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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
- 6Anomaly detection
- 1Binary classification
- 1Clustering
- 1Frequent patterns
- 1Machine failure
- 1Machine learning
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Application of Machine Learning in the Big Data for Broiler Breeders Recorded by a Precision Feeding System
DownloadSpring 2021
A precision feeding (PF) system developed at the University of Alberta is an innovation in precise nutrition and management for broiler breeders. The PF system can automatically feed individual broiler breeders and record vast amounts of real-time data regarding the feeding activity of individual...
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Fall 2014
Anomaly detection in spatial time series is a challenging problem with numerous potential applications. A comprehensive anomaly detection approach not only should be able to detect and identify the emerging anomalies, but it also has to characterize the essence of these anomalies by visualizing...
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Spring 2019
When a machine or a component of a machine fails, corrective maintenance is performed to identify the cause of failure and decide on a repair mechanism to restore the machine to its normal working condition. However, because the machine has failed without any prior warning, a considerable amount...
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Fall 2014
We address the problem of finding ‘surprising’ patterns of variable length in sequence data, where a surprising pattern is defined as a subsequence of a longer sequence, whose observed frequency is statistically significant with respect to a given distribution.Finding statistically significant...
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Fall 2024
In the realm of image processing, machine learning models have achieved remarkable progress in tasks such as classiffcation, recognition, and video analysis. However, their reliance on closed-set assumptions limits their performance in real-world scenarios where unseen anomalies frequently occur....
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Fall 2016
Anomaly detection in time series is one of the fundamental issues in data mining. It addresses various problems in different domains such as intrusion detection in computer networks, anomaly detection in healthcare sensory data, and fraud detection in securities. Though there has been extensive...