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Now showing items 1-9 of 9
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 ...
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 ...
Characterizing the potential energy surface of two dimensional and bulk materials using high dimensional neural network potentials
(2018-08-01)
Computing material properties at the ab-initio level of detail is computationally prohibitive for large systems or long timescales. As a result, such methods cannot be used to efficiently sample configuration space. Force ...
Achieving real-time video summarization on commodity hardware
(2018-04-01)
We present a system for automatic video summarization which is able to operate in
real-time on commodity hardware. This is achieved by performing segmentation
to divide a video into a series of small video clips, which are ...
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 ...
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 ...
An anomaly detection model utilizing attributes of low powered networks, IEEE 802.15.4e/TSCH and machine learning methods
(2019-12-01)
The rapid growth in sensors, low-power integrated circuits, and wireless communication standards has enabled a new generation of applications based on ultra-low powered wireless sensor networks. These are employed in many ...