Search
Now showing items 1-10 of 32
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...