Riser has the advantage of high gas-solids contact efficiency,high gas/solids flux and so on.But there is relatively significant gas and solids backmixing.On the ether hand,downer has the great advantage of uniform ga...Riser has the advantage of high gas-solids contact efficiency,high gas/solids flux and so on.But there is relatively significant gas and solids backmixing.On the ether hand,downer has the great advantage of uniform gas and solids residence time, but the entrance structure has great influence on its performance and the solid concentration is much lower than that in riser.A new type of Riser-Downer-Coupling Circulating Fluidized Bed (RDCCFB) is devised in this research, which is a close combination of riser and downer.This new type of CFB takes advantage of both riser and downer.Phosphor particles were used as tracers to study the solid mixing behavior in a cold-model RDCCFB.The results show that the overall Peclet Number is greater than that in a single riser.And the average residence time and the residence time distribution of the particles can be changed according to the requirement.These characteristics make this coupling reactor attractive in many areas.展开更多
Crowd behaviors analysis is the‘state of art’research topic in the field of computer vision which provides applications in video surveillance to crowd safety,event detection,security,etc.Literature presents some of ...Crowd behaviors analysis is the‘state of art’research topic in the field of computer vision which provides applications in video surveillance to crowd safety,event detection,security,etc.Literature presents some of the works related to crowd behavior detection and analysis.In crowd behavior detection,varying density of crowds and motion patterns appears to be complex occlusions for the researchers.This work presents a novel crowd behavior detection system to improve these restrictions.The proposed crowd behavior detection system is developed using hybrid tracking model and integrated features enabled neural network.The object movement and activity in the proposed crowded behavior detection system is assessed using proposed GSLM-based neural network.GSLM based neural network is developed by integrating the gravitational search algorithm with LM algorithm of the neural network to increase the learning process of the network.The performance of the proposed crowd behavior detection system is validated over five different videos and analyzed using accuracy.The experimentation results in the crowd behavior detection with a maximum accuracy of 93%which proves the efficacy of the proposed system in video surveillance with security concerns.展开更多
文摘Riser has the advantage of high gas-solids contact efficiency,high gas/solids flux and so on.But there is relatively significant gas and solids backmixing.On the ether hand,downer has the great advantage of uniform gas and solids residence time, but the entrance structure has great influence on its performance and the solid concentration is much lower than that in riser.A new type of Riser-Downer-Coupling Circulating Fluidized Bed (RDCCFB) is devised in this research, which is a close combination of riser and downer.This new type of CFB takes advantage of both riser and downer.Phosphor particles were used as tracers to study the solid mixing behavior in a cold-model RDCCFB.The results show that the overall Peclet Number is greater than that in a single riser.And the average residence time and the residence time distribution of the particles can be changed according to the requirement.These characteristics make this coupling reactor attractive in many areas.
文摘Crowd behaviors analysis is the‘state of art’research topic in the field of computer vision which provides applications in video surveillance to crowd safety,event detection,security,etc.Literature presents some of the works related to crowd behavior detection and analysis.In crowd behavior detection,varying density of crowds and motion patterns appears to be complex occlusions for the researchers.This work presents a novel crowd behavior detection system to improve these restrictions.The proposed crowd behavior detection system is developed using hybrid tracking model and integrated features enabled neural network.The object movement and activity in the proposed crowded behavior detection system is assessed using proposed GSLM-based neural network.GSLM based neural network is developed by integrating the gravitational search algorithm with LM algorithm of the neural network to increase the learning process of the network.The performance of the proposed crowd behavior detection system is validated over five different videos and analyzed using accuracy.The experimentation results in the crowd behavior detection with a maximum accuracy of 93%which proves the efficacy of the proposed system in video surveillance with security concerns.
