The results of visual event-related potential(ERP)examinations and reactiontime(RT)tests were reported in 30 elders and compared with their performanceintellegence quotient(PIQ)scores.The subjects consisted of 18 male...The results of visual event-related potential(ERP)examinations and reactiontime(RT)tests were reported in 30 elders and compared with their performanceintellegence quotient(PIQ)scores.The subjects consisted of 18 males and 12 femalesaged 50-71(mean 61.4)years old.No history of central nervous system disease wasfound.The visual stimuli were randomly presented to the subject,including three sym-bols:E as target stimulus with 0.15 probability,and H and E as nontarget stimuliwith 0.15 and 0.70 probability respectively.The recording electrodes were placed on Fzand Pz.The duration from the subject seeing the target to touching a button immediatelywas considered as reaction time(RT).It was shown that the P3 latency at Pz was longer than that at Fz and the P3amplitude at Pz was larger than that at Fz,and that the RT was longer than P3 latencywith obvious effect of distribution(P【0.05 at Fz and P】0.05 at Pz)as well .The higherthe PIQ scores,the longer the RT and the P3 latency.It is suggested that the ERPmight reflect the differences of PIQ scores,and the P3 is an objective index.We considerthat the research of ERP is of great interest in the neuropsychological and neurological sci-ences.展开更多
Through integrating advanced communication and data processing technologies into smart vehicles and roadside infrastructures,the Intelligent Transportation System(ITS)has evolved as a promising paradigm for improving ...Through integrating advanced communication and data processing technologies into smart vehicles and roadside infrastructures,the Intelligent Transportation System(ITS)has evolved as a promising paradigm for improving safety,efficiency of the transportation system.However,the strict delay requirement of the safety-related applications is still a great challenge for the ITS,especially in dense traffic environment.In this paper,we introduce the metric called Perception-Reaction Time(PRT),which reflects the time consumption of safety-related applications and is closely related to road efficiency and security.With the integration of the incorporating information-centric networking technology and the fog virtualization approach,we propose a novel fog resource scheduling mechanism to minimize the PRT.Furthermore,we adopt a deep reinforcement learning approach to design an on-line optimal resource allocation scheme.Numerical results demonstrate that our proposed schemes is able to reduce about 70%of the RPT compared with the traditional approach.展开更多
文摘The results of visual event-related potential(ERP)examinations and reactiontime(RT)tests were reported in 30 elders and compared with their performanceintellegence quotient(PIQ)scores.The subjects consisted of 18 males and 12 femalesaged 50-71(mean 61.4)years old.No history of central nervous system disease wasfound.The visual stimuli were randomly presented to the subject,including three sym-bols:E as target stimulus with 0.15 probability,and H and E as nontarget stimuliwith 0.15 and 0.70 probability respectively.The recording electrodes were placed on Fzand Pz.The duration from the subject seeing the target to touching a button immediatelywas considered as reaction time(RT).It was shown that the P3 latency at Pz was longer than that at Fz and the P3amplitude at Pz was larger than that at Fz,and that the RT was longer than P3 latencywith obvious effect of distribution(P【0.05 at Fz and P】0.05 at Pz)as well .The higherthe PIQ scores,the longer the RT and the P3 latency.It is suggested that the ERPmight reflect the differences of PIQ scores,and the P3 is an objective index.We considerthat the research of ERP is of great interest in the neuropsychological and neurological sci-ences.
基金supported by National Key R&D Program of China(No.2018YFE010267)the Science and Technology Program of Sichuan Province,China(No.2019YFH0007)+2 种基金the National Natural Science Foundation of China(No.61601083)the Xi’an Key Laboratory of Mobile Edge Computing and Security(No.201805052-ZD-3CG36)the EU H2020 Project COSAFE(MSCA-RISE-2018-824019)
文摘Through integrating advanced communication and data processing technologies into smart vehicles and roadside infrastructures,the Intelligent Transportation System(ITS)has evolved as a promising paradigm for improving safety,efficiency of the transportation system.However,the strict delay requirement of the safety-related applications is still a great challenge for the ITS,especially in dense traffic environment.In this paper,we introduce the metric called Perception-Reaction Time(PRT),which reflects the time consumption of safety-related applications and is closely related to road efficiency and security.With the integration of the incorporating information-centric networking technology and the fog virtualization approach,we propose a novel fog resource scheduling mechanism to minimize the PRT.Furthermore,we adopt a deep reinforcement learning approach to design an on-line optimal resource allocation scheme.Numerical results demonstrate that our proposed schemes is able to reduce about 70%of the RPT compared with the traditional approach.
