VictorJuiz/thesis huggingface dataset:
Performance Monitoring of Multi-FPGA Systems

Field-Programmable Gate Arrays (FPGAs) have been increasingly deployed in datacenters and there has been a lot of focus on tools that help the development of FPGA applications. Among the most important tools are performance monitors that provide visibility into the state of the hardware. As the application platforms scale from one FPGA to many FPGAs, such as the well-known examples demonstrated on the Microsoft Catapult platform, it is no longer feasible to rely on low-level FPGA tools such as embedded logic analyzers. This thesis presents Pharos, a lightweight, generic performance monitor for multi-FPGA systems. We show that Pharos is able to measure cycle-accurate unidirectional point-to-point latency between multiple network-connected FPGAs. Pharos is also capable of monitoring network traffic and conducting throughput measurements, as well as tracing events across the datacenter.

Keywords: Computer Hardware
FPGA
Networks
Performance Monitoring
Profiling
Reconfigurable Computing
Advisor: Chow, Paul
Flexure and Shear Base-mechanism for the Enhanced Resilience of RC Coupled High-rise Buildings

This thesis presents the development and analytical investigation of a flexure and shear yielding base-mechanism that improves the seismic performance of RC coupled wall high-rise buildings. Although current design practice achieves life safety and collapse prevention during major earthquake events, there is often extensive damage located in the plastic hinging regions including the wall bases and coupling beams. A system of buckling-restrained braces located below the core is implemented as an alternative seismic fuse. With this system, the first-mode and higher-mode responses of the structure are limited through a combination of flexural and shear yielding. Nonlinear time-history analyses have been carried out comparing the performance of a reference structure to this alternative design. Results demonstrate that the base–mechanism improves the overall performance of the structure by limiting damage and improving safety at all hazard levels. Connection details for the system and design steps are also proposed.

Keywords: base-mechanism
high-rise buildings
higher-mode effects
reinforced concrete coupled walls
seismic resilience
Advisor: Christopoulos, Constantin
Detect Iago Vulnerabilities in Legacy Code with Reverse Syscall Fuzzing

There has been interest in mechanisms that allow legacy code to be securely used to implement trusted code that runs in Trusted Execution Environments (TEEs), such as Intel SGX. However, because legacy code generally assumes the presence of an operating system, this naturally raises the spectre of Iago attacks on the legacy code. We develop Emilia, which automatically detects Iago vulnerabilities in legacy applications using reverse system call fuzzing. We use Emilia to discover 50 Iago vulnerabilities in 17 applications, and find that Iago vulnerabilities are widespread and common. We conduct an in-depth analysis of the vulnerabilities we found and conclude that while common, the majority (84%) can be mitigated with simple, stateless checks in the system call forwarding layer, while the rest are best fixed by finding and patching them in the legacy code. Finally, we study and evaluate different trade-offs in the design of Emilia.

Keywords: Computer Secuirty
Fuzzing
Trust computing
Advisor: Lie, David
Assessment of Convolutional Neural Networks to Classify Freshwater Zooplankton

Zooplankton have been used as indicators of aquatic ecosystem health, but their identification using traditional microscopy can be time consuming. Machinery such as Yokogawa Fluid Imaging Technologies FlowCam allow for rapid imaging of microscopic particles, such as zooplankton. However, these machineries lack sophisticated algorithms like convolutional neural networks (CNNs) to classify images. Here, the efficacy of CNNs to classify six freshwater zooplankton species and a fiber-like particle with images obtained from a FlowCam Macro were examined. Oxford Visual Geometry Group (VGG) CNN architecture best suited our data. CNNs were found to have validation accuracies greater than 97%. The models were further tested with independent random mixtures of species and fiber-like particles, and they achieved accuracies ranging from 84.9% to 96.33% and F1-scores ranging from 82.43% to 95.02%. These results indicate that CNNs are promising tools for the rapid identification of zooplankton species.

Keywords: convolutional neural networks
deep learning
taxonomy
zooplankton
Advisor: de Kerckhove, Dak
Chu, Cindy
Continuous-time Marginal Structural Models for Adverse Drug Effects in Pharmacoepidemiology

Analysis of new user cohort studies of adverse drug effects can be based on either intention-to-treat or as-treated paradigms. In the latter case, controlling for time-dependent confounding is necessary, and can be implemented through inverse probability of treatment (IPT) weighted estimation of marginal structural models (MSM). To develop the weights in the context of pharmacoepidemiological administrative data, besides a time-fixed initial dose model, the subsequent time-varying exposure can be decomposed into modeling the time of the dispensations and the dose at each time through a multinomial or multiordinal logistic model, as a marked point process. We compare different approaches for constructing the weights in a simulation study, simulating data from a multistate model. For estimation of the outcome MSM, we propose IPT weighted case-base sampling, which can reduce the size of long-format data sets needed, especially for rare outcomes. The methods are then demonstrated in a study of the effect of glucocorticoid use on fracture risk.

Keywords: Case-base sampling
Causal Inference
Glucocorticoid
Marginal Structural Model
Pharmacoepidemiology
Survival Analysis
Advisor: Saarela, Olli OS
Cadarette, Suzanne SC
Peracetic Acid Disinfection Synergy With Alum and Direct Reaction With Chlorine

Peracetic acid (PAA) is an effective disinfectant during wastewater treatment. Anecdotal reports suggest that its disinfection efficiency increases when combined with residual alum from upstream coagulation. This research focused on determining if PAA and aluminum could initiate an advanced oxidation process. Two probes were used during this study to test the presence of hydroxyl radicals (OH•), and neither showed OH• formation. E. coli inactivation was also assessed, with no significant increase in log reduction observed when alum was present during PAA disinfection. This research also focused on the effect of PAA on chlorine disinfection when used as a pretreatment for DBP and mussel control during drinking water treatment. A kinetic model was developed to simulate the impact of PAA on chlorine consumption as a function of pH. It was determined that chlorine decay was attributed mainly to the reaction with the slow formation of H2O2 associated with PAA decomposition.

Keywords: alum
chlorine
peracetic acid
radicals
synergy
Advisor: Hofmann, Ronald
Altered Biological Responses of Primary Producers to Multiple Stressors in the Presence of Nanoplastics

The interactions between nanoplastics and factors that simultaneous present in the aquatic environment, including climatic change stressors and local chemicals, are largely unknown. This thesis presents methods to understand how nanoplastics will affect species or interfere with their response to local chemicals in concert with climate change in freshwater ecosystems. With the aid of a high-throughput screening platform, we first discovered the interactive effects among nanoplastics, CO2, light, and temperature on freshwater algae, Scenedesmus obliquus. We then studied the control of CyanoHABs considering nanoplastics contamination and captured the non-additive combined effect of H2O2 and nanoplastics on freshwater cyanobacteria, Microcystis aeruginosa. Using these methods adopted here, one can screen a wide range of stressors combinations, identify interesting ones, then study chronic effects at those levels. They also provided improved accuracy and realism in nanoplastics exposure experiments to properly depict local aquatic conditions and investigate the subsequent ecological impacts on aquatic life.

Advisor: Sinton, David D.S.
Exploring the Development of Playfulness among Youth with Disabilities in the HB FIRST® Robotics Program

Background: Youth with disabilities often have less opportunities to play than their typically developing peers. An adapted robotics program is a promising way to help address problems in play development while learning educational content relevant for success across the lifespan.Objective: To understand the impact of using an adapted robotics program on the development of playfulness among youth with disabilities, aged 9 to 14 years. Methods: Observational research design using a pre-post video analysis on video-recorded raw data using the normalized and standardized assessment tool, the Test of Playfulness. Results: Participants exhibited significantly more playful behaviours following the completion of the adapted robotics program (Δ=0.8, p=0.001). Prior enrollment in the program also significantly impacted playfulness (F(1.0, 25)=10.0, p=0.004) Age, gender and disability type did not improve playfulness. Conclusion: The adapted robotics program improved the playfulness scores of youth with disabilities while enrolled in the program. These findings suggest that youth with disabilities can improve their playfulness through recreational and/or leisurely means.

Keywords: children
disability
paediatrics
rehabilitation
robotics
youth
Advisor: Lindsay, Sally
High Dynamic Range (HDR) Signal Processing, Augmented Reality and Wearable Technology Applications in Audiovisual Perception and Sensing

Sensation and perception are fundamental to how we interact with our surroundings and others. By investigating our ability and capacity to sense, we may better understand human and machine perceptions. This thesis examines how the use of signal processing, augmented reality and wearable technology enhances our audiovisual experience. First, we propose methods to produce a more immersive auditory experience by increasing the dynamic range of the audio signal through HDR signal processing. Next, we explore how augmented reality techniques for visualizing otherwise invisible phenomena are useful for studying, understanding, and interacting with these phenomena. Lastly, we propose methods and algorithms that investigate the relationship of steady-state visually evoked potential responses and the visual field of the human eye with an electroencephalogram device. By tapping into wearable technology, we realize an affordable and accessible solution for auditory and vision-related personalized health care and assistive technologies.

Keywords: augmented reality
electroencephalogram (EEG)
high-dynamic-range (HDR)
signal reconstruction
steady-state visually evoked potentials (SSVEP)
wearable technology
Advisor: Mann, Steve
Sensuous Clothing – Cultivating a Hidden Fashion Curriculum that Moves and Bends with Living Atmospheres

In this thesis I theorize what I call ‘fashion atmospheres’ as a pedagogical mode that considers both the visible and invisible aspects of clothing. I theorize a fashion pedagogy that considers both human and more-than-human presences. I use non-representational theories along with feminist new materialisms and anti-colonial theories to argue for relational, affective and equitable fashion systems. As a research-creation project, I theorize with three textile-based artworks that work to unsettle the idea that clothing is empty of meaning outside of human use and capital gain. Instead, I argue that fashion and clothing are complex sites of knowledge that needs to be taken seriously. I challenge the idea that a garment is a dead object waiting for human extraction by attuning to the many possibilities of a garment as a relational and affective object that has always been influenced by the ways we come to relate to each other and to the more-than-human.

Advisor: Springgay, Stephanie
Investigating the Influence of Fuel Volatility on Particle Emissions Phenomena in a Production Gasoline Direct Injection Engine

Due to both potential climate and health concerns, research interest in the formation of particulate matter in GDI engines remains strong. However, the processes driving the emissions are still not fully understood. This experimental study investigated the influence of fuel volatility on the particulate matter emissions, using both commercial and specifically targeted and controlled surrogate fuel blends to isolate the influence of fuel volatility from traditionally considered causative effects of fuel chemistry and properties. In non-ethanol containing fuels, high measured volatility fuels resulted in increased PM emissions in comparison to low volatility fuels, while also generating increased nitric oxide emissions. The effect of 10\% ethanol match blended in these fuels varied with volatility level, with E10 fuels always presenting high PM emissions, unlike their ethanol-free counterparts. A fuel injector deposit driven change in PM emissions was noted in the dataset, which appeared to show dependence on fuel volatility as well.

Keywords: Deposits
Flash-Boiling
Gasoline
Injection
Volatility
Advisor: Wallace, James S
Modeling the Dynamics of Evaporator Wash Cycles

In the pulp and paper industry, black liquor evaporation is an essential step that leads to energy and chemical recovery. Fluctuations in liquor chemistry can result in evaporator scaling events, which negatively impacts thermal efficiency and mill production. Efficient evaporator washes result in scale dissolution and recovery of the heat transfer rate. Tool development is needed to improve the current evaporator washing strategies, which are primarily based on trial and error. The focus of this work was on the modeling approach and the evaluation of the impact of evaporator wash cycles on the fluctuations in sodium and oxalate in the feed liquor. The simulation was based on the evaporation plant of a South American pulp mill, and the dynamic model was developed in Matlab Simulink. The developed model demonstrated the potential to estimate the concentration of key ions that cause scaling, and to lead to improvements in evaporator washing strategies.

Keywords: Black liquor
Dynamic simulation
Evaporator
Scaling
Soluble scale
Wash cycle
Advisor: DeMartini, Nikolai N.A.D.
Characterizing Unstable Operation in Flow Cells for CO2 Electroreduction

Carbon dioxide (CO2) reduction flow cells are a promising means of curtailing anthropogenic CO2 emissions by reducing CO2 to generate useful carbon fuels when coupled with renewable energy sources. However, operating these devices at commercially relevant conditions is typically accompanied by mass transport issues related to unstable performance that is often overlooked. This thesis contains two studies focused on identifying and characterizing the source of unstable performance in these devices. In the first study, the effect of gaseous accumulation at the cathode gas diffusion electrode interface on the performance of an alkaline flow cell was investigated. In the second study, the relationship between unstable operation and the electrolyte layer gas saturation in a flow cell was characterized. These two studies aim to provide the necessary first steps in addressing unstable operation in CO2 reduction flow cells towards achieving stable, commercially relevant operation.

Keywords: CO2 electrolysis
flow cell
gas evolution
neutron radiography
synchrotron X-ray radiography
unstable performance
Advisor: Bazylak, Aimy
Efficient Subobject-granularity Spatial Memory Safety Enforcement with In-fat Pointer

Lack of memory safety in programming languages like C and C++ can leave programs written in these languages with exploitable memory corruption vulnerabilities. Spatial memory safety defense can catch memory corruptions from out-of-bounds pointer arithmetic. However, none of the existing works can achieve low overhead, high compatibility, and fine-grained protection at the same time. This thesis presents In-Fat Pointer, a hardware-assisted spatial memory safety defense that improves the protection granularity of existing tagged-pointer schemes using object metadata to subobject-bound granularity while maintaining their high compatibility and low overhead. In-Fat Pointer introduces multiple object metadata schemes to spare pointer tag bits from object metadata lookup, and use the spared bits with in-memory type metadata for subobject bound computation. The hardware prototype is implemented on an FGPA board, and In-Fat Pointer is evaluated in functionality, runtime and memory performance, and estimated hardware cost.

Keywords: C/C++
Computer Security
Hardware
Spatial Memory Safety
Tagged-pointer
Advisor: Lie, David
The Function of the FERM Protein Okapi in Regulating the Number of Follicle Stem Cells and Interfollicular Stalk Cells in Drosophila Ovaries

The FERM domain protein Okapi (Oka) is important for normal Drosophila oogenesis. I found that Oka is required in the follicle stem cell (FSC) lineage to prevent an overgrowth of FSCs. To determine how Oka regulates FSCs, I analyzed interactions between oka and Hippo pathway genes, as they have similar mutant phenotypes. Hippo is known to limit nuclear translocation and activity of Yorkie, thereby suppressing cell proliferation. I found a higher proportion of FSCs with nuclear Yorkie in oka mutants than in wild-type. Reduction of Yorkie or Hippo overexpression partially rescued the FSC overgrowth in oka mutant ovaries. Interestingly, I found that oka mutant FSCs were lost when forced to compete with wild-type FSCs, whereas hippo mutant FSCs are known to be hyper-competitive. My findings indicate that Oka regulates the number of FSCs through the Hippo pathway and is required to make FSCs competitive through an unknown mechanism.

Keywords: Cell competition
Drosophila
FERM domain protein
Hippo pathway
Oogenesis
Stem cells
Advisor: Godt, Dorothea DG
Tepass, Ulrich UT
Emergency Use Ventilator Evaluation and Assessment: Open-Source Hardware, Performance, Regulatory Requirements and Technology Readiness

Emergency ventilators have attracted a lot of attention and resources during the COVID-19 pandemic due to which many groups have adopted open-source hardware development models. This study reviews enforceable guidelines as presented by various public health agencies and regulators and creates an assessment framework to determine the said system’s open-source information, performance, and its compliance towards regulatory benchmarks. The study also proposes a modified Technology Readiness Level (TRL) framework accommodating the relevant changes in the development pathways due to emergency circumstances. Furthermore, it investigates the efficacy of cardinal maturity assessment systems over preceding ordinal models. A novel method of Weighted Technology Readiness Level (WTRL) is proposed to quantify the degree of technology maturity of a system. The proposed model is then applied towards the maturity assessment of emergency ventilation systems while highlighting its importance. The model is also applied to ascertain the maturity of 7 NASA technologies and is compared against pre-existing cardinal frameworks.

Keywords: Cardinal TRL
Emergency Ventilator
System Design
Technology Readiness Level
Advisor: Behdinan, Kamran
Driving with Distraction: Brain Activity and Oculomotor Behaviour using fMRI and Eye-tracking

Due to the importance of visual attention to safe driving, this thesis examines the effects of distraction on the neural correlates of driving behaviour and the associated eye movements. Functional magnetic resonance imaging and simultaneous eye-tracking measurements are performed during simulated driving tasks with and without auditory distraction. Results showed no significant differences in the brain activation maps between right turns, left turns with and without oncoming traffic. The introduction of distraction produced significantly increased activations in the frontal and temporal lobes, and decreased activation in the posterior brain, suggesting a decrease in resources for visual attention. Distraction also caused a decrease in gaze variability, significantly greater saccadic eye movements and a significant increase in blink rate. These results suggest that the increase in cognitive load causes decreased visual attention for the primary driving task, reflecting how the brain and eyes deal with cognitive challenges during realistic driving scenarios.

Keywords: distracted driving
driving
driving complexity
eye-movements
fMRI
neural correlates of driving
Advisor: Graham, Simon J
Identification and Characterization of Proteolytic Activities from S. mutans that Hydrolyzes Dentinal Collagen Matrix

Objective: To measure the proteolytic activity of S. mutans, its discrete fractions, and proteases towards demineralized human dentin. Methods: Demineralized human dentin slabs were incubated with either medium, cultures (overnight or newly inoculated) of S. mutans UA159, or different bacterial fractions (intracellular, supernatant or bacterial membrane). Media from each condition was analyzed for a collagen degradation marker, hydroxyproline. Three potential proteolytic enzymes (SMU_759, SMU_761 and SMU_1438c) from S. mutans UA159 were expressed and their activity toward dentinal collagen was measured based on hydroxyproline analysis. Results: Media only and bacterial membrane had no activity towards dentinal collagen. Overnight culture of S. mutans had the highest degradative activity (p

Keywords: Caries
Collagenolytic/gelatinolytic enzymes
Degradation
Dentinal Collagen
Proteolytic Activities
S. mutans
Advisor: Finer, Yoav YF
Cvitkovitch, Dennis DC
Additive Manufacturing of Thermoactivated Morphing Materials

Novel structures fabricated by additive manufacturing and soft robotic actuator designs show promise in aerospace development. These structures and actuators can provide a lightweight alternative to the current solutions and can be tailored to enhance specific properties. This work focuses on the development of printed sandwich core structures and thermally activated surfaces through the characterization and improvements of existing designs. Octet unit cells are 3D printed in the form of a lattice and functionally graded to evaluate during quasi-static compression. The vertical grading is achieved through specific variations in structure and materials to improve energy absorption capabilities. This study is followed by an investigation of the bending deformation of various designs of electrothermal actuators. A series of characterization tests are conducted to reveal the relationship between actuator dimensions, constraints, heating time, and conductive layer thickness to the maximum deflection. A novel actuator array is demonstrated using these findings.

Advisor: Naguib, Hani
Residential Segregation and Inequality: Considering Barriers to Choice in Toronto

Segregation of visible minorities has persisted throughout time in Toronto. In examining these concentrations, the literature has been heavily focused on the notion that visible minorities are choosing to live in proximity of their respective ethno-racial groups and that these are spaces of aspiration rather than marginalization in Canada. This thesis raises questions about the assertion of ‘self-segregation’ by emphasizing affordability constraints on residential choices that are often rooted in discrimination and inequality in the housing and labor markets. Census data from 2016, the dissimilarity index and an adopted neighborhood classification scheme was used to understand the spatial patterning of visible minorities in the Toronto CMA and highlight differences in the socio-economic characteristics of visible minority dominant and white dominant census tracts. The findings invite the inference that economic opportunities play a critical role in the residential choices of visible minorities and raise concerns about the quality of life in visible minority neighborhoods.

Keywords: Neighbourhood Inequality
Residential Segregation
Toronto
Advisor: Wakefield, Sarah