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- Deep Learning (1)
- Distributed Learning (1)
- Distributed energy resources (1)
- Federated Learning (1)
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- Islanding detection (1)
- Load Forecasting (1)
- Motion sensing (1)
- Non-detection zone (1)
- Online Learning (1)
- Parkinson's Disease (1)
- Phase-locked loop (1)
- Piezoelectric (1)
- Recurrent Neural Networks (1)
- Sensors (1)
- Travelling Wave Ultrasonic Motor (1)
- Tremor (1)
- Voluntary motion (1)
- Wearable Mechatronic Devices (1)
- Wearable devices (1)
Articles 1 - 4 of 4
Full-Text Articles in Engineering
A Novel Passive Islanding Detection Method Based On Phase-Locked Loop, Hoda Zamani
A Novel Passive Islanding Detection Method Based On Phase-Locked Loop, Hoda Zamani
Electronic Thesis and Dissertation Repository
The ever-increasing penetration of distributed energy resources in power distribution systems has led to challenges in the detection of islanding. Among different islanding detection methods (IDMs), passive methods are the least intrusive and typically require the lowest investment cost. However, they generally suffer from larger non-detection zones (NDZs) and higher nuisance detection ratios as compared to active, hybrid, and remote IDMs. This study provides an overview of the criteria outlined in the existing technical literature for the performance evaluation of IDMs, a review and comparison of the existing passive IDMs, and an analysis of the phase-locked loop (PLL) behaviour under …
Modelling And Evaluation Of Piezoelectric Actuators For Wearable Neck Rehabilitation Devices, Shaemus D. Tracey
Modelling And Evaluation Of Piezoelectric Actuators For Wearable Neck Rehabilitation Devices, Shaemus D. Tracey
Electronic Thesis and Dissertation Repository
Neck pain is the most common neck musculoskeletal disorder, and the fourth leading cause of healthy years lost due to disability in the world. Due to the need of hands-on physical therapy and Canada’s aging population, access to treatment will become highly constrained. Wearable devices that allow at-home rehabilitation address this future limitation. However, few have emerged from the laboratory setting because they are limited by the use of conventional actuators. An overlooked type of actuation technology is that of piezoelectric actuators, more specifically, travelling wave ultrasonic motors (TWUM).
In this work, a clear procedure that outlines how the required …
The Development Of A Motion Sensing Device For Use In A Home Setting, Jaspreet K. Kalsi
The Development Of A Motion Sensing Device For Use In A Home Setting, Jaspreet K. Kalsi
Electronic Thesis and Dissertation Repository
Parkinson's disease (PD) is the second most prevalent neurodegenerative disease, with over 10 million individuals diagnosed with PD world-wide. The most common symptom characterized by PD is tremor. Tremor is an involuntary oscillatory motion that most prominently occurs in upper limb, specifically in the hand and wrist that has a measurable frequency and amplitude. This thesis aims to evaluate the usability and functionality of a tremor sensing device designed to collect quantitative data on individuals with PD. The designed device uses 23 commercially-available inertial measuring units (IMUs) located between 21 joints: distal interphalangeal (DIP) joints, proximal interphalangeal (PIP) joints, Interphalangeal …
Deep Learning For Load Forecasting With Smart Meter Data: Online And Federated Learning, Mohammad Navid Fekri
Deep Learning For Load Forecasting With Smart Meter Data: Online And Federated Learning, Mohammad Navid Fekri
Electronic Thesis and Dissertation Repository
Electricity load forecasting has been attracting increasing attention because of its importance for energy management, infrastructure planning, and budgeting. In recent years, the proliferation of smart meters has created new opportunities for forecasting on the building and even individual household levels. Machine learning (ML) has achieved great successes in this domain; however, conventional ML techniques require data transfer to a centralized location for model training, therefore, increasing network traffic and exposing data to privacy and security risks. Also, traditional approaches employ offline learning, which means that they are only trained once and miss out on the possibility to learn from …