Seismic Monitoring in Gujarat, India, during 2020 Coronavirus Lockdown and Lessons Learned

2021 ◽  
Vol 92 (2A) ◽  
pp. 849-858 ◽  
Author(s):  
Santosh Kumar ◽  
R. Chaitanya Kumar ◽  
Ketan Singha Roy ◽  
Sumer Chopra
Keyword(s):  
High Frequency ◽  
Background Noise ◽  
Network Reliability ◽  
Signal To Noise Ratio ◽  
Lessons Learned ◽  
Quaternary Sediments ◽  
Positive Aspect ◽  
Seismicity Monitoring ◽  
Using Data ◽  
Seismic Background

Abstract The Gujarat region, situated in the westernmost part of India, experienced a deadly intraplate 2001 Mw 7.6 Bhuj earthquake. In the aftermath of the disaster, the Institute of Seismological Research established the Gujarat (India) seismic network in 2006. The network is being operated in online and offline modes, whereas, seismicity monitoring is being done in near-real-time, using data received from the online seismic stations. The Coronavirus disease-19 lockdown provided an opportunity to assess the network reliability in a difficult and challenging scenario. The positive aspect of the lockdown is reflected in signal-to-noise ratio, which improved significantly at all the sites during the lockdown, with more prominent being at sites located on top of the Quaternary sediments due to the absence of high-frequency anthropogenic noise. A sharp fall in the seismic background noise is noticed at most of the stations during the lockdown period, with respect to the prelockdown period. We used the lockdown data to identify other natural sources of noise, besides anthropogenic. The lockdown helped in solving the enigma of seismicity in certain pockets, which turned out to be related to quarry blasts.

High-frequency analysis of seismic background noise as a function of wind speed and shallow depth

1996 ◽  
Vol 86 (5) ◽  
pp. 1507-1515 ◽  
Author(s):  
Mitchell M. Withers ◽  
Richard C. Aster ◽  
Christopher J. Young ◽  
Eric P. Chael
Keyword(s):  
Wind Speed ◽  
High Frequency ◽  
Background Noise ◽  
Signal To Noise Ratio ◽  
Shallow Depth ◽  
High Frequency Signal ◽  
Wind Speeds ◽  
Noise Characteristics ◽  
Cultural Noise ◽  
Seismic Background

Abstract We used a deep (1500 m) cased borehole near the town of Datil in west-central New Mexico to study high-frequency (>1 Hz) seismic noise characteristics. The remote site had very low levels of cultural noise, but strong winds (winter and spring) made the site an excellent candidate to study the effects of wind noise on seismograms. Along with a three-component set of surface sensors (Teledyne Geotech GS-13), a vertical borehole seismometer (GS-28) was deployed at a variety of depths (5, 43, and 85 m) to investigate signal and noise variations. Wind speed was measured with an anemometer. Event-triggered and time-triggered data streams were recorded on a RefTek 72-02 data acquisition system located at the site. Our data show little cultural noise and a strong correlation between wind speed and seismic background noise. The minimum wind speed at which the seismic background noise appears to be influenced varies with depth: 3 m/sec at the surface, 3.5 m/sec at 43 m in depth, and 4 m/sec at 85 m in depth. For wind speed below 3 to 4 m/sec, we observe omni-directional background noise that is coherent at frequencies below 15 Hz. This coherence is destroyed when wind speeds exceed 3 to 4 m/sec. We use a test event (Md ∼ 1.6) and superimposed noise to investigate signal-to-noise ratio (SNR) improvement with sensor depth. For the low Q valley fill of the Datil borehole (DBH) site, we have found that SNR can be improved by as much as 20 to 40 dB between 23 and 55 Hz and 10 to 20 dB between 10 and 20 Hz, by deploying at a 43-m depth rather than at the surface. At the surface, there is little signal above noise in the 23- to 55-Hz frequency band for wind speeds greater than 8 m/sec. Thus, high-frequency signal information that is lost at the surface can be recorded by deploying at the relatively shallow depth of 40 m. Because we observe only minor further reductions in seismic background noise (SBN) at deeper depths, 40 m is likely to be a reasonable deployment depth for other high-frequency-monitoring sites in similar environmental and geologic conditions.

scholarly journals Territorial black-capped chickadee males respond faster to high- than to low-frequency songs in experimentally elevated noise conditions

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3257 ◽  
Author(s):  
Stefanie E. LaZerte ◽  
Hans Slabbekoorn ◽  
Ken A. Otter
Keyword(s):  
High Frequency ◽  
Background Noise ◽  
Noise Exposure ◽  
Signal To Noise Ratio ◽  
Low Frequency ◽  
Trade Offs ◽  
Dependent Signal ◽  
Noisy Conditions ◽  
Carry Over ◽  
Free Ranging

Low-frequency urban noise can interfere with avian communication through masking. Some species are able to shift the frequency of their vocalizations upwards in noisy conditions, which may reduce the effects of masking. However, results from playback studies investigating whether or not such vocal changes improve audibility in noisy conditions are not clear; the responses of free-ranging individuals to shifted signals are potentially confounded by functional trade-offs between masking-related audibility and frequency-dependent signal quality. Black-capped chickadees (Poecile atricapillus) naturally sing their songs at several different frequencies as they pitch-shift to match conspecifics during song-matching contests. They are also known to switch to higher song frequencies in response to experimental noise exposure. Each male produces both high- and low-frequency songs and absolute frequency is not a signal of aggression or dominance, making this an interesting species in which to test whether higher-frequency songs are more audible than lower-frequency songs in noisy conditions. We conducted playback studies across southern and central British Columbia, Canada, using paired song stimuli (high- vs low-frequency songs, n = 24 pairs) embedded in synthetic background noise created to match typical urban sound profiles. Over the course of each playback, the signal-to-noise ratio of the song stimuli was gradually increased by raising the amplitude of the song stimuli while maintaining background noise at a constant amplitude. We evaluated variation in how quickly and aggressively territorial males reacted to each of the paired stimuli. We found that males responded more quickly to playbacks of high- than low-frequency songs when high-frequency songs were presented first, but not when low-frequency songs were first. This difference may be explained by high-frequency songs being more audible combined with a carry-over effect resulting in slower responses to the second stimulus due to habituation. We observed no difference in overall aggression between stimuli. These results suggest that high-frequency songs may be more audible under noisy conditions.

Selecting the Optimal FM System for Children With Cochlear Implants

2008 ◽  
Vol 18 (1) ◽  
pp. 19-24
Author(s):  
Erin C. Schafer
Keyword(s):  
Speech Recognition ◽  
Cochlear Implants ◽  
Empirical Research ◽  
Background Noise ◽  
Signal To Noise Ratio ◽  
Evidence Based ◽  
Signal To Noise ◽  
Speech Processor ◽  
System Input ◽  
Optimal Type

Children who use cochlear implants experience significant difficulty hearing speech in the presence of background noise, such as in the classroom. To address these difficulties, audiologists often recommend frequency-modulated (FM) systems for children with cochlear implants. The purpose of this article is to examine current empirical research in the area of FM systems and cochlear implants. Discussion topics will include selecting the optimal type of FM receiver, benefits of binaural FM-system input, importance of DAI receiver-gain settings, and effects of speech-processor programming on speech recognition. FM systems significantly improve the signal-to-noise ratio at the child's ear through the use of three types of FM receivers: mounted speakers, desktop speakers, or direct-audio input (DAI). This discussion will aid audiologists in making evidence-based recommendations for children using cochlear implants and FM systems.

scholarly journals Novel approach to modeling high-frequency activity data to assess therapeutic effects of analgesics in chronic pain conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zekun Xu ◽  
Eric Laber ◽  
Ana-Maria Staicu ◽  
B. Duncan X. Lascelles
Keyword(s):  
High Frequency ◽  
Activity Patterns ◽  
Treatment Strategies ◽  
Therapeutic Effects ◽  
Activity Levels ◽  
Activity Data ◽  
Novel Approach ◽  
High Frequency Activity ◽  
Using Data ◽  
Chronic Pain Conditions

AbstractOsteoarthritis (OA) is a chronic condition often associated with pain, affecting approximately fourteen percent of the population, and increasing in prevalence. A globally aging population have made treating OA-associated pain as well as maintaining mobility and activity a public health priority. OA affects all mammals, and the use of spontaneous animal models is one promising approach for improving translational pain research and the development of effective treatment strategies. Accelerometers are a common tool for collecting high-frequency activity data on animals to study the effects of treatment on pain related activity patterns. There has recently been increasing interest in their use to understand treatment effects in human pain conditions. However, activity patterns vary widely across subjects; furthermore, the effects of treatment may manifest in higher or lower activity counts or in subtler ways like changes in the frequency of certain types of activities. We use a zero inflated Poisson hidden semi-Markov model to characterize activity patterns and subsequently derive estimators of the treatment effect in terms of changes in activity levels or frequency of activity type. We demonstrate the application of our model, and its advance over traditional analysis methods, using data from a naturally occurring feline OA-associated pain model.

scholarly journals Exploring the link between C IV outflow kinematics and sublimation-temperature dust in quasars

2020 ◽  
Author(s):  
Matthew J Temple ◽  
Manda Banerji ◽  
Paul C Hewett ◽  
Amy L Rankine ◽  
Gordon T Richards
Keyword(s):  
Emission Line ◽  
High Frequency ◽  
Infrared Emission ◽  
Black Hole Mass ◽  
Sublimation Temperature ◽  
Continuum Source ◽  
Broad Emission ◽  
Line Region ◽  
Using Data

Abstract Using data from SDSS, UKIDSS and WISE, we investigate the properties of the high-frequency cutoff to the infrared emission in ≃5000 carefully selected luminous (Lbol ∼ 1047) type 1 quasars. The strength of ≃2 μm emission, corresponding to emission from the hottest ($T>1200\rm \, K$) dust in the sublimation zone surrounding the central continuum source, is observed to correlate with the blueshift of the C iv λ1550 emission line. We therefore find that objects with stronger signatures of nuclear outflows tend to have a larger covering fraction of sublimation-temperature dust. When controlling for the observed outflow strength, the hot dust covering fraction does not vary significantly across our sample as a function of luminosity, black hole mass or Eddington fraction. The correlation between the hot dust and the C iv line blueshifts, together with the lack of correlation between the hot dust and other parameters, therefore provides evidence of a link between the properties of the broad emission line region and the infrared-emitting dusty regions in quasars.

scholarly journals Student perceptions and lessons learned from flipping a masters level public health course | Perceptions des étudiants et leçons tirées d’une classe inversée pour un cours de maîtrise en santé environnementale et professionnelle

2015 ◽  
Vol 41 (2) ◽  
Author(s):  
Lindsay P. Galway ◽  
Barbara Berry ◽  
Timothy Takaro
Keyword(s):  
Public Health ◽  
Focus Group ◽  
Student Perceptions ◽  
Flipped Classroom ◽  
Lessons Learned ◽  
Instructional Model ◽  
Santé Environnementale ◽  
Health Course ◽  
Using Data ◽  
Groupe De Discussion

The flipped classroom instructional model has emerged as an alternative to conventional lecture-based teaching that has dominated higher education for decades. In 2013, a cohort of graduate-level public health students participated in a flipped environmental and occupational health course. We present the design, implementation, and evaluation of this course. Using data collected from a post-course survey, focus group sessions, and classroom observation, we examine student perceptions of the flipped classroom instructional model and synthesize lessons learned from flipping the classroom more broadly. Post-course survey data indicate that students had generally positive perceptions towards the flipped classroom instructional model. Four major themes emerged from the focus group data in relation to perceptions of the flipped classroom: knowledge application, content delivery, innovation, and connecting the online and in-class components. These results are promising and suggest that this approach warrants further consideration and research. Le modèle pédagogique de la classe inversée a émergé comme solution de rechange à l’enseignement traditionnel par cours magistraux qui a dominé l’éducation supérieure pendant des décennies. En 2013, une cohorte d’étudiants en santé publique aux cycles supérieurs a participé à un cours inversé sur la santé environnementale et professionnelle. Nous présentons la conception, la mise en œuvre et l’évaluation de ce cours. À l’aide de données recueillies par l’entremise d’un sondage après le cours, lors de séances de discussion en groupe et d’observation en classe, nous examinons les perceptions qu’ont les étudiants du modèle pédagogique de la classe inversée et résumons les leçons tirées qui sont pertinentes pour les cours inversés en général. Les données du sondage réalisé après le cours indiquent que les étudiants avaient des perceptions pour la plupart positives du modèle pédagogique de la classe inversée. Quatre thèmes principaux ont émergé des données du groupe de discussion relativement aux perceptions sur la classe inversée : mise en application des connaissances, diffusion du contenu, innovation et lien entre les composantes en ligne et en classe. Ces résultats sont prometteurs et suggèrent que cette approche devrait faire l’objet de plus de considération et de recherche.

Enhancement of Radar Imagery by Maximum Entropy Processing

1977 ◽  
Vol 21 (3) ◽  
pp. 241-243 ◽  
Author(s):  
Clanton E. Mancill
Keyword(s):  
Maximum Entropy ◽  
Signal To Noise Ratio ◽  
Super Resolution ◽  
Doppler Frequency ◽  
Frequency Measurement ◽  
Entropy Method ◽  
Frequency Resolution ◽  
Sampled Data ◽  
Maximum Entropy Spectrum ◽  
Using Data

The maximum entropy spectrum (MES), a sampled data power spectrum estimator, is applied to the enhancement of imagery obtained by synthetic array radar (SAR) imaging systems. MES offers better frequency resolution than conventional Fourier transform methods for certain signal classes. Since azimuth ground resolution in SAR systems is obtained by doppler frequency measurement of the radar return, the method is capable of enhancing the resolution of SAR maps. The principal signal requirement is adequate signal-to-noise ratio. The maximum entropy method has been tested using data obtained by the Hughes FLAMR radar system. The super-resolution capabilities of the method are demonstrated using FLAMR images of corner reflector arrays.

Denoising for full-waveform inversion with expanded prediction-error filters

Geophysics ◽  
2021 ◽  
pp. 1-54
Author(s):  
Milad Bader ◽  
Robert G. Clapp ◽  
Biondo Biondi
Keyword(s):  
High Frequency ◽  
Prediction Error ◽  
Signal To Noise Ratio ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Full Waveform Inversion ◽  
Frequency Data ◽  
Signal To Noise ◽  
Frequency Signal ◽  
Full Waveform

Low-frequency data below 5 Hz are essential to the convergence of full-waveform inversion towards a useful solution. They help build the velocity model low wavenumbers and reduce the risk of cycle-skipping. In marine environments, low-frequency data are characterized by a low signal-to-noise ratio and can lead to erroneous models when inverted, especially if the noise contains coherent components. Often field data are high-pass filtered before any processing step, sacrificing weak but essential signal for full-waveform inversion. We propose to denoise the low-frequency data using prediction-error filters that we estimate from a high-frequency component with a high signal-to-noise ratio. The constructed filter captures the multi-dimensional spectrum of the high-frequency signal. We expand the filter's axes in the time-space domain to compress its spectrum towards the low frequencies and wavenumbers. The expanded filter becomes a predictor of the target low-frequency signal, and we incorporate it in a minimization scheme to attenuate noise. To account for data non-stationarity while retaining the simplicity of stationary filters, we divide the data into non-overlapping patches and linearly interpolate stationary filters at each data sample. We apply our method to synthetic stationary and non-stationary data, and we show it improves the full-waveform inversion results initialized at 2.5 Hz using the Marmousi model. We also demonstrate that the denoising attenuates non-stationary shear energy recorded by the vertical component of ocean-bottom nodes.

Localized Acoustic-Event Measurement Probe: Connector Confirmation Utilizing Acoustic Signatures

2020 ◽  
Author(s):  
Brian Skoglind ◽  
Travis Roberts ◽  
Sourabh Karmakar ◽  
Cameron Turner ◽  
Laine Mears
Keyword(s):  
Background Noise ◽  
Signal To Noise Ratio ◽  
Detection Algorithm ◽  
Consumer Products ◽  
Noise Mitigation ◽  
Acoustic Event ◽  
Electrical Connection ◽  
Acoustic Signatures ◽  
Electrical Connector ◽  
Electrical Connections

Abstract Electrical connections in consumer products are typically made manually rather than through automated assembly systems due to the high variety of connector types and connector positions, and the soft flexible nature of their structures. Manual connections are prone to failure through missed or improper connections in the assembly process and can lead to unexpected downtime and expensive rework. Past approaches for registering connection success such as vision verification or Augmented Reality have shown limited ability to verify correct connection state. However, the feasibility of an acoustic-based verification system for electrical connector confirmation has not been extensively researched. One of the major problems preventing acoustic based verification in a manufacturing or assembly environment is the typically low signal to noise ratio (SNR) between the sound of an electrical connection and the diverse soundscape of the plant. In this study, a physical means of background noise mitigation and signature amplification are investigated in order to increase the SNR between the electrical connection and the plant soundscape in order to improve detection. The concept is that an increase in the SNR will lead to an improvement in the accuracy and robustness of an acoustic event detection and classification system. Digital filtering has been used in the past to deal with low SNRs, however, it runs the risk of filtering out potential important features for classification. A sensor platform is designed to filter out and reduce background noise from the plant without effecting the raw acoustic signal of the electrical connection, and an automated detection algorithm is presented. The solution is over 75% effective at detecting and classifying connections.

scholarly journals A search for transiting planets in the β Pictoris system

2018 ◽  
Vol 615 ◽  
pp. A145 ◽  
Author(s):  
M. Mol Lous ◽  
E. Weenk ◽  
M. A. Kenworthy ◽  
K. Zwintz ◽  
R. Kuschnig
Keyword(s):  
Signal To Noise Ratio ◽  
Large Fraction ◽  
Young Star ◽  
High Signal ◽  
Data Set ◽  
Transiting Planets ◽  
Using Data ◽  
Exoplanet Systems ◽  
Transit Signals

Context. Transiting exoplanets provide an opportunity for the characterization of their atmospheres, and finding the brightest star in the sky with a transiting planet enables high signal-to-noise ratio observations. The Kepler satellite has detected over 365 multiple transiting exoplanet systems, a large fraction of which have nearly coplanar orbits. If one planet is seen to transit the star, then it is likely that other planets in the system will transit the star too. The bright (V = 3.86) star β Pictoris is a nearby young star with a debris disk and gas giant exoplanet, β Pictoris b, in a multi-decade orbit around it. Both the planet’s orbit and disk are almost edge-on to our line of sight. Aims. We carry out a search for any transiting planets in the β Pictoris system with orbits of less than 30 days that are coplanar with the planet β Pictoris b. Methods. We search for a planetary transit using data from the BRITE-Constellation nanosatellite BRITE-Heweliusz, analyzing the photometry using the Box-Fitting Least Squares Algorithm (BLS). The sensitivity of the method is verified by injection of artificial planetary transit signals using the Bad-Ass Transit Model cAlculatioN (BATMAN) code. Results. No planet was found in the BRITE-Constellation data set. We rule out planets larger than 0.6 RJ for periods of less than 5 days, larger than 0.75 RJ for periods of less than 10 days, and larger than 1.05 RJ for periods of less than 20 days.

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