyses,limited use of socioeconomic indicators,and overreliance on Chinese case studies–it provides a foundation for more comparative and interdisciplinary approaches.The study informs policymakers and researchers on how to design future infrastructure projects that balance efficiency with equity.展开更多
The incorporation of graphene fillers into polymer matrices has been recognized for its potential to enhance thermal conductivity,which is particularly beneficial for applications in thermal management.The uniformity ...The incorporation of graphene fillers into polymer matrices has been recognized for its potential to enhance thermal conductivity,which is particularly beneficial for applications in thermal management.The uniformity of graphene dispersion is pivotal to achieving optimal thermal conductivity,thereby directly influencing the effectiveness of thermal management,including the mitigation of local hot-spot temperatures.This research employs a quantitative approach to assess the distribution of graphene fillers within a PBX(plastic-bonded explosive)matrix,focusing specifically on the thermal management of hot spots.Through finite element method(FEM)simulations,we have explored the impact of graphene filler orientation,proximity to the central heat source,and spatial clustering on heat transfer.Our findings indicate that the strategic distribution of graphene fillers can create efficient thermal conduction channels,which significantly reduce the temperatures at local hot spots.In a model containing 0.336%graphene by volume,the central hot-spot temperature was reduced by approximately 60 K compared to a pure PBX material,under a heat flux of 600 W/m^(2).This study offers valuable insights into the optimization of the spatial arrangement of low-concentration graphene fillers,aiming to improve the thermal management capabilities of HMX-based PBX explosives.展开更多
In this paper,the Taixin Integrated Economic Zone in Shanxi Province is taken as the research object,and the coupling coordination degree model and bivariate spatial autocorrelation model are used to judge the couplin...In this paper,the Taixin Integrated Economic Zone in Shanxi Province is taken as the research object,and the coupling coordination degree model and bivariate spatial autocorrelation model are used to judge the coupling coordination and spatial-temporal correlation between urbanization and ecosystem service,and the hotspot analysis is used to judge the spatial-temporal trend of urbanization and ecosystem service.The results show that:(1)The urbanization level from 2000 to 2020 continued to rise,the areas with relatively high urbanization were concentrated in the central part of the study area,and the relatively high terrain areas on both sides of the study area,the urbanization was relatively slow,and the hotspot areas with highly significant and significant urbanization level from 2000 to 2020 were distributed as bands in the central part of the study area and the area was rising,and there was no Cold spot area distribution;between 2000 and 2020,the ecosystem service value in the study area increased by 2.6800×10^(8) yuan.Over these two decades,it exhibited a development trend that first rose and then declined.The woodland and grassland agglomeration areas were located on the two sides of the study area,forming highly significant and significant hotspots.Conversely,the central and northeastern parts of the study area were characterized by concentrated man-made land surfaces and croplands,resulting in the formation of highly significant and significant cold spots.(2)In the central part of the study area where man-made land surface and cultivated land are concentrated,the coupling coordination between urbanization and ecosystem service is in the intermediate dislocation and mild dislocation interval;the woodland and grassland concentration areas on both sides of the study area are ecologically fragile,and the coupling coordination between the two is in the level of less than intermediate dislocation.(3)From 2000 to 2020,urbanization and the value of ecosystem services were both negatively correlated,although the correlation coefficient was low.In the central and northeastern parts,urbanization and ecosystem service exhibited patterns of high-low,high-high,and low-low clustering.Conversely,on both sides of the study area,most of the clusters showed a low-high pattern.展开更多
Because of actual requirement,shield machine always excavates with an inclined angle in longitudinal direction.Since many previous studies mainly focus on the face stability of the horizontal shield tunnel,the effects...Because of actual requirement,shield machine always excavates with an inclined angle in longitudinal direction.Since many previous studies mainly focus on the face stability of the horizontal shield tunnel,the effects of tensile strength cut-off and pore water pressure on the face stability of the longitudinally inclined shield tunnel are not well investigated.A failure mechanism of a longitudinally inclined shield tunnel face is constructed based on the spatial discretization technique and the tensile strength cut-off criterion is introduced to modify the constructed failure mechanism.The pore water pressure is introduced as an external force into the equation of virtual work and the objective function of the chamber pressure of the shield machine is obtained.Moreover,the critical chamber pressure of the longitudinally inclined shield tunnel is computed by optimal calculation.Parametric analysis indicates that both tensile strength cut-off and pore water pressure have a significant impact on the chamber pressure and the range of the collapse block.Finally,the theoretical results are compared with the numerical results calculated by FLAC3D software which proves that the proposed approach is effective.展开更多
The traditional deterministic analysis for tunnel face stability neglects the uncertainties of geotechnical parameters,while the simplified reliability analysis which models the potential uncertainties by means of ran...The traditional deterministic analysis for tunnel face stability neglects the uncertainties of geotechnical parameters,while the simplified reliability analysis which models the potential uncertainties by means of random variables usually fails to account for soil spatial variability.To overcome these limitations,this study proposes an efficient framework for conducting reliability analysis and reliability-based design(RBD)of tunnel face stability in spatially variable soil strata.The three-dimensional(3D)rotational failure mechanism of the tunnel face is extended to account for the soil spatial variability,and a probabilistic framework is established by coupling the extended mechanism with the improved Hasofer-Lind-Rackwits-Fiessler recursive algorithm(iHLRF)as well as its inverse analysis formulation.The proposed framework allows for rapid and precise reliability analysis and RBD of tunnel face stability.To demonstrate the feasibility and efficacy of the proposed framework,an illustrative case of tunnelling in frictional soils is presented,where the soil's cohesion and friction angle are modelled as two anisotropic cross-correlated lognormal random fields.The results show that the proposed method can accurately estimate the failure probability(or reliability index)regarding the tunnel face stability and can efficiently determine the required supporting pressure for a target reliability index with soil spatial variability being taken into account.Furthermore,this study reveals the impact of various factors on the support pressure,including coefficient of variation,cross-correlation between cohesion and friction angle,as well as autocorrelation distance of spatially variable soil strata.The results also demonstrate the feasibility of using the forward and/or inverse first-order reliability method(FORM)in high-dimensional stochastic problems.It is hoped that this study may provide a practical and reliable framework for determining the stability of tunnels in complex soil strata.展开更多
Population aging has become an inevitable trend and exerted profound influences on socio-economic development in China.In this study,we utilized data from national population census and statistical yearbooks in 2010 a...Population aging has become an inevitable trend and exerted profound influences on socio-economic development in China.In this study,we utilized data from national population census and statistical yearbooks in 2010 and 2020 to explore spatio-temporal patterns of aging population and its coupling correlations with socio-economic factors from both global and local perspectives.The results from Local Indicators of Spatial Association(LISA)uncover notable spatial disparities in aging population rates,with higher rates concentrated in the eastern regions and lower rates in the western areas of the Chinese mainland.The results from the global correlation analysis with the changes in aging population rates show significant positive correlations with government interventions and industrial structures,but negatively correlated with economic development,social consumption,and medical facilities.From a local perspective,a Geographically Weighted(GW)correlation analysis is employed to uncover local correlations between aging trends and socio-economic factors.The insights gained from this technique not only underscore the complexity and diversity of economic implications stemming from population aging,but also provide invaluable guidance for crafting region-specific economic policies tailored to various stages of population aging.展开更多
With the rapid development ofmobile Internet,spatial crowdsourcing has becomemore andmore popular.Spatial crowdsourcing consists of many different types of applications,such as spatial crowd-sensing services.In terms ...With the rapid development ofmobile Internet,spatial crowdsourcing has becomemore andmore popular.Spatial crowdsourcing consists of many different types of applications,such as spatial crowd-sensing services.In terms of spatial crowd-sensing,it collects and analyzes traffic sensing data from clients like vehicles and traffic lights to construct intelligent traffic prediction models.Besides collecting sensing data,spatial crowdsourcing also includes spatial delivery services like DiDi and Uber.Appropriate task assignment and worker selection dominate the service quality for spatial crowdsourcing applications.Previous research conducted task assignments via traditional matching approaches or using simple network models.However,advanced mining methods are lacking to explore the relationship between workers,task publishers,and the spatio-temporal attributes in tasks.Therefore,in this paper,we propose a Deep Double Dueling Spatial-temporal Q Network(D3SQN)to adaptively learn the spatialtemporal relationship between task,task publishers,and workers in a dynamic environment to achieve optimal allocation.Specifically,D3SQNis revised through reinforcement learning by adding a spatial-temporal transformer that can estimate the expected state values and action advantages so as to improve the accuracy of task assignments.Extensive experiments are conducted over real data collected fromDiDi and ELM,and the simulation results verify the effectiveness of our proposed models.展开更多
In order to improve the detection accuracy of Doppler asymmetric spatial heterodyne(DASH)interferometer in harsh temperatures,an opto-mechanical-thermal integration analysis is carried out.Firstly,the correlation betw...In order to improve the detection accuracy of Doppler asymmetric spatial heterodyne(DASH)interferometer in harsh temperatures,an opto-mechanical-thermal integration analysis is carried out.Firstly,the correlation between the interference phase and temperature is established according to the working principle and the phase algorithm of the interferometer.Secondly,the optical mechanical thermal analysis model and thermal deformation data acquisition model are designed.The deformation data of the interference module and the imaging optical system at different temperatures are given by temperature load simulation analysis,and the phase error caused by thermal deformation is obtained by fitting.Finally,based on the wind speed error caused by thermal deformation of each component,a reasonable temperature control scheme is proposed.The results show that the interference module occupies the main cause,the temperature must be controlled within(20±0.05)℃,and the temperature control should be carried out for the temperature sensitive parts,and the wind speed error caused by the part is 3.8 m/s.The thermal drift between the magnification of the imaging optical system and the thermal drift of the relative position between the imaging optical system and the detector should occupy the secondary cause,which should be controlled within(20±2)℃,and the wind speed error caused by the part is 3.05 m/s.In summary,the wind measurement error caused by interference module,imaging optical system,and the relative position between the imaging optical system and the detector can be controlled within 6.85 m/s.The analysis and temperature control schemes presented in this paper can provide theoretical basis for DASH interferometer engineering applications.展开更多
Serial remote sensing images offer a valuable means of tracking the evolutionary changes and growth of a specific geographical area over time.Although the original images may provide limited insights,they harbor consi...Serial remote sensing images offer a valuable means of tracking the evolutionary changes and growth of a specific geographical area over time.Although the original images may provide limited insights,they harbor considerable potential for identifying clusters and patterns.The aggregation of these serial remote sensing images(SRSI)becomes increasingly viable as distinct patterns emerge in diverse scenarios,such as suburbanization,the expansion of native flora,and agricultural activities.In a novel approach,we propose an innovative method for extracting sequential patterns by combining Ant Colony Optimization(ACD)and Empirical Mode Decomposition(EMD).This integration of the newly developed EMD and ACO techniques proves remarkably effective in identifying the most significant characteristic features within serial remote sensing images,guided by specific criteria.Our findings highlight a substantial improvement in the efficiency of sequential pattern mining through the application of this unique hybrid method,seamlessly integrating EMD and ACO for feature selection.This study exposes the potential of our innovative methodology,particularly in the realms of urbanization,native vegetation expansion,and agricultural activities.展开更多
In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest a...In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest access. Urban Heat Island Effects are measurable phenomenon that are being experienced by the world’s most urbanized areas, including increased summer high temperatures and lower evapotranspiration from having impervious surfaces instead of vegetation and trees. Tree canopy cover is our natural mitigation tool that absorbs sunlight for photosynthesis, protects humans from incoming radiation, and releases cooling moisture into the air. Unfortunately, urban areas typically have low levels of vegetation. Vulnerable urban communities are lower-income areas of inner cities with less access to heat protection like air conditioners. This study uses mean evapotranspiration levels to assess the variability of urban heat island effects across the state of Tennessee. Results show that increased developed land surface cover in Tennessee creates measurable changes in atmospheric evapotranspiration. As a result, the mean evapotranspiration levels in areas with less tree vegetation are significantly lower than the surrounding forested areas. Central areas of urban cities in Tennessee had lower mean evapotranspiration recordings than surrounding areas with less development. This work demonstrates the need for increased tree canopy coverage.展开更多
Li transient concentration distribution in spherical active material particles can affect the maximum power density and the safe operating regime of the electric vehicles(EVs). On one hand, the quasiexact/exact soluti...Li transient concentration distribution in spherical active material particles can affect the maximum power density and the safe operating regime of the electric vehicles(EVs). On one hand, the quasiexact/exact solution obtained in the time/frequency domain is time-consuming and just as a reference value for approximate solutions;on the other hand, calculation errors and application range of approximate solutions not only rely on approximate algorithms but also on discharge modes. For the purpose to track the transient dynamics for Li solid-phase diffusion in spherical active particles with a tolerable error range and for a wide applicable range, it is necessary to choose optimal approximate algorithms in terms of discharge modes and the nature of active material particles. In this study, approximation methods,such as diffusion length method, polynomial profile approximation method, Padé approximation method,pseudo steady state method, eigenfunction-based Galerkin collocation method, and separation of variables method for solving Li solid-phase diffusion in spherical active particles are compared from calculation fundamentals to algorithm implementation. Furthermore, these approximate solutions are quantitatively compared to the quasi-exact/exact solution in the time/frequency domain under typical discharge modes, i.e., start-up, slow-down, and speed-up. The results obtained from the viewpoint of time-frequency analysis offer a theoretical foundation on how to track Li transient concentration profile in spherical active particles with a high precision and for a wide application range. In turn, optimal solutions of Li solid diffusion equations for spherical active particles can improve the reliability in predicting safe operating regime and estimating maximum power for automotive batteries.展开更多
A novel method of Doppler frequency extraction is proposed for Doppler radar scoring systems. The idea is that the time-frequency map can show how the Doppler frequency varies along the time-line, so the Doppler frequ...A novel method of Doppler frequency extraction is proposed for Doppler radar scoring systems. The idea is that the time-frequency map can show how the Doppler frequency varies along the time-line, so the Doppler frequency extraction becomes curve detection in the image-view. A set of morphological operations are used to implement curve detection. And a map fusion scheme is presented to eliminate the influence of strong direct current （DC） component of echo signal during curve detection. The radar real-life data are used to illustrate the performance of the new approach. Experimental results show that the proposed method can overcome the shortcomings of piecewise-processing-based FFT method and can improve the measuring precision of miss distance.展开更多
Multi-radar signal separation is a critical process in modern reconnaissance systems. However, the complicated battlefield is typically confronted with increasing electronic equipment and complex radar waveforms. The ...Multi-radar signal separation is a critical process in modern reconnaissance systems. However, the complicated battlefield is typically confronted with increasing electronic equipment and complex radar waveforms. The intercepted signal is difficult to separate with conventional parameters because of severe overlapping in both time and frequency domains. On the contrary, time-frequency analysis maps the 1D signal into a 2D time-frequency plane, which provides a better insight into the signal than traditional methods. Particularly, the parameterized time-frequency analysis (PTFA) shows great potential in processing such non stationary signals. Five procedures for the PTFA are proposed to separate the overlapped multi-radar signal, including initiation, instantaneous frequency estimation with PTFA, signal demodulation, signal separation with adaptive filter and signal recovery. The proposed method is verified with both simulated and real signals, which shows good performance in the application on multi-radar signal separation.展开更多
基金supported by the Natural Science Foundation of Beijing Municipality(No.8222004),Chinathe National Natural Science Foundation of China(No.51978019)+3 种基金the Natural Science Foundation of Henan Province(No.252300420445),Chinathe Doctoral Research Initiation Fund of Henan University of Science and Technology(No.4007/13480062),Chinathe Henan Postdoctoral Foundation(No.13554005),Chinathe Joint Fund of Science and Technology R&D Program of Henan Province(No.232103810082),China。
文摘Sandy cobble soil exhibits pronounced heterogeneity.The assessment of the uncertainty surrounding its properties is crucial for the analysis of settlement characteristics resulting from volume loss during shield tunnelling.In this study,a series of probabilistic analyses of surface and subsurface settlements was conducted considering the spatial variability of the friction angle and reference stiffness modulus,under different volumetric block proportions(Pv)and tunnel volume loss rates(ηt).The non-intrusive random finite difference method was used to investigate the probabilistic characteristics of maximum surface settlement,width of subsurface settlement trough,maximum subsurface settlement,and subsurface soil volume loss rate through Monte Carlo simulations.Additionally,a comparison between stochastic and deterministic analysis results is presented to underscore the significance of probabilistic analysis.Parametric analyses were subsequently conducted to investigate the impacts of the key input parameters in random fields on the settlement characteristics.The results indicate that scenarios with higher Pv or greaterηt result in a higher dispersion of stochastic analysis results.Neglecting the spatial variability of soil properties and relying solely on the mean values of material parameters for deterministic analysis may result in an underestimation of surface and subsurface settlements.From a probabilistic perspective,deterministic analysis alone may prove inadequate in accurately capturing the volumetric deformation mode of the soil above the tunnel crown,potentially affecting the prediction of subsurface settlement.
基金supported by the Collaborative Tackling Project of the Yangtze River Delta SciTech Innovation Community(Nos.2024CSJGG01503,2024CSJGG01500)Guangxi Key Research and Development Program(No.AB24010317)Jiangxi Provincial Key Laboratory of Electronic Data Control and Forensics(Jiangxi Police College)(No.2025JXJYKFJJ002).
文摘Multimodal sentiment analysis aims to understand emotions from text,speech,and video data.However,current methods often overlook the dominant role of text and suffer from feature loss during integration.Given the varying importance of each modality across different contexts,a central and pressing challenge in multimodal sentiment analysis lies in maximizing the use of rich intra-modal features while minimizing information loss during the fusion process.In response to these critical limitations,we propose a novel framework that integrates spatial position encoding and fusion embedding modules to address these issues.In our model,text is treated as the core modality,while speech and video features are selectively incorporated through a unique position-aware fusion process.The spatial position encoding strategy preserves the internal structural information of speech and visual modalities,enabling the model to capture localized intra-modal dependencies that are often overlooked.This design enhances the richness and discriminative power of the fused representation,enabling more accurate and context-aware sentiment prediction.Finally,we conduct comprehensive evaluations on two widely recognized standard datasets in the field—CMU-MOSI and CMU-MOSEI to validate the performance of the proposed model.The experimental results demonstrate that our model exhibits good performance and effectiveness for sentiment analysis tasks.
基金Supported by the National Science Foundation of China(42055402)。
文摘The conventional linear time-frequency analysis method cannot achieve high resolution and energy focusing in the time and frequency dimensions at the same time,especially in the low frequency region.In order to improve the resolution of the linear time-frequency analysis method in the low-frequency region,we have proposed a W transform method,in which the instantaneous frequency is introduced as a parameter into the linear transformation,and the analysis time window is constructed which matches the instantaneous frequency of the seismic data.In this paper,the W transform method is compared with the Wigner-Ville distribution(WVD),a typical nonlinear time-frequency analysis method.The WVD method that shows the energy distribution in the time-frequency domain clearly indicates the gravitational center of time and the gravitational center of frequency of a wavelet,while the time-frequency spectrum of the W transform also has a clear gravitational center of energy focusing,because the instantaneous frequency corresponding to any time position is introduced as the transformation parameter.Therefore,the W transform can be benchmarked directly by the WVD method.We summarize the development of the W transform and three improved methods in recent years,and elaborate on the evolution of the standard W transform,the chirp-modulated W transform,the fractional-order W transform,and the linear canonical W transform.Through three application examples of W transform in fluvial sand body identification and reservoir prediction,it is verified that W transform can improve the resolution and energy focusing of time-frequency spectra.
基金supported by Natural Science Foundation of China(No.62371231)Natural Science Foundation on Frontier Leading Technology Basic Research Project of Jiangsu under Grant BK20222001Jiangsu Provincial Key Research and Development Program(No.BE2023027).
文摘With the increasingly complex and changeable electromagnetic environment,wireless communication systems are facing jamming and abnormal signal injection,which significantly affects the normal operation of a communication system.In particular,the abnormal signals may emulate the normal signals,which makes it very challenging for abnormal signal recognition.In this paper,we propose a new abnormal signal recognition scheme,which combines time-frequency analysis with deep learning to effectively identify synthetic abnormal communication signals.Firstly,we emulate synthetic abnormal communication signals including seven jamming patterns.Then,we model an abnormal communication signals recognition system based on the communication protocol between the transmitter and the receiver.To improve the performance,we convert the original signal into the time-frequency spectrogram to develop an image classification algorithm.Simulation results demonstrate that the proposed method can effectively recognize the abnormal signals under various parameter configurations,even under low signal-to-noise ratio(SNR)and low jamming-to-signal ratio(JSR)conditions.
基金supported by the National Natural Science Foundation of China(62175034,62175036,32271510)the National Key R&D Program of China(2021YFF0502900)+2 种基金the Science and Technology Research Program of Shanghai(Grant No.19DZ2282100)the Shanghai Key Laboratory of Metasurfaces for Light Manipulation(23dz2260100)the Shanghai Engineering Technology Research Center of Hair Medicine(19DZ2250500).
文摘A new scheme of super-resolution optical fluctuation imaging(SOFI)is proposed to broaden its application in the high-order cumulant reconstruction by optimizing blinking characteristics,eliminating noise in raw data and applying multi-resolution analysis in cumulant reconstruction.A motor-driven rotating mask optical modulation system is designed to adjust the excitation lightfield and allows for fast deployment.Active-modulated fluorescence fluctuation superresolution microscopy with multi-resolution analysis(AMF-MRA-SOFI)demonstrates enhanced resolution ability and reconstruction quality in experiments performed on sample of conventional dyes,achieving a resolution of 100 nm in the fourth order compared to conventional SOFI reconstruction.Furthermore,our approach combining expansion super-resolution achieved a resolution at-57 nm.
文摘Seepage refers to the flow of water through porous materials.This phenomenon has a crucial role in dam,slope,excavation,tunnel,and well design.Performing seepage analysis usually is a challenging task,as one must cope with the uncertainty associated with the parameters such as the hydraulic conductivity in the horizontal and vertical directions that drive this phenomenon.However,at the same time,the data on horizontal and vertical hydraulic conductivities are typically scarce in spatial resolution.In this context,so-called non-traditional approaches for uncertainty quantification(such as intervals and fuzzy variables)offer an interesting alternative to classical probabilistic methods,since they have been shown to be quite effective when limited information on the governing parameters of a phenomenon is available.Therefore,the main contribution of this study is the development of a framework for conducting seepage analysis in saturated soils,where uncertainty associated with hydraulic conductivity is characterized using fuzzy fields.This method to characterize uncertainty extends interval fields towards the domain of fuzzy numbers.In fact,it is illustrated that fuzzy fields are an effective tool for capturing uncertainties with a spatial component,since they allow one to account for available physical measurements.A case study in confined saturated soil shows that with the proposed framework,it is possible to quantify the uncertainty associated with seepage flow,exit gradient,and uplift force effectively.
文摘Purpose–This paper investigates how high-speed rail(HSR)influences socioeconomic inequality by providing the first systematic bibliometric review of research trends,methodological approaches and thematic structures.It examines whether HSR fosters balanced regional development or reinforces spatial disparities.Design/methodology/approach–Using the Bibliometrix R package,237 records were retrieved from the Web of Science(1985–2024).Citation indicators,keyword co-occurrence and collaboration networks were combined with natural language processing(NLP)to classify studies by territorial scale,methodology,economic variables and inequality outcomes.Findings–The paper offers the first structured overview of how the literature conceptualizes the link between HSR and inequality.It highlights persistent gaps–scarcity of city-level analyses,limited socioeconomic indicators and reliance on Chinese case studies–providing a foundation for more comparative and interdisciplinary research.Originality/value–This paper contributes by offering a structured overview of how the literature has conceptualized and measured the relationship between HSR and inequality.By identifying persistent research gaps–such as the scarcity of city-level analyses,limited use of socioeconomic indicators,and overreliance on Chinese case studies–it provides a foundation for more comparative and interdisciplinary approaches.The study informs policymakers and researchers on how to design future infrastructure projects that balance efficiency with equity.
基金supported by the National Natural Science Foundation of China(Grant No.U2330208).
文摘The incorporation of graphene fillers into polymer matrices has been recognized for its potential to enhance thermal conductivity,which is particularly beneficial for applications in thermal management.The uniformity of graphene dispersion is pivotal to achieving optimal thermal conductivity,thereby directly influencing the effectiveness of thermal management,including the mitigation of local hot-spot temperatures.This research employs a quantitative approach to assess the distribution of graphene fillers within a PBX(plastic-bonded explosive)matrix,focusing specifically on the thermal management of hot spots.Through finite element method(FEM)simulations,we have explored the impact of graphene filler orientation,proximity to the central heat source,and spatial clustering on heat transfer.Our findings indicate that the strategic distribution of graphene fillers can create efficient thermal conduction channels,which significantly reduce the temperatures at local hot spots.In a model containing 0.336%graphene by volume,the central hot-spot temperature was reduced by approximately 60 K compared to a pure PBX material,under a heat flux of 600 W/m^(2).This study offers valuable insights into the optimization of the spatial arrangement of low-concentration graphene fillers,aiming to improve the thermal management capabilities of HMX-based PBX explosives.
基金supported by the Natural Science Foundation of Shanxi Province(Grant No.20210302124437)the Graduate Student Research and Innovation Project of Shanxi Province(Grant No.2023KY551).
文摘In this paper,the Taixin Integrated Economic Zone in Shanxi Province is taken as the research object,and the coupling coordination degree model and bivariate spatial autocorrelation model are used to judge the coupling coordination and spatial-temporal correlation between urbanization and ecosystem service,and the hotspot analysis is used to judge the spatial-temporal trend of urbanization and ecosystem service.The results show that:(1)The urbanization level from 2000 to 2020 continued to rise,the areas with relatively high urbanization were concentrated in the central part of the study area,and the relatively high terrain areas on both sides of the study area,the urbanization was relatively slow,and the hotspot areas with highly significant and significant urbanization level from 2000 to 2020 were distributed as bands in the central part of the study area and the area was rising,and there was no Cold spot area distribution;between 2000 and 2020,the ecosystem service value in the study area increased by 2.6800×10^(8) yuan.Over these two decades,it exhibited a development trend that first rose and then declined.The woodland and grassland agglomeration areas were located on the two sides of the study area,forming highly significant and significant hotspots.Conversely,the central and northeastern parts of the study area were characterized by concentrated man-made land surfaces and croplands,resulting in the formation of highly significant and significant cold spots.(2)In the central part of the study area where man-made land surface and cultivated land are concentrated,the coupling coordination between urbanization and ecosystem service is in the intermediate dislocation and mild dislocation interval;the woodland and grassland concentration areas on both sides of the study area are ecologically fragile,and the coupling coordination between the two is in the level of less than intermediate dislocation.(3)From 2000 to 2020,urbanization and the value of ecosystem services were both negatively correlated,although the correlation coefficient was low.In the central and northeastern parts,urbanization and ecosystem service exhibited patterns of high-low,high-high,and low-low clustering.Conversely,on both sides of the study area,most of the clusters showed a low-high pattern.
基金Projects(52278395,52208409) supported by the National Natural Science Foundation of ChinaProject(2022JJ40531) supported by the Natural Science Foundation of Hunan Province,China。
文摘Because of actual requirement,shield machine always excavates with an inclined angle in longitudinal direction.Since many previous studies mainly focus on the face stability of the horizontal shield tunnel,the effects of tensile strength cut-off and pore water pressure on the face stability of the longitudinally inclined shield tunnel are not well investigated.A failure mechanism of a longitudinally inclined shield tunnel face is constructed based on the spatial discretization technique and the tensile strength cut-off criterion is introduced to modify the constructed failure mechanism.The pore water pressure is introduced as an external force into the equation of virtual work and the objective function of the chamber pressure of the shield machine is obtained.Moreover,the critical chamber pressure of the longitudinally inclined shield tunnel is computed by optimal calculation.Parametric analysis indicates that both tensile strength cut-off and pore water pressure have a significant impact on the chamber pressure and the range of the collapse block.Finally,the theoretical results are compared with the numerical results calculated by FLAC3D software which proves that the proposed approach is effective.
基金supported by the National Natural Science Foundation of China(Grant No.U22A20594)the Fundamental Research Funds for the Central Universities(Grant No.B230205028)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant No.KYCX23_0694).
文摘The traditional deterministic analysis for tunnel face stability neglects the uncertainties of geotechnical parameters,while the simplified reliability analysis which models the potential uncertainties by means of random variables usually fails to account for soil spatial variability.To overcome these limitations,this study proposes an efficient framework for conducting reliability analysis and reliability-based design(RBD)of tunnel face stability in spatially variable soil strata.The three-dimensional(3D)rotational failure mechanism of the tunnel face is extended to account for the soil spatial variability,and a probabilistic framework is established by coupling the extended mechanism with the improved Hasofer-Lind-Rackwits-Fiessler recursive algorithm(iHLRF)as well as its inverse analysis formulation.The proposed framework allows for rapid and precise reliability analysis and RBD of tunnel face stability.To demonstrate the feasibility and efficacy of the proposed framework,an illustrative case of tunnelling in frictional soils is presented,where the soil's cohesion and friction angle are modelled as two anisotropic cross-correlated lognormal random fields.The results show that the proposed method can accurately estimate the failure probability(or reliability index)regarding the tunnel face stability and can efficiently determine the required supporting pressure for a target reliability index with soil spatial variability being taken into account.Furthermore,this study reveals the impact of various factors on the support pressure,including coefficient of variation,cross-correlation between cohesion and friction angle,as well as autocorrelation distance of spatially variable soil strata.The results also demonstrate the feasibility of using the forward and/or inverse first-order reliability method(FORM)in high-dimensional stochastic problems.It is hoped that this study may provide a practical and reliable framework for determining the stability of tunnels in complex soil strata.
基金National Natural Science Foundation of China(No.42071368)Fundamental Research Funds for the Central Universities(Nos.2042022dx0001,2042024kf0005).
文摘Population aging has become an inevitable trend and exerted profound influences on socio-economic development in China.In this study,we utilized data from national population census and statistical yearbooks in 2010 and 2020 to explore spatio-temporal patterns of aging population and its coupling correlations with socio-economic factors from both global and local perspectives.The results from Local Indicators of Spatial Association(LISA)uncover notable spatial disparities in aging population rates,with higher rates concentrated in the eastern regions and lower rates in the western areas of the Chinese mainland.The results from the global correlation analysis with the changes in aging population rates show significant positive correlations with government interventions and industrial structures,but negatively correlated with economic development,social consumption,and medical facilities.From a local perspective,a Geographically Weighted(GW)correlation analysis is employed to uncover local correlations between aging trends and socio-economic factors.The insights gained from this technique not only underscore the complexity and diversity of economic implications stemming from population aging,but also provide invaluable guidance for crafting region-specific economic policies tailored to various stages of population aging.
基金supported in part by the Pioneer and Leading Goose R&D Program of Zhejiang Province under Grant 2022C01083 (Dr.Yu Li,https://zjnsf.kjt.zj.gov.cn/)Pioneer and Leading Goose R&D Program of Zhejiang Province under Grant 2023C01217 (Dr.Yu Li,https://zjnsf.kjt.zj.gov.cn/).
文摘With the rapid development ofmobile Internet,spatial crowdsourcing has becomemore andmore popular.Spatial crowdsourcing consists of many different types of applications,such as spatial crowd-sensing services.In terms of spatial crowd-sensing,it collects and analyzes traffic sensing data from clients like vehicles and traffic lights to construct intelligent traffic prediction models.Besides collecting sensing data,spatial crowdsourcing also includes spatial delivery services like DiDi and Uber.Appropriate task assignment and worker selection dominate the service quality for spatial crowdsourcing applications.Previous research conducted task assignments via traditional matching approaches or using simple network models.However,advanced mining methods are lacking to explore the relationship between workers,task publishers,and the spatio-temporal attributes in tasks.Therefore,in this paper,we propose a Deep Double Dueling Spatial-temporal Q Network(D3SQN)to adaptively learn the spatialtemporal relationship between task,task publishers,and workers in a dynamic environment to achieve optimal allocation.Specifically,D3SQNis revised through reinforcement learning by adding a spatial-temporal transformer that can estimate the expected state values and action advantages so as to improve the accuracy of task assignments.Extensive experiments are conducted over real data collected fromDiDi and ELM,and the simulation results verify the effectiveness of our proposed models.
文摘In order to improve the detection accuracy of Doppler asymmetric spatial heterodyne(DASH)interferometer in harsh temperatures,an opto-mechanical-thermal integration analysis is carried out.Firstly,the correlation between the interference phase and temperature is established according to the working principle and the phase algorithm of the interferometer.Secondly,the optical mechanical thermal analysis model and thermal deformation data acquisition model are designed.The deformation data of the interference module and the imaging optical system at different temperatures are given by temperature load simulation analysis,and the phase error caused by thermal deformation is obtained by fitting.Finally,based on the wind speed error caused by thermal deformation of each component,a reasonable temperature control scheme is proposed.The results show that the interference module occupies the main cause,the temperature must be controlled within(20±0.05)℃,and the temperature control should be carried out for the temperature sensitive parts,and the wind speed error caused by the part is 3.8 m/s.The thermal drift between the magnification of the imaging optical system and the thermal drift of the relative position between the imaging optical system and the detector should occupy the secondary cause,which should be controlled within(20±2)℃,and the wind speed error caused by the part is 3.05 m/s.In summary,the wind measurement error caused by interference module,imaging optical system,and the relative position between the imaging optical system and the detector can be controlled within 6.85 m/s.The analysis and temperature control schemes presented in this paper can provide theoretical basis for DASH interferometer engineering applications.
文摘Serial remote sensing images offer a valuable means of tracking the evolutionary changes and growth of a specific geographical area over time.Although the original images may provide limited insights,they harbor considerable potential for identifying clusters and patterns.The aggregation of these serial remote sensing images(SRSI)becomes increasingly viable as distinct patterns emerge in diverse scenarios,such as suburbanization,the expansion of native flora,and agricultural activities.In a novel approach,we propose an innovative method for extracting sequential patterns by combining Ant Colony Optimization(ACD)and Empirical Mode Decomposition(EMD).This integration of the newly developed EMD and ACO techniques proves remarkably effective in identifying the most significant characteristic features within serial remote sensing images,guided by specific criteria.Our findings highlight a substantial improvement in the efficiency of sequential pattern mining through the application of this unique hybrid method,seamlessly integrating EMD and ACO for feature selection.This study exposes the potential of our innovative methodology,particularly in the realms of urbanization,native vegetation expansion,and agricultural activities.
文摘In recent decades, Urban Heat Island Effects have become more pronounced and more widely examined. Despite great technological advances, our current societies still experience great spatial disparity in urban forest access. Urban Heat Island Effects are measurable phenomenon that are being experienced by the world’s most urbanized areas, including increased summer high temperatures and lower evapotranspiration from having impervious surfaces instead of vegetation and trees. Tree canopy cover is our natural mitigation tool that absorbs sunlight for photosynthesis, protects humans from incoming radiation, and releases cooling moisture into the air. Unfortunately, urban areas typically have low levels of vegetation. Vulnerable urban communities are lower-income areas of inner cities with less access to heat protection like air conditioners. This study uses mean evapotranspiration levels to assess the variability of urban heat island effects across the state of Tennessee. Results show that increased developed land surface cover in Tennessee creates measurable changes in atmospheric evapotranspiration. As a result, the mean evapotranspiration levels in areas with less tree vegetation are significantly lower than the surrounding forested areas. Central areas of urban cities in Tennessee had lower mean evapotranspiration recordings than surrounding areas with less development. This work demonstrates the need for increased tree canopy coverage.
基金the financial support from the National Science Foundation of China(22078190 and 12002196)the National Key Research and Development Program of China(2020YFB1505802)。
文摘Li transient concentration distribution in spherical active material particles can affect the maximum power density and the safe operating regime of the electric vehicles(EVs). On one hand, the quasiexact/exact solution obtained in the time/frequency domain is time-consuming and just as a reference value for approximate solutions;on the other hand, calculation errors and application range of approximate solutions not only rely on approximate algorithms but also on discharge modes. For the purpose to track the transient dynamics for Li solid-phase diffusion in spherical active particles with a tolerable error range and for a wide applicable range, it is necessary to choose optimal approximate algorithms in terms of discharge modes and the nature of active material particles. In this study, approximation methods,such as diffusion length method, polynomial profile approximation method, Padé approximation method,pseudo steady state method, eigenfunction-based Galerkin collocation method, and separation of variables method for solving Li solid-phase diffusion in spherical active particles are compared from calculation fundamentals to algorithm implementation. Furthermore, these approximate solutions are quantitatively compared to the quasi-exact/exact solution in the time/frequency domain under typical discharge modes, i.e., start-up, slow-down, and speed-up. The results obtained from the viewpoint of time-frequency analysis offer a theoretical foundation on how to track Li transient concentration profile in spherical active particles with a high precision and for a wide application range. In turn, optimal solutions of Li solid diffusion equations for spherical active particles can improve the reliability in predicting safe operating regime and estimating maximum power for automotive batteries.
基金the Ministerial Level Advanced Research Foundation(020045089)
文摘A novel method of Doppler frequency extraction is proposed for Doppler radar scoring systems. The idea is that the time-frequency map can show how the Doppler frequency varies along the time-line, so the Doppler frequency extraction becomes curve detection in the image-view. A set of morphological operations are used to implement curve detection. And a map fusion scheme is presented to eliminate the influence of strong direct current （DC） component of echo signal during curve detection. The radar real-life data are used to illustrate the performance of the new approach. Experimental results show that the proposed method can overcome the shortcomings of piecewise-processing-based FFT method and can improve the measuring precision of miss distance.
文摘Multi-radar signal separation is a critical process in modern reconnaissance systems. However, the complicated battlefield is typically confronted with increasing electronic equipment and complex radar waveforms. The intercepted signal is difficult to separate with conventional parameters because of severe overlapping in both time and frequency domains. On the contrary, time-frequency analysis maps the 1D signal into a 2D time-frequency plane, which provides a better insight into the signal than traditional methods. Particularly, the parameterized time-frequency analysis (PTFA) shows great potential in processing such non stationary signals. Five procedures for the PTFA are proposed to separate the overlapped multi-radar signal, including initiation, instantaneous frequency estimation with PTFA, signal demodulation, signal separation with adaptive filter and signal recovery. The proposed method is verified with both simulated and real signals, which shows good performance in the application on multi-radar signal separation.
