To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior in...To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior information with other sensor information in the form of constraints.Firstly,the train precise track constraint method of the train is proposed,and the plane position constraint and train motion state constraints are analysed.A model for combining prior information with constraints is established.Then an adaptive H∞filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor.Finally,the positioning effect of the proposed algorithm is simulated and analysed under the conditions of a straight track and a curved track.The results show that the positioning accuracy of the algorithm with constrained filtering is significantly better than that of the algorithm without constrained filtering and that the algorithm with constrained filtering can achieve better performance when combined with track and condition information,which can significantly reduce the train positioning error.The effectiveness of the proposed algorithm is verified.展开更多
Background:A sudden outbreak of the coronavirus disease 2019(COVID-19)started in December 2019 in Wuhan,China.Up-to-date,there have been limited studies examining the anxiety status of Chinese individuals in the early...Background:A sudden outbreak of the coronavirus disease 2019(COVID-19)started in December 2019 in Wuhan,China.Up-to-date,there have been limited studies examining the anxiety status of Chinese individuals in the early phase of the pandemic period(January 30,2020–February 15,2020).This survey aimed to compare the level of anxiety of the medical staff with that of the public and to provide a theoretical basis for developing an effective psychological intervention.Method:Questionnaires were sent on the Internet(http://www.wjx.cn)during this period.The anxiety levels of Chinese people were investigated using the Self-Rating Anxiety Scale(SAS),and the demographic data were collected simultaneously.Results:A total of 1110 participants were enrolled in this study,with an effective response rate of 100%.A total of 482 respondents were medical staff(43.4%),while 628 were members of the general public(56.6%).The medical staff itself had a higher SAS score than the general public(48.36±13.40 vs.45.74±11.79,P<0.01),while the medical staff in Wuhan were more anxious than the public in Wuhan with a higher SAS score(54.17±14.08 vs.48.53±11.92,P<0.01).Conclusion:The COVID-19 pandemic has had a significant impact on the anxiety levels of the medical staff and the public,with the medical personnel showing a higher anxiety level than the public,especially female medical staff in Wuhan.Therefore,urgent intervention programs to reduce anxiety should be implemented.展开更多
基金the National Natural Science Fund of China(61471080)Training Plan for Young Backbone Teachers in Colleges and Universities of Henan Province(2018GGJS171).
文摘To solve the problem of data fusion for prior information such as track information and train status in train positioning,an adaptive H∞filtering algorithm with combination constraint is proposed,which fuses prior information with other sensor information in the form of constraints.Firstly,the train precise track constraint method of the train is proposed,and the plane position constraint and train motion state constraints are analysed.A model for combining prior information with constraints is established.Then an adaptive H∞filter with combination constraints is derived based on the adaptive adjustment method of the robustness factor.Finally,the positioning effect of the proposed algorithm is simulated and analysed under the conditions of a straight track and a curved track.The results show that the positioning accuracy of the algorithm with constrained filtering is significantly better than that of the algorithm without constrained filtering and that the algorithm with constrained filtering can achieve better performance when combined with track and condition information,which can significantly reduce the train positioning error.The effectiveness of the proposed algorithm is verified.
基金supported by the National Natural Science Foundation of China(41930323,42101147,and 41988101)the Second Tibetan Plateau Scientific Expedition and Research Program(2019QZKK0601)。
文摘Background:A sudden outbreak of the coronavirus disease 2019(COVID-19)started in December 2019 in Wuhan,China.Up-to-date,there have been limited studies examining the anxiety status of Chinese individuals in the early phase of the pandemic period(January 30,2020–February 15,2020).This survey aimed to compare the level of anxiety of the medical staff with that of the public and to provide a theoretical basis for developing an effective psychological intervention.Method:Questionnaires were sent on the Internet(http://www.wjx.cn)during this period.The anxiety levels of Chinese people were investigated using the Self-Rating Anxiety Scale(SAS),and the demographic data were collected simultaneously.Results:A total of 1110 participants were enrolled in this study,with an effective response rate of 100%.A total of 482 respondents were medical staff(43.4%),while 628 were members of the general public(56.6%).The medical staff itself had a higher SAS score than the general public(48.36±13.40 vs.45.74±11.79,P<0.01),while the medical staff in Wuhan were more anxious than the public in Wuhan with a higher SAS score(54.17±14.08 vs.48.53±11.92,P<0.01).Conclusion:The COVID-19 pandemic has had a significant impact on the anxiety levels of the medical staff and the public,with the medical personnel showing a higher anxiety level than the public,especially female medical staff in Wuhan.Therefore,urgent intervention programs to reduce anxiety should be implemented.
