scholarly journals Real-Time Video Content Popularity Detection Based on Mean Change Point Analysis

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 142246-142260 ◽  
Author(s):  
Sotiris Skaperas ◽  
Lefteris Mamatas ◽  
Arsenia Chorti
Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1720
Author(s):  
Pieter Van den Berghe ◽  
Maxim Gosseries ◽  
Joeri Gerlo ◽  
Matthieu Lenoir ◽  
Marc Leman ◽  
...  

A method is presented for detecting changes in the axial peak tibial acceleration while adapting to self-discovered lower-impact running. Ten runners with high peak tibial acceleration were equipped with a wearable auditory biofeedback system. They ran on an athletic track without and with real-time auditory biofeedback at the instructed speed of 3.2 m·s−1. Because inter-subject variation may underline the importance of individualized retraining, a change-point analysis was used for each subject. The tuned change-point application detected major and subtle changes in the time series. No changes were found in the no-biofeedback condition. In the biofeedback condition, a first change in the axial peak tibial acceleration occurred on average after 309 running gait cycles (3′40″). The major change was a mean reduction of 2.45 g which occurred after 699 running gait cycles (8′04″) in this group. The time needed to achieve the major reduction varied considerably between subjects. Because of the individualized approach to gait retraining and its relatively quick response due to a strong sensorimotor coupling, we want to highlight the potential of a stand-alone biofeedback system that provides real-time, continuous, and auditory feedback in response to the axial peak tibial acceleration for lower-impact running.


Author(s):  
Aviral Kumar Tiwari ◽  
Cleiton Guollo Taufemback ◽  
Satish Kumar

Psychometrika ◽  
2015 ◽  
Vol 81 (4) ◽  
pp. 1118-1141 ◽  
Author(s):  
Can Shao ◽  
Jun Li ◽  
Ying Cheng

2018 ◽  
Vol 11 (2) ◽  
pp. 420-433 ◽  
Author(s):  
Adem Yavuz Sönmez ◽  
Semih Kale

Abstract The main purpose of this study was to estimate possible climate change effects on the annual streamflow of Filyos River (Turkey). Data for annual streamflow and climatic parameters were obtained from streamflow gauging stations on the river and Bartın, Karabük, Zonguldak meteorological observation stations. Time series analysis was performed on 46 years of annual streamflow data and 57 years of annual mean climatic data from three monitoring stations to understand the trends. Pettitt change-point analysis was applied to determine the change time and trend analysis was performed to forecast trends. To reveal the relationship between climatic parameters and streamflow, correlation tests, namely, Spearman's rho and Kendall's tau were applied. The results of Pettitt change-point analysis pointed to 2000 as the change year for streamflow. Change years for temperature and precipitation were detected as 1997 and 2000, respectively. Trend analysis results indicated decreasing trends in the streamflow and precipitation, and increasing trend in temperature. These changes were found statistically significant for streamflow (p < 0.05) and temperature (p < 0.01). Also, a statistically significant (p < 0.05) correlation was found between streamflow and precipitation. In conclusion, decreasing precipitation and increasing temperature as a result of climate change initiated a decrease in the river streamflow.


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