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Auditory Processing During Sleep: A Causal Approach to Manipulate Memory Consolidation Through Event-Locked Stimulation
No full textSleep represents a considerable part of our lives and its important roles in cognition and health are constantly being emphasized by emerging research. Investigations of sleep’s role in human memory consolidation have primarily focused on correlative relationships with sleep architecture or characteristic patterns of electrical activity, such as brain oscillations. While non-invasive neuroimaging studies cannot provide direct causal evidence of oscillations’ functional roles, emerging brain stimulation techniques fill this gap by allowing direct interaction with endogenous brain activity. Closed-loop auditory stimulation, which uses quiet sounds time-locked to neural events, shows promise in research and clinical applications, particularly for targeting neural events previously correlated with, and therefore hypothesized to be involved in learning and memory. The present thesis investigates the bidirectional relationship between auditory processing and sleep using a combination of electroencephalography, magnetoencephalography, and behavioural paradigms. This dissertation comprises six studies. In our first studies (Chapters 2 and 3), which used source-localized magnetoencephalography, we demonstrated that cortical sources of auditory evoked responses are affected by sleep depth, while subcortical regions remain unaffected. We also identified the source of sleep-specific evoked responses that are involved in closed-loop auditory stimulation effects. The next study (Chapter 4) challenges a widely held assumption in sleep science by showing that auditory input can still reach the cortex during spindles and their refractory period. This finding is key to our goal of manipulating sleep spindles with sound. In the next group of studies (Chapters 5 and 6), we validated a deep learning-based tool to modulate neurophysiology by stimulating spindles in real-time, and explored the optimal timing for its delivery. This work established the foundation for our behavioural study. Finally, the last study (Chapter 7) assessed the behavioural effects of slow oscillation and spindle stimulation on simple laboratory tasks and on a complex, music-based learning task. We evaluated relationships between stimulation-evoked responses and memory performance across tasks. Our findings provide mechanistic insights into how non-invasive brain stimulation affects neurophysiology and memory and offer a framework for linking brain activity with its function
Grid-Connected PV + Battery AC Nano-grid with EV Integration for Increased Resilience
No full textThis work presents a methodology for integrating a single-phase V2H/V2L inverter into a three-phase nano-grid equipped with photovoltaic (PV) generation and battery storage. The existing system, based on SMA technology, includes three Sunny Boys (SBs) and three Sunny Islands (SIs), all managed by a Data Manager (DM). Due to the inability of the V2H inverter to directly connect to the three-phase system, a novel scheme was developed, incorporating a spare SI, an ioLogik interface, relays, and an alarm system.
The proposed setup enables load shedding and allows the stationary battery to be supplemented with energy from the electric vehicle (EV), effectively extending the supply duration for high priority loads during grid faults or islanded conditions. The control logic is based on the state of charge (SoC) of the stationary battery. This strategy ensures a balance between maintaining power supply to critical loads (priority and higher priority loads) and conserving the EV’s stored energy for critical situations.
The comprehensive experimental setup developed in this work, along with the adopted energy management strategy, was successfully tested, demonstrating its functionality. Furthermore, an alternative scheme and a V2G (Vehicle-to-Grid) configuration were explored to highlight the versatility of this methodology. The system’s flexibility allows the integration of additional energy sources, such as fuel cells, wind turbines, and extra PV systems, by connecting them to the DC bus, providing a robust framework for advanced energy systems and energy management
Performance Evaluation of 5G MIMO DetectorsWith Deep Learning
No full textFifth-generation (5G) wireless networks promise ultra-reliable low-latency communication, enhanced mobile broadband, and massive machine-type connectivity capabilities made possible by advanced technologies such as massive MIMO, OFDM-based modulation, and dynamic spectrum access. However, these benefits introduce new challenges for receiver design, including increased complexity, high data rates, and time-varying channels that degrade the performance of traditional detection methods.
This thesis presents a comprehensive performance analysis of 5G networks using a deep learning–based receiver. A simulation framework is designed to evaluate 5G MIMO receivers under diverse channel environments, including AWGN, Rayleigh fading, and the 3GPP TDL-C model.
A custom dataset is generated using MATLAB’s 5G Toolbox to simulate OFDM-based transmissions across multiple MIMO configurations and modulation schemes. Various neural network architectures
including Fully Connected Neural Network (FCNN), Convolutional Neural Network (CNN), Residual Neural Network (ResNet) and Long Short Term Memory (LSTM network), are implemented and benchmarked against Maximum likelihood (ML), sphere decoding, and MMSE
detection.
Performance metrics including bit error rate (BER), symbol error rate (SER), processing speed, and computational complexity are evaluated. The results highlight trade-offs between accuracy and efficiency and provide insights into the feasibility of deep learning–based detection for practical 5G deployments
Stability of Localized Solutions to Lattice Dynamical Systems
No full textThis thesis focuses on the stability of spatial localized solutions of lattice dynamical systems (LDSs). In particular, I focus on the stability of spatially localized single- and multi-pulse solutions to lattice dynamical systems. By linearizing the nonlinear system around steady-state solutions and applying exponential dichotomy theory, an isomorphism between the localized solutions and the stable front and back solutions is constructed. Then, the proof constructs Evans functions about the localized solutions from Evans functions of the front and back solutions. It gives that eigenvalues of the front and back solutions lead to nearby eigenvalues for the localized solution, which can in turn be used to verify instability of the solution. Furthermore, Rouché's theorem is used to prove that the number of roots in the single-pulse solution is the sum of front and back solutions', and the multi-pulse solution's is the sum of each single-pulse solution's. This work is widely applicable to a range of scalar LDSs, particularly the well-studied discrete Nagumo equation. Finally, this thesis concludes with a discussion of possible avenues for future work
haha.js: The comedic potential of JavaScript frameworks
No full textThis thesis explores the conditions under which humour can emerge through a designer’s playful and reflexive engagement with code, context, and digital tools. While humour is often researched in interaction design for its effects on users, less attention is paid to how it takes shape during the design process. Using a research-through-design approach grounded in reflective and grounded theory, I analyze the design of two original web-based projects, Inner Birdsong and Are You Alone?, built with MediaPipe and Matter.js. Through journals, versioned commits, and open coding, I trace how humour was both discovered and actively shaped through misalignments, surprises, and intentional, playful interventions with digital materials. Guided by Donald Schön’s reflection-in-action, I treat design as a conversation with materials. Humour emerged through this dialogue, responding to system behaviour, appropriating tool affordances, and tuning interactions toward the comedic. Traditional humour theories (incongruity, superiority, relief), alongside interaction design and play theory, are used to interpret these moments. I identify four conditions that supported humour’s emergence: adopting a playful stance, letting materials lead, embracing ambiguity, and practicing attunement to the emotional dynamics of the process. This thesis argues for an open, experimental, care-driven approach, where humour is shaped through a designer’s situated, responsive, and intentional engagement with making
Next-Generation Data Centers: Experimental Analysis of Topologies and Algorithms for Next-Generation Data Centers
No full textIn recent years, data center networks (DCNs) have faced growing pressure from AI and ML workloads with intensive communication patterns and stringent latency requirements. Traditional hierarchical architectures like Clos (Fat-Tree) increasingly struggle with scalability bottlenecks, operational complexity, and congestion under bursty traffic. To address these challenges, this work explores the Structured Re-Arranged Topology (STRAT), which combines expander-graph-inspired path diversity with deterministic structure to enable efficient, scalable, and fault-tolerant designs. Unlike rigid designs, STRAT supports incremental growth, reduced cabling complexity, and better load distribution. This thesis evaluates STRAT not only in simulation but also on real programmable-switch hardware, demonstrating its practical viability. A key contribution is DEALER, a congestion-aware, data-plane-friendly forwarding algorithm leveraging programmable switches. DEALER uses a distributed distance-vector protocol and local queue occupancy to balance load among equal-cost and slightly longer paths, achieving significant improvements over ECMP in high-load scenarios while running at line rate on commercial ASICs. To further enhance STRAT, this work integrates a hybrid electrical-optical fabric with Optical Circuit Switching (OCS) links, guided by proactive, ML-based flow classification. An XGBoost model predicts elephant flows early, enabling their diversion to pre-configured optical paths with minimal control overhead. Simulations show reductions in tail latency and improved throughput. Together, these contributions offer a practical, holistic redesign for DCNs, uniting scalable graph-based topologies, programmable forwarding logic, and ML-guided optical hybridization to meet the performance, efficiency, and scalability demands of modern AI and cloud workloads
DandeBot - An Autonomous Weeding Solution for Residential Lawns
No full textDandeBot – An Autonomous Weeding Solution for Residential Lawns
Author: Nishanth Rajkumar
This thesis presents the development and validation of DandeBot, an autonomous robotic system designed for comprehensive residential lawn maintenance. The robot addresses the need for efficient, eco-conscious, and low maintenance lawn care through a fully electric platform powered by an AI-driven software stack. Emphasizing safety, adaptability, and ease of use, the hardware was developed using CAD and Design for Manufacturing (DFM) principles, resulting in a modular and robust design. The integrated software stack combines localization, mapping, and path planning using odometry, visual odometry, and IMU data fusion to navigate dynamic outdoor environments. Task-specific algorithms were developed and validated for autonomous navigation, weed detection, and obstacle avoidance. Key hardware innovations include a modular gripper system for weed removal and adaptable attachments for multiple lawn care tasks. Field trials confirmed the robot’s capability to perform with high precision and reliability in varied lawn conditions, significantly reducing the need for human intervention. This work contributes to the growing field of service robotics by demonstrating how intelligent systems can automate routine household maintenance. The thesis concludes by outlining future research directions, including system scalability, enhanced multi-tasking capabilities, and integration with smart home networks
A Pedagogy of the Unrepresentable: Encounters with Monochromatic Abstract Art
No full textWe use images in pedagogy as if they should always explain themselves. But what if they don’t? What if they remain silent, resistant, opaque, or ambiguous? This thesis focuses on monochromatic abstract images, particularly those in black, as a means of interrupting dominant habits of perception and exploring how visual opacity can open new pedagogical possibilities. It examines how images that withhold meaning might invite presence, attention, and forms of learning that emerge in a more slow and affective way and without predetermined results. Rather than providing strategies for interpreting or decoding images, this study engages abstraction as a space of friction, where perception is slowed, disrupted, or suspended. Engaging works such as Malevich’s Black Square, selected cinematic images, and past works from my own studio practice, alongside my experiences as an educator, I consider how images that resist comprehension can disrupt or disturb pedagogical habits and open space for learning that is based in unknowing. Pedagogical encounters with abstraction can also shift the role of the image, from something to interpret to something that exerts pressure and creates disorientation. In unravelling these gestures across the chapters, I consider black as a condition—something that unsettles perception, thought, and pedagogy, rather than something fixed or easily understood as colour. I explore this condition through the figure of the black hole, which is offered not merely as a metaphor for gravity, void, or disappearance, but as a diagram for thinking the unknowable within pedagogical experience. Drawing from post-qualitative and non-representational theories of education, I develop concepts and pedagogies of refusal, drift, delay, and disappearance—gestures that interrupt normative habits of perception and teaching. Through tracing these gestures, this thesis proposes a pedagogy of the unrepresentable: a pedagogy that does not aim for clarity and instead holds space for the unknown, the ineffable, and for the affective dimensions of learning
Three Essays in Mental Health Economics: Education and Labor Market Outcomes
No full textThis dissertation explores how mental and physical health influence key economic outcomes over the life course, focusing on education, occupational outcomes, and workplace productivity. Using longitudinal data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), the study employs advanced modeling techniques, including Generalized Structural Equation Modeling (GSEM) and mixed-effects regression, to construct latent health measures and quantify their economic consequences.
The first chapter examines the impact of adolescent mental health on academic achievement, particularly high school completion and college enrollment. It addresses the limitations of using narrow diagnostic proxies for mental health by applying a factor-analytic approach to create latent constructs. The findings reveal that better mental health significantly improves educational attainment, with a stronger effect on college entry than on high school completion.
The second chapter investigates how health status shapes occupational sorting across two major classifications: white-collar and full-time employment. It finds that individuals with poor mental health are disproportionately concentrated in low skill, physically demanding, blue-collar jobs, while those with better health are more likely to enter cognitively intensive, white-collar occupations. Physical health also influences job type, reinforcing disparities in labor market access and long-term mobility.
The third chapter evaluates the effect of mental health on workplace productivity. By constructing a composite latent productivity score, based on job satisfaction, hours worked, and income, the study estimates the long-term effects of lagged health status. A one standard deviation increase in mental health is associated with a 0.0251 rise in latent productivity and a 0.0201 increase in wage measure of productivity, confirming the strong and persistent influence of psychological well-being.
Together, these chapters show that mental health is a critical determinant of economic opportunity, shaping individual outcomes from adolescence through adulthood
"In either a woman or a horse": Emily Murphy and the Road to Supporting Sexual Sterilization in Canada
No full textEmily Murphy was a pioneering advocate for women's rights in Alberta. She was instrumental in securing greater legal protections for married women through her advocacy of the province's
Dower Act and was actively involved in both the suffrage and birth control movements. Perhaps more notably, she is remembered as the instigator of the Person's Case, which sought to amend the British North America Act to recognize women as "persons" eligible for appointment to the Canadian Senate.
However, Murphy's legacy has been complicated by the resurfacing of her support for eugenics and sexual sterilization. A vocal proponent for Alberta's Sexual Sterilization Act of 1928, her view on these issues shocked many Canadians. This thesis examines the intersection of class,
gender, religion, maternal feminism and Irish Protestant ideology to uncover the motivations of Murphy's support for such a controversial piece of legislature. By examining her early life in
Cookstown, the Orange Order's influence on the construction of her values, her writings under the Janey Canuck pseudonym, and her role as a Police Magistrate, this thesis argues that Murphy's involvement in Canada9s eugenic movement was deeply entwined with her views of feminism, nationalism, and class