Electrical and Computer Engineering
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Browsing Electrical and Computer Engineering by Author "Das, Manohar"
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Item A Bayesian Network Based Approach Toward An Anticipatory Safety Reasoning System Autonomous Vehicle Copilot(2022-11-17) Frederick, Philip A.; Cheok, Ka C; Das, Manohar; Sengupta, Sankar; Lipták, László; Del Rose, Michael; Kania, RobertFuture ground vehicle transportation is expected to rely heavily on autonomous mobility. However, the technical progress required to ensure a completely safe autonomous vehicle for unlimited roadway use, and reliable ways to measure its safety, is behind expectations. It is believed that a research breakthrough is required to address this gap. This dissertation defines a novel method for addressing on-road autonomous vehicle safety, explicitly focusing on unsignalized intersections. A method is described to generate an anticipatory safety copilot to assist the autonomous system with motion decisions by combining data collected from global online sources and the local autonomous vehicle sensors. This anticipatory copilot reasons about the environment around the autonomous vehicle and projects the vehicle's real-time motion intent forward into a projected future version of the environment created via features from the combined local and global source information. Based on this processed information, the copilot anticipates the probabilistic success of the autonomous vehicle safely executing its intended action.Item Novel Piezoelectric Biosensor Based On Sars-Cov-2 (Covid-19) Spike Antibody For Coronavirus (Covid-19) Detection(2022-07-17) Alromithy, Fares Sulaimin; Zohdy, Mohamed A.; Auner, Gregory; Kamel-ElSayed, Suzan; Das, Manohar; Kaur, AmanpreetAt the end of December 2019, the novel coronavirus SARS_CoV_2 appeared in Wuhan, China. The World Health Organization released a global health emergency declaration based on growing case notification rates in several locations worldwide. Therefore, sensitive, specific, rapid, and deliverable diagnostic monitoring is vital for making proper decisions on treating and isolating infected patients, which will help prevent the spread of infectious diseases. The surface Acoustic Wave (SAW) biosensor provides a unique, highly sensitive electrical approach to biomolecule detection and cell growth. For this study, a novel SAW sensor is developed, and the mass sensitivities are tested to detect the SARS_CoV_2 by attaching the SARS-CoV-2 spike antibody immobilized on the sensor surface. First, a two-dimensional (2D) and a three-dimensional (3D) finite element model were developed based on a realistic device to obtain a complete characterization of the senor. Then, the AlN/Al2O3 fabricated sensor was tested and ultrasonically rinsed in preparation for silanization. After depositions of (APTMS) on the sensor by the Chemical Vapor Deposition method, the antibodies were immobilized on surfaces with the aid of a crosslinker (EDC) and (Sulfo-NHS). Finally, the SARS-CoV-2 was introduced to the sensor, and the attachment of the immobilized antibody was tested and evaluated. The sensor was tested and characterized by Raman spectroscopy and the vector Network Analyzer. Finally, our device was able to detect the virus in real-time time (within two to three minutes), confirming its high sensitivity and selectivity with regard to the SARS-CoV-2 virus.