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        Exploring COVID-19 in mainland China during the lockdown of Wuhan via functional data analysis

        Li, Xing,Zhang, Panpan,Feng, Qunqiang The Korean Statistical Society 2022 Communications for statistical applications and me Vol.29 No.1

        In this paper, we analyze the time series data of the case and death counts of COVID-19 that broke out in China in December, 2019. The study period is during the lockdown of Wuhan. We exploit functional data analysis methods to analyze the collected time series data. The analysis is divided into three parts. First, the functional principal component analysis is conducted to investigate the modes of variation. Second, we carry out the functional canonical correlation analysis to explore the relationship between confirmed and death cases. Finally, we utilize a clustering method based on the Expectation-Maximization (EM) algorithm to run the cluster analysis on the counts of confirmed cases, where the number of clusters is determined via a cross-validation approach. Besides, we compare the clustering results with some migration data available to the public.

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        Bolt Loosening Localization at Flange Joints Using Wind-Induced Response for High-Rise Tower

        Baifeng Ji,Qian Xiong,Panpan Xing,Penghui Qiu,Wei-lian Qu 한국강구조학회 2021 International Journal of Steel Structures Vol.21 No.5

        Under long term wind load, the bolt looseness occurring at the joints of tower legs will reduce the wind-resistant capability, increasing the wind-induced displacement responses and aff ecting the serviceability of the high-rise steel tower. In order to detect the bolt looseness locations of the fl ange assembling joints of leg members in high-rise steel tubular tower structures, a new bolt loosening localization at fl ange joints method using wind-induced response for high-rise tower was presented in this paper. Wind-induced vertical strain response root variance of fl ange assembling joint on the tower vertical bar is defi ned as the identifi cation parameter of the bolt looseness damage. Then, the normalized wind-induced vertical strain response root variance is defi ned as the damage index of bolt loose-ness damage, thereby eliminating the impact of wind loads of diff erent magnitudes on damage identifi cation. When the damage index exceeds the threshold, it can be considered that the bolt looseness damage occurs in fl ange assembling joint, thereby to realize the damage identifi cation. The results both numerical analyses of a practical transmission tower and scaled model wind tunnel experiment of a steel tubular tower show that the proposed method is effi cient and noise immunity on the bolt looseness location detection for high-rise tower.

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