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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 ...
Application-specific transfer learning over edge networks
(2021-11-01)
Transfer learning uses a profound labeled set of data from the source domain to deal with a similar problem for the target domain. Transfer learning provides accurate decision- making when insufficient data samples are ...
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 ...
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 ...
Machine learning classifiers for critical cardiac conditions
(2016-04-01)
Cardiac diseases are one of the leading causes of death in Canada. Current methods of diagnosing cardiac conditions require a manual and visual analysis of ECG and heart rate (RR interval) data. In this thesis, novel ...
Machine learning classification techniques for non-intrusive load monitoring
(2016-10-01)
Non-intrusive load monitoring is the concept of determining the operational loads using
single-point sensing. The features contained within the electrical load’s signal are used to identify
a unique signature which is ...
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 ...
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 ...
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 ...
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 ...