The development of communication technology will promote the application of Internet of Things,and Beyond 5G will become a new technology promoter.At the same time,Beyond 5G will become one of the important supports f...The development of communication technology will promote the application of Internet of Things,and Beyond 5G will become a new technology promoter.At the same time,Beyond 5G will become one of the important supports for the development of edge computing technology.This paper proposes a communication task allocation algorithm based on deep reinforcement learning for vehicle-to-pedestrian communication scenarios in edge computing.Through trial and error learning of agent,the optimal spectrum and power can be determined for transmission without global information,so as to balance the communication between vehicle-to-pedestrian and vehicle-to-infrastructure.The results show that the agent can effectively improve vehicle-to-infrastructure communication rate as well as meeting the delay constraints on the vehicle-to-pedestrian link.展开更多
Physics-informed neural networks(PINNs)are proved methods that are effective in solving some strongly nonlinear partial differential equations(PDEs),e.g.,Navier-Stokes equations,with a small amount of boundary or inte...Physics-informed neural networks(PINNs)are proved methods that are effective in solving some strongly nonlinear partial differential equations(PDEs),e.g.,Navier-Stokes equations,with a small amount of boundary or interior data.However,the feasibility of applying PINNs to the flow at moderate or high Reynolds numbers has rarely been reported.The present paper proposes an artificial viscosity(AV)-based PINN for solving the forward and inverse flow problems.Specifically,the AV used in PINNs is inspired by the entropy viscosity method developed in conventional computational fluid dynamics(CFD)to stabilize the simulation of flow at high Reynolds numbers.The newly developed PINN is used to solve the forward problem of the two-dimensional steady cavity flow at Re=1000 and the inverse problem derived from two-dimensional film boiling.The results show that the AV augmented PINN can solve both problems with good accuracy and substantially reduce the inference errors in the forward problem.展开更多
In the present scenario,computational modeling has gained much importance for the prediction of the properties of concrete.This paper depicts that how computational intelligence can be applied for the prediction of co...In the present scenario,computational modeling has gained much importance for the prediction of the properties of concrete.This paper depicts that how computational intelligence can be applied for the prediction of compressive strength of Self Compacting Concrete(SCC).Three models,namely,Extreme Learning Machine(ELM),Adaptive Neuro Fuzzy Inference System(ANFIS)and Multi Adaptive Regression Spline(MARS)have been employed in the present study for the prediction of compressive strength of self compacting concrete.The contents of cement(c),sand(s),coarse aggregate(a),fly ash(f),water/powder(w/p)ratio and superplasticizer(sp)dosage have been taken as inputs and 28 days compressive strength(fck)as output for ELM,ANFIS and MARS models.A relatively large set of data including 80 normalized data available in the literature has been taken for the study.A comparison is made between the results obtained from all the above-mentioned models and the model which provides best fit is established.The experimental results demonstrate that proposed models are robust for determination of compressive strength of self-compacting concrete.展开更多
The manner by which the particles settle in the laminar flow region is first described and the characteristics of co sedimentation of two species particles are summarized.The subsequent introduction is focused on th...The manner by which the particles settle in the laminar flow region is first described and the characteristics of co sedimentation of two species particles are summarized.The subsequent introduction is focused on the fabrication process of continuously graded composites using co sedimentation technique.Finally,the authors point out the key problem that should be solved immediately,based on their current work.展开更多
Edge computing refers to the computing paradigm in which the processing power, communication capabilities and intelligence are pushed down to the edge of the networking system like gateways and devices, where the data...Edge computing refers to the computing paradigm in which the processing power, communication capabilities and intelligence are pushed down to the edge of the networking system like gateways and devices, where the data originates. In doing so, edge computing enables an infrastructure for processing the data directly from devices with low latency, battery consumption and bandwidth cost. With opportunities for research and advanced applications such as augmented reality and wearable cognitive assistance come new challenges. This special issue reports the current re? search on various topics related to edge computing, addressing the challenges in the enabling technologies and practical implementations.展开更多
Memory-based collaborative recommender system (CRS) computes the similarity between users based on their declared ratings. However, not all ratings are of the same importance to the user. The set of ratings each user ...Memory-based collaborative recommender system (CRS) computes the similarity between users based on their declared ratings. However, not all ratings are of the same importance to the user. The set of ratings each user weights highly differs from user to user according to his mood and taste. This is usually reflected in the user’s rating scale. Accordingly, many efforts have been done to introduce weights to the similarity measures of CRSs. This paper proposes fuzzy weightings for the most common similarity measures for memory-based CRSs. Fuzzy weighting can be considered as a learning mechanism for capturing the preferences of users for ratings. Comparing with genetic algorithm learning, fuzzy weighting is fast, effective and does not require any more space. Moreover, fuzzy weightings based on the rating deviations from the user’s mean of ratings take into account the different rating scales of different users. The experimental results show that fuzzy weightings obviously improve the CRSs performance to a good extent.展开更多
Anji Ecomuseum is the kind of ＂grown-up ecomuseum＂ which differs from the traditional eco-museum in the sense of those originating in 1970s France, and transferred to China （Via Norway） inGuizhou and later in Guan...Anji Ecomuseum is the kind of ＂grown-up ecomuseum＂ which differs from the traditional eco-museum in the sense of those originating in 1970s France, and transferred to China （Via Norway） inGuizhou and later in Guangxi. Anji Ecomuseum created the ＂cognition center＂ instead of ＂informationcenter＂. Cognition center adds more values to the community, encourages the locals and audiences fromoutside to understand （not only learn from） Eco-community as a whole, emphasizing the living heritage,self-cognition and self-education. Graburn discussed this evolution was closer to the root of Eco.展开更多
基金supported by National Natural Science Foundation of China(No.61871283)the Foundation of Pre-Research on Equipment of China(No.61400010304)Major Civil-Military Integration Project in Tianjin,China(No.18ZXJMTG00170).
文摘The development of communication technology will promote the application of Internet of Things,and Beyond 5G will become a new technology promoter.At the same time,Beyond 5G will become one of the important supports for the development of edge computing technology.This paper proposes a communication task allocation algorithm based on deep reinforcement learning for vehicle-to-pedestrian communication scenarios in edge computing.Through trial and error learning of agent,the optimal spectrum and power can be determined for transmission without global information,so as to balance the communication between vehicle-to-pedestrian and vehicle-to-infrastructure.The results show that the agent can effectively improve vehicle-to-infrastructure communication rate as well as meeting the delay constraints on the vehicle-to-pedestrian link.
基金Project supported by the Fundamental Research Funds for the Central Universities of China(No.DUT21RC(3)063)the National Natural Science Foundation of China(No.51720105007)the Baidu Foundation(No.ghfund202202014542)。
文摘Physics-informed neural networks(PINNs)are proved methods that are effective in solving some strongly nonlinear partial differential equations(PDEs),e.g.,Navier-Stokes equations,with a small amount of boundary or interior data.However,the feasibility of applying PINNs to the flow at moderate or high Reynolds numbers has rarely been reported.The present paper proposes an artificial viscosity(AV)-based PINN for solving the forward and inverse flow problems.Specifically,the AV used in PINNs is inspired by the entropy viscosity method developed in conventional computational fluid dynamics(CFD)to stabilize the simulation of flow at high Reynolds numbers.The newly developed PINN is used to solve the forward problem of the two-dimensional steady cavity flow at Re=1000 and the inverse problem derived from two-dimensional film boiling.The results show that the AV augmented PINN can solve both problems with good accuracy and substantially reduce the inference errors in the forward problem.
文摘In the present scenario,computational modeling has gained much importance for the prediction of the properties of concrete.This paper depicts that how computational intelligence can be applied for the prediction of compressive strength of Self Compacting Concrete(SCC).Three models,namely,Extreme Learning Machine(ELM),Adaptive Neuro Fuzzy Inference System(ANFIS)and Multi Adaptive Regression Spline(MARS)have been employed in the present study for the prediction of compressive strength of self compacting concrete.The contents of cement(c),sand(s),coarse aggregate(a),fly ash(f),water/powder(w/p)ratio and superplasticizer(sp)dosage have been taken as inputs and 28 days compressive strength(fck)as output for ELM,ANFIS and MARS models.A relatively large set of data including 80 normalized data available in the literature has been taken for the study.A comparison is made between the results obtained from all the above-mentioned models and the model which provides best fit is established.The experimental results demonstrate that proposed models are robust for determination of compressive strength of self-compacting concrete.
基金FundedbytheNationalNaturalScienceFoundationofChi na (GrantNo.5 0 1710 4 9)
文摘The manner by which the particles settle in the laminar flow region is first described and the characteristics of co sedimentation of two species particles are summarized.The subsequent introduction is focused on the fabrication process of continuously graded composites using co sedimentation technique.Finally,the authors point out the key problem that should be solved immediately,based on their current work.
文摘Edge computing refers to the computing paradigm in which the processing power, communication capabilities and intelligence are pushed down to the edge of the networking system like gateways and devices, where the data originates. In doing so, edge computing enables an infrastructure for processing the data directly from devices with low latency, battery consumption and bandwidth cost. With opportunities for research and advanced applications such as augmented reality and wearable cognitive assistance come new challenges. This special issue reports the current re? search on various topics related to edge computing, addressing the challenges in the enabling technologies and practical implementations.
文摘Memory-based collaborative recommender system (CRS) computes the similarity between users based on their declared ratings. However, not all ratings are of the same importance to the user. The set of ratings each user weights highly differs from user to user according to his mood and taste. This is usually reflected in the user’s rating scale. Accordingly, many efforts have been done to introduce weights to the similarity measures of CRSs. This paper proposes fuzzy weightings for the most common similarity measures for memory-based CRSs. Fuzzy weighting can be considered as a learning mechanism for capturing the preferences of users for ratings. Comparing with genetic algorithm learning, fuzzy weighting is fast, effective and does not require any more space. Moreover, fuzzy weightings based on the rating deviations from the user’s mean of ratings take into account the different rating scales of different users. The experimental results show that fuzzy weightings obviously improve the CRSs performance to a good extent.
文摘Anji Ecomuseum is the kind of ＂grown-up ecomuseum＂ which differs from the traditional eco-museum in the sense of those originating in 1970s France, and transferred to China （Via Norway） inGuizhou and later in Guangxi. Anji Ecomuseum created the ＂cognition center＂ instead of ＂informationcenter＂. Cognition center adds more values to the community, encourages the locals and audiences fromoutside to understand （not only learn from） Eco-community as a whole, emphasizing the living heritage,self-cognition and self-education. Graburn discussed this evolution was closer to the root of Eco.
