Objective The 2014 Ludian M_w6.1 earthquake in Yunnan occurred in a mountainous area with complex tectonics and topography,which caused serious damage as well as co-seismic landslides of an unusual large scale.Because...Objective The 2014 Ludian M_w6.1 earthquake in Yunnan occurred in a mountainous area with complex tectonics and topography,which caused serious damage as well as co-seismic landslides of an unusual large scale.Because the suspected seismogenic faults on the surface,distribution of aftershocks and focal mechanism展开更多
This study evaluates the structure and regeneration status of woody species in the Munessa Forest,a dry Afromontane forest in southern Ethiopia.Vegetation data were collected using a systematic sampling method.Density...This study evaluates the structure and regeneration status of woody species in the Munessa Forest,a dry Afromontane forest in southern Ethiopia.Vegetation data were collected using a systematic sampling method.Density and distribution of seedlings,saplings and mature trees were assessed along an altitudinal gradient using quadrats of different sizes.The number of individuals,frequencies,heights and DBH of species>1 m and DBH>2.5 cm were recorded in altitudinal bands of 100 m.Analysis of the vegetation structure shows that the density of woody species decreases as DBH and height class increases.Basal area of stems with DBH>2.5 cm was 53.4 m^(2)ha^(−1).Population structure and regeneration patterns indicate a significant degradation of the forest due to anthropogenic disturbances.Regeneration was better for less valuable woody species than for species with economic and ecological value.This suggests a discontinuous recruitment of these species due to selective cutting of middle and higher diameter classes.Therefore,enrichment planting of high value,endangered species is necessary to maintain them as part of this forest.There is a need to develop and implement an effective forest management plan for sustainable use of these forest resources.展开更多
In recent years,deep neural networks have become a fascinating and influential research subject,and they play a critical role in video processing and analytics.Since,video analytics are predominantly hardware centric,...In recent years,deep neural networks have become a fascinating and influential research subject,and they play a critical role in video processing and analytics.Since,video analytics are predominantly hardware centric,exploration of implementing the deep neural networks in the hardware needs its brighter light of research.However,the computational complexity and resource constraints of deep neural networks are increasing exponentially by time.Convolutional neural networks are one of the most popular deep learning architecture especially for image classification and video analytics.But these algorithms need an efficient implement strategy for incorporating more real time computations in terms of handling the videos in the hardware.Field programmable Gate arrays(FPGA)is thought to be more advantageous in implementing the convolutional neural networks when compared to Graphics Processing Unit(GPU)in terms of energy efficient and low computational complexity.But still,an intelligent architecture is required for implementing the CNN in FPGA for processing the videos.This paper introduces a modern high-performance,energy-efficient Bat Pruned Ensembled Convolutional networks(BPEC-CNN)for processing the video in the hardware.The system integrates the Bat Evolutionary Pruned layers for CNN and implements the new shared Distributed Filtering Structures(DFS)for handing the filter layers in CNN with pipelined data-path in FPGA.In addition,the proposed system adopts the hardware-software co-design methodology for an energy efficiency and less computational complexity.The extensive experimentations are carried out using CASIA video datasets with ARTIX-7 FPGA boards(number)and various algorithms centric parameters such as accuracy,sensitivity,specificity and architecture centric parameters such as the power,area and throughput are analyzed.These results are then compared with the existing pruned CNN architectures such as CNN-Prunner in which the proposed architecture has been shown 25%better performance than the existing architectures.展开更多
In this paper,the event-triggered consensus control problem for nonlinear uncertain multi-agent systems subject to unknown parameters and external disturbances is considered.The dynamics of subsystems are second-order...In this paper,the event-triggered consensus control problem for nonlinear uncertain multi-agent systems subject to unknown parameters and external disturbances is considered.The dynamics of subsystems are second-order with similar structures,and the nodes are connected by undirected graphs.The event-triggered mechanisms are not only utilized in the transmission of information from the controllers to the actuators,and from the sensors to the controllers within each agent,but also in the communication between agents.Based on the adaptive backstepping method,extra estimators are introduced to handle the unknown parameters,and the measurement errors that occur during the event-triggered communication are well handled by designing compensating terms for the control signals.The presented distributed event-triggered adaptive control laws can guarantee the boundness of the consensus tracking errors and the Zeno behavior is avoided.Meanwhile,the update frequency of the controllers and the load of communication burden are vastly reduced.The obtained control protocol is further applied to a multi-input multi-output second-order nonlinear multi-agent system,and the simulation results show the effectiveness and advantages of our proposed method.展开更多
In order to improve the accuracy of damage region division and eliminate the interference of damage adjacent region,the airframe damage region division method based on the structure tensor dynamic operator is proposed...In order to improve the accuracy of damage region division and eliminate the interference of damage adjacent region,the airframe damage region division method based on the structure tensor dynamic operator is proposed in this paper.The structure tensor feature space is established to represent the local features of damage images.It makes different damage images have the same feature distribution,and transform varied damage region division into consistent process of feature space division.On this basis,the structure tensor dynamic operator generation method is designed.It integrates with bacteria foraging optimization algorithm improved by defining double fitness function and chemotaxis rules,in order to calculate the parameters of dynamic operator generation method and realize the structure tensor feature space division.And then the airframe damage region division is realized.The experimental results on different airframe structure damage images show that compared with traditional threshold division method,the proposed method can improve the division quality.The interference of damage adjacent region is eliminated.The information loss caused by over-segmentation is avoided.And it is efficient in operation,and consistent in process.It also has the applicability to different types of structural damage.展开更多
In this paper,based on simplified Boltzmann equation,we explore the inverse-design of mesoscopic models for compressible flow using the Chapman-Enskog analysis.Starting from the single-relaxation-time Boltzmann equati...In this paper,based on simplified Boltzmann equation,we explore the inverse-design of mesoscopic models for compressible flow using the Chapman-Enskog analysis.Starting from the single-relaxation-time Boltzmann equation with an additional source term,two model Boltzmann equations for two reduced distribution functions are obtained,each then also having an additional undetermined source term.Under this general framework and using Navier-Stokes-Fourier(NSF)equations as constraints,the structures of the distribution functions are obtained by the leading-order Chapman-Enskog analysis.Next,five basic constraints for the design of the two source terms are obtained in order to recover the NSF system in the continuum limit.These constraints allow for adjustable bulk-to-shear viscosity ratio,Prandtl number as well as a thermal energy source.The specific forms of the two source terms can be determined through proper physical considerations and numerical implementation requirements.By employing the truncated Hermite expansion,one design for the two source terms is proposed.Moreover,three well-known mesoscopic models in the literature are shown to be compatible with these five constraints.In addition,the consistent implementation of boundary conditions is also explored by using the Chapman-Enskog expansion at the NSF order.Finally,based on the higher-order Chapman-Enskog expansion of the distribution functions,we derive the complete analytical expressions for the viscous stress tensor and the heat flux.Some underlying physics can be further explored using the DNS simulation data based on the proposed model.展开更多
基金supported by the National Natural Science Foundation of China(grant No.41572194)the Institute of Geology,China Earthquake Administration(grant No.IGCEA1604)the National Key Basic Research Program of China(grant No.2013CB733205)
文摘Objective The 2014 Ludian M_w6.1 earthquake in Yunnan occurred in a mountainous area with complex tectonics and topography,which caused serious damage as well as co-seismic landslides of an unusual large scale.Because the suspected seismogenic faults on the surface,distribution of aftershocks and focal mechanism
基金supported by the National Key R&D Program of China(2017YFD0600600).
文摘This study evaluates the structure and regeneration status of woody species in the Munessa Forest,a dry Afromontane forest in southern Ethiopia.Vegetation data were collected using a systematic sampling method.Density and distribution of seedlings,saplings and mature trees were assessed along an altitudinal gradient using quadrats of different sizes.The number of individuals,frequencies,heights and DBH of species>1 m and DBH>2.5 cm were recorded in altitudinal bands of 100 m.Analysis of the vegetation structure shows that the density of woody species decreases as DBH and height class increases.Basal area of stems with DBH>2.5 cm was 53.4 m^(2)ha^(−1).Population structure and regeneration patterns indicate a significant degradation of the forest due to anthropogenic disturbances.Regeneration was better for less valuable woody species than for species with economic and ecological value.This suggests a discontinuous recruitment of these species due to selective cutting of middle and higher diameter classes.Therefore,enrichment planting of high value,endangered species is necessary to maintain them as part of this forest.There is a need to develop and implement an effective forest management plan for sustainable use of these forest resources.
文摘In recent years,deep neural networks have become a fascinating and influential research subject,and they play a critical role in video processing and analytics.Since,video analytics are predominantly hardware centric,exploration of implementing the deep neural networks in the hardware needs its brighter light of research.However,the computational complexity and resource constraints of deep neural networks are increasing exponentially by time.Convolutional neural networks are one of the most popular deep learning architecture especially for image classification and video analytics.But these algorithms need an efficient implement strategy for incorporating more real time computations in terms of handling the videos in the hardware.Field programmable Gate arrays(FPGA)is thought to be more advantageous in implementing the convolutional neural networks when compared to Graphics Processing Unit(GPU)in terms of energy efficient and low computational complexity.But still,an intelligent architecture is required for implementing the CNN in FPGA for processing the videos.This paper introduces a modern high-performance,energy-efficient Bat Pruned Ensembled Convolutional networks(BPEC-CNN)for processing the video in the hardware.The system integrates the Bat Evolutionary Pruned layers for CNN and implements the new shared Distributed Filtering Structures(DFS)for handing the filter layers in CNN with pipelined data-path in FPGA.In addition,the proposed system adopts the hardware-software co-design methodology for an energy efficiency and less computational complexity.The extensive experimentations are carried out using CASIA video datasets with ARTIX-7 FPGA boards(number)and various algorithms centric parameters such as accuracy,sensitivity,specificity and architecture centric parameters such as the power,area and throughput are analyzed.These results are then compared with the existing pruned CNN architectures such as CNN-Prunner in which the proposed architecture has been shown 25%better performance than the existing architectures.
基金supported by National Key R&D Program of China(No.2018YFA0703800)Science Fund for Creative Research Group of the National Natural Science Foundation of China(No.61621002)。
文摘In this paper,the event-triggered consensus control problem for nonlinear uncertain multi-agent systems subject to unknown parameters and external disturbances is considered.The dynamics of subsystems are second-order with similar structures,and the nodes are connected by undirected graphs.The event-triggered mechanisms are not only utilized in the transmission of information from the controllers to the actuators,and from the sensors to the controllers within each agent,but also in the communication between agents.Based on the adaptive backstepping method,extra estimators are introduced to handle the unknown parameters,and the measurement errors that occur during the event-triggered communication are well handled by designing compensating terms for the control signals.The presented distributed event-triggered adaptive control laws can guarantee the boundness of the consensus tracking errors and the Zeno behavior is avoided.Meanwhile,the update frequency of the controllers and the load of communication burden are vastly reduced.The obtained control protocol is further applied to a multi-input multi-output second-order nonlinear multi-agent system,and the simulation results show the effectiveness and advantages of our proposed method.
基金the Aviation Science Foundation of China(No.20151067003)。
文摘In order to improve the accuracy of damage region division and eliminate the interference of damage adjacent region,the airframe damage region division method based on the structure tensor dynamic operator is proposed in this paper.The structure tensor feature space is established to represent the local features of damage images.It makes different damage images have the same feature distribution,and transform varied damage region division into consistent process of feature space division.On this basis,the structure tensor dynamic operator generation method is designed.It integrates with bacteria foraging optimization algorithm improved by defining double fitness function and chemotaxis rules,in order to calculate the parameters of dynamic operator generation method and realize the structure tensor feature space division.And then the airframe damage region division is realized.The experimental results on different airframe structure damage images show that compared with traditional threshold division method,the proposed method can improve the division quality.The interference of damage adjacent region is eliminated.The information loss caused by over-segmentation is avoided.And it is efficient in operation,and consistent in process.It also has the applicability to different types of structural damage.
基金supported by the U.S.National Science Foundation(CNS-1513031,CBET-1706130)the National Natural Science Foundation of China(91852205,91741101&11961131006)+1 种基金the National Numerical Wind Tunnel program,Guangdong Provincial Key Laboratory of Turbulence Research and Applications(2019B21203001)Shenzhen Science&Technology Program(Grant No.KQTD20180411143441009).
文摘In this paper,based on simplified Boltzmann equation,we explore the inverse-design of mesoscopic models for compressible flow using the Chapman-Enskog analysis.Starting from the single-relaxation-time Boltzmann equation with an additional source term,two model Boltzmann equations for two reduced distribution functions are obtained,each then also having an additional undetermined source term.Under this general framework and using Navier-Stokes-Fourier(NSF)equations as constraints,the structures of the distribution functions are obtained by the leading-order Chapman-Enskog analysis.Next,five basic constraints for the design of the two source terms are obtained in order to recover the NSF system in the continuum limit.These constraints allow for adjustable bulk-to-shear viscosity ratio,Prandtl number as well as a thermal energy source.The specific forms of the two source terms can be determined through proper physical considerations and numerical implementation requirements.By employing the truncated Hermite expansion,one design for the two source terms is proposed.Moreover,three well-known mesoscopic models in the literature are shown to be compatible with these five constraints.In addition,the consistent implementation of boundary conditions is also explored by using the Chapman-Enskog expansion at the NSF order.Finally,based on the higher-order Chapman-Enskog expansion of the distribution functions,we derive the complete analytical expressions for the viscous stress tensor and the heat flux.Some underlying physics can be further explored using the DNS simulation data based on the proposed model.
