The second-order correlation function of photons is the primary means to quantitatively describe the second-order coherence of a light field.In contrast to the stationary second-order correlation function,the temporal...The second-order correlation function of photons is the primary means to quantitatively describe the second-order coherence of a light field.In contrast to the stationary second-order correlation function,the temporal second-order correlation function can be used to study the second-order coherence of a transient light field.Based on the Monte Carlo algorithm,we carried out theoretical simulation on the temporal second-order correlation function from the perspective of photon statistics.By introducing experimental factors into the simulation,such as intensity jitter of the light field and time resolution of the instruments,the effects of imperfect experimental conditions on the measurement of second-order correlation function have also been elucidated.Our results provide theoretical guidance and analysis methods for experimental measurements on the secondorder coherence of light fields.展开更多
Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithm...Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithms restore image sequences of dynamic scenes, offering advantages such as reduced bandwidth and storage space requirements. The temporal correlation in video data is crucial for Video SCI, as it leverages the temporal relationships among frames to enhance the efficiency and quality of reconstruction algorithms, particularly for fast-moving objects.This paper discretizes video frames to create image datasets with the same data volume but differing temporal correlations. We utilized the state-of-the-art(SOTA) reconstruction framework, EfficientSCI++, to train various compressed reconstruction models with these differing temporal correlations. Evaluating the reconstruction results from these models, our simulation experiments confirm that a reduction in temporal correlation leads to decreased reconstruction accuracy. Additionally, we simulated the reconstruction outcomes of datasets devoid of temporal correlation, illustrating that models trained on non-temporal data affect the temporal feature extraction capabilities of transformers, resulting in negligible impacts on the evaluation of reconstruction results for non-temporal correlation test datasets.展开更多
Target tracking is an essential task in contemporary computer vision applications.However,its effectiveness is susceptible to model drift,due to the different appearances of targets,which often compromises tracking ro...Target tracking is an essential task in contemporary computer vision applications.However,its effectiveness is susceptible to model drift,due to the different appearances of targets,which often compromises tracking robustness and precision.In this paper,a universally applicable method based on correlation filters is introduced to mitigate model drift in complex scenarios.It employs temporal-confidence samples as a priori to guide the model update process and ensure its precision and consistency over a long period.An improved update mechanism based on the peak side-lobe to peak correlation energy(PSPCE)criterion is proposed,which selects high-confidence samples along the temporal dimension to update temporal-confidence samples.Extensive experiments on various benchmarks demonstrate that the proposed method achieves a competitive performance compared with the state-of-the-art methods.Especially when the target appearance changes significantly,our method is more robust and can achieve a balance between precision and speed.Specifically,on the object tracking benchmark(OTB-100)dataset,compared to the baseline,the tracking precision of our model improves by 8.8%,8.8%,5.1%,5.6%,and 6.9%for background clutter,deformation,occlusion,rotation,and illumination variation,respectively.The results indicate that this proposed method can significantly enhance the robustness and precision of target tracking in dynamic and challenging environments,offering a reliable solution for applications such as real-time monitoring,autonomous driving,and precision guidance.展开更多
Taking the time varying nature of wireless channels into account, two user selection schemes with lower complexity are developed for multiple-input multiple-output broadcast （MIMO BC）systems. According to the relati...Taking the time varying nature of wireless channels into account, two user selection schemes with lower complexity are developed for multiple-input multiple-output broadcast （MIMO BC）systems. According to the relationship between coherence time and Doppler frequency, an information frame is divided into several segments. At the beginning of each segment, the user selection is carded out with the greedy selection algorithm. In the simplified user selection algorithms employing the temporal correlation （SUSTC）, the selection results are applied for all the remaining slots in each segment. But in the improved simplified user selection algorithms employing the temporal correlation（ISUSTC）, at the remaining slots, users are kept with favorable channel conditions selected at the previous slot, and other users are updated from the candidate pool to communicate simultaneously. Simulations show that compared with the greedy user selection method, the proposed algorithms can reduce the selection complexity with a little sum capacity loss.展开更多
Rock failure process as a natural response to mining activities is associated with seismic events, which can pose a potential hazard to mine operators, equipment and infrastructures. Mining-induced seismicity has been...Rock failure process as a natural response to mining activities is associated with seismic events, which can pose a potential hazard to mine operators, equipment and infrastructures. Mining-induced seismicity has been found to be internally correlated in both time and space domains as a result of rock fracturing during progressive mining activities. Understanding the spatio-temporal(ST) correlation of mininginduced seismic events is an essential step to use seismic data for further analysis, such as rockburst prediction and caving assessment. However, there are no established methods to perform this critical task. Input parameters used for the prediction of seismic hazards, such as the time window of past data and effective prediction distance, are determined based on site-specific experience without statistical or physical reasons to support. Therefore, the accuracy of current seismic prediction methods is largely constrained, which can only be addressed by quantitively assessing the ST correlations of mininginduced seismicity. In this research, the ST correlation of seismic event energy collected from a study mine is quantitatively analysed using various statistical methods, including autocorrelation function(ACF), semivariogram and Moran’s I analysis. In addition, based on the integrated ST correlation assessment, seismic events are further classified into seven clusters, so as to assess the correlations within individual clusters. The correlation of seismic events is found to be quantitatively assessable, and their correlations may vary throughout the mineral extraction process.展开更多
User identity linkage(UIL)refers to identifying user accounts belonging to the same identity across different social media platforms.Most of the current research is based on text analysis,which fails to fully explore ...User identity linkage(UIL)refers to identifying user accounts belonging to the same identity across different social media platforms.Most of the current research is based on text analysis,which fails to fully explore the rich image resources generated by users,and the existing attempts touch on the multimodal domain,but still face the challenge of semantic differences between text and images.Given this,we investigate the UIL task across different social media platforms based on multimodal user-generated contents(UGCs).We innovatively introduce the efficient user identity linkage via aligned multi-modal features and temporal correlation(EUIL)approach.The method first generates captions for user-posted images with the BLIP model,alleviating the problem of missing textual information.Subsequently,we extract aligned text and image features with the CLIP model,which closely aligns the two modalities and significantly reduces the semantic gap.Accordingly,we construct a set of adapter modules to integrate the multimodal features.Furthermore,we design a temporal weight assignment mechanism to incorporate the temporal dimension of user behavior.We evaluate the proposed scheme on the real-world social dataset TWIN,and the results show that our method reaches 86.39%accuracy,which demonstrates the excellence in handling multimodal data,and provides strong algorithmic support for UIL.展开更多
We simulated the temporal correlation of sound transmission using a two-dimensional advective frozen-ocean model with temperature data from a temperature sensor array on a propagation path in the South China Sea （SCS...We simulated the temporal correlation of sound transmission using a two-dimensional advective frozen-ocean model with temperature data from a temperature sensor array on a propagation path in the South China Sea （SCS） Experiment 2009, and investigated the relationships of temporal correlation length, source-receiver range, and maximal sound speed fluctuation mainly caused by the solitary internal waves. We found that the temporal correlation length is -h2-power dependent on source-receiver range and -0.9-power dependent on maximal sound speed fluctuation. The empirical relationship is deduced from one-day environmental measurements in a limited area, needing more works and verification in the future with more acoustic data. But the relationship is useful in many applications in the area of SCS Experiment 2009.展开更多
Universal lesion detection(ULD)methods for computed tomography(CT)images play a vital role in the modern clinical medicine and intelligent automation.It is well known that single 2D CT slices lack spatial-temporal cha...Universal lesion detection(ULD)methods for computed tomography(CT)images play a vital role in the modern clinical medicine and intelligent automation.It is well known that single 2D CT slices lack spatial-temporal characteristics and contextual information compared to 3D CT blocks.However,3D CT blocks necessitate significantly higher hardware resources during the learning phase.Therefore,efficiently exploiting temporal correlation and spatial-temporal features of 2D CT slices is crucial for ULD tasks.In this paper,we propose a ULD network with the enhanced temporal correlation for this purpose,named TCE-Net.The designed TCE module is applied to enrich the discriminate feature representation of multiple sequential CT slices.Besides,we employ multi-scale feature maps to facilitate the localization and detection of lesions in various sizes.Extensive experiments are conducted on the DeepLesion benchmark demonstrate that thismethod achieves 66.84%and 78.18%for FS@0.5 and FS@1.0,respectively,outperforming compared state-of-the-art methods.展开更多
We report the observed photon bunching statistics of biexciton cascade emission at zero time delay in single quantum dots by second-order correlation function g（2） （T） measurements under continuous wave excitation...We report the observed photon bunching statistics of biexciton cascade emission at zero time delay in single quantum dots by second-order correlation function g（2） （T） measurements under continuous wave excitation. It is found that the bunching phenomenon is independent of the biexciton binding energy when it varies from 0.59 meV to nearly zero. The photon bunching takes place when the exeiton photon is not spectrally distinguishable from the biexciton photon, and either of them can trigger the %tart＇ in a Hanbury-Brown and Twiss setup. However, if the exciton energy is spectrally distinguishable from the biexciton, the photon statistics will become asymmetric and a cross-bunching lineshape can be obtained. The theoretical calculations based on a model of three-level rate-equation analysis are consistent with the result of g（2）（τ） correlation function measurements.展开更多
Research on human motion prediction has made significant progress due to its importance in the development of various artificial intelligence applications.However,effectively capturing spatio-temporal features for smo...Research on human motion prediction has made significant progress due to its importance in the development of various artificial intelligence applications.However,effectively capturing spatio-temporal features for smoother and more precise human motion prediction remains a challenge.To address these issues,a robust human motion prediction method via integration of spatial and temporal cues(RISTC)has been proposed.This method captures sufficient spatio-temporal correlation of the observable sequence of human poses by utilizing the spatio-temporal mixed feature extractor(MFE).In multi-layer MFEs,the channel-graph united attention blocks extract the augmented spatial features of the human poses in the channel and spatial dimension.Additionally,multi-scale temporal blocks have been designed to effectively capture complicated and highly dynamic temporal information.Our experiments on the Human3.6M and Carnegie Mellon University motion capture(CMU Mocap)datasets show that the proposed network yields higher prediction accuracy than the state-of-the-art methods.展开更多
Based on the monitoring data of PM 10 concentration from six environmental monitoring stations and the ground meteorological observation data in Yantai City from 2019 to 2021,the spatial and temporal variation of PM 1...Based on the monitoring data of PM 10 concentration from six environmental monitoring stations and the ground meteorological observation data in Yantai City from 2019 to 2021,the spatial and temporal variation of PM 10 concentration and its relationship with meteorological factors were studied.The results show that from the perspective of temporal variation,the annual average of PM 10 concentration in Yantai City tended to decrease year by year.It was high in winter and spring and low in summer and autumn.In terms of monthly variation,the changing curve is U-shaped,and it was high in December and January but low in July and August.During a day,PM 10 concentration had two peaks.The first peak appeared approximately from 09:00 to 11:00,and the second peak can be found from 21:00 to 23:00.From the perspective of spatial distribution,PM 10 concentration was the highest in the development area and Fushan District.It was the highest in the west,followed by the east,while it was the lowest in the middle.The spatial difference rate was the highest in summer.Average temperature,relative humidity,wind speed and precipitation were the main meteorological factors influencing PM 10 concentration in Yantai area.PM 10 concentration was negatively correlated with average temperature and relative humidity,and the correlation was the most significant from June to October.It was negatively correlated with wind speed and precipitation,and the correlation was different in various months.The negative correlation was significant in summer and winter.展开更多
The error model of a quantum computer is essential for optimizing quantum algorithms to minimize the impact of errors using quantum error correction or error mitigation.Noise with temporal correlations,e.g.low-frequen...The error model of a quantum computer is essential for optimizing quantum algorithms to minimize the impact of errors using quantum error correction or error mitigation.Noise with temporal correlations,e.g.low-frequency noise and context-dependent noise,is common in quantum computation devices and sometimes even significant.However,conventional tomography methods have not been developed for obtaining an error model describing temporal correlations.In this paper,we propose self-consistent tomography protocols to obtain a model of temporally correlated errors,and we demonstrate that our protocols are efficient for low-frequency noise and context-dependent noise.展开更多
We propose a new framework combining weak measurement and second-order correlated technique. The theoretical analysis shows that weak value amplification （WVA） experiment can also be implemented by a second-order co...We propose a new framework combining weak measurement and second-order correlated technique. The theoretical analysis shows that weak value amplification （WVA） experiment can also be implemented by a second-order correlated system. We then build two-dimensional second-order correlated function patterns for achieving higher amplification factor and discuss the signal-to-noise ratio influence. Several advantages can be obtained by our proposal. For instance, detectors with high resolution are not necessary. Moreover, detectors with low saturation intensity are available in WVA setup. Finally, type-one technical noise can be effectively suppressed.展开更多
Objective:To investigate whether major dengue outbreaks in the last two decades in Kaohsiung follow a precise temporal pattern.Methods:Government daily lab-confirmed dengue case data from three major dengue outbreaks ...Objective:To investigate whether major dengue outbreaks in the last two decades in Kaohsiung follow a precise temporal pattern.Methods:Government daily lab-confirmed dengue case data from three major dengue outbreaks occurring during the last two decades in Kaohsiung in2002,2014 and 2015,is utilized to compute the corresponding weekly cumulative percentage of total case numbers.We divide each of the three time series data into two periods to examine the corresponding weekly cumulative percentages of case numbers for each period.Pearson’s correlation coefficient was calculated to compare quantitatively the similarity between the temporal patterns of these three years.Results:Three cutoff points produce the most interesting comparisons and the most different outcomes.Pearson’s correlation coefficient indicates quantitative discrepancies in the similarity between temporal patterns of the three years when using different cutoff points.Conclusions:Temporal patterns in 2002 and 2014 are comparatively more similar in early stage.The 2015 outbreak started late in the year,but ended more like the outbreak in 2014,both with record-breaking number of cases.The retrospective analysis shows that the temporal dynamics of dengue outbreaks in Kaohsiung can strongly vary from one year to another,making it difficult to identify any common predictor.展开更多
The second-order temporal interference of two independent single-mode continuous-wave lasers is discussed by em- ploying two-photon interference in Feynman＇s path integral theory. It is concluded that whether the sec...The second-order temporal interference of two independent single-mode continuous-wave lasers is discussed by em- ploying two-photon interference in Feynman＇s path integral theory. It is concluded that whether the second-order temporal interference pattern can or cannot be retrieved via two-photon coincidence counting rate is dependent on the resolution time of the detection system and the frequency difference between these two lasers. Two identical and tunable single-mode continuous-wave diode lasers are employed to verify the predictions. These studies are helpful to understand the physics of two-photon interference with photons of different spectra.展开更多
For deployment flexibility and device lifetime prolonging,energy harvesting communications have drawn much attention recently,which however,encounter energy domain randomness in addition to the channel state randomnes...For deployment flexibility and device lifetime prolonging,energy harvesting communications have drawn much attention recently,which however,encounter energy domain randomness in addition to the channel state randomness and traffic load randomness.The three-dimensional randomness makes the resource allocation problem extremely difficult.To resolve this,we exploit the inherent correlations of energy arrival and information.The correlations include self correlations of energy profiles and mutual correlations between energy and information in both time and spatial domains.The correlations are explicitly explained followed by a state-of-art survey.Candidate mechanisms exploiting the correlations for the ease of resource allocation are introduced along with some recent progress.Finally,a case study is presented to illustrate the performance of the proposed algorithm.展开更多
The spatial-temporal evolution of coherent structures （CS） is significant for turbulence control and drag re- duction. Among the CS, low and high speed streak structures show typical burst phenomena. The analysis wa...The spatial-temporal evolution of coherent structures （CS） is significant for turbulence control and drag re- duction. Among the CS, low and high speed streak structures show typical burst phenomena. The analysis was based on a time series of three-dimensional and three-component （3D-3C） velocity fields of the flat plate turbulent boundary layer （TBL） measured by a Tomographic and Time-resolved PIV （Tomo TRPIV） system. Using multi-resolution wavelet transform and conditional sampling method, we extracted the intrinsic topologies and found that the streak structures appear in bar-like patterns. Furthermore, we seized locations and velocity information of transient CS, and then calculated the propagation velocity of CS based on spatial-temporal cross-correlation scanning. This laid a foundation for further studies on relevant dynamics properties.展开更多
Traffic prediction already plays a significant role in applications like traffic planning and urban management,but it is still difficult to capture the highly non-linear and complicated spatiotemporal correlations of ...Traffic prediction already plays a significant role in applications like traffic planning and urban management,but it is still difficult to capture the highly non-linear and complicated spatiotemporal correlations of traffic data.As well as to fulfil both long-termand short-termprediction objectives,a better representation of the temporal dependency and global spatial correlation of traffic data is needed.In order to do this,the Spatiotemporal Graph Neural Network(S-GNN)is proposed in this research as amethod for traffic prediction.The S-GNN simultaneously accepts various traffic data as inputs and investigates the non-linear correlations between the variables.In terms of modelling,the road network is initially represented as a spatiotemporal directed graph,with the features of the samples at the time step being captured by a convolution module.In order to assign varying attention weights to various adjacent area nodes of the target node,the adjacent areas information of nodes in the road network is then aggregated using a graph network.The data is output using a fully connected layer at the end.The findings show that S-GNN can improve short-and long-term traffic prediction accuracy to a greater extent;in comparison to the control model,the RMSE of S-GNN is reduced by about 0.571 to 9.288 and the MAE(Mean Absolute Error)by about 0.314 to 7.678.The experimental results on two real datasets,Pe MSD7(M)and PEMS-BAY,also support this claim.展开更多
One of the ingredients of anthropogenic global warming is the existence of a large correlation between carbon dioxide concentrations in the atmosphere and the temperature. In this work we analyze the original time-ser...One of the ingredients of anthropogenic global warming is the existence of a large correlation between carbon dioxide concentrations in the atmosphere and the temperature. In this work we analyze the original time-series data that led to the new wave of climate research and test the two hypotheses that might explain this correlation, namely the (more commonly accepted and well-known) greenhouse effect (GHE) and the less-known Henry’s Law (HL). This is done by using the correlation and the temporal features of the data. Our conclusion is that of the two hypotheses the greenhouse effect is less likely, whereas the Henry’s Law hypothesis can easily explain all effects. First the proportionality constant in the correlation is correct for HL and is about two orders of magnitude wrong for GHE. Moreover, GHE cannot readily explain the concurring methane signals observed. On the temporal scale, we see that GHE has difficulty in the apparent negative time lag between cause and effect, whereas in HL this is of correct sign and magnitude, since it is outgasing of gases from oceans. Introducing feedback into the GHE model can overcome some of these problems, but it introduces highly instable and chaotic behavior in the system, something that is not observed. The HL model does not need feedback.展开更多
How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image re...How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image registration are analysed, two improved approaches based on spatial-temporal relationship are presented. This method adds the correlation matrix according to the displacements in x- cirection and y- directions, and the registration pose is searched in the added matrix. The method overcomes the shortcoming that the probability of registration decreasing with area increasing owing to geometric distortion, improves the probability and the robustness of registration.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.12474070,12174112,and 12274159)the Natural Science Foundation of Chongqing Province and Shanghai(Grant Nos.2023NSCQ-MSX1489 and 23ZR1419800).
文摘The second-order correlation function of photons is the primary means to quantitatively describe the second-order coherence of a light field.In contrast to the stationary second-order correlation function,the temporal second-order correlation function can be used to study the second-order coherence of a transient light field.Based on the Monte Carlo algorithm,we carried out theoretical simulation on the temporal second-order correlation function from the perspective of photon statistics.By introducing experimental factors into the simulation,such as intensity jitter of the light field and time resolution of the instruments,the effects of imperfect experimental conditions on the measurement of second-order correlation function have also been elucidated.Our results provide theoretical guidance and analysis methods for experimental measurements on the secondorder coherence of light fields.
基金supported in part by the National Natural Science Foundation of China (No. U23B2011)。
文摘Video snapshot compressive imaging(Video SCI) modulates scenes using various encoding masks and captures compressed measurements with a low-speed camera during a single exposure. Subsequently, reconstruction algorithms restore image sequences of dynamic scenes, offering advantages such as reduced bandwidth and storage space requirements. The temporal correlation in video data is crucial for Video SCI, as it leverages the temporal relationships among frames to enhance the efficiency and quality of reconstruction algorithms, particularly for fast-moving objects.This paper discretizes video frames to create image datasets with the same data volume but differing temporal correlations. We utilized the state-of-the-art(SOTA) reconstruction framework, EfficientSCI++, to train various compressed reconstruction models with these differing temporal correlations. Evaluating the reconstruction results from these models, our simulation experiments confirm that a reduction in temporal correlation leads to decreased reconstruction accuracy. Additionally, we simulated the reconstruction outcomes of datasets devoid of temporal correlation, illustrating that models trained on non-temporal data affect the temporal feature extraction capabilities of transformers, resulting in negligible impacts on the evaluation of reconstruction results for non-temporal correlation test datasets.
基金supported by the Natural Science Foundation of Sichuan Province of China under Grant No.2025ZNSFSC0522partially supported by the National Natural Science Foundation of China under Grants No.61775030 and No.61571096.
文摘Target tracking is an essential task in contemporary computer vision applications.However,its effectiveness is susceptible to model drift,due to the different appearances of targets,which often compromises tracking robustness and precision.In this paper,a universally applicable method based on correlation filters is introduced to mitigate model drift in complex scenarios.It employs temporal-confidence samples as a priori to guide the model update process and ensure its precision and consistency over a long period.An improved update mechanism based on the peak side-lobe to peak correlation energy(PSPCE)criterion is proposed,which selects high-confidence samples along the temporal dimension to update temporal-confidence samples.Extensive experiments on various benchmarks demonstrate that the proposed method achieves a competitive performance compared with the state-of-the-art methods.Especially when the target appearance changes significantly,our method is more robust and can achieve a balance between precision and speed.Specifically,on the object tracking benchmark(OTB-100)dataset,compared to the baseline,the tracking precision of our model improves by 8.8%,8.8%,5.1%,5.6%,and 6.9%for background clutter,deformation,occlusion,rotation,and illumination variation,respectively.The results indicate that this proposed method can significantly enhance the robustness and precision of target tracking in dynamic and challenging environments,offering a reliable solution for applications such as real-time monitoring,autonomous driving,and precision guidance.
基金The National High Technology Research and Develop-ment Program of China(863 Program)(No.2006AA01Z268)the NationalNatural Science Foundation of China(No.60496311).
文摘Taking the time varying nature of wireless channels into account, two user selection schemes with lower complexity are developed for multiple-input multiple-output broadcast （MIMO BC）systems. According to the relationship between coherence time and Doppler frequency, an information frame is divided into several segments. At the beginning of each segment, the user selection is carded out with the greedy selection algorithm. In the simplified user selection algorithms employing the temporal correlation （SUSTC）, the selection results are applied for all the remaining slots in each segment. But in the improved simplified user selection algorithms employing the temporal correlation（ISUSTC）, at the remaining slots, users are kept with favorable channel conditions selected at the previous slot, and other users are updated from the candidate pool to communicate simultaneously. Simulations show that compared with the greedy user selection method, the proposed algorithms can reduce the selection complexity with a little sum capacity loss.
文摘Rock failure process as a natural response to mining activities is associated with seismic events, which can pose a potential hazard to mine operators, equipment and infrastructures. Mining-induced seismicity has been found to be internally correlated in both time and space domains as a result of rock fracturing during progressive mining activities. Understanding the spatio-temporal(ST) correlation of mininginduced seismic events is an essential step to use seismic data for further analysis, such as rockburst prediction and caving assessment. However, there are no established methods to perform this critical task. Input parameters used for the prediction of seismic hazards, such as the time window of past data and effective prediction distance, are determined based on site-specific experience without statistical or physical reasons to support. Therefore, the accuracy of current seismic prediction methods is largely constrained, which can only be addressed by quantitively assessing the ST correlations of mininginduced seismicity. In this research, the ST correlation of seismic event energy collected from a study mine is quantitatively analysed using various statistical methods, including autocorrelation function(ACF), semivariogram and Moran’s I analysis. In addition, based on the integrated ST correlation assessment, seismic events are further classified into seven clusters, so as to assess the correlations within individual clusters. The correlation of seismic events is found to be quantitatively assessable, and their correlations may vary throughout the mineral extraction process.
文摘User identity linkage(UIL)refers to identifying user accounts belonging to the same identity across different social media platforms.Most of the current research is based on text analysis,which fails to fully explore the rich image resources generated by users,and the existing attempts touch on the multimodal domain,but still face the challenge of semantic differences between text and images.Given this,we investigate the UIL task across different social media platforms based on multimodal user-generated contents(UGCs).We innovatively introduce the efficient user identity linkage via aligned multi-modal features and temporal correlation(EUIL)approach.The method first generates captions for user-posted images with the BLIP model,alleviating the problem of missing textual information.Subsequently,we extract aligned text and image features with the CLIP model,which closely aligns the two modalities and significantly reduces the semantic gap.Accordingly,we construct a set of adapter modules to integrate the multimodal features.Furthermore,we design a temporal weight assignment mechanism to incorporate the temporal dimension of user behavior.We evaluate the proposed scheme on the real-world social dataset TWIN,and the results show that our method reaches 86.39%accuracy,which demonstrates the excellence in handling multimodal data,and provides strong algorithmic support for UIL.
基金Supported by the Knowledge Innovation Program of Chinese Academy of Sciences (No.KZCX1-YW-12-02)the National Natural Science Foundation of China (Nos.10974218,10734100)
文摘We simulated the temporal correlation of sound transmission using a two-dimensional advective frozen-ocean model with temperature data from a temperature sensor array on a propagation path in the South China Sea （SCS） Experiment 2009, and investigated the relationships of temporal correlation length, source-receiver range, and maximal sound speed fluctuation mainly caused by the solitary internal waves. We found that the temporal correlation length is -h2-power dependent on source-receiver range and -0.9-power dependent on maximal sound speed fluctuation. The empirical relationship is deduced from one-day environmental measurements in a limited area, needing more works and verification in the future with more acoustic data. But the relationship is useful in many applications in the area of SCS Experiment 2009.
基金Taishan Young Scholars Program of Shandong Province,Key Development Program for Basic Research of Shandong Province(ZR2020ZD44).
文摘Universal lesion detection(ULD)methods for computed tomography(CT)images play a vital role in the modern clinical medicine and intelligent automation.It is well known that single 2D CT slices lack spatial-temporal characteristics and contextual information compared to 3D CT blocks.However,3D CT blocks necessitate significantly higher hardware resources during the learning phase.Therefore,efficiently exploiting temporal correlation and spatial-temporal features of 2D CT slices is crucial for ULD tasks.In this paper,we propose a ULD network with the enhanced temporal correlation for this purpose,named TCE-Net.The designed TCE module is applied to enrich the discriminate feature representation of multiple sequential CT slices.Besides,we employ multi-scale feature maps to facilitate the localization and detection of lesions in various sizes.Extensive experiments are conducted on the DeepLesion benchmark demonstrate that thismethod achieves 66.84%and 78.18%for FS@0.5 and FS@1.0,respectively,outperforming compared state-of-the-art methods.
基金Supported by the National Key Basic Research Program of China under Grant No 2013CB922304the National Natural Science Foundation of China under Grant Nos 11474275 and 11464034
文摘We report the observed photon bunching statistics of biexciton cascade emission at zero time delay in single quantum dots by second-order correlation function g（2） （T） measurements under continuous wave excitation. It is found that the bunching phenomenon is independent of the biexciton binding energy when it varies from 0.59 meV to nearly zero. The photon bunching takes place when the exeiton photon is not spectrally distinguishable from the biexciton photon, and either of them can trigger the %tart＇ in a Hanbury-Brown and Twiss setup. However, if the exciton energy is spectrally distinguishable from the biexciton, the photon statistics will become asymmetric and a cross-bunching lineshape can be obtained. The theoretical calculations based on a model of three-level rate-equation analysis are consistent with the result of g（2）（τ） correlation function measurements.
基金supported by the National Key R&D Program of China(No.2018YFB1305200)the Natural Science Foundation of Zhejiang Province(No.LGG21F030011)。
文摘Research on human motion prediction has made significant progress due to its importance in the development of various artificial intelligence applications.However,effectively capturing spatio-temporal features for smoother and more precise human motion prediction remains a challenge.To address these issues,a robust human motion prediction method via integration of spatial and temporal cues(RISTC)has been proposed.This method captures sufficient spatio-temporal correlation of the observable sequence of human poses by utilizing the spatio-temporal mixed feature extractor(MFE).In multi-layer MFEs,the channel-graph united attention blocks extract the augmented spatial features of the human poses in the channel and spatial dimension.Additionally,multi-scale temporal blocks have been designed to effectively capture complicated and highly dynamic temporal information.Our experiments on the Human3.6M and Carnegie Mellon University motion capture(CMU Mocap)datasets show that the proposed network yields higher prediction accuracy than the state-of-the-art methods.
基金the Science and Technology Research Project of Shandong Meteorological Bureau(2022SDQN11)Science and Technology Research Project of Yantai Meteorological Bureau(2024ytcx07).
文摘Based on the monitoring data of PM 10 concentration from six environmental monitoring stations and the ground meteorological observation data in Yantai City from 2019 to 2021,the spatial and temporal variation of PM 10 concentration and its relationship with meteorological factors were studied.The results show that from the perspective of temporal variation,the annual average of PM 10 concentration in Yantai City tended to decrease year by year.It was high in winter and spring and low in summer and autumn.In terms of monthly variation,the changing curve is U-shaped,and it was high in December and January but low in July and August.During a day,PM 10 concentration had two peaks.The first peak appeared approximately from 09:00 to 11:00,and the second peak can be found from 21:00 to 23:00.From the perspective of spatial distribution,PM 10 concentration was the highest in the development area and Fushan District.It was the highest in the west,followed by the east,while it was the lowest in the middle.The spatial difference rate was the highest in summer.Average temperature,relative humidity,wind speed and precipitation were the main meteorological factors influencing PM 10 concentration in Yantai area.PM 10 concentration was negatively correlated with average temperature and relative humidity,and the correlation was the most significant from June to October.It was negatively correlated with wind speed and precipitation,and the correlation was different in various months.The negative correlation was significant in summer and winter.
基金supported by the National Key R&D Program of China(Grant No.2016YFA0301200)the National Basic Research Program of China(Grant No.2014CB921403)+3 种基金supported by Science Challenge Project(Grant No.TZ2017003)the National Natural Science Foundation of China(Grants No.11774024,No.11534002,and No.U1530401)supported by National Natural Science Foundation of China(Grant No.11875050,12088101)NSAF(Grant No.U1930403)。
文摘The error model of a quantum computer is essential for optimizing quantum algorithms to minimize the impact of errors using quantum error correction or error mitigation.Noise with temporal correlations,e.g.low-frequency noise and context-dependent noise,is common in quantum computation devices and sometimes even significant.However,conventional tomography methods have not been developed for obtaining an error model describing temporal correlations.In this paper,we propose self-consistent tomography protocols to obtain a model of temporally correlated errors,and we demonstrate that our protocols are efficient for low-frequency noise and context-dependent noise.
基金Project supported by the Union Research Centre of Advanced Spaceflight Technology(Grant No.USCAST2013-05)the National Natural Science Foundation of China(Grant Nos.61170228,61332019,and 61471239)the High-Tech Research and Development Program of China(Grant No.2013AA122901)
文摘We propose a new framework combining weak measurement and second-order correlated technique. The theoretical analysis shows that weak value amplification （WVA） experiment can also be implemented by a second-order correlated system. We then build two-dimensional second-order correlated function patterns for achieving higher amplification factor and discuss the signal-to-noise ratio influence. Several advantages can be obtained by our proposal. For instance, detectors with high resolution are not necessary. Moreover, detectors with low saturation intensity are available in WVA setup. Finally, type-one technical noise can be effectively suppressed.
基金supported by Taiwan Ministry of Science and Technology postdoctoral fellowship(104-2811-B-039-005)supported by funding from Taiwan Ministry of Science and Technology grants(103-2314-B-039-010-MY3,103-2115-M-039-002-MY2)
文摘Objective:To investigate whether major dengue outbreaks in the last two decades in Kaohsiung follow a precise temporal pattern.Methods:Government daily lab-confirmed dengue case data from three major dengue outbreaks occurring during the last two decades in Kaohsiung in2002,2014 and 2015,is utilized to compute the corresponding weekly cumulative percentage of total case numbers.We divide each of the three time series data into two periods to examine the corresponding weekly cumulative percentages of case numbers for each period.Pearson’s correlation coefficient was calculated to compare quantitatively the similarity between the temporal patterns of these three years.Results:Three cutoff points produce the most interesting comparisons and the most different outcomes.Pearson’s correlation coefficient indicates quantitative discrepancies in the similarity between temporal patterns of the three years when using different cutoff points.Conclusions:Temporal patterns in 2002 and 2014 are comparatively more similar in early stage.The 2015 outbreak started late in the year,but ended more like the outbreak in 2014,both with record-breaking number of cases.The retrospective analysis shows that the temporal dynamics of dengue outbreaks in Kaohsiung can strongly vary from one year to another,making it difficult to identify any common predictor.
基金Project supported by the National Natural Science Foundation of China(Grant No.11404255)the Doctor Foundation of Education Ministry of China(Grant No.20130201120013)
文摘The second-order temporal interference of two independent single-mode continuous-wave lasers is discussed by em- ploying two-photon interference in Feynman＇s path integral theory. It is concluded that whether the second-order temporal interference pattern can or cannot be retrieved via two-photon coincidence counting rate is dependent on the resolution time of the detection system and the frequency difference between these two lasers. Two identical and tunable single-mode continuous-wave diode lasers are employed to verify the predictions. These studies are helpful to understand the physics of two-photon interference with photons of different spectra.
基金supported by the National Natural Science Foundation of China under grant Nos.61771495 and 61571265
文摘For deployment flexibility and device lifetime prolonging,energy harvesting communications have drawn much attention recently,which however,encounter energy domain randomness in addition to the channel state randomness and traffic load randomness.The three-dimensional randomness makes the resource allocation problem extremely difficult.To resolve this,we exploit the inherent correlations of energy arrival and information.The correlations include self correlations of energy profiles and mutual correlations between energy and information in both time and spatial domains.The correlations are explicitly explained followed by a state-of-art survey.Candidate mechanisms exploiting the correlations for the ease of resource allocation are introduced along with some recent progress.Finally,a case study is presented to illustrate the performance of the proposed algorithm.
基金supported by the National Natural Science Foundation of China(11332006,11272233,and 11411130150)the National Basic Research Programm of China(2012CB720101)
文摘The spatial-temporal evolution of coherent structures （CS） is significant for turbulence control and drag re- duction. Among the CS, low and high speed streak structures show typical burst phenomena. The analysis was based on a time series of three-dimensional and three-component （3D-3C） velocity fields of the flat plate turbulent boundary layer （TBL） measured by a Tomographic and Time-resolved PIV （Tomo TRPIV） system. Using multi-resolution wavelet transform and conditional sampling method, we extracted the intrinsic topologies and found that the streak structures appear in bar-like patterns. Furthermore, we seized locations and velocity information of transient CS, and then calculated the propagation velocity of CS based on spatial-temporal cross-correlation scanning. This laid a foundation for further studies on relevant dynamics properties.
基金supported by Science and Technology Plan Project of Zhejiang Provincial Department of Transportation“Research and System Development of Highway Asset Digitalization Technology inUse Based onHigh-PrecisionMap”(Project Number:202203)in part by Science and Technology Plan Project of Zhejiang Provincial Department of Transportation:Research and Demonstration Application of Key Technologies for Precise Sensing of Expressway Thrown Objects(No.202204).
文摘Traffic prediction already plays a significant role in applications like traffic planning and urban management,but it is still difficult to capture the highly non-linear and complicated spatiotemporal correlations of traffic data.As well as to fulfil both long-termand short-termprediction objectives,a better representation of the temporal dependency and global spatial correlation of traffic data is needed.In order to do this,the Spatiotemporal Graph Neural Network(S-GNN)is proposed in this research as amethod for traffic prediction.The S-GNN simultaneously accepts various traffic data as inputs and investigates the non-linear correlations between the variables.In terms of modelling,the road network is initially represented as a spatiotemporal directed graph,with the features of the samples at the time step being captured by a convolution module.In order to assign varying attention weights to various adjacent area nodes of the target node,the adjacent areas information of nodes in the road network is then aggregated using a graph network.The data is output using a fully connected layer at the end.The findings show that S-GNN can improve short-and long-term traffic prediction accuracy to a greater extent;in comparison to the control model,the RMSE of S-GNN is reduced by about 0.571 to 9.288 and the MAE(Mean Absolute Error)by about 0.314 to 7.678.The experimental results on two real datasets,Pe MSD7(M)and PEMS-BAY,also support this claim.
文摘One of the ingredients of anthropogenic global warming is the existence of a large correlation between carbon dioxide concentrations in the atmosphere and the temperature. In this work we analyze the original time-series data that led to the new wave of climate research and test the two hypotheses that might explain this correlation, namely the (more commonly accepted and well-known) greenhouse effect (GHE) and the less-known Henry’s Law (HL). This is done by using the correlation and the temporal features of the data. Our conclusion is that of the two hypotheses the greenhouse effect is less likely, whereas the Henry’s Law hypothesis can easily explain all effects. First the proportionality constant in the correlation is correct for HL and is about two orders of magnitude wrong for GHE. Moreover, GHE cannot readily explain the concurring methane signals observed. On the temporal scale, we see that GHE has difficulty in the apparent negative time lag between cause and effect, whereas in HL this is of correct sign and magnitude, since it is outgasing of gases from oceans. Introducing feedback into the GHE model can overcome some of these problems, but it introduces highly instable and chaotic behavior in the system, something that is not observed. The HL model does not need feedback.
文摘How to improve the probability of registration and precision of localization is a hard problem, which is desiderated to solve. The two basic approaches (normalized cross-correlation and phase correlation) for image registration are analysed, two improved approaches based on spatial-temporal relationship are presented. This method adds the correlation matrix according to the displacements in x- cirection and y- directions, and the registration pose is searched in the added matrix. The method overcomes the shortcoming that the probability of registration decreasing with area increasing owing to geometric distortion, improves the probability and the robustness of registration.
