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
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
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
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
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
In order to relate the design and analysis of an optical pattern recognition system with the structural parameters, only by introducing the prolate spheroidal wave function (PSWF) can the amount of information be comp...In order to relate the design and analysis of an optical pattern recognition system with the structural parameters, only by introducing the prolate spheroidal wave function (PSWF) can the amount of information be computed. Combining the imaging wave function set {ψi(x)} and distorted wave function set {b_i(p)} and two integral equations they satisfy derives the expression of the amount of information. The design method of matched filter connected with its amount of information is studied, and their amounts of information belonging to different pattern recognition systems are illustrated. It can be seen that the difference of the amounts of information for various systems is obvious.展开更多
在相干信号波达方向(direction of arrival,DOA)估计中,当阵列接收到的相干信号处于低信噪比时,DOA估计性能会大大降低。针对该问题,提出一种增强的时空平滑(enhanced spatio-temporal smoothing,ESTS)算法,在使用时空相关矩阵重构接收...在相干信号波达方向(direction of arrival,DOA)估计中,当阵列接收到的相干信号处于低信噪比时,DOA估计性能会大大降低。针对该问题,提出一种增强的时空平滑(enhanced spatio-temporal smoothing,ESTS)算法,在使用时空相关矩阵重构接收数据矩阵的时空平滑(spatio-temporal smoothing,STS)方法的基础上进行了改进。首先对子阵列时空相关矩阵进行平方预处理,然后通过充分利用子阵列时空相关矩阵的协方差和互协方差信息解相干,提高了相干信号的分辨率以及对噪声扰动的鲁棒性。理论分析和统计结果均表明,与其他空间平滑类解相干方法相比,该方法提高了在低信噪比、少快拍数、小角度分离情况下的相干信号DOA估计的去相关性能。展开更多
高维变量间的时空随机关联影响着水风光耦合场景序列生成,针对如何生成考虑时空相关性的水风光场景集,提出了一种创新的场景生成方法。首先采用马尔可夫链蒙特卡洛(Markov Chain Monte Carlo,MCMC)方法构建一套水风光时间相关性场景集,...高维变量间的时空随机关联影响着水风光耦合场景序列生成,针对如何生成考虑时空相关性的水风光场景集,提出了一种创新的场景生成方法。首先采用马尔可夫链蒙特卡洛(Markov Chain Monte Carlo,MCMC)方法构建一套水风光时间相关性场景集,捕捉水风光资源在日内每个小时之间的动态演变特性;然后引入R-vine Copula函数模型表征流域内水风光等异质能源之间的空间相关性,生成一套融合水风光时空相关性的高维耦合场景集;最后通过算例分析了所提场景生成方法的有效性。结果表明:与传统的场景生成方法相比,所提方法得到的场景集在4个季节的时间相关性误差和空间相关性误差有所降低,其中,时间相关性误差平均减少19%及以上,空间相关性误差平均减少35%及以上。展开更多
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.
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.
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.
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.
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Project supported by the National Natural Science Foundation of China.
文摘In order to relate the design and analysis of an optical pattern recognition system with the structural parameters, only by introducing the prolate spheroidal wave function (PSWF) can the amount of information be computed. Combining the imaging wave function set {ψi(x)} and distorted wave function set {b_i(p)} and two integral equations they satisfy derives the expression of the amount of information. The design method of matched filter connected with its amount of information is studied, and their amounts of information belonging to different pattern recognition systems are illustrated. It can be seen that the difference of the amounts of information for various systems is obvious.
文摘高维变量间的时空随机关联影响着水风光耦合场景序列生成,针对如何生成考虑时空相关性的水风光场景集,提出了一种创新的场景生成方法。首先采用马尔可夫链蒙特卡洛(Markov Chain Monte Carlo,MCMC)方法构建一套水风光时间相关性场景集,捕捉水风光资源在日内每个小时之间的动态演变特性;然后引入R-vine Copula函数模型表征流域内水风光等异质能源之间的空间相关性,生成一套融合水风光时空相关性的高维耦合场景集;最后通过算例分析了所提场景生成方法的有效性。结果表明:与传统的场景生成方法相比,所提方法得到的场景集在4个季节的时间相关性误差和空间相关性误差有所降低,其中,时间相关性误差平均减少19%及以上,空间相关性误差平均减少35%及以上。
