VictorJuiz/thesis huggingface dataset:
Curriculum Governance in the Professions: A Comparative and Sociological Analysis of Engineering Accreditation
Keywords: accreditation
curriculum
engineering
governance
professions

Professional education operates in a tension between its two key institutional homes – universities and professional bodies. Curriculum governance – the structures and processes for making decisions about the curriculum – is embedded in higher education but influenced by professional accreditation. This multiple paper thesis explores the implications of a worldwide shift in engineering towards outcomes-based accreditation. The study is framed by a comparative case study methodology, and empirical data is drawn from 78 interviews across the United Kingdom, Australia, Singapore, and South Africa. All four countries are signatory to the Washington Accord, a mutual recognition agreement that has been influential in helping to spread outcomes-based accreditation.This study is theoretically grounded in Bernstein’s pedagogic device, from the sociology of education, and regime theory, from international relations. At a global level, the key findings are that the Washington Accord has evolved into an explicit regime that shapes the behaviour of its 20+ signatories, as well as countries thinking about applying. From a power perspective, the regime disproportionately benefits its founding members, while newer signatories are scrutinized before being admitted. From a cognitivist perspective, the regime is under threat from a subtle shift in its purpose, from mobility to quality assurance. Drawing on the pedagogic device, the thesis finds meaningful differences across countries in the structure of the ‘recontextualizing field’ – comprised of the official field which sets accreditation policy, and the pedagogic field which interprets and implements the policy. Four archetypes, based on the four countries, are shown to explain some of the differences in uptake of outcomes-based accreditation. Within the ‘field of reproduction’, curriculum governance structures are shown to differ according to the type of university. Research-intensive universities are less invested in accreditation, more decentralized, and centrally control the curriculum less. Teaching-intensive universities depend on accreditation for legitimacy and invest more in a centralized approach to curriculum governance. Overall, this study highlights the importance of power differences between old and new signatories, between research-intensive and teaching-intensive universities, and between central faculties and their departments. These tensions represent an important area of research within professional education at large.
Accelerating the Discovery of Materials for Energy Capture and Energy Storage Using Quantum Chemistry and Machine Learning
Keywords: density functional theory
electrocatalysis
light emission
machine learning
photovoltaics
quantum chemistry

In order to reduce the global dependence on fossil fuels it is critical that we develop new materials to efficiently capture and store energy. The enormous size of the material space poses a formidable challenge to the discovery of energy materials. In this thesis, I develop machine learning (ML) approaches and search algorithms that enable accelerated discovery of energy materials. First, I develop a material representation that enables relaxed crystal properties prediction from unrelaxed crystal structures using ML. The results show that the approach accelerates the discovery of mixed halide perovskites by a factor of 105 over conventional computational screening approaches based on Density Functional Theory (DFT). I apply the method to two material discovery problems: the search for photovoltaic materials with small bandgaps; and UV and IR light-emitting materials. Next, I generalize the above-mentioned approach to tackle one of the main criticisms of ML-based approaches: their black-box nature i.e., lack of interpretability. I do this by training accurate ML models that can predict energy above hull, bandgaps, and the nature of bandgaps among different material classes using unrelaxed crystal structures. With the combination of statistical techniques and simpler supervised learning methods, I develop a method to extract scientific insights from trained ML models and use these generated insights to design new, stable UV light emitting materials and direct bandgap semiconductors. Finally, I develop a method to efficiently search the chemical space. The proposed search method efficiently identifies the material with the desirable set of properties an order of magnitude faster than genetic algorithms and bayesian optimizations. Applying this to the discovery of oxygen evolution reaction (OER) catalysts, I predict several previously unreported promising candidates that are then validated in the lab. The best candidate Ru0.58Cr0.25Mn0.08Sb0.07O2 shows a mass activity 8 times higher than the current state-of-art, RuO2, and maintains performance for 180 hours while operating at 10mA/cm2 in acidic 0.5M H2SO4 electrolyte. The studies in this thesis introduce and demonstrate the application of data-driven approaches to accelerate the discovery of energy materials through the development of generalizable ML models, interpretability analysis and efficient search algorithms.
Tethered Magnetic Serial Robots for Minimally Invasive Neurosurgery
Keywords: Magnetic actuation
Minimally invasive surgery (MIS)
Robot surgery

The high-speed, non-ionizing, wireless power transfer capabilities of low-frequency magnetic fields make them an attractive option for actuating devices on the nanometer scale up to the centimeter scale, enabling a new suite of minimally-invasive techniques for a wide variety of medical procedures. There is a significant demand for smaller, more manoeuvrable, surgical robot tools to reduce the invasiveness of neurosurgical procedures. A magnetic approach to surgical robots could enable smaller tools, but no viable magnetic robot approach exists. Existing magnetic approaches to surgical tasks involve either untethered agents, serial arms with bulky surface-mount transmission units, or highly-underactuated continuum bodies. Surgical tasks, especially in delicate regions such as the brain, require precisely controlled trajectories and applied forces: they require fully-actuated robots.In this thesis, rigid-link serial robots with embedded magnets in each link are designed to achieve high forces and ensure full actuation over their configuration space. A novel analytical model was derived from a combination of magnetostatics and rigid-link serial robot dynamics to determine the equivalent actuator torques at the joints of the serial robot for a given actuating field, as well as the effective torsion-spring-like behaviour induced by interactions between the magnets in the serial robot. From this analytical model, a performance metric and novel design methodology was developed to improve the actuation performance and tailor the magnetic torsion-spring behaviour in the robot by adjusting the orientation and position of the embedded magnetic material. Several 3 mm - 4 mm diameter rigid-link robot prototypes were developed using this methodology, and their performance was evaluated according to key design criteria for microneurosurgical tasks. The tools can be operated open loop or closed loop with computer vision feedback, achieving step response rise times of less than 1 second and maximum output forces of up to 181 mN. By enabling smaller tools without a need for transmission components, more space is left in the trocar (surgical insertion point) for other systems, such as lighting, irrigation, or integrated sensing. Magnetic serial robots could thus enable a new class of multifunctional surgical tools.
Life and Love Under Criminalization: The Experiences of People Living with HIV in Canada
Keywords: HIV Criminalization
People Living with HIV
Racialized People Living with HIV
Romantic Relationships
Sexual Relationships
Women Living with HIV

Through in-depth qualitative interviews with 75 people living with HIV (PLWH), this dissertation examines the impact of HIV criminalization upon the lives of PLWH in Ontario, Canada, particularly in terms of HIV stigma, sexual and romantic relationships, and community, as well as the unique challenges the law creates for marginalized groups, specifically women living with HIV (WLWH) and racialized people living with HIV (RPLWH). The first paper of this dissertation examines how HIV criminalization impacts the lives of WLWH and the HIV stigma they experience. Key themes that emerge from the accounts of women in the study include how the law facilitates social exploitation, the impact of the law upon sexual and romantic relationships, and their treatment by the criminal justice system. The women in the study experience criminalization through the lens of motherhood – regardless of whether they have children. The second paper of this dissertation focuses on the experiences of Indigenous, Black, and other racialized people living with HIV who participated in the study, as they navigate disclosure, relationships, and life under HIV criminalization. RPLWH in the study report the experience of high amounts of HIV stigma in their communities. RPLWH employ various strategies to navigate the law and the high levels of perceived community stigma. These include keeping their HIV status hidden, having firm boundaries between and within communities, abstaining from relationships, leaving the country to have sex, avoiding HIV networks, and self-non-disclosure. Drawing upon the full sample, the third paper of this dissertation examines the impact of HIV criminalization upon the sexual and romantic relationships of PLWH, as well as the strategies they employ to navigate and protect themselves from the law. Key themes include concern with the law’s impact on dating desires and practices, the power imbalance that the law enables with serodiscordant partners, the privacy implications of being investigated or charged, as well as their potential treatment by both police and media. PLWH use various navigation strategies to protect themselves from the law including staying in relationships, celibacy, serosorting, anonymous and casual sex, leaving the jurisdiction, universal disclosure, non-disclosure, and disclosure documentation.
Dielectric Properties of Minerals and Ores and the Application of Microwaves for Assisted Comminution and Ore Sorting
Keywords: comminution
liberation
microwaves
minerals
permittivities
sorting

Upon exposure to microwave radiation, most valuable minerals heat very well, while in general, gangue minerals do not. This selective heating leads to differential thermal expansion across phase boundaries and causes microfractures, which can improve liberation and reduce ore competency. During ore sorting, the heat signature is detected using infrared sensors to accept or reject valuable or gangue rock, respectively. A comprehensive literature review identified research gaps in the field of microwave-assisted comminution and ore sorting and found that developments have been limited by complexities associated with scaling up from bench- to pilot-scale. Dielectric properties were measured on key sulphide and silicate minerals and select ores at various frequencies and temperatures using the cavity perturbation technique. In combination with data from the literature, experimental data were used to ascertain which minerals could be defined as highly microwave-amenable phases (HMAPs). Bench-scale microwave heating experiments were completed on 42 ores. These data were then combined with the total wt.% HMAPs and the ore dielectric property data to create a database that can be used to predict the bench-scale heating behaviour of any ore based on the wt.% HMAPs. High-power microwave tests were done on select ores, which were subsequently ground using the SAGDesign test, and the degree of liberation of valuable minerals was obtained via QEMSCAN® (quantitative evaluation of minerals by scanning electron microscopy). Microwave treatment increased mineral liberation from most ores but reduced the competency of only a few ores. Massive sulphide ores could not be treated on the pilot-scale system given their very high conductivities, which caused severe arcing. A study on a Cu porphyry ore found that an upper boundary exists for the power density, above which the ore will experience excessive arcing. Bench-scale microwave infrared and conductivity sorting tests on a Cu-Ni ore found general agreement between rock conductivity and its overall sortability. Optimization tests were completed to determine the limitations of the pilot-scale system. Recommendations for high-power microwave treatment include microwave pulsing, quenching, and treatment of iron ores.
¡Saca Mi Foto!: The Visual Cultures of Undocumented Migration
Keywords: Borderlands
Latinx History
Photography
Surveillance
Undocumented Migration
Visual Culture

This interdisciplinary study traces the emergence of two competing visual cultures of undocumented migration in the U.S. borderlands between the 1950s and the 1990s. One was a nativist visual culture crafted by the Immigration and Naturalization Service (INS) and its backers in the wake of the bracero program. Photographers affiliated with the agency, popular magazines, and the news media objectified Latin American migrants and depicted the border as vulnerable territory that required constant surveillance but would never be completely controlled. In doing so, they fortified xenophobic law and practice by framing sovereignty as a visual project that depended on rigorous oversight and the regulation of racialized migrants. Through this visual regime, the state cemented the ontological divide between citizens and “illegals” and helped forge the stereotype of the Latinx “alien”: a criminal trespasser who posed a persistent, insidious threat to the nation. In response, an eclectic cohort of artists, photojournalists, and documentary photographers based in Arizona, California, Florida, and Texas generated a critical, humanitarian visuality attuned to migrants’ subjectivities and lived realities. They collaborated with activists, new labor unions, and outlets from the radical and mainstream press. In the 1970s and 1980s, their work critiqued the militarization of the border, displayed the intimate bonds and rich culture that sustained transnational communities, condemned the exploitation that Latinx workers experienced under U.S. capitalism, and propelled movements for the rights of the undocumented. To access the perspectives of photographers, migrants, and spectators, I draw on evidence from memoirs, photo-essays, newspapers, oral history interviews, archival documents, private collections, and gallery exhibits. In doing so, I demonstrate that photographers played a pivotal role in creating—and reimagining—the modern image of “illegality.” In the hands of the state and its boosters, the camera was a disciplinary technology that fueled xenophobia and naturalized surveillance. But for migrants and their advocates, it was a tool of resistance that questioned nativist tropes and promoted solidarity with Latinx communities.
Building a Scalable Sensing Foundation for Contextual and Precise Interaction
Keywords: Human Computer Interaction
Scalable Sensing
Ubiquitous Computing

A majority of our interactions with computing devices are localized to surfaces that are physically on the device or in their vicinity. However, emerging modes of computational interaction such as mixed reality and voice based intelligent agents demonstrate a pressing need for the ability to interact on any surface, at any time, pervasively and reliably. Traditional sensor deployments, instrumentation of the user and the environment begin to address this problem. However, doing this at scale presents multiple challenges in the form of prohibitive cost of deployment, reliability and obtrusiveness. This goal of interacting with arbitrary surfaces easily and unobtrusively has been elusive.In this dissertation, we make the case for pervasive sensing that relies on passive or no instrumentation of the environment. We demonstrate two different technologies with ID’em detailing a centimeter scale localization through the embedding of tags into materials and pressAR showcasing the ability to sense finger presses and touch precisely using off the shelf camera systems. We believe that this highly scalable approach to sensing empowers designers, engineers, and researchers to deploy rich, ubiquitous interactions at a large scale.
Algorithms for Data-driven Geometric Stylization Acceleration
Keywords: Computer Graphics
Geometry Processing
Machine Learning

In this thesis, we investigate computer algorithms for creating stylized 3D digital content and numerical tools for processing high-resolution geometric data.This thesis first addresses the problem of geometric stylization. Existing 3D content creation tools lack support for creating stylized 3D assets. They often require years of professional training and are tedious for creating complex geometries. One goal of this thesis is to address such a difficulty by presenting a novel suite of easy-to-use stylization algorithms. This involves a differentiable rendering technique to generalize image filters to filter 3D objects and a machine learning approach to renovate classic modeling operations. In addition, we address the problem by proposing an optimization framework for stylizing 3D shapes. We demonstrate how these new modeling tools can lower the difficulties of stylizing 3D geometric objects. The second part of the thesis focuses on scalability. Most geometric algorithms suffer from expensive computation costs when scaling up to high-resolution meshes. The computation bottleneck of these algorithms often lies in fundamental numerical operations, such as solving systems of linear equations. In this thesis, we present two directions to overcome such challenges. We first show that it is possible to coarsen a geometry and enjoy the efficiency of working on coarsened representation without sacrificing the quality of solutions. This is achieved by simplifying a mesh while preserving its spectral properties, such as eigenvalues and eigenvectors of a differential operator. Instead of coarsening the domain, we also present a scalable geometric multigrid solver for curved surfaces. We show that this can serve as a drop-in replacement of existing linear solvers to accelerate several geometric applications, such as shape deformation and physics simulation. The resulting algorithms in this thesis can be used to develop data-driven 3D stylization tools for inexperienced users and for scaling up existing geometry processing pipelines.
A Solution to the Multimodal Binding Problem
Keywords: Isomorphism
Multi-echo fMRI
Multimodal binding problem
Perceptually uniform space
Representation
Working memory

Known as the multimodal binding problem, a long-standing question in the cognitive sciences has asked how the mind forms complex object representations from basic sensory features. Integrating features into object representations is fundamental to human experience, yet there remains little theoretical consensus towards how the mind accomplishes this remarkable ability. In Chapter 1, I first describe how existing theoretical perspectives differ in their levels of analysis in terms of how feature integration is understood, focusing on the working memory literature. I then provide a link between seemingly contradictory perspectives, interpreting memory performance in terms of mental representations. In Chapter 2, I show how shape representations can be quantified through similarity judgments, constructing the first perceptually uniform shape space comparable to the ‘color wheel’. In Chapter 3, I combine perceptually uniform shape and color space together, creating a novel simultaneous reproduction task to quantify visual object representations along a continuous metric. Critically, objects in working memory were represented hierarchically as both independent and integrated features, providing evidence for one solution towards how the mind constructs objects from their basic features. In Chapter 4, I directly ask how the brain solves the binding problem, recording brain activity using multi-echo functional neuroimaging as participants experienced 3-dimensional multimodal objects. Using a novel 4-day learning task, I found that the brain constructs multimodal object representations through a hierarchical architecture: experience-dependent integrative coding in the anterior temporal lobes distinct from individual features coded across distributed sensory regions. In Chapter 5, I conclude with future research directions, including how these findings may relate to the design of more human-like artificial neural networks that aim to learn multimodal object concepts. These results provide one solution to the multimodal binding problem, revealing that a hierarchical neural architecture supports the representation of multimodal objects in working memory. Furthermore, I introduce several new tools to quantify object representations, revealing that how we understand feature integration is fundamentally intertwined with the level of analysis by which we measure and interpret human behaviour in the first place.
Public-Private Partnership Schools in Punjab: Is there a Learning Premium that can be Explained by Management Practices?
Keywords: Education
Management
Pakistan
Privatization
Public-Private Partnerships
Vouchers

The rapid rise of low-cost private schools (LCPS) in developing countries has sparked fierce debate. Proponents argue these schools promote access in areas underserved by government schools, as well as benefit from improved autonomy in decision-making and accountability to parents to produce superior learning outcomes. Critics note that they fail to reach the poor, and any learning premium is driven by selection effects. Despite the ongoing debate, in the face of growing demand for schooling, public-private partnerships (PPPs) have become a key feature of the global education landscape. This trend is especially pronounced in the Punjab province of Pakistan, where many private schools participate in public financing schemes through subsidy, charter and voucher programs. With increasing recognition of the global learning crisis, the performance of PPP schools, as well as the drivers of any achievement gap, are of great interest to policy makers. Recent scholarship has foregrounded school management practices – including accountability to clients – as a key factor in school effectiveness. Drawing on data from the Service Delivery Indicator (SDI) Survey from Punjab, this dissertation contributes to these debates: first by asking if there is an achievement gap between PPP and government schools in Punjab (as well as fee-based private schools), and second, assessing the role of school management quality in explaining the achievement gap. I hypothesize that certain management best practices – focusing on the domains of people management, operations, leadership, target setting and monitoring, as measured by the SDI – are driven by increased autonomy for private schools, and should account for part of the hypothesized ‘PPP school premium’. The results suggest that while the achievement gap between PPP and public schools is small after accounting for student background, it is statistically significant and relatively consistent across models. In addition, when comparing the PPP approaches, voucher schools have the strongest achievement followed by subsidy and then charter schools. Second, I find that the index for management practices is positively associated with learning outcomes. However, despite having more autonomy in decision making, fee-based private schools and PPP schools do not appear better managed than government schools, and as a result, management practices do not explain the achievement gap.