Computer Analysis of Total Electron Content in the Earth’s Ionosphere in Problems of Searching for and Detection of Earthquake Precursors: Current Problems and Challenges

Zolotov, O. V.; Knyazeva, M. A.; Romanovskaya, Yu. V.

doi:10.1134/s1990793119040146

Cited by 4 publications

(2 citation statements)

References 15 publications

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“…Over about 50 years of research, no consensus in the scientific community has been formed on the existence of ionospheric earthquake precursors (Rishbeth, 2006;Dautermann et al, 2007;Masci, 2012;Ovalle et al, 2013;Masci and Thomas, 2014;Zolotov et al, 2019). Dautermann et al (2007) indicated that there was no statistically significant correlation between TEC anomalies and earthquakes in Southern California during 2003Kon et al (2011) selected M≥6.0 earthquakes in Japan during 1998-2010, and found that significant positive TEC anomalies within 1000 km above the epicenter appeared within 1-5 days before the earthquakes.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, a quartile-based process is the most common method for extracting ionospheric VTEC anomalies, but different authors use different numbers of days as the lengths of the sliding windows, such as, 10 days (e.g., Zhou et al, 2009;Zhu et al, 2014), 15 days (e.g., Liu et al, 2010;Ke et al, 2016;Liu and Xu, 2017), 27 days (e.g., Xu et al, 2011;Guo et al, 2015), etc. It should be noted that the effects of different sliding windows on the ionospheric anomalies are rarely studied (Zolotov et al, 2019). To solve the above problems, this study uses GIM VTEC to carry out a statistical analysis by studying the VTEC anomalies within 1-10 days before 1522 global shallow (≤60 km) Mw≥6.0 earthquakes during 2000-2020.…”

Section: Introductionmentioning

confidence: 99%

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Statistical analysis of ionospheric vertical total electron content anomalies before global Mw≥6.0 shallow earthquakes during 2000–2020

Zhou

Yang

et al. 2023

Front. Earth Sci.

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To quantitatively investigate the relationship between earthquakes and ionospheric anomalies, this paper presents a statistical study of pre-earthquake vertical total electron content (VTEC) variations. A total of 1522 shallow (≤60 km) strong (Mw≥6.0) earthquakes in the global area during 2000-2020 are selected, and classified according to different magnitudes, latitudes and focal depths. A quartile-based process with different lengths of sliding windows, equaling 10 days, 15 days and 27 days, respectively, has been utilized to detect VTEC anomalies. The abnormal level is first defined, and then VTEC anomalies occurrence probabilities (Po) and occurrence rates (PE) within 1-10 days before 1522 earthquakes have been calculated. Besides, VTEC anomalies occurrence rates of the background days (PN) are also calculated. The results show that the significant correlation between Po and epicentral latitudinal locations could be observed within 1-10 days before earthquakes. The values of Po increase with larger magnitudes in the equatorial and low-latitude regions, but decrease with greater magnitudes in the mid- and high-latitude regions to some degree. Within 1-5 days before earthquakes, the overall trend of PE shows an increase with larger magnitudes, but the correlation between the values of PE and magnitudes is relatively weak in the southern mid- and high-latitude regions. There is no evident causality between PN and the magnitude, and most of the values of PE/PN are larger than 1, indicating that VTEC anomalies within a few days before earthquakes are probably related with the forthcoming earthquakes. Moreover, when the abnormal level exceeds 60%, different sliding window lengths have a significant impact on the values of Po and PE in the mid- and high-latitude regions. In particular, there are obvious systematic deviations between the values of Po obtained from different sliding windows in the southern mid- and high-latitude regions. However, the selection of the optimal sliding window needs to be further studied.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Statistical analysis of ionospheric vertical total electron content anomalies before global Mw≥6.0 shallow earthquakes during 2000–2020

Zhou

Yang

et al. 2023

Front. Earth Sci.

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Application of the Motion Detector and the Artificial Neural Network to Detect Vehicle Collisions: A Case Study

2019

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Motor vehicle collisions are a common cause of deaths or/and injuries. The key to lowering the death rate and damages to the health of collision accident victims is a timely arrival of Emergency Services to the accident scene. In the paper, we present and discuss the first results of the design and implementation of the vehicles collision detection system, which is based on a motion detector (MD) and Artificial Neural Network (ANN). To test MD and ANN separately, a small set of video records from traffic cameras that was not a part of a training dataset, were used. We found that while MD demonstrates reasonable performance, Haar Cascades-based pre-trained ANN requires significant improvements. Possible solutions to the aforementioned problem were proposed and discussed.

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On Definition of BigData

2019

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The term Big Data (or BigData) is widely used in scientific, educational, and business literature; however, there does not exist a single definition that can be unreservedly called “canonical”. A careless use of Big Data term to promote commercial software further emphasizes the importance of this issue. In this paper, we have performed a review of definitions of Big Data and highlighted the principal features that are attributed to Big Data. We compared all these principal features with features of databases compiled using Edgar F. Codd’s publications, and showed that they are not unique and can also be attributed to the databases. Having studied C. Lynch original work, we proposed the definition of Big Data based on the so-called conservation institution. The key point of this definition is a shift from purely technical attitude towards public institutions. Since the current use of the Big Data term may lead to a loss of meaning. There is a need not only to spread out best practices but also to eliminate or minimize the use of dubious or misleading ones.

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Computer Analysis of Total Electron Content in the Earth’s Ionosphere in Problems of Searching for and Detection of Earthquake Precursors: Current Problems and Challenges

Cited by 4 publications

References 15 publications

Statistical analysis of ionospheric vertical total electron content anomalies before global Mw≥6.0 shallow earthquakes during 2000–2020

Statistical analysis of ionospheric vertical total electron content anomalies before global Mw≥6.0 shallow earthquakes during 2000–2020

Application of the Motion Detector and the Artificial Neural Network to Detect Vehicle Collisions: A Case Study

On Definition of BigData

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