Wind-noise reduction for infrasonic measurements using adaptive line enhancement.

Measurement quality and analysis capability of infrasonic signals are both affected by background wind-noise. Physical filters, i.e., barriers and pipe arrays, are traditionally employed to reduce such noise. However, limited efficacy, site dependence, cost, requirement of space, non-portability, and frequent maintenance are some of their major drawbacks. This work proposes an adaptive filtering-based adaptive line enhancer (ALE) noise cancellation scheme as an alternative. Two infrasonic sensors (Chaparral Physics 50A), are adjacently deployed. One sensor is fitted with a conventional four-armed non-porous hose array (physical filter), while the ALE scheme is applied to the second sensor, sans physical filter. In high wind-noise conditions, the ALE scheme seems to behave as a lowpass filter (cutoff at 0.2 Hz), with a maximum attenuation of 26 dB at 8 Hz, while the physical filter provides significant attenuation only above 4 Hz with a maximum attenuation of 17 dB at 8 Hz. Generally, at other frequencies, the ALE scheme provides up to 20 dB superior noise attenuation as compared to the physical filter. The ALE also provides up to 6 dB gain in the signal-to-noise ratio as compared to the physical filter, due to non-attenuation of the infrasonic signal.

EVALUATION OF INDOOR/OUTDOOR GAMMA EXPOSURE RATES AND EXCESS LIFE TIME CANCER RISK IN DIFFERENT CITIES OF PAKISTAN.

This study presents a detailed measurement of indoor and outdoor terrestrial gamma radiation levels in different cities of Pakistan. The measurements covered dwellings in 27 cities, covering all provinces and region of Azad Kashmir. Most of the houses were of attached type, made of brick walls and concrete roofs. The measurements were made by a handheld radiation survey meter containing Geiger-Muller tube. The average absorbed dose rate in air was 100 ± 32 nGy h-1 for indoor and 74 ± 30 nGy h-1 for outdoor. The population-weighted mean terrestrial dose rates were 90 nGy h-1 for indoor and 78 nGyh-1 for outdoor. The ratio of indoor to outdoor absorbed dose rate was 1.5 as compared to 1.3 for the world average. The estimated average annual effective dose rate was 0.58 ± 0.18 mSv a-1 and the mean excess life time cancer risk was 2.0 × 10-3.

Automated anomalous behaviour detection in soil radon gas prior to earthquakes using computational intelligence techniques.

In this article, three computational intelligence (CI) models were developed to automatically detect anomalous behaviour in soil radon gas (222Rn) time series data. Data were obtained at a fault line and analysed using three machine learning techniques with the aim at identifying anomalies in temporal radon data prompted by seismic events. Radon concentrations were modelled with corresponding meteorological and statistical parameters. This leads to the estimation of soil radon gas without and with meteorological parameters. The comparison between computed radon concentration and actual radon concentrations was used in finding radon anomaly based upon automated system. The anomaly in radon time series data could be considered due to noise or seismic activity. Findings of study show that under meticulously characterized environments, on exclusion of noise contribution, seismic activity is responsible for anomalous behaviour seen in radon time series data.

Earthquake prediction model using support vector regressor and hybrid neural networks.

Earthquake prediction has been a challenging research area, where a future occurrence of the devastating catastrophe is predicted. In this work, sixty seismic features are computed through employing seismological concepts, such as Gutenberg-Richter law, seismic rate changes, foreshock frequency, seismic energy release, total recurrence time. Further, Maximum Relevance and Minimum Redundancy (mRMR) criteria is applied to extract the relevant features. A Support Vector Regressor (SVR) and Hybrid Neural Network (HNN) based classification system is built to obtain the earthquake predictions. HNN is a step wise combination of three different Neural Networks, supported by Enhanced Particle Swarm Optimization (EPSO), to offer weight optimization at each layer. The newly computed seismic features in combination with SVR-HNN prediction system is applied on Hindukush, Chile and Southern California regions. The obtained numerical results show improved prediction performance for all the considered regions, compared to previous prediction studies.

Monitoring and descriptive analysis of radon in relation to seismic activity of Northern Pakistan.

Earthquakes are one of the major causes of natural disasters and its forecasting is challenging task. Some precursory phenomenon exists in theory in relation to earthquakes occurrence. The emission of radioactive gas named 'radon' before the earthquakes is a potential earthquake precursory candidate. The study aims to monitor and to analyze the radon in relation to seismic activity in Northern Pakistan. For this purpose RTM-2200 has been used to monitor the changes in radon concentration from August 01, 2014 to January 31, 2015 in Northern Pakistan. Significant temporal variations has been observed in radon concentration. The bivariate analysis of radon with other variables manifests its positive relationship with air pressure and relative humidity and negative relationship with temperature. 2σ upper control limit on monthly basis are computed for detection of anomalous trends in the data. Overall increasing trend is detected in radon concentration. Five earthquakes from August 01, 2014 to January 31, 2015 have been selected from earthquake catalogue, depending upon their magnitude and distance from monitoring station and out of which radon concentration can be associated with only two earthquakes correlated with tectonic effect of radon concentration. Both of events have same magnitude 5.5 and occurred on September 13 and October 14, 2014 respectively. Very large variations have been observed in radon for the last two months of the study period, which may be occurred due to some other geological and environmental changes, but are not related to the earthquake activity.