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Characterizing water-metal interfaces and machine learning potential energy surfaces
(2017-08-01)
In this thesis, we first discuss the fundamentals of ab initio electronic structure theory and density functional theory (DFT). We also discuss statistics related to computing thermodynamic averages of molecular dynamics ...
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 ...
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 ...
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 ...
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 ...
Perpetually playing physics
(2019-08-01)
Here we discuss ideas of reinforcement learning and the importance of various aspects of it. We show how reinforcement learning methods based on genetic algorithms can be used to reproduce thermodynamic cycles without prior ...
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 ...
Automatic fall risk detection based on imbalanced data
(2021-08-01)
In recent years, the declining birthrate and ageing population have gradually brought countries into an ageing society. In regards to the accidents that occur amongst the elderly, falls are an important problem that quickly ...
Design and development of advanced machine learning algorithms for lithium-ion battery state-of-charge estimation
(2019-11-01)
Batteries have been becoming more and more popular because of their long life and lightweight. Accurate estimation of the SOC help in making plans in an application to conserve and further enhance battery life. State of ...
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 ...