Faculty of Graduate Studies and Research

Permanent URI for this communityhttps://hdl.handle.net/10294/32

The Faculty of Graduate Studies and Research (FGSR) embraces numerous departments and institutes, and offers an impressive range of programs. Although its primary focus is to provide students with mastery of their subject, it prides itself on the accessibility of the faculty and quality of their research and scholarship.

FGSR emphasizes the partnership of teaching and research that provides the essence of any university: the dissemination and expansion of knowledge. Through its programs, research centres, and international activities, FGSR attempts to respond to the ever changing needs of our global community.

Doctoral degrees are regularly offered in Biology, Bio-Chemistry, Chemistry, Computer Science, Education, Engineering, Mathematics, Physics, Psychology, and Statistics.

Master's degrees are offered through the faculties of Arts, Business Administration, Education, Engineering, Fine Arts, Graduate School of Public Policy, Kinesiology and Health Studies, Science, and Social Work.

Research is vital to the University and demonstrates the broad spectrum of our involvement. It can be pure research or applied research, long term in scope or short term. University resources are enhanced in this effort by collaboration with the public and colleagues around the world enable our researchers to examine problems in diverse physical, social, and cultural settings and provide opportunities for scholarly activity at several other Canadian and international facilities. The Office of Research Services is responsible for the administration of research at the University of Regina.

FGSR is a member of the Canadian Association for Graduate Studies (CAGS) and participates in a number of graduate agreements with other Canadian universities.

For more information on the Faculty of Graduate Studies and Research, visit the web site at: www.uregina.ca/gradstudies/

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Open Access
A mixed methods study on barriers and facilitators to exercise for suicidal ideation management
(Faculty of Graduate Studies and Research, University of Regina, 2024-10) Vig, Kelsey Danielle; Asmundson, Gordon; Hadjistavropoulos, Heather; Hadjistavropoulos, Thomas; Totosy, Julia; Gibb, Brandon E.
Suicide is a leading cause of premature death. Innovative and effective interventions are needed to prevent suicide deaths. Randomized controlled trials (RCTs) have demonstrated that a variety of structured exercise programs (e.g., aerobic exercise, resistance training exercise) improve mental health, including reducing anxiety and depressive symptoms. Moreover, failure to meet established guidelines for physical activity is associated with increased odds of experiencing suicidal behaviours. Exercise may, therefore, be one intervention option to reduce the suicidal behaviours (i.e., suicidal ideation [SI] and plans for suicide) that often precede suicide. In order to benefit from the effects of exercise, individuals with suicidal ideation must perceive exercise as an accessible, acceptable, and effective treatment option, otherwise they are unlikely to initiate and sustain an exercise program. This mixed-methods dissertation includes two studies that explored how individuals with SI perceive and experience exercise, with an emphasis on identifying facilitators and barriers to exercise. In Study 1, grounded theory methods were used to analyze data from semi-structured interviews with 17 adult Canadian participants with past-month SI. The overall theory derived from Study 1 suggests that exercise for individuals with SI is complex and should be tailored to each individual. This theory is made up of a core category of individualization, as well as four key concepts that relate to three major categories. The four key concepts of the theory are that facilitators and barriers to exercise (a) have individualized weights/impacts on exercise decisions, (b) are cumulative, interactive, and opposing forces, (c) are dynamic, and (d) exist on a spectrum from internal to external. The three major categories included in the study theory are (a) the cognitive-behavioural cycle, (b) priorities, values, and identity, and (c) interpersonal factors. In Study 2, 261 Canadian adult participants with past-month SI completed an online survey. The survey included measures of suicidal behaviour, facilitators and barriers to exercise (open-ended and closed-ended questions), past-week physical activity, and demographic and health questions. Due to the exploratory nature of the study, quantitative analyses were restricted to descriptive statistics. The qualitative and quantitative results of Study 2 supported and added to the theory developed in Study 1, including offering additional evidence of the core category, the four key concepts, and the three major categories. Most participants thought exercise can reduce SI. Improved health, both mental and physical, was a commonly reported motivator to exercise, and poor mental health was also a commonly reported barrier to exercise. Overall, the results of both studies demonstrated the importance of individualization when it comes to exercise for individuals with SI. Exercise may or may not be an accessible, acceptable, and/or effective intervention for any given individual with SI. The results may be used by clinicians, researchers, policy makers, and advocacy groups considering whether exercise might be an intervention option for individuals with SI. The results may assist future researchers who endeavor to develop exercise-based interventions for individuals with SI by providing a theoretical framework to guide intervention development and study planning (e.g., by highlighting the need to anticipate and address individual and fluctuating facilitators and barriers). Keywords: suicidal ideation, exercise, physical activity, facilitators and barriers to exercise, exercise adherence, grounded theory
Open Access
A multi-proxy environmental and limnologic paleo-reconstruction of two lakes in Southern Saskatchewan recording the past 6,700 cal. years BP based on ostracods
(Faculty of Graduate Studies and Research, University of Regina, 2025-03) Velandia Bahamon, Maria Juliana; Velez, Maria; Robbins, Leslie; McBeth, Joyce
Paleoenvironmental and paleolimnological reconstructions are of great importance to understand future responses of the environment to climate change and environmental stress. Two lake archives, Deep Lake and St. Denis – Pond 1, are used to understand past environmental and limnological conditions in the northernmost part of the Great Plains of North America. Climatic conditions are inferred from the lake sediments and the ostracod assemblage for the Mid- to Late-Holocene (6,700 to 120 cal. yr BP). Mainly, dry conditions with shorter wetter conditions prevailed during the Mid-Holocene as suggested by the presence of a depositional hiatus from 6,302 to 4,366 cal. yr BP and evidences for wetter periods inferred from the bulk-sediment chemistry (Al, Si, K, Fe, K/Ti, Fe/Ti and Mn/Ti), the stable isotopes (ẟ18O, ẟ13C), and the trace element composition of the ostracod valves (Mg/Ca, U/Ca, Fe/Ca). The Late-Holocene displays overall centennial cyclicity fluctuations between wet and dry periods but mostly dry during the last 2,000 years. Both Deep Lake and St. Denis – Pond 1 records seem to respond to regional changes although the period between 2,714 and 1,691 cal. yr BP appear to be responding to local rather than regional forcings due to the moist signature that presents like some but not all the lakes in the northern Great Plains. Likewise, the Medieval Warm Period is recorded by the record of St. Denis – Pond 1, in which dry conditions were inferred.
Open Access
A novel beam management strategy using UE trajectory mapping
(Faculty of Graduate Studies and Research, University of Regina, 2024-12) Chowdhury, MD Thouhidul Islam; Paranjape, Raman; Wang, Zhanle (Gerald)
This research presents a novel beam management strategy aimed at optimizing performance in multi-user mobile communication systems, specifically within the framework of 5G mmWave networks. As the demand for reliable and high-speed data transmission increases, traditional beamforming techniques face challenges such as high computational load and inefficiencies in indoor environments. The proposed method leverages user equipment (UE) trajectory information by segmenting user trajectories into equal-length segments, focusing the beam on the centre of each segment to ensure stable and consistent signal coverage. The methodology integrates angular weighting, and dynamic power control to enhance beamforming efficiency. The angular weighting function prioritizes signals aligned closely with the beam direction, further enhancing signal strength while reducing unwanted energy dispersion. Additionally, dynamic power control is employed to adjust transmit power according to the user’s position relative to the segment center, maintaining robust Received Signal Strength (RSS) without unnecessary energy expenditure. Simulation results indicate that the proposed approach significantly reduces beam switching frequency and computational load compared to conventional methods, while maintaining stable RSS and Signal-to-Interference-plus-Noise Ratio (SINR) across multiple users. This study demonstrates the potential of combining trajectory mapping, subarray-based beamforming, and nulling techniques for effective beam management in dynamic indoor environments. Overall, the findings highlight the scalability and efficiency of the proposed strategy in enhancing wireless communication systems, paving the way for future advancements in next generation 5G networks. Key words: Beamforming; Interference Management; Dynamic Indoor Environment; Predefined Segments; Subarray; Nulling Algorithm.
Open Access
A security risk assessment framework for IoT systems
(Faculty of Graduate Studies and Research, University of Regina, 2024-12) Waqdan, Mofareh Abdullah S; Mouhoub, Malek; Louafi, Habib; Shahriar, Nashid; Hepting, Daryl; Uddin, Md. Sami; Al-Anbagi, Irfan; Amamra, Abdelfattah
The emergence and growth of the Internet of Things (IoT) have changed how we live and interact with technology. The seamless integration of connected devices, from household to industrial equipment, has brought about a new era of interconnectedness. However, this rapid expansion of the IoT also introduces new security concerns that need to be assessed. Assessing the security risks associated with deploying and using this technology is crucial. Consequently, organizations need a risk assessment framework that helps identify, evaluate, and manage the risks of IoT, including data privacy and confidentiality, system integrity, availability, and performance. The stateof- the-art has been given significant attention to security risk assessment in traditional cybersecurity with powerful computer systems, but the challenges of deploying IoT devices and their associated vulnerabilities have been overlooked. In this thesis, we first present a novel IoT security risk assessment framework for the healthcare environment, in which we have improved upon existing methodologies. The proposed framework dynamically calculates the risk score for different device profiles, considering their population and other parameters, such as network protocols, device heterogeneity, device security updates, device physical security status, device history status, layer history status, and device criticality. Second, we present a customizable framework for assessing the security risk of deploying and utilizing IoT devices in various environments. We dynamically calculate risk scores for different devices, considering their importance to the system and their vulnerabilities, among other parameters. The customizable framework considers the important parameters of the devices, their vulnerabilities, and how they impact the overall risk assessment. The importance of these devices and the severity of vulnerabilities are incorporated in the framework using the well-known Multi-Attribute Decision Making (MADM) methods, namely, Simple Additive Weighting (SAW) and Weighting Product (WP). Finally, the risk is assessed on a setup comprised of IoT devices widely deployed in healthcare systems, such as emergency rooms.
Open Access
Absorption capacity of carbon dioxide in aqueous solution of 1,2-bis(3-aminopropylamino) ethane and Dytek EP diamine: Experimental measurements and simulation with the E-NRTL model
(Faculty of Graduate Studies and Research, University of Regina, 2024-12) Fallah, Abbas; Henni, Amr; Peng, Wei; Khan, Sharfuddin
The increasing threat of climate change has elevated the importance of carbon dioxide (CO2) capture technologies. This thesis explores the solubility of CO2 on aqueous solution of two novel amines 1,2-Bis(3-AminoPropylamino) Ethane and Dytek EP diamine at two different temperatures of 313.15 K and 333.15 K, and two different concentrations of 10 wt% and 30 wt%. These amines were selected for their potential to enhance CO2 absorption efficiency and reduce energy consumption in carbon capture and storage (CCS) processes to provide valuable data for developing more efficient CO2 capture systems. Utilizing the Electrolyte Non-Random Two-Liquid (eNRTL) model for the liquid phase and the RK equation of state for the gas phase, the research includes extensive thermodynamic modelling to simulate the experimental data and predict the behaviour of these amines in CO2 capture processes. The binary e-NRTL and molecule–ion pair parameters were obtained by regression. The overall percentage of the average absolute deviation (%AAD) between the experimental and estimated values for the temperature, pressure, and mole fractions are 0.006%, 0.052% and 0.015%, respectively, for 1,2-Bis(3-AminoPropylamino) Ethane, and similarly, 0.197%, 0.093%, 0.105% for Dytek EP diamine. 1,2-Bis(3-AminoPropylamino) Ethane showed superior solubility performance concerning other amines studied in the literature due to its high molecular weight and four amine groups in its structure, which increased its reactivity and decreased its steric hindrance. Dytek EP diamine had a moderate performance due to its lower molecular weight and the presence of only two amino groups and a methyl group in the structure, creating a steric hindrance and decreasing its capacity.
Open Access
Acceptance and commitment therapy for women experiencing infertility: A randomized controlled trial
(Faculty of Graduate Studies and Research, University of Regina, 2025-03) Balsom, Ashley Anne; Gordon, Jennifer; Hadjistavropoulos, Heather; Klest, Bridget; Lasiuk, Gerri; Corsini-Munt, Serena
Approximately one in six Canadian couples are infertile, defined as the inability to achieve pregnancy despite 12 or more months of active attempts to conceive. While the psychological burden is well-established in the literature, currently available and adapted psychological interventions have had minimal effects on infertility-related distress, anxiety, or depression. We examined the efficacy of Acceptance and Commitment Therapy (ACT) to reduce distress associated with infertility. In Study One, we created the ACT-based intervention in collaboration with a panel of women who had lived experience with infertility. We then conducted a pilot trial with 20 women and used their feedback to refine and update the intervention. Study Two involved a randomized controlled trial (RCT) of the updated ACT intervention, recruiting 90 women who were randomized to the intervention or waitlist control groups. This study aimed to rigorously evaluate the efficacy of the ACT program in alleviating infertility-related distress. Among the recruited sample, 71% completed the entire intervention. Among the eighty-five participants who provided at least partial outcome data, the intervention group showed statistically greater improvements in all three primary outcomes: anxious symptoms (B(SE) = -2.3 (1.3), p = .036), depressive symptoms (B(SE) = -3.8 (1.2), p <.001), and fertility quality of life (B(SE) = 13.6 (3.1), p <.001) relative to the waitlist control group when adjusting for baseline symptom severity. Psychological inflexibility also decreased (B(SE) = -0.6 (0.2), p = .004), while psychological flexibility and relationship satisfaction remained unchanged (p > .05) in the intervention condition compared to the waitlist control condition. Effects were maintained at a one-month follow-up. This intervention shows promise as a cost-effective and accessible intervention for individuals experiencing infertility.
Open Access
Adaptive systems for DDoS attacks detection and mitigation in IoT networks
(Faculty of Graduate Studies and Research, University of Regina, 2025-01) Saiyed, Makhdumabanu Farukali; Al-Anbagi, Irfan; Bais, Abdul; Laforge, Paul; Louafi, Habib; Karimipour, Hadis
The rapid growth of IoT devices has revolutionized industries while exposing IoT networks to cybersecurity threats, particularly DDoS attacks, which compromise network stability. Traditional detection methods struggle to address the constraints of resource-limited environments, scalability, and the need for lightweight, optimized, and reliable systems. This thesis addresses these challenges through five objectives aimed at adaptive DDoS detection and mitigation systems for IoT networks, balancing accuracy, resource efficiency, and adaptability. The first objective focuses on developing a Flow and Unified Information-based DDoS detection system (FLUID) for small-scale IoT networks, enabling DDoS detection with minimal computational overhead. The FLUID system uses flow metrics and unified information measures, to detects both high and low-volume attacks while optimizing resource use. The second objective introduces a system with novel hybrid feature selection to enhance detection accuracy in medium-scale IoT networks. By combining Genetic Algorithm and t-test for DDoS Attack Detection (GADAD), this system improves feature selection efficiency and supporting binary and multiclass classification. For large-scale networks, the third objective is the design of a Deep Ensemble Learning with Pruning (DEEPShield) system that integrates CNN and LSTM architectures, optimized through post-training pruning and a novel preprocessing method. This system achieves high detection accuracy with low resource demand, suitable for resource-constrained IoT environments. The fourth objective focuses on optimizing deep learning-based detection systems to enhance resource efficiency and explainability using the OMEGA, ADEPT, and SHIELD systems. The Optimized Ensemble Learning with Pruning (OMEGA) and Interactive and Explainable Optimized Learning (ADEPT) systems apply techniques like genetic algorithms and differential evolution for resource efficiency. The SHAP-Based Explanation and Lightweight DDoS Attack Detection (SHIELD) system uses SHapley Additive exPlanations (SHAP) for interpretability of individual predictions. The final objective addresses adaptive mitigation through a Game-Theoretic DDoS Defense Strategy Model (GT-DDSM) that dynamically adjusts defense strategies based on attack intensity. These systems are evaluated on metrics such as accuracy, precision, recall, F1-score, and scalability, while optimization efficiency is assessed by preprocessing time, inference speed, memory usage, and model size. Explainability is assessed through SHAP and priority assessment values, while mitigation effectiveness is measured by gradients, cumulative payoff, mitigation time, resource utilization, and network QoS parameters.
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, Raphael
Alzheimer'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.
Open Access
Alcohol and social work: Context and meanings
(Faculty of Graduate Studies and Research, University of Regina, 2024-10) Redekop, Erin Violet; Fletcher, Kara; Albert, Jason; Sorensen, Michele
There is little research available about alcohol use among social workers in Canada. This mixedmethodology study seeks to address gaps in research regarding alcohol use among social workers in Saskatchewan. Social workers in Saskatchewan were invited to participate in an online survey that collected quantitative data including demographic information, alcohol consumption, adverse childhood experiences, and professional quality of life. Qualitative data was collected using semi-structured interviews to capture the meanings social workers attribute to their experiences of alcohol use. The survey found that the overall alcohol consumption of Saskatchewan social workers may be lower than that of the general Canadian population. The survey also found find higher rates of adverse childhood experiences and mental health issues among Saskatchewan social workers than the general Canadian population. The qualitative interviews found that social workers in Saskatchewan worry about the potential negative consequences of alcohol use as a coping mechanism for stress and feel a dissonance between perceived social norms of alcohol use and what alcohol use means to them in their role as social workers. Key words: Social work; alcohol use; alcohol misuse; Saskatchewan; mental health
Open Access
All that is carried
(Faculty of Graduate Studies and Research, University of Regina, 2024-11) Tayaraniyousefabadi, Rozhin; Truszkowski, Robert; Fay, Holly; Garneau, David
This paper supports my Master of Fine Arts thesis exhibition, All That Is Carried, presented at The Fifth Parallel Gallery from November 25 to December 7, 2024. All That Is Carried concerns ideas of home, longing, displacement, and memory. My intention is to convey feelings of disorientation and in-betweenness caused by leaving my family home, and home country. This exhibition addresses the complexity of my transitional state between homes. The installation consists of unstretched, shaped, and cut fabrics painted with images of interiors of my former home in Iran. The paintings draw from photographs I took of my former home. A wooden suitcase filled with folded paintings accompanies the hung paintings. Migration is the most significant change of my life. Visiting my family home in Iran, while living in Rome, was like stepping back in time, but into a timeline that I no longer belonged to. I was a visitor in my parent’s house. Everything that remained behind: my family, friends, most significantly, my feelings of home, was altered. What once felt whole and meaningful was now distant. Yet, the existence of my parent’s house kept these feelings of home prevalent in my life. Despite living in Rome, I carried the unsettling feeling of being tied to a home while also separate from it. This state of suspension had me question what home and belonging mean, especially now that my parents, too, have left that house. This double loss felt like the centre of my world had disappeared, leaving me adrift. All That Is Carried remembers and reimagines that house through painting—transforming it into a tangible memory. The paintings are on a lightweight fabric, like clothes, something I can pack and carry with me. Through the process of making, I am now at a better understanding of what my former home provided for me. I can preserve and carry the significance of home with me.
Open Access
Alliances, assemblages, and affect: Teacher activism within and beyond the union in Saskatchewan
(Faculty of Graduate Studies and Research, University of Regina, 2025-03) Keil, Trudy Lynn; Osmond-Johnson, Pamela; Sterzuk, Andrea; Massing, Christine; Sorensen, Michele; Winton, Sue
In recent decades, Canadian governments have increasingly drawn upon global neoliberal policies to regulate the work of teachers and their professional organizations (Bascia, 2015; Smaller, 1998). Neoliberalism has radically altered educational policies with respect to curriculum, teaching pedagogy, and teachers’ professionalism (Apple, 2006; Ball, 2003), impeding teachers’ ability to deliver democratic education (Darder, 2019). Viewing teacher activism broadly, this research explored Saskatchewan teacher activists’ resistance to marketdriven educational reforms through their engagement with both the power of grassroots social movements and the institutional authority of their union. Guided by Harding et al.’s (2018) poststructural framework of alliances, assemblages, and affects, this dissertation utilized Bartlett and Vavrus's (2017) comparative case study approach to explore teachers’ activism across place, space, and time. Sources included semi-structured interviews with ten known teacher activists and two focus groups with the same participants. Informed by Saldaña (2021), data was analyzed using eclectic coding then interweaved to generate poetry-like narratives representing teachers’ individual and collective voices. Findings showed that teachers strategically navigated activism amidst conflicting personal, professional, and political demands. Both cognitive and affective motivations served as the impetus for participation and activists’ involvements shifted dependent upon factors such as work-life balance and perceived risks. Though teachers viewed grassroots activism as more responsive and hopeful, they also valued the collective strength of the union and recognized its role in their political development. This dissertation distinguishes itself by exploring multifaceted teacher activism through poststructuralism thereby moving beyond mere critique and emphasizing how teachers resist neoliberalism through intentional acts. Keywords: teacher activism, teacher unions, social movements, poststructuralism
Open Access
Analyse stylistique du métissage dans Le Ventre de l’Atlantique
(Faculty of Graduate Studies and Research, University of Regina, 2025-02) Akuoko, Faustina; Rheault, Sylvain; Melancon, Jerome
Fatou Diome, née au Sénégal, a quitté son pays natal pour aller en France. Cette période a été difficile pour elle, mais elle en a tiré l'inspiration pour Le Ventre de l'Atlantique, roman à caractère autobiographique paru en 2003. Elle y confronte les rêves d'émigration des jeunes Sénégalais, qui voient la France comme un paradis, à la dure réalité de l’exploitation des immigrants africains. Tout au long de son oeuvre, Fatou Diome navigue entre les mondes européens et africains et il en résulte de nombreux procédés de métissage culturel. Cette étude se concentre sur l’analyse du métissage culturel dans Le Ventre de l'Atlantique de Fatou Diome. Au moyen des matériaux de la stylistique, la recherche mettra en lumière les interactions parfois dramatiques et parfois humoristiques entre la culture sénégalaise et la culture française. Concernant le matériau du locuteur, l’auteure Fatou Diome, tout comme la narratrice Salie, doivent questionner leur identité métissée. Concernant le destinataire, le choix de la langue française révèle que le public est européen, tandis que la question de l’immigration s’adresse aux jeunes africains. Concernant la situation, les mélanges de lieux et de moments au Sénégal et en France permettent de combiner les cultures et de construire la nouvelle identité métissée de Diome/Salie. Concernant la visée argumentative, l’auteure fait flèche de tout bois en encensant et en critiquant en même temps les aspects positifs et négatifs des cultures africaines et européennes. Il faut, par exemple, s’inspirer du modèle européen pour s’opposer aux mariages arrangés, ou s’efforcer de développer l’Afrique au lieu de chercher à émigrer. Concernant l’immigration, c’est là le thème central du roman, qui motive les décisions et qui est, en quelque sorte, le moteur du métissage culturel. Enfin, il y a le thème du football, une activité « unificatrice » profondément ancrée dans les deux cultures qui est aussi, comme l’immigration, source de métissage. Enfin, la recherche veut mettre en lumière l’humour dans cette oeuvre. L’humour est plus qu’une tonalité narrative, c’est aussi un outil de métissage culturel et cela semble avoir été jusqu’à maintenant peu reconnu par les critiques de Fatou Diome.
Open Access
Analysis of dissolved organic matter character and dynamics using optical techniques in prairie wetland ponds
(Faculty of Graduate Studies and Research, University of Regina, 2024-12) Khan, Faraz; Hall, Britt; Soares, Bruno; McBeth, Joyce
Carbon plays an important role in a variety of Earth’s biogeochemical processes, through its various reservoirs and the interconnections between them. The hydrosphere is an important reservoir for carbon, and inland waters have often been regarded as unimportant in carbon biogeochemical cycling. However, important transformations and transport mechanisms occur within inland waters. Wetlands are an example of this, where carbon is in flux with the atmosphere and hydrosphere. Dissolved organic carbon (DOC), the carbon fraction and majority of dissolved organic matter (DOM), is found in the earth’s aquatic environments, is an important connection in the carbon cycle between terrestrial and aquatic systems and plays a variety of biogeochemical roles. Within aquatic environments, DOM plays an intermediary role in trace metal cycling such as that of toxic mercury. DOM is highly heterogenous and can be characterized according to its structure, origin, and molecular weight. Optical techniques have emerged as a powerful tool to analyze DOM according to its origin and chemical character, and in several techniques such as derived fluorescence indices and parallel factor analysis (PARAFAC) models based on emission-excitation matrices have become common. Within Saskatchewan, Canada and located in the prairie pothole region (PPR), the St Denis National Wildlife Area is home to a series of wetlands where a more toxic form of mercury, called methylmercury (MeHg) is found in highly differing amounts within close proximity. DOM is known to influence MeHg concentrations and the process of mercury methylation. This thesis hypothesized that the differing characteristics of DOM may explain differences in high methylmercury concentrations. Through the use of optical techniques, including derived fluorescence indices and PARAFAC modelling, this thesis establishes that high MeHg concentration wetland ponds in SDNWA have more humic and terrestrially derived DOM, and low MeHg concentration wetland ponds have more aromatic DOM. This suggests that the highly aromatic DOM, combined with the high sulfur conditions of the SDNWA enable a greater amount of photodemethylation of MeHg in low MeHg concentration wetland ponds. Keywords: Dissolved organic matter, Methylmercury, Emission-excitation matrix, Parallel factor analysis, Prairie Pothole Region
Open Access
Automated aerial detection of spruce tree crowns through YOLOv5 and watershed segmentation
(Faculty of Graduate Studies and Research, University of Regina, 2025-01) Mohemi Moshkenani, Mahdi; Peng, Wei; Henni, Amr; Kabir, Golam
The spruce tree, a key species in Canada, is crucial to industries like timber and pulp. Effective management of these resources relies on monitoring forest parameters to ensure long-term forest health and productivity. Tree crown dimensions contribute valuable insights into these parameters. This study investigates an automated approach for detecting and measuring spruce tree crowns using the YOLOv5 machine learning model combined with watershed segmentation. The method enhances the accuracy of crown measurements from aerial drone images. Over 2,000 spruce trees in a limited forested area of Saskatchewan, Canada, are analysed using top-view images captured by a DJI Mavic 3 Classic drone, which is sufficient for this project as the model trained well. The YOLOv5 model is initially employed to detect trees, following by watershed segmentation to refine the tree crown boundaries. In the forest measuring area, some regions contain closely spaced trees with overlapping crowns that cause challenges for accurate recognition of tree boundaries. Although feeding watershed segmentation with YOLO-detected individual trees addresses this issue, tuning the IoU threshold in the NMS stage, applying data augmentation, and utilizing high-resolution images further enhance detection accuracy. One issue in predicting tree crowns is the underestimation of diameters, often resulting from systematic errors in image capture, measurement methods, environmental conditions, and limitations in image resolution. To address this issue, a linear regression model is applied to adjust the predicted crown diameters, aligning them more closely with the actual field measurements. This approach demonstrates an acceptable accuracy of 89.1% compared to prior research and existing methodologies, which reported accuracies ranging from 67.72% to 95.4%, particularly in complex forest environments. Although the primary focus of this research is on measuring tree crowns, the findings have broader implications for forestry management activities, such as biomass estimation and forest health monitoring. Future research could explore further improvements to the model for real-time forest management applications, as well as expand its use to detect and measure other tree species in mixed forests and agriculture plants.
Open Access
Barriers to entry: The impact of non-standard orthography on learning the Lakota language
(Faculty of Graduate Studies and Research, University of Regina, 2025-03) Buffo, William; O’Reilly, E. Kathleen; Weenie, Angelina; Wolvengrey, Arok; Miller, Andrew M.
The revitalization of the Lakota language is hindered by the absence of a universally accepted orthographic standard. This thesis investigates how non-standard orthographies influence Lakota language acquisition, cultural preservation, and educational practices. Guided by qualitative methodologies, this research explores the diverse orthographies used within the Lakota-speaking community and their impacts on learners, educators, and cultural authenticity. Data were collected through surveys and interviews with students, educators, and community members, focusing on their experiences and perceptions of orthographic systems. Analysis revealed key themes, including the challenges posed by inconsistent orthographies, the cultural tensions arising from orthographic choices, and the need for systems that balance phonetic accuracy with cultural sensitivity. Findings indicate that while orthographic diversity reflects the community’s linguistic heritage, it often complicates learning and teaching efforts. This study concludes that sustainable language revitalization requires a dual approach: adopting standardized orthographies to support literacy and educational consistency while respecting traditional oral practices and cultural values. Recommendations include developing flexible orthographic systems that cater to diverse learners, promoting community-led initiatives, and integrating technological resources to bridge gaps between tradition and modernity. Keywords: Lakota language, orthography, language revitalization, Indigenous education, cultural preservation, phonetic representation
Open Access
Bayesian probabilistic projections of future climate over Canada based on the RCM ensemble
(Faculty of Graduate Studies and Research, University of Regina, 2024-03) Song, Tangnyu; Huang, Guohe (Gordon); Veawab, Amy; Zhu, Hua; Deng, Dianliang; Li, Jonathan
In this research, a series of approaches are proposed to address the challenges in generating robust probabilistic projections of climatic variables (e.g., temperature, precipitation, and Intensity-Duration-Frequency curves) and analyzing the associated uncertainties based on the Regional Climate Model (RCM) ensemble. The proposed approaches have been applied to Canada for demonstrating their effectiveness. Specifically, a new discriminant-Bayesian Model Averaging (BMA) ensemble climate modeling (DBEC) approach is developed to help address the neglected spatiotemporal variations of model biases. Through the proposed method, the BMA weights are used as prior distributions to drive the Bayesian discriminant analysis in order to generate refined weights for individual ensemble models according to their spatiallyand temporally-clustered performance. The results suggest that the DBEC approach can improve both the accuracy and reliability of ensemble projections to some extent, especially in winter and Arctic regions. The probabilistic projections of temperature for three future periods under two emission scenarios are then obtained through the proposed DBEC model. The results indicate that comparatively larger temperature increases can be observed in Arctic regions. In addition, the magnitude of uncertainties is found to be negatively correlated to the elevation. Then a new multi-dimensional discriminant-BMA ensemble approach (MDBE) is developed to quantitively characterize the relationships between the modeling performances and climatic conditions. Through the comparative assessments of the proposed approach against three other ensemble methods, its effectiveness in generating the probabilistic projections of annual and seasonal precipitation over Canada has been illustrated. In detail, the R2 and percentage coverage will increase up to 0.15 (from 0.52 to 0.67) and 20% (from 60% ~ 80%), respectively. The generated projections suggest that significant precipitation increases are observed in future periods, especially in the Arctic regions. The warming climate could be the primary reason for such increases. Moreover, the intensified atmospheric radiative cooling is also a possible explanation for the winter precipitation increase. Finally, a new CDF-distance-based method is proposed to generate ensemble projections of IDF curves over Canada. Compared with the traditional ensemble methods, the proposed CDF-distance-based ensemble approach depends less on the simulated accuracy of annual maximum precipitation time series. Consequently, it can improve both the accuracy and reliability of the probabilistic projections in IDF curves. The proposed method has been applied to Canada for assessing the future changes of the IDF curves. The results suggest that the upward shifts of the IDF curves under all return periods are observed under changing climate conditions. Moreover, the percentage changes of precipitation intensities increase with return periods.
Open Access
Beam asymmetry in the reaction channel γp→ηΔ + at Glue X
(Faculty of Graduate Studies and Research, University of Regina, 2024-08) Neelamana, Varun; Papandreou, Zisis; Lolos, George; Huber, Garth; Stevens, Justin R.; McBeth, Joyce; Watts, Dan
Photoproduction mechanisms studied in the GlueX experiment allows the mapping of light mesons in unprecedented detail with particular interest in exotic meson candidates. This is achieved by impinging an 8.2-8.8 GeV linearly polarized photon beam on a liquid hydrogen target. The measurement of beam asymmetry Σ will help constrain quasi-particle t-channel exchange processes using Regge theory. Understanding the photoproduction exchange mechanisms is a crucial ingredient in establishing hybrid and exotic photoproduced light meson states. Σ is extracted from the azimuthal angular distribution between the meson production plane and the polarized photon beam. In particular, we will report results on the beam asymmetry measurements for η in the reaction p →η Δ+. This reaction with a recoiling Δ+ will allow for comparison and validation of theoretical calculations and provide additional validation of the η asymmetry with a recoiling proton. The different isospin of the Δ+ imposes additional restrictions that further constrain allowed Regge exchanges. The results were similar to η-proton i.e Σ ≈ 1 but showed a deviation from theoretical models of the η - Δ+ especially towards higher t values. This may help guide modifications to these models for production and exchange processes involving η meson.
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, Nader
In 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
Open Access
Beyond net-zero carbon emissions in industrial processes through catalyst-aided amine solvents for the indirect co-combustion of natural gas and biomass
(Faculty of Graduate Studies and Research, University of Regina, 2025-01) Adjetey, Samuel; Idem, Raphael; Supap, Teeradet; Ibrahim, Hussameldin
This thesis investigates the application of absorber catalysts developed and optimized for effective CO₂ capture in a power production process involving the indirect co-combustion of biomass and natural gas, addressing a crucial case study challenge of carbon emissions from large. By employing a novel bi-blend amine solvent system, improved by heterogeneous solid base catalysts, the study explores the synthesis of various super basic catalysts in a bid to optimize CO₂ absorption rates, solvent loading, and overall process efficiency A series of heterogeneous catalysts which include PEI modified catalysts, K/MgO, K/MgO-CaO, and activated carbon blends, were synthesized and tested using a semi-batch apparatus. The initial CO₂ absorption rates of these catalysts were thoroughly analyzed against a non-catalytic baseline (control experiment). The results obtained revealed that catalysts such as AC Hydrothermal and K/MgO-CaO (5-35-60) significantly increased CO₂ absorption rates by up to 46% and 21%, respectively, over the baseline. Contrarily, despite characterized by high basic strength, some PEI-modified catalysts, exhibited lower performance due to reduced surface area and electron transfer limitations. However, further analysis was conducted on the K/MgO-CaO (5-35-60) catalyst over the activated carbon catalyst considering its superior chemical, thermal and mechanical stability, as well as the ease of preparation and reduced waste. The screening of the catalysts was carried out at a gas composition of 4.5% CO2 (balance N2, an absorption temperature of 40℃ ± 2, and a gas flow rate of 200± 5 ml/min). Additionally, extensive catalyst characterization test, including Powder X-ray Diffraction (XRD), CO₂ Temperature Programmed Desorption (TPD), and BET surface analysis, were conducted to understand how catalyst properties such as basic site strength, surface area, and pore structure influence CO₂ capture rates observed. The environmental impact and potential cost savings of catalyst-aided carbon capture were then evaluated in a simulated power generation process, where an LCA, life cycle assessment, model was applied based on the ReCiPe methodology. From comparing traditional MEA benchmark solvent, the novel AMP-PRLD amine bi-blend, and the AMP-PRLD solvent enhanced with a K/MgO-CaO catalyst, the results demonstrated that the catalyst-enhanced system achieved superior carbon dioxide reductions across various gas compositions, underscoring its potential for net-zero emissions. Conclusively, this catalyst-solvent system provides a promising pathway for the power and energy sectors to significantly reduce emissions while enhancing cost-effectiveness and sustainability.
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, Paitoon
Technology 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.

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