Open Theses and Dissertations
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Item Open Access Ontology-Enhanced Automated Machine Learning(2024-11-20) Davies, Cooper T.S.; Denzinger, Jorg; Maurer, Frank; Jacob, Christian; Walker, Robert; Dick, Scott; Boyd, JeffreyThis thesis addresses the challenge of bridging the gap between traditional Problem-Specific Machine Learning (PSML) and Automated Machine Learning (AutoML) systems. While PSML offers high accuracy but demands substantial expertise, AutoML aims to auto-mate the process of building a machine learning (ML) model but often lacks domain-specific knowledge. To address this, we propose Ontology-Enhanced AutoML, a novel approach that integrates domain knowledge from ontologies into the AutoML pipeline. We first examine the current landscape of AutoML, highlighting the complexities faced by a system in selecting appropriate algorithms and hyperparameters. We identify the limitations of existing AutoML systems, particularly their blind reliance on datasets, which often leads to poor performance and lengthy training times. Our thesis presents experiments demonstrating the effectiveness of Ontology-Enhanced AutoML in mitigating these challenges. By incorporating mechanisms for ontology-based feature extraction and example filtering, we demonstrate significant improvements in accu-racy and optimization time compared to traditional AutoML. These results highlight the potential of Ontology-Enhanced AutoML to provide a wide range of systems lying between the extremes of PSML and AutoML. This thesis contributes not only a technical solution but also a conceptual framework for understanding ML as a spectrum. We discuss implications for future research and the potential for further advancements in bridging the gap between domain expertise and ML proficiency.Item Open Access Single-player to Two-player Knowledge Transfer in Atari 2600 Games(2024-11-18) Saadat, Kimiya; Zhao, Richard; Abou-Zeid, Hatem; Aycock, JohnPlaying two-player games using reinforcement learning and self-play can be challenging due to the complexity of two-player environments and the potential instability in the training process. It is proposed that a reinforcement learning algorithm can train more efficiently and achieve improved performance in a two-player game by leveraging the knowledge from the single-player version of the same game. This study examines the proposed idea in ten different Atari 2600 environments using the Atari 2600 RAM as the input state. The advantages of using transfer learning from a single-player training process over training in a two-player setting from scratch are discussed, and the results are demonstrated in several metrics, such as the training time and average total reward. Finally, a method for calculating RAM complexity and its relationship to performance after transfer is discussed. Results show that in most cases transferred agent is performing better than the agent trained from scratch while taking less time to train. Moreover, it is shown that RAM complexity can be used as a weak predictor to predict the transfer's effectiveness.Item Open Access Exploring Public Expectations of Care and Communication in Intensive Care Units: A Cross-sectional Web-based Survey(2024-11-18) Trotter, Bethany Therese; King-Shier, Kathryn; Cuthbert, Colleen; Banner- Lukaris, DavinaBackground Explaining critical illnesses to family members or support persons of patients admitted to an Intensive Care Unit (ICU) is a sensitive and challenging duty for healthcare providers (HCPs). Current literature indicates that families often report insufficient and inadequate communication from critical care staff, leading to stress, anxiety, and sometimes even post-traumatic stress disorder (PTSD). Inaccurate media portrayals of ICU care and healthcare further contribute to unrealistic expectations, resulting in a mismatch between family expectations and the reality of care in ICUs. Objective This study aimed to identify and understand the public’s expectations of ICU care and communication if they were a family member or support person of an ICU patient. Methods A 36-question online survey of the Canadian public (n=489) was conducted to explore their expectations should they have a family member admitted to an ICU. The currently used and validated Family Satisfaction in the ICU (FSICUR-24) tool was used as a basis for the survey in this study, with the questions amended to be public facing. Participants were recruited through social media. The inclusion criteria required participants to be Canadian citizens or residents, over 18 years old, and could not have had any previous exposure or experience in ICUs. Results Participants expressed high expectations for substantial emotional support, frequent and clear communication from all specialties of HCPs, compassionate care, and a supportive physical environment. Recommendations for practice based on these findings include improving family conversations by managing expectations, expanding ICU HCP education, and procuring organizational support. Conclusions The public holds high expectations of ICU care, particularly regarding communication and support. Understanding these expectations can help improve families’ experiences, foster better communication, and improve patient and family-centred care in ICUs.Item Open Access Improving Stroke Clinical Trials with Medical Imaging and Advanced Algorithms(2024-11-18) Charatpangoon, Pattarawut; MacDonald, M. Ethan; Ganesh, Aravind; Bayat, Sayeh; Menon, Bijoy; Murari, KartikeyaClinical trials are essential for advancing healthcare by exploring new treatments to improve patient outcomes. However, recruiting eligible participants for trials remains a significant challenge, particularly in acute conditions like stroke. Stroke is a leading cause of mortality, and timely treatment is critical. While recruiting patients for stroke trials is essential, manual screening for trial eligibility can be slow, prone to errors, and costly. Additionally, the complexity of trial inclusion criteria and the need for rapid decision-making in emergencies make it unrealistic for clinicians to be aware of all ongoing trials. This thesis focuses on three key areas to enhance both the quality and quantity of stroke trial recruitment: 1) the development of automated matching algorithms to improve the number and quality of enrollment; 2) reducing radiation doses in computed tomography perfusion (CTP) imaging to keep patients safer; 3) implementing a multi-site data harmonization pipeline on CTP images to improve the quality of data and ensure consistent and comparable results. The results show that the automated algorithms could quickly and accurately identify eligible participants, reducing human error and bias. The post-processing denoising algorithm effectively reduced the radiation dose by up to 80% while retaining most clinical features. For the harmonization, the variations between sites were mitigated, ensuring more consistent and reliable imaging data. In conclusion, these studies have potential implications that could enhance both the quality and quantity of stroke clinical trials, accelerating medical advancements and promising to improve the outcomes for stroke patients.Item Open Access The Transition to Net-Zero of Heavy-Duty Road Freight in Alberta: A Scenario Model(2024-11-18) Redick, Zachary Campo; Layzell, David B.; de Barros, Alexandre; Heshami, Seiran; Kattan, LinaThe global climate crisis has prompted Canada’s commitment to achieving net-zero greenhouse-gas (GHG) emissions by 2050. The transportation sector, responsible for ~25% of Canada's GHG emissions, faces challenges in decarbonizing heavy-duty vehicles (HDVs), which make up ~20% of transportation emissions. Alberta’s heavy-duty trucking industry, a significant emissions contributor, encounters challenging conditions with strict range and vehicle weight requirements, complicating efforts to decarbonize. This thesis models the transition of Alberta’s heavy-duty trucking sector to net-zero GHG emissions, evaluating the feasibility of meeting Canada’s federal targets of 35% zero-emission vehicle (ZEV) sales by 2030 and nearly 100% by 2040. A comprehensive stock and flow model for hydrogen fuel-cell electric vehicles (FCEVs) and battery electric vehicles is developed, integrating vehicle projections, kilometers traveled, energy use, and GHG emissions under different decarbonization scenarios. The study also explores the development of a hydrogen-based value chain for Alberta's long-haul trucking industry, addressing the economic, logistical, and technical challenges of building infrastructure to support FCEVs. The economic analysis compares the total cost of ownership (TCO) for FCEVs and internal combustion engine vehicles (ICEVs) and examines the role of government policies, particularly the carbon tax, in supporting the transition. Key findings indicate that meeting the 2030 sales target is unlikely due to infrastructure and deployment challenges, while the 2040 target, though challenging, remains feasible. The extended timeline allows for the development of zero-emission vehicle technologies and hydrogen infrastructure, providing substantial GHG emission reduction benefits of at least 87% across all scenarios. FCEVs initially have a higher TCO than ICEVs, but as production scales and technology improves, the TCO is projected to fall below ICEVs by 2045. Incremental costs are projected to peak at CAD 500 million annually by 2035, achieving cost parity by 2040, and resulting in total costs of CAD 4 billion, with potential savings of up to CAD 2.5 billion annually by 2050. The projected carbon tax revenue covers the incremental costs, and even if doubled, would require only 75% of the revenue, demonstrating the strong economic feasibility of this beneficial and essential transition.Item Open Access AestheticID: Human Identification Using Audio-Visual Preferences(2024-11-14) Iffath, Fariha; Gavrilova, Marina; Sousa, Mario Costa; Tepperman, CharlesOver the last decade, Online Social Media platforms have witnessed a substantial expansion due to the extensive reliance of individuals on these communication channels. These platforms are widely utilized to convey emotions, share opinions, and express preferences through various means such as artworks, multimedia content, and blogs. These individual-specific traits have a wide range of applications such as personalized recommender systems, human behavior analysis, human-computer interaction, robotics, and biometric security. Aesthetic biometric systems utilize users’ unique preferences towards various subjective forms such as images, music, and textual content. This study introduces a novel deep learning-based multi-modal aesthetic system, with a primary contribution to the development of an attention-based fusion method for person identification. The proposed identification system leverages a deep pre-trained model for high-level feature extraction from visual and auditory modalities. The paper introduces a novel fusion architecture named attention-based residual fusion network (ARF-Net) to incorporate two heterogeneous aesthetic modalities. The proposed system is validated on two proprietary aesthetic datasets outperforming the existing state-of-the-art aesthetic biometric systems for person identification. The proposed architecture stands out for its efficiency, showcasing a lightweight architecture with minimal parameters, ensuring optimal performance across multiple aesthetic modalities.Item Open Access Maternal Metabolism and Pregnancy: Predicting Pregnancy Outcomes Using Metabolomic Assessment(2024-10-31) Han, Ying Chieh; Shearer, Jane; Slater, Donna; Manske, Sarah; Duggan, GavinDespite the significant health risks preterm birth poses to both mothers and babies, assessing the risk remains challenging due to its heterogeneous nature. Common risk factors, such as personal health history or lifestyle habits, have had some success in identifying at-risk mothers. However, their effectiveness is limited in asymptomatic and niche populations that lack distinct, identifiable preterm traits. Recent efforts have shifted toward exploring metabolic biomarkers for preterm prediction, aiming to capture the metabolic changes occurring during gestation. Nevertheless, most targeted compounds in these studies have been chosen based on their association with other underlying conditions, such as obesity or uterine disorders. With advancements in computational methods, particularly in machine learning, prediction models based on high-dimensional data have emerged as a promising new approach. This project aims to explore metabolic signatures associated with preterm birth by leveraging machine learning and untargeted metabolomics. We analyzed third-trimester serum samples from primigravid participants—first-time mothers—enrolled in the All Our Families (AOF) Cohort. Significant reductions in acylcarnitines and amino acid derivatives were identified, with various acylcarnitines, particularly butenylcarnitine, notably reduced in preterm mothers. These metabolites proved effective in predicting preterm birth, as shown by receiver operating characteristic (ROC) analysis. Next, we compared the performance of six different machine learning models in predicting preterm birth across a broader population from the AOF cohort, using Shapley Additive Explanations (SHAP) analysis to evaluate feature importance. We also assessed the impact of resampling techniques, such as bootstrapping. Linear models, including PLS-DA and linear logistic regression, demonstrated moderate predictive performance, while non-linear models like XGBoost and artificial neural networks (ANN) showed a slight advantage. Bootstrapping improved model accuracy and predictive strength, with varying degrees of enhancement across different models. Among the models tested, the bootstrap-resampled XGBoost model was the top performer in predicting preterm birth. SHAP analysis consistently identified acylcarnitines as the most significant class of metabolites in preterm prediction, with kynurenic acid also emerging as a contributing metabolite in several models following bootstrapping. The observed alterations in acylcarnitines suggest possible disruptions in lipid transport and energy metabolism in preterm mothers. The modeling results underscored the complexity of preterm prediction, while resampling techniques proved effective in mitigating the overtraining and low-variance challenges posed by the small sample size. This project introduces a novel approach to predicting preterm birth based on a combination of metabolites. As preterm birth continues to present significant risks to fetal health, the development of newer and more effective prediction models could improve maternal and fetal outcomes.Item Open Access A Weighted Multilevel Monte Carlo Method(2024-11-07) Li, Yu; Ware, Antony; Qiu, Jinniao; Swishchuk, AnatoliyThis thesis begins by introducing the Weighted Multilevel Monte Carlo (WMLMC) method in a one-dimensional context, expanding upon the established Multilevel Monte Carlo (MLMC) method. The focus is on demonstrating that the WMLMC method provides even greater computational savings compared to the traditional MLMC method, which has already shown superior efficiency over the standard Monte Carlo (MC) approach under similar conditions. In the second part, we apply a mixed Partial Differential Equation (PDE)/Weighted Multilevel Monte Carlo (WMLMC) method to the pricing of Double-No-Touch options. We compare these results with those obtained using a mixed PDE/Multilevel Monte Carlo (MLMC) method. The analysis reveals a significant reduction in total computational costs when substituting the MLMC method with the more efficient WMLMC method. This finding prompts us to explore the broader applicability of the WMLMC method as a superior alternative to the MLMC method across various domains, anticipating substantial cost savings in computational tasks traditionally dominated by the MLMC approach. The adoption of the WMLMC method is expected to optimize resource utilization and enhance computational performance, making it a promising avenue for future research and application in diverse fields beyond options pricing. The third part integrates the WMLMC method with one-step Richardson Extrapolation (RE), resulting in a considerable boost in efficiency from a convergence standpoint. A comparative analysis highlights this computational advantage, demonstrating that the WMLMC method with one-step RE achieves the greatest reduction in computational cost. This approach could potentially be extended to combine WMLMC with multi-step RE for even greater efficiency. In the final section, we present the Weighted Multi-Index Multilevel Monte Carlo (WMIMLMC) method designed for a multi-dimensional setting, building on the Multi-Index Monte Carlo (MIMC) method. By utilizing high-order mixed differences instead of first-order differences, the WMIMLMC method significantly reduces the variance of hierarchical differences while adhering to similar assumptions as its predecessors. We provide a 2-dimensional example to showcase the computational advantages of the WMIMLMC method.Item Open Access Cross-sectionally Exploring Proxy Usage for Historical Data Analysis: A Proof of Concept(2024-11-01) Adeboye, Promise Anjolaoluwa; McDonald, Sheila; Suzanne, Tough; Patten, Scott; Holodinsky, JessalynIntroduction: Longitudinal cohorts routinely collect information that encompass many different aspects of the life course, but their analysis is often restricted to validated scales. Such validated scales are often routinely shifting to reflect contemporary understandings of important concepts. Such routine changes often mean that a present-day scale measuring a concept may be incomparable to a different scale measuring the same concept in previous time-points. This restriction greatly hampers the strength of longitudinal cohorts in being able to make comparisons across time points. In this problem lies an opportunity to create a method of proxy development such that the proxy would be impervious to scale evolution over time. Flourishing is a common, well-studied concept that is a good candidate for this proof of concept. This thesis explores the use of proxy measurements as an optimization procedure for longitudinal cohorts going forward. Methods: As a proof of concept, two methods were explored for proxy creation using the test concept of flourishing. Using a bootstrapped linear regression approach, the proxy models were evaluated on performance metrics. Discussion: Although the proxy models performed similarly, the interpretation of results differed per model. Through the development of a flourishing proxy based on available data, it is possible to quantify historical flourishing, such that associations can be made between that and other concepts. Due to the context of the model derivation, the coefficients of either models cannot be extrapolated to other cohorts, but the coefficients of the knowledge-driven model can be furthur validated temporally within the derivation cohort. The included variables from both proxies contribute to the conceptual understanding of flourishing, but only in this specific cohort. Conclusion: Proxy derivation methods have the capacity to increase the value-add of historically collected data. However, more evaluations and validations of both the coefficients and the derivation method are needed before this can be used as a finalized procedure.Item Open Access Long-Term Opioid Prescribing among Patients Living with Metastatic Cancer as a Chronic Disease(2024-10-28) Harsanyi, Hannah; Cuthbert, Colleen; Yang, Lin; Lau, Jenny; Cheung, Winson Y.Patients living with metastatic cancer often experience pain which requires involvement of palliative care and symptom management teams. Opioids are a commonly used tool for the treatment of this cancer-related pain. While opioids serve an important purpose in symptom management and end-of-life care, harms related to their use are increasingly recognized as having a significant impact on patients with cancer. This changing perception has resulted from a growing body of literature investigating opioid-related harms, such as long-term prescribing, opioid-related healthcare utilization, and nonmedical use within cancer populations. However, many of these studies exclude patients with metastatic disease, and very few specifically investigate this population. The work reported in this thesis aims to address this knowledge gap by reviewing perceptions of opioid use among patients with metastatic disease, investigating the incidence of opioid-related hospitalizations and emergency department visits among recipients of long-term opioid prescribing, and determining the contribution of nonmedical opioid use to these encounters. Based on a review of previously published literature, stigmatization of opioid use was identified as a significant barrier to effective cancer pain management. Patients reported fears of addiction, tolerance, and side-effects which led to opioid-restricting behaviours. Despite these reported concerns, a large proportion of patients in Alberta received long-term opioid prescribing, with 23% of opioid-naïve patients with chronic metastatic disease being affected. Among these patients, the incidence of opioid-related healthcare encounters was higher than that reported in other cancer populations and was significantly associated with higher dosage and concurrent prescribing of psychoactive medications. Increased implementation of harm-reduction measures may be useful to mitigate this risk. From reviewing medical records of patients who experienced opioid-related healthcare encounters, nonmedical opioid use was identified as a possible contributing factor for 35% of patients. However, a majority of encounters were not primarily attributable to nonmedical opioid use and many patients experienced poorly controlled pain and displayed possible manifestations of opioid stigma. While risk assessment for nonmedical opioid use is important for patients receiving long-term opioid prescribing, it should be conducted in a non-stigmatizing manner which encourages patients to prioritize effective management of their pain.Item Open Access Identifying Somatic Variants using DNA Derived from Stereo-Electroencephalography Electrodes in Patients with Focal Epilepsy(2024-11-04) Mascarenhas, Rumika; Klein, Karl Martin; Tarailo-Graovac, Maja; Kurrasch, Deborah; Wiebe, SamuelBrain somatic variants play a crucial role in the etiology of focal epilepsy. Detecting these variants is challenging due to their presence in a subset of cells, resulting in a reduced variant allele frequency (VAF). Traditional methods rely on brain tissue obtained during resective epilepsy surgery, limiting accessibility and applicability, especially in patients with non-lesional epilepsies who are less likely to undergo surgery. In response to these limitations, a novel approach utilizes DNA extracted from depth electrodes employed in stereo-electroencephalography (SEEG) procedures. This method offers several advantages over resected brain tissue, such as the inclusivity of patients not undergoing surgery and access to multiple brain regions through implanted depth electrodes. Recent studies demonstrated the feasibility of detecting somatic variants using SEEG-derived DNA, highlighting its potential in non-lesional epilepsies. However, challenges remain, including potential cell contaminations and lower cell yields, necessitating DNA amplification that introduces associated artifacts. This thesis introduces an improved SEEG harvesting protocol addressing these issues. Our optimized technique purifies neuronal nuclei, mitigating cell contaminations, and incorporates a newer amplification method to minimize artifacts. Additionally, the thesis introduces the implementation of quality control steps for sample selection and a bioinformatic workflow to reduce artifactual and false positive variants, enhancing the reliability of downstream variant identification. With these improvements, this project aims to enhance the reliability and applicability of SEEG-derived DNA in understanding the molecular basis of focal epilepsy, paving the way for diagnosis and improved treatment strategies.Item Open Access Ultrasound Mediated Mild Hyperthermia Resolves Neuroinflammation in an Animal Model(2024-11-01) Seasons, Graham; Pike, Bruce; Kuipers, Hedwich; Pichardo, Samuel; Dunn, JeffChronic neuroinflammation is an often overlooked aspect of the development of neurodegenerative and autoimmune disease, especially in older populations, and there are few treatments capable of addressing this type of inflammation. We sought to address this gap by following up on our clinical finding where focused ultrasound resolved chronic radiation-related neuroinflammation Using ultrasound-mediated mild hyperthermia to treat chronic neuroinflammation in a preclinical mouse model, we investigated the impact on the immune response, and the resolution of inflammation. Seven days after peripheral infection, we targeted the mouse midbrain with focal hyperthermia (4 mins at 39 oC and 6 mins at 42 oC). Proteomic changes were analyzed, and demonstrated that hyperthermia reduced inflammation in female mice 24 hours after treatment, alleviating blood brain barrier disruption, antigen presentation, and anti-viral signalling. In contrast, male mice did not show a change in inflammatory mediators at 24 hours, but showed an upregulation in proteins associated with the heat shock response, chromatin maintenance, and chaperone mediated autophagy. At the cellular level, microglia and astrocytes demonstrated homeostatic phenotypes seven days after hyperthermia treatment in both males and females. We also investigated the role of the immunosuppressive CD200/CD200R signalling pathway in immune resolution, and discovered that it is dysregulated in chronic neuroinflammation – exacerbating inflammation in males, while maintaining a resolving function in females. Ultrasound mediated mild hyperthermia was able to restore homeostatic CD200/CD200R signalling, alleviating the pro-inflammatory rewiring observed in males. Consequently, we demonstrate that ultrasound mediated mild hyperthermia is capable of restoring the homeostatic function of receptors, and resolving chronic neuroinflammation across pathology, through the induction of the heat shock response. We propose a new application of clinically approved magnetic resonance guided focused ultrasound systems in the treatment of chronic neuroinflammation, with the potential for rapid clinical translation.Item Open Access Urban design, climate + context: Exploring the interplay of thermal comfort and human perception in the case of Lahore, Pakistan.(2024-10-28) Mazhar, Naveed; Dall'Ara, Enrica; Sinclair, Brian Robert; Kenny, Natasha; Hachem-Vermette, CarolineWeather is arguably the most important human thermal comfort factor, both as an actual and perceived component, from a user's viewpoint. The user's received energy, real or presumed, is highly decisive in how well an outdoor space is used. The present study illuminates the human perceptual mechanisms involved in an urban open environment and human thermal comfort assessment, emphasizing hot climates. The primary objective is to identify underlying conditions influencing people's behaviour and usage of outdoor spaces. An in-depth literature review demonstrated that a physiological approach alone is inadequate in characterizing human thermal comfort conditions. Therefore, embracing a holistic approach, a novel conceptual model is proposed, aligning direct and indirect factors. The proposed model, Man vs. Machine, is a two-pronged approach focusing on qualitative and quantitative parameters. This study deciphered the effects of weather parameters (e.g., air temperature, wind, and solar radiation) and personal factors (e.g., place perception, emotions, sensations, and behaviours) on participants' emotional estimations of urban open spaces. Fused with the physical design components, the proposed model distinguishes the simultaneous and equal assessment of the two fundamental characteristics – empirical measurements and subjective human feelings. The study investigated four neighbourhoods – Mohallaz in the Walled City of Lahore, Pakistan. Users of urban open spaces are the fulcrum, and the intended Man vs. Machine conceptual framework is a robust side-by-side comparative analysis of the unique domains of urban microclimates, human psychology, and behaviour. The proposed study model handled only simple computations through the COMFA model to ensure quality results, such as charts of energy budgets and the total amount of radiation absorbed by a person ( Rabs) and a comparative analysis. At the collective level, the comparative charts based on site surveys informed the behavioural pattern(s) obtained from a 20-day field study comprising 800 respondents. At the individual level, cross-comparisons of thermal comfort and spatial perception helped derive theoretical and practical environment-behaviour relationship(s). The final results, derived from 800 studies, were categorized into two key factors: a) the site’s microclimate and b) the user’s spatial psychology. The analysis revealed that 65% of respondents (520 out of 800) sitting outdoors during summer felt satisfied with their experience. However, it is crucial to note that despite these perceptions of spatial satisfaction, 62% of the recorded time data indicated that respondents were vulnerable to danger or extreme danger of heat stress, according to the HTCI scale. The study determined that outdoor thermal discomfort is peripheral for users compared to the sense of place factor. The motivational factors with the most demonstrable impact on human spatial perception(s) and outdoor open space usage are space uniqueness, spatial affinity and individual features of traditional Mughal architecture. The study is groundbreaking, unique, and unparalleled in the realm of hot-climate cities. It represents a substantial and valuable advancement in comprehending the psychological factors that impact human thermal perception and behaviour in urban environments, with implications for urban design. The results of this research aimed to change how architects and environmental behaviour experts approach urban design and improve the built environments by using design recommendations outlined in the research.Item Open Access Multi-Frequency Microwave Interactions of Snow-Covered Arctic First-Year Sea Ice(2018-08-20) Nanda Kumar Sreeletha, Vishnu Nandan; Yackel, John J.; Else, Brent G. T.; Hall-Beyer, Mryka C.; Kim, Jeong Woo; Tonboe, Rasmus TageIn this thesis, the thermophysical, dielectric and Ku-, X- and C-band polarimetric microwave properties of relatively smooth snow covered first-year sea ice (FYI), from late-winter to pre-early melt onset thermodynamic regime are investigated. Fully-polarimetric microwave backscatter data acquired from a unique, surface-based multi-frequency (Ku-, X- and C-band) scatterometer system is used near-coincident with in situ snow thermophysical measurements, to investigate thermodynamic and electrical state of snow covered FYI. Using a first-order microwave backscatter model, a multi-frequency framework is theoretically established to determine the dominant snow thermophysical properties sensitive to the modeled microwave backscatter, at Ku-, X- and C-band frequencies. Multi-frequency microwave observations acquired from the scatterometer system are then used to inter-compare with modeled backscatter, to investigate the potential of the surface-based system to determine the thermodynamic and electrical state of snow covered FYI, at diurnal and temporal scales, from late-winter to pre-early melt onset. A unique frequency-dependent polarimetric parameter is developed to characterize frequency-dependent changes in microwave backscatter, as a function of snow thickness, polarization and incidence angle. Theoretical and observational findings indicate significant influence of snow salinity affecting microwave propagation through snow covers on FYI, for all three frequencies. These findings are utilized semi-empirically to develop a thickness-dependent snow salinity correction factor to improve FYI freeboard and thickness measurement retrievals from space-borne radar altimeters, operating at Ku-band.Item Open Access Characterizing Physical and Hydrotechnical Properties of Sediments Surrounding Soap Hole Features Near Didsbury, Alberta, Canada(2024-10-22) Cunningham, Dylan Z.; Lauer, Rachel; Karchewski, Brandon; Hayley, JocelynSoap holes are discrete occurrences of fluidized sediments that have been reduced to zero effective stress resulting in quick conditions. These features can be detrimental to farming operations through evaporitic concentration of ions in surface sediments surrounding the features or by fatally trapping livestock. Currently, the sediment properties and subsurface conditions required to generate soap holes are relatively unknown. A site investigation conducted near Didsbury, Alberta, analyzed the geologic, hydrogeologic and geotechnical conditions surrounding four active soap hole features to improve the understanding of soap hole formation. Glacially derived surface sediments and Paskapoo formation bedrock were extensively analyzed using a combination electrical resistivity tomography (ERT), cone penetration testing (CPT), and sediment coring and sampling. Laboratory analyses were completed on recovered sediment samples to determine index properties, particle-size distribution, Atterberg consistency limits, dispersive properties and chemical composition. ERT transects indicated there are three distinct sedimentary units on-site, and bedrock depth of approximately 11-mbgs, which was confirmed by drilling. Near-surface sediments are primarily comprised of non-sensitive, over-consolidated fine-grained material, with medium to high plasticity, and are highly dispersive. Discontinuous coarse-grains sediments were also noted in the sediment core, potentially providing flow-paths through the extensive fine-grained sediments. Hydrogeologic conditions were analyzed utilizing pressure transducer data, manual water level measurements, CPT correlations, and single well response tests. Artesian conditions were confirmed within a soap hole feature that was instrumented on site and are suspected to persist in the surrounding features. Pore pressures within and below the instrumented feature correlate with regional potentiometric surface maps of the Paskapoo formation, suggesting hydraulic connection to deep groundwater flow-paths. Strong upward vertical gradients (>1-m/m) within the soap hole feature exceed the critical gradient of surrounding sediments. Downward vertical gradients less than critical were found in most background sediments surrounding the features. Overall, sediments at the study site did not have properties indicative of being prone to liquefication. However, results suggest that high pore pressures, dispersive soils and vertical hydraulic gradients exceeding sediment critical gradients are some of the primary formation mechanisms of the soap hole features.Item Open Access Design of Phase Shifters for Phased Array Antenna Applications(2024-10-24) Jebeli Haji Abadi, Ali; Ghannouchi, Fadhel M.; Ghannouchi, Fadhel M.; Helaoui, Mohamed; Belostotski, Leo; Fapojuwo, AbrahamThis thesis presents a method for reducing the complexity of the I-Q phase shifter. This new method is based on the I-Q phase shifter architecture, where the input signal is divided into two orthogonal paths. By adjusting the amplitude of these two signals and then combining them, a signal with a phase difference relative to the input signal is obtained. The variable attenuators used in this method must be adjusted based on the required phase shift, and these attenuators are controlled by the system's control unit through multiple control lines. By reducing the number of control lines in this phase shifter, we effectively decrease the complexity and load on the control section. In this work, we first introduce a Voltage Variable Gamma Phase Shifter. This phase shifter requires only one control line and provides continuous phase variation. In this approach, the input divider is replaced with a circulator, and the two attenuators are replaced with a single variable resistor. The variable resistor is a PIN diode, controlled by a single control line. This phase shifter was fabricated and tested at 3.45 GHz with a bandwidth of 300 MHz. It provided approximately 95 degrees of phase change, with insertion loss less than 14 dB. The limitation of this method is the circulator, which prevents its use in Microwave Monolithic Integrated Circuits (MMIC). To address this issue, we have developed the next version of this phase shifter. The second step in this thesis involves modifying the Voltage Variable Gamma Phase Shifter to make it suitable for MMIC applications. To achieve this, we replace the input circulator with a coupler. This method has its own pros and cons. Although this version can be used in MMIC applications, we do not have control over both paths, which means we will lose the ability to vary the phase. In this configuration, since we have control over only 50 percent of the input signal, we will lose at least 50 percent of the phase variation. This phase shifter has been fabricated and tested at 3 GHz with a bandwidth of 400 MHz. The final step is the MMIC version of this phase shifter. Using a GaN substrate and 250 µm technology, we designed the MMIC phase shifter using the process design kit (PDK) from United Monolithic Semiconductor (UMS).This phase shifter provides a phase variation of 40 degrees and a bandwidth of 400 MHz at 3.5 GHz, with an insertion loss of less than 8 dB. The dimension of the final version of this phase shifter is 2 by 1.6 mm.Item Open Access Associations between Neighbourhood Built Environment and Leisure and Transportation Physical Activity among Canadian-Born Residents and Recent and Established Immigrants in Canada(2024-10-22) Masihay Akbar, Hasti; McCormack, Gavin Robert; Turin, Tanvir Chowdhury; Olstad, Dana LeeDespite well-established health benefits, nearly half of adults in Canada do not engage in enough physical activity for optimal health benefits. In Canada there are differences in physical activity levels among immigrants and non-immigrants. The built environment has the potential to reduce or widen inequalities if its effects on physical activity differ among population subgroups. While evidence has highlighted potential differences in how the built environment is associated with physical activity across various population subgroups, some equity-seeking groups, such as immigrants, have received little research attention. Globally, most studies examining this association among immigrants have been conducted in the U.S., with inconsistent findings. The study presented in this thesis addresses these knowledge gaps, guided by two relevant theoretical perspectives, including the socioecological model and acculturation theory. The aim of this research was to generate novel evidence regarding the associations between the neighbourhood built environment, specifically objectively-measured walkability, and physical activity according to residency status (Canadian-born, recent immigrants, and established immigrants). Our objectives were 1) to estimate and compare TPA and LPA participation and duration between Canadian-born, recent and established immigrant adults and determine whether neighbourhood walkability accounts for any observed residency group differences, and 2) to estimate and compare the direction and magnitude of associations between neighbourhood walkability and TPA and LPA participation and duration between these groups. The study included cross-sectional analysis of nationally representative data from Canadian Community Health survey (CCHS 2017-2018) linked with 2016 Can-ALE data. We found that recent and established immigrants were more likely than Canadian-born to participate in TPA, but these differences attenuated after controlling for walkability. Moreover, recent and established immigrants were less likely to participate in LPA and undertook fewer LPA minutes, compared to Canadian-born individuals. However, the differences in LPA minutes attenuated after controlling for walkability. Walkability was positively associated with TPA participation and duration in all residency status groups, but the magnitude of these associations differed between these groups. Findings from this thesis suggest that improving neighbourhood walkability could have broad public health benefits, but tailored strategies are essential to address the needs of immigrant populations.Item Open Access Characterisation of universal qudit gates(2024-10-21) Amaro Alcala, David; Sanders, Barry Cyril; de Guise, Hubert; Emerson, Joseph; Simon, Christoph; Scandolo, Carlo Maria; Feder, DavidTo harness the potential of quantum computing, increasing the number of quantum units, a process known as scaling, is critical. Whereas qubits have traditionally been used as the units for quantum computing, the development of multi-level systems (qudits), which offer larger Hilbert spaces and advantages over qubits in cryptography and circuit complexity reduction, requires new methods to characterise the quality of quantum gates and ensure safe scaling. Randomised benchmarking offers a simple and inexpensive method for this characterisation. This thesis reports advances in the characterisation of universal single- and multi-qudit gates. I introduce the characterisation of universal qutrit gates through the definition of an optimal scheme that requires similar experimental resources as the standard method for non- universal gates. The feasibility of my qutrit scheme is tested numerically using parameters from experimental qutrit implementations. I then generalise my qutrit results and devise a general scheme for a qudit system with arbitrary d. Because using the same construction for qudits with d > 3 as in the qutrit case leads to more than two parameters, a different strategy was necessary. I note that my qudit characterisation obtains an estimate of the average error per gate; thus, this characterisation is collective. A more realistic characterisation requires estimating the average gate fidelity of a single non-Clifford gate. In the last part, I generalise my qudit method to individually, in contrast to the previous collective result, characterise non-Clifford gates. My schemes are relevant to at least two communities: experimental groups with a qudit platform, as my work effectively characterises a complete gate set, and randomised bench- marking theorists, who may be interested both in the gate set I introduce and in the schemes I developed.Item Open Access Nurses Experiences, Long-Term Care, and Covid-19(2024-10-17) Gruszecki, Holly; McGhan, Gwen; Venturato, Lorraine; McAffrey, Graham; Toohey, Ann; McGhan, Gwen; Venturato, LorraineThis master’s thesis explores the experiences of registered and licensed practical nurses working in long-term care both during, and in the immediate aftermath of the Covid-19 pandemic in Alberta, Canada. Using Van Manen’s Phenomenology as a guiding research methodology, semi structured interviews were conducted with registered and licensed practical nurses working in long-term care to explore the experiences of the participants. There were four common themes identified from the data: (1) fear and uncertainty, (2) workload, (3) burnout, and (4) resilience and adaptability. These themes have been explored in comparison to the literature with the intention to provide recommendations for future pandemics and the retention of a robust, healthy, and experienced workforce. As the healthcare landscape in Alberta approaches another period of change and flux with the introduction of a system wide restructure, these findings may relate to on-going change within the sector and the turbulence that nurses experience following change. In the wake of the pandemic, the experiences of nurses who battled through it can inform policy makers to implement policies that leverage the strengths of the long-term care nursing workforce.Item Open Access Improving Sidewalk Maintenance through Smartphone Citizen Reporting of Pothole Damage(2024-10-18) Sornsakul, Chavisa; Lichti, Derek; O'Keefe, Kyle; Radovanovic, Robert; Detchev, IvanPedestrian walkways potholes pose significant risks to pedestrian safety, causing accidents and disruptions. This thesis explores using Structure-from-Motion (SfM) 3D reconstruction with smartphone GNSS measurements to improve citizen pothole reporting, aiming to enhance local engagement, infrastructure management, and public safety. The methodology uses SfM camera poses recovered from citizen pothole image reports and relative positioning from smartphone GNSS measurements to resolve the scale ambiguity of SfM pothole models. The relationship between images and a reconstructed point cloud from the SfM technique estimates pothole quantity, perimeter, and maximum depth. Key contributions include developing an integrated system for accurate pothole dimension measurement, with a scale error of approximately 12% from reference measurements, and establishing data acquisition guidelines for assessing the reliability of citizen-reported data. This method results in pedestrian walkway pothole perimeters differing by approximately 35 cm and depths by less than 1 cm. A guide for citizens capturing pothole images is proposed.