VictorJuiz/thesis huggingface dataset:
Analyzing Organizational Processes in Machine Learning Projects: Exploring Modeling Approaches
Keywords: Conceptual modeling
Data Science
Machine Learning
Organizational processes

As Machine Learning (ML) continues its emergence across numerous industries, software teams and organizations face new challenges beyond those found in conventional software projects. While many of these challenges are technical in nature, many organizational issues could jeopardize project success. In this work, we explore conceptual modeling techniques for deepening understanding of organizational problems in ML projects. We studied practices in an empirical case study of three ML software project organizations. We applied i* modeling to uncover and analyze several types of organizational issues and how they have been addressed in practice. This thesis aims to identify how conceptual modeling techniques can be refined and improved to better support ML project organizations and to advance ML maturity.
Northern Ontario Air Transportation and Remote Community Resilience and Wellbeing
Keywords: Air Transportation
Northern Ontario
Remote Communities
Resilience

This thesis explores the role air transportation plays in northern Ontario remote community wellbeing and resilience using mixed methods based on a modified resilience framework. Six years of cargo data and flight operations data from one airline in the region are analyzed to first, map how remote communities and their infrastructure systems are dependent on air transportation, and second, to analyze air transportation performance. Air transportation is the only mode of year-round travel in 31 northern Ontario communities and therefore plays an essential role in connecting communities to essential goods and services (e.g. food, healthcare). In terms of infrastructure interdependencies, the main cargo delivered by air is diesel fuel for energy, with a secondary good being construction materials. Performance-wise, air transportation faces both infrastructure challenges (e.g. lack of weather reporting, inadequate de-icing services) and operating challenges (e.g. poor weather) that are exacerbated by climate change effects.
I Hate it Here: A Critical-creative inquiry into Notions of Freedom, Safety, and Privilege
Keywords: Black global Diaspora
Black Studies
Freedom
Liberalism
Privilege
Safety

My research examines how Black critical thinkers theorize notions of freedom, safety and privilege. The research asks, how do Black radical understandings of these concepts overlap with, contradict, and challenge the ways in which freedom, safety and privilege are operationalized in liberal discourses? What are the implications and potentialities of Black radical notions of freedom, safety, and privilege for Black life in good relation with Indigenous Peoples? Building on Lisa William-White’s (2011) work of expanding the potentials of qualitative research methodology through evocative performance narratives that are created from journal entries, document analysis, music, poetics, spoken word performance, and sociological introspection; I situate Black critical-creative praxis as one that challenges whiteness, liberal multiculturalism, settler colonialism, patriarchy, transatlantic slavery, racial capitalism and high-education investment in perpetuating imperialism. I comment on “academic freedom”, “safe space”, and the “privilege” of entering the academy through an engagement with poetics, as I grapple with belonging, unbelonging, love, music, and aesthetics.
Elucidating Memory Specificity by Exploring Parvalbumin Interneuron Modulation of Perineuronal Nets
Keywords: Hippocampus
Interneuron
Memory
Parvalbumin
Perineuronal Nets
Specificity

Infantile generalization, a unique type of generalization seen during early development, has not been widely studied in the ontogeny of memory. However, understanding this phenomenon is important for elucidating the mechanisms underlying the emergence of memory specificity. Preliminary studies form our lab have identified the ability of hippocampal perineuronal nets (PNNs) to bidirectionally modulate memory specificity. Other recent studies have determined that parvalbumin (PV) interneuron activity could modulate PNN assemblies in the visual cortex. Taken together, we predicted that PNN formations could be bidirectionally modulated by hippocampal CA1 PV interneuron activity, and in turn affect the emergence of memory specificity. Instead, only chemogenetic excitation of PV interneurons increased PNN intensities, while PV inhibition had no affect on PNN assemblies. It remains inconclusive whether these molecular changes impact the emergence of memory specificity, as only memory specificity was exhibited from both PV manipulations.
Awe and Perspective taking
Keywords: Awe
Emotion
Perspective taking

Understanding another’s perspective is an essential component of a healthy social interaction. However, the motivation to empathize with others can often be low. My thesis investigated whether the emotion of awe may motivate perspective taking. I found that dispositional awe was positively correlated with multiple trait measures of perspective taking. However across a variety of analyses inducing awe did not consistently promote greater accuracy and reduce reaction time in a visual perspective taking task compared to neutral and amusement control conditions. I found evidence that awe improved overall cognitive flexibility, but it is not clear that this flexibility is specific to taking another’s visual perspective. These results suggest that awe may be related to dispositional perspective taking or perspective taking at a higher social cognitive level, but it does not affect other-focused visual attention or perspective taking.
Effectiveness of Software-enhanced CBCT-image Artifact Reduction Software
Keywords: Artifact Reduction
Artifacts
Beam Hardening
CBCT
Cone Beam CT
root fillings

Objectives: The purpose of this study is to quantify the degree of BH artifact production and evaluate the effectiveness of AR software in two CBCT systems. Materials and Methods: Palatal roots of Dent-Alike™ model teeth were prepared, root-filled and imaged with or without AR software applied using the ProMax3D and the Pax-i3D systems. “Light” and “Dark” components of the BH artifact were quantified two-dimensionally and, three-dimensionally. Results: Significant reductions observed in the “light” artifact with the Planmeca system (p
Innovation in Workplace Learning: Perceptions of the Value of Game-based Learning among Training and Development Professionals
Keywords: Game-Based Learning
Learning Innovation
Training and Development
Workplace Learning

Games are a fundamental part of the fabric of human existence. Their utility extend beyond the sole purpose of entertainment and transcends to the realm of games for learning. The impetus of this study was to examine the perceptions of game-based learning (GBL) through the lens of training and development professionals in Canada. Employing a mixed-method approach, a survey questionnaire was used to explore experience using GBL, intention to use GBL and barriers to adoption. A descriptive analysis of frequencies was performed on the quantitative data and content analysis for the open-ended qualitative survey responses. Based on the results of 172 respondents, only 43.6 percent were using GBL. Majority of respondents lacked GBL knowledge and experienced low self-efficacy for GBL design and application. This was exacerbated by social, organizational and systems-wide barriers. Increased GBL knowledge and support from leadership and peers were among the factors to mitigate GBL adoption barriers.
Control, Planning, and Learning for Multi-UAV Cooperative Hunting
Keywords: control
motion planning
multi-agent systems
reinforcement learning
unmanned aerial vehicles

This thesis presents a model predictive control (MPC) algorithm for solving the cooperative hunting problem with multiple unmanned aerial vehicles (UAVs) in obstacle rich and moving obstacle environments and builds upon the MPC algorithm using a reinforcement learning method called Guided Policy Search (GPS). The cooperative hunting problem deals with surrounding a target while navigating around obstacles and avoiding collisions, and the MPC algorithm combines the cooperative hunting objective with planning and obstacle avoidance. Simulation results show that the MPC algorithm successfully surrounds the target in both scenarios. Local minima are avoided for obstacle rich environments and the obstacle interaction is minimized in moving obstacle environments. Furthermore, the MPC algorithm was validated with physical quadrotors. Finally, the GPS algorithm improves upon the MPC solutions by reducing the trajectory length and capture time, and then uses the improved trajectories to train a global neural network policy.
A General Method for Analyzing Visual Scanning Behaviour in Neuropsychiatric Disorders
Keywords: eye-gaze tracking
machine learning
objective diagnosis
selective attention
visual saliency
visual scanning bias

The growing availability of eye-gaze tracking technology has allowed for its employment in a wide variety of applications, one of which is the objective diagnosis and monitoring of neuropsychiatric disorders from biases in visual scanning behaviour (VSB). Current techniques in this field are largely comprised of non-generalizable methodologies that rely on domain expertise and study-specific assumptions. This thesis presents a general, data-driven, end-to-end method that extracts relevant features of attention from biases in VSB and uses these features to classify between subject groups with standard machine learning techniques. The general method is compared to methods developed by domain experts to evaluate attentional biases in two psychiatry studies: eating disorders and depression. The results show that the general method can perform just as well as expert-defined techniques, demonstrating its utility as a standard baseline method for analyzing visual scanning data in neuropsychiatric disorders.
Developing a Patient-reported Outcome Measure for Retinoblastoma
Keywords: Patient Centered Care
Patient-Report Outcome Measures
Pediatric Oncology
Pediatric Ophthalmology
Qualitative Research
Retinoblastoma

Background: Patient-reported outcome measures (PROMs) are self-report instruments measuring health outcomes from the patient perspective. A retinoblastoma PROM could provide important insight into patient outcomes. Objectives: Characterize PROMs currently used in retinoblastoma, pediatric ophthalmology, and pediatric oncology; explore retinoblastoma survivor and parent views on treatment outcomes. Methods: A scoping review identified and analyzed relevant PROMs. Results informed a qualitative study to determine parent and survivor opinions on treatment outcomes. Results: One retinoblastoma-specific, 56 pediatric ophthalmology, and 86 pediatric oncology PROMs were identified and considered for their application to retinoblastoma. Seventeen retinoblastoma survivors and 9 parents, participated in discussions. A need for a PROM measuring psychosocial impact, daily functioning, cosmetic outcomes, and retinoblastoma education was identified. Conclusion: Existing PROMs can be modified for application to retinoblastoma, there are also additional retinoblastoma-specific domains to consider. Next steps include dissemination of results to experts and patients in research to plan further development.
Impact of Teacher Leadership on Teacher Self-efficacy
Keywords: challenges
collaboration
qualitative research
teacher leadership
teacher leadership impact
teacher self-efficacy

Being a teacher leader involves teachers understanding and believing in their ability to influence and lead change, which requires teachers to be self-efficacious. Teacher self-efficacy is an important catalyst for the development of students and schools. This paper explored the connection between teacher leadership and teacher self-efficacy, to highlight the importance of developing teacher leadership to improve the education system. I used previously conducted research and one-on-one interviews with teachers to gather data. An analysis of the interviews indicated that teacher leadership supports teachers beyond the classroom, nurtures collaboration and according to the participants it has the capacity to build teacher self-efficacy. It can also be concluded that both concepts bolster each other and collectively impact teacher practice and thus student achievement. Although there are limitations to this study, it forms the basis for understanding teacher leadership and how it supports teachers’ beliefs of their own practice.
Improving Interprofessional Bedside Rounds in a Paediatric Critical Care Unit
Keywords: human factors
intensive care
interprofessional collaboration
interprofessional rounds
user-centered design

In critical care, communication is essential to patient safety. Patient care rounds are integral to communication and collaboration among interprofessional healthcare providers (HCPs). However, little research has explicitly aligned rounding interventions to HCP needs, which neglects the principle of tailoring interventions to local needs. This study aimed to elucidate HCPs rounding needs, to transform them into interventions within a paediatric critical care unit. First, needs were elucidated from interviews and surveys. Second, interventions were co-designed with HCPs using participatory design. Results uncovered collective and profession-specific needs and associated interventions were identified. To minimize undesirable variability from insufficient clarity on content that should be discussed, HCPs reached consensus regarding the main reasons for rounds. Aligned with these reasons, a rounding structured was created to collaboratively synthesize patient’s problem and develop corresponding care plans. Findings outline how a user-centred design approach can be adapted by institutions to tailor interventions to local needs.
Estimating Uncertainty in Neural Networks for Cardiac MRI Segmentation
Keywords: Bayesian neural networks
cardiac MRI segmentation
segmentation quality control
uncertainty

Convolutional neural networks have shown promising results in automated cardiac MRI segmentation. In this thesis, we performed a systematic study of Bayesian and non-Bayesian methods for estimating uncertainty in these segmentation neural networks. Specifically, we evaluated Bayes by Backprop (BBB), Monte Carlo (MC) Dropout, and Deep Ensembles in terms of segmentation accuracy, probability calibration, uncertainty on out-of-distribution images, and application for segmentation quality control. We found that Deep Ensembles outperformed other methods in most cases. In addition, we identified a limitation of current methods which have low predictive uncertainty on images with heavy distortions. For the problem of segmentation quality control, we showed that the average symmetric surface distance (ASSD) segmentation accuracy metric correlates well with the ASSDWithinSamples uncertainty measure. Uncertainty measures can be used to flag potentially inaccurate segmentation and reduce the number of images that need to be reviewed.
Three-dimensional Shape of Facial Attractiveness in Patients with Sagittal Skeletal Discrepancy
Keywords: Attractiveness
Facial Esthetic
Geometric Morphometrics
Sexual Dimorphism
Skeletal Malocclusion
Three-Dimensional

Many patients with sagittal skeletal discrepancy (SSD) express dissatisfaction with their facial esthetics. Studies have shown that males and females possess distinct recognizable facial features that need to be considered when addressing these concerns. We sought to identify the 3D morphological shape correlates of facial attractiveness (FATT) and sexual dimorphism (SD) using CBCT scans of subjects with SSD. Forty anonymized CBCT images of adult subjects with varying severity of SSD were evaluated for FATT and masculinity/femininity (M/F) by 100 laypeople using Visual Analog Scales (VAS). Using Geometric Morphometric (GM) analysis, we found that more anterior and inferior shape displacement of the chin was significantly associated with increases in FATT (R2=0.46, b=0,0015, P= 0.049). Prominent cheeks and posterior displacement of the tip of the nose were associated with a more feminine facial appearance (R2=0.62, b=0.0013, P=0.192). Our results provide guidance in the treatment planning of subjects with SSD, taking sex into consideration.
Uncertainty Measurement as a Sensor Performance Metric in Adverse Conditions
Keywords: Adverse
Conditions
Detection
Object
Uncertainty

In autonomous driving, object detection remains an ongoing challenge, as solutions must be reliable and safe to use on the road. Current state-of-the-art solutions provide point estimate predictions, which may be inadequate, as reports of deaths due to autonomous vehicle collisions continue to appear. To increase the safety of these algorithms, uncertainty estimation can be incorporated into traditional object detection pipelines to produce a measure of uncertainty alongside traditional point estimate object predictions. To evaluate uncertainty as a performance metric, signal detection theory is leveraged to generate an uncertainty based classifier. The classifier can be used to track the ratio of false positive to true positive detections, defined as the anomalous detections ratio. Findings from this work indicate that the novel metric is responsive to degraded driving conditions including night time driving and lens obstructions for the RGB camera, while the LiDAR is responsive to snowfall and simulated rain conditions.
Work-life Balance among Female Dentists In Canada
Keywords: Dentistry
Female Dentists
Work-life Balance

Work-life balance is increasingly gaining attention as a possible predictive factor in emotional exhaustion and burnout among professionals. While there are studies that point to challenges to work-life balance among female dentists in the United States, there is no study that looks into these issues in Canada, nor has the specific nature of these issues among female dentists been documented anywhere. The first part of our study consisted of secondary statistical analysis of previously collected survey data from a random sample of 3000 dentists practicing in Ontario in 2012 showing significant gender differences, such that female dentists appear to face more obstacles to a well-balanced work and life. In the second part, a qualitative study into what and how female dentists encounter challenges to work-life balance showed nature of the profession of dentistry, dental practice structure, personal life factors, and personal attributes to be contributing factors to such challenges.
Effect of Skin Tone on the Confidence of WearOS Smartwatches
Keywords: Data analytics
Health monitoring
Heart rate
PPG
Smartwatch

Smartwatch technology has the potential to make monitoring chronically ill people continuously without hampering their daily life easier. Physiological information e.g. heart rate can be collected and monitored remotely by smartwatches which can be useful in long term studies, monitoring chronic conditions, timely intervention. However, before we can use the smartwatch data for an error-sensitive clinical setting, we need to be sure about the reliability of the data, both in terms of quality and quantity. In this work, we investigate the effect of skin tone on the heart-rate reliability estimation of seven consumer-grade WearOS based smartwatches by collecting data from 18 individuals. We find that watches tend to report fewer high-confidence measurements for dark skin tones, despite no substantial difference in the actual error of heart rate reading. We also report a wide variation in the behavior of those watches even though they implement the same API for data collection.
Supporting Students’ Well-being through Student Voice Initiatives: An Exploration of Well-being Teams in Ontario Secondary Schools
Keywords: education policy
mental health
student leadership
student voice
well-being

As mental health concerns among youth persist, there is a growing need for schools to better support students’ well-being and to also involve students in these efforts. Using a qualitative research design, this study explores student-led well-being teams across secondary schools in Ontario, Canada. Interviews were conducted with four students involved in their school’s well-being team in order to better understand their perceptions of their roles and experiences on these teams. This study’s conceptual framework was informed by the literature related to student voice and its connection to well-being. Using interpretative phenomenological analysis (IPA), three superordinate themes were identified in this study: Independent/Dependent Nature of Roles, Integral to and Integrated in School Community, and Experiencing Growth. Overall, students described aspects of both positive and negative well-being as a result of their experiences, which demonstrates the importance of establishing certain conditions that allow for student voice and well-being to thrive.
Adhesion of Bio-inspired Micropillar Arrays
Keywords: Adhesion
Bio-Inspired
Fibrillar
Micropillar

Bio-inspired micropillar arrays have found broad applications in everything from human skin adhesion to robotic gripping. However, their adhesion remains too low for many practical engineering uses. To improve upon their adhesion, their detachment dynamics are investigated both on a single contact level and on an array level with in situ observation. Adhesion experiments revealed a strong dependence on preload force and a size-scale effect where smaller samples had higher normalized adhesion. The introduction of mechanical divisions within a single sample led to a more random detachment and produced adhesion that was up to 25% greater. Experiments on single roughness features resulted in a significant drop in adhesion which is attributed to an uneven preload force distribution, leading to adhesive contributions from only a fraction of the sample. These fundamental understandings of micropillar adhesion dynamics can help enable the next generation of bio-inspired adhesives and guide micropillar array design.
Evaluation of Energy Efficiency Measures in High-rise Buildings from a Life Cycle Greenhouse Gas Emissions Perspective
Keywords: Building Envelope
Energy Efficiency Measures
Greenhouse Gas Emissions
Life Cycle Assessment

Due to its significant contribution to greenhouse gas (GHG) emissions, the building industry is taking action to fight climate change, developing measures for reducing the operational emissions of buildings. However, some of these well-intentioned measures can result in higher embodied emissions. Under certain conditions, this increase in embodied emissions can more than offset the reductions achieved during the building operational phase. This thesis evaluates the effectiveness of five passive energy efficiency measures to reduce GHG emissions from a life cycle perspective for high-rise residential buildings in Toronto, Canada. Decreasing the window-to-wall ratio was found to be the most effective measure to reduce total GHG emissions. Increasing the continuous insulation on walls and roofs with GHG intensive materials can increase total emissions. The thesis also compares the embodied GHG emissions of curtain walls and window walls finding no practical difference in embodied GHG emissions between the options studied.