Master Projects & Major Papers

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    Development and validation of scaled electric combat vehicle virtual model
    (2023-11-01) Vaz, Glenn Xavier; El-Sayegh, Zeinab
    This research focuses on an 8x8 scaled electric combat vehicle (SECV) and aims to create a virtual model made of the same vehicle on a vehicle dynamics simulation software using parameters from the actual vehicle. In the proposed vehicle, each wheel is independently driven and steered. MATLAB and Simulink software were used to design and implement the electric powertrain while TruckSim Modelling and Simulation software was used to simulate the on-road conditions tests. The simulation data was then compared with the experimental data obtained from the physical test scenarios.
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    Filtering honeywords using probabilistic context free grammar
    (2023-10-01) Tanniru, Alekhya; Vargas Martin, Miguel
    With the growing prevalence of cyber threats, effective password policies have become crucial for safeguarding sensitive information. Traditional password-based authentication techniques are open to a number of threats. The idea of honeywords, which was developed to improve password-based security, entails using dummy passwords with real ones to build a defence mechanism based on deceit. The importance of password policies is examined in the context of honeywords in this study, emphasizing how they might improve security and reduce password-related risks. We present the idea of using the existing passwords to extract a policy and using this policy to filter good and strong passwords. Through this capstone project, we aim to contribute to the broader understanding of honeywords and their role in improving password-based authentication systems. I have conducted experiments on Chunk-GPT3 and GPT 4 models, to see which one of the models produces more honeywords which are very similar to the real passwords.
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    Enhancing password security: a quest for optimal honeywords
    (2023-10-01) Nety, Meher Viswanath; Vargas Martin, Miguel
    In this capstone report, our primary focus is on harnessing the capabilities of the GPT4 model to enhance password security through the generation of honeywords. Honeywords are decoy passwords designed to strengthen the security of sensitive systems by confusing potential attackers. The utilization of GPT4, a powerful language model developed by OpenAI, offers a n innovative approach to this challenge. By directly generating honeywords without relying on password segmentation, GPT4 introduces a unique dimension to password security. This approach is particularly valuable in thwarting targeted attacks, as honeywords generated by GPT4 are designed to deceive potential attackers effectively. In addition to the exploration of GPT4, this report also delves into the realm of Chunk-GPT3. Chunk-GPT3, as detailed in previous research, employs advanced language models to generate honeywords through the segmentation of passwords into discrete chunks. These chunks are ingeniously recombined to form decoy passwords. The re-engineered Chunk-GPT3 approach incorporates enhancements to the password segmentation process, including ”mapping digits to alphabets” and ”removal of digits” functions. These modifications aim to produce more potent and effective honeywords, ultimately elevating password security. The report includes a comprehensive comparative analysis of honeywords generated by the original Chunk-GPT3 approach and the re-engineered Chunk GPT3 approach, as well as honeywords created by GPT4. By assessing the effectiveness of these honeyword generation methods using the HWSimilarity metric, the report provides valuable insights into the strengths and weaknesses of each approach. Examining the capabilities of both GPT4 and Chunk-GPT3 in the context of honeyword generation, this report aims to provide a holistic perspective on cutting-edge strategies for safeguarding sensitive data in the ever-evolving digital landscape.
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    Guarding the gate: using honeywords to enhance authentication security
    (2023-10-01) Koppada, Gowtham; Vargas Martin, Miguel
    A honeyword (false password) can be defined as a duplicate password (rearranged) resembling the same characteristics of the original password. It is very challenging for any cyberpunk to distinguish between a real password and honeyword (containing PI). Using HGT’s (honeyword generation technique), these honeywords are generated in lump sum and the hashed honeywords are placed in an organization database with triggers to identify breach before it’s too late. In accordance with the previous research, the concept of HGT’s might fail if the generated honeywords does not contain the personal information of the user, making it easy for the attacker to perform targeted attack. It is a good practice to include the chucks containing PI or part of the original password of that particular user in generated honeywords to make it look natural. In order to generate such honeywords with chunks, the concept of prompt engineering in LLM (Large Learning Models) is used. In this report, we tried to improve the existing prompt, making it easy for the LLM to get deep understanding and to produce better throughput. In addition to that, we compared the base GPT Learning model (existing) with the newly upgraded GPT models like GPT-3.5-turbo and GPT-4. Considering the ‘strength of password‘ as a base factor, we came up with results and statements stating which model outperformed the others.
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    Using the evidence-development-validation-consensus (EDVC) approach to develop an online training program for healthcare professionals and laypeople to provide outside-hospital cardiac arrest care in rural and remote places
    (2023-09-01) Gino, Bruno; Dubrowski, Adam
    Introduction: The COVID-19 pandemic exacerbated challenges in delivering cardiac arrest (CA) courses in remote and rural (R&R) areas and affected training for laypeople (LP) and healthcare professionals (HCPs). Due to the combined issues, medical education suffered, including the suspension of basic life support and defibrillation (BLSD) training. Materials and Methods: In this study, researchers developed an online training program via evidence-development-validation-consensus (EDVC) approach using a learning management system (LMS) model. Results: A comprehensive online training program should encompass cognitive, affective, and psychomotor learning domains, addressing various skills and knowledge aspects in BLSD training. Conclusion: The study presents the EDVC approach used to develop an online training program, enabling effective out-of-hospital CA care courses in R&R places. The program incorporates expert feedback and improves knowledge and techniques in automated external defibrillator (AED) delivered by drones use.
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    Co-designing instruction in virtual learning environments using AI
    (2023-12-01) Ganesh, Aishwarya; Hunter, William
    The literature was explored to determine how artificial intelligence (AI) systems and algorithms are currently being used in the co-design of learning within virtual learning environments. Through the analysis of literature, the study aims to retrieve multiple methods of AI assistance to ease or uplift the educator’s role in online learning design. The study determined a variety of themes that determine methods of AI use in online instruction, such as prediction, providing feedback, adaptive learning, and providing visualization of student data on learning management systems (LMS). The study also determined the importance of a repository of various student data input in AI algorithms, and the collaboration of educators and experts in the process of using AI systems. The key implications suggest the importance of bridging feedback immediacy and formative approaches to improving student performance in online environments. Furthermore, the study also determines the changing roles of stakeholders in the education process. Finally, it also suggests the potential to create a multifaceted AI system and an effective LMS that supports such features.
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    Instructional design and development tools for online adult education: a literature review
    (2023-12-01) Elbaghdadi, Ziad; Hunter, William
    This paper examines the intersection of online learning, adult learning theories, and instructional methods in adult education. Through a comprehensive literature review, it analyzes prominent adult learning theories and models, emphasizing their implications for designing effective learning experiences. The study also explores adult learners' unique characteristics and needs, addressing key features such as self-directedness, experience, intrinsic motivation, and external factors influencing learning. Additionally, the paper discusses instructional design methods for online adult learners and identifies key principles, including the importance of feedback, engagement through collaborative activities, and personalized learning experiences. The analysis covers experience-based learning, scaffolding, blended learning models, and the role of technology, with a focus on learning management systems. The study also explores the significance of online communities of practice for collaborative adult learning, emphasizing factors influencing engagement and success. Overall, the findings provide valuable information for educators, instructional designers, and researchers seeking insights into online education for adult learners.
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    Ontario Ministry of Education’s Policy/Program Memorandum 140: a review and critique of current resource allocation and practices for supporting autistic students in elementary classrooms
    (2023-12-01) Conway, Kathleen M.; Power, Rob
    A review of recent literature on Applied Behaviour Analysis (ABA) and alternative evidence-based therapies for autistic students, as well as data extracted from Ontario school boards’ recent financial reports. Information from this review is used to conduct a critique of Ontario's Policy/Program Memorandum 140 (PPM 140) by scrutinizing current funding models to determine whether they allow the policy to be implemented in a way that facilitates execution of Applied Behaviour Analysis (ABA) methods that align with best practice recommendations. The critique determines that most of Ontario’s school boards are currently underspending from their Behaviour Expertise Amount (BEA) allocations, which are intended to fund ABA training for educators, ASSD programs for students, and school board hiring of behaviour experts. Data reviewed as part of this critique revealed that half of Ontario’s school boards employ two or fewer full-time behaviour experts. Based on best-practice guidelines, this behavioural expert-to-student ratio makes the mandated requirement of integrating ABA methods into the IEPs of students unsustainable and likely means that autistic students are not receiving the required support. Underspending in ABA training for educators indicates that limited teacher-focused educational opportunities are available, creating a divide between policy and practice. The current approach to PPM 140 in Ontario schools renders genuine and authentic application of ABA principles difficult, if not impossible, to implement and indicates a need for improvements moving forward. This critique and review of the literature reveals that PPM 140 could be more efficient if new oversight and monitoring protocols could be developed, including standards and quality indicators used to establish training requirements for education staff, behaviour expert hiring practices that align with board enrollment numbers, and accessible data collection protocol to monitor implementation and to measure student outcomes.
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    The challenges and benefits of assistive technology and educational programs for educators, caregivers, and youth with multiple exceptionalities/special needs
    (2023-08-23) Ivan, Paula M.; Hunter, William J.
    Assistive technology (AT) is a process that provides opportunities for youth with multiple exceptionalities/special needs to learn, grow, and discover meaningful avenues in order to navigate through an evolving digital world. A growing body of research literature suggests that when assistive technology is introduced into the educational curriculum by teachers, included in the educational system by stakeholders, and made accessible in the learning community; it has the potential to enhance digital literacy, language, and numeracy skills for youth with multiple exceptionalities/special needs. Assistive technology also has the potential to augment cognitive development, language development, social development, and physical development, while improving the overall well-being of youth with multiple exceptionalities/special needs. This systematic literature review is qualitative by nature and seeks to explore the broad question, “what are the challenges and benefits of assistive technology and educational programs for educators and families of youth with multiple exceptionalities/special needs in the educational system?”
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    Substance use disorder education for emergency registered nurses
    (2023-08-14) Shillington, Kelly; Lemonde, Manon
    Patients with substance use disorders (SUD) constitute up to 1 in 11 emergency department (ED) visits in North America and this number increasing throughout the COVID-19 pandemic (Morin et al., 2017). The ED presents an excellent opportunity to intervene and improve care for patients with SUDs, however there is currently no required or expected level of competency in managing SUDs for registered nurses (RNs) working in an emergency setting. To inform an educational intervention for improving nursing care for patients with SUDs, this project aimed to leverage nursing leadership opportunities to understand the current competency and confidence amongst ED RNs and identify gaps to be ameliorated through continuing education and policy implementation.
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    Enhancing password security: advancements in password segmentation technique for high-quality honeywords
    (2023-07-01) Sannihith Lingutla, Satya; Vargas Martin, Miguel
    Passwords play a major role in the field of network security and play as a first line of defense against attackers who gain unauthorized access to the profiles. However, passwords are vulnerable to various types of attacks making it essential to ensure that they are strong, unique, and confidential. One of the major techniques that evolved over time to enhance password security is the use of honeywords that are decoy passwords designed to alert the administrator when a data breach has happened. The main goal of this project is to addresses one of the limitations of a honeyword generation technique, called Chunk-GPT3, by performing better password segmentation through a re-engineered chunking algorithm that maps digits into characters, and which would seem to lead to better honeywords. We justify our re-engineering method and generate honeywords that we compare to those generated by Chunk-GPT3. Nonetheless, after evaluating honeywords using the HWSimilarity metric, the results suggest that improved chunking does not necessarily lead to better honeywords in all cases.
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    Exploring the perceptions and concerns of Canadian international students (IS)
    (2023-07-01) Parmar, Nagina; Hunter, William; Stokes, Joe
    Higher education institutions may not fully understand the challenges faced by international students (IS), such as housing, mental health, and discrimination. The present study looked at factors that influence IS’s decision to study abroad, using a push-and-pull framework. The study began after approval from Ontario Tech and Toronto Metropolitan University ethics boards. 95 students completed an online questionnaire and 10 were interviewed for more details. Our findings suggested various factors, which can either attract or deter IS, and impact their decision to pursue their education in this country. Information collected will be used to shape policies and practices at participating universities.
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    The evolving role of online assessment as a steering mechanism for 21st-century learning
    (2023-08-01) Lean, Graham; van Oostveen, Roland
    Framed by Jürgen Habermas’ theory of society as being constituted of systems and lifeworlds, this project aims to critically analyze the recent academic literature on online assessment in higher education. Through a metasynthesis template analysis, the research in this project intends to uncover themes that help elucidate what informs assessment design, development and implementation in online learning and the impacts this has on teaching and learning. The findings suggest that online assessment in higher education is geared towards instilling 21st century learning skills through more formative assessments. However, somewhat paradoxically, the desire to instill these skills and satisfy institutional imperatives is leading to the closer monitoring of student learning and activity through assessments. These developments in online learning are contributing to the changing roles of teachers and students, with the former entailing a focus on facilitation, or management, and the latter an emphasis on self-reliance. Nevertheless, there remain opportunities for collaboration and communicative action through online assessment practices.
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    Health care provider’s perceptions of a newly revised eHealth breastfeeding resource for use in clinical practice to increase breastfeeding health literacy
    (2023-08-01) Azam, Sidra; Abbass Dick, Jennifer; Lemonde, Manon
    Global breastfeeding rates are low, despite the World Health Organization’s breastfeeding recommendations. Health care providers are encouraged to provide education and support. Ehealth resources are increasingly being used to provide breastfeeding information to patients. The purpose of this project was to determine health care providers’ perceptions of a newly revised eHealth breastfeeding resource. This project followed a program evaluation approach and addressed the resources component of the logic model framework. Healthcare providers in Ontario were surveyed to determine their perceptions of the content, design and usability of a breastfeeding eHealth resource for use in clinical practice to increase breastfeeding health literacy and rates. The findings suggest that minimal revisions are needed to the resource and indicate that healthcare professionals found it acceptable for use in their clinical practice.
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    Assessing the behaviour of solid particulates in the flow of molten salt reactor coolant circuits
    (2023-04-01) Arthurs, Cole William; Piro, Markus
    This work investigated solid particulate behaviour in molten salt nuclear reactors. Solid particulates are expected to form from fission products reacting with fuel components, creating compounds with melting temperatures above the reactor operational temperature. These particulates may present operational risks including flow obstruction and corrosion. A sensitivity analysis was performed by simulating flow of molten salt within a reactor containing solid particulates via Computational Fluid Dynamics, where three parameters of the particulate were varied: diameter, density, and initial concentration. A case was simulated where values for these properties were selected based on a review of related literature. Subsequently, two more simulations were performed for each parameter using high and low values within the expected ranges, modifying only one parameter at a time. Results indicate that particle diameter has low impact on fluid dynamics of the reactor, but particulate density and concentration resulted in increased localized accumulation and cyclical movement of the particulate at the reactor outer edges.
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    Matching expectations and reality in AI systems - cybersecurity use case
    (2023-04-01) Defo Aymar, Tala; Lewis, Peter
    Artificial intelligence (AI) is a growing field in computer science which develops intelligent systems capable of performing things that a human mind can do. The manufacturers of security systems integrate AI capabilities into their systems for threat hunting, and market them with an emphasis on AI used to provide security features. This study evaluates the expectations of marketed AI features with reality in a use case of a cybersecurity system. To this end, we evaluated a system in a real-live environment with huge amount of data sent to it for analysis. Our evaluation demonstrates that, first, the virtual security analyst feature provided by the system cannot replace a human security analyst as it can only perform 3 amongst the 8 tasks of a human security analyst. Secondly, marketing claims exaggerate regarding the features provided by AI in the system.
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    Conceptual videos in mathematics: theory to practice
    (2023-03-01) Allen, Rachel K.; LeSage, Ann
    This project begins by providing an overview of the research on the purpose and criteria for creating quality educational videos and the development of a conceptual understanding of proportional reasoning. The paper then shifts from theory to practice, illustrating how I used research to create a four-part video series titled Is it Proportional? Designed for middle school students, the videos demonstrate identifying and solving proportional and non-proportional situations. The videos are analysed through the lens of technological design, content and pedagogical choices, focusing on the practical application of theory. The issues and successes of putting research into practice are critiqued, finding potential for conceptual videos in the middle school classroom, with a need for content and pedagogical understanding and acknowledgement of barriers such as time and access to technology.
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    Comparative economic analysis of conventional and plug-in battery electric vehicles in Canada
    (2022-12-01) Muaz ur Rehman, Muhammad; Ibrahim, Walid Morsi
    Conventional vehicles typically use gasoline for their internal combustion engines (ICEs). On the other hand, plug-in battery electric vehicles (PBEVs) use electricity to charge their batteries, so they do not need gasoline. With the soaring gasoline prices in Canada and around the world, the interest in electric vehicles from the public and the government has increased. However, given the wide range in prices of PBEVs, the high maintenance cost of conventional vehicles and the volatility in gasoline prices, there is a need for a comparative economic analysis to address the following two main questions: (1) What should be the minimum ownership period of a PBEV to be economical than a conventional vehicle? (2) At what gasoline prices do the PBEVs become more economical than conventional vehicles? The work in this project addresses these questions to assist customers in making the correct decision when they intend to purchase a new vehicle. The results have shown that the longer the ownership period is, the PBEVs become more economical compared to conventional vehicles. The work in this report has shown that the total ownership cost savings may reach $88,482 over 15 years.
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    Development of a point-kinetics simulator for molten-salt reactors
    (2022-08-01) Mazher, Momal; Nichita, Eleodor
    Molten-salt-fueled reactors (MSRs) are nuclear fission reactors that use a mixture of fissile material and molten fluoride salts as both fuel and primary coolant. Such reactors, which can operate at low pressure and high temperature, have been initially proposed in the 1950s and have been the subject of renewed interest and investigations in the last decade. In contrast to regular, fixed-fuel reactors, the dynamic behavior of MSRs is determined by both the fuel properties and by the fact that fuel is constantly flowing in and out of the core, which causes some of the delayed-neutrons to be produced outside the core, thus not contributing to the fission chain. Most of the kinetics codes in current use for power reactors do not have the capability to account for fuel convection (flow). The objective of this work was to develop a point-kinetics code for simulating MSR transient behavior while accounting for fuel convection, with intended applications in education and preliminary studies of MSR conceptual designs. The code was developed in the FORTRAN programming language and uses finite differences to discretize the coupled differential equations. Several MSR-specific transient scenarios are analyzed using the developed code to demonstrate its capabilities, to illustrate how the dynamic behavior of the reactor is influenced by changes in the fuel flow rate, and to study the effect of different precursor-mixing approximations.
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    Student webcam use and its impacts on teacher self-efficacy, engagement, and well-being: a literature review
    (2022-11-01) Lee, Melanie E.; Laffier, Jennifer
    Due to the COVID-19 pandemic lockdowns in March 2020, higher education institutions around the globe had to quickly pivot online. Since then, many schools have relied on video conferencing platforms equipped with webcams to help teachers and students stay virtually connected during synchronous classes. However, an ongoing trend has emerged in which students are not using their webcams during their online classes even though teachers wish them to do so. Thus, the following literature review investigated the reasons for student webcam use and non-use, as well as the impacts of this use and non-use on teachers’ well-being, self-efficacy, and engagement. Overall findings, gathered between 2020 and 2022, revealed that a lack of student webcam use can negatively impact teachers’ self-efficacy, engagement, and well-being. Implications and theory are discussed, which provide a framework for further analysis of the disconnect between students’ intentions and teachers’ expectations for webcam use in synchronous learning.