In this paper, we investigate the method of computer simulation for derivative weave by adopting the way of weave differentiation with mathematical function. And on that base, we explore the way for dealing with compo...In this paper, we investigate the method of computer simulation for derivative weave by adopting the way of weave differentiation with mathematical function. And on that base, we explore the way for dealing with composed weave. It is purposed for building a simple and efficient way of computer simulation for weave.展开更多
A novel face recognition method based on fusion of spatial and frequency features was presented to improve recognition accuracy. Dual-Tree Complex Wavelet Transform derives desirable facial features to cope with the v...A novel face recognition method based on fusion of spatial and frequency features was presented to improve recognition accuracy. Dual-Tree Complex Wavelet Transform derives desirable facial features to cope with the variation due to the illumination and facial expression changes. By adopting spectral regression and complex fusion technologies respectively, two improved neighborhood preserving discriminant analysis feature extraction methods were proposed to capture the face manifold structures and locality discriminatory information. Extensive experiments have been made to compare the recognition performance of the proposed method with some popular dimensionality reduction methods on ORL and Yale face databases. The results verify the effectiveness of the proposed method.展开更多
The system of mixture of single lane and double lane is studied by a cellular automata model, which is developed by us based on the Nagel and Schreckenberg＇s models. We justify that the model can reach a stable state...The system of mixture of single lane and double lane is studied by a cellular automata model, which is developed by us based on the Nagel and Schreckenberg＇s models. We justify that the model can reach a stable states quickly. The density distributions of the stable state is presented for several cases, which illustrate the manner of the congestion. The relationship between the outflow rate and the total number of vehicles and that between the outflow rate and the density just before the bottleneck are both given. Comparing with the relationship that occurring in the granular flow, we conclude that the transition from the free traffic flow to the congested traffic flow can also be attributed to the abrupt variation through unstable flow state, which can naturally explain the discontinuities and the complex time variation behavior observed in the traffic flow experiments.展开更多
For complex chemical processes,process optimization is usually performed on causal models from first principle models.When the mechanism models cannot be obtained easily,restricted model built by process data is used ...For complex chemical processes,process optimization is usually performed on causal models from first principle models.When the mechanism models cannot be obtained easily,restricted model built by process data is used for dynamic process optimization.A new strategy is proposed for complex process optimization,in which latent variables are used as decision variables and statistics is used to describe constraints.As the constraint condition will be more complex by projecting the original variable to latent space,Hotelling T^2 statistics is introduced for constraint formulation in latent space.In this way,the constraint is simplified when the optimization is solved in low-dimensional space of latent variable.The validity of the methodology is illustrated in pH-level optimal control process and practical polypropylene grade transition process.展开更多
Identifying the impacts of climate change is important for conservation of ecosystems under climate change, particularly in mountain regions. Holdridge life zone system and Koppen classification provide two effective ...Identifying the impacts of climate change is important for conservation of ecosystems under climate change, particularly in mountain regions. Holdridge life zone system and Koppen classification provide two effective methods to assess impacts of climate change on ecosystems, as typical climate-vegetation models. Meanwhile, these previous studies are insufficient to assess the complex terrain as well as there are some uncertainties in results while using the given methods. Analysis of the impacts of the prevailing climate conditions in an area on shifts of ecosystems may reduce uncertainties in projecting climate change. In this study, we used different models to depict changes in ecosystems at 1 km × 1 km resolution in Sichuan Province, China during 1961-2010. The results indicate that changes in climate data during the past 50 years were sufficient to cause shifts in the spatial distribution of ecosystems. The trend of shift was from low temperature ecosystems to high temperature ecosystems. Compared with K？ppen classification, the Holdridge system has better adaptation to assess the impacts of climate change on ecosystems in low elevation（0-1000 m）. Moreover, we found that changed areas in ecosystems were easily affected by climate change than unchanged areas by calculating current climate condition.展开更多
Severe water erosion is notorious for its harmful effects on land-water resources as well as local societies. The scale effects of water erosion, however, greatly exacerbate the difficulties of accurate erosion evalua...Severe water erosion is notorious for its harmful effects on land-water resources as well as local societies. The scale effects of water erosion, however, greatly exacerbate the difficulties of accurate erosion evaluation and hazard control in the real world. Analyzing the related scale issues is thus urgent for a better understanding of erosion variations as well as reducing such erosion. In this review article, water erosion dynamics across three spatial scales including plot, watershed, and regional scales were selected and discussed. For the study purposes and objectives, the advantages and disadvantages of these scales all demonstrate clear spatial-scale dependence. Plot scale studies are primarily focused on abundant data collection and mechanism discrimination of erosion generation, while watershed scale studies provide valuable information for watershed management and hazard control as well as the development of quantitatively distributed models. Regional studies concentrate more on large-scale erosion assessment, and serve policymakers and stakeholders in achieving the basis for regulatory policy for comprehensive land uses. The results of this study show that the driving forces and mechanisms of water erosion variations among the scales are quite different. As a result, several major aspects contributing to variations in water erosion across the scales are stressed: differences in the methodologies across various scales, different sink-source roles on water erosion processes, and diverse climatic zones and morphological regions. This variability becomes more complex in the context of accelerated global change. The changing climatic factors and earth surface features are considered the fourth key reason responsible for the increased variability of water erosion across spatial scales.展开更多
Abnormal conditions are hazardous in complex process systems, and the aim of condition recognition is to detect abnormal conditions and thus avoid severe accidents. The relationship of linkage fluctuation between moni...Abnormal conditions are hazardous in complex process systems, and the aim of condition recognition is to detect abnormal conditions and thus avoid severe accidents. The relationship of linkage fluctuation between monitoring variables can characterize the operation state of the system. In this study,we present a straightforward and fast computational method, the multivariable linkage coarse graining(MLCG) algorithm, which converts the linkage fluctuation relationship of multivariate time series into a directed and weighted complex network. The directed and weighted complex network thus constructed inherits several properties of the series in its structure. Thereby, periodic series convert into regular networks, and random series convert into random networks. Moreover, chaotic time series convert into scale-free networks. It demonstrates that the MLCG algorithm permits us to distinguish, identify, and describe in detail various time series. Finally, we apply the MLCG algorithm to practical observations series, the monitoring time series from a compressor unit, and identify its dynamic characteristics. Empirical results demonstrate that the MLCG algorithm is suitable for analyzing the multivariable linkage fluctuation relationship in complex electromechanical system. This method can be used to detect specific or abnormal operation condition, which is relevant to condition identification and information quality control of complex electromechanical system in the process industry.展开更多
文摘In this paper, we investigate the method of computer simulation for derivative weave by adopting the way of weave differentiation with mathematical function. And on that base, we explore the way for dealing with composed weave. It is purposed for building a simple and efficient way of computer simulation for weave.
基金National Natural Science Foundation of China(No.61004088)Key Basic Research Foundation of Shanghai Municipal Science and Technology Commission,China(No.09JC1408000)
文摘A novel face recognition method based on fusion of spatial and frequency features was presented to improve recognition accuracy. Dual-Tree Complex Wavelet Transform derives desirable facial features to cope with the variation due to the illumination and facial expression changes. By adopting spectral regression and complex fusion technologies respectively, two improved neighborhood preserving discriminant analysis feature extraction methods were proposed to capture the face manifold structures and locality discriminatory information. Extensive experiments have been made to compare the recognition performance of the proposed method with some popular dimensionality reduction methods on ORL and Yale face databases. The results verify the effectiveness of the proposed method.
基金supported by National Natural Science Foundation of China under Grant Nos. 10674157 and 10875166
文摘The system of mixture of single lane and double lane is studied by a cellular automata model, which is developed by us based on the Nagel and Schreckenberg＇s models. We justify that the model can reach a stable states quickly. The density distributions of the stable state is presented for several cases, which illustrate the manner of the congestion. The relationship between the outflow rate and the total number of vehicles and that between the outflow rate and the density just before the bottleneck are both given. Comparing with the relationship that occurring in the granular flow, we conclude that the transition from the free traffic flow to the congested traffic flow can also be attributed to the abrupt variation through unstable flow state, which can naturally explain the discontinuities and the complex time variation behavior observed in the traffic flow experiments.
基金Supported by the National Natural Science Foundation of China(61174114)the Research Fund for the Doctoral Program of Higher Education in China(20120101130016)+1 种基金the Natural Science Foundation of Zhejiang Province(LQ15F030006)the Educational Commission Research Program of Zhejiang Province(Y201431412)
文摘For complex chemical processes,process optimization is usually performed on causal models from first principle models.When the mechanism models cannot be obtained easily,restricted model built by process data is used for dynamic process optimization.A new strategy is proposed for complex process optimization,in which latent variables are used as decision variables and statistics is used to describe constraints.As the constraint condition will be more complex by projecting the original variable to latent space,Hotelling T^2 statistics is introduced for constraint formulation in latent space.In this way,the constraint is simplified when the optimization is solved in low-dimensional space of latent variable.The validity of the methodology is illustrated in pH-level optimal control process and practical polypropylene grade transition process.
基金Under the auspices of National Basic Research Program of China(No.2015CB452702)
文摘Identifying the impacts of climate change is important for conservation of ecosystems under climate change, particularly in mountain regions. Holdridge life zone system and Koppen classification provide two effective methods to assess impacts of climate change on ecosystems, as typical climate-vegetation models. Meanwhile, these previous studies are insufficient to assess the complex terrain as well as there are some uncertainties in results while using the given methods. Analysis of the impacts of the prevailing climate conditions in an area on shifts of ecosystems may reduce uncertainties in projecting climate change. In this study, we used different models to depict changes in ecosystems at 1 km × 1 km resolution in Sichuan Province, China during 1961-2010. The results indicate that changes in climate data during the past 50 years were sufficient to cause shifts in the spatial distribution of ecosystems. The trend of shift was from low temperature ecosystems to high temperature ecosystems. Compared with K？ppen classification, the Holdridge system has better adaptation to assess the impacts of climate change on ecosystems in low elevation（0-1000 m）. Moreover, we found that changed areas in ecosystems were easily affected by climate change than unchanged areas by calculating current climate condition.
基金Under the auspices of National Natural Science Foundation of China (No. 40925003, 40930528, 40801041)
文摘Severe water erosion is notorious for its harmful effects on land-water resources as well as local societies. The scale effects of water erosion, however, greatly exacerbate the difficulties of accurate erosion evaluation and hazard control in the real world. Analyzing the related scale issues is thus urgent for a better understanding of erosion variations as well as reducing such erosion. In this review article, water erosion dynamics across three spatial scales including plot, watershed, and regional scales were selected and discussed. For the study purposes and objectives, the advantages and disadvantages of these scales all demonstrate clear spatial-scale dependence. Plot scale studies are primarily focused on abundant data collection and mechanism discrimination of erosion generation, while watershed scale studies provide valuable information for watershed management and hazard control as well as the development of quantitatively distributed models. Regional studies concentrate more on large-scale erosion assessment, and serve policymakers and stakeholders in achieving the basis for regulatory policy for comprehensive land uses. The results of this study show that the driving forces and mechanisms of water erosion variations among the scales are quite different. As a result, several major aspects contributing to variations in water erosion across the scales are stressed: differences in the methodologies across various scales, different sink-source roles on water erosion processes, and diverse climatic zones and morphological regions. This variability becomes more complex in the context of accelerated global change. The changing climatic factors and earth surface features are considered the fourth key reason responsible for the increased variability of water erosion across spatial scales.
基金supported by the National Natural Science Foundation of China(Grant No.51375375)
文摘Abnormal conditions are hazardous in complex process systems, and the aim of condition recognition is to detect abnormal conditions and thus avoid severe accidents. The relationship of linkage fluctuation between monitoring variables can characterize the operation state of the system. In this study,we present a straightforward and fast computational method, the multivariable linkage coarse graining(MLCG) algorithm, which converts the linkage fluctuation relationship of multivariate time series into a directed and weighted complex network. The directed and weighted complex network thus constructed inherits several properties of the series in its structure. Thereby, periodic series convert into regular networks, and random series convert into random networks. Moreover, chaotic time series convert into scale-free networks. It demonstrates that the MLCG algorithm permits us to distinguish, identify, and describe in detail various time series. Finally, we apply the MLCG algorithm to practical observations series, the monitoring time series from a compressor unit, and identify its dynamic characteristics. Empirical results demonstrate that the MLCG algorithm is suitable for analyzing the multivariable linkage fluctuation relationship in complex electromechanical system. This method can be used to detect specific or abnormal operation condition, which is relevant to condition identification and information quality control of complex electromechanical system in the process industry.
