Electronic Theses and Dissertations

Permanent URI for this collectionhttps://ontariotechu.scholaris.ca/handle/10155/5

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Signal and power integrity analysis of bidirectional DC-DC converters for hybrid energy storage systems with EMI/EMC optimization
(2024-09-01) Ladhar, Manraj Singh; Williamson, Sheldon
Hybrid Energy Storage System (HESS) utilizes multiple energy storage architectures to achieve a broader range of characteristics in terms of power density, energy density and calendar life. A 500W bidirectional synchronous DC-DC converter design is implemented for the active topology of HESS. This thesis examines optimal design principles and practices essential for the printed circuit board (PCB) layout of switching regulators with fast dv/dt and di/dt edge rates to achieve electromagnetic interference (EMI) compliance standards. Furthermore, it focuses on comparative analysis and investigation of near-field noise emissions measured from three PCB designs each sharing the same schematic but different layout design rules and stackup configurations. Reflections, crosstalk, and transmission line management techniques along with power delivery network/system (PDN/PDS) design are implemented for enhanced signal and power integrity. 4-layer board designed with embedded interplane capacitance, controlled impedance traces, proper signal termination and crosstalk management exhibits lowest noise emissions. The experimental results show good consistency with electromagnetic field theory and simulations.
Design of a power, communications, and cable system for use with a robotic crawler for CANDU fuel channel inspection
(2024-09-01) Elvin, Bryce C.; Nokleby, Scott
Canadian Deuterium-Uranium Reactors (CANDU) are currently the only kind of power reactor used in Canada. These reactors supply a large quantity of the energy consumed in Canada. CANDU reactors require regular fuel channel inspection to ensure safety and performance. Fuel channel inspection is currently done one channel at a time which results in significant reactor downtime. The proposed system is a robotic crawler inspection system which can inspect the fuel channels while sealed inside the reactor. This allows for simultaneous inspection of multiple fuel channels using multiple copies of the system. The work in this thesis describes improvements to an existing inspection system. New hardware and software was created for the robotic crawler to improve the performance of different subsystems, as well as facilitate the complete separation of the system from the outside of the reactor. A new cable system was also designed to allow the crawler to have its power and communications system located inside the end-fitting of the fuel channel. The crawler was modified to function wirelessly from the operator, removing the need for wires to be led from the fuel channel to the operator’s device. A proof of concept prototype was created which demonstrates that the system can be operated remotely and that all subsystems can be placed inside of the fuel channel during inspection.
Understanding and defining threats to national security and public safety: a thematic analysis and grounded theory approach
(2024-09-01) Mulyk, Garon; Perry, Barbara
Threats to national security and public safety occupy the minds of many following the 9/11 attacks in the U.S. However, the Canadian national security and public safety mandate is at risk of irrelevance if it fails to adequately address and understand the complex threats Canadians face. Through semi-structured interviews with Canadian law enforcement and intelligence personnel, I use a grounded theory approach to thematically analyze how national security, public safety, terrorism, and hate-motivated incidences are understood and defined by those on the front lines. Hate-motivated incidences are often categorized as a risk to public safety, whereas terrorism is seen as an issue of national security. Currently, there is little literature or definitional analysis on public safety to adequately make this distinction. As such, I argue that national security and public safety should not be considered disparate entities. Rather, a continuum exists where national security occupies one end and public safety lies on the other. Threats such as Severe and Intentionally I/P/R Motivated instances, I/P/R Motivated Violent Extremism, and hate-motivated incidences occupy points along the National Security – Public Safety Continuum (NS-PS Continuum).
Three essays on pricing, quality, and advertising decisions while anticipating a product recall
(2024-08-01) Jafarzadeh Ghazi, Amirhossein; Karray, Salma; Azad, Nader
Product recalls have been rising significantly in both numbers and severity across various industries. The consequences of recalls can be substantial, leading to direct and indirect financial losses for the entire supply chain. Using a game theoretic modelling approach, this thesis examines pricing, quality, and advertising decisions to manage product recalls and mitigate associated risks and losses. The core chapters of the thesis consider three relevant topics on product recall management. In the second chapter, we analyze quality and pricing strategies for two competing firms facing the risk of a severe quality-related recall, which makes the product hazardous and leads to its removal from the market. We develop a two-stage Nash game where the probability of recall depends on the firms’ chosen quality investments, and either firm can experience a recall. Our results indicate that the competitor of the affected firm by the recall should lower its price after the recall if consumers’ price sensitivity changes enough and may increase or keep its price the same otherwise. Surprisingly, considering the risk of a recall does not always lead firms to enhance their product quality. The third chapter considers a monopoly supply chain wherein a manufacturer sells a product through a retailer while anticipating a moderate or minor product recall and subsequent recovery process. Developing a manufacturer-Stackelberg game-theoretic model, we investigate how cost-sharing and revenue-sharing contracts serve as a retailer’s strategies to encourage the manufacturer to enhance product quality, thereby preventing the potential product recall and its associated costs, while also boosting demand. Our results reveal that revenue sharing through bargaining stands out as the most effective contract in driving product quality, diminishing recall probability, and generating higher profits for the manufacturer and the whole supply chain. Nevertheless, the retailer favours typical revenue sharing over the other contracts. In the fourth chapter, we investigate the optimal cooperative advertising and pricing strategies in a bilateral monopolistic marketing channel, including a manufacturer and a retailer, when anticipating a moderate or minor product recall and recovery afterwards. We develop a two-period cooperative advertising game model in which the manufacturer is the leader, and the retailer is the follower. We find that the manufacturer sets a higher wholesale price for its product when there is a recall risk compared to when uncertainties regarding the recall are resolved. Moreover, the retailer’s advertising initiatives and pricing strategies may increase or decrease following the recall, depending on the recall probability and the damage to baseline demand or advertising effectiveness. Finally, the manufacturer consistently favours cooperative advertising pre- and post-recall. This thesis offers several important managerial insights. First, pricing and quality, as well as pricing and advertising decisions, should be managed in an integrated manner to effectively mitigate product recall risks, as independent strategies are less effective. Furthermore, this thesis suggests that managers should adjust their pre- and post-recall strategies in response to changes in the market and consumer behaviour following recalls, such as lost sales and shifts in consumer sensitivity to price, quality, and advertising. Additionally, collaborative contracts between manufacturers and retailers focusing on quality efforts or advertising efforts can significantly enhance supply chain effectiveness when facing product recall risks.
Development and validation of tools to examine neural correlates and constructs associated with sensorimotor integration
(2021-08-01) Ambalavanar, Ushani; Murphy, Bernadette; La Delfa, Nicholas
Subclinical neck pain (SCNP) is linked to disordered sensorimotor integration (SMI), and worse upper limb proprioception. Visuomotor force matching relies on accurate proprioception, but has not been assessed in those with SCNP. Thus, somatosensory evoked potential (SEP) amplitude changes in response to a novel force matching tracking task (FMTT) were compared to a motor tracing task known to impact SEPs. Following both tasks, motor performance improved, with differential changes in SEP peaks associated with cortical and cerebellar processing of proprioceptive input. In addition, disordered SMI in SCNP has never been quantified via a self-report questionnaire. This led to the development and measurement of test-retest reliability of the SMI subscale of “The Spine Dysfunction – Stress and Sensory-Motor Integration Questionnaire” in the SCNP population. The SMI subscale had good reliability for 8 out of 12 questions. The FMTT and SMI subscale are promising measures of correlates and constructs associated with disordered SMI.
Development and evaluation summaries of a percutaneous nephrolithotomy (PCNL) surgical simulator
(2024-05-01) Sainsbury, Ben; Green, Mark; Ren, Jing
Traditional surgical training methods, such as the use of cadavers, and porcine models (pigs) fall short of providing the realistic, real-time feedback necessary for mastering complex procedures. Virtual reality (VR) simulators with haptics offer a significant improvement, delivering immersive and interactive experiences that closely mimic real-life surgeries. Cadavers are also costly, averaging $1,300 each, and are in limited supply. Simulation devices for teaching surgical skills have been shown to significantly reduce surgical errors, enhancing both the safety and effectiveness of surgical training (Anderson & Abrahamson, 2017; Badash et al., 2016; Bushey, 2013; Chen et al., 2021; Chiang et al., 2013; Fried et al., 2005; Pottle, 2019; Sommer et al., 2021). While many existing surgical simulators incorporate elements of VR and haptics, they often lack full integration of a 3D VR operating environment that immerses surgeons completely in the procedural context. The Marion K181 PCNL Simulator addresses this gap by providing a comprehensive VR surgical simulation platform that integrates advanced haptic feedback and accurate 3D models to create a realistic training environment. This simulator aims to reduce the significant number of deaths caused by medical errors in the US, which total approximately 251,000 annually (James, 2013). These errors lead to additional surgeries, lower patient quality of life, and substantial costs to the healthcare system, estimated at $5.95 billion per year (Badash et al., 2016). The evaluation of the Marion K181 simulator demonstrates its effectiveness in improving surgical skills, with users reporting high levels of satisfaction with the realism of the haptic feedback and the accuracy of the anatomical models. This platform not only enhances the technical abilities of surgeons but also provides a cost-effective, ethical, and sustainable solution for surgical training.
Police perception of danger
(2024-08-01) Ouellet, Michael; Frederick, Tyler
Previous research has highlighted the relationship between danger, stress, and the well-being of police officers. Still, gaps remain in understanding officers' perceptions of danger. This study addresses these gaps by exploring the concept of subjective danger perception, a cognitive and emotional response to potential physical or psychological harm. The study identifies that environmental cues influence danger perception and exist on a spectrum shaped by social and personal factors. Firstly, this research modernizes the understanding of subejctive danger perception in policing, which was previously limited and outdated. Secondly, it expands the focus beyond physical injury to include the emotional aspects of danger, identifying stress, anxiety, worry, and fear as key components. Thirdly, it adopts a multi-level approach, exploring situational factors and structural, cultural, and institutional influences on danger perception. Additionally, this study addresses the need for a comprehensive theory in policing by advocating for the social-ecological model. Thus, this research provides a richer, more nuanced understanding of how police officers perceive danger and the impact of police culture. Considering the improvement of the safety and well-being of police officers and their communities, this research used a mixed-method approach to explore police officers in Quebec and Ontario. ANOVA and Spearman’s Rho correlation were used to determine group differences in age/length of service, micro-systems, and situational factors. Furthermore, a thematic analysis will provide rich insights into the different aspects that impact police officers' perception of danger. The study's results determined that the key factors that impacted police officers' perception of danger relate to the individual factors of age and length of service (experience and knowledge). Additionally, more proximal factors (micro-systems) to the individual in the social-ecological model had a bigger impact on police officer's perception of danger than the more distal (exo and macro systems) factors. In brief, this research revealed that further research needs to be conducted on the perception of danger, which could help develop better policies for using force and increase officers' physical and mental well-being.
Unified data management in collaborative IoT systems
(2024-08-01) Ouda, Hossameldin; Elgazzar, Khalid
Data has become a central focus for industries and businesses in delivering services. Furthermore, efficient collaboration solutions for IoT systems are increasingly needed to optimize IoT data usage across various domains. This work provides a comparative analysis between data models for handling heterogeneous IoT data. The analysis shows that the document data model outperforms its competitors with a throughput rate of 597.2/sec and an average end-to-end execution time of 0.54 seconds in CRUD operations on IoT data. Furthermore, the work introduces a data unification framework that standardizes IoT device messages sent to the MQTT broker, eliminating the need to read extensive documentation. The framework includes a data interpreter approach that unifies heterogeneous IoT data into a well-defined JSON document the sensing information along with the metadata for the corresponding IoT device, storing it in data modelling collections. The results show an optimization of 88% in the IoT devices profile more than state-of-the-art solutions like Iotivity and SensorML. Also, Interoperability tests have been carried out in the area of smart intersections and their collaboration with weather and healthcare systems. The tests confirm the framework’s versatility and reliability thus proving its suitability for adoption by the developing community.
Development and experimental investigation of direct urea fuel cells
(2024-06-01) Meke, Ayse Sinem; Dincer, Ibrahim
This thesis study considers the development and experimental investigation of Direct Urea-Hydrogen Peroxide Fuel Cells (DUHPFC). The research focuses on preparing electrodes using nickel zinc iron oxide on stainless steel foil and evaluates single cells and stacks under varying conditions. Optimal single-cell performance is achieved at 65°C with 9 M KOH and 0.5 M urea, yielding a peak power density of 46.38 mW/cm². The stack shows improved performance at 65°C, with a power output of 0.307 kW. The single cell attains an open circuit voltage (OCV) of 0.72 V, while the stack reaches 8.8 V. The energy and exergy efficiencies are 58% and 24% at 5 M KOH for single cells, and 48% and 41% at 65°C for stack, respectively. The electrochemical impedance spectroscopy (EIS) shows impedance reduction from 30 ohm.cm² at 25°C to 15 ohm.cm² at 65°C, indicating enhanced ionic conductivity and reduced resistance. These findings provide insights for advancing DUHPFC technology.
Context-aware pedestrian intent prediction for connected and automated vehicles
(2024-08-01) Abdelkader, Ghadeer; Elgazzar, Khalid; Khamis, Alaa
The safety of pedestrians crossing intersections continues to raise concerns since a continuous level of awareness should be maintained to achieve optimal safety. Advanced safety features in assisted and self-driving vehicles have the potential to augment situational awareness and improve the safety of road users. Detecting pedestrian intention is a key element in providing safer urban environments to automated vehicles. However, the complexity involved in anticipating pedestrian crossing intentions makes the task challenging, as these are internal states characterized by dynamic, non-verbal signals, and unpredictable or sudden movements. Such intricacies can lead to misunderstandings for autonomous vehicles, potentially leading to a higher incidence of pedestrian accidents. To achieve this target, there is a need for real-time crossing intentions for pedestrians. In recent years, there has been an increasing shift towards a new trend in extending deep neural networks into non-Euclidean spaces, commonly known as geometric deep learning. Research in deep learning on graphs is gaining momentum, showcasing the powerful descriptive capabilities of graph structures. These structures provide essential relationship data among various elements, proving invaluable across diverse learning applications. Our study introduces an innovative spatio-temporal graph-based model designed to extract and leverage spatial and temporal features from spatio-temporal graph data. The goal is to uncover hidden patterns within these graphs, which is crucial for accurately predicting pedestrian crossing intentions. By integrating both visual and contextual information, we present a unique approach to structuring traffic scenes as graph data. This involves a novel ego-centric vehicle approach with a wheel topology that effectively captures the dynamics and interactions among traffic participants, the surrounding environment, and pedestrians. Additionally, we explore the most impactful nodes that significantly influence the model’s predictive accuracy. The model was tested on three datasets, demonstrating promising results in predicting pedestrian crossing intentions across various urban traffic scenarios.
Characterizing aerobic and anaerobic performance in alpine skiing
(2024-08-01) Cormier, Justin Curtis; Logan-Sprenger, Heather
The purpose of this secondary data analysis was to characterize dryland performance of trained adolescent alpine skiers from the end of season to pre-season, and to assess the longitudinal changes in dryland jump performance over a 26-month period. Skiers between the ages of 15 and 18 volunteered for this study (n = 8; 16.5 ± 1.1 years; 73.3 ± 10.2 kilograms; 175.9 ± 7.2 cm; VO2max 55.5 ± 7.2 ml/kg/min). Clockwise (p = 0.008) and counterclockwise jump performance (p = 0.001) improved from April to September. Peak power and mean power improved from April to September (p < 0.01). Hexagon jump performance improved over 26 months in the clockwise (p < 0.05) and counterclockwise directions (p < 0.01). These results demonstrate the changes in aerobic and anaerobic performance in youth alpine skiers during different seasons and over a 26-month period.
Energy planning with hydrogen deployment strategies within interconnected infrastructures using enhanced SWITCH model
(2024-07-01) Villalobos Herra, Elena; Gaber, Hossam
The water dimension is not adequately considered in energy models when planning for hydrogen technologies. To overcome this, three novel modules have been developed for the SWITCH energy model: one that considers water drinking systems, a second module that optimizes the size/location/type of hydrogen plants, and the buildings module to integrate buildings using hydrogen-based combined heat and power systems. The modules contribute to the research community by linking the water, hydrogen and power sectors in an energy model. The modules were tested in a case study for Durham Region, using data from 2022. The main results show that the zone of Oshawa is optimal for building a hydrogen electrolysis plant, but facing drastic changes in its power and water demands. Results also show hydrogen-based combined heat and power systems would not be economically feasible unless the price of hydrogen per kilogram is less than CAD$2.13, considering the 2022 parameters.
Examining women’s knowledge, health risk perceptions, beliefs and behaviours in relation to toxic chemicals commonly found in personal care and household products: a mixed-methods approach
(2024-08-01) Trifunovski, Adrianna; Barakat, Caroline
Many personal care and household products (PCHP) contain toxic chemicals harmful to health. For instance, parabens, commonly found in shampoos, are endocrine disruptors that increase the risk of hormonal and reproductive disorders among women. Despite safer alternatives, research suggests women are unaware of these risks and options. This research used a mixed-methods approach to examine knowledge, health risk perceptions, beliefs, and avoidance behavior of women regarding toxic chemicals in PCHP. It focused on lead, parabens, bisphenol A (BPA), phthalates, triclosan, and perchloroethylene. A questionnaire was administered to 200 women, and 10 women participated in virtual interviews. Multivariate analysis found positive associations between avoidance of lead, parabens, BPA, and phthalates and knowledge, perceived health risks, and harm beliefs. Higher education and chemical sensitivity diagnoses increased lead avoidance. Factors influencing PCHP purchases included price, social media, effectiveness, and brand preference. The study emphasizes enhancing women’s knowledge about PCHP health risks and the importance of safer alternatives.
Multi-omic analysis of contaminated sediments from Contrecoeur, QC on Planorbid snails
(2024-07-01) St-Laurent-Guérin, Jeanne; Gilroy, Ève; Simmons, Denina
Contrecoeur’s history of industrial development resulted in sediment contamination (by butyltins, heavy metals, and petroleum hydrocarbons), which can be harmful to aquatic and benthic life. Additionally, future development threatens to further exacerbate the contamination in the area. This study examines the effect of Contrecoeur’s contaminated sediment and increased water temperature on Planorbid snails’ survival, growth, reproductive output, metabolomic profile, and proteomic profile. A two-week in-situ exposure was performed on Helisoma trivolvis, and a 28-d laboratory exposure of Planorbella pilsbryi to the same sediments was completed. Snail tissue samples were collected for proteomic and metabolomic analysis. Sediment contamination caused mortality and affected the insulin signaling and the transsulfuration pathways. Thermal stress increased the effect of ammonia through urea metabolites and affected the abundances of guanidinoacetate, creatine, and creatinine. The other effects (on DNA translation and transcription, on energy metabolism, and on key biomarker proteins) cannot be attributed specifically to one stressor.
In pursuit of the good life: masculinity and reintegration
(2024-08-01) Stevenson, Alia M.; Harkins, Leigh; Cesaroni, Carla
Successful reintegration is not simply desistance from crime but a fulfilling life without crime. These studies utilize the Good Lives Model (GLM) and masculinity theory to understand barriers or facilitators to reintegration for previously incarcerated men. In Study 1, a sample of 35 previously incarcerated men were utilized to examine whether endorsement of masculine norms and achievement of goods in the GLM were related to perceived reintegration success. Results showed that self-reliance (i.e., reluctance to seek help) and emotional control (i.e., reluctance to share emotions) were negatively related to the achievement of goods in the GLM. In Study 2, 19 participants from Study 1 were interviewed to explore the above themes in greater depth. Barriers and facilitators consistent with Study 1 were observed, with self-reliance and emotional control emerging as key themes. The current studies highlight both positive and potentially problematic conceptions about being a man that could be applied alongside the GLM in reintegrative programming.
Bias and fairness in transfer learning
(2024-07-01) Salmani, Parisa; Lewis, Peter R.
Transfer learning involves using knowledge from one task to improve performance and reduce training time on a related task. However, recent studies highlight a critical issue: the fairness of models trained with transfer learning. One study showed that transfer learning can transfer intentionally planted biases from the source task to the target task. This thesis explores a different but equally critical problem: whether transfer learning can introduce new biases or lead to greater biases in the target task. Our investigation reveals that transfer learning can introduce varying degrees of bias in the target task that were not present in the source task. We examined two applications that commonly use transfer learning. Our findings indicate that, in both cases, transfer learning increases bias concerning sex, age, and race compared to non-transfer learning methods trained from scratch, which are nearly as accurate. These results emphasize the need for understanding the limitations and risks of transfer learning, especially in high risk domains like healthcare and security, and call for further research into conditions under which transfer learning introduces and amplifies bias.
Forced sterilization in the 21st century: A qualitative analysis of women's experiences in Canada
(2024-08-01) Morton, Mckenzie A.; Cesaroni, Carla
Among women’s reproductive rights issues, non-consensual sterilization (NCS) is commonly overlooked or mistaken as a historical issue, despite being prevalent today. While sexual sterilization can have benefits, it is traumatic when performed without consent. Research suggests that women belonging to marginalized groups – particularly racialized or cultural minorities, women with intellectual disabilities, impoverished women - have historically faced higher risks of NCS in Canada. To gain a comprehensive understanding of the scope of this issue, this study proposes a secondary analysis of the testimonies of women who have undergone NCS in Canada in the late 20th and early 21st centuries. Utilizing qualitative methodologies, the study identifies common themes in these narratives, which call particular attention to the systemic failures in Canadian healthcare ethics and practice, the psychological and cultural consequences of NCS, and the demand for justice by survivors. Feminist bioethics provides a critical framework, emphasizing the importance of intersecting social identities.
Development and evaluation of Nuclear-Renewable Hybrid Energy System simulator with load following
(2024-07-01) Lopes Alves Esteves, Otavio; Gaber, Hossam
This thesis addresses the integration and optimization of Nuclear-Renewable Hybrid Energy Systems (N-RHES) with a focus on Load Following (LF) capabilities. The primary aim is to enhance the operational flexibility of nuclear reactors to adapt to dynamic power demands. A dynamic simulation tool was developed for different nuclear reactor technologies, including Pressurized Water Reactors (PWR) and Molten Salt Reactors (MSR), enabling detailed analysis of reactor power behaviour under different Load Following scenarios. Additionally, a Nuclear Reactor in the Loop (NRiL) system was implemented for accurate real-time evaluation of control systems, providing precise assessments without the need for expensive and time-consuming physical tests. The final component, the Nuclear-Renewable Hybrid Energy System Simulator (N-RHESS), integrates an energy management system within the simulation environment, improving N-RHES designs and decision-making by allowing users to develop complex energy load profiles and assess the feasibility of integrating nuclear reactors. The research demonstrated significant improvements in the operational efficiency and economic viability of N-RHES, highlighting its potential to enhance grid reliability, reduce carbon emissions, and promote sustainable energy solutions. This work contributes to the field of energy systems engineering by providing innovative tools and methodologies for integrating and optimizing nuclear and renewable energy sources.
Consent and sexual assault in heterosexual versus same-sex sexual encounters
(2024-07-01) Kirkpatrick, Sarah M. M.; Emeno, Karla; Vettor, Shannon
Consent is a vital component of all sexual encounters, and its absence can lead to harmful sexual behaviours. Although the concepts of consent and sexual assault should be applied appropriately to all individuals, this may not be the case. This thesis examined whether public perceptions of consent and sexual assault differ based on participant gender and rape myth acceptance, as well as the sexual orientation of individuals portrayed in various sexual encounter vignettes. It also examined whether specific behaviours are perceived as universally consenting or non-consenting by participants. Results of this study suggest that the public can accurately identify consent and sexual assault, with little evidence for differences across heterosexual versus homosexual vignettes. However, male participants with high rape myth acceptance demonstrated diminished accuracy in identifying consent and sexual assault in certain scenarios. Several behaviours were found to be reasonably universally consenting and non-consenting by participants. Implications will be discussed.
A targeted reverse mapping machine learning approach for non-dominated solutions in multi-objective optimization
(2024-08-01) Kermani Poor, Masoud; Ibrahimi, Mehran; Rahnamayan, Shahryar
Multi-objective optimization problems aim to identify solutions that maximize or minimize conflicting objectives. Population-based multi-objective algorithms, inspired by biological populations, are effective but often provide limited solutions within the decisionmakers’ region of interest (ROI) on the Pareto front. Recent advancements in machine learning have shown promise in generating solutions, yet they suffer from a lack of control and require knowledge of objective function attributes. This study proposes a framework using Gaussian process regression and artificial neural networks to generate innovative solutions in the ROI. By employing diverse sampling techniques and integrating long term memory, the framework can produce more than twice as many solutions in the ROI, as demonstrated in experiments with real-world problems and various benchmark functions.

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