In order to reduce the accident rate of consumer-grade unmanned aerial vehicles(UAVs)in daily use scenarios,the accident causes are analyzed based on the accident cases of consumer-grade UAVs.By extracting accident ca...In order to reduce the accident rate of consumer-grade unmanned aerial vehicles(UAVs)in daily use scenarios,the accident causes are analyzed based on the accident cases of consumer-grade UAVs.By extracting accident causing factors based on the Grounded theory,the relationship between these factors is analyzed.The Bayesian network for consumer-grade UAV accidents is constructed.With the Grounded theory-Bayesian network,the probability of four types of accidents is inferred:fall,air collision,disappearance,and personal injury.With the posterior probability of each factor being reversely reasoned,the causal chain with the maximum probability of each accident is obtained.After the sensitivity of each factor is analyzed,the key nodes in the network accordingly are inferred.Then the causing factors of consumer-grade UAV accidents are analyzed.The results show that the probability of fall accident is the highest,the fall accident is associated with the probabilistic maximum causal chain of personal injury,and the sensitivity analysis results of each type of accident as the result node are inconsistent.展开更多
Electroencephalogram(EEG)is a method of capturing the electrophy-siological signal of the brain.An EEG headset is a wearable device that records electrophysiological data from the brain.This paper presents the design ...Electroencephalogram(EEG)is a method of capturing the electrophy-siological signal of the brain.An EEG headset is a wearable device that records electrophysiological data from the brain.This paper presents the design and fab-rication of a customized low-cost Electroencephalogram(EEG)headset based on the open-source OpenBCI Ultracortex Mark IV system.The electrode placement locations are modified under a 10–20 standard system.The fabricated headset is then compared to commercially available headsets based on the following para-meters:affordability,accessibility,noise,signal quality,and cost.First,the data is recorded from 20 subjects who used the EEG Headset,and signals were recorded.Secondly,the participants marked the accuracy,set up time,participant comfort,and participant perceived ease of set-up on a scale of 1 to 7(7 being excellent).Thirdly,the self-designed EEG headband is used by 5 participants for slide changing.The raw EEG signal is decomposed into a series of band sig-nals using discrete wavelet transform(DWT).Lastly,thesefindings have been compared to previously reported studies.We concluded that when used for slide-changing control,our self-designed EEG headband had an accuracy of 82.0 percent.We also concluded from the results that our headset performed well on the cost-effectiveness scale,had a reduced setup time of 2±0.5 min(the short-est among all being compared),and demonstrated greater ease of use.展开更多
基金supported by the Fun⁃damental Research Funds for the Central Universities(No.3122022103).
文摘In order to reduce the accident rate of consumer-grade unmanned aerial vehicles(UAVs)in daily use scenarios,the accident causes are analyzed based on the accident cases of consumer-grade UAVs.By extracting accident causing factors based on the Grounded theory,the relationship between these factors is analyzed.The Bayesian network for consumer-grade UAV accidents is constructed.With the Grounded theory-Bayesian network,the probability of four types of accidents is inferred:fall,air collision,disappearance,and personal injury.With the posterior probability of each factor being reversely reasoned,the causal chain with the maximum probability of each accident is obtained.After the sensitivity of each factor is analyzed,the key nodes in the network accordingly are inferred.Then the causing factors of consumer-grade UAV accidents are analyzed.The results show that the probability of fall accident is the highest,the fall accident is associated with the probabilistic maximum causal chain of personal injury,and the sensitivity analysis results of each type of accident as the result node are inconsistent.
基金funded this work(DSR),King Abdulaziz University,Jeddah,Saudi Arabia,under grant no.(RG-18-130-43).
文摘Electroencephalogram(EEG)is a method of capturing the electrophy-siological signal of the brain.An EEG headset is a wearable device that records electrophysiological data from the brain.This paper presents the design and fab-rication of a customized low-cost Electroencephalogram(EEG)headset based on the open-source OpenBCI Ultracortex Mark IV system.The electrode placement locations are modified under a 10–20 standard system.The fabricated headset is then compared to commercially available headsets based on the following para-meters:affordability,accessibility,noise,signal quality,and cost.First,the data is recorded from 20 subjects who used the EEG Headset,and signals were recorded.Secondly,the participants marked the accuracy,set up time,participant comfort,and participant perceived ease of set-up on a scale of 1 to 7(7 being excellent).Thirdly,the self-designed EEG headband is used by 5 participants for slide changing.The raw EEG signal is decomposed into a series of band sig-nals using discrete wavelet transform(DWT).Lastly,thesefindings have been compared to previously reported studies.We concluded that when used for slide-changing control,our self-designed EEG headband had an accuracy of 82.0 percent.We also concluded from the results that our headset performed well on the cost-effectiveness scale,had a reduced setup time of 2±0.5 min(the short-est among all being compared),and demonstrated greater ease of use.
