Statistical Time Series Analysis of Crack Movements at Bayon Main Tower, Cambodia

2010 ◽  
Vol 133-134 ◽  
pp. 397-402 ◽  
Author(s):  
Shunsuke Yamada ◽  
Masato Araya ◽  
Mitsuharu Fukuda ◽  
Yoshinori Iwasaki
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
State Space ◽  
Weather Conditions ◽  
Space Representation ◽  
State Space Representation ◽  
The Past ◽  
Series Analysis ◽  
Crack Movement ◽  
Statistical Time

Based on the past monitoring data of crack movements and various weather conditions by JASA (Japanese Government Team of Safeguarding Angkor), we quantitatively examine about the effects of each weather conditions to each crack movements at Bayon main tower. Then, we applied the time series analysis using a state-space representation in the examination. In the model of the state-space representation, the factors of crack movement are assumed as temperature, wind velocity and rainfall. Those quantitative examinations of crack movements will be necessary for the planning of reinforcement and restoration at Bayon main tower.

scholarly journals Vibration-based damage detection in structures using time series analysis

2006 ◽  
Vol 220 (3) ◽  
pp. 261-272 ◽  
Author(s):  
I Trendafilova
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
State Space ◽  
The State ◽  
Statistical Characteristics ◽  
Space Representation ◽  
Test Case ◽  
State Space Representation ◽  
Series Analysis ◽  
Concrete Plate

The paper considers some possibilities to use pure time series analysis for damage diagnosis in vibrating structures. It introduces the basics of the state space methodology and discusses a number of possible methods to extract damage sensitive features from the state space representation of the attractor of a vibrating system. The discussed methods can be divided into two groups: methods that use non-linear dynamics characteristics and methods based on the statistical characteristics of the distribution of points on the attractor. Each possible damage feature is introduced separately and the advantages and shortfalls of its application are discussed. The application of the suggested techniques is demonstrated on a test case of a reinforced concrete plate.

Provincial Level Time Series Analysis : Community Mobility and COVID-19 Daily Cases in Turin, Italy (Preprint)

2021 ◽  
Author(s):  
Dayana Benny
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Cross Correlation ◽  
Provincial Level ◽  
Epidemic Curve ◽  
The Past ◽  
Series Analysis ◽  
Community Mobility ◽  
Cross Correlation Analysis ◽  
Restrictive Measures

BACKGROUND Turin, a province in the Piedmont region sees second highest new COVID-19 infections in Northern part of Italy as of March 31, 2021. During the first wave of pandemic, many restrictive measures were introduced in this province. There are many studies that conducted time series analysis of various regions in Italy, but studies that are analysing the data in province level are limited. Also, no applications of Cross Correlation Function(CCF) have been proposed to analyse relationships between COVID-19 new cases and community mobility at the provincial level in Italy. OBJECTIVE The goal of this time series analysis is to find how the restrictive measures in Turin province, Italy impacted community mobility and helped in flattening the epidemic curve during the first wave of the pandemic. METHODS A simple time series analysis is conducted in this study to analyse whether there is an association between COVID-19 daily cases and community mobility. In this study, we analysed whether the time series of the parameter that estimates the reproduction of infection in the outbreak is related to the past lags of community mobility time series by performing cross-correlation analysis. RESULTS Multiple regression is carried out in which the R0 variable is a linear function of past lags 6, 7, 8, and 1 of the community mobility variable and all coefficients are statistically significant where P = 0.024043, 2.69e-05, 0.045350 and 0.000117 respectively. The cross-correlation between data fitted from the significant past lags of community mobility and transformed basic reproduction number (R0) time-series is obtained in such a manner that the R0 of a day is related to the past lags of community mobility in Turin province. CONCLUSIONS Our analysis shows that the restrictive measures are having an impact on community mobility during the first wave of COVID-19 and it can be related to the reported secondary cases of COVID-19 in Turin province at that time. Through further improvement, this simple model could serve as preliminary research for developing right preventive methods during the early stages of an epidemic.

Provincial Level Time Series Analysis : Community Mobility and COVID-19 Daily Cases in Turin, Italy (Preprint)

2021 ◽  
Author(s):  
Dayana Benny
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Cross Correlation ◽  
Provincial Level ◽  
Epidemic Curve ◽  
The Past ◽  
Series Analysis ◽  
Community Mobility ◽  
Cross Correlation Analysis ◽  
Restrictive Measures

BACKGROUND Turin, a province in the Piedmont region sees second highest new COVID-19 infections in Northern part of Italy as of March 31, 2021. During the first wave of pandemic, many restrictive measures were introduced in this province. There are many studies that conducted time series analysis of various regions in Italy, but studies that are analysing the data in province level are limited. Also, no applications of Cross Correlation Function(CCF) have been proposed to analyse relationships between COVID-19 new cases and community mobility at the provincial level in Italy. OBJECTIVE The goal of this time series analysis is to find how the restrictive measures in Turin province, Italy impacted community mobility and helped in flattening the epidemic curve during the first wave of the pandemic. METHODS A simple time series analysis is conducted in this study to analyse whether there is an association between COVID-19 daily cases and community mobility. In this study, we analysed whether the time series of the parameter that estimates the reproduction of infection in the outbreak is related to the past lags of community mobility time series by performing cross-correlation analysis. RESULTS Multiple regression is carried out in which the R0 variable is a linear function of past lags 6, 7, 8, and 1 of the community mobility variable and all coefficients are statistically significant where P = 0.024043, 2.69e-05, 0.045350 and 0.000117 respectively. The cross-correlation between data fitted from the significant past lags of community mobility and transformed basic reproduction number (R0) time-series is obtained in such a manner that the R0 of a day is related to the past lags of community mobility in Turin province. CONCLUSIONS Our analysis shows that the restrictive measures are having an impact on community mobility during the first wave of COVID-19 and it can be related to the reported secondary cases of COVID-19 in Turin province at that time. Through further improvement, this simple model could serve as preliminary research for developing right preventive methods during the early stages of an epidemic.

Soft Computing Based Statistical Time Series Analysis, Characterization of Chaos Theory, and Theory of Fractals

2013 ◽  
pp. 30-61 ◽  
Author(s):  
Mofazzal H. Khondekar ◽  
Dipendra N. Ghosh ◽  
Koushik Ghosh ◽  
Anup Kumar Bhattacharya
Keyword(s):  
Time Series ◽  
Fractal Dimension ◽  
Time Series Analysis ◽  
Soft Computing ◽  
Chaos Theory ◽  
Filter Design ◽  
Theoretical Perspective ◽  
Series Analysis ◽  
Statistical Time

The present work is an attempt to analyze the various researches already carried out from the theoretical perspective in the field of soft computing based time series analysis, characterization of chaos, and theory of fractals. Emphasis has been given in the analysis on soft computing based study in prediction, data compression, explanatory analysis, signal processing, filter design, tracing chaotic behaviour, and estimation of fractal dimension of time series. The present work is a study as a whole revealing the effectiveness as well as the shortcomings of the various techniques adapted in this regard.

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