Browsing Faculty of Graduate Studies Online Theses by Subject "Machine Learning"
Now showing items 21-40 of 64
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Early prediction of skin toxicities during radiotherapy using optical and infrared imaging
(2022-08-31)Approximately 90% of breast cancer radiation therapy patients experience skin toxicities that are difficult to predict. The objectives of this study are to evaluate correlation between the skin toxicity occurrences and ... -
ELECTRONIC GAMING MACHINE PLAYSTYLE DETECTION AND RAPID PLAYSTYLE CLASSIFICATION USING MULTIVARIATE CONVOLUTIONAL LSTM NEURAL NETWORK ARCHITECTURE
(2021-09-01)Electronic Gaming Machines (EGM) are common, anonymous, stateless gambling machines operated by a region’s lottery and situated in licensed venues. Previous work have shown that problem gambling detection is possible ... -
An Ensemble Regression Approach For OCR Error Correction
(2017-04-11)This thesis deals with the problem of error correction for Optical Character Recognation (OCR) generated text, or OCR-postprocessing: how to detect error words in a text generated from OCR process and to suggest the most ... -
Evaluation of DeepLabCut as a Human Markerless Motion Capture Tool
(2023-08-31)There are a variety of motion capture methods available; however, many of them are not well suited for collections outside a laboratory setting. AI markerless motion capture may fit this need, but its implementation and ... -
Exploration of NLP-Based Feature Extraction Techniques for Security Analysis and Anomaly Detection of Service Logs
(2023-04-28)The goal of this research is to provide security and machine learning (ML) practitioners with deeper insight when selecting features and algorithms for unsupervised log analysis. This thesis explores the effect of traditional ... -
Exploring Phishing Detection Using Search Engine Optimization and Uniform Resource Locator based Information
(2021-04-29)Phishing attacks are the work of social engineering. They are used to trick users to obtain their sensitive/private information using malicious links, websites, and electronic messages. In this thesis, phishing attack ... -
Forecasting algae blooms in aquaculture using mussels' openings data
(2021-04-28)Time series data consists of a series of measurements collected over a period of time. This type of data is very relevant in several domains, including healthcare, manufacturing, finance, environment, and many more. For ... -
A Hybrid Machine Learning Intrusion Detection System Framework with Integrated Server and Client Models for Wireless Sensor Networks
(2024-04-15)Federated Learning (FL) has emerged as a novel distributed Machine Learning (ML) approach to tackle the challenges associated with data privacy and overload in ML-based intrusion detection systems (IDSs). Drawing inspiration ... -
Identification of high-frequency periodic acoustic tags with deep learning
(2021-07-30)Marine life researchers use the concept of fish tracking to determine the activity andbehaviour of fish. It allows the researchers to recognize the valuable biological andphysical support systems required by fish species ... -
Identifying Factors Influencing Electronic Gaming Machine Player Behavior Using Interpretable AI and Mimicking Player Behavior Using Reinforcement Learning
(2022-12-06)People in venues like casinos play games on Electronic Gaming Machines (EGMs). These machines do not record information about players, such as their playing experience. The gaming industry is keen on learning about the ... -
IMPROVED POWER SYSTEM REALIZATION AND INTEGRATION
(2020-04-14)The main goal of this research is to pave a new path to solve electric power system problems from a realistic perspective. The problems covered in this thesis are power transmission lines, power flow (PF) or load flow (LF) ... -
Improving Efficacy and Efficiency of Hypothesis Adaptation and Federated Learning
(2023-07-28)Small computing devices, such as smartphones, constantly collect and store data that can potentially help machines learn complex tasks. However, the data contained on a single device is relatively small and biased, making ... -
IMPROVING MOBILE MALWARE DETECTORS USING CO-EVOLUTION TO CREATE AN ARTIFICIAL ARMS RACES
(2018-08-21)On the Internet today, mobile malware is one of the most common attack methods. These attacks are usually established via malicious mobile apps. One technique used to combat this threat is the deployment of mobile malware ... -
Insider Threat Detection Data Augmentation Using WCGAN-GP
(2022-04-12)This thesis explores the application of Generative Adversarial Networks (GANs) in augmenting insider threat detection datasets to alleviate class imbalance. In addition, a machine learning based insider threat detection ... -
Interactive Learning To Rank And Visual Rank Interpretation
(2020-04-08)Many algorithms in the Information Retrieval domain have been developed considering training models using vast amounts of data. The acquisition of this data, however, is time-consuming and requires lots of human effort. ... -
INVESTIGATING CLUSTER ENSEMBLE METHODS TO DEVELOP PHYSICIAN PHENOTYPES BASED ON PATHOLOGY TEST ORDERING PATTERNS
(2021-04-16)Pathology laboratory testing is central to medical practice as most diagnostic and therapeutic decisions are guided by the patient’s bloodwork results. Pathology laboratory tests are ordered by clinicians, and it has been ... -
An Investigation on Detecting Applications Hidden in SSL Streams using Machine Learning Techniques
(2010-09-09)The importance of knowing what type of traffic is flowing through a network is paramount to its success. Traffic shaping, Quality of Service, identifying critical business applications, Intrusion Detection Systems, as ... -
LITHOSPHERIC-SCALE TECTONICS OF THE INDIA-ASIA COLLISIONAL SYSTEM
(2024-06-09)The India-Asia orogenic system is the largest and among the most well studied orogens on Earth. Despite its status as an archetype for large hot orogens, there remain many unknowns regarding the first-order evolution of ... -
A MACHINE LEARNING APPROACH FOR ALERT BEHAVIOR RESPONSE MODELING TO MITIGATE ALERT FATIGUE IN HEALTH INFORMATION SYSTEMS
(2019-04-23)This research investigates novel approaches to reduce the burden of alert fatigue faced by primary care physicians using Clinical Decision Support Systems (CDSS) within EMR systems. CDSS issue a range of alerts to assist ... -
A Machine Learning Approach to Forecasting Consumer Food Prices
(2017-08-24)Building on the success of the Canada Food Price Report 2017 and its inclusion of a machine learning methodology, this research thesis posed and attempted to answer the following question, “What is the best way to predict ...