About MacSphere

MacSphere is McMaster University's Institutional Repository (IR). The purpose of an IR is to bring together all of a University's research under one umbrella, with an aim to preserve and provide access to that research. The research and scholarly output included in MacSphere has been selected and deposited by the individual university departments and centres on campus.

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Students wishing to deposit their PhD or Masters thesis, please follow the instructions outlined by the School of Graduate Studies.

Communities in MacSphere

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Recent Submissions

COMPRESSION AND COMPUTATION METHODS FOR COMPUTER-GENERATED HOLOGRAPHY
(2026) Shima Rafiei
Holographic displays provide an immersive visualization of three-dimensional scenes by reconstructing light wavefronts that preserve both amplitude and phase information. Computer-generated holography enables the numerical creation of holograms without complex optical setups, offering scalability for 3D content generation. However, conventional Computer-Generated Holography techniques face critical challenges in balancing computational cost, storage efficiency, and visual quality, hindering their use in real-time and resource-constrained applications. The first method employs a Haar wavelet decomposition to generate multilevel hologram representations. By incorporating object saliency, the approach emphasizes perceptually important regions while significantly reducing computation time during offline dataset generation. The second method explores the capability of Vector Quantized Variational Autoencoder with hierarchical latent spaces to effectively encode complex-valued holograms, achieving high-fidelity compression through training on the diverse InterfereI dataset. This framework provides a compact and robust hologram representation suitable for holographic applications. Building upon these advancements, the third contribution introduces our Rate Adaptive Vector Quantized Variational Autoencoder framework, designed to achieve flexible compression within a single network. Our proposed network delivers high-quality reconstructions in real-time for phase-only hologram at both low and ultra-low bit rates, outperforming a state-of-the-art method on the natural image dataset of Div2K with a BD-Rate reduction of $-33.91% and a BD-PSNR improvement of 1.02 dB. The proposed method paves the way toward practical and scalable holographic systems for next-generation 3D display technologies, such as virtual reality near-eye display.
SAFETY ENHANCEMENT OF AI-ENABLED AUTONOMOUS VEHICLE ARCHITECTURES VIA ASSURANCE CASE DESIGN ANALYSIS
(2026) Faron, Arthur
The exponential advancements in Artificial Intelligence (AI) capabilities in recent years have sparked rapid integration of this technology within the automotive industry via the addition of numerous autonomous vehicle control features. Despite these features being touted for the safety improvements they provide, AI-enabled feature development remains largely focused on performance with less research being done on corresponding safety systems. This work makes use of an existing Connected & Automated Vehicle (CAV) architecture designed and developed for the EcoCAR EV challenge - a collegiate vehicle engineering competition sponsored by the United States of America (USA) Department of Energy (DOE), General Motors (GM), and Mathworks. The CAV architecture makes use of AI-enabled perception algorithms without appropriate mitigation strategies required in safety-critical systems to cover hazards inherently introduced by AI as this was beyond the scope of the competition. An assurance case is used to argue the safety of the vehicle within the context of the competition, and to identify perceived points of failure from a system safety perspective. A modified CAV architecture inspired by the Perception Simplex architecture [Bansal et al., 2024] is proposed which introduces a parallel perception safety layer using the same sensor data and comprised exclusively of deterministic algorithms. The safety layer compares its output to that of the high-performance AI-powered layer and overrides vehicle control commands if discrepancies are found. This proposed architecture was designed to meet the constraints of the EcoCAR competition. A second assurance case was constructed to outline the assumptions and supporting evidence required to demonstrate the safety of the proposed architecture. This thesis aims to document the feasibility of rendering existing AI-enabled systems fault-tolerant, the usefulness of assurance cases as tools to guide the iterative design process of complex safety critical systems, and the practicality of using assurance cases to justify the safety of these systems throughout their development timeline.
Bodyweight Supported Treadmill Vs. Overground Walking Effects On Gait And Quality Of Life In Multiple Sclerosis: A Proof Of Concept Study
(2026) Oliphant, Nathan; Kobsar, Dylan
Multiple Sclerosis (MS) often leads to difficulties with walking, balance, and daily mobility. Rehabilitation programs that reduce fall risk while promoting active walking may be important for maintaining function. Bodyweight supported (BWS) treadmill training is frequently used in rehabilitation, yet BWS overground walking, which more closely resembles real-world mobility, has received far less study. The purpose of this thesis was to examine the feasibility of an eight-week BWS overground training intervention in people with MS and to compare its effects with BWS treadmill training on functional mobility, gait, and self-reported outcomes. This proof-of-concept study used a crossover design in which five adults with MS completed sixteen sessions of both BWS overground and treadmill training. Attendance and missed-session reasons were recorded, and participants completed balance confidence and quality-of-life questionnaires, as well as timed functional mobility tests and free-living activity monitoring during each intervention phase. Participants attended most training sessions, and no statistically significant difference in attendance was observed between interventions, demonstrating that BWS overground training was feasible for individuals with MS. Across both interventions, changes in functional mobility, gait metrics, and self-reported outcomes were generally small, and no statistically significant differences were detected between the treadmill and overground conditions. Effect sizes suggested mostly negligible to moderate improvements, depending on the measure. Exploratory analyses considered participant preference and suggested that individuals tended to perform better on the modality they preferred, indicating that personal comfort or perceived suitability may influence response to training. Overall, this study provides initial evidence that BWS overground training is feasible and produces functional outcomes comparable to BWS treadmill training. These findings support continued investigation into overground BWS training and highlight the potential value of individualized rehabilitation approaches. Future research should explore how training progression, patient preference, and specific exercise strategies can optimize mobility and quality-of-life outcomes in people living with MS.
Policy Scan for the Financially Assisted Social Prescribing Initiative
(Prepared by the McMaster Research Shop for Canadian Red Cross, 2025-05) Saini, Amandeep; Okpalugo, Kamsi; Munir, Mehnaz; Corbett, David; Kalmin, Josh; Jia, Annie
In Hamilton, CRC is implementing a three-phase Financially Assisted Social Prescribing (FASP) intervention. Social prescribing aims to integrate health and social services to recognize and address the social determinants of health, in addition to caring for direct medical needs. As the project moves into implementation, CRC seeks to understand the policy landscape across municipal, provincial, and federal levels to align the intervention with relevant frameworks, especially those supporting equity-deserving populations and adapt accordingly.
"If you can see me, you can be me": Documenting the impacts of a Black entrepreneurial support program in Hamilton
(Prepared by the McMaster Research Shop for BLK Owned, 2026-10) Cheetu, Shruti; Abdella, Sabrina; Amer, Rand; Kanwar, Priyanshita; Shen, Nianzu; Gravely, Evan
BLK Owned is a Black-led, community-based nonprofit founded in 2020. The organization aims to support Black entrepreneurs across Southwestern Ontario by reducing systemic barriers and fostering economic empowerment through programs rooted in cultural identity and community connection. In 2025, as part of its five-year anniversary, BLK Owned partnered with the McMaster Research Shop to collect data on its impact. This project aimed to elicit both the individual and regional impact of the organization directly from BLK Owned program participants and supporters.

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