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Full-Text Articles in Engineering
Participation Of Electric Vehicle Aggregators In Wholesale Electricity Markets: Recent Works And Future Directions, Saeed Salimi Amiri, Fazlur Rahman Bin Karim, Pedro Cesar Lopes Gerum
Participation Of Electric Vehicle Aggregators In Wholesale Electricity Markets: Recent Works And Future Directions, Saeed Salimi Amiri, Fazlur Rahman Bin Karim, Pedro Cesar Lopes Gerum
Electrical and Computer Engineering Faculty Publications and Presentations
Electric Vehicles are key to reducing carbon emissions while bringing a revolution to the transportation sector. With the massive increase of EVs in road networks and the growing demand for charging services, the electric power grid faces enormous system reliability and operation stability challenges. Demand and supply disparities create inconsistency in the smooth delivery of electrical power. As a potential solution, EVs and their charging infrastructure can be aggregated to prevent the unwanted effects on power systems and also facilitate ancillary services to the power grid. When not need for transportation purposes, EVs can leverage their batteries for power grid …
Failure Detection In Deep Neural Networks For Medical Imaging, Sabeen Ahmed, Dimah Dera, Saud Ul Hassan, Nidhal Bouaynaya, Ghulam Rasool
Failure Detection In Deep Neural Networks For Medical Imaging, Sabeen Ahmed, Dimah Dera, Saud Ul Hassan, Nidhal Bouaynaya, Ghulam Rasool
Electrical and Computer Engineering Faculty Publications and Presentations
Deep neural networks (DNNs) have started to find their role in the modern healthcare system. DNNs are being developed for diagnosis, prognosis, treatment planning, and outcome prediction for various diseases. With the increasing number of applications of DNNs in modern healthcare, their trustworthiness and reliability are becoming increasingly important. An essential aspect of trustworthiness is detecting the performance degradation and failure of deployed DNNs in medical settings. The softmax output values produced by DNNs are not a calibrated measure of model confidence. Softmax probability numbers are generally higher than the actual model confidence. The model confidence-accuracy gap further increases for …