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Articles 1 - 7 of 7
Full-Text Articles in Engineering
Knowledge Integration In Domain-Informed Machine Learning And Multi-Scale Modeling Of Nonlinear Dynamics In Complex Systems, Phat K. Huynh
Knowledge Integration In Domain-Informed Machine Learning And Multi-Scale Modeling Of Nonlinear Dynamics In Complex Systems, Phat K. Huynh
USF Tampa Graduate Theses and Dissertations
Nonlinear dynamical systems have been extensively used to model various phenomena in the changing world around us, especially in science and engineering fields. Thanks to breakthrough advancements in sensing technologies, an increasingly high volume of multi-modal sensor data has been collected, which enables us gain better insights into complex systems dynamics and build sophisticated data-driven machine-learning-based dynamic models without having the access to the underlying governing equations. However, integrating domain-specific knowledge in machine learning algorithms remains pivotal for various reasons: it promises enhanced predictive accuracy, better model interpretability, and increased generalizability. This dissertation delves into three core research questions, each …
Knowledge Integration In Domain-Informed Machine Learning And Multi-Scale Modeling Of Nonlinear Dynamics In Complex Systems, Phat K. Huynh
Knowledge Integration In Domain-Informed Machine Learning And Multi-Scale Modeling Of Nonlinear Dynamics In Complex Systems, Phat K. Huynh
USF Tampa Graduate Theses and Dissertations
Nonlinear dynamical systems have been extensively used to model various phenomena in the changing world around us, especially in science and engineering fields. Thanks to breakthrough advancements in sensing technologies, an increasingly high volume of multi-modal sensor data has been collected, which enables us gain better insights into complex systems dynamics and build sophisticated data-driven machine-learning-based dynamic models without having the access to the underlying governing equations. However, integrating domain-specific knowledge in machine learning algorithms remains pivotal for various reasons: it promises enhanced predictive accuracy, better model interpretability, and increased generalizability. This dissertation delves into three core research questions, each …
Live Audiovisual Remote Assistance System (Laras) For Person With Visual Impairments, Zachary Frey, Nghia Vo, Varaha Maithreya, Tais Mota, Urvish Trivedi, Redwan Alqasemi, Rajiv Dubey
Live Audiovisual Remote Assistance System (Laras) For Person With Visual Impairments, Zachary Frey, Nghia Vo, Varaha Maithreya, Tais Mota, Urvish Trivedi, Redwan Alqasemi, Rajiv Dubey
36th Florida Conference on Recent Advances in Robotics
According to "The World Report on Vision" by World Health Organization (WHO) [1], there are more than 2.2 billion people who have near or distant vision Impairments, out of which 36 million people are classified as entirely blind. This report also emphasizes the importance of social and communal support in enabling individuals with vision impairments to integrate into society and reach their full potential. While performing daily activities and navigating the environment, people with visual impairments (PVIs) often require direct or synchronous assistance [2]. Consequently, there is a growing need for automated solutions to assist in this regard. However, existing …
Evaluating Foot-Drop Interventions For Multiple Sclerosis Using A Multimodal System, Laura Marie Byrnes-Blanco
Evaluating Foot-Drop Interventions For Multiple Sclerosis Using A Multimodal System, Laura Marie Byrnes-Blanco
USF Tampa Graduate Theses and Dissertations
This dissertation explores how multimodal walking impacts quantitative and qualitative aspects of gait for persons with multiple sclerosis (pwMS) experiencing foot-drop. Foot-drop can dramatically impede mobility and clinicians routinely prescribe ankle-foot-orthosis (AFO) and functional electrical stimulation (FES) devices to alleviate its impacts on daily life. However, little is known about how these devices affect pwMS while traversing environments with real-world complexity. To explore this topic, an interventional, parallel assigned study was conducted. A realistic nature pathway containing changes in floor pitch, audiovisual stimulation, and during-trial tasks (for dual-tasking) was generated in an immersive virtual reality system called CAREN: Computer Assisted …
Development And Implementation Of Telemetry Devices To Identify And Characterize Sources Of Intraocular Pressure Variability In Rats, Christina M. Nicou
Development And Implementation Of Telemetry Devices To Identify And Characterize Sources Of Intraocular Pressure Variability In Rats, Christina M. Nicou
USF Tampa Graduate Theses and Dissertations
Eye health depends partially on intraocular pressure (IOP) as abnormal levels can lead to ocular tissue damage. Glaucoma is a neurodegenerative disease that affects nearly 80 million people worldwide [1]. It is associated with elevated IOP, which can lead to irreversible blindness. Relatively little is known about IOP dynamics and the physiological factors that affect it as IOP is typically monitored using tonometry. Tonometry is a common tool used by clinicians and researchers to measure IOP noninvasively. It provides a good estimate of IOP mean but not variance because data collection takes time. Readings can also be influenced by subject …
Human Spacesuit Interaction During Eva Of The Legs Using A Force Sensing System, Niraliben D. Patel
Human Spacesuit Interaction During Eva Of The Legs Using A Force Sensing System, Niraliben D. Patel
USF Tampa Graduate Theses and Dissertations
Astronauts perform a multitude of tasks in space, both in the spacecraft and outside of the spacecraft. Extravehicular Activity (EVA) refers to any activity that is completed outside of the spacecraft, whether it is work on the actual spacecraft, spacewalks, or conducting sample collections on other planets and moons. To do this safely, a pressurized Extravehicular Mobility Unit (EMU) or commonly known as the spacesuit is used. There have been multiple iterations of the United States EMU with advances to further optimize the astronaut safety and EVA tasks. However, there is still relatively little information on the movement of the …
Eeg Classifier Validation Methods For Neuroprosthetic Hand Development, Keigo Yamauchi
Eeg Classifier Validation Methods For Neuroprosthetic Hand Development, Keigo Yamauchi
USF Tampa Graduate Theses and Dissertations
To date, many challenges have been reported in the development of neuroprosthetic hands using EEG and neural signals. In this study, we report the results of a literature review on Brain Computer Interface (BCI) technology, an investigation of estimation methods using applications in MATLAB, and the results of Electroencephalography (EEG) classification to assist in the development of neural prosthetic hands using biological signals such as EEG. Confusion Matrix was created using Motor Imagery (MI) data as the predictive value, and the average accuracy of more than 90% was obtained for the K-Nearest Neighbor (KNN) and decision tree method. The results …