Master's Theses
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Item Open Access Meteorological risk assessment of Canadian transcontinental freight railway: Case study of Saskatchewan and Ontario(Faculty of Graduate Studies and Research, University of Regina, 2023-08) Bahramimehr, Mehrnoush; Khan, Sharfuddin; Khondoker, Mohammad; Ruparathna, Vithanapalpita Koralalage Rajeev JayangaRailway transportation is the heart of the supply chain in Canada. The reason is that railway transportation is known as one of the most reliable and safest modes of transportation. However, due to its complexity, a wide range of risks are associated with this means of transportation. Considering Canada's climate, studying meteorological risks associated with the railway network can be useful for decision-makers in railway transportation, especially when preparing for cold seasons and implementing railway network development. In this study, a comprehensive spatial analysis using ArcMap has been applied to identify hotspots and vulnerable geographical areas in terms of meteorological factors in two provinces with slightly different climates: Saskatchewan and Ontario. Floods, rain, snow, minimum temperature, and wind have been selected as factors to generate meteorological risk maps for the mentioned provinces. The selected railway network for analysis is the Canadian National Railway (CN), one of the two major railways in Canada and the only Transcontinental Freight Railway in North America. However, the results can be applied to any other railway network in Canada. After developing risk maps for each factor, 5 different types of integrated risk maps are generated in this thesis. The first type assumes that the weight (importance) of all factors in causing accidents or service disruptions is the same. Two versions utilize different weights for different factors. One version applies score-based weighting of factors, while the other employs expert opinion-based Analytical Hierarchy Process (AHP). Additionally, two season-based risk maps for warm and cold seasons are also generated. The risk maps demonstrate hotspots and hazardous areas that require more attention and planning to maintain the continuity of the supply chain. The results can be used to enhance safety, reduce service disruptions, and ensure the smooth operation of the railway network.Item Open Access Classifying ovarian cancer using machine learning methods(Faculty of Graduate Studies and Research, University of Regina, 2023-11) Rahman, Rushda; Peng, Wei; Henni, Amr; Muthu, S. D. JacobOvarian cancer is one of the most fatal cancers for women nowadays. It is ranked as fifth most common cancer deaths among women resulting more deaths than any other cancers in female reproductive system. According to Canadian Cancer society that about 3000 ovarian cancer patients were detected, and among them 1950 patients died in 2022 which indicating more than 50% of mortality rate. Ovarian cancer is mainly generated from cancerous ovarian tumour. So, it is very important to classify cancerous tumour from noncancerous tumour to prevent false positive for ovarian cancer. Moreover, if cancerous tumour is diagnosed in early stage, it can be prevented from spreading and thus survival rate for ovarian cancer can be increased. Also, by separating cancer patients from benign tumour patients, it will be easier for doctors to know the stages of the cancer and know patient’s prognosis and life expectancy. The principal and initial objective of this thesis is building a feasible system using Artificial Intelligence which is easy to use and compatible to classify ovarian cancer. Proposed study will give a new non-conventional way to classify ovarian cancer from ovarian tumour which will be affordable for the patients. Moreover, one of the primary benefits of this study is that doctors/physicians can detect ovarian cancer with only blood test/ serum test. There is no need to do any expensive tests such as: ultrasound, MRI or CT-Scan. The main concept of this research is the application of several machine learning techniques to correctly classify ovarian cancer and finding best technique among those in terms of Accuracy, Precision, Sensitivity, and Specificity. Original dataset is taken from website named Kaggle (https://www.kaggle.com/). This dataset is screened, cleaned and normalized first and then expert’s advice has been taken to extract the most important features to do the correct classification. Later, a correlation test has been done for better understanding of the relations and independency among the input features. 10 input features have been selected including age, menopause, CA-125, AFP, NEU etc. From correlation test result 7 inputs were taken again and a comparison had been made between 10 inputs and 7 inputs. And the output is TYPE which denotes 1 for benign ovarian tumour and 0 for ovarian cancer. Four machine learning models have been used for classification and they are, ANN, SVM, Naïve Bayes, and k-NN. Training of each model is performed and after training, each algorithm is tested and hence performance is calculated and compared. After analysing results, it is found that for the problem considered, the Artificial Neural Network (ANN) is the best classifier in terms of accuracy giving 85.91% accurate results on test data whereas SVM, NB and k-NN gave accuracy of 76.05%, 83.09% and 76.06% respectively. In terms of sensitivity and precision calculation, Naïve Bayes is best, and the ANN Classifier is second best algorithm. Taking specificity into Consideration, the ANN is best with 87.50%. Keywords: Machine Learning Classifier, Ovarian Cancer, Benign Ovarian Tumour, Artificial Intelligence, Artificial Neural Network (ANN), Support Vector Machine (SVM), Naïve Bayes (NB), k-nearest Neighbour (k-NN), Confusion Matrix.Item Open Access Carbon capture, utlization, and storage supply chain risk management framework development(Faculty of Graduate Studies and Research, University of Regina, 2023-12) Kabir, Md Ainul; Kabir, Golam; Kahn, Sharfuddin; Tontiwachwuthikul, PaitoonTechnology called Carbon Capture, Utilization, and Storage (CCUS) is important for capturing CO2 emissions before they get into the air. Because everyone wants to stop global warming by reducing CO2 emissions, CCUS is an important and emerging technology that can help slow down climate change, lower emissions in many areas, and support the move to a sustainable and carbon-neutral future. As CCUS technology and its adaptation increases, it is very important to pay attention to the CCUS risks from the supply chain (SC) point of view. The ultimate goal of this study is to is to identify CCUS supply chain risks and develop a framework that provides a structured approach to ensure safe and reliable CCUS supply chain. This study develops a complete CCUS SC risk management framework including CCUS SC functions, risks and risk management strategies. Therefore, this study analyzes the literature related to SC of different sectors and identifies the SC risks which is the foundation for CCUS SC risks identification. This study depicts that there is no research article that provides a comprehensive CCUS SC risks as well as risk management framework that connects with risk management strategies. Moreover, the framework provides a guideline for future research which enrich the CCUS supply chain risk management system as well as fight against the climate change. This study has deployed Delphi technique to validate the risks that have been identified from the literature. In addition, principal component analysis (PCA) has been used to identify the communalities of the risks related to the CCUS SC functions. At the same time, 44 risk management strategies have been developed from the supply chain risk management literature in relation with the CCUS SC risks. Finally, the risk management framework has been developed in CCUS SC context which is the main objective of this study. This is the first risk management framework in CCUS SC context which connects the CCUS SC functions, risks, and strategies. This framework provides a comprehensive guideline for the management to develop sustainable roadmaps in CCUS SC management systems. Moreover, this framework helps to prevent the environment and promotes further research in CCUS risk management systems. Keywords: Carbon Capture, Utilization, and Storage (CCUS); Supply Chain (SC); Supply Chain Risk; Risk Management (RM); Principal Component Analysis (PCA), Risk Management Strategies.Item Open Access Design, development, and control of an off-road hybrid electric vehicle power system(Faculty of Graduate Studies and Research, University of Regina, 2024-01) Hedayat Pour, Mehdi; Mehranddezh, Mehran; Stilling, Denise; Kabir, GolamWith global warming and climate change threatening the planet, the auto industry is transitioning from conventional internal combustion engines to electrical power trains. Globally, electric vehicles and hybrid electric vehicles are becoming popular with 10 million cars sold in 2022. Electrification is not limited to the personal cars and public transport, but includes applications in transportation, mining, and military. The power system and battery pack are the main components of electric and hybrid electric vehicles. Battery pack capacity and performance affect the overall mileage. This thesis models and sizes the battery pack based on the mechanical and electrical specifications of the vehicle. The control algorithm is the heart of an unmanned, remote controlled, electric vehicle. This work presents a combined control strategy for an unmanned hybrid electric vehicle using a Joystick. The control algorithm consists of a dynamic controller designed using the mechanical modeling of the vehicle combined with an electrical control strategy known as Field Oriented Control. The proposed technique generates the torque and speed signals using dynamic model of the vehicle and trajectories applied to the model. These signals are then utilized by the inverter controller in the vehicle's power system. The proposed algorithm generates excellent results based on trajectory following and can guarantee the safe operation of the battery pack without over discharging the battery higher than its nominal discharge rate to provide longer lifespan during harsh operations. The simulation results show that the vehicle can operate in different road conditions without violating the discharge limit of the battery pack, while following the input trajectories. The highest discharge currents are associated with the toughest road conditions and shorter terminal time during which the vehicle should reach the desired speed applied through the trajectories. The proposed control algorithm can be applied to other vehicular application by taking their specific mechanical behaviors and characteristics into account. Keywords: electric vehicle, hybrid electric vehicle, power system, battery pack, field oriented control, dynamic modelingItem Open Access Preferences and experiences of interdisciplinary communication across hospital unit types: A survey of three health professions in a Regina, Saskatchewan hospital(Faculty of Graduate Studies and Research, University of Regina, 2024-03) Morrissette, Alana Marie; Camillo, Cheryl; Zarzeczny, Amy; Mou, HaizhenIn the literature, interdisciplinary communication has been linked to high quality patient care, reduced medical error and improved patient and care provider satisfaction. Information sharing, role clarity, and shared goal setting amongst care providers are also attributed with interdisciplinary communication. The Accountable Care Unit (ACU) is an innovative, microsystem-based approach to inpatient hospital care that incorporates distinct features facilitating interdisciplinary collaboration and communication including: geographic co-location of a physicians’ patients and Structured Interdisciplinary Bedside Rounds (SIBR). During SIBR, care providers meet at the patient’s bedside and use a standardized communication protocol to provide and receive information. Traditional hospital wards, on the contrary, lack such features and intentional design. While existing research has separately explored outcomes of ACUs and aspects of interdisciplinary care, no known study has assessed healthcare providers experiences with interdisciplinary communication on ACUs versus traditional wards. The overarching purpose of this study was to understand perceived differences between interdisciplinary communication on traditional medicine wards and ACUs. The research questions that prompted this investigation included: 1. What are the experiences and perceptions of interdisciplinary communication on ACUs at the Pasqua Hospital by nurses, pharmacists and physicians who have previously worked on a traditional medicine ward? 2. How do participants perceive interdisciplinary communication on an ACU versus a traditional ward? 3.Do common themes emerge amongst research participants with similar demographics or professions? The first ACU in Canada was implemented in 2016 on unit 4A at the Pasqua Hospital in Regina, Saskatchewan to reduce lengths of stay, decrease mortality rates, and improving patient and staff satisfaction. In the following years, additional ACUs were implemented at the Pasqua Hospital and in other Saskatchewan hospitals. This research was carried out via an online survey that offered 9 demographic questions and 6 qualitative questions pertaining to interdisciplinary communication both generally, on ACUs, and on traditional wards. The survey was administered from July 13 2022 until October 31 2022 to physicians, pharmacists and nurses who volunteered to participate and who had work experience on both types of units. Fifteen respondents completed the survey and responses were analyzed using descriptive statistics and thematic analysis. Participants of this study reported an overall positive and enhanced experience with interdisciplinary communication on ACUs, generally finding it more effective than on traditional units. Reasons for this included structured communication amongst multiple care providers, regionalization of patients within the hospital with consistency in care providers, respect, and role clarity. Conversely, participants reported interdisciplinary communication to be more difficult on traditional units due to a lack of structure, absence or unavailability of team members, professional silos, hierarchies and egos. With the exception of respondents’ profession, correlations between demographic information, such as gender or age, and thematic codes proved to be inconclusive. The findings of this research could assist in guiding policies that adopt techniques or models, such as microsystem-based care models and scheduled, structured interdisciplinary rounds, which foster improved interdisciplinary communication and teamwork on acute care medicine wards. The implementation of such approaches could improve staff satisfaction, retention, and patient safety, while reducing liability risks and medical errors. Future researchers may consider investigating ACUs at other sites while acquiring more in-depth demographic information of increasingly diversified participants.Item Open Access Crushed: Climate anxiety and grief support through ceramic art(Faculty of Graduate Studies and Research, University of Regina, 2024-07) Snider, Amy Ruth; Garneau, David; Chambers, Ruth; Fay, Holly“Crushed: Climate Anxiety and Grief Support through Ceramic Art” is the support paper that accompanies my Master of Fine Arts graduating thesis exhibition, Crushed, an installation held at the Fifth Parallel Gallery from August 19-28, 2024. This paper delineates the exhibition its background, development, context, methodology, and artistic influence. It describes components of this project that extend beyond the gallery, and anticipants audience participation and reception. Crushed is an expression of my climate change anxiety and grief. With a floor scattered with super fragile ceramic vessels and a text about my fear and sadness on the walls, Crushed shows participants that such feelings are justified and shared and offers resources and support. At the end of the wall text is information about a support group I founded, and a discussion circle led by a psychologist that will take place in the gallery at the end of the show.Item Open Access Intersexual roost site selection by the little brown Myotis in Cypress Hills, Saskatchewan(Faculty of Graduate Studies and Research, University of Regina, 2024-07) Blanken, Emma Catherine; Brigham, Mark; Vanderwel, Mark; Somers, ChrisRoost structures provide habitats for bats to engage in critical life processes. Identifying, characterizing, and conserving these structures is crucial for individual fitness and survival to mitigate population loss, especially for species such as the little brown Myotis facing threats such as pathogen spread from White-Nose Syndrome. During summer, little brown Myotis rely on roosts to maintain populations through successful reproduction and winter preparation, including rapid development of young and fat accumulation for the winter for all individuals. Summer daytime roosts are particularly critical for these processes to occur effectively. My research aimed to characterize the natural roost selection of nonreproductive female and male little brown Myotis during the summer in Cypress Hills, Saskatchewan (SK). I determined if roost choice differed from random available roosts and explored intersexual variation in roost use between nonreproductive females and males. Using radio-telemetry, I tracked nonreproductive female and male bats to their daytime roosts in Cypress Hills, Saskatchewan, over the summers of 2022 and 2023. Identifying occupied roost structures for males and females, and comparing them against data for random available roosts may provide valuable insight to roost characteristics such as tree structure and temperature, which are essential for forest-dwelling bats. I found individuals of both sexes roosting in anthropogenic structures, though nonreproductive females were observed roosting in a known maternity colony consisting of several anthropogenic structures more than males. In terms of natural roosts, my results suggest that little brown Myotis are roosting mostly in white spruce in Cypress Hills, SK though the characteristics of these trees may differ between male and nonreproductive females. Assessing the roost selection of little brown Myotis and how intersexual variation affects such selection can guide future conservation efforts by protecting and promoting these sites for future populations.Item Open Access Suspending echoes(Faculty of Graduate Studies and Research, University of Regina, 2024-08) Malakootikhah, Amin; Marsh, Charity; french, Lindsey; Holmes, ShannonThis critical engagement paper outlines the conceptual and technical details and theoretical support for my Master of Fine Arts exhibition project titled Suspending Echoes, presented at the Fifth Parallel Gallery from August 1 to August 15, 2024. Suspending Echoes is an interactive and immersive installation through which I attempt to represent my perception of self as a fluid entity, continuously shaped and influenced by currents, created by interactions with my surrounding environment and people. The installation creates a dynamic environment where the audience's presence and movements contribute to their overall experience. I aim to evoke empathy and self-reflection through this artwork. Through the creation of an interactive and dynamic immersive experience focused on sensory and bodily effects, I invite the audience to consider the feeling of suspension, reflecting on their own experiences of being influenced by their surroundings, which can prompt reflection on social relationships and cultural concerns. Additionally, in this paper, I review how I have developed my approach to interact with the audience, design the interaction system, create immersive and sensory-evoking spaces, provide metaphoric, universal, evocative elements and cues, and make room for the audience to create their own unique experiences and interpretations of the work.Item Open Access Do microaggressions influence cognitive performance of racial minorities?(Faculty of Graduate Studies and Research, University of Regina, 2024-08) Adedun, Ayomide Danielle; Sangster, Sarah; Klest, Bridget; Sharpe, Donald; Tottenham, Laurie SykesWithin the university setting, students from marginalized groups may be more likely to experience microaggressions and associated harmful effects than their White counterparts. This study investigated whether experiencing a racial microaggression hinders performance on a cognitive task among racialized students. Undergraduate students (n = 256) completed a demographic survey and then were randomly assigned to a racial microaggression or control condition in which they watched a video explaining a cognitive task (i.e., mental rotation), completed a mental rotation task, and completed ethnic identification, discomfort, and perceived discrimination measures. Racialized students had higher ethnic identification levels than White students. Further, students in the racial microaggression condition had increased discomfort and were more likely to perceive discrimination. Neither mental rotation task reaction time nor accuracy was affected by experiencing a microaggression. This study demonstrates that microaggressions within the classroom are perceived by students and have the potential to impact student well-being.Item Open Access Development of a pellet extruder with co-axial nozzle for 3D printing using inflatable extrudates(Faculty of Graduate Studies and Research, University of Regina, 2024-08) Habib, Md Ahsanul; Khondoker, Mohammad; Muthu, SD Jacob; Peng, WeiAdditive manufacturing (AM) has emerged as one of the core components of the fourth industrial revolution, Industry 4.0. Among others, the extrusion AM (EAM) of thermoplastic materials has been named as the most widely adopted technology. Fused filament fabrication (FFF) relies on the commercial availability of expensive filaments; hence pellet extruder-based EAM techniques are desired. Large-format EAM systems would benefit from the ability to print lightweight objects with less materials and lower power consumption which can be possible by using hollow extrudates rather than solid extrudates to print objects. In this work, we designed a custom extruder head and developed an EAM system that allows the extrusion of inflatable hollow extrudates of a relatively wide material choice. By incorporating a co-axial nozzle-needle system, a thermoplastic shell was extruded while the hollow core was generated by using pressurized Nitrogen gas. The ability to print using hollow extrudates with controllable inflation allows printing objects with gradient part density with different degrees of mechanical properties. In this article, the effect of different process parameters namely, extrusion temperature, extrusion speed, and gas pressure were studied using poly-lactic acid (PLA) pellets. Initially, a set of preliminary tests was conducted to identify the maximum and minimum ranges of these parameters that result in consistent hollow extrudates. Later, the parameters were varied to understand how they affect the core diameter and shell thickness of the hollow extrudates. These findings were supported by analyses of microscopic images taken under an optical microscope. In the next phase of our experiment, we printed an inflated cylindrical part using the process parameters derived from the initial set of experiments. We carefully compared the results with the data obtained earlier to ensure accuracy and consistency. Finally, we successfully printed an object with varying densities in different sections. Keywords: Additive Manufacturing; Extrusion Additive Manufacturing; Hollow Extrudates; Pellet Extrusion; Fused Filament Fabrication.Item Open Access Psychometric evaluation of the COVID stress scales in older adults and the impact of ageism and pain on COVID-related stress(Faculty of Graduate Studies and Research, University of Regina, 2024-08) Arsenault, Kylie Ann; Hadjistavropoulos, Thomas; Asmundson, Gordon; Yamamoto, SusanThe literature has documented strong manifestations of ageism stemming from the COVID-19 pandemic (e.g., social media posts suggesting that older adults’ deaths from COVID-19 are less tragic than younger individuals, beliefs that public health restrictions should only target older persons). Additionally, pain is highly prevalent among older adults and often limits mobility, which can exacerbate stress and pain severity during pandemics in which public health measures promote physical distancing or impose restrictions that reduce access to pain treatment. Prior to the COVID-19 pandemic, both ageism and pain have been identified as predictors of adverse health outcomes in older adults (e.g., stress, anxiety, functional impairment). However, the influence of ageism and pain on stress specifically within the context of COVID-19 had not been investigated among older adults. The COVID Stress Scales (CSS) is a widely used measure designed to measure multidimensional stress reactions related to the COVID-19 pandemic (i.e., danger and contamination fears; socioeconomic consequences; xenophobia; compulsive checking and reassurance seeking; traumatic stress symptoms). Though the CSS has been extensively validated across cultures, its psychometric properties had not been confirmed in an older adult sample. Moreover, item response theory (IRT) analysis was needed to examine its properties at the item level with older adults. This study was aimed at addressing these gaps by validating the CSS in older adults and examining how ageism and pain impact COVID-related stress responses measured by the CSS in this population. A population-representative sample of 486 Canadian and American older adults aged ≥65 years completed an online Qualtrics survey in January 2024. Participants completed measures of COVID-related stress, pain, ageism, and social desirability. As expected, results indicate that the CSS demonstrates robust psychometric properties and has a defensible five- and six-factor model structure, though its six-factor model provides the most optimal measurement of COVID-related stress in the older adult population. All items on the CSS were also found to adequately differentiate between older adults with lower and higher levels of COVID-related stress, though some items were identified as having lower overall discriminatory efficacy. Furthermore, as expected, the extent to which older adults reported experiencing ageism was positively associated with both the combined domains of COVID-related stress and each individual domain of the CSS. Pain was also associated with the combined domains of COVID-related stress and several individual CSS domains (i.e., fear of danger; fear of socioeconomic consequences; traumatic stress symptoms; compulsive checking and reassurance seeking). Findings from this investigation highlight factors that are related to increased pandemic-related stress in older adults. This evidence can guide future treatment strategies for healthcare providers working with the older adult population in response to future waves of COVID- 19, or during other pandemics or infectious outbreaks. Additionally, this investigation confirms that the CSS is a highly reliable and valid measure which can be used by clinicians or researchers in future studies to assess pandemic-related stress experienced by older adults within the context of COVID-19 or future pandemics and determine appropriate interventions. Keywords: ageism, COVID Stress Scales, older adults, pain, pandemic-related stressItem Open Access L'efficacité du programme de l'année à l'étranger pour les étudiants de français au Ghana: perspectives des professeurs et des étudiants(Faculty of Graduate Studies and Research, University of Regina, 2024-08) Anaglate, Joanita Aku Eyako; Akinpelu, Michael; Poplyansky, MichaelThe growing interest in learning French in Ghana has become markedly noticeable. This increase can be attributed to a strategic emphasis placed on French education by the Ghanaian government, driven by the country's close proximity to francophone neighbors like Ivory Coast, Burkina Faso, and Togo. Additionally, in April 2019, the Ghanaian government announced plans to adopt French as one of the nation's official languages, further bolstering this initiative. This study investigates the effectiveness of a Year-Abroad program in enhancing French language proficiency among students at Ghanaian universities. With a focus on oral competence, the research assesses linguistic improvements by comparing students' proficiency levels before and after their participation, utilizing the Common European Framework of Reference for Languages (CEFR). The interest of this research lies in providing a comprehensive evaluation of the program's impact on students' academic and linguistic capabilities. Additionally, it collects evaluations from French professors to gauge the program’s effectiveness and explores the necessity of ongoing program evaluation to ensure continuous improvement. The findings aim to guide stakeholders, including educational institutions and the Ghana Scholarship Secretariat, in refining the program to maximize benefits for students. This study not only influences educational policy and planning within Ghana but also offers insights for other English-speaking West African countries interested in similar language learning strategies. The ultimate goal is to determine the tangible benefits of immersive language experiences and to substantiate the allocation of resources towards such educational initiatives. Keywords: Year Abroad, French language proficiency, Language immersion, Linguistic skills, Common European Framework of Reference for Languages (CEFR), French as a Foreign language (FLE).Item Open Access The role of modular construction and BIM technologies in sustainable construction and demolition waste management(Faculty of Graduate Studies and Research, University of Regina, 2024-08) Naghibalsadati, Farzin; Ng, Kelvin Tsun Wai; Wu, PengConstruction and demolition activities significantly contribute to global waste generation, necessitating sustainable measures. This thesis explores advanced C&DW management through Building Information Modeling (BIM) and modular construction techniques. In the initial phase of the study, a comprehensive text-mining analysis of 493 scholarly publications (2009-2024) reveals key themes and temporal trends. The cooccurrence analysis identified three distinct clusters centered on C&DW management, highlighting strong correlations between "sustainability" (Links=41), "BIM" (Links=46), and "C&DW" (Links=46). Thematic development and evolution analysis indicated that during the third period (2018-2021), transversal themes included Material Passport (OCC=92) and Prefabrication (OCC=482). In the fourth period (2022-2024), transversal themes encompassed Digital Twin (OCC=44), Waste Minimization approaches in BIM (OCC=64), and Decision-Making Systems (OCC=64). Strategic diagrams and Temporal evolution mapping generated by SciMAT software illustrate the progressive integration of BIM tools like digital twins, Material Passport, Prefabrication, and Decision-Making System, offering avenues to optimize waste reduction. The subsequent part of the study explores modular construction techniques for their potential to mitigate material waste and enhance sustainability in building practices. Significant research interest since 2015, coinciding with the UN Sustainable Development Goals (SDGs), is observed. Keyword trends have sustained interest in recycling since 2014. Cluster and network analysis highlight "Recycled Aggregate Concrete (RAC)" as a high-impact theme (confidence 100%).The importance of the mechanical properties of RAC in modular construction is also emphasized.Item Open Access Investigative studies on the stability of an amine blend in the presence of exhaust gas dust (metal oxide) impurities during an amine-based CO2 capture process(Faculty of Graduate Studies and Research, University of Regina, 2024-08) Boakye, Thomas; Idem, Raphael; Supap, Teeradet; Ibrahim, HussameldinThis research work investigates the degradation kinetics of MEA/DMAE bi-blend solvent, with a focus on the influence of temperature, oxygen concentration, and type and amount of exhaust gas metal oxides. Utilizing a combination of experimental approaches and kinetic modeling, this study was used to provide a comprehensive analysis of the factors that affect MEA/DMAE stability and degradation rates. This research commenced first, by determining the solubility of various dominant iron and steel flue gas metal oxides, namely, Fe2O3, ZnO, MnO, and Al2O3. The oxides were dissolved in a 200 ml, 5M, and 0.30 mol CO2/mol bi-blend of MEA/DMAE solvent. In decreasing order, the solubility results for ZnO, Fe2O3, MnO, and Al2O3 were 387.51 ppm, 15.96 ppm, 4.57 ppm, and 3.43 ppm, respectively. By flowing oxygen at different concentrations (balance nitrogen) through a 200 ml volume filtrate of the generated metal oxide dissolved amine solvent in a three-necked flask exposed to different absorber temperatures, a continuous 21-day lab-scale degradation experiment was carried out. Fe2O3 had the greatest influence on the degradation of a CO2-loaded bi-blend of MEA/DMAE among the metal oxides taken into consideration, followed by ZnO all based on amine degradation results in mmol/hr, accumulated amount of ammonia emissions in ppmV, and ammonia emissions rate in ppmV/hr. Based solely on which one had the most degrading effect, Fe2O3 in the concentrations of 15.96 ppm, 11.97 ppm, and 7.98 ppm was selected and used against varying temperatures (in the range of 40 oC, 50 oC, and 60 oC) and oxygen concentrations (ranging from 6%, 12%, and 18%) to explore their effects on degradation rates and ammonia emission rates. A kinetic model was developed for the DMAE degradation rate and MEA degradation rate with activation energies of 50,495.13 J/mol, and 60,310.9 J/mol respectively. The order of reactions obtained from the kinetic analysis was 1.22 and 0.98 for DMAE and MEA respectively. The results showed that DMAE degraded at a faster rate than MEA. The studies also showed an increasing trend in the rate of MEA/DMAE degradation and the rate of ammonia emissions with increasing oxygen concentration and operating temperature. A high activation energy for MEA implies that more energy (temperature) was needed to degrade MEA relative to DMAE, which had a lower activation energy. A lower order of reaction for oxygen for MEA, also implies that the impact of oxygen on MEA degradation is less than its impact on DMAE degradation. Fe2O3 therefore has a higher catalytic effect on MEA/DMAE degradation implying that upon contact with the amine solvent, the amine has a high tendency to degrade at a faster rate, causing an increase in solvent losses and an increase in the cost of solvent replacement. Further implications include corrosion, clogging, and the degraded amine's fouling of columns and piping.Item Open Access Prevalence and predictors of alcohol use disorder among Canadian Armed Forces members and veterans with military sexual trauma(Faculty of Graduate Studies and Research, University of Regina, 2024-08) Kinsman, Laura Marie; Asmundson, Gordon J.G.; Yamamoto, SusanMilitary sexual trauma (MST) is a pervasive issue that is associated with adverse psychological and physical health sequelae (e.g., chronic health conditions, mental health disorders, suicidal ideation). Alcohol use disorder (AUD) is positively associated with MST and may exacerbate physical and mental health conditions. An elevated lifetime prevalence of MST was recently reported among Canadian Armed Forces (CAF) Members and Veterans. Still, research examining the relationship between MST and AUD within a Canadian context is lacking. Risk factors for AUD among CAF Members and Veterans with MST have also yet to be identified. The current thesis used the 2018 CAF Members and Veterans Mental Health Survey (n = 2,941) to assess the prevalence and predictors of AUD since 2002 among participants with lifetime MST, non-military sexual trauma (NMST), and no sexual trauma. Findings from cross tabulations revealed greater prevalence estimates of AUD among participants with any sexual trauma (MST = 21.6%, NMST = 29.2%) compared to those without sexual trauma (14.68%). Disproportionately greater prevalence estimates of AUD were found among males relative to females across all sexual trauma groups. Results of logistic regression analyses indicated that individuals with MST and NMST had significantly greater odds of AUD than those without sexual trauma. Younger age, male sex, and greater moral injury significantly predicted increased odds of AUD among all three groups. Few unique predictors of AUD were observed across the sexual trauma groups. Deployment history predicted AUD among those with MST and no sexual trauma. Lower rank predicted AUD among those with NMST and no sexual trauma. Military environment, lifetime other mental health disorders, and childhood maltreatment history were associated with significantly increased odds of AUD only among participants without sexual trauma. The current thesis determined that AUD represents a substantial issue among CAF Members and Veterans, particularly among those with military and civilian sexual trauma. This investigation contributes to the advancement of the current understanding of AUD among CAF Members and Veterans by identifying prevalence estimates of AUD and elucidating factors that enhance vulnerability to AUD among those with and without sexual trauma. These findings highlight the importance of supporting initiatives designed to prevent civilian and military sexual trauma. Additionally, the current findings suggest that screening for AUD among individuals with MST and NMST may be especially important. Keywords: military sexual trauma, alcohol use disorder, Canadian Armed Forces, VeteransItem Open Access Victim blaming in the courtroom: The influence of lawyer gender and style on juror decision-making(Faculty of Graduate Studies and Research, University of Regina, 2024-08) MacDonald, Katie Lynne; Yamamoto, Susan; Tottenham, Laurie Sykes; Sangster, SarahDespite the present Canadian laws meant to protect victims of sexual assault during the trial process, it is common for defence lawyers to employ stereotypes against the victim (a process known as “whacking”; Tanovich, 2015). It is unclear whether the gender of the defence lawyer is a determining factor in the influence of such stereotypes. Only a limited number of studies have examined the effects of lawyer gender, which yielded conflicting findings (Levi et al., 2022; Villemur & Hyde, 1983). Moreover, the previous studies did not explore whether the lawyers’ cross-examination style or the juror’s level of sexism factor into their verdict choice. This thesis extended previous literature by examining the potential impact of defence lawyer gender, cross-examination style, and jurors’ benevolent sexist attitudes on the outcomes of sexual assault trials and lawyer perceptions. A community sample (N = 212) of jury-eligible Canadians were recruited to read a mock sexual assault trial transcript. The defence lawyer’s gender (woman/man) and cross-examination content (whacking/no whacking) were manipulated. Following the trial transcript, participants delivered an individual verdict and completed measures of ambivalent sexism, rape myth acceptance, and perceived lawyer capability. Three-way interactions were not observed between lawyer gender, cross-examination style, and juror sexism on the verdict outcome or lawyer capability. However, benevolent sexism did directly predict perceptions of the defence lawyer, and the whacking manipulation indirectly affected the verdict outcome via mock jurors’ perceptions of the victim’s culpability. Of most interest, implementing the whacking tactic increased the defence lawyer’s chance at obtaining a not-guilty verdict if the lawyer and the juror were men. Keywords: Juror-decision making, lawyer gender, benevolent sexism, rape myth acceptance, sexual assault trials, victim blamingItem Open Access Advanced CNN architecture integrating machine learning algorithms for precise Alzheimer's disease classification(Faculty of Graduate Studies and Research, University of Regina, 2024-08) Mollazadeh, Shima; Torabi, Farshid; Tontiwachwuthikul, Paitoon (P.T.); Idem, RaphaelAlzheimer's disease (AD) is a degenerative neurological disorder that affects millions of individuals worldwide and is very difficult to detect and treat in its early stages. This thesis presents a novel architecture for a convolutional neural network (CNN) designed exclusively to classify Alzheimer's disease using functional magnetic resonance imaging (fMRI) data. This work improves the accuracy and reliability of early Alzheimer's identification by using state-of-the-art deep learning techniques to the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset. The basis of this research is the ADNI dataset, a vast collection of brain imaging and associated data from people with different degrees of cognitive impairment. The primary objectives are to classify Alzheimer's disease into distinct categories using cognitively normal (CN), early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI), and Alzheimer's disease (AD) using the recently developed CNN architecture. This study also uses transfer learning techniques to compare the performance of the new CNN with well-known deep learning models like ResNet50 and VGG16, as well as with more conventional machine learning algorithms like XG Boost, k-nearest neighbor (KNN), and Random Forest. The innovative CNN architecture is meticulously designed to maximize classification accuracy. The preprocessing steps involve resizing fMRI images to 109x91 pixels and labeling them accordingly. The network incorporates convolution layers with 3x3 kernels, ReLU activation functions, and 2x2 pooling layers, transforming the images into feature vectors that are subsequently classified. Compared to previous tested models, the innovative CNN architecture performed better, achieving an impressive 99.51% classification accuracy. In terms of comparison analysis, the accuracy of the VGG16 model was 98.24%, whereas the accuracy of the ResNet50 model was 96.05%. The XG Boost classifier, combined with VGG16 for feature extraction, reached an accuracy of 96.93%. The KNN algorithm, also paired with VGG16, exhibited outstanding performance with an accuracy of 98.68%, making it the most effective among the traditional machine learning methods tested. With VGG16 included, the Random Forest classifier produced an accuracy of 94.70%. The outcomes demonstrate how well the suggested CNN architecture performs in comparison to current deep learning and machine learning models in precisely classifying Alzheimer's disease stages. This study demonstrates how sophisticated CNN designs and transfer learning can be used to enhance Alzheimer's disease early detection and diagnosis. The findings suggest that further exploration of alternative deep learning networks, such as convolutional auto encoders, Alex Net, and Google Net, as well as ensemble methods, could enhance model generalization and minimize overfitting. In conclusion, this thesis presents a significant advancement in Alzheimer’s disease classification using fMRI data, providing a robust framework for future research and development in neuroimaging and deep learning applications. The superior performance of the novel CNN architecture demonstrates its potential as a valuable tool for early diagnosis, which is crucial for managing and potentially mitigating the way Alzheimer's disease advances.Item Open Access Mathematical modeling and simulation of the performance of potassium glycinate in CO2 absorption in a packed-bed absorption column(Faculty of Graduate Studies and Research, University of Regina, 2024-09) Domfeh, Adjei; Idem, Raphael; Torabi, Farshid; Ibrahim, Hussameldin; Supap, TeeradetThe aim of this research undertaking was to develop a mathematical model representation for the capture of CO2 using potassium glycinate as the absorption solvent. To this end, the study was subdivided into three major parts each designed to generate the requisite data for the subsequent stage. The three major parts of the study included the development of industrial process simulation to ascertain the emission data and characteristics of flue gas emanating from different industrial processes. The main processes under study were, Power Generation with particular emphasis on the Combined Cycle Gas Turbine setup, Natural Gas Pre-treatment, where the simulations were developed for gas dehydration, chilling and Natural Gas Liquid (NGL) recovery, and the Acid Gas Removal (AGR) Modules, Cement Manufacturing with emphasis on the Pyroprocessing stage and finally Iron and Steel Production, where simulations were built for such production stages as the Raw material Sintering, Pelletization, Coke Production, Pig Iron Production, and the Basic Oxygen Furnace setup. The emission data from each of these process industries were collected and used for the sizing of an absorption tower which then became the basis for the hydrodynamic solution. The Absorber model developed in Aspen Hysys based on the flowrates and CO2 partial pressures in each flue gas stream served as the template to generating a Computer Aided Design (CAD) version of the column as a flow channel facilitating the process of resolving the hydrodynamic solution. In the second section of the study, the hydrodynamic solution of the absorption model was solved based on the physicochemical properties of potassium glycinate particularly density and viscosity at 6M and 60 ºC after a thorough assessment of the flow behaviour dynamics of the solvent was performed and the results was contrasted with MEA which is the bench mark solvent in CO2 post combustion capture. The final phase of the study investigated the mass transfer with reaction aspect of the interaction of CO2 and potassium glycinate at varying CO2 concentrations to understand its impact on capture processes. The solution; based on a stated rate expression; −𝑟𝐶𝑂2 = 7.5 × 10−1 𝑒(−6.7×102 𝑇)𝐶𝑠 0.11 𝐶 𝐶𝑂2 1.14 reveal that the reaction rate of CO2 increases from 0.0022 kg/m³·s at 5% CO2 to 0.0027 kg/m³·s at 10% CO2, stabilizes at 0.0026 kg/m³·s at 15% CO2, and remains constant at 0.0027 kg/m³·s from 20% CO2 onwards. In contrast, potassium glycinate's reaction rate increases from 0.0058 kg/m³·s at 5% CO2 to 0.0068 kg/m³·s at 10% CO2, remains steady at 0.0068 kg/m³·s up to 20% CO2, and slightly rises to 0.0069 kg/m³·s at 30% and 40% CO2. The initial rise in CO2 reaction rates suggests enhanced efficiency with increasing CO2 concentration, while the plateau indicates a saturation point. Potassium glycinate shows improved absorption capacity and reaction efficiency up to a steady state, with minimal gains at higher concentrations. These trends imply that potassium glycinate remains effective across a broad range of CO2 concentrations, crucial for optimizing CO2 capture systems.Item Open Access Regina Lawn Bowling Club Open-source Accessibility Project(Faculty of Graduate Studies and Research, University of Regina, 2024-09) Watson, Brandon Scott Cooper; Marsh, Charity; Maciag, Timothy; french, LindseyThis critical engagement paper supports and documents an interdisciplinary project, integrating maker culture, people-centered design, and community-based research to address key issues identified by the members of the Regina Lawn Bowling Club (RLBC) community, including concerns around the ability of the aging members to continue participating in the sport, potential for addressing social isolation, and other concerns related to health and wellness. The questions guiding my creative research were: (1) How could integrating maker culture, people-centered design, and community-based research address identified concerns by the RLBC such as isolation, engagement, and accessibility to continue play and social involvement?; and (2) What kinds of innovative technologies could we produce and build together to create sustainable social connections for the aging community at the Regina Lawn Bowling Club? With the support of the Regina Lawn Bowling Club community, (including consultation, collaboration, and user testing), I designed two devices: an inclusively designed music playing device called the User-Friendly Jukebox (UFJ) and an inclusively designed, electronic-based lawn bowling bowl distance measuring device called the Easy-Shot. This report will discuss the projects and the results of evaluation as a community-based project.Item Open Access Beta-delayed proton emission of magnesium-20 and the RCMP silicon detector array(Faculty of Graduate Studies and Research, University of Regina, 2024-09) Liu, Jizhong; Grinyer, Gwen; Berg, Marcella; Mobed, NaderIn 2011, experiment e09024 was performed in National Superconducting Cyclotron Laboratory(NSCl) located at Michigan State University from Michigan state. The goal was to investigate delayed particle emission for isotopes near proton drip line. The main secondary beam was ²²Si while other exotic beam such as ²⁰Mg,²²Al,²³Si was also produced. The delayed particle emission from ²⁰Mg is of particular interest in this thesis and has been studied in details. In 2018, Dr.Gwen Grinyer's group at University of Regina started constructing a Silicon Detector Array named Regina Cube for Multiple Particle(RCMP) used for studying delayed particles at proton drop line with high resolution and high solid angle coverage. The detector is designed to be placed inside GRIFFIN chamber located at TRIUMF cyclotron facility. GRIFFIN chamber designed by GRIFFIN collaboration consists of 16 High Purity Germanium detectors with 8 fast timing LaBr3 used for studying gamma rays. It is a high effociency detector chamber with BGO shielding for Compton suppression. The combination of the two could provide more detailed study of nuclear structure for isotopes near proton drip line. The detector has been deployed in 2024 and a new experiment on ²⁰Mg S2232 is being scheduled during 2024 summer. In this thesis, I will be presenting analysis of ²⁰Mg from experiment e09024 with development and testing of RCMP detector array and experiment S2232. Key words: Proton Drip line,Beta-delayed, NSCL, TRIUMF, RCMP, GRIFFIN