VLF signal phase variations due to annular solar eclipses of May 20-21, 2012 and December 26, 2019

2020 ◽  
Author(s):  
Alexey A. Korsakov ◽  
Vladimir I. Kozlov ◽  
Rustam R. Karimov
Keyword(s):  
Signal Phase ◽  
Phase Variations ◽  
Solar Eclipses

Calculated Coronal Magnetic Fields and Their Comparison with the Coronal Structures as Observed during Five Solar Eclipses

1994 ◽  
Vol 144 ◽  
pp. 559-564
Author(s):  
P. Ambrož ◽  
J. Sýkora
Keyword(s):  
Magnetic Field ◽  
Solar Cycle ◽  
Magnetic Fields ◽  
Solar Corona ◽  
Coronal Magnetic Field ◽  
Coronal Magnetic Fields ◽  
Solar Eclipses ◽  
Coronal Structures

AbstractWe were successful in observing the solar corona during five solar eclipses (1973-1991). For the eclipse days the coronal magnetic field was calculated by extrapolation from the photosphere. Comparison of the observed and calculated coronal structures is carried out and some peculiarities of this comparison, related to the different phases of the solar cycle, are presented.

Synoptic Charts of the Solar Eclipses of 1990 and 1991

1994 ◽  
Vol 144 ◽  
pp. 517-521
Author(s):  
Z. Mouradian ◽  
G. Buchholtz ◽  
G. Zlicaric
Keyword(s):  
Solar Limb ◽  
Active Regions ◽  
Solar Eclipses ◽  
Coronal Structures

AbstractThe synoptic charts of solar rotations 1831 and 1844 have been drawn up, corresponding to the eclipses of 22 July 1990 and 11 July 1991. These charts contain the active regions and the filaments, and show the position of the solar limb, at the time of the eclipse. They are for use in studying the coronal structures observed during these eclipses. The variation of these structures is given in the table. The last section of the article contains a formula for identifying the structures out of the limb.

Polynesian Petroglyphs : Reports about Solar Eclipses

1998 ◽  
Vol 107 (2) ◽  
pp. 231-232 ◽  
Author(s):  
Serge V. Rjabchikov
Keyword(s):  
Solar Eclipses

FM-CW Signal Phase Error Analysis and Compensation

2015 ◽  
Author(s):  
Y. Deng ◽  
X. Guo ◽  
R. Wang ◽  
C. Hu ◽  
T. Zeng
Keyword(s):  
Error Analysis ◽  
Phase Error ◽  
Signal Phase

Sitsen: Passive sitting posture sensing based on wireless devices

2021 ◽  
Vol 17 (7) ◽  
pp. 155014772110248
Author(s):  
Miaoyu Li ◽  
Zhuohan Jiang ◽  
Yutong Liu ◽  
Shuheng Chen ◽  
Marcin Wozniak ◽  
...  
Keyword(s):  
Radio Frequency ◽  
Radio Frequency Identification ◽  
High Performance ◽  
Learning Algorithm ◽  
Low Cost ◽  
Recognition System ◽  
Sitting Posture ◽  
Average Accuracy ◽  
Phase Variations ◽  
Window Approach

Physical health diseases caused by wrong sitting postures are becoming increasingly serious and widespread, especially for sedentary students and workers. Existing video-based approaches and sensor-based approaches can achieve high accuracy, while they have limitations like breaching privacy and relying on specific sensor devices. In this work, we propose Sitsen, a non-contact wireless-based sitting posture recognition system, just using radio frequency signals alone, which neither compromises the privacy nor requires using various specific sensors. We demonstrate that Sitsen can successfully recognize five habitual sitting postures with just one lightweight and low-cost radio frequency identification tag. The intuition is that different postures induce different phase variations. Due to the received phase readings are corrupted by the environmental noise and hardware imperfection, we employ series of signal processing schemes to obtain clean phase readings. Using the sliding window approach to extract effective features of the measured phase sequences and employing an appropriate machine learning algorithm, Sitsen can achieve robust and high performance. Extensive experiments are conducted in an office with 10 volunteers. The result shows that our system can recognize different sitting postures with an average accuracy of 97.02%.

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