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- 8artificial intelligence
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- 3deep learning
- 39Graduate and Postdoctoral Studies (GPS), Faculty of
- 39Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 11Concordia University of Edmonton
- 6Concordia University of Edmonton/Master of Science in Information Technology Project Reports (Concordia University of Edmonton)
- 4Computing Science, Department of
- 3Electrical and Computer Engineering, Department of
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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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Behavioral-based classification and identification of ransomware variants using machine learning
Download2018
Due to the changing behavior of ransomware, traditional classification and detection techniques do not accurately detect new variants of ransomware. Attackers use polymorphic and metamorphic techniques to avoid detection of signature -based systems. We use machine learning classification to...
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2023
Chat-bots could be considered as one of widely used technologies since it increases the business efficiency and throughput. Proposed project is to develop a web based chat-bot that is capable of booking appointments via the website Telecare Plus. Machine learning techniques are used to provide an...
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2022
Every living species has cells and based on those cells scientists observe and make some predictions or observations. The identification and classification of cells is a highly crucial part of medical research and involves human efforts to a huge extent. Due to human involvement, the research may...
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Computational psychiatry: machine learning for clinical decision support in the treatment of major depression
DownloadFall 2019
The goal of this thesis is to contribute to the fields of data-driven medicine and computational psychiatry by attempting to demonstrate the viability of machine learning for use in psychiatry, specifically in predicting treatment outcomes for major depression. This is attempted in four ways: ...
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Fall 2022
Imperfect information games model many large-scale real-world problems. Hex is the classic two-player zero-sum no-draw connection game where each player wants to join their two sides. Dark Hex is an imperfect information version of Hex in which each player sees only their own moves. Finding Nash...
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Data-Driven Approaches to Modeling Heterogeneity and Variability Across Asymptomatic Brain and Cognitive Aging, Mild Cognitive Impairment, and Alzheimer’s disease
DownloadSpring 2024
Objective We apply data-driven approaches to identify predictors of heterogeneous trajectories across normal aging, Mild Cognitive Impairment (MCI), and Alzheimer’s disease (AD). In Study 1, we investigated predictors of left and right hippocampal (HC) volume trajectory classes. In Study 2, we...
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Fall 2023
With the advances made in machine learning and data science, data-driven modeling and optimization techniques have garnered significant attention in recent years. However, despite the availability of various data-driven methods for addressing optimization problems under uncertainty, their...
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2017
Aggarwal, K., Timbers, F., Rutgers, T., Hindle, Abram, Stroulia, E., Greiner, R.
Bug deduplication, ie, recognizing bug reports that refer to the same problem, is a challenging task in the software-engineering life cycle. Researchers have proposed several methods primarily relying on information-retrieval techniques. Our work motivated by the intuition that domain knowledge...
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2015
Aggarwal, K., Rutgers, T., Timbers, F., Hindle, Abram, Greiner, R., Stroulia, E.
In previous work by Alipour et al., a methodology was proposed for detecting duplicate bug reports by comparing the textual content of bug reports to subject-specific contextual material, namely lists of software-engineering terms, such as non-functional requirements and architecture keywords....