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Skip to Search Results- 101Machine learning
- 75Adsorption
- 9Artificial intelligence
- 7Biochar
- 5Activated Carbon
- 5Reinforcement learning
- 5Kuznicki, S. M.
- 4Hindle, Abram
- 4Mark A. Lewis
- 4Russell Greiner
- 3Jin, Zhehui
- 3Noonari, Juned (Supervisor)
- 126Graduate and Postdoctoral Studies (GPS), Faculty of
- 126Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 8WISEST Summer Research Program
- 8WISEST Summer Research Program/WISEST Research Posters
- 7Master of Science in Internetworking (MINT)
- 7Master of Science in Internetworking (MINT)/Capstone Projects & Reports (Master of Science in Internetworking (MINT))
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Fall 2009
This thesis addresses the challenge of prognosis, in terms of survival prediction, for patients with Glioblastoma Multiforme brain tumors. Glioblastoma is the most malignant brain tumor, which has a median survival time of no more than a year. Accurate assessment of prognostic factors is critical...
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Public Health Applications Using Big Data and Machine Learning Methods: Name- and Location-based Aboriginal Ethnicity Classification and Sentiment Analysis of Breast Cancer Screening in the United States Using Twitter
DownloadFall 2017
Applications using big data and machine learning techniques are transforming how people live in the 21st century, however they are generally underutilized in public health compared to other domains. We proposed and conducted two independent studies to investigate how big data and machine learning...
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Reclamation of Unconventional Oil Processed Water through the Adsorption of Naphthenic Acids by Carbon Xerogel
DownloadFall 2017
This study examines the use of carbon xerogel (CX) material for the adsorption of naphthenic acids (NAs). The adsorption of NAs is crucial for the reclamation of unconventional oil processed water, more specifically Alberta’s oil sands process-affected water (OSPW). CX material is synthesized at...
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Fall 2018
Gaussian processes are flexible probabilistic models for regression and classification. However, their success hinges on a well-specified kernel that can capture the structure of data. For complex data, the task of hand crafting a kernel becomes daunting. In this thesis, we propose new methods...
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Regenerable Composites for Removal of Organic Dye in Aqueous Media and Water in Heavy Oil and the Associated Interaction Mechanism
DownloadSpring 2018
Water plays an indispensable role in all aspects of life, including farming, domestic and industrial uses. In industries, water has been extensively applied in mining, production and surface treatment, producing a large quantity of contaminated water that threatens human health, endangers...
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Spring 2015
This dissertation explores regularized factor models as a simple unification of machine learn- ing problems, with a focus on algorithmic development within this known formalism. The main contributions are (1) the development of generic, efficient algorithms for a subclass of regularized...
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Removal of Heavy Metal Ions and Diethylenetriamine Species from Solutions by Magnetic Activated Carbon
DownloadSpring 2013
Even though activated carbon is widely used in the removal of contaminants from effluents, it is difficult to be completely recovered by screening or classification. In this project, we prepared a magnetic form of activated carbon (M-AC) by co-precipitation of iron oxides onto activated...
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Removal of Organic and Inorganic Contaminants from Oil Sands Tailings using Carbon Based Adsorbents and Native Sediment
DownloadFall 2013
The extraction and refinement of oil sands bitumen produces substantial quantities of liquid tailings and solid coke. Tailings contain metals and naphthenic acids, which require remediation before mine closure. Adsorption is a potential remediation technique which may reuse stockpiled petroleum...