Theses

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The theses in UWSpace are publicly accessible unless restricted due to publication or patent pending.

This collection includes a subset of theses submitted by graduates of the University of Waterloo as a partial requirement of a degree program at the Master's or PhD level. It includes all electronically submitted theses. (Electronic submission was optional from 1996 through 2006. Electronic submission became the default submission format in October 2006.)

This collection also includes a subset of UW theses that were scanned through the Theses Canada program. (The subset includes UW PhD theses from 1998 - 2002.)

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Compiler Support for Constant-Time Programs in LLVM
(University of Waterloo, 2025-07-21) Aghakishiyev, Mehdi
Side-channel attacks aim to extract sensitive information by monitoring the additional information generated during program execution, such as execution time or power consumption. Certain coding patterns, such as using secret data in control flow and memory addressing instructions, cause the execution time of the program to vary based on secret input, making the program vulnerable to timing-based side-channel attacks. Constant-time programming offers a defense against such attacks; however, it is difficult to implement manually as it requires tracking secret data through complex program logic. In this thesis, we propose an automated approach to generate constant-time programs based on static analysis and program transformations. First, we use taint tracking to monitor the flow of secret input through the program and mark branching and memory addressing instructions that depend on secret data. Then, we apply program transformation techniques such as branch linearization to remove these dependencies and produce constant-time code. We perform our analysis and transformations on LLVM IR and implement our tool as part of the LLVM Pass Infrastructure. To evaluate our tool’s effectiveness, we apply our analysis and transformations to programs from the OISA benchmark. We validate our results through BliMe, an architecture performing hardware-enforced taint tracking to prevent side-channel attacks.
Effect of Feedstock Powder, Processing Parameters, and Post-Heat Treatment on Cold-Sprayed Cu Alloys: Development of Heterogeneous Material
(University of Waterloo, 2025-07-17) Eftekhari, Niloofar
Cold spray (CS) is a solid-state powder deposition technique that utilizes high-velocity impact to bond particles onto a substrate or previously deposited layers in a layer-by-layer approach. This technology is extensively used for repairing high-performance components, protective and functional coatings, and 3D printing applications. However, a major challenge in cold spray additive manufacturing (CSAM) is understanding the relationship between feedstock powder characteristics and the final deposit properties. This thesis focuses on characterizing feedstock powders and analyzing the microstructure, physical properties, and mechanical behavior of cold-sprayed deposits. A key limitation in CS deposited materials is their low ductility. To address this, various strategies, including process optimization and post-deposition heat treatment, are explored to enhance their mechanical properties. Furthermore, a novel approach has been introduced to improve ductility through the fabrication of heterogeneous laminated structures, where alternating layers of hard and soft alloys create a microstructure with fine-grained and coarse-grained regions, ultimately enhancing the mechanical performance of CS deposits. To explore this, the cold-sprayability of various Cu powders produced by electrolysis, gas atomization, and grinding was examined and compared using scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), particle analysis (CAMSIZER, FT4 powder flow tester), and nano-hardness testing. The results indicated that the spherical morphology of gas-atomized powders had a lower surface area compared to the irregular-shaped electrolytic and ground powders, reducing surface interactions and improving powder flowability. Additionally, gas-atomized Cu powders with equiaxed grains exhibited an average nano-hardness value, balancing flowability and deformability. Therefore, these powders were identified as promising feedstock materials for CS applications. Furthermore, the impact of these powders on coating microstructure and mechanical properties was investigated. A comprehensive statistical model was developed to optimize process gas temperature and pressure for deposition. It was found that operating near the upper temperature and pressure limits of the low-pressure cold spray (LPCS) system resulted in coatings with minimal porosity, high flattening ratio, increased microhardness, and enhanced bonding strength. Surface and microstructural evolution analysis revealed that lower oxide content near the surface of more spherical, satellite-free powders significantly enhanced plastic deformation and grain refinement during deposition. Improving the mechanical properties of CS depositions for optimal strength and ductility under uniaxial tensile testing leads to the next step, which involves investigating the effects of different processing gases (Nitrogen and Helium) and post-heat treatment on pure Cu. The findings suggest that while Cu 3D-printed parts processed with He exhibit higher deposition efficiency, N₂-processed samples show greater plastic deformation and lower porosity due to the higher number of deposition passes and the peening effect required to achieve the same thickness as He-processed samples. Heat treatment, when applied at an appropriate temperature and duration, enhances interfacial bonding, promotes recrystallization, and facilitates grain growth, leading to strength and ductility improvements of up to 2.7 times and 28 times, respectively. Heat treatment also plays a critical role in defining the microstructure and mechanical performance of CSAM CuCrZr alloys, an area that remains less explored. The as-sprayed CuCrZr alloy exhibited weakly bonded particle interfaces and porosity, which were significantly reduced by solution annealing and age hardening (SA+AH). This process led to grain reorganization, interfacial healing, solid-state diffusion bonding and precipitation of ultra fine particles resulting in strength and ductility enhancements of up to 2.4 times and 9 times, respectively. Engineering heterogeneous microstructures has emerged as an effective strategy to enhance the mechanical behavior of materials processed through various thermomechanical and manufacturing techniques. However, this approach remains largely unexplored in 3D-printed cold-sprayed components. In this study, a dual heterogeneous laminated Cu/CuCrZr composite structure with varying interface spacing was developed using LPCS followed by post-heat treatment. This tailored microstructure consists of alternating coarse- and fine-grained regions, generating microstructural contrast that induces hetero-deformation-induced (HDI) strengthening. The mechanical incompatibility between the soft Cu and hard Cu-Cr-Zr layers enhances strength and ductility, with decreasing interface spacing improving strength and ductility by up to 10% and 28%, respectively. To further understand the strain hardening mechanisms, loading-unloading-reloading (LUR) experiments and microstructural analyses were conducted. The findings attribute the enhanced mechanical performance to well-bonded particles and HDI strengthening, driven by geometrically necessary dislocations (GNDs) at heterogeneous interfaces. This effect improves work-hardening capacity, leading to simultaneous increases in both strength and tensile ductility of the laminated alloy. While this innovative heterogeneous design strategy for cold-sprayed materials requires further exploration across various topologies, heat treatment methods, and alloy systems, it presents a promising approach to enhancing strength and ductility in low-pressure cold spray materials.
Variations in Laser-Induced Carbon from Structurally Varied Poly(furfuryl alcohol)
(University of Waterloo, 2025-07-17) Yip, Emily
The laser-induced graphene technique, wherein a polymer precursor is irradiated by a CO2 IR laser, provides a simple method for patterning of carbon materials like graphene or glassy carbon under ambient conditions. This is a highly attractive method of carbonization for applications in electronics and energy storage devices, and fine tuning of the laser-induced carbon’s properties is permitted by the choice of precursor. For example, glassy carbon with its disordered structure and defects is desirable for high-performance supercapacitors and so an appropriate precursor can be selected to form glassy carbon by laser irradiation instead of graphene. However, direct structure-property correlations between the precursor and the nature of the resulting laser-induced carbon as well as its quality are unclear. To investigate this, poly(furfuryl alcohol) (PFA), a glassy carbon precursor that is infamously comprised of several structural motifs aside from its monomer unit, was synthesized under a variety of reaction conditions to create three series with different key structural features and then laser irradiated to analyze the resulting carbon material. Typical laser-induced carbon formed from PFA is more akin to glassy carbon, though varied lasing parameters and structures can potentially enable graphenization. Three series of PFA were prepared which exhibit varying degrees of polymerization, extents of ring opening, and high thermal stability. The PFA chemistry had a notable influence on the quality of the resulting laser-induced carbon, which demonstrated a broad range of ordering from an amorphous structure to that with more crystalline graphitic domains. Correlations between the PFA structure and laser-induced carbon quality showed that the most ordered carbon material formed when the PFA crosslinking was minimal and had high thermal resistance. Further structural engineering of the PFA with these properties may then enable laser-induced graphenization of the precursor.
Engineering a Synthetic Bacterial Consortium of Escherichia coli and Pseudomonas putida for Mixed Plastic Monomer Bioprocessing
(University of Waterloo, 2025-07-17) Dharmasiddhi, Ida Putu Wiweka
Plastics are indispensable to modern life, but their widespread use has created an environmental crisis due to inefficient waste management. Mixed plastic waste, comprising diverse polymers, presents significant recycling challenges due to the high costs of sorting and processing, leading to ecosystem accumulation and harmful by-product generation. This study addresses this issue by engineering a synthetic bacterial consortium (SBC) designed to degrade mixed plastic monomers. The consortium pairs Escherichia coli Nissle 1917, which uses ethylene glycol (EG), a monomer derived from polyethylene terephthalate (PET), as a carbon source, with Pseudomonas putida KT2440, which metabolizes hexamethylenediamine (HD), a monomer from nylon-6,6, as a nitrogen source. Adaptive evolution of the SBC revealed a novel metabolic interaction where P. putida developed the ability to degrade both EG and HD, while E. coli played a critical role in degrading glycolate, mitigating its by-product toxicity. The evolved cross-feeding pattern enhanced biomass production, metabolic efficiency, and community stability compared to monocultures. The consortium’s performance was validated through constraint-based modeling, high-performance liquid chromatography (HPLC), and comprehensive growth assays. These findings highlight the potential of cross-feeding SBCs in addressing complex plastic waste, offering a promising avenue for sustainable bioremediation and advancing future polymer degradation strategies.
Projector Calibration via Overlapping Point Cloud Distance Minimization
(University of Waterloo, 2025-07-16) Ayee Goundar Venkatesan, Pranav Kumar
Projection mapping is a technique that transforms any 3D surface into an interactive display by projecting visuals that conform to the surface’s shape. Camera and projector calibration is a fundamental prerequisite for accurate spatial measurement and perception in projection mapping. The calibration of projectors is necessary to ensure that they correctly map the surface they are projecting onto. An accurately calibrated projector will have the image projected perfectly in line with the intended surface, without any misalignment. Such alignment is important for a number of applications, one of which is projection mapping, in which multiple projectors are used to create immersive visual displays on complex surfaces such as buildings, stages, or statues. Since projector calibration involves highly nonlinear relationships between the projector's parameters, a nonlinear optimization is required. Typically such optimizations include reprojection error as the objective functions, which is also one of the most commonly used objective function to calibrate projectors. However, in scenarios where there is a lack of ground truth reprojection error fails to accurately align the multiple overlapping projector point clouds, resulting in visible gaps between them instead of forming a continuous surface. To address this issue, this thesis proposes a multi-step optimization with a novel global objective function. To analyze its robustness, the proposed optimization is tested both on simulated and on multiple real world configurations. Experimental results show that the proposed approach achieves higher calibration accuracy compared to existing methods, while also maintaining low runtime. The proposed multi-step optimization process parameterizes the calibration problem as a function of the degree of stereo overlap to improve accuracy. The stereo overlap plays a key role in projection mapping, influencing calibration accuracy and system cost. Understanding the relationship between stereo overlap and calibration error allows for reducing overlap while maintaining acceptable accuracy, thus reducing the number of cameras needed and cutting costs. In summary, this thesis introduces a novel global objective function that minimizes the distance between overlapping projector point clouds, rather than relying solely on reprojection error. It also provides insight into the required overlap between devices, including both cameras and projectors, helping to achieve higher accuracy while efficiently covering an entire projection surface that may not be uniform.
Exploring Menopause Through a Cultural Lens: Beliefs, Perceptions, and Experiences of Immigrant Punjabi Women in the Peel Region
(University of Waterloo, 2025-07-16) Randhawa, Tanveer
Background: Menopause, despite being a pivotal stage in a woman’s life, is not a uniform experience. For immigrant Punjabi women, it is shaped by challenges influenced by their socio-cultural backgrounds, beliefs and social norms (Zou et al., 2023). In addition to the complexities introduced by migration, language barriers, social marginalization, and a lack of culturally relevant healthcare services often contribute to unmet needs of immigrant Punjabi women. While existing literature highlights how menopause is shaped by cultural and social factors, the experiences of South Asian immigrant women – particularly Punjabi women in Canada – remain unexplored. This study seeks to address this gap by exploring the beliefs, perceptions, and lived experiences of menopause among immigrant Punjabi women in the Peel Region, with the goal of informing how cultural humility and tailored healthcare approaches can enhance menopausal care for this population. Research Questions: What are the beliefs and perceptions of immigrant Punjabi women in the Peel Region regarding menopause, and how do these shape their lived experiences of this transition? How do cultural practices, social norms, and immigration experiences influence the perceptions and management of menopause? What insights from their experiences can inform culturally responsive practices to better address their needs? Methods: This qualitative study employed a Constructivist Grounded Theory (CGT) methodology to explore the experiences of menopause among immigrant Punjabi women aged 35 and older who have lived in the Peel Region for at least five years. Thirteen semi-structured interviews were conducted in either English or Punjabi, depending on participant preference, to ensure linguistic and cultural comfort. Interviews were audio-recorded, transcribed, and translated by the researcher to preserve cultural nuance. Data were analyzed inductively through the CGT process of initial coding, focused coding, and axial coding, allowing themes, and analytical categories, to emerge from participants’ narratives. Reflexivity and attention to positionality were prioritized throughout, recognizing the co-constructed nature of meaning between the researcher and participants. Findings: Three interconnected core themes emerged from the data: (1) Silenced and Stigmatized: Cultural Taboos and Lack of Menopause Education, (2) Navigating Menopause in Isolation: Gender Roles, Migration, and Social Expectations, and (3) Seeking Support and Self-Advocacy: Pathways to Empowerment and Care. Participants described menopause as a topic shrouded in silence, often associated with shame and misinformation in their upbringing. Many women felt unprepared and unsupported, facing the transition in isolation while juggling familial responsibilities, caregiving roles, and the pressures of migration. However, some participants emphasized the importance of informal peer networks and expressed a desire for culturally safe, linguistically appropriate, and holistic care. These narratives reflected a tension between traditional cultural expectations and the evolving understanding of health and aging in a new socio-cultural context. Conclusions: This study provides an in-depth, intersectional understanding of how immigrant Punjabi women experience menopause within the complex contexts of culture, gender, and migration. The findings underscore the urgent need for culturally responsive healthcare services that acknowledge the social realities and cultural frameworks of immigrant communities. By promoting cultural humility among healthcare providers and engaging in community-informed education initiatives, it is possible to reduce stigma, improve early intervention, and support immigrant women in navigating menopause with dignity and agency. This research contributes to the broader discourse on reproductive aging and equity in healthcare by centering the voices of a marginalized population whose experiences have been largely overlooked.
Novel 1,4-Diazepane Derivatives as Amyloid Beta (Aβ) Aggregation Inhibitors
(University of Waterloo, 2025-07-16) Karuturi, Rahul Chowdary
Alzheimer’s disease (AD) is a progressive and irreversible neurodegenerative disease that represents one of the most pressing medical and social challenges of our time. Characterized by cognitive decline and memory loss, AD is primarily driven by the accumulation of amyloid-β (Aβ) plaques and tau tangles in the brain. The Aβ aggregation is indeed the primary pathological event, playing a key role in the initiation and progression of the disease. Despite extensive research, effective disease-modifying treatments remain elusive, and current therapies offer only symptomatic relief. While monoclonal antibody therapies targeting Aβ have emerged as a potential treatment option, their clinical effectiveness is limited. Small molecules, however, represent a more versatile and economical approach, with the potential for targeted action within the brain. In this regard, this thesis focuses on the design, synthesis, and biological evaluation of small molecules that specifically target Aβ aggregation, aiming to identify effective therapeutic candidates for AD. To this end, the present work explores the use of nitrogen-containing heterocyclics as small-molecule inhibitors of Aβ aggregation. Specifically, small molecules containing a flexible 1,4-diazepane scaffold were investigated for their ability to target the two major isoforms of amyloid-β, Aβ42 and Aβ40. A library of 38 derivatives based on the 1,4-diazepane scaffold was synthesized and evaluated for their ability to inhibit Aβ aggregation. The anti-aggregation activity of these compounds was determined through a combination of fluorescence-based aggregation kinetic assays, transmission electron microscopy (TEM), and computational modelling studies. Additionally, cytotoxicity assessments were performed using mouse hippocampal HT22 neuronal cells, alongside antioxidant assays and blood-brain barrier permeability evaluations. An overview of each chapter is outlined below: Chapter one provides an in-depth background on AD, addressing its prevalence, clinical diagnosis, and associated brain alterations. It reviews major pathological hypotheses, mainly cholinergic deficits, amyloid-β toxicity, tau pathology, and oxidative stress, and their roles in disease development. The chapter also reviews current therapeutic strategies, including small molecules, and their limitations. Chapter two provides a rationale for investigating the proposed 1,4-diazepane derivatives in the context of AD drug design by discussing the medicinal chemistry principles and structural features of bioactive natural compounds with amyloid-β inhibition properties. From this rationale, an AD-related hypothesis was formulated, guiding the selection and modification of chemical templates. A design strategy was developed, supported by computational studies, to propose a library of 1,4-diazepane derivatives for evaluation. Chapter three describes the design, synthesis, and evaluation of the first series of (1,4-diazepan-1-yl)(phenyl)methanone derivatives (4a–n). A library of 14 derivatives was synthesized, featuring varying functional groups at the para-position of the phenyl ring. The design incorporated 3,4-positions of the phenyl ring with known Aβ inhibition pharmacophores and antioxidant moieties, including a masked catechol group to study its effect on Aβ42 and Aβ40 inhibition. The compounds were synthesized by coupling acid chlorides or carboxylic acids with secondary amines. This study identified compounds with moderate to good inhibition of Aβ42 aggregation (32–52%) and enhanced inhibition towards Aβ40 (53–77%). This chapter also reports derivatives showing dual inhibitory effects on both Aβ42 and Aβ40. Chapter four describes the design, synthesis, and evaluation of a series of symmetric (1,4-diazepane-1,4-diyl)bis(phenylmethanone) derivatives (6a–p). This series contains 16 derivatives and includes derivatives incorporating functional groups at the para-position of the bisphenyl rings. This design strategy also incorporated 3,4-positions of the bis-phenyl rings with known Aβ inhibition pharmacophores and antioxidant moieties, including a masked catechol group, to investigate their impact on the inhibition of Aβ42 and Aβ40 aggregation. Additionally, this design also featured bicyclic aromatic rings, such as naphthyl derivatives. This study identified compounds exhibiting moderated inhibition of Aβ42 aggregation (31– 50%) and better inhibition of Aβ40 (60–63%), along with dual-targeting activity. Chapter five describes the design, synthesis, and evaluation of a series of (4-substituted-1,4-diazepan-1-yl)(phenyl)methanone derivatives (9a–h). This series comprised eight derivatives, each incorporating alkyl substituents of varying chain lengths at the N4 position of the 1,4-diazepane ring, along with a para-substituent on the phenyl ring. The findings revealed that the N-alkylated 1,4-diazepane derivatives exhibited reduced inhibitory activity toward Aβ42 (34%), in contrast to the derivatives described in Chapters 3 and 4. However, these compounds demonstrated improved inhibition of Aβ40 aggregation (55–67%) compared to those from Chapter 4, with one derivative identified as a dual-targeting agent. Chapter six focused on the biological evaluation of the most active compounds identified through the biophysical studies conducted in Chapters 3, 4, and 5. The lead 1,4-diazepane derivatives exhibited significant neuroprotective potential and effectively rescued the cells from Aβ42-induced cytotoxicity in HT22 cells (47.9–57.4%) and were not toxic to cells. Furthermore, compounds containing pharmacophores with antioxidant properties demonstrated reactive oxygen species (ROS) scavenging activity (13.2–90.7%). The findings also indicated that these derivatives possessed the ability to cross the blood-brain barrier (BBB). Chapter seven provides a comprehensive summary of the discovery of 1,4-diazepane derivatives as novel templates to design amyloid aggregation inhibitors and discusses the key findings of this study, including the physicochemical properties of the lead derivatives, the significance of this work, and future research directions to consider.
Mixed Triangular-Square Lattices on a Spherical Surface
(University of Waterloo, 2025-07-16) Xie, Han
Defects play a crucial role in determining the structures and properties of materials. When putting lattices onto a curved surface that has non-trivial Euler characteristics, defects must appear due to the geometric frustrations. Extensive studies have shown the singular lattices on curved surfaces presenting point- and scar- disclinations with high symmetry. Of recent interest is the mixed ordered lattices on flat surfaces. The phase separation of multi-ordered lattices produces a complicated, maze-like structure, where defect also plays an important role. It makes us curious about the defect properties when arranging mixed lattices on a curved geometry. In the thesis, we propose and discuss a computational and theoretical approach to study the properties of the mixed two-dimensional triangular-square lattices on a spherical surface. First, we introduce Hertzian interactions in molecular dynamics simulations to stabilize the coexistence of triangular and square domains and enable soft particles to self-assemble on a sphere. The simulations reveal novel defect morphologies beyond conventional point and scar defects—domains of one lattice type acting as defects within the bulk of the other, arranged with unexpected symmetry. To analyze these assemblies further, we develop tiling methods to arrange mixed triangular-square lattices onto spherical geometries, where defects type and locations are determined. we generalize the Caspar–Klug construction for triangulations of the sphere and introduce two operations---Face‐Rotation (FR) and Cut‐and-Rotate (CR)---to generate mixed tilings with minimal defects and high symmetries. This tiling methods enables the comparison of the defective energies of these structures with a coarse-grained model developed by Bowick \textit{et al.}. A state diagram is plotted to show the energetically favored structure at a given area fraction of square lattices. Finally, we compare these mixed configurations to singular lattices via a limiting approximation to their energy landscapes. Our work presents a new angle to understand the tripartite tug-of-war among crystalline orders, defects, and topology—an interplay that occurs across scales, from biomolecular assemblies to architectural frameworks.
Understanding Dependency in the Work of Eva Feder Kittay and Alasdair MacIntyre
(University of Waterloo, 2025-07-16) Bachiochi, Anna
This thesis offers a systematic exploration of Eva Feder Kittay’s and Alasdair MacIntyre’s perspectives on dependency, primarily through a comparison of their work in Love’s Labor and Dependent Rational Animals respectively. While Kittay and MacIntyre share what I call a “care concern” (namely, an understanding of the importance of the reality of dependency in human lives), their differing ethical frameworks of a care-ethics-informed liberalism and Aristotelian-Thomistic virtue ethics lead to different conceptions of dependency and different recommendations for responding to that reality. In Ch. 1, I compare Kittay’s and MacIntyre’s accounts of dependency from within their ethical frameworks and argue that their attempts to integrate care concerns into ethical frameworks which do not usually contain them leads to parallel sources of potential self-contradiction. In Ch. 2, I compare the two theorists’ large-scale recommendations for responding to dependency, highlighting the ways that their central disagreement about the merits of liberalism and liberal government paves the way for their differing recommendations, specifically Kittay’s focus on governmental monetary support for dependency workers and MacIntyre’s focus on mid-sized communities. In Ch. 3, I build a conceptual framework to highlight three shared concepts in Kittay’s and MacIntyre’s interpersonal ethics: 1) uncalculating care, 2) expanded (or community-based) reciprocity, and 3) the role of the emotions and desires in moral action. I argue that these similarities provide both Kittay and MacIntyre with robust interpersonal frameworks which are responsive to our moral intuitions about care relationships and so avoid some of the pitfalls of other ethical frameworks. In Ch. 4, I ask broader questions about collaborations between ethical frameworks, using my work in this thesis as a backdrop. I put forth and illustrate three models of collaboration: 1) the critique model, 2) the learning model, and 3) the hybrid model. Finally, I use the work of this thesis to enter into conversations about the relationship between care ethics and virtue ethics. I argue specifically that care ethics cannot be subsumed under virtue ethics without losing some of its central and unique features (namely, its focus on care as the central ethical concept and its relational ontology) and that we can turn to MacIntyre’s work on traditions to investigate the relationship between an ethic which has care concerns and a care ethic.
Learning the Quantum, Scrambling the Universe
(University of Waterloo, 2025-07-10) Liu, Shuwei
This thesis explores how quantum information behaves in extreme physical settings, from black hole interiors to noisy quantum devices. First, we derive a thermodynamic relation linking gravitational shockwaves to microscopic deformations of the black hole horizon, illuminating the connection between quantum chaos and horizon area deformation. Next, we explore the black hole information problem through the lens of holography, demonstrating how scrambling and recoverability emerge from gravitational backreaction in shockwave geometries. Finally, we shift to quantum technologies, introducing noise-strength-adapted (NSA) quantum error-correcting codes discovered via hybrid machine learning. These non-stabilizer codes outperform conventional designs under amplitude damping and generalize to larger systems. Together, these works reveal how quantum information unifies seemingly disparate domains, offering both conceptual insights into spacetime and practical tools for building resilient quantum systems.
Bending the curve of biodiversity loss: Identifying barriers and opportunities to accelerate endangered species recovery in Canada
(University of Waterloo, 2025-07-09) Kraus, Daniel
The decline of wild species represents one of the most urgent crises of our time, with significant ecological, cultural, and economic implications. Understanding the barriers and opportunities to accelerate wildlife recovery is essential to inform effective conservation planning, policymaking, and action, and ultimately to halt and reverse the loss of nature. Research for this thesis was guided by three interconnected objectives: 1) identify the patterns and processes of wildlife extinction and recovery in Canada, with a detailed examination of nationally endemic species, 2) compare and examine the effectiveness of national approaches to endangered species assessment, listing and recovery, thereby identifying bridges and barriers to recovery, and 3) develop and advance new approaches to planning and implementation that will accelerate endangered species recovery in Canada. These objectives are intended to provide novel contributions that fill key knowledge gaps to support the practice of endangered species conservation. This research describes over 200 species ‘missing’ from Canada since European settlement, revealing significantly more extinctions and extirpations than reported under the Species at Risk Act. These losses are concentrated in Ontario, BC, and Quebec, with unsustainable harvesting historically driving extinctions, and habitat degradation emerging as the dominant contemporary threat. In contrast, the research also identifies 49 species with genuine improvements in conservation status, as well as over 50 species that began to recover before formal national assessments began. Key drivers of recovery include harvest management, pollution abatement, with more contemporary recoveries resulting from translocations, stewardship, and protected areas. The research also highlights that most improvements in the conservation status of species at risk are the result of discovering new populations and cautions against misclassifying these as conservation successes. This research also provides the first comprehensive inventory of Canada’s 308 nationally endemic species, approximately 90% of which are of global conservation concern. The analysis identifies 27 spatial concentrations of endemic species, many of which are associated with glacial refugia, islands, coasts, and unique habitats. Despite their significance, nationally endemic species have not been prioritized in national conservation efforts, but their conservation will play an essential role in Canada’s contribution to preventing global extinctions. Drawing on comparisons with the US and Australia, the thesis identifies systemic barriers to endangered species recovery and offers ten strategic "bridges" to overcome them. These include ecosystem-based recovery, community co-governance, linking wildlife recovery to ecosystem services, and improving public narratives around wildlife loss and recovery. Insights from a survey of 136 Canadian recovery planning practitioners further highlighted that effective implementation of SARA remains illusive, with respondents emphasizing the need for improved consultations, co-production with Indigenous communities, streamlined processes, and knowledge sharing. The thesis concludes by proposing pathways to reduce extinction risks and accelerate recoveries that are based on the relationships between processes, places and peoples. These include approaches to increase proactive conservation, supporting community-based recovery planning and action, and improving knowledge mobilization. These recommendations aim to strengthen Canada’s capacity to meet its national and global biodiversity commitments and bending the curve of biodiversity loss.
On the distributions of prime divisor counting functions
(University of Waterloo, 2025-07-09) Das, Sourabhashis
Let k and n be natural numbers. Let ω(n) denote the number of distinct prime factors of n, Ω(n) denote the total number of prime factors of n counted with multiplicity, and ω_k(n) denote the number of distinct prime factors of n that occur with multiplicity exactly k. Let h ≥ 2 be a natural number. We say that n is h-free if every prime factor of n has multiplicity less than h, and h-full if all prime factors of n have multiplicity at least h. In 1917, Hardy and Ramanujan proved that both ω(n) and Ω(n) have normal order log log n over the natural numbers. In this thesis, using a new counting argument, we establish the first and second moments of all these arithmetic functions over the sets of h-free and h-full numbers. We show that the normal order of ω(n) is log log n for both h-free and h-full numbers. For Ω(n), the normal order is log log n over h-free numbers and h log log n over h-full numbers. We also show that ω_1(n) has normal order log log n over h-free numbers, and ω_h(n) has normal order log log n over h-full numbers. Moreover, we prove that the functions ω_k(n) with 1 < k < h do not have a normal order over h-free numbers, and that the functions ω_k(n) with k > h do not have a normal order over h-full numbers. In their seminal work, Erdős and Kac showed that ω(n) is normally distributed over the natural numbers. Later, Liu extended this result by proving a subset generalization of the Erdős–Kac theorem. In this thesis, we leverage Liu’s framework to establish the Erdős–Kac theorem for both h-free and h-full numbers. Additionally, we show that ω_1(n) satisfies the Erdős–Kac theorem over h-free numbers, while ω_h(n) satisfies it over h-full numbers.
Development of Ecohydrological Processes on a Partially Removed Well Pad Undergoing Restoration to a Peatland on the Western Boreal Plain, Alberta, Canada
(University of Waterloo, 2025-07-09) McKinnon, Murdoch
Peatlands on the Western Boreal Plain have been disturbed at a landscape scale by industrial developments including those associated with the oil and gas industry. Among these disturbances are in-situ well pads, which are constructed to provide a stable base for oil and gas drilling and extraction infrastructure. In the province of Alberta, Canada, well pads must legally be returned to a state of ‘equivalent land capability’ after decommissioning. For well pads constructed in peatlands, equivalent land capability has recently been defined as including the reestablishment of a self-sustaining and peat accumulating vegetation community. One method proposed to reintroduce peatland vegetation (including peatland mosses) onto decommissioned well pads involves the partial removal of the mineral fill used to construct a well pad. Termed the ‘Partial Removal Technique,’ this approach aligns the reprofiled surface elevation of a pad with that of the water table in the surrounding peatland. Peatland vegetation propagules are then introduced onto the residual mineral substrate using a modified version of the established Moss Layer Transfer Technique. However, considerable uncertainty has remained surrounding the efficacy of the technique as a form of peatland restoration, as it had not yet been applied at the scale of a full-size well pad. Accordingly, a five-year ecohydrological study was undertaken following the first full-scale implementation of the Partial Removal Technique on a well pad. The subject well pad was located in a fen complex on the Western Boreal Plain near the town of Slave Lake, Alberta, Canada. A series of field studies were undertaken to assess the extent to which the residual mineral substrate would support environmental conditions requisite for the initiation and establishment of a peatland vegetation community. Specific objectives addressed included characterization of the hydrophysical properties of the residual mineral fill and their effect on hydrological connectivity with an adjacent fen, and assessment of whether hydrological connectivity was sufficient to maintain a near-surface water table and optimal moisture availability to mosses across the entire site. The role of additional water balance terms in supporting near-surface water tables and water availability was also assessed, including quantification of snowmelt, vertical groundwater exchange, and evapotranspiration. Additionally, monitoring of the development of biogeochemical processes in the first five years post-partial removal was undertaken, including quantification of the rates of nutrient cycling and supply. The effects of microtopography and application of straw mulch and rock phosphate fertilizer on moisture and nutrient dynamics were also assessed. Results indicate that hydrological connectivity between the residual well pad and the adjacent fen was limited by the low hydraulic conductivity of the mineral fill and the compacted peat underlying it. Combined with rapid drainage from the mineral fill into the underlying peat following rainfall, this resulted in the water table being poorly regulated across just over half of the pad’s surface area. The deeper water tables observed in those areas were associated with non-optimal moisture availability to mosses (i.e., exceedance of literature desiccation thresholds), particularly in the late growing season when rainfall inputs were infrequent. Combined with high rates of water loss through evapotranspiration, it appears that much of the pad’s surface area is likely to be favourable for the establishment of only those mosses with a high desiccation tolerance. The establishment of a vegetation community characteristic of swamps may thus occur over the long term in areas that are hydrologically disconnected from the fen. Nonetheless, hydrological connectivity with the adjacent fen was sufficient to maintain a water table within 6 cm of the surface in areas located within approximately 20 to 30 metres of the upgradient pad edges. This water table depth was associated with optimal water supply at the surface for moss survival and growth. As such, the establishment of a peatland true moss community is likely to be supported across just under half of the pad’s surface area. Snowmelt may also have provided a large source of water in the early season, although additional study is required to determine the extent to which snowmelt may be lost from the pad as overland flow. Surface runoff from an upland feature constructed out of the excess mineral fill produced during the partial removal process did not constitute an appreciable source of water to the pad. Nutrient cycling and availability demonstrated limited spatial variability across the residual well pad. Owing to the high cation content of the calcareous residual mineral fill, cation supply rates were sufficiently high to further increase the likelihood of peatland true moss establishment in areas with optimal substrate moisture availability. However, low rates of nitrogen production and a low ratio of nitrogen to phosphorus supply rates indicate that productivity of the vegetation community on the residual pad may be nitrogen limited. This may change over time, as a layer of organic litter was observed to accumulate on the surface of the residual well pad during the study. This is likely to result in increased rates of decomposition, and thus also of nutrient mineralization over time. Combined, the results of this thesis indicate that there is a need to increase horizontal hydrological connectivity with adjacent peatlands in future implementations of the Partial Removal Technique. This may improve the availability of moisture across a greater proportion of the surface area of residual well pads, while also ensuring the long-term development of anaerobic biogeochemical processes. Additional work is also required to reduce water losses in the form of both vertical drainage from residual mineral substrates and evapotranspiration from the surfaces of residual well pads. Overall, the Partial Removal Technique appears to have promise as a strategy to create favourable environmental conditions for the initiation and establishment of peatland mosses on decommissioned well pads.
Detection of Biological Tissue Anomalies Using Low-Frequency Electromagnetic Fields
(University of Waterloo, 2025-07-09) Akbari Chelaresi, Hamid
This PhD thesis presents a novel biomedical imaging modality—proposed and developed for the first time—for the detection of breast cancer using low-frequency electromagnetic (EM) fields. The core principle stems from the fact that the penetration depth of EM waves into biological tissues is inversely proportional to their operating frequency. Unlike conventional high-frequency imaging techniques, this approach leverages sub-GHz frequencies (hundreds of MHz), which offer significantly deeper tissue penetration, making them particularly suitable for imaging dense breast tissues (BI-RADS categories C and D), where conventional X-ray mammography fails. Operating at low frequencies introduces critical challenges in designing radio-frequency (RF) components that are compact, human-compatible, and suitable for clinical deployment. To address this, a novel low-frequency metasurface-based film antenna—conceptually analogous to traditional X-ray films—has been developed. This metasurface sensor effectively captures scattered EM fields after interaction with biological tissues, enabling high-fidelity imaging while operating within a non-ionizing and biologically safe frequency range. The proposed system is cost-effective and portable, with strong potential for widespread deployment in low-resource settings where access to magnetic resonance imaging (MRI) is limited. Unlike MRI, which is expensive and not readily available, or ultrasound, which is prone to operator-dependent errors, this technique enables consistent and repeatable screening. Also, this work investigates the impact of various EM sources on image resolution and contrast. It is shown that magnetically enhanced sources significantly improve field-tissue interaction, thereby increasing sensitivity to early-stage tumorous anomalies. Advanced post-processing algorithms, including differentiation techniques and both supervised and unsupervised machine learning models, were implemented to enhance image quality and minimize diagnostic errors, further improving the system’s diagnostic performance. The methodology has been rigorously validated through both numerical simulations and experimental studies. Multiple iterations of the transmitter antennas and metasurface sensors have been developed, optimized, and evaluated throughout the course of the research. The final system demonstrates high accuracy in detecting early-stage abnormalities. Moreover, this thesis introduces a new low-frequency tomography method, also for the first time, that reconstructs images of internal tissues by modeling the X-ray-like behavior of localized, electrically small transmitters and receivers. A novel mathematical framework has been proposed and implemented using Radon transform techniques, enabling accurate spatial reconstruction of the object under test.
Comparison of Flow Path Mapping Between Unreal Engine and ArcGIS: The Potential Role for Game Engines in GIScience
(University of Waterloo, 2025-07-09) Fang, Amerald
Advances in the videogame industry, particularly game engines, offer promising, unconventional tools for processing spatial data and representing complex geographical processes through integrated physics. This thesis explores the potential of using Unreal Engine (UE) as a multi-disciplinary platform for combining simulation models from the field of Computational Fluid Dynamics (CFD) with GIS. We present a case study implementing a fluid simulation workflow using Smoothed Particle Hydrodynamics (SPH) and quantitatively compare its results to conventional flowpath mapping methods (D8). A multi-spatial resolution raster comparison revealed that the UE model produced flow paths with a similar length to traditional methods, but with fine-scale disagreements on where flow occurs. The vector path analysis found that the UE model produced more but shorter paths than the D8. The comparison highlights the viability of game engines for dynamic simulation and suggests extensions to broader geocomputation applications such as erosion modelling. Moreover, this research demonstrates how leveraging game engine capabilities can contribute to a more integrative evolution of GIScience.
Dance/Movement Therapy for Dementia Caregiver Resilience: A Mixed-Methods Study
(University of Waterloo, 2025-07-08) Champagne, Eden
As Canada’s population continues to age, more individuals will be living with neurodegenerative conditions such as dementia and caring for loved ones with these conditions. The Government of Canada estimates that in 2022-2023, over 400,000 people were living with diagnosed dementia, and close to 99,000 were newly diagnosed that year (StatsCan, 2025). Most individuals living with dementia are taken care of by a family member (romantic partner/spouse or adult child). However, individuals who step in to take on this role often become burdened and distressed due to the grief associated with the losses their loved one is going through (relational, physical, cognitive) and the compounded strains of caregiving. Once dementia emerges and continues to progress, the negative impact on caregivers’ health and well-being is greater than on other caregiving groups (Kim & Schulz, 2008). Thus, it is imperative to explore how caregiver well-being can be maintained despite the ongoing losses with their loved one. The majority of caregiver support programs which have been developed and evaluated are based on stress-process models, aiming to mitigate impacts of illness-related stress through learning communication skills, coping skills, and information about dementia (Schulz et al., 2020). While some of these programs have shown reductions in caregiver depression, most have minimal effect sizes (Schulz et al., 2020) and focus on reducing dysfunction (e.g., burden), rather than promoting holistic resilience factors (Palacio et al., 2020). Resilience literature suggests that taking a strengths-based approach to caregiver support may offer meaningful pathways to caregiver well-being, by promoting malleable factors such as positive affect, self-efficacy, and ways of coping (Palacio et al., 2020). Despite evidence of how the creative-arts therapies (CATs) such as dance/movement therapy (DMT) can promote positive aspects of well-being such as mood and coping in other populations, they remain underexplored for caregivers in their own right (Irons et al., 2020). CAT programs which have been explored often include the caregiver as a co-facilitator of the activity, alongside their loved one with dementia, and thus they may experience burden rather than respite (Irons et al., 2020). Importantly, proposed therapeutic mechanisms of DMT inherently correspond to resilience factors for caregivers (Champagne, 2024), providing a rationale for how DMT may help caregivers to focus on their own needs and build resources. However, scant if any research has designed or evaluated the benefits of DMT for caregivers. The purpose of this exploratory research was to design, facilitate, and evaluate the impact of a 6-session, theory-driven DMT program on resilience for dementia caregivers and to understand their experiences of this program. The objectives and activities in the DMT sessions were informed by resilience theories and previous work on DMT for resilience in other populations. A pretest-posttest convergent mixed-methods design was used. Outcome measures included caregiving burden, resilience, and psychological flourishing. Weekly quantitative measures of active creativity and DMT therapeutic factors were also distributed to consider therapeutic mechanisms of the program. Qualitative data was captured through post-session journal entries and semi-structured debrief interviews. Online survey data was collected at two time points from 10 dementia caregivers (before and after the DMT program). Repeated-measures t-tests were used to examine the changes in caregiver burden and well-being from before to after the DMT program. Results indicated that caregiver burden was significantly reduced from baseline to follow-up, as expected. However, increases in benefit finding, resilience, and psychological flourishing were not statistically significant. Pearson correlations of key study variables indicated that higher resilience immediately following DMT caused significantly lower caregiver burden at follow-up and was significantly associated with higher resilience at follow-up. Additionally, experiencing more DMT therapeutic factors was negatively associated with burden at follow-up, and positively associated with resilience and psychological flourishing at follow-up, with a medium effect size, but these correlations did not reach statistical significance. Thematic findings from qualitative interviews and post-session journals revealed that the DMT program offered participants experiences of holistic engagement, liberation, and meaningful connection with others, which led to benefits of enhanced coping. Participants described their caregiving experiences as exhausting and overwhelming. They reported feeling constrained and that it was hard to find time for self-care. Participants contrasted their experiences in DMT with preexisting caregiver programs and emphasized how creative movement elicited benefits such as feeling “lighter” and empowered, gaining an attitude of acceptance, and emotional regulation. These findings suggest that DMT programs should continue to be designed and offered on a continual basis for dementia caregivers, for the unique ways in which movement provided a needed “release” and “liberation” which promoted experiences of emotional expression and improved coping. Participants suggested that future iterations of the program should have more sessions, longer sessions to enable more deep processing and debriefing, and more social time. Together, the quantitative and qualitative findings suggest preliminary evidence of the potential for DMT to foster resilience factors and benefit caregiver well-being and coping. Participants in the present study emphasized their own surprise at how useful the modality of DMT was for their needs and urged for more DMT programs to be accessible to them.
Algorithmic Tools for Network Analysis
(University of Waterloo, 2025-07-08) Chen, Jingbang
Network analysis is a crucial technique used in various fields such as computer science, telecommunications, transportation, social sciences, and biology. Its importance includes optimizing network performance, understanding social and organizational structures, and detecting fraud or misinformation. In this thesis, we propose algorithmic results on several aspects of network analysis. The Abelian sandpile model is recognized as the first dynamical system discovered exhibiting self-organized criticality. We present algorithms that compute the final state of the sandpile instance on various classes of graphs, solving the \textit{sandpile prediction} problem on: (1) general graphs, with further analyses on regular graphs, expander graphs, and hypercubes. (2) trees and paths, surpassing previous methods in time complexity. To analyze the structure and dynamics of networks, counting motifs is one of the most popular methods, as they are considered the basic construction block of the network. In this thesis, we introduce several tools developed for counting motifs on bipartite networks. Despite its importance, counting (p,q)-bicliques is very challenging due to its exponential increase with respect to p and q. We present a new sampling-based method that produces a high-accuracy approximate counting of (p,q)-bicliques, with provably error guarantee and unbiasedness. In another line of work, we consider the temporal bipartite graphs, which edges carry timestamps. To capture the dynamic nature of relationships, we consider counting butterflies ((2,2)-bicliques) in temporal bipartite graphs within specified time windows, called the historical butterfly counting problem. We present a hardness result between memory usage and query time for this problem and a new index algorithm that surpasses the hardness when applied to power-law graphs, with outstanding empirical performance. Lastly, we discuss tools that find the polarized community in the network. A classical model that applies to networks to deal with polarization is the signed graphs, which have positive and negative edges between vertices. A signed graph is balanced if it can be decomposed into two disjoint sets such that positive edges are between vertices in the same set while negative edges are between vertices from different sets. This notion of balance is strict in that no edge can disobey the condition, which seldom appears in reality. To address this phenomenon, we propose a new model for identifying balanced subgraphs with tolerance in signed graphs and a new heuristic algorithm that computes maximal balanced subgraphs under the new tolerance model.
Investigation of Neck Posture and Muscle Activity on Cervical Spine Impact Kinematics Using a Finite Element Human Body Model
(University of Waterloo, 2025-07-08) Correia, Matheus Augusto
Whiplash-associated disorders (WAD) define a broad range of symptoms affecting the neck such as pain and stiffness, reported in up to half of motor vehicle collisions. WAD are typically associated with, but not limited to, low-severity rear impacts. The high incidence of WAD and high socioeconomic cost have led to significant, but still inconclusive, efforts to better understand the associated causal injury mechanisms. Neck posture and muscle behaviour are known factors that contribute to neck injuries during low-severity vehicle impacts. Quantifying the effects of such parameters at the tissue level is challenging in experimental studies but may be informed by computational human body models (HBMs). However, three limitations in neck models have been identified: (1) neck muscle controllers were often tuned to a narrow set of specific load cases, (2) neck models were unable to predict the S-shape (upper cervical spine flexion) magnitude observed in experiments during rear impacts, and (3) defining tissue-level injury thresholds remain elusive for the neck. To address these challenges, three studies were defined for this thesis using a contemporary head and neck finite element model from an average-stature male HBM (Global Human Body Models Consortium (GHBMC)) with the aim of enhancing and evaluating the tissue-level response associated with WAD injury risk following rear impact. In the first study, a new closed-loop controller with a single set of parameters for neck muscle activation based on known reflex mechanisms was implemented in the GHBMC model. The updated model was assessed over a range of impact conditions. The closed-loop controller had an average cross-correlation to the experimental data of 0.699 for 14 load cases, including frontal, rear and lateral impacts, within 2% to 9% of previous calibrated open-loop approaches. In the second study, a novel methodology was developed to integrate pre-tension in the neck muscles based on experimental cadaveric and volunteer data and assessed in rear impact scenarios. Only the model with pre-tension achieved flexion of the upper cervical spine at the same magnitude as reported in impact tests with volunteers. Pre-tension increased the muscle tissue strain relative to cases with no pre-tension, and, in some cases, led to potentially injurious-level strains, reinforcing that the initial muscle strain is essential for evaluating WAD injury risk. In the third study, the methods from the first and second studies (closed-loop muscle activation controller and muscle pre-tension) were combined to assess possible WAD injury mechanisms based on tissue-level analysis of stresses and strains in 4g to 10g rear impacts. The existing injury metrics and tissue-level muscle strains identified that hyperextension was the main injurious phase in low-severity rear impacts. In addition, muscle pre-tension and activation changed the distribution of muscle strains, better representing the injury regions reported in the literature. New model developments and knowledge obtained from the three studies completed in this research can be generalizable to other HBMs and can be applied to evaluate the efficacy of vehicle safety systems, ultimately reducing injury risk and diminishing societal costs related to low-severity neck injury in the future. Further, the enhanced neck model developed in this work has identified possible areas of experimental interest for future neck injury research.
Digital Agent-Based Resource Management for Short Video Streaming in Multicast Networks
(University of Waterloo, 2025-07-07) Huang, Xinyu
As fifth-generation (5G) networks approach maturity and widespread deployment, both industry and academia are turning their attention to sixth-generation (6G) networks. It is anticipated that 6G networks will support an unprecedented diversity of services with heterogeneous user requirements, accelerating the shift from service-oriented to experience-centric resource management. Among these services, short video streaming has become one of the majority of users’ daily mobile traffic consumptions due to its highly engaging content, but this also leads to substantial traffic increase, especially in densely populated areas. Considering the popularity-based and user similarity-driven recommendation principles in short video platforms, multicast transmission over the air can effectively relieve traffic pressure by delivering the same video data to a group of users with similar characteristics and locations. Quality of experience (QoE), as a subjective performance metric in experience-centric resource management, can reflect the user satisfaction level on multicast short video streaming, which usually consists of rebuffer time, video quality, and video quality variation. To achieve experience-centric resource management, digital agent (DA), as a cutting-edge technology in 6G networks, owns advanced status emulation, data analytics, and decision-making capabilities, which can perceive network dynamics, abstract hidden behavior patterns or QoE models, and solve complex optimization problems. The interesting issue is maximizing user QoE in multicast short video streaming under limited radio and computing resources within dynamic network environments. However, the main technical challenges are: (1) how DAs abstract user swipe behavior patterns for large-timescale resource reservation to enhance resource utilization and improve long-term user QoE; (2) how DAs characterize multicast buffer dynamics for real-time resource allocation to alleviate buffer length overestimation and improve real-time user QoE; (3) how to adaptively select appropriate DA models to assist resource management and timely update them to further improve user QoE. In this thesis, we develop an efficient DA-based resource management framework to enhance user QoE for multicast short video streaming, including swipe behavior-aware resource reservation, multicast buffer-aware resource allocation, and network dynamics-aware DA management. First, we propose a DA-based resource reservation scheme by considering dynamic user swipe behaviors to enhance resource utilization and large-timescale user QoE. Particularly, user DAs are constructed for individual users, which store users’ historical data for updating multicast groups and abstracting useful information. The swipe probability distributions and recommended video lists are abstracted from user DAs to predict bandwidth and computing resource demands. Parameterized sigmoid functions are leveraged to characterize multicast groups’ user QoE. A joint non-convex bandwidth and computing resource reservation problem is formulated and transformed into a convex piecewise problem by utilizing a tangent function to approximately substitute the concave part. A low-complexity scheduling algorithm is developed to find the optimal resource reservation decisions. Simulation results based on the real-world dataset demonstrate that the proposed scheme outperforms benchmark schemes in terms of user QoE and resource utilization. Second, we propose a DA-based resource allocation scheme by considering multicast buffer dynamics to enhance real-time user QoE. In specific, user statuses emulated by DAs are utilized to estimate the transmission capabilities and watching probability distributions of sub-multicast groups for adaptive segment buffering. The sub-multicast groups’ buffers are aligned to the unique virtual buffers managed by DAs for fine-grained buffer updates. A multicast QoE model consisting of multicast rebuffer time, video quality, and quality variation is developed by considering the mutual influence of segment buffering among sub-multicast groups. A joint optimization problem of segment version selection and slot division is formulated to maximize user QoE. To efficiently solve the problem, a data-model-driven algorithm is proposed by integrating a convex optimization method and a deep reinforcement learning (DRL) algorithm. Simulation results based on the real-world dataset demonstrate that the proposed DA-based resource allocation scheme outperforms benchmark schemes in terms of user QoE improvement. Third, we develop an adaptive DA-based resource management scheme to enhance long-term user QoE. Particularly, DAs consist of user status data and data-based models, which can update multicast groups and abstract user swipe features. An adaptive DA management mechanism for DA data processing model selection and update is developed to adapt to user status dynamics. A fine-grained QoE model is established by considering the impact of resource constraints and DA model accuracy. A joint optimization problem of bandwidth and computing resource management is formulated to maximize long-term user QoE. To efficiently solve this problem, a diffusion-based DRL algorithm is proposed, which utilizes the denoising technique to improve the action exploration capabilities of DRL. Simulation results based on a real-world dataset demonstrate that the proposed adaptive DA-based resource management scheme outperforms benchmark schemes in terms of user QoE, with improvements of 18.4\% and 20.5\% under low and high user dynamics, respectively. In summary, we have investigated DA-based radio and computing resource management from the perspectives of large-timescale resource reservation, real-time resource allocation, and adaptive DA management. The proposed approaches and theoretical results provide valuable insights and practical guidelines for experience-centric resource management in future 6G networks.
Statistical Inference in ROC Curve Analysis
(University of Waterloo, 2025-07-07) Hu, Dingding
The receiver operating characteristic (ROC) curve is a powerful statistical tool to evaluate the diagnostic abilities of a binary classifier for varied discrimination thresholds. It has been widely applied in various scientific areas. This thesis considers three inference problems in the ROC curve analysis. In Chapter 1, we introduce the basic concept of the ROC curve, along with some of its summary indices. We then provide an overview of the research problems and outline the structure of the subsequent chapters. Chapter 2 focuses on improving the ROC curve analysis with a single biomarker by incorporating the assumption that higher biomarker values indicate greater disease severity or likelihood. We interpret “greater severity” as a higher probability of disease, which corresponds to the likelihood ratio ordering between diseased and healthy individuals. Under this assumption, we propose a Bernstein polynomial-based method to model and estimate the biomarker distributions using the maximum empirical likelihood framework. From the estimated distributions, we derive the ROC curve and its summary indices. We establish the asymptotic consistency of our estimators and validate their performance through extensive simulations and compare them with existing methods. A real-data example is used to demonstrate the practical applicability of our approach. Chapter 3 considers the ROC curve analysis for medical data with non-ignorable missingness in the disease status. In the framework of the logistic regression models for both the disease status and the verification status, we first establish the identifiability of model parameters, and then propose a likelihood method to estimate the model parameters, the ROC curve, and the area under the ROC curve (AUC) for the biomarker. The asymptotic distributions of these estimators are established. Via extensive simulation studies, we compare our method with competing methods in the point estimation and assess the accuracy of confidence interval estimation under various scenarios. To illustrate the application of the proposed method in practical data, we apply our method to the Alzheimer's disease dataset from the National Alzheimer's Coordinating Center. Chapter 4 explores the combination of multiple biomarkers when disease status is determined by an imperfect reference standard, which can lead to misclassification. Previous methods for combining multiple biomarkers typically assume that all disease statuses are determined by a gold standard test, limiting their ability to accurately estimate the ROC curve and AUC in the presence of misclassification. We propose modeling the distributions of biomarkers from truly healthy and diseased individuals using a semiparametric density ratio model. Additionally, we adopt two assumptions from the literature: (1) the biomarkers are conditionally independent of the classification of the imperfect reference standard given the true disease status, and (2) the classification accuracy of the imperfect reference standard is known. Using this framework, we establish the identifiability of model parameters and propose a maximum empirical likelihood method to estimate the ROC curve and AUC for the optimal combination of biomarkers. An Expectation-Maximization algorithm is developed for numerical calculation. Additionally, we propose a bootstrap method to construct the confidence interval for the AUC and the confidence band for the ROC curve. Extensive simulations are conducted to evaluate the robustness of our method with respect to label misclassification. Finally, we demonstrate the effectiveness of our method in a real-data application. In Chapter 5, we provide a brief summary of Chapters 2-4 and outline several directions for future research.

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