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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 ...
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 ...
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 ...
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 ...
Polymorphic Adversarial DDoS attack on IDS using GAN
(2020-12-01)
IDS are essential components in preventing malicious traffic from penetrating networks. IDS have been rapidly enhancing their detection ability using ML algorithms. As a result, attackers look for new methods to evade the ...
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 ...
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 ...
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 ...
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 ...