This decommissioned ERA site remains active temporarily to support our final migration steps to https://ualberta.scholaris.ca, ERA's new home. All new collections and items, including Spring 2025 theses, are at that site. For assistance, please contact erahelp@ualberta.ca.
Theses and Dissertations
This collection contains theses and dissertations of graduate students of the University of Alberta. The collection contains a very large number of theses electronically available that were granted from 1947 to 2009, 90% of theses granted from 2009-2014, and 100% of theses granted from April 2014 to the present (as long as the theses are not under temporary embargo by agreement with the Faculty of Graduate and Postdoctoral Studies). IMPORTANT NOTE: To conduct a comprehensive search of all UofA theses granted and in University of Alberta Libraries collections, search the library catalogue at www.library.ualberta.ca - you may search by Author, Title, Keyword, or search by Department.
To retrieve all theses and dissertations associated with a specific department from the library catalogue, choose 'Advanced' and keyword search "university of alberta dept of english" OR "university of alberta department of english" (for example). Past graduates who wish to have their thesis or dissertation added to this collection can contact us at erahelp@ualberta.ca.
Items in this Collection
- 7machine learning
- 2reinforcement learning
- 1 adsorption
- 1 latent dirichlet allocation
- 1CO2 capture
- 1ERP
- 1Bennett, Brendan
- 1Chakravarty, Sucheta
- 1Croshaw, Jeremiah
- 1Damasah, Elliot Akwanfo
- 1Lu, Zhe
- 1Salimi, Amir Saeid
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Spring 2021
The development of the modern transistor has sparked a technological revolution which has flourished for the past 70 years. Advancements in transistor design and fabrication have allowed for their continued shrinking in size and increase in operation speed. With the continued reduction in size...
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Spring 2021
Temporal difference (TD) methods provide a powerful means of learning to make predictions in an online, model-free, and highly scalable manner. In the reinforcement learning (RL) framework, we formalize these prediction targets in terms of a (possibly discounted) sum of rewards, called the...
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Machine learning-based design and techno-economic assessments of adsorption processes for CO2 capture
DownloadFall 2021
Cyclic adsorption processes are widely considered for various industrial gas separations, including CO2 capture. The flexibility to configure a variety of process cycles is an attractive process design feature of these processes. Despite such flexibility for process design, computationally...
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Fall 2021
This work focuses on the virtual generation of short percussive samples which can be used by electronic music artists in their compositions. Although recent advancements in digital synthesis, heuristic search, and neural networks have been utilized for the generation of a variety of sounds, the...
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Fall 2021
Successful learning is of vital importance to human cognition. Accordingly, researchers have been interested to understand brain-activity signals that support it. However, traditional analysis of brain activity is based on planned comparisons and descriptive methods, which can both overestimate...
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Spring 2021
The number of childhood cancer survivors has dramatically increased in the past few decades due to advances in cancer treatment, shifting the priority from clinical treatment to improving long-term survivors’ quality of life. One late effect that greatly impacts female survivors is premature...
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Using Machine Learning to Understand the National Security Agency’s Data Surveillance Trends
DownloadFall 2021
For over six decades, the public has remained ignorant about the National Security Agency (NSA) and its activities and has been shielded from the agency’s invasive and unlawful projects. While the NSA’s activities have proven valuable to the United States and its allies, it sometimes undertakes...