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Skip to Search Results- 10Machine Learning
- 4Deep Learning
- 2Artificial Intelligence
- 2Internal Combustion Engines
- 2Model Predictive Control
- 1Adaptive Sampling
- 1Ansari, Amir
- 1Govindan, Aswin Ramaswamy
- 1Imam, Habiba Z
- 1Kullar, Jagbir S.
- 1Norouzi Yengeje, Armin
- 1Rezvan Rafiee Alavi
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Spring 2023
With rising demands in industry for reliable electrical cable distribution networks comes an inherent need for utility providers to know well the condition of the assets in their network. Heightened expectations from regulators and consumers require methods of reliability assessment to improve...
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A Data-Driven Neural Network Model to Correct Derived Features in a RANS-Based Simulation of the Flow Around a Sharp-Edge Bluff Body
DownloadSpring 2023
In this dissertation, a machine-learning method is utilized to enhance the accuracy of wake parameters calculated by Reynolds Averaged Navier Stokes (RANS) k-ω SST model of flow on and around wall-mounted rectangular cylinders. Using high-quality results from Large Eddy Simulation (LES), this...
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Spring 2021
This thesis applies computer vision and machine learning techniques to three engineering projects: a self-driving vehicle, a predictive display system, and a vision-based robot manipulator joint detector. In the first project, we build a remote-controlled car and implement three core self-driving...
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Spring 2022
The rapid increase in global water and energy demand due to industrialization and population growth is a pressing challenge humankind faces today. Recent estimates indicate that due to population growth and reduction of water supplies, 40% of the global population is struggling with water...
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Development of AI-based ergonomics risk assessment tools for harmonization of industrial work systems
DownloadFall 2023
Manufacturing industry workers face significant ergonomic risks due to poorly designed work systems. Consequently, it is crucial to periodically assess work systems to identify areas for improvement. However, the assessment process is often disregarded due to the absence of userfriendly...
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Spring 2024
This thesis aims to create a platform to estimate and monitor the University of Alberta (UAlberta) fleet vehicles’ fuel consumption and Carbon Dioxide (CO2) emissions. The main objective is to collect and analyze fleet vehicles information to reduce energy consumption and greenhouse gas emissions...
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Fall 2022
Internal Combustion Engines (ICEs) are ubiquitous; they power a wide range of systems. The broad use of ICEs globally causes more than 20% of the total greenhouse gas emissions. In many countries, emission legislation is transitioning from certification using only traditional chassis dynomometer...
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Machine Learning for Emission Modeling of Fossil-fueled and Hydrogen-fueled Internal Combustion Engines
DownloadFall 2023
Development of fast and accurate emission models for engine-out and tailpipe of internal combustion engines (ICEs) using machine learning (ML) and hybrid methods are the focus of this thesis. The application is on medium and heavy-duty vehicles powered by both fossil fuels and alternative fuels...
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Near-Field to Far-Field Transformation and Fault Detection Using Adaptive Sampling and Machine Learning in Source Reconstruction Method
DownloadFall 2019
Until not so long ago, near-field and far-field measurement techniques were the two prominent approaches to evaluating antennas. A direct far-field measurement can be conducted in outdoor or indoor environments. The measurement of small antennas can be performed in anechoic chambers. For large...
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Towards an Autonomous Robot-based Laser Cladding Repair Process: A Framework for Damage Detection, Localization and Path Planning
DownloadFall 2021
With piling scientific evidence and growing public concerns about climate change and depletion of natural resources, policymakers are being forced to implement stringent environmental regulations. One such sector under scrutiny for the concerning pace at which it is ...