26734 research outputs found
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Reframing Women at Work in the Skilled Trades
No full textThis thesis investigates how abstract painting can be used to reframe women at work in the skilled trades. Despite ongoing recruitment efforts, women remain underrepresented in these areas of work and continue to face structural, cultural, and visual barriers. Using methods of inquiry grounded in research-creation, personal experience, and observation, this project draws from lived experience and studio experimentation to create relationships between abstraction, labour, gender, and agency through colour, embedded text, and abstracted forms drawn from tools, body, gestures, and material environments. The paper is structured into three main sections: a historical and cultural framing of women in trades; an outline of studio process and visual strategies developed through rhizomatic and experiential approaches; and the installation of five large-scale abstract paintings at the Southern Alberta Institute of Technology (SAIT). Situated within a high-traffic institutional space, the project engages students, young girls, mentors, trades professionals, the SAIT community, the broader art community, and the public. By reframing women’s labour through abstract visual language, this research emphasizes agency and encourages new ways of thinking. The work invites reflection and conversation without opposition, aiming to expand how labour, identity, and experience are seen and valued within skilled trades contexts
Performance Prediction Techniques for Deep Neural Network Inference
No full textAs Deep Neural Networks (DNNs) become increasingly central to real-time, decision-critical applications, such as autonomous vehicles detecting road objects within milliseconds, ensuring predictable and reliable inference performance is essential. However, latency prediction for DNNs remains understudied due to such systems’ complex behavior under diverse conditions and a traditional emphasis on accuracy over performance. This thesis addresses the urgent need for DNN inference latency prediction in practical deployment settings, where performance is as critical as accuracy. I present a sequence of three interlinked contributions that progressively tackle this challenge. First, I propose a hybrid model that predicts inference latency for popular DNNs served via TensorFlow Serving. A key feature of this approach is that it does not require invasive instrumentation or large training datasets, critical for real-world deployments. The model accurately captures the impact of workload and resource variability, maintaining prediction error below 10% for unseen configurations. Building on the observations from this part of my work, I address co-hosted environments where multiple DNNs share resources. I develop a performance prediction model that combines system-level features with DNN performance behavior observed in an isolated setting. I show that the model enables early detection of inference response time violations with over 92% accuracy, while not requiring extensive data collection. Finally, I confront the practical challenge of predicting performance for previously unseen DNNs in novel deployments. By analyzing utilization patterns and measurements of each DNN’s in-isolation performance, I demonstrate the feasibility of accurate response time predictions in new DNNs with an error of nearly 13%. Together, these contributions form a unified and generalizable framework for modeling DNN inference performance, from isolated to co-hosted and from known to unseen DNNs, supporting scalable, efficient, and dependable deployment of DNN-powered systems
Integrating Critical Media Literacy into Elementary Schools
No full textThis qualitative case study evaluates how Critical Media Literacy (CML) is integrated into a fifth-grade elementary classroom, focusing on how instructional tactics, resources and pedagogical approaches influence students' critical engagement with media texts. In today’s environment, young learners are constantly exposed to a range of digital and print media, which makes it essential to cultivate elementary students' ability to analyze, evaluate, and produce media critically. This study seeks to examine how a classroom instructor uses CML in regular education to help students develop critical thinking and media literacy abilities. The research draws on interpretivist theory, focusing on how meaning is constructed and interpreted within the classroom context. Data were collected through semi-structured interviews with the teacher participant, detailed classroom observations over several weeks and the examination of instructional artifacts such as lesson plans, student work samples and digital media resources. Thematic analysis was applied to identify key patterns related to instructional methods, student engagement and the integration of media texts across the curriculum. This study's findings show that the instructor used a variety of multimodal tools, such as interactive whiteboards, Chromebooks, digital storytelling platforms and visual aids, to enhance students' critical examination of media. The instruction was balanced between direct teaching, collaborative learning and innovative student assignments that fostered deep thought and critical thinking. The study also shows how CML was integrated into a variety of areas, including Language Arts, Social Studies, Science and Mathematics, allowing students to apply critical literacy abilities across disciplines. By documenting the lived experiences of the teacher, the study sheds light on the practical realities of applying CML in an elementary school context. It emphasizes the significance of teacher preparation, access to relevant digital resources and the careful integration of media literacy into current curricular frameworks. This research adds to the greater discussion on CML by providing concrete examples of best practices that educators and policymakers may use to improve critical media literacy teaching at the elementary level
Dear App, It’s not you, it’s me: A quest for traffic transparency in Android
No full textTLS encryption in Android, while providing much-needed privacy and security for user data, becomes a double-edged sword when the same security measures that guard user privacy paradoxically create unprecedented opportunities for SDKs and apps to collect sensitive information without explicit user consent. It further presents methodological challenges for users and privacy researchers attempting to audit data flows in mobile applications on their own devices. In this thesis, we critically examine several existing TLS instrumentation approaches, identify their limitations, and provide empirical evidence showing the use of encrypted channels to collect sensitive data such as location data, device identifiers, and usage patterns by apps and SDKs. We further develop our extended Berkeley Packet Filter (eBPF)–based solution, Advaita, and evaluate its effectiveness against other approaches–Mitm, Aosp-Sci, and SSLKeyLog. We use rigorous quantitative assessment and statistical analysis to establish that Advaita outperforms other approaches across a corpus of mobile applications, highlighting the gaps in the current TLS instrumentation landscape, such as the use of native custom TLS libraries and certificate pinning. Our findings further reveal that TLS key logging on Android production devices is not only obscure and effectively unavailable to users, but with constraints due to Android’s Logging architecture and the ability of apps to exploit native Android APIs to disable logging entirely, there exists a lack of transparency by design in Android. Finally, we show that deliberate downgrading of QUIC/HTTP3 connections falls back to HTTP/1.1 four times more often than HTTP/2, which can be used to enhance TLS instrumentation visibility when using other techniques. This research establishes an empirical foundation for understanding encrypted mobile traffic and its privacy implications. It argues that users and security researchers have a reasonable expectation to audit network traffic generated by applications running on their own devices while offering practical solutions that enhance transparency as a form of digital self-determination
Didactic Sacred Dramas: Giovan Maria Cecchi’s use of Petrarchism in his Moral Plays
No full textThe study of moral plays is often one concerned with identifying the purpose of theological theater. Scholars have often focused on the cultural and literary significance of these religious works, while identifying how virtue is represented and interpreted by the audience. However, in-dept analyses of the technical approach to these didactic attempts are limited. To improve our understanding of the intrigue of these sixteenth century religious moral plays, we must further investigate how the author accomplishes the delivery of the theological and philosophical
contemplation in a successful way. To better comprehend some of the strategies employed by Renaissance playwrights, I analyze Giovan Maria Cecchi’s strategical approach to his sacre
rappresentazioni: Disprezzo Dell'Amore e Beltà Terrena (Contempt of Love and Earthly Beauty) and Duello della Vita Attiva e Contemplativa (Duel of the Active and Contemplative Life). This
analysis includes close readings which provide evidence that these didactic moral plays benefitted by the author’s use of Petrarchism as a mechanism to allure his audience, while reaching a different conclusion than that of Petrarca’s Canzoniere. Namely, this study finds that Cecchi’s didactic moral plays employ three main strategies to achieve maximum effectiveness in their teachings: the use of Petrarchism’s linguistic allure to engage the audience, the selection of allegorical figures as characters to entice the audience to engage with moral introspection, and a
combination of idioms and imagery to evoke an aesthetic literary work which gains the trust of its audience
Development and Analysis of Efficient Numerical Methods for Helmholtz Equation
No full textThe Helmholtz equation, which describes the oscillatory behavior and propagation of waves, is a partial differential equation that appears in a wide range of applications. Solving the Helmholtz equation analytically, especially in higher dimensions with variable coefficients, is nearly impossible. The cost due to high memory requirements in numerical methods and the failures of classical iterative methods emphasize the need to find efficient methods to solve the Helmholtz problem. In this work, a fourth-order compact finite difference scheme, known as the Pad´e approximation, a sixth-order compact finite difference scheme, compact combined schemes, and Alternating Direction Implicit methods are utilized in developing a class of novel methods to solve the one-dimensional and two-dimensional Helmholtz problem. The efficiencies and orders of convergence of the newly derived methods are tested and compared using numerical examples, which also demonstrate that the proposed methods are higher-order and efficient
Integrating Techno-Economic Optimization and Life Cycle Assessment to Evaluate Carbon Intensity and Economic Potential of Carbon Dioxide Enhanced Oil Recovery in Alberta
No full textCarbon capture, transportation, and utilization for CO2-enhanced oil recovery (CO2-EOR) presents a promising approach for utilizing anthropogenic CO2 while increasing oil production. However, despite extensive research on the life cycle carbon footprints of CO2-EOR over the past two decades, inconsistent methodologies yield widely varying results, limiting their reliability for policy development. This thesis addresses these methodological challenges through a systematic meta-analysis, an optimization-based techno-economic model, and an integrated techno-economic and life cycle assessment framework to enhance the robustness and Alberta relevance of CO2-EOR evaluations. Chapter 2 performs a global systematic review and meta-analysis of life cycle assessment (LCA) studies examining greenhouse gas (GHG) emission factors from CO2-EOR systems utilizing both natural and industrial CO2 sources. A comprehensive workflow—screening, eligibility review, data validation, and parameter harmonization—standardizes critical background inputs, with particular emphasis on electricity-grid emission factors (Scope 2). Economic allocation and system-expansion (substitution) quantify cradle-to-grave impacts across the multi-product supply chain. Statistical analysis shows that electricity consumption correlates more strongly with gate-to-gate emission factors than net CO2 utilization, and no meaningful correlation appears between electricity use and net CO2 utilization. The choice of allocation methodology emerges as the dominant determinant of well-to-wheel results. Venting and fugitive contributions range from 2%–90% of harmonized gate-to-gate emission factors across the reported studies, underscoring the need for standardized monitoring. Chapter 3 builds upon and improves an existing techno-economic analysis (TEA) model to determine optimum reservoir-specific hydrocarbon pore volume (HCPV) injection rates that honour injectivity constraints and to calculate the corresponding cumulative HCPV injected over the flood life, thereby evaluating Alberta’s basin-wide CO2-EOR potential under multiple economic scenarios. The enhanced model integrates technical data from over 10,000 vertical wells and lithology-based permeability estimates. It also introduces economic refinements such as optimized CO2-EOR flood life. The model incorporates potential carbon offset price and availability (allocated to the operator), and operational performance statistics from 31 West Texas CO2-EOR projects. Sensitivity analyses demonstrate that project economics are highly responsive to the oil price, CO2 offset pricing, and field-level operating metrics such as CO2 retention and incremental oil recovery. This study thus enhances the applicability of the improved TEA model to Alberta’s unique geological and economic context, enabling a more granular and realistic assessment of CO₂-EOR deployment potential. Chapter 4 evaluates the Well-to-Refinery gate (WtR) emissions potential of CO2-EOR development in Alberta through an integrated techno-economic and emissions assessment framework. The analysis examines 2,950 technically screened field-pools by combining the Oil Production Greenhouse Gas Emissions Estimator (OPGEE) with a techno-economic assessment (TEA) model, incorporating varying economic and operational parameters. Spearman rank correlation analysis identifies key drivers of emissions variability, finding that oil production rate, project before-tax net present value, and the gas flooding injection ratio are the strongest correlates of WtR carbon intensity across the screened pools. Overall, the thesis demonstrates that methodological choices, boundary definitions, and underlying assumptions critically shape CO2-EOR evaluations. Specifically, the analysis finds that: (i) at US50/t offset, Alberta’s technically screened pools support ~ 1 Gt of CO2 storage and ~2.2 billion bbl of incremental oil, with 50% of 637 clusters achieving before tax net present value discounted at 10% >0; (ii) the volume-weighted break-even net field-delivered CO2 price averages ~C1 change in WTI than to a C120–C$170/t) shift value toward storage while leaving oil volumes relatively inelastic; and (v) the lowest-CI quartiles tend to coincide with stronger project economics, enabling regulators and investors to prioritize low-CI barrels without sacrificing returns. Together, these insights guide Chapters 3 and 4, provide practical guidance to optimize CO2-EOR designs, target clusters with the greatest system-level impact, and align policy instruments with verifiable storage and low-CI production in Alberta
Soil Stabilization with Cement and Duraflex (DFI) Admixture
No full textTo improve the engineering properties of soils, such as their strength and durability, the soils need to be stabilized. In other words, to construct roads, railways, airports, and high-rise buildings, the soil needs to be a firm foundation. Portland cement is considered the basic stabilizer for soil strength improvement and is used globally. However, it is well-known that no step from the production to application of Portland cement is eco-friendly, which contributes approximately 7% to 8% of the global carbon dioxide (CO2) emissions. Researchers are in a continuous race to find eco-friendly and cost-effective alternative solutions for soil stabilization. Duraflex-DFI is a novel soil-stabilization material. The effectiveness of Duraflex as an additive in various soils collected from different locations across Alberta, Canada is assessed in this thesis. Various tests, such as strength, durability, and microstructural level analyses, were conducted to fully explore the outcomes. The results obtained from the research described in this thesis confirmed that soils treated with Portland cement plus DFI performed overall better, such as for mechanical strength (unconfined compression strength (UCS), uniaxial tension test (UT), and splitting tensile strength (STS)) and durability performance (freeze-thaw (F-T) and wetting-drying (W-D)). The DFI-stabilized soils resulted in approximately 10% to 30% better results than those of the reference mixes (soil plus only Portland cement). The scanning electron microscopy (SEM) and Quantitative-X-ray diffraction (Q-XRD) analyses showed that Diatomite and Clinoptilolite (natural zeolite) are two possible minerals in DFI that help boost the pozzolanic reaction in the DFI-stabilized mix. This results in the formation of more cementitious compounds, including calcium silicate hydrate gel (C-S-H gel), which fills the pores and voids, resulting in improved strength and additionally, the stress intensity factor is lower as pores are smaller. The formation of cementitious compounds was validated through the mechanical strength test results, as well as the pozzolanic reaction. The formation of these additional cementitious compounds results in the reduction of pore size and volume, validated by the Brunauer-Emmett-Teller (BET-N2), matric suction (ua-uw), and the percentage pore reduction seen in SEM photomicrographs (ImageJ software). Therefore, Duraflex a new eco-friendly and economical soil stabilization admixture, is ready to be used in projects located in severe and harsh environmental zones exposed to severe freezing-thawing and/or wetting-drying
Ready or Not: K-12 Teachers’ Perspectives on GenAI and Critical Thinking
No full textThe academic poster showcases the preliminary results of this qualitative study.The increasing advancement and omnipresence of generative artificial intelligence (GenAI) has provoked significant discourse surrounding its potential to transform the education system. The purpose of this study is to explore K-12 teacher perspectives on how using GenAI in classrooms to support student learning and teacher workflow may impact students’ critical thinking skills through the research question: under what factors/conditions does GenAI use help or hinder critical thinking when used by educators in K-12 classrooms? In this qualitative study, a fulsome literature review coupled with semi-structured interviews (N=10) were conducted with K-12 teachers who work with students in formal or informal classroom settings. The results indicated that whether GenAI use has a positive impact on critical thinking can depend on how the teacher is facilitating its use with students. Additionally, students are more apt to critically evaluate outputs if the use is embedded in the learning process and expectations are explicit. Further, the degree to which teachers were supported with GenAI-focused professional learning influenced whether teachers would enhance their GenAI integration independently or would not engage with the technology altogether. Future research should consider student perceptions of GenAI’s capabilities and inabilities to positively impact their learning to help provide further context into student readiness for GenAI adoption in classrooms.University of Calgary- PURE Research Experiential Learning OpportunityOthe
Between Shyness and Niceness : Cross-Cultural Friendship and the Politics of Belonging in Multicultural Canadian High Schools
No full textThis thesis explores how cross-cultural friendships between Canadian-born and newcomer high school students are shaped by institutional discourses, emotional labor, and norms of belonging within multicultural public schools in Canada. Drawing on in-depth, semi-structured interviews with both Canadian-born and immigrant youth, this study employs a hybrid methodological approach, combining Constructivist Grounded Theory (CGT) and Foucauldian Discourse Analysis (FDA), to examine how students interpret, navigate, and contest dominant narratives of inclusion. Findings reveal a disconnect between policy-driven multicultural ideals and the lived experiences of students. While schools often promote values such as kindness, diversity, and inclusion, these are frequently enacted as symbolic performances that mask structural inequities. Unspoken norms, such as emotional restraint, linguistic fluency, and cultural conformity, place the burden of adaptation disproportionately on newcomer students, who are often expected to perform emotional labor to remain socially legible. This thesis re-conceptualizes friendship not as a neutral or private bond but as a politicized, emotionally negotiated space where norms of civility and belonging are reproduced and, at times, resisted. It argues that institutional discourses of “niceness” often function as affectively neutral yet exclusionary practices that limit the possibility of authentic connection. Through students’ narratives, this study foregrounds friendship as a micro-political site of discursive negotiation, emotional asymmetry, and institutional critique. The research contributes to ongoing discussions in multicultural education by offering a nuanced theoretical framework for understanding inclusion, not as policy compliance or optics, but as a relational, affective, and justice-oriented process. It calls for school practices that center emotional reciprocity, cultural humility, and the redistribution of relational labor in order to foster more equitable educational environments