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Full-Text Articles in Computer Engineering
Purdue Air Sense: A Methodology For Improving The Accuracy Of Ambient Aerosol Mass Concentration And Size Distribution Measurement With Low-Cost Optical Sensing Techniques, Rishabh Ramsisaria, Satya Sundar Patra, Brandon Emil Boor
Purdue Air Sense: A Methodology For Improving The Accuracy Of Ambient Aerosol Mass Concentration And Size Distribution Measurement With Low-Cost Optical Sensing Techniques, Rishabh Ramsisaria, Satya Sundar Patra, Brandon Emil Boor
The Summer Undergraduate Research Fellowship (SURF) Symposium
There is a global lack of a means for monitoring air pollutant levels at a local level due to expensive and bulky instrument requirements. It is important to monitor toxic gas levels, as well as particulate matter levels, in the atmosphere to study their effects on human health and to further develop city- and community-level air pollution solutions. In this study, with the means of a Raspberry Pi, low-cost Alphasense Optical Particle Counter and gas sensors, and methodical calibration techniques, we built a portable 3-D printed module powered by clean electricity generated by an on-board Voltaic solar cell that measures …
Deep Neural Network Architectures For Modulation Classification Using Principal Component Analysis, Sharan Ramjee, Shengtai Ju, Diyu Yang, Aly El Gamal
Deep Neural Network Architectures For Modulation Classification Using Principal Component Analysis, Sharan Ramjee, Shengtai Ju, Diyu Yang, Aly El Gamal
The Summer Undergraduate Research Fellowship (SURF) Symposium
In this work, we investigate the application of Principal Component Analysis to the task of wireless signal modulation recognition using deep neural network architectures. Sampling signals at the Nyquist rate, which is often very high, requires a large amount of energy and space to collect and store the samples. Moreover, the time taken to train neural networks for the task of modulation classification is large due to the large number of samples. These problems can be drastically reduced using Principal Component Analysis, which is a technique that allows us to reduce the dimensionality or number of features of the samples …