Rayleigh phase velocities in Southern California from beamforming short-duration ambient noise

2017 ◽  
Vol 211 (1) ◽  
pp. 450-454 ◽  
Author(s):  
Philippe Roux ◽  
Yehuda Ben-Zion
Keyword(s):  
Ambient Noise ◽  
Southern California ◽  
Adaptive Beamforming ◽  
Time Interval ◽  
Short Time Interval ◽  
Seismic Arrays ◽  
Phase Velocities ◽  
Correlation Processing ◽  
Cross Correlations ◽  
Point To Point

Abstract Beamforming of ambient noise recorded by regional arrays of seismometers is presented as an alternative imaging approach to cross-correlations between pairs of sensors. The method is used to obtain phase velocities and propagation directions of Rayleigh surface waves around the first and second microseism peaks in southern California. The derived velocity maps and propagation directions correlate with major geological structures and changes of the coastal shape in the region. The results are consistent with and complementary to those obtained using cross-correlations of long-duration data between pairs of sensors. Significant advantages of the presented high-resolution adaptive beamforming method over point-to-point noise cross-correlations are the short time interval of required data (hours to days compared to a year) and robust performance with directive (rather than omnidirectional) noise propagation. Given the recent trend toward dense and large seismic arrays at various scales, the combination of beamforming and noise-correlation processing may provide an optimal strategy for performing noise-based tomography.

scholarly journals Improving cross-correlations of ambient noise using an rms-ratio selection stacking method

2020 ◽  
Vol 222 (2) ◽  
pp. 989-1002
Author(s):  
Jinyun Xie ◽  
Yingjie Yang ◽  
Yinhe Luo
Keyword(s):  
Short Duration ◽  
Ambient Noise ◽  
Signal To Noise Ratio ◽  
Ambient Noise Tomography ◽  
Noise Sources ◽  
Time Duration ◽  
Crust And Upper Mantle ◽  
Phase Velocities ◽  
Noise Data ◽  
Cross Correlations

SUMMARY Stacking of ambient noise correlations is a crucial step to extract empirical Green's functions (EGFs) between station pairs. The traditional method is to linearly stack all short-duration cross-correlation functions (CCFs) over a long period of time to obtain final stacks. It requires at least several months of ambient noise data to obtain reliable phase velocities at periods of several to tens of seconds from CCFs. In this study, we develop a new stacking method named root-mean-square ratio selection stacking (RMSR_SS) to reduce the time duration required for the recovery of EGFs from ambient noise. In our RMSR_SS method, rather than stacking all short-duration CCFs, we first judge if each of the short-duration CCF constructively contributes to the recovery of EGFs or not. Then, we only stack those CCFs which constructively contribute to the convergence of EGFs. By applying our method to synthetic noise data, we demonstrate how our method works in enhancing the signal-to-noise ratio of CCFs by rejecting noise sources which do not positively contribute to the recovery of EGFs. Then, we apply our method to real noise data recorded in western USA. We show that reliable and accurate phase velocities can be measured from 15-d long ambient noise data using our RMSR_SS method. By applying our method to ambient noise tomography (ANT), we can reduce the deployment duration of seismic stations from several months or years to a few tens of days, significantly improving the efficiency of ANT in imaging crust and upper-mantle structures.

Arrival-angle effects on two-receiver measurements of phase velocity

2019 ◽  
Vol 220 (3) ◽  
pp. 1838-1844
Author(s):  
Fabrizio Magrini ◽  
Giovanni Diaferia ◽  
Lapo Boschi ◽  
Fabio Cammarano
Keyword(s):  
Ambient Noise ◽  
Western Mediterranean ◽  
Propagation Path ◽  
Data Set ◽  
Arrival Angle ◽  
Phase Velocities ◽  
Angle Correction ◽  
Wide Range ◽  
Cross Correlations ◽  
Teleseismic Events

SUMMARY We compile a data set of Rayleigh-wave phase velocities between pairs of stations, based on teleseismic events located on the same great circle as the two stations. We validate our observations against dispersion estimates based on ambient-noise cross correlations at the same station pairs. Discrepancies between the results of the two methods can in principle be explained by deviations in the wave propagation path between earthquake and receivers, due to lateral heterogeneity in the Earth’s structure, but the latter effect has, so far, not been precisely quantified nor corrected for. We implement an algorithm to measure the arrival angle of earthquake-generated surface waves and correct the dispersion measurements accordingly. Application to a data set from the Central-Western Mediterranean shows that the arrival-angle correction almost entirely accounts for the discrepancy in question, decreasing significantly the velocity bias for a wide range of periods.

Evaluating Uncertainties of Phase Velocity Measurements from Cross-Correlations of Ambient Seismic Noise

2020 ◽  
Vol 91 (3) ◽  
pp. 1717-1729
Author(s):  
Yinhe Luo ◽  
Yingjie Yang ◽  
Jinyun Xie ◽  
Xiaozhou Yang ◽  
Fengru Ren ◽  
...  
Keyword(s):  
Phase Velocity ◽  
Ambient Noise ◽  
Signal To Noise Ratio ◽  
The United States ◽  
Velocity Measurements ◽  
Phase Velocities ◽  
Phase Velocity Dispersion ◽  
Noise Data ◽  
Cross Correlations ◽  
Fitting In

Abstract Ambient-noise tomography (ANT) has become a well-established method to image the crust and uppermost mantle structures in the past 15 yr. Having a good estimate of uncertainties of phase velocity dispersion measurements in ANT is critical as they can guide the level of data fitting in tomography. However, to date, there are still no systemic studies to evaluate these uncertainties. In this study, we obtain cross correlations with different stacking durations from 17 yr of ambient-noise data recorded at 120 stations in the United States. We analyze the variations of signal-to-noise ratio (SNR) and phase velocities of cross correlations. We find that the uncertainties of phase velocities are affected by SNRs, interstation distances, and stacking durations. However, none of those three variables can be solely used as a proxy to estimate the uncertainties of phase velocity measurements. Based on our analysis, we graphically present empirical relations of uncertainties of phase velocity measurements as a function of SNR, interstation distance, and stacking duration. These relations can be employed as a guide to estimate phase velocity uncertainties in applications of ANT, assisting in evaluating the reliability of resulting models from ANT.

On Multiple Access of a Large Number of Machine-Type Devices in Cellular Networks

2018 ◽  
pp. 105-114
Author(s):  
O. S. Galinina ◽  
S. D. Andreev ◽  
A. M. Tyurlikov
Keyword(s):  
Success Probability ◽  
Random Access ◽  
Time Interval ◽  
Short Time Interval ◽  
Control Mechanisms ◽  
Network Access ◽  
Smart Meters ◽  
Machine To Machine ◽  
Machine To Machine Communication ◽  
Machine Communication

Introduction: Machine-to-machine communication assumes data transmission from various wireless devices and attracts attention of cellular operators. In this regard, it is crucial to recognize and control overload situations when a large number of such devices access the network over a short time interval.Purpose:Analysis of the radio network overload at the initial network entry stage in a machine-to-machine communication system.Results: A system is considered that features multiple smart meters, which may report alarms and autonomously collect energy consumption information. An analytical approach is proposed to study the operation of a large number of devices in such a system as well as model the settings of the random-access protocol in a cellular network and overload control mechanisms with respect to the access success probability, network access latency, and device power consumption. A comparison between the obtained analytical results and simulation data is also offered. 

scholarly journals Improving the Stochastic Model of Ionospheric Delays for BDS Long-Range Real-Time Kinematic Positioning

2021 ◽  
Vol 13 (14) ◽  
pp. 2739
Author(s):  
Huizhong Zhu ◽  
Jun Li ◽  
Longjiang Tang ◽  
Maorong Ge ◽  
Aigong Xu
Keyword(s):  
Real Time ◽  
Long Range ◽  
Ionospheric Delay ◽  
Time Interval ◽  
Short Time Interval ◽  
Dual Frequency ◽  
Triple Frequency ◽  
Ambiguity Fixing ◽  
Power Spectral ◽  
Observation Noise

Although ionosphere-free (IF) combination is usually employed in long-range precise positioning, in order to employ the knowledge of the spatiotemporal ionospheric delays variations and avoid the difficulty in choosing the IF combinations in case of triple-frequency data processing, using uncombined observations with proper ionospheric constraints is more beneficial. Yet, determining the appropriate power spectral density (PSD) of ionospheric delays is one of the most important issues in the uncombined processing, as the empirical methods cannot consider the actual ionosphere activities. The ionospheric delays derived from actual dual-frequency phase observations contain not only the real-time ionospheric delays variations, but also the observation noise which could be much larger than ionospheric delays changes over a very short time interval, so that the statistics of the ionospheric delays cannot be retrieved properly. Fortunately, the ionospheric delays variations and the observation noise behave in different ways, i.e., can be represented by random-walk and white noise process, respectively, so that they can be separated statistically. In this paper, we proposed an approach to determine the PSD of ionospheric delays for each satellite in real-time by denoising the ionospheric delay observations. Based on the relationship between the PSD, observation noise and the ionospheric observations, several aspects impacting the PSD calculation are investigated numerically and the optimal values are suggested. The proposed approach with the suggested optimal parameters is applied to the processing of three long-range baselines of 103 km, 175 km and 200 km with triple-frequency BDS data in both static and kinematic mode. The improvement in the first ambiguity fixing time (FAFT), the positioning accuracy and the estimated ionospheric delays are analysed and compared with that using empirical PSD. The results show that the FAFT can be shortened by at least 8% compared with using a unique empirical PSD for all satellites although it is even fine-tuned according to the actual observations and improved by 34% compared with that using PSD derived from ionospheric delay observations without denoising. Finally, the positioning performance of BDS three-frequency observations shows that the averaged FAFT is 226 s and 270 s, and the positioning accuracies after ambiguity fixing are 1 cm, 1 cm and 3 cm in the East, North and Up directions for static and 3 cm, 3 cm and 6 cm for kinematic mode, respectively.

scholarly journals Evaluation and Validation of a Joint Stress Test to Induce Activity-Related Knee Joint Discomfort — a Prospective Case-Control Study

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Christiane Schön ◽  
Claudia Reule ◽  
Katharina Knaub ◽  
Antje Micka ◽  
Manfred Wilhelm ◽  
...  
Keyword(s):  
Knee Joint ◽  
Healthy Subjects ◽  
Stress Test ◽  
Osteoarthritis Of The Knee ◽  
Time Interval ◽  
Short Time Interval ◽  
Joint Stress ◽  
Joint Health ◽  
The Impact ◽  
Health Function

Abstract Background The assessment of improvement or maintenance of joint health in healthy subjects is a great challenge. The aim of the study was the evaluation of a joint stress test to assess joint discomfort in subjects with activity-related knee joint discomfort (ArJD). Results Forty-five subjects were recruited to perform the single-leg-step-down (SLSD) test (15 subjects per group). Subjects with ArJD of the knee (age 22–62 years) were compared to healthy subjects (age 24–59 years) with no knee joint discomfort during daily life sporting activity and to subjects with mild-to-moderate osteoarthritis of the knee joint (OA, Kellgren score 2–3, age 42–64 years). The subjects performed the SLSD test with two different protocols: (I) standardization for knee joint discomfort; (II) standardization for load on the knee joint. In addition, range of motion (ROM), reach test, acute pain at rest and after a single-leg squat and knee injury, and osteoarthritis outcome score (KOOS) were assessed. In OA and ArJD subjects, knee joint discomfort could be reproducibly induced in a short time interval of less than 10 min (200 steps). In healthy subjects, no pain was recorded. A clear differentiation between study groups was observed with the SLSD test (maximal step number) as well as KOOS questionnaire, ROM, and reach test. In addition, a moderate to good intra-class correlation was shown for the investigated outcomes. Conclusions These results suggest the SLSD test is a reliable tool for the assessment of knee joint health function in ArJD and OA subjects to study the improvements in their activities. Further, this model can be used as a stress model in intervention studies to study the impact of stress on knee joint health function.

Estimation of Time-Dependent Turning Fractions at Signalized Intersections

1998 ◽  
Vol 1644 (1) ◽  
pp. 142-149 ◽  
Author(s):  
Gang-Len Chang ◽  
Xianding Tao
Keyword(s):  
Signalized Intersections ◽  
Efficient Estimation ◽  
Estimation Accuracy ◽  
Time Interval ◽  
Short Time Interval ◽  
Simulation Experiments ◽  
Proposed Model ◽  
Short Time ◽  
Estimation Of Time ◽  
Additional Constraints

An effective method for estimating time-varying turning fractions at signalized intersections is described. With the inclusion of approximate intersection delay, the proposed model can account for the impacts of signal setting on the dynamic distribution of intersection flows. To improve the estimation accuracy, the use of preestimated turning fractions from a relatively longer time interval has been proposed to serve as additional constraints for the same estimation but over a short time interval. The results of extensive simulation experiments indicated that the proposed method can yield sufficiently accurate as well as efficient estimation of dynamic turning fractions for signalized intersections.

Micro-Expression Recognition using 3D - CNN

2020 ◽  
pp. 5-13
Author(s):  
Vishal Dubey ◽  
◽  
◽  
◽  
Bhavya Takkar ◽  
...  
Keyword(s):  
Emotional Response ◽  
High Speed ◽  
Actual State ◽  
Time Interval ◽  
Short Time Interval ◽  
Expression Recognition ◽  
Specific Emotion ◽  
3D Cnn ◽  
Short Time ◽  
Micro Expression

Micro-expression comes under nonverbal communication, and for a matter of fact, it appears for minute fractions of a second. One cannot control micro-expression as it tells about our actual state emotionally, even if we try to hide or conceal our genuine emotions. As we know that micro-expressions are very rapid due to which it becomes challenging for any human being to detect it with bare eyes. This subtle-expression is spontaneous, and involuntary gives the emotional response. It happens when a person wants to conceal the specific emotion, but the brain is reacting appropriately to what that person is feeling then. Due to which the person displays their true feelings very briefly and later tries to make a false emotional response. Human emotions tend to last about 0.5 - 4.0 seconds, whereas micro-expression can last less than 1/2 of a second. On comparing micro-expression with regular facial expressions, it is found that for micro-expression, it is complicated to hide responses of a particular situation. Micro-expressions cannot be controlled because of the short time interval, but with a high-speed camera, we can capture one's expressions and replay them at a slow speed. Over the last ten years, researchers from all over the globe are researching automatic micro-expression recognition in the fields of computer science, security, psychology, and many more. The objective of this paper is to provide insight regarding micro-expression analysis using 3D CNN. A lot of datasets of micro-expression have been released in the last decade, we have performed this experiment on SMIC micro-expression dataset and compared the results after applying two different activation functions.

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