Optical Tweezers-Assisted Cross-Correlation Analysis for a Non-intrusive Fluid Temperature Measurement in Microdomains

2012 ◽  
Vol 51 (6R) ◽  
pp. 067002 ◽  
Author(s):  
Chih-Ming Cheng ◽  
Ming-Chih Chang ◽  
Yu-Fen Chang ◽  
Wei-Ting Wang ◽  
Chien-Ting Hsu ◽  
...  
2012 ◽  
Vol 51 ◽  
pp. 067002
Author(s):  
Chih-Ming Cheng ◽  
Ming-Chih Chang ◽  
Yu-Fen Chang ◽  
Wei-Ting Wang ◽  
Chien-Ting Hsu ◽  
...  

2002 ◽  
Vol 13 (7) ◽  
pp. 1072-1078 ◽  
Author(s):  
V Hohreiter ◽  
S T Wereley ◽  
M G Olsen ◽  
J N Chung

2019 ◽  
Vol 11 (1) ◽  
pp. 01025-1-01025-5 ◽  
Author(s):  
N. A. Borodulya ◽  
◽  
R. O. Rezaev ◽  
S. G. Chistyakov ◽  
E. I. Smirnova ◽  
...  

Sensors ◽  
2018 ◽  
Vol 18 (5) ◽  
pp. 1571 ◽  
Author(s):  
Jhonatan Camacho Navarro ◽  
Magda Ruiz ◽  
Rodolfo Villamizar ◽  
Luis Mujica ◽  
Jabid Quiroga

2010 ◽  
Vol 09 (02) ◽  
pp. 203-217 ◽  
Author(s):  
XIAOJUN ZHAO ◽  
PENGJIAN SHANG ◽  
YULEI PANG

This paper reports the statistics of extreme values and positions of extreme events in Chinese stock markets. An extreme event is defined as the event exceeding a certain threshold of normalized logarithmic return. Extreme values follow a piecewise function or a power law distribution determined by the threshold due to a crossover. Extreme positions are studied by return intervals of extreme events, and it is found that return intervals yield a stretched exponential function. According to correlation analysis, extreme values and return intervals are weakly correlated and the correlation decreases with increasing threshold. No long-term cross-correlation exists by using the detrended cross-correlation analysis (DCCA) method. We successfully introduce a modification specific to the correlation and derive the joint cumulative distribution of extreme values and return intervals at 95% confidence level.


2021 ◽  
Vol 27 (S1) ◽  
pp. 1540-1541
Author(s):  
Tristan O'Neill ◽  
B. C. Regan ◽  
Matthew Mecklenburg

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