Grasping the spatial correlation structure of transportation carbon emission efficiency(TCEE)and its influencing factors is significant for promoting high-quality and coordinated development of the transportation indu...Grasping the spatial correlation structure of transportation carbon emission efficiency(TCEE)and its influencing factors is significant for promoting high-quality and coordinated development of the transportation industry and the relevant region.Based on the ideal point cross-efficiency(IPCE)model,the social network analysis method was employed herein to explore the spatial correlation network structure of China’s provincial TCEE and its influencing factors.The results obtained showed the following outcomes.(1)During the study period,China’s provincial TCEE formed a complex and multithreaded network association relationship,but its network association structure was still relatively loose and presented the hierarchical gradient characteristics of dense in the east and sparse in the west.(2)The correlation of China’s TCEE formed a block segmentation based on the regional boundaries,and its factional structure was relatively obvious.The eastern region was closely connected with the central region,and generally connected with the western and northeastern regions.The central region was mainly connected with the eastern and western regions,and relatively less connected with the northeastern region.Besides,the northeastern region was weakly connected with the western region.(3)Shanghai,Beijing,Zhejiang,Guangdong,Jiangsu,Tianjin,and other developed provinces were in the core leading position in the TCEE network,which significantly impacted the spatial correlation of TCEE.However,Heilongjiang,Jilin,Xinjiang,Qinghai,and other remote provinces in the northeast and northwest were at the absolute edge of the network,which weakly impacted the spatial correlation of TCEE.(4)Provincial distance,economic development-level difference,transportation intensity difference,and transportation structure difference had significant negative impacts on the spatial correlation network of China’s provincial TCEE.In contrast,the energy-saving technology level difference had a significant positive impact on it.The regression coefficients of transportation energy structure and environmental regulation differences were positive but insignificant;their response mechanism and effects need to be improved and enhanced.展开更多
Many complex networks in real life are embedded in space and most infrastructure networks are interdependent,such as the power system and the transport network.In this paper,we construct two cascading failure models o...Many complex networks in real life are embedded in space and most infrastructure networks are interdependent,such as the power system and the transport network.In this paper,we construct two cascading failure models on the multilayer spatial network.In our research,the distance l between nodes within the layer obeys the exponential distribution P(l)~exp(-l/ζ),and the length r of dependency link between layers is defined according to node position.An entropy approach is applied to analyze the spatial network structure and reflect the difference degree between nodes.Two metrics,namely dynamic network size and dynamic network entropy,are proposed to evaluate the spatial network robustness and stability.During the cascading failure process,the spatial network evolution is analyzed,and the numbers of failure nodes caused by different reasons are also counted,respectively.Besides,we discuss the factors affecting network robustness.Simulations demonstrate that the larger the values of average degree<k>,the stronger the network robustness.As the length r decreases,the network performs better.When the probability p is small,asζdecreases,the network robustness becomes more reliable.When p is large,the network robustness manifests better performance asζincreases.These results provide insight into enhancing the robustness,maintaining the stability,and adjusting the difference degree between nodes of the embedded spatiality systems.展开更多
Focusing on the peculiarities of urban construction resulting from specific mountain terrains, the purpose of this study is to find out a suitable method based on a Spatial Network Comprehensive Model(SNCM) to reasona...Focusing on the peculiarities of urban construction resulting from specific mountain terrains, the purpose of this study is to find out a suitable method based on a Spatial Network Comprehensive Model(SNCM) to reasonably plan and distribute primary schools in low-income mountain cities. The construction principles and advantages of the SNCM method are proposed and the method tested in Wanyuan city of Qinba Mountain area(Southwest China) to verify its feasibility and optimization. Taking account of the mountain terrain and its influence on user behavior, we used the SNCM method to build a comprehensive model which integrates the road slope and the walking speed of pupils into the basic spatial model. The model is used to calculate a reasonable layout of the primary schools and to validate the rationale. The results show that the SNCM method can be effectively applied in low-income mountainous cities. It can not only improve the accessibility and service efficiency of primary schools using as little capital-investment as possible, but also help the city grow in an intensive and efficient way.展开更多
Many networks in the real world have spatial attributes, such as location of nodes and length of edges, called spatial networks. When these networks are subject to some random or deliberate attacks, some nodes in the ...Many networks in the real world have spatial attributes, such as location of nodes and length of edges, called spatial networks. When these networks are subject to some random or deliberate attacks, some nodes in the network fail, which causes a decline in the network performance. In order to make the network run normally, some of the failed nodes must be recovered. In the case of limited recovery resources, an effective key node identification method can find the key recovering node in the failed nodes, by which the network performance can be recovered most of the failed nodes. We propose two key recovering node identification methods for spatial networks, which are the Euclidean-distance recovery method and the route-length recovery method. Simulations on homogeneous and heterogeneous spatial networks show that the proposed methods can significantly recover the network performance.展开更多
Aiming at the problems of low detection accuracy and large model size of existing object detection algorithms applied to complex road scenes,an improved you only look once version 8(YOLOv8)object detection algorithm f...Aiming at the problems of low detection accuracy and large model size of existing object detection algorithms applied to complex road scenes,an improved you only look once version 8(YOLOv8)object detection algorithm for infrared images,F-YOLOv8,is proposed.First,a spatial-to-depth network replaces the traditional backbone network's strided convolution or pooling layer.At the same time,it combines with the channel attention mechanism so that the neural network focuses on the channels with large weight values to better extract low-resolution image feature information;then an improved feature pyramid network of lightweight bidirectional feature pyramid network(L-BiFPN)is proposed,which can efficiently fuse features of different scales.In addition,a loss function of insertion of union based on the minimum point distance(MPDIoU)is introduced for bounding box regression,which obtains faster convergence speed and more accurate regression results.Experimental results on the FLIR dataset show that the improved algorithm can accurately detect infrared road targets in real time with 3%and 2.2%enhancement in mean average precision at 50%IoU(mAP50)and mean average precision at 50%—95%IoU(mAP50-95),respectively,and 38.1%,37.3%and 16.9%reduction in the number of model parameters,the model weight,and floating-point operations per second(FLOPs),respectively.To further demonstrate the detection capability of the improved algorithm,it is tested on the public dataset PASCAL VOC,and the results show that F-YOLO has excellent generalized detection performance.展开更多
Background In resource-based cities,long-term irrational exploitation of resources has caused severe damage to ecosystem functions,mainly manifested in the signifcant decline of biodiversity,land degradation,water pol...Background In resource-based cities,long-term irrational exploitation of resources has caused severe damage to ecosystem functions,mainly manifested in the signifcant decline of biodiversity,land degradation,water pollution,and the deterioration of air quality.This has led to a signifcant decline in the cities’sustainable development capabilities.Establishing and optimizing an ecological spatial network(ESN)can promote the efective transmission of material energy and enhance the ecosystem functions,which holds fundamental importance in ensuring the ecological integrity of the region and promoting sustainable urban development.In this study,by combining the ecological environment with the landscape to determine the ecological sources,we constructed the ESN of Shenmu City,a mining city,based on the minimum cumulative resistance(MCR)model,and conducted a correlation analysis between the topological structure of the ESN and the signifcance of ecosystem functions.Then,the optimization strategy scheme based on ecosystem functions was proposed.Finally,robustness was used to determine the efect before and after optimization.Results The results showed that the high-value ecosystem service areas in Shenmu City were predominantly located in the central and western parts,with the highest value in the southeast.There was a strong correlation between the importance of ecosystem functions and the degree and feature vector of ecological nodes.Conclusions The ESN can be optimized efectively by adding stepping stone nodes and new corridors.Through the robustness of the optimized ESN,we found that the optimized network has more robust connectivity and stability and can show better recovery ability after ecological function damage.This research presents an efective method for the construction and optimization of the ESN in the mining area and provides a theoretical basis for realizing the sustainability of the mining economy,regional development,and ecological protection in Shenmu City.展开更多
City cluster is an effective platform for encouraging regionally coordinated development.Coordinated reduction of carbon emissions within city cluster via the spatial association network between cities can help coordi...City cluster is an effective platform for encouraging regionally coordinated development.Coordinated reduction of carbon emissions within city cluster via the spatial association network between cities can help coordinate the regional carbon emission management,realize sustainable development,and assist China in achieving the carbon peaking and carbon neutrality goals.This paper applies the improved gravity model and social network analysis(SNA)to the study of spatial correlation of carbon emissions in city clusters and analyzes the structural characteristics of the spatial correlation network of carbon emissions in the Yangtze River Delta(YRD)city cluster in China and its influencing factors.The results demonstrate that:1)the spatial association of carbon emissions in the YRD city cluster exhibits a typical and complex multi-threaded network structure.The network association number and density show an upward trend,indicating closer spatial association between cities,but their values remain generally low.Meanwhile,the network hierarchy and network efficiency show a downward trend but remain high.2)The spatial association network of carbon emissions in the YRD city cluster shows an obvious‘core-edge’distribution pattern.The network is centered around Shanghai,Suzhou and Wuxi,all of which play the role of‘bridges’,while cities such as Zhoushan,Ma'anshan,Tongling and other cities characterized by the remote location,single transportation mode or lower economic level are positioned at the edge of the network.3)Geographic proximity,varying levels of economic development,different industrial structures,degrees of urbanization,levels of technological innovation,energy intensities and environmental regulation are important influencing factors on the spatial association of within the YRD city cluster.Finally,policy implications are provided from four aspects:government macro-control and market mechanism guidance,structural characteristics of the‘core-edge’network,reconfiguration and optimization of the spatial layout of the YRD city cluster,and the application of advanced technologies.展开更多
Seal authentication is an important task for verifying the authenticity of stamped seals used in various domains to protect legal documents from tampering and counterfeiting.Stamped seal inspection is commonly audited...Seal authentication is an important task for verifying the authenticity of stamped seals used in various domains to protect legal documents from tampering and counterfeiting.Stamped seal inspection is commonly audited manually to ensure document authenticity.However,manual assessment of seal images is tedious and laborintensive due to human errors,inconsistent placement,and completeness of the seal.Traditional image recognition systems are inadequate enough to identify seal types accurately,necessitating a neural network-based method for seal image recognition.However,neural network-based classification algorithms,such as Residual Networks(ResNet)andVisualGeometryGroup with 16 layers(VGG16)yield suboptimal recognition rates on stamp datasets.Additionally,the fixed training data categories make handling new categories to be a challenging task.This paper proposes amulti-stage seal recognition algorithmbased on Siamese network to overcome these limitations.Firstly,the seal image is pre-processed by applying an image rotation correction module based on Histogram of Oriented Gradients(HOG).Secondly,the similarity between input seal image pairs is measured by utilizing a similarity comparison module based on the Siamese network.Finally,we compare the results with the pre-stored standard seal template images in the database to obtain the seal type.To evaluate the performance of the proposed method,we further create a new seal image dataset that contains two subsets with 210,000 valid labeled pairs in total.The proposed work has a practical significance in industries where automatic seal authentication is essential as in legal,financial,and governmental sectors,where automatic seal recognition can enhance document security and streamline validation processes.Furthermore,the experimental results show that the proposed multi-stage method for seal image recognition outperforms state-of-the-art methods on the two established datasets.展开更多
In view of the weak ability of the convolutional neural networks to explicitly learn spatial invariance and the probabilistic loss of discriminative features caused by occlusion and background interference in pedestri...In view of the weak ability of the convolutional neural networks to explicitly learn spatial invariance and the probabilistic loss of discriminative features caused by occlusion and background interference in pedestrian re-identification tasks,a person re-identification method combining spatial feature learning and multi-granularity feature fusion was proposed.First,an attention spatial transformation network(A-STN)is proposed to learn spatial features and solve the problem of misalignment of pedestrian spatial features.Then the network was divided into a global branch,a local coarse-grained fusion branch,and a local fine-grained fusion branch to extract pedestrian global features,coarse-grained fusion features,and fine-grained fusion features,respectively.Among them,the global branch enriches the global features by fusing different pooling features.The local coarse-grained fusion branch uses an overlay pooling to enhance each local feature while learning the correlation relationship between multi-granularity features.The local fine-grained fusion branch uses a differential pooling to obtain the differential features that were fused with global features to learn the relationship between pedestrian local features and pedestrian global features.Finally,the proposed method was compared on three public datasets:Market1501,DukeMTMC-ReID and CUHK03.The experimental results were better than those of the comparative methods,which verifies the effectiveness of the proposed method.展开更多
With the increasing availability of real-time traffic information, dynamic spatial networks are pervasive nowa- days and path planning in dynamic spatial networks becomes an important issue. In this light, we propose ...With the increasing availability of real-time traffic information, dynamic spatial networks are pervasive nowa- days and path planning in dynamic spatial networks becomes an important issue. In this light, we propose and investigate a novel problem of dynamically monitoring shortest paths in spatial networks （DSPM query）. When a traveler aims to a des- tination, his/her shortest path to the destination may change due to two reasons： 1） the travel costs of some edges have been updated and 2） the traveler deviates from the pre-planned path. Our target is to accelerate the shortest path computing in dynamic spatial networks, and we believe that this study may be useful in many mobile applications, such as route planning and recommendation, car navigation and tracking, and location-based services in general. This problem is challenging due to two reasons： 1） how to maintain and reuse the existing computation results to accelerate the following computations, and 2） how to prune the search space effectively. To overcome these challenges, filter-and-refinement paradigm is adopted. We maintain an expansion tree and define a pair of upper and lower bounds to prune the search space. A series of optimization techniques are developed to accelerate the shortest path computing. The performance of the developed methods is studied in extensive experiments based on real spatial data.展开更多
We examine how spatial heterogeneity combines with mobility network structure to influence vector-borne disease dynamics.Specifically,we consider a Ross-Macdonald-type disease model on n spatial locations that are cou...We examine how spatial heterogeneity combines with mobility network structure to influence vector-borne disease dynamics.Specifically,we consider a Ross-Macdonald-type disease model on n spatial locations that are coupled by host movement on a strongly connected,weighted,directed graph.We derive a closed form approximation to the domain reproduction number using a Laurent series expansion,and use this approximation to compute sensitivities of the basic reproduction number to model parameters.To illustrate how these results can be used to help inform mitigation strategies,as a case study we apply these results to malaria dynamics in Namibia,using published cell phone data and estimates for local disease transmission.Our analytical results are particularly useful for understanding drivers of transmission when mobility sinks and transmission hot spots do not coincide.展开更多
Intractable delays occur in air traffic due to the imbalance between ever-increasing air traffic demand and limited airspace capacity.As air traffic is associated with complex air transport systems,delays can be magni...Intractable delays occur in air traffic due to the imbalance between ever-increasing air traffic demand and limited airspace capacity.As air traffic is associated with complex air transport systems,delays can be magnified and propagated throughout these systems,resulting in the emergent behavior known as delay propagation.An understanding of delay propagation dynamics is pertinent to modern air traffic management.In this work,we present a complex network perspective of delay propagation dynamics.Specifically,we model air traffic scenarios using spatial–temporal networks with airports as the nodes.To establish the dynamic edges between the nodes,we develop a delay propagation method and apply it to a given set of air traffic schedules.Based on the constructed spatial-temporal networks,we suggest three metrics-magnitude,severity,and speed-to gauge delay propagation dynamics.To validate the effectiveness of the proposed method,we carry out case studies on domestic flights in the Southeastern Asia region(SAR)and the United States.Experiments demonstrate that the propagation magnitude in terms of the number of flights affected by delay propagation and the amount of propagated delays for the US traffic are respectively five and ten times those of the SAR.Experiments further reveal that the propagation speed for US traffic is eight times faster than that of the SAR.The delay propagation dynamics reveal that about six hub airports in the SAR have significant propagated delays,while the situation in the United States is considerably worse,with a corresponding number of around 16.This work provides a potent tool for tracing the evolution of air traffic delays.展开更多
This paper presents an artificial neural network（ANN）-based response surface method that can be used to predict the failure probability of c-φslopes with spatially variable soil.In this method,the Latin hypercube s...This paper presents an artificial neural network（ANN）-based response surface method that can be used to predict the failure probability of c-φslopes with spatially variable soil.In this method,the Latin hypercube sampling technique is adopted to generate input datasets for establishing an ANN model;the random finite element method is then utilized to calculate the corresponding output datasets considering the spatial variability of soil properties;and finally,an ANN model is trained to construct the response surface of failure probability and obtain an approximate function that incorporates the relevant variables.The results of the illustrated example indicate that the proposed method provides credible and accurate estimations of failure probability.As a result,the obtained approximate function can be used as an alternative to the specific analysis process in c-φslope reliability analyses.展开更多
Based on the theories and methods of complex network,crude oil trade flows between countries along the Belt and Road(B&R,hereafter)are inserted into the Geo-space of B&R and form a spatial interaction network ...Based on the theories and methods of complex network,crude oil trade flows between countries along the Belt and Road(B&R,hereafter)are inserted into the Geo-space of B&R and form a spatial interaction network which takes the countries as nodes and takes the trade relations as edges.The networked mining and evolution analysis can provide important references for the research on trade relations among the B&R countries and the formulation of trade policy.This paper researches and discusses the construction,statistical analysis,top networks and stability of the crude oil trade network between the B&R countries from 2001 to 2020 from the perspectives of Geo-Computation for Social Sciences(GCSS)and spatial interaction.Firstly,evolutions of out-degree,in-degree,out-strength and in-strength of the top 10 countries in the crude oil trade network are computed and analyzed.Secondly,the top network method is used to explore the evolution characteristics of hierarchical structures.And finally,the sequential evolution characteristics of the crude oil trade network stability are analyzed utilizing the network stability measure method based on the trade relationship autocorrelation function.The analysis results show that Russia has the largest out-degree and out-strength,and China has the largest in-degree and in-strength.The crude oil trade volume of the top 10 import and export networks between 2001—2020 accounts for over 90%of the total trade volume of the crude oil trade network,and the proportion remains relatively stable.However,the stability of the network showed strong fluctuations in 2009,2012 and 2014,which may be closely related to major international events in these years,which could furtherly be used to build a correlation model between network volatility and major events.This paper explores how to construct and analyze the spatial interaction network of crude oil trade and can provide references for trade relations research and trade policy formulation of B&R countries.展开更多
Human beings’ intellection is the characteristic of a distinct hierarchy and can be taken to construct a heuristic in the shortest path algorithms.It is detailed in this paper how to utilize the hierarchical reasonin...Human beings’ intellection is the characteristic of a distinct hierarchy and can be taken to construct a heuristic in the shortest path algorithms.It is detailed in this paper how to utilize the hierarchical reasoning on the basis of greedy and directional strategy to establish a spatial heuristic,so as to improve running efficiency and suitability of shortest path algorithm for traffic network.The authors divide urban traffic network into three hierarchies and set forward a new node hierarchy division rule to avoid the unreliable solution of shortest path.It is argued that the shortest path,no matter distance shortest or time shortest,is usually not the favorite of drivers in practice.Some factors difficult to expect or quantify influence the drivers’ choice greatly.It makes the drivers prefer choosing a less shortest,but more reliable or flexible path to travel on.The presented optimum path algorithm,in addition to the improvement of the running efficiency of shortest path algorithms up to several times,reduces the emergence of those factors,conforms to the intellection characteristic of human beings,and is more easily accepted by drivers.Moreover,it does not require the completeness of networks in the lowest hierarchy and the applicability and fault tolerance of the algorithm have improved.The experiment result shows the advantages of the presented algorithm.The authors argued that the algorithm has great potential application for navigation systems of large_scale traffic networks.展开更多
A new algorithm called spatially aware routing algorithm with enhanced learning (SAREL) is proposed to guarantee the rationality of route selecting in inter-vehicle communication scenario. Firstly, the traffic model i...A new algorithm called spatially aware routing algorithm with enhanced learning (SAREL) is proposed to guarantee the rationality of route selecting in inter-vehicle communication scenario. Firstly, the traffic model is discussed and set up by using Poisson distribution. Then we analyze the process of traffic evaluation with enhanced learning, and exploit movement estimation to assist state memorization. The improvement of algorithm is provided at last compared with our previous work. Simulation results show that SAREL algorithm could achieve better performance in packet delivery ratio, especially when network connection ratio is average. Key words mobile ad hoc network - spatially aware routing - enhanced learning CLC number TP 316 Foundation item: Supported by Open Laboratory Foundation by China Ministry of Education (TKLJ9903), Project CarTALK 2000 by the European Commission (IST-2000-28185) and Project FleetNet-Internet on the Road by the German Ministry of Education and Research (01AK025)Biography: HAN Lu (1974-), male, Ph. D candidate, research direction; distributed artificial intelligence.展开更多
Spatial coherence resonance in a two-dimensional neuronal network induced by additive Gaussian coloured noise and parameter diversity is studied. We focus on the ability of additive Gaussian coloured noise and paramet...Spatial coherence resonance in a two-dimensional neuronal network induced by additive Gaussian coloured noise and parameter diversity is studied. We focus on the ability of additive Gaussian coloured noise and parameter diversity to extract a particular spatial frequency （wave number） of excitatory waves in the excitable medium of this network. We show that there exists an intermediate noise level of the coloured noise and a particular value of diversity, where a characteristic spatial frequency of the system comes forth. Hereby, it is verified that spatial coherence resonance occurs in the studied model. Furthermore, we show that the optimal noise intensity for spatial coherence resonance decays exponentially with respect to the noise correlation time. Some explanations of the observed nonlinear phenomena are also presented.展开更多
On the basis of measuring the regional high-quality development in China from 2011 to 2020,this study uses gravity model to build spatial correlation network,and uses social network analysis method to analyze the stru...On the basis of measuring the regional high-quality development in China from 2011 to 2020,this study uses gravity model to build spatial correlation network,and uses social network analysis method to analyze the structural characteristics and influencing factors of correlation network.The results are shown as follows.First,from 2011 to 2020,the level of regional high-quality development in China is rising gradually,and the discrete characteristics between regions are gradually obvious,showing a step-like distribution structure decreasing from east to west.Second,the network density of regional high-quality development is generally low and tends to decline,but it has strong stability and correlation strength.Third,the spatial correlation network has an obvious core-edge structure.Shanghai is always at the center of the network and plays a significant intermediary role,while Qinghai and Xinjiang are always at the edge of the network.Fourth,the regional high-quality development association network can be divided into four major sectors:main benefit,net benefit,net spillover,and broker,showing the spatial correlation characteristics of inter-plate contact and intra-plate agglomeration.Fifth,the level of economic development,the level of urbanization and geographical proximity have a significant impact on the formation of regional high-quality development correlation network.展开更多
Spatial division multiplexing enabled elastic optical networks(SDM-EONs) are the potential implementation form of future optical transport networks, because it can curve the physical limitation of achievable transmiss...Spatial division multiplexing enabled elastic optical networks(SDM-EONs) are the potential implementation form of future optical transport networks, because it can curve the physical limitation of achievable transmission capacity in single-mode fiber and single-core fiber. However, spectrum fragmentation issue becomes more serious in SDM-EONs compared with simple elastic optical networks(EONs) with single mode fiber or single core fiber. In this paper, multicore virtual concatenation(MCVC) scheme is first proposed considering inter-core crosstalk to solve the spectrum fragmentation issue in SDM-EONs. Simulation results show that the proposed MCVC scheme can achieve better performance compared with the baseline scheme, i.e., single-core virtual concatenation(SCVC) scheme, in terms of blocking probability and spectrum utilization.展开更多
Traffic is an indispensable prerequisite for a tourism system. The ＂four vertical and four horizontal＂ HSR network represents an important milestone of the ＂traffic revolution＂ in China. It will affect the spatial...Traffic is an indispensable prerequisite for a tourism system. The ＂four vertical and four horizontal＂ HSR network represents an important milestone of the ＂traffic revolution＂ in China. It will affect the spatial pattern of tourism accessibility in Chinese cities, thus substan- tially increasing their power to attract tourists and their radiation force. This paper examines the evolution and spatial characteristics of the power to attract tourism of cities linked by China＇s HSR network by measuring the influence of accessibility of 338 HSR-linked cities using GIS analysis. The results show the following. （1） The accessibility of Chinese cities is optimized by the HSR network, whose spatial pattern of accessibility exhibits an obvious traf- fic direction and causes a high-speed rail-corridor effect. （2） The spatial pattern of tourism field strength in Chinese cities exhibits the dual characteristics of multi-center annular diver- gence and dendritic diffusion. Dendritic diffusion is particularly more obvious along the HSR line. The change rate of urban tourism field strength forms a high-value corridor along the HSR line and exhibits a spatial pattern of decreasing area from the center to the outer limit along the HSR line. （3） The influence of the higher and highest tourism field strength areas along the HSR line is most significant, and the number of cities that distribute into these two types of tourism field strengths significantly increases： their area expands by more than 100% HSR enhances the tourism field strength value of regional central cities, and the radiation range of tourism attraction extends along the HSR line.展开更多
基金This research was funded by the National Science Foundation under the Project“Synergic evolution mechanism of intercity transportation and metropolitan tourism spatial pattern”[Grant number.41771162]It was also funded by the National First-Class Discipline Development Project in Hunan Province under the category of“Geography”[Grang number.510002].
文摘Grasping the spatial correlation structure of transportation carbon emission efficiency(TCEE)and its influencing factors is significant for promoting high-quality and coordinated development of the transportation industry and the relevant region.Based on the ideal point cross-efficiency(IPCE)model,the social network analysis method was employed herein to explore the spatial correlation network structure of China’s provincial TCEE and its influencing factors.The results obtained showed the following outcomes.(1)During the study period,China’s provincial TCEE formed a complex and multithreaded network association relationship,but its network association structure was still relatively loose and presented the hierarchical gradient characteristics of dense in the east and sparse in the west.(2)The correlation of China’s TCEE formed a block segmentation based on the regional boundaries,and its factional structure was relatively obvious.The eastern region was closely connected with the central region,and generally connected with the western and northeastern regions.The central region was mainly connected with the eastern and western regions,and relatively less connected with the northeastern region.Besides,the northeastern region was weakly connected with the western region.(3)Shanghai,Beijing,Zhejiang,Guangdong,Jiangsu,Tianjin,and other developed provinces were in the core leading position in the TCEE network,which significantly impacted the spatial correlation of TCEE.However,Heilongjiang,Jilin,Xinjiang,Qinghai,and other remote provinces in the northeast and northwest were at the absolute edge of the network,which weakly impacted the spatial correlation of TCEE.(4)Provincial distance,economic development-level difference,transportation intensity difference,and transportation structure difference had significant negative impacts on the spatial correlation network of China’s provincial TCEE.In contrast,the energy-saving technology level difference had a significant positive impact on it.The regression coefficients of transportation energy structure and environmental regulation differences were positive but insignificant;their response mechanism and effects need to be improved and enhanced.
基金Project supported by the National Natural Science Foundation of China(Grant No.61871046).
文摘Many complex networks in real life are embedded in space and most infrastructure networks are interdependent,such as the power system and the transport network.In this paper,we construct two cascading failure models on the multilayer spatial network.In our research,the distance l between nodes within the layer obeys the exponential distribution P(l)~exp(-l/ζ),and the length r of dependency link between layers is defined according to node position.An entropy approach is applied to analyze the spatial network structure and reflect the difference degree between nodes.Two metrics,namely dynamic network size and dynamic network entropy,are proposed to evaluate the spatial network robustness and stability.During the cascading failure process,the spatial network evolution is analyzed,and the numbers of failure nodes caused by different reasons are also counted,respectively.Besides,we discuss the factors affecting network robustness.Simulations demonstrate that the larger the values of average degree<k>,the stronger the network robustness.As the length r decreases,the network performs better.When the probability p is small,asζdecreases,the network robustness becomes more reliable.When p is large,the network robustness manifests better performance asζincreases.These results provide insight into enhancing the robustness,maintaining the stability,and adjusting the difference degree between nodes of the embedded spatiality systems.
基金funded by the National Social Science Foundation of Chongqing (Grants No. 2016YBJJ031)
文摘Focusing on the peculiarities of urban construction resulting from specific mountain terrains, the purpose of this study is to find out a suitable method based on a Spatial Network Comprehensive Model(SNCM) to reasonably plan and distribute primary schools in low-income mountain cities. The construction principles and advantages of the SNCM method are proposed and the method tested in Wanyuan city of Qinba Mountain area(Southwest China) to verify its feasibility and optimization. Taking account of the mountain terrain and its influence on user behavior, we used the SNCM method to build a comprehensive model which integrates the road slope and the walking speed of pupils into the basic spatial model. The model is used to calculate a reasonable layout of the primary schools and to validate the rationale. The results show that the SNCM method can be effectively applied in low-income mountainous cities. It can not only improve the accessibility and service efficiency of primary schools using as little capital-investment as possible, but also help the city grow in an intensive and efficient way.
基金Project supported by Zhejiang Provincial Natural Science Foundation of China (Grant No. LQ23F030012)the Fundamental Research Funds for the Provincial Universities of Zhejiang (Grant No. GK229909299001-018)。
文摘Many networks in the real world have spatial attributes, such as location of nodes and length of edges, called spatial networks. When these networks are subject to some random or deliberate attacks, some nodes in the network fail, which causes a decline in the network performance. In order to make the network run normally, some of the failed nodes must be recovered. In the case of limited recovery resources, an effective key node identification method can find the key recovering node in the failed nodes, by which the network performance can be recovered most of the failed nodes. We propose two key recovering node identification methods for spatial networks, which are the Euclidean-distance recovery method and the route-length recovery method. Simulations on homogeneous and heterogeneous spatial networks show that the proposed methods can significantly recover the network performance.
基金supported by the National Natural Science Foundation of China(No.62103298)。
文摘Aiming at the problems of low detection accuracy and large model size of existing object detection algorithms applied to complex road scenes,an improved you only look once version 8(YOLOv8)object detection algorithm for infrared images,F-YOLOv8,is proposed.First,a spatial-to-depth network replaces the traditional backbone network's strided convolution or pooling layer.At the same time,it combines with the channel attention mechanism so that the neural network focuses on the channels with large weight values to better extract low-resolution image feature information;then an improved feature pyramid network of lightweight bidirectional feature pyramid network(L-BiFPN)is proposed,which can efficiently fuse features of different scales.In addition,a loss function of insertion of union based on the minimum point distance(MPDIoU)is introduced for bounding box regression,which obtains faster convergence speed and more accurate regression results.Experimental results on the FLIR dataset show that the improved algorithm can accurately detect infrared road targets in real time with 3%and 2.2%enhancement in mean average precision at 50%IoU(mAP50)and mean average precision at 50%—95%IoU(mAP50-95),respectively,and 38.1%,37.3%and 16.9%reduction in the number of model parameters,the model weight,and floating-point operations per second(FLOPs),respectively.To further demonstrate the detection capability of the improved algorithm,it is tested on the public dataset PASCAL VOC,and the results show that F-YOLO has excellent generalized detection performance.
基金supported by the National Key Research and Development Program of China(2022YFE0127700)the 5·5 Engineering Research&Innovation Team Project of Beijing Forestry University(No.BLRC2023B06).
文摘Background In resource-based cities,long-term irrational exploitation of resources has caused severe damage to ecosystem functions,mainly manifested in the signifcant decline of biodiversity,land degradation,water pollution,and the deterioration of air quality.This has led to a signifcant decline in the cities’sustainable development capabilities.Establishing and optimizing an ecological spatial network(ESN)can promote the efective transmission of material energy and enhance the ecosystem functions,which holds fundamental importance in ensuring the ecological integrity of the region and promoting sustainable urban development.In this study,by combining the ecological environment with the landscape to determine the ecological sources,we constructed the ESN of Shenmu City,a mining city,based on the minimum cumulative resistance(MCR)model,and conducted a correlation analysis between the topological structure of the ESN and the signifcance of ecosystem functions.Then,the optimization strategy scheme based on ecosystem functions was proposed.Finally,robustness was used to determine the efect before and after optimization.Results The results showed that the high-value ecosystem service areas in Shenmu City were predominantly located in the central and western parts,with the highest value in the southeast.There was a strong correlation between the importance of ecosystem functions and the degree and feature vector of ecological nodes.Conclusions The ESN can be optimized efectively by adding stepping stone nodes and new corridors.Through the robustness of the optimized ESN,we found that the optimized network has more robust connectivity and stability and can show better recovery ability after ecological function damage.This research presents an efective method for the construction and optimization of the ESN in the mining area and provides a theoretical basis for realizing the sustainability of the mining economy,regional development,and ecological protection in Shenmu City.
基金Under the auspices of the National Natural Science Foundation of China (No.72273151)。
文摘City cluster is an effective platform for encouraging regionally coordinated development.Coordinated reduction of carbon emissions within city cluster via the spatial association network between cities can help coordinate the regional carbon emission management,realize sustainable development,and assist China in achieving the carbon peaking and carbon neutrality goals.This paper applies the improved gravity model and social network analysis(SNA)to the study of spatial correlation of carbon emissions in city clusters and analyzes the structural characteristics of the spatial correlation network of carbon emissions in the Yangtze River Delta(YRD)city cluster in China and its influencing factors.The results demonstrate that:1)the spatial association of carbon emissions in the YRD city cluster exhibits a typical and complex multi-threaded network structure.The network association number and density show an upward trend,indicating closer spatial association between cities,but their values remain generally low.Meanwhile,the network hierarchy and network efficiency show a downward trend but remain high.2)The spatial association network of carbon emissions in the YRD city cluster shows an obvious‘core-edge’distribution pattern.The network is centered around Shanghai,Suzhou and Wuxi,all of which play the role of‘bridges’,while cities such as Zhoushan,Ma'anshan,Tongling and other cities characterized by the remote location,single transportation mode or lower economic level are positioned at the edge of the network.3)Geographic proximity,varying levels of economic development,different industrial structures,degrees of urbanization,levels of technological innovation,energy intensities and environmental regulation are important influencing factors on the spatial association of within the YRD city cluster.Finally,policy implications are provided from four aspects:government macro-control and market mechanism guidance,structural characteristics of the‘core-edge’network,reconfiguration and optimization of the spatial layout of the YRD city cluster,and the application of advanced technologies.
基金the National Natural Science Foundation of China(Grant No.62172132)Public Welfare Technology Research Project of Zhejiang Province(Grant No.LGF21F020014)the Opening Project of Key Laboratory of Public Security Information Application Based on Big-Data Architecture,Ministry of Public Security of Zhejiang Police College(Grant No.2021DSJSYS002).
文摘Seal authentication is an important task for verifying the authenticity of stamped seals used in various domains to protect legal documents from tampering and counterfeiting.Stamped seal inspection is commonly audited manually to ensure document authenticity.However,manual assessment of seal images is tedious and laborintensive due to human errors,inconsistent placement,and completeness of the seal.Traditional image recognition systems are inadequate enough to identify seal types accurately,necessitating a neural network-based method for seal image recognition.However,neural network-based classification algorithms,such as Residual Networks(ResNet)andVisualGeometryGroup with 16 layers(VGG16)yield suboptimal recognition rates on stamp datasets.Additionally,the fixed training data categories make handling new categories to be a challenging task.This paper proposes amulti-stage seal recognition algorithmbased on Siamese network to overcome these limitations.Firstly,the seal image is pre-processed by applying an image rotation correction module based on Histogram of Oriented Gradients(HOG).Secondly,the similarity between input seal image pairs is measured by utilizing a similarity comparison module based on the Siamese network.Finally,we compare the results with the pre-stored standard seal template images in the database to obtain the seal type.To evaluate the performance of the proposed method,we further create a new seal image dataset that contains two subsets with 210,000 valid labeled pairs in total.The proposed work has a practical significance in industries where automatic seal authentication is essential as in legal,financial,and governmental sectors,where automatic seal recognition can enhance document security and streamline validation processes.Furthermore,the experimental results show that the proposed multi-stage method for seal image recognition outperforms state-of-the-art methods on the two established datasets.
基金the Foshan Science and technology Innovation Team Project(No.FS0AA-KJ919-4402-0060)the National Natural Science Foundation of China(No.62263018)。
文摘In view of the weak ability of the convolutional neural networks to explicitly learn spatial invariance and the probabilistic loss of discriminative features caused by occlusion and background interference in pedestrian re-identification tasks,a person re-identification method combining spatial feature learning and multi-granularity feature fusion was proposed.First,an attention spatial transformation network(A-STN)is proposed to learn spatial features and solve the problem of misalignment of pedestrian spatial features.Then the network was divided into a global branch,a local coarse-grained fusion branch,and a local fine-grained fusion branch to extract pedestrian global features,coarse-grained fusion features,and fine-grained fusion features,respectively.Among them,the global branch enriches the global features by fusing different pooling features.The local coarse-grained fusion branch uses an overlay pooling to enhance each local feature while learning the correlation relationship between multi-granularity features.The local fine-grained fusion branch uses a differential pooling to obtain the differential features that were fused with global features to learn the relationship between pedestrian local features and pedestrian global features.Finally,the proposed method was compared on three public datasets:Market1501,DukeMTMC-ReID and CUHK03.The experimental results were better than those of the comparative methods,which verifies the effectiveness of the proposed method.
基金This work is partially supported by the National Natural Science Foundation of China under Grant Nos. 61402532 and 41371386, the Science Foundation of China University of Petroleum-Beijing under Grant No. 2462013YJRC031, the Excellent Talents of Beijing Program under Grant No. 2013D009051000003, Beijing Nova Program, and the Open Research Fund Program of Shenzhen Key Laboratory of Spatial Smart Sensing and Services （Shenzhen University）.
文摘With the increasing availability of real-time traffic information, dynamic spatial networks are pervasive nowa- days and path planning in dynamic spatial networks becomes an important issue. In this light, we propose and investigate a novel problem of dynamically monitoring shortest paths in spatial networks （DSPM query）. When a traveler aims to a des- tination, his/her shortest path to the destination may change due to two reasons： 1） the travel costs of some edges have been updated and 2） the traveler deviates from the pre-planned path. Our target is to accelerate the shortest path computing in dynamic spatial networks, and we believe that this study may be useful in many mobile applications, such as route planning and recommendation, car navigation and tracking, and location-based services in general. This problem is challenging due to two reasons： 1） how to maintain and reuse the existing computation results to accelerate the following computations, and 2） how to prune the search space effectively. To overcome these challenges, filter-and-refinement paradigm is adopted. We maintain an expansion tree and define a pair of upper and lower bounds to prune the search space. A series of optimization techniques are developed to accelerate the shortest path computing. The performance of the developed methods is studied in extensive experiments based on real spatial data.
基金support of the Mathematical Biosciences Institute-DMS 1440386,NSF grant-DMS 1814737.
文摘We examine how spatial heterogeneity combines with mobility network structure to influence vector-borne disease dynamics.Specifically,we consider a Ross-Macdonald-type disease model on n spatial locations that are coupled by host movement on a strongly connected,weighted,directed graph.We derive a closed form approximation to the domain reproduction number using a Laurent series expansion,and use this approximation to compute sensitivities of the basic reproduction number to model parameters.To illustrate how these results can be used to help inform mitigation strategies,as a case study we apply these results to malaria dynamics in Namibia,using published cell phone data and estimates for local disease transmission.Our analytical results are particularly useful for understanding drivers of transmission when mobility sinks and transmission hot spots do not coincide.
基金This work was supported by SUG Research Grant M4082126.050 by the School of Mechanical and Aerospace Engineering(MAE),Nanyang Technological University(NTU),SingaporeNTU-CAAS Research Grant M4062429.052 by the ATM Research Institute,School of MAE,NTU,Singapore.
文摘Intractable delays occur in air traffic due to the imbalance between ever-increasing air traffic demand and limited airspace capacity.As air traffic is associated with complex air transport systems,delays can be magnified and propagated throughout these systems,resulting in the emergent behavior known as delay propagation.An understanding of delay propagation dynamics is pertinent to modern air traffic management.In this work,we present a complex network perspective of delay propagation dynamics.Specifically,we model air traffic scenarios using spatial–temporal networks with airports as the nodes.To establish the dynamic edges between the nodes,we develop a delay propagation method and apply it to a given set of air traffic schedules.Based on the constructed spatial-temporal networks,we suggest three metrics-magnitude,severity,and speed-to gauge delay propagation dynamics.To validate the effectiveness of the proposed method,we carry out case studies on domestic flights in the Southeastern Asia region(SAR)and the United States.Experiments demonstrate that the propagation magnitude in terms of the number of flights affected by delay propagation and the amount of propagated delays for the US traffic are respectively five and ten times those of the SAR.Experiments further reveal that the propagation speed for US traffic is eight times faster than that of the SAR.The delay propagation dynamics reveal that about six hub airports in the SAR have significant propagated delays,while the situation in the United States is considerably worse,with a corresponding number of around 16.This work provides a potent tool for tracing the evolution of air traffic delays.
基金financially supported by the National Natural Science Foundation of China(Grant No.51278217)
文摘This paper presents an artificial neural network（ANN）-based response surface method that can be used to predict the failure probability of c-φslopes with spatially variable soil.In this method,the Latin hypercube sampling technique is adopted to generate input datasets for establishing an ANN model;the random finite element method is then utilized to calculate the corresponding output datasets considering the spatial variability of soil properties;and finally,an ANN model is trained to construct the response surface of failure probability and obtain an approximate function that incorporates the relevant variables.The results of the illustrated example indicate that the proposed method provides credible and accurate estimations of failure probability.As a result,the obtained approximate function can be used as an alternative to the specific analysis process in c-φslope reliability analyses.
基金National Natural Science Foundation of China(No.42171448)Key Laboratory of National Geographic Census and Monitoring,Ministry of Nature Resources(No.2020NGCMZD03)。
文摘Based on the theories and methods of complex network,crude oil trade flows between countries along the Belt and Road(B&R,hereafter)are inserted into the Geo-space of B&R and form a spatial interaction network which takes the countries as nodes and takes the trade relations as edges.The networked mining and evolution analysis can provide important references for the research on trade relations among the B&R countries and the formulation of trade policy.This paper researches and discusses the construction,statistical analysis,top networks and stability of the crude oil trade network between the B&R countries from 2001 to 2020 from the perspectives of Geo-Computation for Social Sciences(GCSS)and spatial interaction.Firstly,evolutions of out-degree,in-degree,out-strength and in-strength of the top 10 countries in the crude oil trade network are computed and analyzed.Secondly,the top network method is used to explore the evolution characteristics of hierarchical structures.And finally,the sequential evolution characteristics of the crude oil trade network stability are analyzed utilizing the network stability measure method based on the trade relationship autocorrelation function.The analysis results show that Russia has the largest out-degree and out-strength,and China has the largest in-degree and in-strength.The crude oil trade volume of the top 10 import and export networks between 2001—2020 accounts for over 90%of the total trade volume of the crude oil trade network,and the proportion remains relatively stable.However,the stability of the network showed strong fluctuations in 2009,2012 and 2014,which may be closely related to major international events in these years,which could furtherly be used to build a correlation model between network volatility and major events.This paper explores how to construct and analyze the spatial interaction network of crude oil trade and can provide references for trade relations research and trade policy formulation of B&R countries.
文摘Human beings’ intellection is the characteristic of a distinct hierarchy and can be taken to construct a heuristic in the shortest path algorithms.It is detailed in this paper how to utilize the hierarchical reasoning on the basis of greedy and directional strategy to establish a spatial heuristic,so as to improve running efficiency and suitability of shortest path algorithm for traffic network.The authors divide urban traffic network into three hierarchies and set forward a new node hierarchy division rule to avoid the unreliable solution of shortest path.It is argued that the shortest path,no matter distance shortest or time shortest,is usually not the favorite of drivers in practice.Some factors difficult to expect or quantify influence the drivers’ choice greatly.It makes the drivers prefer choosing a less shortest,but more reliable or flexible path to travel on.The presented optimum path algorithm,in addition to the improvement of the running efficiency of shortest path algorithms up to several times,reduces the emergence of those factors,conforms to the intellection characteristic of human beings,and is more easily accepted by drivers.Moreover,it does not require the completeness of networks in the lowest hierarchy and the applicability and fault tolerance of the algorithm have improved.The experiment result shows the advantages of the presented algorithm.The authors argued that the algorithm has great potential application for navigation systems of large_scale traffic networks.
文摘A new algorithm called spatially aware routing algorithm with enhanced learning (SAREL) is proposed to guarantee the rationality of route selecting in inter-vehicle communication scenario. Firstly, the traffic model is discussed and set up by using Poisson distribution. Then we analyze the process of traffic evaluation with enhanced learning, and exploit movement estimation to assist state memorization. The improvement of algorithm is provided at last compared with our previous work. Simulation results show that SAREL algorithm could achieve better performance in packet delivery ratio, especially when network connection ratio is average. Key words mobile ad hoc network - spatially aware routing - enhanced learning CLC number TP 316 Foundation item: Supported by Open Laboratory Foundation by China Ministry of Education (TKLJ9903), Project CarTALK 2000 by the European Commission (IST-2000-28185) and Project FleetNet-Internet on the Road by the German Ministry of Education and Research (01AK025)Biography: HAN Lu (1974-), male, Ph. D candidate, research direction; distributed artificial intelligence.
基金Project supported by the National Natural Science Foundation of China (Grant No. 10872014)
文摘Spatial coherence resonance in a two-dimensional neuronal network induced by additive Gaussian coloured noise and parameter diversity is studied. We focus on the ability of additive Gaussian coloured noise and parameter diversity to extract a particular spatial frequency （wave number） of excitatory waves in the excitable medium of this network. We show that there exists an intermediate noise level of the coloured noise and a particular value of diversity, where a characteristic spatial frequency of the system comes forth. Hereby, it is verified that spatial coherence resonance occurs in the studied model. Furthermore, we show that the optimal noise intensity for spatial coherence resonance decays exponentially with respect to the noise correlation time. Some explanations of the observed nonlinear phenomena are also presented.
文摘On the basis of measuring the regional high-quality development in China from 2011 to 2020,this study uses gravity model to build spatial correlation network,and uses social network analysis method to analyze the structural characteristics and influencing factors of correlation network.The results are shown as follows.First,from 2011 to 2020,the level of regional high-quality development in China is rising gradually,and the discrete characteristics between regions are gradually obvious,showing a step-like distribution structure decreasing from east to west.Second,the network density of regional high-quality development is generally low and tends to decline,but it has strong stability and correlation strength.Third,the spatial correlation network has an obvious core-edge structure.Shanghai is always at the center of the network and plays a significant intermediary role,while Qinghai and Xinjiang are always at the edge of the network.Fourth,the regional high-quality development association network can be divided into four major sectors:main benefit,net benefit,net spillover,and broker,showing the spatial correlation characteristics of inter-plate contact and intra-plate agglomeration.Fifth,the level of economic development,the level of urbanization and geographical proximity have a significant impact on the formation of regional high-quality development correlation network.
基金supported in part by NSFC project (61571058, 61601052)
文摘Spatial division multiplexing enabled elastic optical networks(SDM-EONs) are the potential implementation form of future optical transport networks, because it can curve the physical limitation of achievable transmission capacity in single-mode fiber and single-core fiber. However, spectrum fragmentation issue becomes more serious in SDM-EONs compared with simple elastic optical networks(EONs) with single mode fiber or single core fiber. In this paper, multicore virtual concatenation(MCVC) scheme is first proposed considering inter-core crosstalk to solve the spectrum fragmentation issue in SDM-EONs. Simulation results show that the proposed MCVC scheme can achieve better performance compared with the baseline scheme, i.e., single-core virtual concatenation(SCVC) scheme, in terms of blocking probability and spectrum utilization.
基金Foundation： National Natural Science Foundation of China, No. 41271134
文摘Traffic is an indispensable prerequisite for a tourism system. The ＂four vertical and four horizontal＂ HSR network represents an important milestone of the ＂traffic revolution＂ in China. It will affect the spatial pattern of tourism accessibility in Chinese cities, thus substan- tially increasing their power to attract tourists and their radiation force. This paper examines the evolution and spatial characteristics of the power to attract tourism of cities linked by China＇s HSR network by measuring the influence of accessibility of 338 HSR-linked cities using GIS analysis. The results show the following. （1） The accessibility of Chinese cities is optimized by the HSR network, whose spatial pattern of accessibility exhibits an obvious traf- fic direction and causes a high-speed rail-corridor effect. （2） The spatial pattern of tourism field strength in Chinese cities exhibits the dual characteristics of multi-center annular diver- gence and dendritic diffusion. Dendritic diffusion is particularly more obvious along the HSR line. The change rate of urban tourism field strength forms a high-value corridor along the HSR line and exhibits a spatial pattern of decreasing area from the center to the outer limit along the HSR line. （3） The influence of the higher and highest tourism field strength areas along the HSR line is most significant, and the number of cities that distribute into these two types of tourism field strengths significantly increases： their area expands by more than 100% HSR enhances the tourism field strength value of regional central cities, and the radiation range of tourism attraction extends along the HSR line.
