Application of principal component analysis on temporal evolution of COVID-19

The COVID-19 is one of the worst pandemics in modern history. We applied principal component analysis (PCA) to the daily time series of the COVID-19 death cases and confirmed cases for the top 25 countries from April of 2020 to February of 2021. We calculated the eigenvalues and eigenvectors of the cross-correlation matrix of the changes in daily accumulated data over monthly time windows. The largest eigenvalue describes the overall evolution dynamics of the COVID-19 and indicates that evolution was faster in April of 2020 than in any other period. By using the first two PC coefficients, we can identify the group dynamics of the COVID-19 evolution. We observed groups under critical states in the loading plot and found that American and European countries are represented by strong clusters in the loading plot. The first PC plays an important role and the correlations (C1) between the normalized logarithmic changes in deaths or confirmed cases and the first PCs may be used as indicators of different phases of the COVID-19. By varying C1 over time, we identified different phases of the COVID-19 in the analyzed countries over the target time period.

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Ionospheric Anomalies Related to the (M = 7.3), August 27, 2012, Puerto Earthquake, (M = 6.8), August 30, 2012 Jan Mayen Island Earthquake, and (M = 7.6), August 31, 2012, Philippines Earthquake: Two-Dimensional Principal Component Analysis

The Scientific World JOURNAL ◽

10.1155/2013/271513 ◽

2013 ◽

Vol 2013 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

Jyh-Woei Lin

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Component Analysis ◽

The Philippines ◽

Electron Content ◽

Two Dimensional ◽

Total Electron ◽

Duration Time ◽

Time Period ◽

A Tec

Two-dimensional principal component analysis (2DPCA) and principal component analysis (PCA) are used to examine the ionospheric total electron content (TEC) data during the time period from 00:00 on August 21 to 12: 45 on August 31 (UT), which are 10 days before the M = 7.6 Philippines earthquake at 12:47:34 on August 31, 2012 (UT) with the depth at 34.9 km. From the results by using 2DPCA, a TEC precursor of Philippines earthquake is found during the time period from 4:25 to 4:40 on August 28, 2012 (UT) with the duration time of at least 15 minutes. Another earthquake-related TEC anomaly is detectable for the time period from 04:35 to 04:40 on August 27, 2012 (UT) with the duration time of at least 5 minutes during the Puerto earthquake at 04: 37:20 on August 27, 2012 (UT) (Mw= 7.3) with the depth at 20.3 km. The precursor of the Puerto earthquake is not detectable. TEC anomaly is not to be found related to the Jan Mayen Island earthquake (Mw= 6.8) at 13:43:24 on August 30, 2012 (UT). These earthquake-related TEC anomalies are detectable by using 2DPCA rather than PCA. They are localized nearby the epicenters of the Philippines and Puerto earthquakes.

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Principal Component Analysis Method with Space and Time Windows for Damage Detection

Sensors ◽

10.3390/s19112521 ◽

2019 ◽

Vol 19 (11) ◽

pp. 2521 ◽

Cited By ~ 3

Author(s):

Ge Zhang ◽

Liqun Tang ◽

Licheng Zhou ◽

Zejia Liu ◽

Yiping Liu ◽

...

Keyword(s):

Principal Component Analysis ◽

Damage Detection ◽

Structural Damage ◽

Time Windows ◽

Principal Component ◽

Element Model ◽

Component Analysis ◽

Previous Method ◽

Beam Model ◽

Space And Time

Long-term structural health monitoring (SHM) has become an important tool to ensure the safety of infrastructures. However, determining methods to extract valuable information from large amounts of data from SHM systems for effective identification of damage still remains a major challenge. This paper provides a novel effective method for structural damage detection by introduction of space and time windows in the traditional principal component analysis (PCA) technique. Numerical results with a planar beam model demonstrate that, due to the presence of space and time windows, the proposed double-window PCA method (DWPCA) has a higher sensitivity for damage identification than the previous method moving PCA (MPCA), which combines only time windows with PCA. Further studies indicate that the developed approach, as compared to the MPCA method, has a higher resolution in localizing damage by space windows and also in quantitative evaluation of damage severity. Finally, a finite-element model of a practical bridge is used to prove that the proposed DWPCA method has greater sensitivity for damage detection than traditional methods and potential for applications in practical engineering.

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State and group dynamics of world stock market by principal component analysis

Physica A Statistical Mechanics and its Applications ◽

10.1016/j.physa.2015.12.144 ◽

2016 ◽

Vol 450 ◽

pp. 85-94 ◽

Cited By ~ 9

Author(s):

Ashadun Nobi ◽

Jae Woo Lee

Keyword(s):

Principal Component Analysis ◽

Stock Market ◽

Group Dynamics ◽

Principal Component ◽

Component Analysis

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Wavelet and principal component analysis of electromyographic activity and slow component of oxygen uptake during heavy and severe cycling exercise

Applied Physiology Nutrition and Metabolism ◽

10.1139/apnm-2019-0037 ◽

2020 ◽

Vol 45 (2) ◽

pp. 187-192

Author(s):

Liping Qi ◽

Xiao-Chi Ma ◽

Dong-Dong Zhou ◽

Shuo Guan ◽

Feng-Shan Gao ◽

...

Keyword(s):

Principal Component Analysis ◽

Oxygen Uptake ◽

Slow Component ◽

Time Windows ◽

Principal Component ◽

Component Analysis ◽

Medial Gastrocnemius ◽

Muscle Fibres ◽

Cycling Exercise ◽

Severe Exercise

The aim of the study was to investigate whether the slow component of oxygen uptake was concurrent with the recruitment of large α-motoneuron muscle fibres by using wavelet and principal component analysis (PCA) of electromyography (EMG) during heavy and severe cycling exercise. Eleven male subjects participated in the study. After establishing each subject’s maximum value of oxygen uptake through an incremental test on the cycle ergometer, the subjects performed 6-min cycling tests at heavy and severe intensity. EMG signals were collected from rectus femoris, biceps femoris long head, tibialis anterior, and medial gastrocnemius and processed by combined use of wavelet and PCA analysis. The time delays to the onset of slow component occurred significantly earlier during severe (105.22 ± 5.45 s) compared with during heavy (138.78 ± 15.09 s) exercise. ANOVA with repeated measures showed that for all muscles tested, the angle θ formed by the first and second principal components decreased significantly between time windows during heavy and severe exercise. However, significant increases of EMG mean power frequency (MPF) were found only during heavy exercise. Our results show the concurrence of the oxygen uptake slow component with the additional recruitment of muscle fibres, presumably less efficient large α-motoneuron fibres. Novelty The expected rise in MPF may be offset by muscle fatigue occurring in the later time windows of the slow component during severe exercise. The gradual shift to higher EMG frequencies throughout the slow-component phase was reflected in the progressive and significant decrease of angle θ.

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A German version of the Intermittent Claudication Questionnaire (ICQ): cultural adaptation and validation

VASA ◽

10.1024/0301-1526/a000218 ◽

2012 ◽

Vol 41 (5) ◽

pp. 333-342 ◽

Cited By ~ 3

Author(s):

Kirchberger ◽

Finger ◽

Müller-Bühl

Keyword(s):

Principal Component Analysis ◽

Intermittent Claudication ◽

Completion Time ◽

Short Form ◽

Principal Component ◽

Component Analysis ◽

German Version ◽

Average Completion Time ◽

Sf 36 ◽

Related Quality

Background: The Intermittent Claudication Questionnaire (ICQ) is a short questionnaire for the assessment of health-related quality of life (HRQOL) in patients with intermittent claudication (IC). The objective of this study was to translate the ICQ into German and to investigate the psychometric properties of the German ICQ version in patients with IC. Patients and methods: The original English version was translated using a forward-backward method. The resulting German version was reviewed by the author of the original version and an experienced clinician. Finally, it was tested for clarity with 5 German patients with IC. A sample of 81 patients were administered the German ICQ. The sample consisted of 58.0 % male patients with a median age of 71 years and a median IC duration of 36 months. Test of feasibility included completeness of questionnaires, completion time, and ratings of clarity, length and relevance. Reliability was assessed through a retest in 13 patients at 14 days, and analysis of Cronbachs alpha for internal consistency. Construct validity was investigated using principal component analysis. Concurrent validity was assessed by correlating the ICQ scores with the Short Form 36 Health Survey (SF-36) as well as clinical measures. Results: The ICQ was completely filled in by 73 subjects (90.1 %) with an average completion time of 6.3 minutes. Cronbachs alpha coefficient reached 0.75. Intra-class correlation for test-retest reliability was r = 0.88. Principal component analysis resulted in a 3 factor solution. The first factor explained 51.5 of the total variation and all items had loadings of at least 0.65 on it. The ICQ was significantly associated with the SF-36 and treadmill-walking distances whereas no association was found for resting ABPI. Conclusions: The German version of the ICQ demonstrated good feasibility, satisfactory reliability and good validity. Responsiveness should be investigated in further validation studies.

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