Success rates of rescue ICSI and analysis of embryo cleavage rates by real time video imaging

A multipath is a major error source in bridge deformation monitoring and the key to achieving millimeter-level monitoring. Although the traditional MHM (multipath hemispherical map) algorithm can be applied to multipath mitigation in real-time scenarios, accuracy needs to be further improved due to the influence of observation noise and the multipath differences between different satellites. Aiming at the insufficiency of MHM in dealing with the adverse impact of observation noise, we proposed the MHM_V model, based on Variational Mode Decomposition (VMD) and the MHM algorithm. Utilizing the VMD algorithm to extract the multipath from single-difference (SD) residuals, and according to the principle of the closest elevation and azimuth, the original observation of carrier phase in the few days following the implementation are corrected to mitigate the influence of the multipath. The MHM_V model proposed in this paper is verified and compared with the traditional MHM algorithm by using the observed data of the Forth Road Bridge with a seven day and 10 s sampling rate. The results show that the correlation coefficient of the multipath on two adjacent days was increased by about 10% after residual denoising with the VMD algorithm; the standard deviations of residual error in the L1/L2 frequencies were improved by 37.8% and 40.7%, respectively, which were better than the scores of 26.1% and 31.0% for the MHM algorithm. Taking a ratio equal to three as the threshold value, the fixed success rates of ambiguity were 88.0% without multipath mitigation and 99.4% after mitigating the multipath with MHM_V. The MHM_V algorithm can effectively improve the success rate, reliability, and convergence rate of ambiguity resolution in a bridge multipath environment and perform better than the MHM algorithm.

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Utilisation of CryoSat-2 SAR altimeter in operational ice charting

The Cryosphere ◽

10.5194/tc-10-121-2016 ◽

2016 ◽

Vol 10 (1) ◽

pp. 121-131 ◽

Cited By ~ 14

Author(s):

E. Rinne ◽

M. Similä

Keyword(s):

Synthetic Aperture Radar ◽

Real Time ◽

Training Data ◽

Synthetic Aperture ◽

First Year ◽

Success Rates ◽

Hit Rate ◽

Snow Conditions ◽

Simple Product ◽

Barents And Kara Seas

Abstract. We present methods to utilise CryoSat-2 (CS-2) synthetic aperture radar (SAR) mode data in operational ice charting. We compare CS-2 data qualitatively to SAR mosaics over the Barents and Kara seas. Furthermore, we compare the CS-2 to archived operational ice charts. We present distributions of four CS-2 waveform parameters for different ice types as presented in the ice charts. We go on to present an automatic classification method for CS-2 data which, after training with operational ice charts, is capable of determining open ocean from ice with a hit rate of >  90 %. The training data are dynamically updated every 5 days using the most recent 15 days of CS-2 data and operative ice charts. This helps the adaption of the classifier to the evolving ice/snow conditions throughout winter. The classifier is also capable of detecting three different ice classes (thin and thick first-year ice as well as old ice) with success rates good enough for the output to be usable to support operational ice charting. Finally, we present a near-real-time CS-2 product just plotting the waveform characteristics and conclude that even such a simple product is usable for some of the needs of ice charting.

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Real-time single-pixel video imaging with Fourier domain regularization

Optics Express ◽

10.1364/oe.26.020009 ◽

2018 ◽

Vol 26 (16) ◽

pp. 20009 ◽

Cited By ~ 23

Author(s):

Krzysztof M. Czajkowski ◽

Anna Pastuszczak ◽

Rafał Kotyński

Keyword(s):

Real Time ◽

Fourier Domain ◽

Video Imaging ◽

Single Pixel

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Advanced Techniques for Travel Time Data Collection

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198196155100107 ◽

1996 ◽

Vol 1551 (1) ◽

pp. 51-58 ◽

Cited By ~ 8

Author(s):

Shawn M. Turner

Keyword(s):

Data Collection ◽

Travel Time ◽

Real Time ◽

Cellular Phone ◽

License Plate ◽

Time Data ◽

Video Imaging ◽

Advantages And Disadvantages ◽

Travel Time Data ◽

Time Information

Travel time information is becoming more important for applications ranging from congestion measurement to real-time travel information. Several advanced techniques for travel time data collection are discussed, including electronic distance-measuring instruments (DMIs), computerized and video license plate matching, cellular phone tracking, automatic vehicle identification (AVI), automatic vehicle location (AVL), and video imaging. The various advanced techniques are described, the necessary equipment and procedures are outlined, the applications of each technique are discussed, and the advantages and disadvantages are summarized. Electronic DMIs are low in cost but typically limited to congestion monitoring applications. Computerized and video license plate matching are more expensive and would be most applicable for congestion measurement and monitoring. Cellular phone tracking, AVI, and AVL systems may require a significant investment in communications infrastructure, but they can provide real-time information. Video imaging is still in testing stages, with some uncertainty about costs and accuracy.

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