Browsing Graduate & Postdoctoral Studies by Subject "Machine learning"
Now showing items 21-32 of 32
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Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers
(2016-10-01)The ability to predict financial markets has tremendous potential to limit exposure to risk and provide better assurances of annualized gains. In this thesis, a model for predicting the future daily price of Bitcoin is ... -
Predicting mutation score using source code and test suite metrics
(2012-09-01)Mutation testing has traditionally been used to evaluate the effectiveness of test suites and provide con dence in the testing process. Mutation testing involves the creation of many versions of a program each with a single ... -
Predicting the threat of death in stalking cases through Artificial Neural Network
(2020-10-01)Stalking is a complex phenomenon that needs to be explained through several frameworks of research. During the years, scientists from the psychological, criminological, psychological, and legal fields made important steps ... -
Predictive analytics for maintenance activities in nuclear power plants: a feasibility study
(2021-12-01)Nuclear power plants are known for their use of legacy systems and processes. As plants age, the amount of maintenance increases while resources remain finite, leading to unwanted delays, affecting the health of assets and ... -
Proposing an ensemble-based model using data clustering and machine learning algorithms for effective predictions
(2019-08-01)One of the most important tasks in machine learning is prediction. Data scientists use various regression methods to find the most appropriate and accurate model applicable for each type of datasets. This study proposes a ... -
Rapid remaining-useful-life prediction of Li-ion batteries using image-based machine learning
(2022-08-01)With the increased integration of lithium-ion batteries in our everyday lives, accurate and reliable battery management systems have become an imperative aspect of the well-being of our everyday electronics. This thesis ... -
A supervised machine learning-based framework to detect low-level fault injections in software systems
(2022-08-01)Fault injection attacks inject faults into system components, inducing abnormal software behavior. Software vulnerability analysis cannot prevent new attack vectors without software modifications. Attack detection methods ... -
Supporting student success with machine learning and visual analytics
(2019-08-01)Post secondary institutions have a wealth of student data at their disposal. This data has recently been used to explore a problem that has been prevalent in the education domain for decades. Student retention is a complex ... -
Time-efficient offloading and execution of machine learning tasks between embedded systems and fog nodes
(2019-12-01)As embedded systems become more prominent in society, it is important that the technologies that run on them must be used efficiently. One such technology is the Neural Network (NN). NN's, combined with the Internet of ... -
Understanding and predicting method-level source code changes using commit history data
(2016-10-01)Software development and software maintenance require a large amount of source code changes to be made to a software repositories. Any change to a repository can introduce new resource needs which will cost more time and ... -
Using machine learning methods to aid scientists in laboratory environments
(2019-12-01)As machine learning gains popularity as a scientific instrument, we look to create methods to implement it as a laboratory tool for researchers. In the first of two projects, we discuss creating a real-time interference ... -
The World Trade Web: using network analysis and machine learning as tools for public policy decision-making
(2020-11-01)The World Trade Web (WTW) contains a wealth of information that upon rigorous analysis can aid governments in public policy decision-making. In my attempt to provide this valuable input, this dissertation uses two main ...