To comprehensively understand the law of urban-rural relationship and propose scientific measures of urban-rural coordinated development in Northeast China,this study uses the coupling coordination degree model and ge...To comprehensively understand the law of urban-rural relationship and propose scientific measures of urban-rural coordinated development in Northeast China,this study uses the coupling coordination degree model and geographically and temporally weighted regression(GTWR)model to analyze the spatial-temporal patterns and the corresponding driving mechanisms of its urban-rural coordination since 1990.The results are as follows.First,the urban-rural coupling coordination degree in Northeast China was very low and improved slowly,but its stages of evolution is a good interpretation of the strategic arrangements of China's urbanization.Second,the urban-rural coupling coordination degree in Northeast China had spatial differences and was characterized by central polarization,converging on urban agglomeration,which was high in the south and low in the north.Moreover,the gap between the north and south weakened.Third,the spatial-temporal evolution of the urban-rural coordination relationship in Northeast China was influenced by pulling from the central cities,pushing from rural transformation,and government regulations.The influence intensity of the three mechanisms was weak,but the pulling from the central cities was stronger than that of the other two mechanisms.Furthermore,the spatial difference between the three mechanisms determines the spatial pattern and its evolution of the urban-rural coordination relationship in Northeast China.Fourth,to promote the development of urban-rural coordination in Northeast China,it is essential to advance urban-rural economic correlation,enhance the government^role in regulating and guiding,and adopt different policies for each region in Northeast China.展开更多
The relationship between China’s urbanization and economic development(RCUED) is an important concern nationwide. As important actors in regional strategy and policy, county-level regions have played an increasingly ...The relationship between China’s urbanization and economic development(RCUED) is an important concern nationwide. As important actors in regional strategy and policy, county-level regions have played an increasingly significant role in the development of China’s social economy. However, the existing research on the RCUED lacks the fine depiction of the county-level administrative units.Using 2000 and 2010 census data and the statistical analysis method, we uncovered the evolution characteristics of China’s urbanization and economic development and conducted a quantitative identification for the RCUED with improved methods using the quadrant map approach. In addition, we investigated the spatial correlation effect of the RCUED using the spatial autocorrelation analysis method. The results were as follows: 1) In general, a high degree of matching exists between China’s urbanization and economic development at the county level at the significance level of 0.01. The correlation coefficients between China’s urbanization and economic development in2000 and 2010 were 0.608 and 0.603, respectively. 2) A significant regional difference exists in the RCUED at the county level. Based on a comparative analysis of 2276 county units in China in the two years, we found that county units can be categorized as under-urbanized, basic coordination and over-urbanized in various areas. No situation was observed where urbanization seriously lagged behind the economic development level, so the levels of urbanization and economic development appear to be basically coordinated,and the coordination state may be gradually optimized over time. 3) Over time, the spatial dependency of the RCUED has weakened and the spatial heterogeneity has increased. Northeast China has always been an area characterized by over-urbanization. The number of county units classified as under-urbanized has begun to decline in eastern coastal urban agglomeration areas, while counties rich in resources have transformed from having point-shaped over-urbanization to plane-shaped under-urbanization along the northern border,and the number of over-urbanized county units has increased in the middle reaches of the Yangtze River. 4)’Lag-lag’ type and ’advance-advance’ type accounted for 68% of all counties in China, and these counties were shown to have obvious spatial differentiation characteristics.展开更多
Vegetation cover derived from remote sensing image is widely used for soil erosion risk assessment, but there is no clear guideline to select the most appropriate temporal satellite data. It is common practice that sa...Vegetation cover derived from remote sensing image is widely used for soil erosion risk assessment, but there is no clear guideline to select the most appropriate temporal satellite data. It is common practice that satellite data during growing season are randomly selected and used in soil erosion risk assessment. However, the effectiveness of vegetation in protecting the soil is quite different even if it is the same growing season since vegetation covers change as they grow. This article aims to provide a method of choosing optimal vegetation cover for studying soil erosion risk using remote sensing, that is, the vegetation cover in the most appropriate temporal period. Based on the temporal relationship of the two most active impact factors, rainfall and vegetation, an index of RV is developed and used to indicate the relative erosion risk during the year. The results show that annual variation of rainfall is significant, and vegetation is relatively stable, resulting in their matching relationship is different in each year. The correlation coefficient reaches 0.89 between RV and real sediment transport during the period when rainfall can cause soil erosion. In other words, RV is a good indicator of soil erosion. Therefore, there is a good correlation between RV maximum and the optimal vegetation cover, which can help facilitate erosion research in the future, showing good potential for successful application in other places.展开更多
Action recognition,a fundamental task in the field of video understanding,has been extensively researched and applied.In contrast to an image,a video introduces an extra temporal dimension.However,many existing action...Action recognition,a fundamental task in the field of video understanding,has been extensively researched and applied.In contrast to an image,a video introduces an extra temporal dimension.However,many existing action recognition networks either perform simple temporal fusion through averaging or rely on pre-trained models from image recognition,resulting in limited temporal information extraction capabilities.This work proposes a highly efficient temporal decoding module that can be seamlessly integrated into any action recognition backbone network to enhance the focus on temporal relationships between video frames.Firstly,the decoder initializes a set of learnable queries,termed video-level action category prediction queries.Then,they are combined with the video frame features extracted by the backbone network after self-attention learning to extract video context information.Finally,these prediction queries with rich temporal features are used for category prediction.Experimental results on HMDB51,MSRDailyAct3D,Diving48 and Breakfast datasets show that using TokShift-Transformer and VideoMAE as encoders results in a significant improvement in Top-1 accuracy compared to the original models(TokShift-Transformer and VideoMAE),after introducing the proposed temporal decoder.The introduction of the temporal decoder results in an average performance increase exceeding 11%for TokShift-Transformer and nearly 5%for VideoMAE across the four datasets.Furthermore,the work explores the combination of the decoder with various action recognition networks,including Timesformer,as encoders.This results in an average accuracy improvement of more than 3.5%on the HMDB51 dataset.The code is available at https://github.com/huangturbo/TempDecoder.展开更多
Because of unpredictable node mobility and absence of global information in Delay Tolerant Networks (DTNs), effective data forwarding has become a significant challenge in such network. Currently, most of existing dat...Because of unpredictable node mobility and absence of global information in Delay Tolerant Networks (DTNs), effective data forwarding has become a significant challenge in such network. Currently, most of existing data forwarding mechanisms select nodes with high cumulative contact capability as forwarders. However, for the heterogeneity of the transient node contact patterns, these selection approaches may not be the best relay choices within a short time period. This paper proposes an appropriate data forwarding mechanism, which combines time, location, and social characteristics into one coordinate system, to improve the performance of data forwarding in DTNs. The Temporal-Social Relationship and the Temporal-Geographical Relationship reveal the implied connection information among these three factors. This mechanism is formulated and verified in the experimental studies of realistic DTN traces. The empirical results show that our proposed mechanism can achieve better performance compared to the existing schemes with similar forwarding costs (e.g. end-to-end delay and delivery success ratio).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
Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurr...Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurrent Temporal Graph Convolution Networks(IndRT-GCNets)framework to efficiently and accurately capture event attribute information.The framework models the knowledge graph sequences to learn the evolutionary represen-tations of entities and relations within each period.Firstly,by utilizing the temporal graph convolution module in the evolutionary representation unit,the framework captures the structural dependency relationships within the knowledge graph in each period.Meanwhile,to achieve better event representation and establish effective correlations,an independent recurrent neural network is employed to implement auto-regressive modeling.Furthermore,static attributes of entities in the entity-relation events are constrained andmerged using a static graph constraint to obtain optimal entity representations.Finally,the evolution of entity and relation representations is utilized to predict events in the next subsequent step.On multiple real-world datasets such as Freebase13(FB13),Freebase 15k(FB15K),WordNet11(WN11),WordNet18(WN18),FB15K-237,WN18RR,YAGO3-10,and Nell-995,the results of multiple evaluation indicators show that our proposed IndRT-GCNets framework outperforms most existing models on knowledge reasoning tasks,which validates the effectiveness and robustness.展开更多
<span style="font-family:Verdana;">Convolutional neural networks, which have achieved outstanding performance in image recognition, have been extensively applied to action recognition. The mainstream a...<span style="font-family:Verdana;">Convolutional neural networks, which have achieved outstanding performance in image recognition, have been extensively applied to action recognition. The mainstream approaches to video understanding can be categorized into two-dimensional and three-dimensional convolutional neural networks. Although three-dimensional convolutional filters can learn the temporal correlation between different frames by extracting the features of multiple frames simultaneously, it results in an explosive number of parameters and calculation cost. Methods based on two-dimensional convolutional neural networks use fewer parameters;they often incorporate optical flow to compensate for their inability to learn temporal relationships. However, calculating the corresponding optical flow results in additional calculation cost;further, it necessitates the use of another model to learn the features of optical flow. We proposed an action recognition framework based on the two-dimensional convolutional neural network;therefore, it was necessary to resolve the lack of temporal relationships. To expand the temporal receptive field, we proposed a multi-scale temporal shift module, which was then combined with a temporal feature difference extraction module to extract the difference between the features of different frames. Finally, the model was compressed to make it more compact. We evaluated our method on two major action recognition benchmarks: the HMDB51 and UCF-101 datasets. Before compression, the proposed method achieved an accuracy of 72.83% on the HMDB51 dataset and 96.25% on the UCF-101 dataset. Following compression, the accuracy was still impressive, at 95.57% and 72.19% on each dataset. The final model was more compact than most related works.</span>展开更多
In this research,a modeling approach of rainfall generator coupled with high resolution rainfall products were proposed to generate designed rainfall events under multiple spatial and temporal distributions,which was ...In this research,a modeling approach of rainfall generator coupled with high resolution rainfall products were proposed to generate designed rainfall events under multiple spatial and temporal distributions,which was then employed to analyze the impacts of spatial and temporal rainfall heterogeneities on peak runoff for watersheds.Three scenarios were developed under multiple degrees of impermeable underlying surface areas within an urban watershed in south China.Detailed runoff processes were analyzed through the adoption of a distributed hydrological model(GSSHA).A covariance analysis method combined with rainfall spatio-temporal heterogeneity characteristic were used to quantify heterogeneity effects on peak runoff.Results indicated that coupling short period(2008–2016)remotely rainfall data and RainyDay results could successfully reproduce designed rainfall events,spatio-temporal heterogeneity of rainfall contributed significantly to the peak runoff,which was greater than those by rainfall duration and capacity,and the increase in impermeable underlying surface enhanced the complexities of the effects.Over each rainfall duration with increasing rainfall return period,the indicator of rainfall peak coefficient(RWD)would decrease and then increase.Regarding the total rainfall center(tg),25 mm/h threshold rainfall spatial coverage(A25)decreased with increasing imperviousness,1-h maximum rainfall(Rmax)surged with increasing imperviousness at rainfall duration of 2 and 24 h.Innovations of this research lied in:combination of a rainfall generator model based on a stochastic storm transposition technique and remote-sensing rainfall data to generate designed rainfall events,a rainfall spatial and temporal heterogeneities index system was developed to reveal how the changing characteristics of rainfall distribution and the impacts on peak runoff,and in-depth analysis of the impacts on runoff peak under multiple urban development scenarios for increasing capability in flood control/prevention.展开更多
Spatio-temporal variation of actual evapotranspiration(ETa) in the Pearl River basin from 1961 to 2010 are analyzed based on daily data from 60 national observed stations. ETa is calculated by the Advection-Aridity mo...Spatio-temporal variation of actual evapotranspiration(ETa) in the Pearl River basin from 1961 to 2010 are analyzed based on daily data from 60 national observed stations. ETa is calculated by the Advection-Aridity model(AA model) in the current study, and Mann-Kendall test(MK) and Inverse Distance Weighted interpolation method(IDW)were applied to detect the trends and spatial variation pattern. The relations of ETa with climate parameters and radiation/dynamic terms are analyzed by Person correlation method. Our findings are shown as follows: 1) Mean annual ETa in the Pearl River basin is about 665.6 mm/a. It has significantly decreased in 1961-2010 at a rate of-24.3mm/10 a. Seasonally, negative trends of summer and autumn ETa are higher than that of spring and winter. 2) The value of ETa is higher in the southeast coastal area than in the northwest region of the Pearl River basin, while the latter has shown the strongest negative trend. 3) Negative trends of ETa in the Pearl River basin are most probably due to decreasing radiation term and increasing dynamic term. The decrease of the radiation term is related with declining diurnal temperature range and sunshine duration, and rising atmospheric pressure as well. The contribution of dynamic term comes from increasing average temperature, maximum and minimum temperatures in the basin. Meanwhile, the decreasing average wind speed weakens dynamic term and finally, to a certain extent, it slows down the negative trend of the ETa.展开更多
The relationship between ecosystem services(ES)and human well-being(HWB)is fundamental to the science and practice of sustainability.However,studies have shown conflicting results,which has been attributed to the infl...The relationship between ecosystem services(ES)and human well-being(HWB)is fundamental to the science and practice of sustainability.However,studies have shown conflicting results,which has been attributed to the influences of indicators,contexts,and scales.Yet,another potential factor,which has been overlooked,may be the mixed use of spatial and temporal approaches.Using twelve ES and seven well-being indicators and multiple statistical methods,we quantified and compared the spatial and temporal ES–HWB relationships for Inner Mongolia,China.The spatial and temporal relationships differed in both correlation direction and strength.Most relationships of economic and employment-related indicators with food provisioning and supporting services were temporally positive but spatially nonsignificant or negative.Some relationships of economic and employmentrelated indicators with water retention,sandstorm prevention,and wind erosion were temporally negative but spatially complex.However,the spatial and temporal ES–HWB relationships could also be similar in some cases.We conclude that although both the spatial and temporal approaches have merits,space generally cannot substitute for time in the study of ES–HWB relationship.Our study helps reconcile the seemingly conflicting findings in the literature,and suggests that future studies should explicitly distinguish between the spatial and temporal ES–HWB relationships.展开更多
Climate change brings new challenges to the sustainable development of agriculture in the new era.Accurately grasping the patterns of climate change impacts on agricultural systems is crucial for ensuring agricultural...Climate change brings new challenges to the sustainable development of agriculture in the new era.Accurately grasping the patterns of climate change impacts on agricultural systems is crucial for ensuring agricultural sustainability and food security.Taking the Loess Plateau(LP),China as an example,this study used a coupling coordination degree model and spatial autocorrelation analysis to portray the spatial and temporal features of crop-cropland coupling relationship from 2000 to 2020 and explored the impact law of climate change through geographically and temporally weighted regression(GTWR).The results were as follows:1)the crop-cropland coupling coordination degree of the LP showed a gradual upward trend from 2000 to 2020,forming a spatial pattern with lower values in the central region and higher values in the surrounding areas.2)There was a positive correlation in the spatial distribution of cropcropland coupling coordination degree in the LP from 2000 to 2020,and the high value-low value(H-L)and low value-low value(L-L)agglomerations continued to expand eastward,while the spatial and temporal evolution of the high value-high value(H-H)and low value-high value(L-H)agglomerations was not obvious.3)The impacts of climatic elements on crop-cropland coupling coordination degree in the LP showed strong heterogeneity in time scales.The inhibitory impacts of summer days(SU)and frost days(FD)accounted for a higher proportion,while the annual average temperature(TEM)had both promoting and inhibiting impacts.The impacts proportion and intensity of extreme heavy precipitation day(R25),continuous drought days(CDD),and annual precipitation(PRE)all experienced significant changes.4)In space,the impacts of SU and FD on the crop-cropland coupling coordination degree varied with latitude and altitude.The adaptability of the LP to R25 gradually strengthened,and the extensions of CDD and increase of PRE led to the increasing inhibition beyond the eastern region of LP,and TEM showed a promoting impact in the Fenwei Plain.As an important grainproducing area in China,the LP should actively deal with the impacts of climate change on the crop-cropland coupling relationship,vigorously safeguard food security,and promote sustainable agricultural development.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41401182,41501173)Youth Fund for Humanities and Social Sciences of the Ministry of Education of China(No.19YJC630177)+2 种基金Natural Science Foundation of Heilongjiang Province(No.LH2019D008)University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province(No.UNPYSCT-2018194)Talent Introduction Project of Southwest University(No.SWU019020)。
文摘To comprehensively understand the law of urban-rural relationship and propose scientific measures of urban-rural coordinated development in Northeast China,this study uses the coupling coordination degree model and geographically and temporally weighted regression(GTWR)model to analyze the spatial-temporal patterns and the corresponding driving mechanisms of its urban-rural coordination since 1990.The results are as follows.First,the urban-rural coupling coordination degree in Northeast China was very low and improved slowly,but its stages of evolution is a good interpretation of the strategic arrangements of China's urbanization.Second,the urban-rural coupling coordination degree in Northeast China had spatial differences and was characterized by central polarization,converging on urban agglomeration,which was high in the south and low in the north.Moreover,the gap between the north and south weakened.Third,the spatial-temporal evolution of the urban-rural coordination relationship in Northeast China was influenced by pulling from the central cities,pushing from rural transformation,and government regulations.The influence intensity of the three mechanisms was weak,but the pulling from the central cities was stronger than that of the other two mechanisms.Furthermore,the spatial difference between the three mechanisms determines the spatial pattern and its evolution of the urban-rural coordination relationship in Northeast China.Fourth,to promote the development of urban-rural coordination in Northeast China,it is essential to advance urban-rural economic correlation,enhance the government^role in regulating and guiding,and adopt different policies for each region in Northeast China.
基金Under the auspices of the Strategic Priority Research Program of Chinese Academy of Sciences,Pan-Third Pole Environment Study for a Green Silk Road(Pan-TPE)(No.XDA20040400)
文摘The relationship between China’s urbanization and economic development(RCUED) is an important concern nationwide. As important actors in regional strategy and policy, county-level regions have played an increasingly significant role in the development of China’s social economy. However, the existing research on the RCUED lacks the fine depiction of the county-level administrative units.Using 2000 and 2010 census data and the statistical analysis method, we uncovered the evolution characteristics of China’s urbanization and economic development and conducted a quantitative identification for the RCUED with improved methods using the quadrant map approach. In addition, we investigated the spatial correlation effect of the RCUED using the spatial autocorrelation analysis method. The results were as follows: 1) In general, a high degree of matching exists between China’s urbanization and economic development at the county level at the significance level of 0.01. The correlation coefficients between China’s urbanization and economic development in2000 and 2010 were 0.608 and 0.603, respectively. 2) A significant regional difference exists in the RCUED at the county level. Based on a comparative analysis of 2276 county units in China in the two years, we found that county units can be categorized as under-urbanized, basic coordination and over-urbanized in various areas. No situation was observed where urbanization seriously lagged behind the economic development level, so the levels of urbanization and economic development appear to be basically coordinated,and the coordination state may be gradually optimized over time. 3) Over time, the spatial dependency of the RCUED has weakened and the spatial heterogeneity has increased. Northeast China has always been an area characterized by over-urbanization. The number of county units classified as under-urbanized has begun to decline in eastern coastal urban agglomeration areas, while counties rich in resources have transformed from having point-shaped over-urbanization to plane-shaped under-urbanization along the northern border,and the number of over-urbanized county units has increased in the middle reaches of the Yangtze River. 4)’Lag-lag’ type and ’advance-advance’ type accounted for 68% of all counties in China, and these counties were shown to have obvious spatial differentiation characteristics.
文摘Vegetation cover derived from remote sensing image is widely used for soil erosion risk assessment, but there is no clear guideline to select the most appropriate temporal satellite data. It is common practice that satellite data during growing season are randomly selected and used in soil erosion risk assessment. However, the effectiveness of vegetation in protecting the soil is quite different even if it is the same growing season since vegetation covers change as they grow. This article aims to provide a method of choosing optimal vegetation cover for studying soil erosion risk using remote sensing, that is, the vegetation cover in the most appropriate temporal period. Based on the temporal relationship of the two most active impact factors, rainfall and vegetation, an index of RV is developed and used to indicate the relative erosion risk during the year. The results show that annual variation of rainfall is significant, and vegetation is relatively stable, resulting in their matching relationship is different in each year. The correlation coefficient reaches 0.89 between RV and real sediment transport during the period when rainfall can cause soil erosion. In other words, RV is a good indicator of soil erosion. Therefore, there is a good correlation between RV maximum and the optimal vegetation cover, which can help facilitate erosion research in the future, showing good potential for successful application in other places.
基金Shanghai Municipal Commission of Economy and Information Technology,China (No.202301054)。
文摘Action recognition,a fundamental task in the field of video understanding,has been extensively researched and applied.In contrast to an image,a video introduces an extra temporal dimension.However,many existing action recognition networks either perform simple temporal fusion through averaging or rely on pre-trained models from image recognition,resulting in limited temporal information extraction capabilities.This work proposes a highly efficient temporal decoding module that can be seamlessly integrated into any action recognition backbone network to enhance the focus on temporal relationships between video frames.Firstly,the decoder initializes a set of learnable queries,termed video-level action category prediction queries.Then,they are combined with the video frame features extracted by the backbone network after self-attention learning to extract video context information.Finally,these prediction queries with rich temporal features are used for category prediction.Experimental results on HMDB51,MSRDailyAct3D,Diving48 and Breakfast datasets show that using TokShift-Transformer and VideoMAE as encoders results in a significant improvement in Top-1 accuracy compared to the original models(TokShift-Transformer and VideoMAE),after introducing the proposed temporal decoder.The introduction of the temporal decoder results in an average performance increase exceeding 11%for TokShift-Transformer and nearly 5%for VideoMAE across the four datasets.Furthermore,the work explores the combination of the decoder with various action recognition networks,including Timesformer,as encoders.This results in an average accuracy improvement of more than 3.5%on the HMDB51 dataset.The code is available at https://github.com/huangturbo/TempDecoder.
文摘Because of unpredictable node mobility and absence of global information in Delay Tolerant Networks (DTNs), effective data forwarding has become a significant challenge in such network. Currently, most of existing data forwarding mechanisms select nodes with high cumulative contact capability as forwarders. However, for the heterogeneity of the transient node contact patterns, these selection approaches may not be the best relay choices within a short time period. This paper proposes an appropriate data forwarding mechanism, which combines time, location, and social characteristics into one coordinate system, to improve the performance of data forwarding in DTNs. The Temporal-Social Relationship and the Temporal-Geographical Relationship reveal the implied connection information among these three factors. This mechanism is formulated and verified in the experimental studies of realistic DTN traces. The empirical results show that our proposed mechanism can achieve better performance compared to the existing schemes with similar forwarding costs (e.g. end-to-end delay and delivery success ratio).
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the National Natural Science Founda-tion of China(62062062)hosted by Gulila Altenbek.
文摘Due to the structural dependencies among concurrent events in the knowledge graph and the substantial amount of sequential correlation information carried by temporally adjacent events,we propose an Independent Recurrent Temporal Graph Convolution Networks(IndRT-GCNets)framework to efficiently and accurately capture event attribute information.The framework models the knowledge graph sequences to learn the evolutionary represen-tations of entities and relations within each period.Firstly,by utilizing the temporal graph convolution module in the evolutionary representation unit,the framework captures the structural dependency relationships within the knowledge graph in each period.Meanwhile,to achieve better event representation and establish effective correlations,an independent recurrent neural network is employed to implement auto-regressive modeling.Furthermore,static attributes of entities in the entity-relation events are constrained andmerged using a static graph constraint to obtain optimal entity representations.Finally,the evolution of entity and relation representations is utilized to predict events in the next subsequent step.On multiple real-world datasets such as Freebase13(FB13),Freebase 15k(FB15K),WordNet11(WN11),WordNet18(WN18),FB15K-237,WN18RR,YAGO3-10,and Nell-995,the results of multiple evaluation indicators show that our proposed IndRT-GCNets framework outperforms most existing models on knowledge reasoning tasks,which validates the effectiveness and robustness.
文摘<span style="font-family:Verdana;">Convolutional neural networks, which have achieved outstanding performance in image recognition, have been extensively applied to action recognition. The mainstream approaches to video understanding can be categorized into two-dimensional and three-dimensional convolutional neural networks. Although three-dimensional convolutional filters can learn the temporal correlation between different frames by extracting the features of multiple frames simultaneously, it results in an explosive number of parameters and calculation cost. Methods based on two-dimensional convolutional neural networks use fewer parameters;they often incorporate optical flow to compensate for their inability to learn temporal relationships. However, calculating the corresponding optical flow results in additional calculation cost;further, it necessitates the use of another model to learn the features of optical flow. We proposed an action recognition framework based on the two-dimensional convolutional neural network;therefore, it was necessary to resolve the lack of temporal relationships. To expand the temporal receptive field, we proposed a multi-scale temporal shift module, which was then combined with a temporal feature difference extraction module to extract the difference between the features of different frames. Finally, the model was compressed to make it more compact. We evaluated our method on two major action recognition benchmarks: the HMDB51 and UCF-101 datasets. Before compression, the proposed method achieved an accuracy of 72.83% on the HMDB51 dataset and 96.25% on the UCF-101 dataset. Following compression, the accuracy was still impressive, at 95.57% and 72.19% on each dataset. The final model was more compact than most related works.</span>
基金Program for Guangdong Introducing Innovative and Entrepreneurial Teams,Grant/Award Number:2021ZT09Key-Area Research and Development Program of Guangdong Province,Grant/Award Number:2020B1111380003National Natural Science Foundation of China,Grant/Award Number:U20A20117。
文摘In this research,a modeling approach of rainfall generator coupled with high resolution rainfall products were proposed to generate designed rainfall events under multiple spatial and temporal distributions,which was then employed to analyze the impacts of spatial and temporal rainfall heterogeneities on peak runoff for watersheds.Three scenarios were developed under multiple degrees of impermeable underlying surface areas within an urban watershed in south China.Detailed runoff processes were analyzed through the adoption of a distributed hydrological model(GSSHA).A covariance analysis method combined with rainfall spatio-temporal heterogeneity characteristic were used to quantify heterogeneity effects on peak runoff.Results indicated that coupling short period(2008–2016)remotely rainfall data and RainyDay results could successfully reproduce designed rainfall events,spatio-temporal heterogeneity of rainfall contributed significantly to the peak runoff,which was greater than those by rainfall duration and capacity,and the increase in impermeable underlying surface enhanced the complexities of the effects.Over each rainfall duration with increasing rainfall return period,the indicator of rainfall peak coefficient(RWD)would decrease and then increase.Regarding the total rainfall center(tg),25 mm/h threshold rainfall spatial coverage(A25)decreased with increasing imperviousness,1-h maximum rainfall(Rmax)surged with increasing imperviousness at rainfall duration of 2 and 24 h.Innovations of this research lied in:combination of a rainfall generator model based on a stochastic storm transposition technique and remote-sensing rainfall data to generate designed rainfall events,a rainfall spatial and temporal heterogeneities index system was developed to reveal how the changing characteristics of rainfall distribution and the impacts on peak runoff,and in-depth analysis of the impacts on runoff peak under multiple urban development scenarios for increasing capability in flood control/prevention.
基金National Natural Science Foundation of China(41401056,41571494)Research Innovation Program for College Graduates of Jiangsu Province(KYLX15_0858)
文摘Spatio-temporal variation of actual evapotranspiration(ETa) in the Pearl River basin from 1961 to 2010 are analyzed based on daily data from 60 national observed stations. ETa is calculated by the Advection-Aridity model(AA model) in the current study, and Mann-Kendall test(MK) and Inverse Distance Weighted interpolation method(IDW)were applied to detect the trends and spatial variation pattern. The relations of ETa with climate parameters and radiation/dynamic terms are analyzed by Person correlation method. Our findings are shown as follows: 1) Mean annual ETa in the Pearl River basin is about 665.6 mm/a. It has significantly decreased in 1961-2010 at a rate of-24.3mm/10 a. Seasonally, negative trends of summer and autumn ETa are higher than that of spring and winter. 2) The value of ETa is higher in the southeast coastal area than in the northwest region of the Pearl River basin, while the latter has shown the strongest negative trend. 3) Negative trends of ETa in the Pearl River basin are most probably due to decreasing radiation term and increasing dynamic term. The decrease of the radiation term is related with declining diurnal temperature range and sunshine duration, and rising atmospheric pressure as well. The contribution of dynamic term comes from increasing average temperature, maximum and minimum temperatures in the basin. Meanwhile, the decreasing average wind speed weakens dynamic term and finally, to a certain extent, it slows down the negative trend of the ETa.
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.B240201068)the National Natural Science Foundation of China(Grant No.42361144861)the National Basic Research Program of China(Grant No.2014CB954303).
文摘The relationship between ecosystem services(ES)and human well-being(HWB)is fundamental to the science and practice of sustainability.However,studies have shown conflicting results,which has been attributed to the influences of indicators,contexts,and scales.Yet,another potential factor,which has been overlooked,may be the mixed use of spatial and temporal approaches.Using twelve ES and seven well-being indicators and multiple statistical methods,we quantified and compared the spatial and temporal ES–HWB relationships for Inner Mongolia,China.The spatial and temporal relationships differed in both correlation direction and strength.Most relationships of economic and employment-related indicators with food provisioning and supporting services were temporally positive but spatially nonsignificant or negative.Some relationships of economic and employmentrelated indicators with water retention,sandstorm prevention,and wind erosion were temporally negative but spatially complex.However,the spatial and temporal ES–HWB relationships could also be similar in some cases.We conclude that although both the spatial and temporal approaches have merits,space generally cannot substitute for time in the study of ES–HWB relationship.Our study helps reconcile the seemingly conflicting findings in the literature,and suggests that future studies should explicitly distinguish between the spatial and temporal ES–HWB relationships.
基金Under the auspices of Major Program of National Natural Science Foundation of China(No.42293271)Alliance of International Science Organizations(No.ANSO-PA-2023-16)。
文摘Climate change brings new challenges to the sustainable development of agriculture in the new era.Accurately grasping the patterns of climate change impacts on agricultural systems is crucial for ensuring agricultural sustainability and food security.Taking the Loess Plateau(LP),China as an example,this study used a coupling coordination degree model and spatial autocorrelation analysis to portray the spatial and temporal features of crop-cropland coupling relationship from 2000 to 2020 and explored the impact law of climate change through geographically and temporally weighted regression(GTWR).The results were as follows:1)the crop-cropland coupling coordination degree of the LP showed a gradual upward trend from 2000 to 2020,forming a spatial pattern with lower values in the central region and higher values in the surrounding areas.2)There was a positive correlation in the spatial distribution of cropcropland coupling coordination degree in the LP from 2000 to 2020,and the high value-low value(H-L)and low value-low value(L-L)agglomerations continued to expand eastward,while the spatial and temporal evolution of the high value-high value(H-H)and low value-high value(L-H)agglomerations was not obvious.3)The impacts of climatic elements on crop-cropland coupling coordination degree in the LP showed strong heterogeneity in time scales.The inhibitory impacts of summer days(SU)and frost days(FD)accounted for a higher proportion,while the annual average temperature(TEM)had both promoting and inhibiting impacts.The impacts proportion and intensity of extreme heavy precipitation day(R25),continuous drought days(CDD),and annual precipitation(PRE)all experienced significant changes.4)In space,the impacts of SU and FD on the crop-cropland coupling coordination degree varied with latitude and altitude.The adaptability of the LP to R25 gradually strengthened,and the extensions of CDD and increase of PRE led to the increasing inhibition beyond the eastern region of LP,and TEM showed a promoting impact in the Fenwei Plain.As an important grainproducing area in China,the LP should actively deal with the impacts of climate change on the crop-cropland coupling relationship,vigorously safeguard food security,and promote sustainable agricultural development.
