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Physical Sciences and Mathematics Commons™
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Full-Text Articles in Physical Sciences and Mathematics
Classification Of Electropherograms Using Machine Learning For Parkinson’S Disease, Soroush Dehghan
Classification Of Electropherograms Using Machine Learning For Parkinson’S Disease, Soroush Dehghan
Electronic Theses and Dissertations
Parkinson’s disease (PD) is a neurodegenerative movement disorder that progresses gradually over time. The onset of symptoms in people who are suffering from PD can vary from case to case, and it depends on the progression of the disease in each patient. The PD symptoms gradually develop and exacerbate the patient’s movements throughout time. An early diagnosis of PD could improve the outcomes of treatments and could potentially delay the progression of this disorder and that makes discovering a new diagnostic method valuable. In this study, I investigate the feasibility of using a machine learning (ML) approach to classify PD …
Wind Turbine Parameter Calibration Using Deep Learning Approaches, Rebecca Mccubbin
Wind Turbine Parameter Calibration Using Deep Learning Approaches, Rebecca Mccubbin
Electronic Theses and Dissertations
The inertia and damping coefficients are critical to understanding the workings of a wind turbine, especially when it is in a transient state. However, many manufacturers do not provide this information about their turbines, requiring people to estimate these values themselves. This research seeks to design a multilayer perceptron (MLP) that can accurately predict the inertia and damping coefficients using the power data from a turbine during a transient state. To do this, a model of a wind turbine was built in Matlab, and a simulation of a three-phase fault was used to collect realistic fault data to input into …
Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard
Longitudinal Tracking Of Physiological State With Electromyographic Signals., Robert Warren Stallard
Electronic Theses and Dissertations
Electrophysiological measurements have been used in recent history to classify instantaneous physiological configurations, e.g., hand gestures. This work investigates the feasibility of working with changes in physiological configurations over time (i.e., longitudinally) using a variety of algorithms from the machine learning domain. We demonstrate a high degree of classification accuracy for a binary classification problem derived from electromyography measurements before and after a 35-day bedrest. The problem difficulty is increased with a more dynamic experiment testing for changes in astronaut sensorimotor performance by taking electromyography and force plate measurements before, during, and after a jump from a small platform. A …
Audio-Based Productivity Forecasting Of Construction Cyclic Activities, Chris A. Sabillon
Audio-Based Productivity Forecasting Of Construction Cyclic Activities, Chris A. Sabillon
Electronic Theses and Dissertations
Due to its high cost, project managers must be able to monitor the performance of construction heavy equipment promptly. This cannot be achieved through traditional management techniques, which are based on direct observation or on estimations from historical data. Some manufacturers have started to integrate their proprietary technologies, but construction contractors are unlikely to have a fleet of entirely new and single manufacturer equipment for this to represent a solution. Third party automated approaches include the use of active sensors such as accelerometers and gyroscopes, passive technologies such as computer vision and image processing, and audio signal processing. Hitherto, most …