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  • The use of EEG and VR in Mental State Recognition

    Resource Type:
    Thesis
    Creator:
    El-Habrouk, Jaser
    Abstract:
    Mental state recognition (MSR) is important to multiple health-related fields. A virtual reality (VR) headset is used to induce mental states through both distractors and stressors. Participants solved arithmetic questions in VR, then outside of VR using a Muse S EEG device. A heart monitor was used throughout. Three research contributions followed: First, heart rate variability (HRV) data were compared between VR and non-VR sessions and correlated with established Test of Variables of Attention (T.O.V.A.) measurements used to asses participants' attention and focus. Second, a classifier was developed to differentiate between clean and noisy EEG data, with 92% accuracy. Lastly, linear regression models were developed, achieving mean squared error scores of 0.65 and 0.63 for 3-level stress and attention prediction from EEG data, respectively. In summary, this thesis explores the use of VR to induce mental states and advances the state of the art in EEG-based MSR.
    Thesis Degree:
    Master of Applied Science (M.App.Sc.)
    Thesis Degree Discipline:
    Engineering, Biomedical
    Date Created:
    2023

  • Modular Verification of Hierarchical Component-Based Software Systems

    Resource Type:
    Thesis
    Creator:
    Baak, James Alec William
    Abstract:
    Using Component-based Software Engineering approaches with Formal Methods has seen an influx of interest in the recent decades. The joining of these two disciplines have been stifled though due to unclear component specifications and expensive formal verification techniques, which hurt the reusability and scalability of complex software systems. In this work, we expand on current component-port-connector metamodels for formally specifying a system's architectural and behavioural requirements into a hierarchical component system structure by using abstract Composite Components. The Composite Components of a system model can then utilize modular verification for isolating the verification process into modules surrounding Composite Components and generating higher level properties. We formalize our metamodel in Alloy 6 and present a template for specifying system properties for modular verification which enables the reuse of previous verification efforts on satisfied modules. We conclude with an example case study system and analysis of the modular verification strategy.
    Thesis Degree:
    Master of Applied Science (M.App.Sc.)
    Thesis Degree Discipline:
    Engineering, Electrical and Computer
    Date Created:
    2023

  • Analysis of Open-Source Data in Wind Power Prediction Modeling

    Resource Type:
    Thesis
    Creator:
    von Zuben, Elizabeth Lynn
    Abstract:
    As identified in the 2021 IPCC AR6 WGIII report, wind energy has a high potential to reduce greenhouse gas emissions. The deployment of wind energy, however, has fallen behind its potential in part because of the need for improved wind power predictions. This thesis combines historical power production data, meteorological station data, reanalysis data, and numerical weather prediction output data (WRF model) to determine the optimal combination of data sources and variables for wind power prediction using a random forests model. A study then further evaluates reanalysis data and methods of bias correction for this type of data, to improve power predictions at 52 wind farms across Canada using power curve and machine learning methods. Recommendations are proposed for: the use of data sources and important input variables; the utility of global reanalysis data sources by terrain features; and the utility of bias correction methods for downstream wind power prediction.
    Thesis Degree:
    Master of Applied Science (M.App.Sc.)
    Thesis Degree Discipline:
    Engineering, Mechanical
    Date Created:
    2022

  • A NUMERICAL STUDY OF THE IMPACT OF MAKE-UP AIR VELOCITY ON THE SMOKE CONDITIONS IN AN ATRIUM

    Resource Type:
    Thesis
    Creator:
    Boakyewah, Barbara
    Abstract:
    This research numerically investigates the effect of make-up air on the smoke conditions in an atrium under different make-up air velocities and fire sizes. A total of twenty-four (24) simulations were conducted using the Fire Dynamics Simulator (FDS) to consider different scenarios of fire located at the center (axisymmetric), northwest corner and southeast corner of the atrium. Fire sizes of 1 MW, 3 MW and 5 MW along with different make-up air velocities of 1 m/s, 1.5 m/s, 2.5 m/s and 3.5 m/s were simulated to investigate their effect on smoke conditions the atrium. The results showed that the simulation predicted slightly higher temperatures and lower smoke layer heights when compared to the experimental tests. The position of the fire source at different locations showed different and increasing temperatures when the velocity changes from 1 m/s to 3.5 m/s, however the effects of make-up air velocities were minor.
    Thesis Degree:
    Master of Applied Science (M.App.Sc.)
    Thesis Degree Discipline:
    Engineering, Civil
    Date Created:
    2023

  • QoS Performance Measurement Through SRv6 Network Programming for Smart City IoT Traffic

    Resource Type:
    Thesis
    Creator:
    Kuri, Sajib Kumar
    Abstract:
    Segment Routing over IPv6, also known as SRv6, is a modern networking solution that aims to improve the current Internet of Things (IoT) network's reliability, availability, and scalability. Performance measures are required to evaluate SRv6 behaviors or functions. The proposed work aims to provide real IoT traffic profiles to assess the performance of SRv6 behaviors. In particular, a three-module SRv6 programming model is proposed to measure the performance of SRv6 policy headend and endpoint behavior and ensure reliability and quality of service (QoS). Moreover, a novel finder algorithm for maximum receive rate (MRR) benchmarking is proposed, which can outperform existing techniques in terms of throughput/bandwidth performance while maintaining the same computational resources. Finally, implementation results provide insights into forwarding different IoT use-cases traffic based on the functional service requirements. That also ensures a higher usage level of existing IoT networks, minimizing the need for additional capacity and lowering network costs.
    Thesis Degree:
    Master of Applied Science (M.App.Sc.)
    Thesis Degree Discipline:
    Engineering, Electrical and Computer
    Date Created:
    2022

  • Optimal Selection of IPsec-Based Security Mechanisms in Resource Constrained IoT Environment

    Resource Type:
    Thesis
    Creator:
    Mahmoud, Abdullah Fahmi Mustafa
    Abstract:
    Internet of Things (IoT) is a modern-day technology that supports many different applications such as smart cities, e-health, and smart homes. However, the specific IoT nature of connecting various heterogeneous devices complicates the implementation of conventional security mechanisms. In this work, a device-based security approach has been proposed to assign optimal security mechanisms to the set of heterogeneous IoT devices based on their available resources and the system requirements. To achieve the proposed approach, the security overhead equation was formulated to include 3 parameters: RAM usage, energy consumption and throughput. A hardware implementation was used to measure these parameters and to calculate the security overhead for the tested security mechanisms. The Pareto frontline was used to select the optimal security mechanism that minimizes the security overhead per device while maximizing the system requirement. The selection algorithm was tested in a simulation of 50 heterogeneous devices that ran 30 security mechanisms.
    Thesis Degree:
    Master of Applied Science (M.App.Sc.)
    Thesis Degree Discipline:
    Engineering, Electrical and Computer
    Date Created:
    2023

  • Simulating 3D Tailings Dam Breach With Thixotropic Bifurcation Rheology using the Material Point Method

    Resource Type:
    Thesis
    Creator:
    Xia, Xuexin
    Abstract:
    Mining is a booming industry and it indirectly involves everyone living in modern society. Tailings, the primary solid waste generated as the side effect of extracting valuable minerals, often require vast facilities to store the large quantity of waste. Failure of tailings storage facilities often causes significant damage both environmentally and economically, and frequently results in fatalities. Nowadays numerical simulation of tailings flows resulting from potential failures has become widespread in practice to assist the design of tailings storage facilities. In this thesis, tailings runout simulations are attempted using a numerical method suitable for large deformation analysis (Material Points Method) employing an advanced rheological model. This study aims to simulate the runout of tailings dam breach incident such as Merriespruit in South Africa using realistic geotechnical properties and producing results that fulfill the expectations from both geo-mechanical and hydrodynamical requirements.
    Thesis Degree:
    Master of Applied Science (M.App.Sc.)
    Thesis Degree Discipline:
    Engineering, Environmental
    Date Created:
    2023

  • Safety Evaluation of Red-Light Cameras and Dynamic Speed Display Signs Within the City of Ottawa

    Resource Type:
    Thesis
    Creator:
    Saffarzadeh Parizi, Sorousha
    Abstract:
    This thesis evaluates the safety impacts of red-light cameras (RLCs) and Dynamic Speed Display Signs (DSDSs) in Ottawa, Canada. The study examines the safety impacts of RLCs on safety performance, using collision records, and driver behaviour using surrogate safety measures. The safety impacts of DSDSs on driver behaviour are evaluated using speed analysis. An empirical Bayes method for RLCs showed a significant impact, where total and PDO collisions increased while injury and fatal collisions decreased. The impact of RLCs also depended on the collision types, where sideswipe, rear-end, and SMV collisions increased, but the angle and turning collisions decreased. The increase in rear-end collisions was also examined through an analysis of traffic conflicts. The results indicated that treated sites had significantly more severe rear-end conflicts that had likely resulted from harder deceleration rates. Speed analysis for DSDSs indicated drivers reduced their speed when they saw their actual speed on DSDSs.
    Thesis Degree:
    Master of Applied Science (M.App.Sc.)
    Thesis Degree Discipline:
    Engineering, Civil
    Date Created:
    2023

  • Deep Learning and Synthetic Imagery for Migratory Bird Species Identification Using Drones

    Resource Type:
    Thesis
    Creator:
    Costa, Alexsander Cassio Aguiar Antunes
    Abstract:
    In this thesis work, the use of UAS in the study of migratory shorebird species in Canada is explored with the development of computer vision applications. A deep learning classification model is trained to identify the presence of birds of a given species in an image. Images were collected from UAS for the development of the vision models, and realistic models of the species of interest were used. To address a data scarcity issue, the datasets used were augmented with synthetic data with realistic models of the birds. For evaluation of the quality of the artificially generated images, a novel measure is developed. The synthetic image quality measure showed better results in controlled environments when compared to a popular alternative in the literature. The classifiers trained with the augmented dataset showed appropriate performance, with mean accuracy and standard deviation of 94% +- 0.04 in the test set.
    Thesis Degree:
    Master of Applied Science (M.App.Sc.)
    Thesis Degree Discipline:
    Engineering, Mechanical
    Date Created:
    2023

  • Knowledge Graph Generation for Unstructured Data Using Data Processing Pipeline

    Resource Type:
    Thesis
    Creator:
    Sukumar, Sushmi Thushara
    Abstract:
    Research on effective usage of Machine Learning (ML) and Natural Language Processing (NLP) techniques are taken up to mitigate the problem of extracting information from huge volumes of unstructured data available on the Internet without losing valuable information. Constructing Knowledge Graph is one such application to query and extract unstructured data. The data is passed through a coreference resolution module using Neuralcoref, a named entity linking module using Wikifier API, and a relationship extraction module using two models, namely, OpenNRE and REBEL, and stores the results as a KG in Neo4j with its corresponding entities and relationships. Experiments were conducted on an unstructured dataset (BBC news dataset) containing text data to analyze the results obtained from the pipeline. The results obtained in the relationship extraction stage were analyzed for evaluation purposes and achieved 61.4% and 87% accuracy through the OpenNRE and REBEL models, respectively.
    Thesis Degree:
    Master of Applied Science (M.App.Sc.)
    Thesis Degree Discipline:
    Engineering, Electrical and Computer
    Date Created:
    2023