Digital Commons Network^™

Capital Structure Models And Contingent Convertible Securities, Di Meng

Theses and Dissertations (Comprehensive)

The 2007-09 financial crisis showed financial institutions are vulnerable during distressed times. As an alternative resolution to a government bail-out, contingent convertible securities (contingent capital or CoCos) were proposed by various researchers. CoCo is a hybrid capital security that converts from a bond to common equity when a pre-determined event occurs. The loss absorption mechanism of CoCo is essential to the financial health of a bank during a crisis as it provides an instant capital infusion when public capital is difficult to access.

In this thesis, we first implement a methodology to calibrate capital structure models for large Canadian banks. …

Uncertainty And Strategy In Fair Allocation Of Indivisible Items, Fahimeh Ziaei

Theses and Dissertations (Comprehensive)

In studies of collective decision-making, the problem of allocating indivisible items fairly and efficiently is widely acknowledged as particularly challenging. Our study assesses various algorithms for finding balanced allocations based on their ability to achieve desirable properties such as envy-freeness, Pareto-optimality, maximin, maximum Borda sum, and Borda maximin.

Two players with additive preferences allocate an even number of indivisible items, given only each other's strict preference ordering. The algorithms under study include both naive and sophisticated versions of Alternating selection, bottom-up Alternating selection (or Alternating rejection), Zigzag selection, bottom-up Zigzag alternation, and fallback bargaining. The results suggest that fallback bargaining, …

Knowledge, Efficacy, And Experience In Components Of Stem Education: The Impact Of Teacher Professional Development, Emily Krysten Marilyn Spencer-Mueller

Theses and Dissertations (Comprehensive)

Abstract

Around the globe, there has been a significant focus on ensuring youth receive sufficient education and training in Science, Technology, Engineering, and Math (STEM) domains. Education reforms often begin with educators, who are responsible for effectively implementing curriculum changes. However, in Canada, although STEM education reform is underway, teacher education and professional learning (PL) and development may not have kept pace, potentially leaving some teachers feeling unprepared to integrate these changes confidently and effectively. This dissertation introduces two studies that investigate pre-service teachers’ readiness to teach STEM domains in the classroom, as well as the impact of a PL …

Reinforcement Learning For Scheduling And Routing: Electric Vehicles Charging And Patrol Scheduling, Majid Ghasemi

Theses and Dissertations (Comprehensive)

This thesis offers a comprehensive exploration of Reinforcement Learning (RL), beginning with fundamental theoretical constructs, Markov Decision Processes, Dynamic Programming, Monte Carlo, and Temporal Difference methods, and extending into state-of-the-art deep RL approaches such as Deep Q-Networks (DQN) and policy-gradient algorithms. Through analytical experiments in controlled environments, the thesis demonstrates how distinct algorithmic choices (e.g., exploration techniques, eligibility traces, or network architectures) influence convergence and stability. These foundational insights pave the way for two in-depth case studies, which apply RL techniques to critical, real-world scheduling and routing challenges.

The first case study tackles the Electric Vehicle (EV) routing and charging …

Multi-Lingual And Cross-Domain Frontiers In Machine-Generated Content Detection, Gurunameh Singh Chhatwal

Theses and Dissertations (Comprehensive)

The rapid advancement of generative artificial intelligence, particularly Large Language Models (LLMs) such as GPT-4 and their multilingual capabilities, has significantly blurred the distinction between human-authored and machine-generated content. This technological evolution introduces critical challenges concerning the detection and attribution of textual authenticity and authorship, exacerbating societal issues like misinformation proliferation and compromising academic and professional integrity. Traditional detection methodologies, predominantly monolingual and heuristic-based, have demonstrated inadequate generalizability and efficacy against the sophisticated, multilingual capabilities of contemporary generative models.

This thesis addresses two major problems arising from these advancements. Firstly, it introduces novel multilingual detection methodologies explicitly designed to differentiate …

Using Landscape Ecology And Spatial Statistics To Examine The Impacts Of Proposed Removals To Natural Heritage System And The Agricultural System Of Ontario’S Greenbelt, Brianna Downey

Theses and Dissertations (Comprehensive)

The 2022 proposed removals from the Greater Toronto Area (GTA), Southern Ontario’s Greenbelt would have resulted in negative impacts including, reductions to the size and functionality of the Agricultural System and Natural Heritage System, which are components of protected Greenbelt area. Several removal sites were located either on or in close proximity to corridor areas of the NHS, reducing connectivity and negatively impacting the surrounding ecological area. The removal of Agricultural land primarily consisted of corn and soybeans, as well as large removals of woodland, wetland, and shrubland class areas. The removal sites on local Agricultural composition and configuration were …

Controls Of Wetland Hydrology In The Zone Of Discontinuous Permafrost, Northwest Territories, Canada, Iain Thomson

Theses and Dissertations (Comprehensive)

Mean annual air temperatures are increasing rapidly in northwestern Canada, which is among the most rapidly warming regions on Earth (Box et al., 2019). Consequently, permafrost thaw within northwestern Canada is proceeding at a rate not found in the historical record (Pelletier et al., 2017), with areal thaw rates especially high in the peatland-dominated southern margin of discontinuous permafrost (Quinton et al., 2019). Permafrost thaw has caused vast land cover changes and transformed the permafrost underlain forest into permafrost free wetlands over much of Taiga Plains (Carpino et al., 2018; Jorgenson & Osterkamp, 2005). This land cover change has …

Technology-Enhanced Professional Development For Early Literacy: A Comparative Study Of Online Teacher Learning Models In Kenya, Constanza Uribe-Banda

Theses and Dissertations (Comprehensive)

Growing recognition of early literacy as essential for lifelong learning, along with evidence that teachers’ mastery of foundational literacy instruction influences student outcomes (Darling-Hammond et al., 2017; UNESCO, 2020), has led to increased investment in teacher professional development. Despite these efforts, many educators face significant challenges in accessing high-quality training, particularly in resource-constrained settings where geographical barriers and limited institutional support persist. This is especially true in rural Kenyan communities, where teachers often work in under-resourced schools with unreliable electricity and internet connectivity yet bear responsibility for laying critical literacy foundations. The present study examines the potential to deliver effective …

Negotiated Cultural Identity And Belonging Of Self-Identified Indo-Guyanese Immigrant Women, Neta (Goomatee) Deonarain-Gear

Theses and Dissertations (Comprehensive)

This dissertation examines how young, self-identified Indo-Guyanese women who immigrated to Southwestern Ontario in the 1970s negotiate cultural identity and belonging. Utilizing a bio-ethnographic bricolage narrative methodology, the study explores the impact of postcolonial diaspora and social displacement on these women’s experiences within the "third space" or borderlands. Grounded in relativist ontology and constructivist epistemology, storytelling serves as the primary data collection method through a critical theory lens. Interviews with 12 participants were analyzed thematically and reflexively, revealing how participants construct meaning and navigate cultural identities. The analysis, conducted through feminist, decolonial, and trauma-informed perspectives, offers insights into "psychological homelessness" …

Macroinvertebrate Communities And Food Web Structure In Tundra Streams Are Shaped By Substrate Size And Beaver Impoundments, Mathew K. Mervyn

Theses and Dissertations (Comprehensive)

North American beavers (Castor Canadensis) are expanding their range into the Arctic tundra as climate change drives earlier ice and snowmelt, and increased shrub cover. As ecosystem engineers, beavers build dams that alter water chemistry by creating impoundments within streams, trapping sediment and organic matter, and modifying nutrient cycling. This thesis evaluates how beaver impoundments interact with natural geomorphic variation in tundra streams and how impoundments affect tundra freshwater ecosystems in the western Canadian Arctic.

In Chapter 2, I compared water chemistry and benthic macroinvertebrate (BMI) community composition across 16 stream reaches, including those with and without beaver dams, with …

Crime Modeling Using An Integrated Cnn–Lstm Architecture With Embedded Self-Excitation, Pawandeep Kaur

Theses and Dissertations (Comprehensive)

It is often assumed that natural phenomena occur randomly over time. However, careful analysis reveals that these events typically form some series or sequences and exhibit distinctive temporal patterns. These patterns are not exclusive to nature. They also appear in human activities, often studied under the concept of bursty human dynamics. The statistical methods analyzing bursty human dynamics not only capture overall trends or seasonality but also explore how past events influence future ones. It makes the analysis more realistic and the results more closely aligned with reality. Bursty human dynamics can be studied at two levels: the individual level …

The Munster Statement On The Principles Of Research Ethics And Research Integrity (English), Ingenium

Dissemination

INGENIUM is an alliance of ten institutions of higher education from ten European countries. This European University seeks to enable each member of the network to offer high-quality study and qualification programmes with digital components that are shared within the INGENIUM Alliance.

In Higher Education Institutions there is a growing emphasis on promoting good research practices in all aspects of research1,2, including everything from fundamental research to applied research to commercialisation. Research ethics (RE) and research integrity (RI) underpin research activity and excellence and are considered a critical component of the basis for researchers to trust each other as well …

Oer Ancient Egyptian Numerals Activity, Cynthia Huffman Ph.D.

Open Educational Resources - Math

Ancient Egypt captures our imagination not just because of its pyramids, but because of its incredible staying power. This civilization thrived for over 3,000 years, influencing cultures across the globe—including the very roots of mathematics. As Egyptologist Bob Brier puts it, “No civilization lasted so long, contributed so much, or repeatedly amazed as did ancient Egypt.”

Ready to crack the code of Ancient Egypt and the pharoahs? In this activity, you will learn to decipher Egyptian numerals by examining real photos from temples and museums. Master this skill, and next time you visit a museum exhibit on ancient Egypt, you …

Phishing Detection Using Continual Learning And Large Language Models, Gopi Prajeev Battula

Master's Projects

Adaptive phishing detection remains crucial as the nature of cyber-attacks changes over time, which renders static models obsolete. This project extends phishing detection through the implementation of continual learning approaches, namely Elastic Weight Consolidation (EWC) and Learning Without Forgetting (LWF) with RoBERTa, a Large Language Model (LLM) and compares the results of these approaches against GPT-4o-mini, another LLM. Our approach begins with fine-tuning RoBERTa on multiple phishing datasets to establish an effective baseline. EWC is then implemented to preserve vital model parameters based on their importance measured by the Fisher Information Matrix, while LWF uses knowledge distillation to retain prior …

Disease Diagnosis Using Rag Llm With Smart Prompt Engineering, Qadeerullah Syed

Master's Projects

Although recent trends indicate that LLMs outperform traditional methods in solving complex problems with enhanced reasoning, there has been barely any progress in replicating the quality of diagnoses like those of actual human doctors. The identification of an accurate diagnosis with thorough reasoning is still a significant challenge, even with advanced AI models. The process of performing accurate diagnosis remains challenging due to a lack of transparency in state-of-the-art models existing today, a lack of explanation in the diagnosis process, an emphasis on results rather than reasoning, and a lack of foundational knowledge in models, along with limited exploration of …

Hierarchical Bloom Filter Tree (Hbft): Scalable Geospatial Metadata Indexing For Bigdata Systems, Mrudula Patteparapu

Master's Projects

Big Data infrastructure growth has produced overwhelming metadata volumes which create extensive problems for spatial indexing and both system scalability and database queries. Traditional solutions consisting of R-trees and conventional Bloom filters manage to provide either range query support or approximate membership testing, yet they face performance issues when used at large-scale metadata management. This research proposes Hierarchical Bloom Filter Tree (HBFT) as an improved framework that integrates hierarchical spatial partitioning with partitioned, scalable, cuckoo, and striped Bloom filter variants based on existing studies in hierarchical and probabilistic indexing. The complete evaluation process shows that HBFT outperforms PostGIS (an industry-standard …

Mycelia: Cross-Chain Data Oracle Using Frost Signatures, Bala Komatireddy

Master's Projects

The interoperability of heterogeneous blockchain networks is the basis for the widespread application of blockchains in various fields. Cross-chain data oracles play a significant role in enabling distributed applications to exchange data and assets across different blockchains, thereby greatly enriching and expanding the application scenarios and use of blockchains. With the continuous advancement of blockchain technology, more and more researchers and industry participants have begun to focus on developing cross-chain data oracles. Current cross-chain data oracles face issues with trust, as they rely on centralized intermediaries or limited validator networks, increasing the risk of manipulation or single points of failure. …

Rul Estimation Of N-Cmapss Turbofan Engines Using Deep Learning With Customized Penalty And Expanded Sensors, Prathmesh Pethkar

Master's Projects

Accurate prediction of Remaining Useful Life (RUL) for aircraft engines is important to enhance maintenance efficiency and flight safety. For this project, a solution to RUL prediction on NASA's N-CMAPSS data set, mimicking realistic engine degradation under simulated full-flight scenarios, is being proposed. For addressing the high-dimensional noisy sensor data challenge, a new feature engineering pipeline was utilized. Models trained on healthy data predict normal sensor behavior, and the discrepancy between these predictions—referred to as residual features—is a measure of degradation. To handle the size and computational demands of the dataset, training was conducted on Google Cloud Platform using GPU-supported …

Physiotrack: A Gamified Physiotherapy System, Pranavi Chaturvedula

Master's Projects

Traditional physiotherapy methods tend to be non-interactive and provide little to no personalized instruction, even though physiotherapy is critical to stroke recovery. This thesis explores a fully adaptive, sensor-based, feedback architecture intended for stroke patients which remotely supervises movement and personalizes exercises enabled by multimodal sensors. The system uses filtering and windowed segmentation of accelerometer and skeletal data to compute features like jerk, speed, and joint movement angular range. A game engine applies accelerometer and skeletal features together with optimized, lightweight ML models to drive adaptive feedback, scoring, and difficulty adjustment. The architecture supports responsive continuous sensor streaming within the …

Optimization Of Permutation Flowshop Scheduling Using An Island Genetic Algorithm For Makespan Minimization, Sahil Salim

Master's Projects

The Permutation Flowshop Scheduling Problem is a well-known NP-hard combinatorial optimization problem that involves the sequencing of n jobs across m machines in the same order to minimize the total makespan value. This project proposes a Heterogeneous Island Genetic Algorithm framework (HIGA). Each island represents a group of solutions that evolve in parallel using different initialization heuristics, crossover and mutation operators, and adaptive parameters. A dynamic, stagnation-based migration strategy is proposed to maintain targeted communication between the islands. The proposed HIGA approach was compared against the basic Standard Genetic Algorithm (SGA) and a more advanced Niche-based Genetic Algorithm (NEH-NGA) on …

Enhancing Recommender Systems Using Graph Neural Networks, Long Short-Term Memory And Textual Embeddings, Tianxiang Chen

Master's Projects

Recommender systems surround us. They shape what we watch, how we buy, and even what our future might look like next. The Amazon Review Dataset and Movielens, those two datasets will help this project explore how to improve recommender systems through the user’s preferences. Two methods were combined: sequence-based models and graph-based models. Sequence models, such as LSTMs and Transformers, look at the order of user actions to find patterns by their sequence. On the other hand, Graphbased models focus on relationships between users, items, and their attributes. Textual embeddings added depth and context. Both methods offer something special, according …

Performance Comparison Of Machine Learning Across Metal, Cuda, And Neuromorphic Frameworks, Ryan Saini

Master's Projects

Machine learning’s computational demands necessitate optimal performance and utilization. This research compares Apple Silicon M3 Pro with MPS, NVIDIA RTX 3070 GPU with CUDA, and neuromorphic computing for machine learning methods. We provide a cross-platform and cross-architecture performance analysis of machine learning methods to identify optimal configurations for training and inference scenarios. On traditional neural networks, Apple Silicon with MPS delivers superior energy efficiency at the cost of longer processing times for training and inference. NVIDIA with CUDA offers faster computation in training and inference at higher energy costs. Convolutional spiking neural networks perform competitively on event-based data, particularly on …

Synthetic Malware Generation Using Generative Ai, Phanidhar Sai Sravan Chandana

Master's Projects

Malware grows in numbers and complexity, evading conventional signature-and anomaly-based defenses and worsening extreme data sparsity and class imbalance problems for machine learning based detection. Generative models, specifically GANs conditioned on contextual embeddings like BERT have proved effective augmenting training corpora to improve classifier accuracy, but these approaches have largely produced family-specific samples In this paper, we propose a generalized augmentation scheme for generating robust malware embeddings for various families. We begin by extracting opcode sequences from 13 malware families and encoding them into three embedding methods: CountVectorizer, TF-IDF, and BERT’s ‘[CLS]‘ vectors. We therefore train standard GANs and Wasserstein …

Malware Opcode Embedding And Quality Assessment Of Generative Sample Embeddings, Atishay Jain

Master's Projects

Malware is software used to damage and disrupt computer systems with the intent to cause damage to the victim. Malware detection and classification into malware families is a crucial problem for cybersecurity researchers. One of the major bottlenecks in improving these systems is the shortage of good quality labeled malware data, especially for malware families with scarce samples. Researchers have utilized generative models to generate malware data to address this issue. Malware embeddings encode patterns within a malware file, which can be used to detect and classify malware. Recently, encouraging results have been obtained in generating malware embeddings using generative …

Comparative Analysis Of Adversarial Permeability In Cpu-Native, Qat And Onnx-Based Quantized Transformer Models, Fahad Siddiqui

Master's Projects

This work explores securing and optimization of Transformer-based time series forecasting models. We employ several quantization techniques, including quantization-aware training (QAT), and tested the robustness of quantized models by adversarially attacking them. The preliminary results of this work, in our controlled setup, indicate that quantized models outperform the full precision model in terms of robustness against adversarial attacks. They achieved this robustness while showing a very minimal decrease in their forecasting performance.

Large Language Models For Bacterial Genomic Analysis, Manvendra Chavan

Master's Projects

Identification of bacterial gene sequences with agricultural applications has the potential to transform agricultural biotechnology. These genes can be used in environmentally friendly pest control strategies. One such use case is identifying genes with potential insecticidal properties. With an increasing number of genomic information and decreasing numbers of available annotated sequences, finding new insecticidal genes has become more challenging.The traditional methods relying on sequence alignment and annotated databases are not effective in detecting functionally relevant genes lacking close homology to known cases. This project investigates the data-driven classification of genes by sequence modeling. This research is focused on learning DNA …

Genegate: Genetic Gating In A Mixture-Of-Experts For Real-Time Multi-Objective Traffic Signal Control, Rashmi Vishwanath Bhat

Master's Projects

Urban traffic signal control often needs to juggle between competing goals. It needs to minimize delays, reduce emissions, prevent crashes, and prioritize emergency vehicles all while the demand is constantly fluctuating. Traditional fixed-time or statically blended policies cannot reallocate priorities quickly when conditions change. We introduce GeneGate, a mixture-of-experts framework that uses a lightweight genetic gate to fuse four specialist controllers (throughput, emissions, safety, emergency) and adjusts their weights in real time. A short offline genetic search produces a robust initial blend, and an online micro-evolution step refines it every few cycles based on live traffic feedback. GeneGate’s adaptive gating …

Monitoring Plastic Pollution Using Bioindicators: A Global Review And Recommendations For Marine Environments, Matthew S. Savoca, Neil Angelo Abreo, Andres H. Arias, Laura Baes, Matteo Baini, Elisa Bergami, Susanne Brander, C. Anela Choy, Illaria Corsi, Bavo De Witte, Camila Domit, Sarah Dudas, Emily M. Duncan, Claudia E. Fernández, Maria Cristina Fossi, Ostin Garcés-Ordóñez, Brendan J. Godley, Daniel Gonzalez-Parades, Victoria González Carman, Bonnie M. Hamilton, Britta Denise Hardesty, Sang Hee Hong, Shirel Kahane-Rapport, Lauren M. Kashiwabara, Mariana Baptista Lacerda, Guillermo Luna-Jorquera, Clara Manno, Sarah E. Nelms, Cristina Panti, Diego J. Pérez-Venegas, Christopher K. Pham, Jennifer F. Provencher, Sara Purca, Harunur Rashid, Yasmina Rodríguez, Conrad Sparks, Chengjun Sun, Martin Thiel, Catherine Tsangaris, Robson G. Santos

Biological Sciences Faculty Publications

Monitoring the movement of plastic into marine food webs is central to understanding and mitigating the plastic pollution crisis. Bioindicators have been a component of the environmental monitoring toolkit for decades, but how, where, and which bioindicators are used in long-term monitoring programs has not yet been assessed. Moreover, these programs have yet to be synthesized and evaluated globally. Doing so is imperative if we are to learn from these pioneering programs and expand on their efforts. We reviewed global monitoring programs using bioindicators that focus on plastic pollution and found 11 worldwide that met our definition of long-term monitoring. …

Heterotrophy Of Particulate Organic Matter Subsidies Contributes To Divergent Bleaching Responses In Tropical Sclaractinian Corals, Connor R. Love, Kelly E. Speare, Michael D. Fox, Veronica Z. Radice, Kelton W. Mcmahon, Gretchen E. Hofmann,, David L. Valentine, Marie E. Strader

Biological Sciences Faculty Publications

Heterotrophic feeding on plankton and particulate organic matter (POM) by tropical Scleractinian corals is known to aid in the resistance and recovery from thermally induced bleaching. However, the relative importance of heterotrophy in promoting bleaching resistance and recovery is likely to vary based on ecological context and the severity of heat stress. In 2019, the Pacific Island of Mo'orea experienced mass coral mortality during a widespread marine heatwave. Many Acropora hyacinthus colonies on the shallow reef slope (5 m) were resistant to bleaching, while colonies on the deeper fore reef (14 m) often bleached and subsequently recovered, despite similar thermal …

Analyzing Microbial Communities In Porites Astreoides, Sanaa Caldwell, Katie Parker, Daniel Barshis

Biological Sciences Faculty Publications

Coral reefs are vital marine ecosystems that support many different species and ecosystem services through protecting coastlines from storms and erosion, providing raw materials for medication, and facilitating diversity amongst marine species. Anthropogenic climate change is causing ocean temperatures to exceed the range of coral thermal tolerance resulting in more coral bleaching events globally. However, some corals have the capacity to withstand high temperatures through different thermal tolerance strategies. A balanced microbial community plays a critical role in coral health and recent studies have indicated that a balanced microbiome is associated with temperature-stress tolerant corals. Yet, there is a severe …