VictorJuiz/thesis huggingface dataset:
Enriched Reduced Model Accelerated Level Set Topology optimization

In this work, we develop level-set topology optimization methods accelerated by projection-based reduced-order models (ROM) constructed on the fly. We extend existing trust-region-based ROM-accelerated topology optimization methods, which are restricted to density-based topology optimization, to level-set cut finite element methods (FEMs), which provide accurate geometry representation and avoid so-called ``ersatz materials'' or ``passive elements''. One challenge to apply ROM to topology optimization based on cut FEM is that the support of the solution snapshots changes with the geometry, which makes the construction of reduced basis difficult particularly near the domain boundaries. To overcome the challenge, we introduce a family of enriched reduced models, which enrich the reduced basis using finite element basis near part or all of the boundaries. We devise various methods to specify the enrichment regions. We assess the methods using two-dimensional structural topology optimization problems. We observe that a multi-stage algorithm which adaptively selects the enrichment region considerably reduces the computational time, especially as the full order model cost increases.

Keywords: Cut-Cell
Finite Element Method
Level-Set
Model Order Reduction
Optimization
Topology Optimization
Advisor: Yano, Masayuki
Exploring Urban Residents’ Knowledge and Participation in Green Infrastructure Initiatives in Philadelphia

Green infrastructure (GI) is an emerging concept refers to trees and vegetation that provide ecosystem services to humans. Recently, GI has been adopted in urban planning and policy because it provides a nature-based solution for storm water management and many other socio-environmental benefits. Public understanding and engagement are essential for GI development, but few studies have examined residents’ knowledge and attitudes towards GI. This research surveyed residents in Philadelphia, PA, on their understanding of GI and participation in local GI programs. Results indicate residents’ knowledge of GI is limited, and most have minimal concerns about urban flooding, the main focus of Philadelphia’s GI programs. GI program participants are not only more familiar with the concept of GI, but also are more likely to install additional GI features in the future. The thesis ends with a discussion of implicating these findings in the context of GI expansion opportunities in residential landscapes.

Keywords: Ecosystem services
Green infrastructure
Philadelphia
Public engagement
Stormwater management
Advisor: Conway, Tenley
Assessing the Impact of Climate Change on Electricity Planning in Ontario, Canada

Electricity grid adequacy is the ability of the electric system to supply the electricity required at all times, accounting for derates and outages of system components. Ontario’s electricity needs are primarily met by thermal and hydroelectric generators, shown to be impacted by climate conditions. We quantify the effects of climate change on Ontario’s future demand and capacity based on the highest risk climate change scenario (RCP 8.5) for the year 2040. The main climate change variables considered are temperature, humidity, and precipitation. Very minor reductions in summer effective capacity are expected (approximately 0.2%), together with a moderate increase in summer demand (approximately 6%). These results only reflect the impacts of climate change relative to the current climate. Although the Independent Electricity System Operator appears to capture enough variability in their grid adequacy estimates, it may be wise to add additional butter to capture the impact of climate change discovered here.

Advisor: Posen, I. Daniel
MacLean, Heather
Office Hours: A UX investigation on How Might We Improve the Remote Office Hours Experience in Higher Education through Design Thinking

Instructors and students in higher education experienced abrupt pedagogical changes due to the COVID-19 pandemic. Despite the breadth of new digital products available, instructors and students still experience communication challenges and dissatisfaction during remote learning. This thesis used design-thinking to prototype a digital tool that facilitates remote office hours as an extension of communication between students and instructors outside of the virtual classroom. By following design thinking, the study illustrated the insights synthesized from faculty and students’ user experience during office hours to help the reader to emphasize the challenges, needs, and goals stemming from remote learning. Meanwhile, the thesis aimed to elucidate the best practices for facilitating remote office hours to help faculty and students cultivate meaningful conversations and build a more collaborative work environment in the digital age.

Keywords: design thinking
Digital communication
Higher Education
Office hours
remote learning
user experience design
Advisor: Ryan, Dan
Development of a System to Measure Adherence to Lower Back Pain Rehabilitation with Wearable Sensors and Artificial Intelligence

Lower back pain (LBP) is a prevalent health problem that is often effectively treated with physiotherapy/rehabilitation. Adherence to a prescribed rehabilitation program is positively correlated with its overall effectiveness. However, currently there are no simple and deployable quantitative methods to assess home-based LBP rehabilitation participation, where the majority of exercises should be performed. It is hypothesized that inertial data collected from a set of multi-IMU-based wearables analyzed with machine learning will successfully identify the performance of LBP exercises and good sitting posture. With an optimized system utilizing an XGBoost classifier and three IMU sensors placed at the lower back, thigh, and ankle, accuracies of 94% ± 3% and 90% ± 11% were achieved for classification of LBP exercises and good sitting posture, respectively. The technology generated within this project has the potential to improve the effectiveness of LBP rehabilitation by facilitating remote monitoring, early problem diagnosis, and quantitative clinical feedback.

Keywords: Adherence
Home-Monitoring
IMU
Lower Back Pain
Physiotherapy
Rehabilitation
Advisor: Whyne, Cari
Hardisty, Michael
A Pattern-driven Stochastic Process for Degradation Forecasting with Applications to Rechargeable Batteries

In recent decades, there has been significant growth in the development of rechargeable battery-powered devices such as electric vehicles, leading to an urgent demand for batteries with high reliability and quality. The end-of-life (EoL), a critical indicator of battery health, can be estimated by adaptive stochastic processes or advanced machine learning techniques. However, unless such approaches assume that the degradation path has a specific form, they operate as black boxes and are unable to provide stochastic interpretation. To address these challenges, a pattern-driven degradation process (PdDP) was executed that can model battery degradation, controlling degradation fluctuation by a GRU-driven degradation pattern. Further, a joint-learning sampling-based expectation maximization (JSEM) algorithm was developed to handle non-Markovian state transitions in estimating model parameters. Finally, a case study showed that the proposed methods outperform traditional methods with respect to both one-step and multistep-ahead prediction accuracies.

Keywords: Degradation Pattern
End-of-life Prediction
State-space Model
Stochastic Process
Advisor: Lee, Chi-Guhn CG
Understanding Material Stocks in Roads at the City and Multinational Scale

Improving resource efficiency is critical to reduce the environmental impacts of constructing and maintaining the built environment. Construction materials represent a growing share of global greenhouse gas emissions, but limited knowledge concerning the quantity and distribution of materials making up infrastructure is an obstacle to designing robust policies and tracking progress towards greater resource efficiency. This thesis investigates material stocks in roads at the city and multinational scale through case studies of the road networks of Toronto and six high-income countries. Modelling material stocks at the city scale using simplified archetypes is shown to introduce significant uncertainty that is not well addressed in existing studies. Multinational road stocks are estimated using a method that better captures the inherent variability in pavement design. Considerable differences in the material intensities of different countries’ road networks are observed, suggestive of opportunities to build roads with lower environmental impact.

Keywords: industrial ecology
material efficiency
material flow analysis (MFA)
pavement
roads
transportation
Advisor: Saxe, Shoshanna
Establishing a Novel Approach to Engineer Inhibitors of Pathogenic Transcription Factors

Transcription factors (TFs) are central regulators of cellular activity. Abnormal TF activity is often a root cause behind diseases, including cancer. However, TFs are largely considered ‘undruggable’ as they lack the deep binding pockets that traditional small molecule drug inhibitors recognize. Luckily, proteins structurally similar to DNA (‘DNA mimics’) exist in nature and bind DNA binding proteins. Because their properties are similar to DNA, I hypothesize that DNA mimics can be re-engineered to bind pathogenic TFs, thereby generating a novel approach to TF-DNA inhibition. Here, I established a general pipeline to engineer novel TF inhibitors using DNA mimic proteins. Computational models predicted how TFs can bind DNA mimic proteins based on their mode of DNA binding. Mutating DNA mimics generated libraries of variants to be screened with high-throughput bacterial screening systems developed to identify novel TF-DNA interaction inhibitors. Once established, this general pipeline could be applied to most TF-DNA interactions.

Advisor: Kim, Philip M
The Role of Teacher Mental Health Literacy in Identifying Emerging Mental Health Disorders in Students

The present study explored the relationship between teaching experience, mental health literacy and the ability of teachers to accurately rate the severity of behaviors presented through a vignette measure. Canadian certified primary grade teachers (N = 101) completed a survey with a novel vignette measure and a mental health literacy scale. Participants rated the severity of the behaviors depicted in the vignettes and their accuracy was calculated based on how closely their ratings matched the intended severity of symptoms depicted. A hierarchical regression model established that teaching experience alone was not significantly predictive of behavioral rating accuracy, but the inclusion of mental health literacy yielded a significant model. A binomial logistics regression indicated that neither the gender nor pathology depicted in the vignettes significantly influenced rating accuracy. These results substantiate the importance of teacher mental health literacy training in supporting the identification of emerging mental health disorders in students.

Keywords: Education
Mental Health
Psychology
Psychopathology
Teachers
Advisor: Cunningham, Todd
Rhonda, Martinussen
Reliability of RHS X-connections in Branch Axial Compression

Revisions were recently proposed, by Wei and Packer (2021), to how RHS sidewall instability is handled in AISC 360. This topic is updated with very recent research, and proposed revisions. An expanded database containing both experimental and numerical tests of RHS-to-RHS chord sidewall failure tests is amassed. An analysis of this data reinforces the recommendations by Wei and Packer (2021). A review is given of methods for determining the structural reliability of steel members and connections. A reliability study is performed on the Wei and Packer (2021) recommendations, using various closed-form reliability methods and Monte Carlo simulation, to determine resistance factors for use with the recommended nominal-strength design equations. The influence of live-to-dead load ratio, as well as material and geometric properties, on the structural reliability of full-width RHS-to-RHS X-connections under branch axial compression is studied. Test specimens are designed for an investigation of RHS-to-RHS X-connections under branch axial tension.

Advisor: Packer, Jeffrey A
Tousignant, Kyle
Operations Research Applications in Ontario's Healthcare System during the COVID-19 Pandemic

The COVID-19 pandemic challenged former norms in hospital operations and motivated innovative strategies for allocating healthcare resources. We present three strategies for mitigating stress on Ontario’s healthcare system. First, we consider inter-hospital patient transfers to address capacity concerns and uneven distribution of COVID-19 caseloads among hospitals. We formulate a queueing control problem and propose an approximate solution approach. With a case study of 21 hospitals we show that patient transfers significantly reduce the number of patient-days above occupancy thresholds, while distributing the COVID caseload. Second, we formulate an integer program to facilitate staff redeployment, and summarize some major challenges in redeployment efforts. Finally, we propose a virtual assessment centre for LTC residents. With data from seven hospitals we estimate staffing and diagnostic imaging resource requirements, and find that 1) aggregating call volume across multiple hospitals greatly reduces staffing requirements; 2) existing outpatient facilities could likely meet the diagnostic imaging requirements.

Keywords: Healthcare
Optimization
Queueing
Stochastic Models
Advisor: Chan, Timothy C. Y.
Managing Type 2 Diabetes During a Pandemic: An Investigation of Reddit Data

Type 2 Diabetes (T2D) is a chronic disease that can be managed through lifestyle. However, the COVID-19 pandemic impacted management of T2D. Our objective is to examine the impact of the pandemic on the health behaviours and attitudes of people living with T2D by examining Reddit forums. Support Vector Machines classifed a post as COVID-related and Latent Dirichlet Allocation topic modelling gathered topics of discussion. VADER Sentiment Analysis gauged attitudes. Amongst COVID-specific posts, topics of discussion were Coping with Poor Mental Health, Accessing Doctor Medications and Controlling Blood Sugar, Changing Food Habits during Pandemic, Impact of Stress of Blood Glucose Levels, Changing Status of Employment Insurance, and Risk of COVID Complications. Posts classified as COVID-related were associated with lower sentiment. Discussions pertaining to receiving support, stress and glycemic control, and mental health were associated with lower sentiment. Discussions pertaining to food habits were associated with higher sentiment.

Keywords: COVID-19
Natural Language Processing
Reddit
Sentiment Analysis
Topic Modelling
Type 2 Diabetes
Advisor: Cafazzo, Joseph A
Influence of Psychosocial Factors on The Experience of Pain Synaesthesia

Pain synaesthesia is a phenomenon in which one can personally feel the pain of another on their own body. This phenomenon has commonly been observed in populations who have experienced prior traumatic injury. However, the influence of psychosocial factors which commonly influence the experience of subjective pain have not been considered. The purpose of this study was to examine the influence of psychosocial factors on the experience of pain synaesthesia. Regression analyses revealed several aspects of empathy (e.g., emotional empathy) were predicative of pain perception ratings in response to painful images. In addition, factors know to increase hypervigilance towards pain cues contributed to the experience of pain synaesthesia in participants with a previous injury. The overall findings suggest empathy may play a central role in the experience of pain synaesthesia while psychosocial factors such as state anxiety and perceived social support might also contribute to the overall experience.

Keywords: Empathy
Pain
Perception
Psychosocial
Synaesthesia
Advisor: Martin, Loren J
Equitable Green Infrastructure for Climate Change Adaptation: Distributional and Procedural Justice in the City of Toronto

Green Infrastructure (GI) presents as a potential tool for climate change adaptation. This study seeks to answer the questions: where should GI be implemented to improve both distributional justice and climate change adaptation in the City of Toronto and how can GI plans be implemented to improve procedural justice. This study takes a mixed-methods approach, developing and applying a GI Equity Index, modelled after Heckert Rosan’s (2016) methodology, to answer question one and semi-structured interviews to answer question two. The results of this study highlight the inequitable distribution of GI in the City of Toronto and proposes prioritizing GI implementation in six neighbourhoods to improve distributional justice. Interviews with residents of the priority neighbourhoods revealed key considerations for future engagement such as distributional injustice and lack of access, desire for more GI and co- production of space, accounting for quality and maintenance in distributional justice, and an inequitable burden of adaptation.

Keywords: Adaptation
Climate Change Adaptation
Environmental Justice
Green Equity
Green Infrastructure
Toronto
Advisor: Conway, Tenley
The Effect of Bilingual Exposure on Language and Cognitive Recovery in Children following Stroke

Pediatric stroke often affects higher-level cognition and linguistic processes. Certain linguistic and cognitive advantages have been confirmed in behavioural studies of typically developing bilingual children. This research evaluates the effects of bilingual exposure on linguistic/cognitive recovery in children post-stroke. In Study 1, an interaction effect between language group and stroke-onset group revealed that bilinguals 1-12 months at stroke onset had better expressive language compared to monolinguals, based on the Pediatric Stroke Outcome Measure administered at several points post-stroke. In Study 2, a monolingual-bilingual pair of children aged 78 at stroke onset were compared using language/cognitive assessments in a case study. Results taking relative change over time in account showed similarities to Study 1, with the bilingual case having a more consistent recovery of expressive language. Overall, no negative effect of bilingualism on development after stroke was found; rather there may be an expressive linguistic advantage post-stroke outcome for bilingual patients.

Keywords: bilingual
children
cognition
language
pediatric stroke
recovery
Advisor: Molnar, Monika
Integrated Modelling of Statistical Process Control and Maintenance

Quality of products has been a major concern in various industries due to increasing competition. Maintenance of machines and production processes is a key factor in ensuring high quality of the products. In addition, control charts have long been utilized to monitor variation in the production process. In this thesis, we propose a Semi-Markov Decision Process (SMDP) model to integrate Statistical Process Control (SPC) and maintenance operations. The objective is to determine jointly optimal maintenance and process control policies that minimize the total long-run average costs comprised of maintenance and monitoring costs. We propose a policy iteration algorithm to find the optimal parameters. Finally, we illustrate the results and benefits of integrated SPC and maintenance using a numerical case study.

Keywords: Condition Based Maintenance
Semi-Markov Decision Process
Statistical Process Control
Advisor: Sarhangian, Vahid
Generating Constraints for Electromigration Safety for Chip Power Grids

This project is focused on generating constraints that the supply currents drawn by the underlying circuit blocks must satisfy in order to guarantee electromigration (EM) safety in the on-chip power grid. This safety is based on an accurate physical model of EM that comprehends atomic flux and material flow among connected metal lines. Normally, one takes user-provided currents as inputs and produces the stress in metal lines as output, and this forms the basis for EM checking and verification. In contrast, we are here solving what may be called the inverse problem: given a grid and a safety threshold for stress in the metal lines, we want to produce constraints on the circuit supply currents that guarantee EM safety. These constraints, taken altogether, provide a description of the space of safe currents, which we call the safety set.

Keywords: Chip
Constraints
Electromigration
Power Grid
Safety
Advisor: Najm, Farid
Qualitative Study Examining the Role of Stigma in the Help-seeking Behaviours of South Asian Youth Accessing Psychotherapy in Ontario

South Asian (SA) youth face many mental health challenges yet access psychotherapy less often than other ethnic groups and this may be, in part, due to stigma. The aim of this qualitative descriptive study (N=10) was to understand SA youth’s experiences with stigma when accessing psychotherapy using semi-structured interviews. This level of understanding is sought to learn how the barrier of stigma was overcome. The Cultural Help-seeking Model served as a theoretical framework informing the author’s understanding of the role of stigma within the help-seeking process of SA youth. Six major themes were identified in the data: 1) influence of SA culture; 2) others as barriers to accessing psychotherapy; 3) others as facilitators to accessing psychotherapy; 4) personal attitudes; 5) context of mental health care; and 6) strategies for reducing stigma. The results of this study are used to propose recommendations for social work researchers, educators, practitioners, and policymakers.

Keywords: Help-Seeking
Psychotherapy
South Asian
Stigma
Youth
Advisor: Ashcroft, Rachelle
First-order Fast Algorithms for Structurally Optimal Large-scale Multi-Group Multicast Beamforming

This thesis considers multi-group multicast beamforming design in large-scale systems, where two typical problems, the quality-of-service (QoS) problem and the max-min fair (MMF) problem, are studied. Based on the optimal multicast beamforming structure obtained recently, we propose two fast first-order algorithms to obtain the beamforming solutionsfor the QoS problem. The two algorithms both utilize the successive convex approximation (SCA) method, and they solve each SCA subproblem by the extragradient method and the alternating direction method of multipliers (ADMM), respectively. Initialization methods for SCA are also developed, including an extragradient-based approach, an ADMM-based approach, and semi-definite relaxation. Next, we propose solving the MMF problem via a simple closed-form scaling scheme, whose feasibility and bounded performance are guaranteed from the theoretical analysis. Our extensive experimental results show clear evidence of the effectiveness of our proposed methods.

Keywords: Alternating direction method of multipliers
Computational complexity
Extragradient algorithm
Multicast beamforming
Optimal structure
Successive convex approximation
Advisor: Liang, Ben
Dong, Min