Now showing items 1-5 of 5
Quantification of Effect of Solar Storms on TEC over U.S. sector Using Machine Learning
(Virginia Tech, 2018-06-26)
A study of large solar storms in the equinox periods of solar cycles 23 and 24 is presented to quantify their effects on the total electron content (TEC) in the ionosphere. We study the dependence of TEC over the contiguous ...
Classification of ADHD and non-ADHD Using AR Models and Machine Learning Algorithms
(Virginia Tech, 2016-12-12)
As of 2016, diagnosis of ADHD in the US is controversial. Diagnosis of ADHD is based on subjective observations, and treatment is usually done through stimulants, which can have negative side-effects in the long term. ...
Temporal Frame Difference Using Averaging Filter for Maritime Surveillance
(Virginia Tech, 2015-09-04)
Video surveillance is an active research area in Computer Vision and Machine Learning. It received a lot of attention in the last few decades. Maritime surveillance is the act of effective detection/recognition of all ...
Hoeffding-Tree-Based Learning from Data Streams and Its Application in Online Voltage Security Assessment
(Virginia Tech, 2017-09-05)
According to the proposed definition and classification of power system stability addressed by IEEE and CIGRE Task Force, voltage stability refers to the stability of maintaining the steady voltage magnitudes at all buses ...
Real-World Considerations for Deep Learning in Spectrum Sensing
(Virginia Tech, 2018-06-15)
Recently, automatic modulation classification techniques using deep neural networks on raw IQ samples have been investigated and show promise when compared to more traditional likelihood-based or feature-based techniques. ...