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There has been a surge in research interest in learning feature representation of networks in recent times. Researchers, motivated by the recent successes of embeddings in natural language processing and advances in deep learning, have explored various means for network embedding. Network embedding is useful as it can exploit off-the-shelf machine learning algorithms for network mining tasks like...
We analyze time series from continuously recording GPS stations in Nepal spanning the pre- and post-seismic period associated to the Mw7.8 Gorkha earthquake which ruptured the Main Himalayan Thrust (MHT) fault on April 25th, 2015. The records show strong seasonal variations due to surface hydrology. After corrections for these variations, the time series covering the pre- and post-seismic periods...
We propose a reference site for the site effect study in and around the Kathmandu valley, Nepal. The used data were the accelerograms recorded at two stations, DMG and KKA, and velocity seismograms co-recorded at the PKIN station during nine shallow local and regional earthquakes of local magnitude equal to or greater than 5.0. The DMG station is located on the thick sediments of the Kathmandu valley,...
For effective spectrum utilization, cognitive radio makes use of wideband spectrum sensing receiver. Current wideband receiver architectures need wideband analog to digital converter (ADC) to sample wideband signal. As current state-of-art ADC has limitation in terms of power and sampling rate, there is a need to explore other alternative solutions. Compressive sampling (CS) data acquisition method...
This work presents a frequency domain ultra-wideband receiver architecture spanning from 500 MHz to 10.5 GHz. Proposed architecture uses Transform Domain (TD) sampling method which relaxes the ADC performance bottleneck for digitizing 500 MHz baseband signal. To achieve wideband operation a RF front end consisting of wideband LNA, VGA, baseband mixer and integrator is designed using UMC 130nm technology...
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