The differences between children' s L1 acquisition and adults' L2 acquisition based on a qualitative analysis are discussed and compared.Through systematic review of the relevant literature in light of the the...The differences between children' s L1 acquisition and adults' L2 acquisition based on a qualitative analysis are discussed and compared.Through systematic review of the relevant literature in light of the theories of L1 and L2 acquisition between children and adults,and analysis of the factors both influencing children s L1 and adults L2 acquisition.The findings show that two different acquisitions are distinguished in such aspects as in acquisition age,device,mode,environment and motivation,which conclude that children's L1 acquisition is effortless while adults' L2 acquisition is painful.展开更多
Neither structural linguistics nor behaviorist linguistics can explain how children acquire their mother tongue reasonably, so Noam Chomsky founds mental linguistics. According to the theory of the mental linguistics,...Neither structural linguistics nor behaviorist linguistics can explain how children acquire their mother tongue reasonably, so Noam Chomsky founds mental linguistics. According to the theory of the mental linguistics, the essence of language is interior, physical and genetic. Universal Grammar is the foundation of language development and the most essential part of human beings languages.展开更多
The ability to accurately classify fault type within traveling wave data is crucial for real-time online fault location and protection using traveling wave technology.However,the current common practice in the power i...The ability to accurately classify fault type within traveling wave data is crucial for real-time online fault location and protection using traveling wave technology.However,the current common practice in the power industry relies on manual data screening followed by offline processing,leading to several limitations such as poor timeliness,low accuracy,and high skill requirements for operators.These drawbacks restrict the application of traveling wave acquisition devices.To address these issues,this paper proposes a fault identification method for measuring the traveling wave of transmission lines based on the CSCRFAM-Transformer.Firstly,CSCRFAM is used to encode the temporal and spatial information of the measured traveling wave data.Next,pixel-level features are further aggregated through dimensional interaction.Then,an adaptive encoding hierarchy Transformer adjustment mechanism is employed to extract multi-level differentiated traveling wave high-frequency information from the aggregated features to complete fault identification.This method combines the dimensional interaction of the EMA mechanism and the self-attention mechanism of the Transformer’s sensitivity to the spatiotemporal characteristics of traveling waves.The proposed method is trained and tested using a massive dataset of 396672 measured samples from 110 kV to 220 kV transmission lines in Yunnan Power Grid.The method is used to identify,classify,test,and compare four distinct types of traveling wave data.The obtained results show that the method reduces the number of model parameters and improves the identification accuracy.The mAUC,Accuracy,Precision,and F1 values of the algorithm reach 0.969,0.969,0.965,and 0.957,respectively,indicating better detection accuracy and identification efficiency.展开更多
文摘The differences between children' s L1 acquisition and adults' L2 acquisition based on a qualitative analysis are discussed and compared.Through systematic review of the relevant literature in light of the theories of L1 and L2 acquisition between children and adults,and analysis of the factors both influencing children s L1 and adults L2 acquisition.The findings show that two different acquisitions are distinguished in such aspects as in acquisition age,device,mode,environment and motivation,which conclude that children's L1 acquisition is effortless while adults' L2 acquisition is painful.
文摘Neither structural linguistics nor behaviorist linguistics can explain how children acquire their mother tongue reasonably, so Noam Chomsky founds mental linguistics. According to the theory of the mental linguistics, the essence of language is interior, physical and genetic. Universal Grammar is the foundation of language development and the most essential part of human beings languages.
基金supported by the Key Program of National Science Foundation of China:Research on the Basic Theory and Method of Multiple Lightning Stroke Identification and Protection for Transmission Lines in Plateau Mountainous Areas(No.52337005).
文摘The ability to accurately classify fault type within traveling wave data is crucial for real-time online fault location and protection using traveling wave technology.However,the current common practice in the power industry relies on manual data screening followed by offline processing,leading to several limitations such as poor timeliness,low accuracy,and high skill requirements for operators.These drawbacks restrict the application of traveling wave acquisition devices.To address these issues,this paper proposes a fault identification method for measuring the traveling wave of transmission lines based on the CSCRFAM-Transformer.Firstly,CSCRFAM is used to encode the temporal and spatial information of the measured traveling wave data.Next,pixel-level features are further aggregated through dimensional interaction.Then,an adaptive encoding hierarchy Transformer adjustment mechanism is employed to extract multi-level differentiated traveling wave high-frequency information from the aggregated features to complete fault identification.This method combines the dimensional interaction of the EMA mechanism and the self-attention mechanism of the Transformer’s sensitivity to the spatiotemporal characteristics of traveling waves.The proposed method is trained and tested using a massive dataset of 396672 measured samples from 110 kV to 220 kV transmission lines in Yunnan Power Grid.The method is used to identify,classify,test,and compare four distinct types of traveling wave data.The obtained results show that the method reduces the number of model parameters and improves the identification accuracy.The mAUC,Accuracy,Precision,and F1 values of the algorithm reach 0.969,0.969,0.965,and 0.957,respectively,indicating better detection accuracy and identification efficiency.
