Queen's Graduate Theses and Dissertations
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This is a collection of the Queen's University Masters Degree and PhD Theses and Dissertations. Submissions are limited to officially registered Queen's University graduate students only.
Note: theses which are temporarily embargoed by the author’s request will display a lock icon beside the thesis file link. For more information, including the embargo lift date, please click on “Full item page” at the bottom of the QSpace record.
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Item Wind-Driven Sea Surface Wave and Coastal Water Level Dynamics Across Different Spatial Scales(2024-11-29) Benoit, Delaney Michelle; Civil Engineering; Mulligan, RyanWind-generated surface waves can propagate over long distances towards vulnerable coastal regions. Complex factors that impact the properties of surface waves, including wind, topography, and water levels, must be incorporated into numerical models to achieve accurate simulations of the wave climate. Predictions of the offshore surface wave conditions can inform projections of nearshore impacts in response to storms or sea level rise, such as flooding, erosion, and elevated groundwater, and aid the design limits of protective infrastructure, such as dykes. In this thesis, numerical models, physical models, and field observations are used to investigate surface waves and water levels at three scales: a coastal sea, a tidal bay, and a sandy beach. A numerical model is developed for the Strait of Georgia to investigate the influence of wind resolution on locally generated wave and storm surge. A finer scale numerical model is applied to Boundary Bay, a tidal flat within the Strait of Georgia, to simulate the combined surface wave and water level overtopping potential and intertidal reduction under future sea level rise scenarios. A series of high resolution, small-scale laboratory experiments are run to investigate the relationship between wave runup-driven infiltration into the subsurface and various beach properties. The findings of this study emphasize the importance of wind resolution in models with large domains and the error induced by model input uncertainty. Increased mean sea elevation is found to increase nearshore wave heights and heighten risk of infrastructure overtopping and changes to the intertidal zone. Detailed observations of surface wave runup on unsaturated beach face demonstrate how fluid infiltrates the subsurface and raises the phreatic surface. The overall findings of this thesis contribute to understanding and improving prediction of coastal hazards and nearshore impacts in response to storm events and sea level rise at different spatial scales.Item Federated Learning With Generalization To New Domains(2024-11-29) Soltany, Milad; Electrical and Computer Engineering; Greenspan, Michael; Etemad, AliFederated Learning (FL) is an area of research that focuses on training machine learning models in a decentralized fashion without having the need to store all data on one central server. In this thesis, we address the challenges of data heterogeneity and label scarcity in FL by proposing two novel approaches for federated domain generalization in both unsupervised and supervised settings. First, to tackle federated domain generalization in an unsupervised setting, we introduce Federated Unsupervised Domain Generalization using Global and Local Alignment of Gradients. We establish a connection between domain shifts and gradient alignment in unsupervised federated learning, demonstrating that aligning gradients at both the client and server levels facilitates the generalization of the model to new, unseen domains. FedGaLA performs gradient alignment locally to encourage clients to learn domain-invariant features, and globally at the server to obtain a more generalized aggregated model. Extensive experiments on four multi-domain datasets—PACS, OfficeHome, DomainNet, and TerraInc—show that FedGaLA outperforms comparable baselines. Ablation and sensitivity studies highlight the impact of different components and hyper-parameters in our approach. Second, to address data heterogeneity in a supervised federated learning framework, we propose Federated Domain Generalization with Label Smoothing and Balanced Decentralized Training (FedSB). FedSB utilizes label smoothing at the client level to prevent overfitting to domain-specific features, thereby enhancing generalization capabilities across diverse domains when aggregating local models into a global model. Additionally, FedSB incorporates a decentralized budgeting mechanism that balances training among clients, improving the performance of the aggregated global model. Experiments on four commonly used multi-domain datasets—PACS, VLCS, OfficeHome, and TerraInc—demonstrate that FedSB outperforms competing methods, achieving state-of-the-art results on three out of four datasets. Collectively, these contributions address critical challenges in FL by enhancing model generalization across diverse and unseen domains in both unsupervised and supervised settings. The effectiveness of FedGaLA and FedSB in addressing data heterogeneity is evidenced by their superior performance in extensive empirical evaluations.Item Non-Hydrostatic Modelling to Improve Nearshore Optical Remote Sensing Algorithms: Applications for Surf Zone Hydrodynamics and Morphodynamics(2024-11-28) Oades, Elora M. H.; Civil Engineering; Mulligan, RyanAccurate bathymetric data is essential for predicting changes in coastal environments. Traditional surveying methods the seabed provide precise measurements but are limited in coverage and cost. Video remote sensing offers a cost-effective alternative that can capture wave, current, and bathymetric information in dynamic nearshore areas. However, reliable methods are needed to extract accurate data from imagery across various wave conditions. This thesis aims to enhance two retrieval algorithms used to estimate bathymetry and alongshore currents from optical data. Using the non-hydrostatic numerical model SWASH (Simulating WAves til SHore), synthetic wave and current fields are generated to simulate storm events at the US Army Corps of Engineers Field Research Facility in Duck, NC. The simulations complement field observations and offer a new method of identifying sources of error in optical data. The first of these algorithms is cBathy, which faces challenges during large offshore wave conditions, which causes signal interference. By incorporating SWASH-generated water surface elevation data, the errors in depth estimates were reduced, especially in areas of wave breaking. The results of different versions of cBathy are also investigated, which are discussed alongside recommendations for further refinement. The second of these algorithms calculates alongshore current speed, a key driver of bathymetric change. A new version of the Optical Current Meter method (OCM) is developed using SWASH model results and field observations. The updated algorithm lowers measurement error and improves optical measurements across a broader range of conditions. The open-source code is now included in the Coastal Imaging Research Network (CIRN) Video-Currents-Toolbox and is available to other researchers. Informed by the numerical model and field sensor observations, the results provide improved estimates of coastal bathymetry and alongshore currents from optical data, especially during storm conditions that are challenging to monitor.Item Exploring the Knowledge, Understanding, and Preparedness to Teach Students with Fetal Alcohol Spectrum Disorder (FASD) by Preservice Teachers in Ontario(2024-11-27) Joseph, Tanya Ann; Education; Berg, Derek; Morcom, LindsayFetal Alcohol Spectrum Disorder (FASD) is one of the most prevalent exceptionalities in Canadian classrooms, and one of the most challenging for teachers to support. Children affected by FASD exhibit a range of symptoms and various degrees of impairment, requiring multi-faceted supports. In teacher education programs, preservice teachers receive training through a combination of coursework and placements. Although courses offered to preservice teachers reflecting special education may be compulsory, explicit instruction on specific exceptionalities is limited. As studies have been completed in the past on teacher knowledge to support students with exceptionalities, there is a lack of research completed in Ontario reflecting how teachers are prepared to support students with FASD. If teachers are not prepared to teach students with FASD within the classroom, children with FASD may not receive the support they require. The objective of this study was to examine preservice teachers’ knowledge and understanding of FASD and their preparedness to teach these students. Both quantitative and qualitative data was collected through a 52-item online questionnaire to examine experiences supporting exceptionalities and FASD, knowledge of the condition, Teacher Sense of Efficacy (TSES), and preparedness to support students with FASD. Participants of this study (N = 80) were preservice teachers at a teacher education program accredited by the Ontario College of Teachers (OCT). It was observed that preservice teachers felt that they were not adequately trained to support students with FASD, and they did not discuss FASD as a topic of interest within their preservice teacher education programs. Experiences with exceptionalities was variable, and specific knowledge of needs of students with FASD was limited. Correlational analyses indicated that preservice teachers had low confidence of knowledge which was attributed to lack of awareness of the condition, lack of experiences supporting students with FASD, and lack of discussion of FASD and challenges faced by students with the condition. These findings suggest that FASD is a topic that should be further emphasized in preservice teacher education programs and challenges faced by students with the condition and strategies to support them must be discussed.Item Frank P. Wood: Collector Extraordinare and Client of Sir Joseph Duveen(2024-11-27) Graham, Lucinda; Art History; Stephanie , DickeyFrank Porter Wood (1882—1955) was a Toronto Interwar art collector, philanthropist and financier, whose donations to the Art Gallery of Toronto (which is now called the Art Gallery of Ontario, or the AGO) earned him the legacy as the greatest collector of old master paintings in Canadian history. Wood was a major client of the famous English dealer, Sir Joseph Duveen (1869—1939). Letters between the collector and dealer remain at the Getty Archives, which have been sourced for this thesis to trace the origins of Wood’s collection. Documents from the Art Gallery of Ontario determine Frank’s role as a donor to the Gallery, and documents from the Avery Drawings & Archives at Columbia University demonstrate the designs of his Toronto Beaux-Arts estate by Delano & Aldrich. This thesis traces the evolution of Wood’s taste in art in the context of biographical details and larger historical events. This analysis demonstrates the maturation of Wood as a collector and Toronto as the cultural and financial epi-centre of Canada. An examination of Wood’s acquisitions in the context of North American collections from the Gilded Age to the Interwar era determines that Frank Wood was an exceptional collector amongst his Toronto peers, and his collection rivalled that of his most highly esteemed American counterparts.