The first problem considered in this article reads： is it possible to find upper estimates for the spanning tree congestion in bipartite graphs, which are better than those for general graphs？ It is proved that ther...The first problem considered in this article reads： is it possible to find upper estimates for the spanning tree congestion in bipartite graphs, which are better than those for general graphs？ It is proved that there exists a bipartite version of the known graph with spanning tree congestion of order n3/2, where n is the number of vertices. The second problem is to estimate spanning tree congestion of random graphs. It is proved that the standard model of random graphs cannot be used to find graphs whose spanning tree congestion has order greater than n3/2.展开更多
Recently a great deal of effort has been made to explicitly determine the mean first-passage time （MFPT） between two nodes averaged over all pairs of nodes on a fractal network. In this paper, we first propose a fam...Recently a great deal of effort has been made to explicitly determine the mean first-passage time （MFPT） between two nodes averaged over all pairs of nodes on a fractal network. In this paper, we first propose a family of generalized delayed recursive trees characterized by two parameters, where the existing nodes have a time delay to produce new nodes. We then study the MFPT of random walks on this kind of recursive tree and investigate the effect of the time delay on the MFPT. By relating random walks to electrical networks, we obtain an exact formula for the MFPT and verify it by numerical calculations. Based on the obtained results, we further show that the MFPT of delayed recursive trees is much shorter, implying that the efficiency of random walks is much higher compared with the non-delayed counterpart. Our study provides a deeper understanding of random walks on delayed fractal networks.展开更多
Controls, especially effficiency controls on dynamical processes, have become major challenges in many complex systems. We study an important dynamical process, random walk, due to its wide range of applications for m...Controls, especially effficiency controls on dynamical processes, have become major challenges in many complex systems. We study an important dynamical process, random walk, due to its wide range of applications for modeling the transporting or searching process. For lack of control methods for random walks in various structures, a control technique is presented for a class of weighted treelike scale-free networks with a deep trap at a hub node. The weighted networks are obtained from original models by introducing a weight parameter. We compute analytically the mean first passage time （MFPT） as an indicator for quantitatively measurinM the et^ciency of the random walk process. The results show that the MFPT increases exponentially with the network size, and the exponent varies with the weight parameter. The MFPT, therefore, can be controlled by the weight parameter to behave superlinearly, linearly, or sublinearly with the system size. This work provides further useful insights into controllinM eftlciency in scale-free complex networks.展开更多
We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Se...We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Sentinel-1 SAR dual-pol(SVV,vertically transmitted and vertically received and SVH,vertically transmitted and horizontally received)configuration,one notes that S_(HH),the horizontally transmitted and horizontally received scattering element,is unavailable.The S_(HH)data were constructed using the SVH data,and polarimetric SAR(PolSAR)data were obtained.The proposed approach was first verified in simulation with satisfactory results.It was next applied to construct PolInSAR data by a pair of dual-pol Sentinel-1A data at Duke Forest,North Carolina,USA.According to local observations and forest descriptions,the range of estimated tree heights was overall reasonable.Comparing the heights with the ICESat-2 tree heights at 23 sampling locations,relative errors of 5 points were within±30%.Errors of 8 points ranged from 30%to 40%,but errors of the remaining 10 points were>40%.The results should be encouraged as error reduction is possible.For instance,the construction of PolSAR data should not be limited to using SVH,and a combination of SVH and SVV should be explored.Also,an ensemble of tree heights derived from multiple PolInSAR data can be considered since tree heights do not vary much with time frame in months or one season.展开更多
面对采摘作业的复杂环境,提出了一种终点区域RRT(Goal Area RRT,GA-RRT)算法,以提高路径生成的效率并降低路径成本。根据环境系数确定初始步长与终点区域,当拓展节点进入终点区域后,随机点生成范围缩小至终点区域,同时调整步长;然后,在...面对采摘作业的复杂环境,提出了一种终点区域RRT(Goal Area RRT,GA-RRT)算法,以提高路径生成的效率并降低路径成本。根据环境系数确定初始步长与终点区域,当拓展节点进入终点区域后,随机点生成范围缩小至终点区域,同时调整步长;然后,在此基础上引入目标概率偏向方法,提高路径搜索效率;最后,对生成的路径进行简化节点处理以减少路径代价,并使用三次B样条方法平滑路径。仿真实验结果表明:二维环境下,GA-RRT算法相较于RRT、RRT-Connect算法,耗时缩短85.15%、29.86%,路径代价减少19.18%、18.26%;机械臂仿真环境下,与引入目标概率偏向方法的RRT算法进行比较,耗时缩短54.70%,路径代价减少51.59°。利用IRB120机械臂实验平台,验证了算法的可行性。展开更多
Height–diameter relationships are essential elements of forest assessment and modeling efforts.In this work,two linear and eighteen nonlinear height–diameter equations were evaluated to find a local model for Orient...Height–diameter relationships are essential elements of forest assessment and modeling efforts.In this work,two linear and eighteen nonlinear height–diameter equations were evaluated to find a local model for Oriental beech（Fagus orientalis Lipsky） in the Hyrcanian Forest in Iran.The predictive performance of these models was first assessed by different evaluation criteria： adjusted R^2（R^2_（adj））,root mean square error（RMSE）,relative RMSE（%RMSE）,bias,and relative bias（%bias） criteria.The best model was selected for use as the base mixed-effects model.Random parameters for test plots were estimated with different tree selection options.Results show that the Chapman–Richards model had better predictive ability in terms of adj R^2（0.81）,RMSE（3.7 m）,%RMSE（12.9）,bias（0.8）,%Bias（2.79） than the other models.Furthermore,the calibration response,based on a selection of four trees from the sample plots,resulted in a reduction percentage for bias and RMSE of about 1.6–2.7%.Our results indicate that the calibrated model produced the most accurate results.展开更多
This paper studies the strong law of large numbers and the Shannom-McMillan theorem for Markov chains field on Cayley tree. The authors first prove the strong law of large number on the frequencies of states and order...This paper studies the strong law of large numbers and the Shannom-McMillan theorem for Markov chains field on Cayley tree. The authors first prove the strong law of large number on the frequencies of states and orderd couples of states for Markov chains field on Cayley tree. Then they prove the Shannon-McMillan theorem with a.e. convergence for Markov chains field on Cayley tree. In the proof, a new technique in the study the strong limit theorem in probability theory is applied.展开更多
Although airborne hyperspectral data with detailed spatial and spectral information has demonstrated significant potential for tree species classification,it has not been widely used over large areas.A comprehensive p...Although airborne hyperspectral data with detailed spatial and spectral information has demonstrated significant potential for tree species classification,it has not been widely used over large areas.A comprehensive process based on multi-flightline airborne hyperspectral data is lacking over large,forested areas influenced by both the effects of bidirectional reflectance distribution function(BRDF)and cloud shadow contamination.In this study,hyperspectral data were collected over the Mengjiagang Forest Farm in Northeast China in the summer of 2017 using the Chinese Academy of Forestry's LiDAR,CCD,and hyperspectral systems(CAF-LiCHy).After BRDF correction and cloud shadow detection processing,a tree species classification workflow was developed for sunlit and cloud-shaded forest areas with input features of minimum noise fraction reduced bands,spectral vegetation indices,and texture information.Results indicate that BRDF-corrected sunlit hyperspectral data can provide a stable and high classification accuracy based on representative training data.Cloud-shaded pixels also have good spectral separability for species classification.The red-edge spectral information and ratio-based spectral indices with high importance scores are recommended as input features for species classification under varying light conditions.According to the classification accuracies through field survey data at multiple spatial scales,it was found that species classification within an extensive forest area using airborne hyperspectral data under various illuminations can be successfully carried out using the effective radiometric consistency process and feature selection strategy.展开更多
This paper presents a human action recognition method. It analyzes the spatio-temporal grids along the dense trajectories and generates the histogram of oriented gradients （HOG） and histogram of optical flow （HOF）...This paper presents a human action recognition method. It analyzes the spatio-temporal grids along the dense trajectories and generates the histogram of oriented gradients （HOG） and histogram of optical flow （HOF） to describe the appearance and motion of the human object. Then, HOG combined with HOF is converted to bag-of-words （BoWs） by the vocabulary tree. Finally, it applies random forest to recognize the type of human action. In the experiments, KTH database and URADL database are tested for the performance evaluation. Comparing with the other approaches, we show that our approach has a better performance for the action videos with high inter-class and low inter-class variabilities.展开更多
文摘The first problem considered in this article reads： is it possible to find upper estimates for the spanning tree congestion in bipartite graphs, which are better than those for general graphs？ It is proved that there exists a bipartite version of the known graph with spanning tree congestion of order n3/2, where n is the number of vertices. The second problem is to estimate spanning tree congestion of random graphs. It is proved that the standard model of random graphs cannot be used to find graphs whose spanning tree congestion has order greater than n3/2.
基金Project supported by the National Natural Science Foundation of China (Grant Nos.61203155 and 11232005)the Natural Science Foundation of Zhejiang Province,China (Grant No.LQ12F03003)the Hong Kong Research Grants Council under the GRF Grant CityU (Grant No.1109/12)
文摘Recently a great deal of effort has been made to explicitly determine the mean first-passage time （MFPT） between two nodes averaged over all pairs of nodes on a fractal network. In this paper, we first propose a family of generalized delayed recursive trees characterized by two parameters, where the existing nodes have a time delay to produce new nodes. We then study the MFPT of random walks on this kind of recursive tree and investigate the effect of the time delay on the MFPT. By relating random walks to electrical networks, we obtain an exact formula for the MFPT and verify it by numerical calculations. Based on the obtained results, we further show that the MFPT of delayed recursive trees is much shorter, implying that the efficiency of random walks is much higher compared with the non-delayed counterpart. Our study provides a deeper understanding of random walks on delayed fractal networks.
基金Supported by the National Natural Science Foundation of China under Grant Nos 61173118,61373036 and 61272254
文摘Controls, especially effficiency controls on dynamical processes, have become major challenges in many complex systems. We study an important dynamical process, random walk, due to its wide range of applications for modeling the transporting or searching process. For lack of control methods for random walks in various structures, a control technique is presented for a class of weighted treelike scale-free networks with a deep trap at a hub node. The weighted networks are obtained from original models by introducing a weight parameter. We compute analytically the mean first passage time （MFPT） as an indicator for quantitatively measurinM the et^ciency of the random walk process. The results show that the MFPT increases exponentially with the network size, and the exponent varies with the weight parameter. The MFPT, therefore, can be controlled by the weight parameter to behave superlinearly, linearly, or sublinearly with the system size. This work provides further useful insights into controllinM eftlciency in scale-free complex networks.
文摘We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Sentinel-1 SAR dual-pol(SVV,vertically transmitted and vertically received and SVH,vertically transmitted and horizontally received)configuration,one notes that S_(HH),the horizontally transmitted and horizontally received scattering element,is unavailable.The S_(HH)data were constructed using the SVH data,and polarimetric SAR(PolSAR)data were obtained.The proposed approach was first verified in simulation with satisfactory results.It was next applied to construct PolInSAR data by a pair of dual-pol Sentinel-1A data at Duke Forest,North Carolina,USA.According to local observations and forest descriptions,the range of estimated tree heights was overall reasonable.Comparing the heights with the ICESat-2 tree heights at 23 sampling locations,relative errors of 5 points were within±30%.Errors of 8 points ranged from 30%to 40%,but errors of the remaining 10 points were>40%.The results should be encouraged as error reduction is possible.For instance,the construction of PolSAR data should not be limited to using SVH,and a combination of SVH and SVV should be explored.Also,an ensemble of tree heights derived from multiple PolInSAR data can be considered since tree heights do not vary much with time frame in months or one season.
文摘面对采摘作业的复杂环境,提出了一种终点区域RRT(Goal Area RRT,GA-RRT)算法,以提高路径生成的效率并降低路径成本。根据环境系数确定初始步长与终点区域,当拓展节点进入终点区域后,随机点生成范围缩小至终点区域,同时调整步长;然后,在此基础上引入目标概率偏向方法,提高路径搜索效率;最后,对生成的路径进行简化节点处理以减少路径代价,并使用三次B样条方法平滑路径。仿真实验结果表明:二维环境下,GA-RRT算法相较于RRT、RRT-Connect算法,耗时缩短85.15%、29.86%,路径代价减少19.18%、18.26%;机械臂仿真环境下,与引入目标概率偏向方法的RRT算法进行比较,耗时缩短54.70%,路径代价减少51.59°。利用IRB120机械臂实验平台,验证了算法的可行性。
基金This research received no specific grant from any funding agency in the public,commercial,or not-for-profit sectors
文摘Height–diameter relationships are essential elements of forest assessment and modeling efforts.In this work,two linear and eighteen nonlinear height–diameter equations were evaluated to find a local model for Oriental beech（Fagus orientalis Lipsky） in the Hyrcanian Forest in Iran.The predictive performance of these models was first assessed by different evaluation criteria： adjusted R^2（R^2_（adj））,root mean square error（RMSE）,relative RMSE（%RMSE）,bias,and relative bias（%bias） criteria.The best model was selected for use as the base mixed-effects model.Random parameters for test plots were estimated with different tree selection options.Results show that the Chapman–Richards model had better predictive ability in terms of adj R^2（0.81）,RMSE（3.7 m）,%RMSE（12.9）,bias（0.8）,%Bias（2.79） than the other models.Furthermore,the calibration response,based on a selection of four trees from the sample plots,resulted in a reduction percentage for bias and RMSE of about 1.6–2.7%.Our results indicate that the calibrated model produced the most accurate results.
文摘This paper studies the strong law of large numbers and the Shannom-McMillan theorem for Markov chains field on Cayley tree. The authors first prove the strong law of large number on the frequencies of states and orderd couples of states for Markov chains field on Cayley tree. Then they prove the Shannon-McMillan theorem with a.e. convergence for Markov chains field on Cayley tree. In the proof, a new technique in the study the strong limit theorem in probability theory is applied.
基金supported by the National Natural Science Foundation of China (Grant No.42101403)the National Key Researchand Development Program of China (Grant No.2017YFD0600404)。
文摘Although airborne hyperspectral data with detailed spatial and spectral information has demonstrated significant potential for tree species classification,it has not been widely used over large areas.A comprehensive process based on multi-flightline airborne hyperspectral data is lacking over large,forested areas influenced by both the effects of bidirectional reflectance distribution function(BRDF)and cloud shadow contamination.In this study,hyperspectral data were collected over the Mengjiagang Forest Farm in Northeast China in the summer of 2017 using the Chinese Academy of Forestry's LiDAR,CCD,and hyperspectral systems(CAF-LiCHy).After BRDF correction and cloud shadow detection processing,a tree species classification workflow was developed for sunlit and cloud-shaded forest areas with input features of minimum noise fraction reduced bands,spectral vegetation indices,and texture information.Results indicate that BRDF-corrected sunlit hyperspectral data can provide a stable and high classification accuracy based on representative training data.Cloud-shaded pixels also have good spectral separability for species classification.The red-edge spectral information and ratio-based spectral indices with high importance scores are recommended as input features for species classification under varying light conditions.According to the classification accuracies through field survey data at multiple spatial scales,it was found that species classification within an extensive forest area using airborne hyperspectral data under various illuminations can be successfully carried out using the effective radiometric consistency process and feature selection strategy.
基金supported by the MOST,Taiwan under Grant No.102-2221-E-468-013
文摘This paper presents a human action recognition method. It analyzes the spatio-temporal grids along the dense trajectories and generates the histogram of oriented gradients （HOG） and histogram of optical flow （HOF） to describe the appearance and motion of the human object. Then, HOG combined with HOF is converted to bag-of-words （BoWs） by the vocabulary tree. Finally, it applies random forest to recognize the type of human action. In the experiments, KTH database and URADL database are tested for the performance evaluation. Comparing with the other approaches, we show that our approach has a better performance for the action videos with high inter-class and low inter-class variabilities.
