Theses, Dissertations, and other Required Graduate Degree Essays

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This collection contains digitized SFU theses except for those theses submitted within the last 12 months. If you cannot find the thesis you are looking for please search Recently Submitted Theses as it may be a recently submitted thesis and thus not yet available in Summit.

Confocal microscopy for T centres in silicon

Date created: 
2020-04-07
Abstract: 

Spin defects in silicon boast long lifetimes and potential scalability with existing nanofabrication foundry processes. Paired with silicon photonics, optically active spin defects offer a path to scalable optically interfaced quantum technologies, such as quantum communication networks and optically coupled qubits. The T centre in silicon is a paramagnetic radiation damage centre that is optically active in the telecommunication O-band, making it a strong candidate for spin-photon interfaces. Certain single-photon based quantum technologies rely on the production of indistinguishable photons, a characteristic which may be found from an optical centre’s zero-phonon line. In this study we measure the zero-phonon line fraction of the T centre in silicon-28 at 4.2 K to be 22.9 ± 0.2%. Isolating optical defects in silicon is difficult due to the relatively low radiative efficiencies of silicon-based emitters and silicon’s large refractive index (n ≈ 3.5), trapping light by total internal reflection. Estimates using bound exciton ground state lifetime measurements from previous studies suggest isolation and measurement of single T centres is possible by confocal microscopy. We develop a confocal microscope system designed for measuring photoluminescence from cryogenically cooled silicon and characterize its resolution performance in reflection and above-band photoluminescence. Silicon photonic ‘micropuck’ structures were designed and fabricated to increase collection efficiency from single T centres into a microscope objective.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Stephanie Simmons
Department: 
Science: Department of Physics
Thesis type: 
(Thesis) M.Sc.

Lobbying for democracy: Interest groups in Canada’s parliamentary system

Author: 
Date created: 
2020-04-20
Abstract: 

Political scientists have long been interested in how interest groups influence policy—especially the information they provide to elected officials. In the American presidential system and in European consensus-parliamentary systems, information is increasingly understood as a subsidy from groups to their allies in the legislature. However, in majoritarian parliamentary systems (i.e. “Westminster” countries), such a perspective remains underdeveloped. The central motivation of this project is to understand how interest groups use information to intervene in the Westminster policy process. As an empirical case, I focus on a prominent majoritarian parliament: Canada. I generate quantitative evidence from three original datasets. First, I use aggregated Canadian lobbying registrations spanning fifteen policy areas from 1990-2009. Second, I use a dataset of 41,619 individual-level lobbying records from the House of Commons between 2010 and 2017. Third, I use a large dataset of committee utterances by Canadian parliamentarians and witnesses between 2006 and 2018, totalling 1.09M utterances. I present three major findings. First, lobbying from “cause” groups—representing diffuse interests like climate change—strengthens government responsiveness to public opinion. Lobbying from “sectional” groups—representing industry and professional associations— has no observable effect. Second, interest groups are more likely to communicate with government frontbenchers than with opposition or backbench members. This gap diminishes as agenda control diffuses to the opposition (i.e. during minority government). Third, interest groups—although nominally non-partisan—talk about policy issues in much the same way as partisan elected officials. Although we might expect legislative committees to help parliamentarians find common ground, the evidence suggests they often provide a venue for rival parties to learn about and develop competing issue frames.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Mark Pickup
Department: 
Arts & Social Sciences: Department of Political Science
Thesis type: 
(Thesis) Ph.D.

Modeling novel ionenes for electrochemical devices with first principles and machine learning methods

Author: 
Date created: 
2020-04-06
Abstract: 

Polybenzimidazole-based ionenes are being developed for use in both alkaline anion-exchange membrane fuel cells and alkaline polymer electrolysers. The first part of this work explores the impact of the degree of methylation on the conformations and electronic structure properties of poly-(hexamethyl-p-terphenylbenzimidazolium) (HMT-PMBI), the materials of interest in this thesis. For this purpose, HMT-PMBI oligomers, from monomer to pentamer, are studied with density functional theory calculations. Next, molecular dynamics simulations are used to calculate the trajectory paths of all atoms of the fully methylated HMT-PMBI tetramer. Lastly, recurrent neural networks are explored as a means to accelerate the statistical sampling of molecular conformations of polymeric systems, thereby providing complementary tools for molecular dynamics simulations. It is demonstrated that these types of artificial neural networks can be learned from the distribution of the coordinates of atoms over molecular dynamics simulations. As shown, the trained multivariate time series model enables forecasting trajectory paths of atoms accurately and in much reduced time with over 96% accuracy.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Steven Holdcroft
Department: 
Science: Department of Chemistry
Thesis type: 
(Thesis) M.Sc.

Quantitative analysis of dynamic Spliced Leader Trans-Splicing in Caenorhabditis elegans

Author: 
Date created: 
2020-04-08
Abstract: 

Spliced Leader Trans-Splicing (SLTS) is an important process in Caenohabditis elegans transcript maturation that is required for viability. However, the role it plays in development remains unclear. We explore the dynamic use of SLTS during C. elegans development. Using PacBio Iso-Seq data and WormBase annotations, we characterized SLTS Acceptor Sites (SLTS ASs) in full-length transcripts and predicted putative SLTS ASs for 98.8% of annotated protein-coding transcripts. By taking advantage of over 1000 publicly available RNA-seq datasets, we quantified the level of SL1 and SL2 SLTS and found evidence supporting SLTS for 70.3% of annotated protein-coding transcripts, which was consistent with previous research. We found cases of dynamics during embryogenesis, including those where the dominant SL changed, which suggests that SLTS is dynamic and may be regulated. This improves the current understanding of the role of SLTS in gene expression during development and provides insight into the dynamic nature of operons.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Jack Chen
Department: 
Science: Department of Molecular Biology and Biochemistry
Thesis type: 
(Thesis) M.Sc.

Will robots take our jobs?: The effects of artificial intelligence on high-skilled Canadians

Author: 
Date created: 
2020-04-09
Abstract: 

With the forthcoming Artificial Intelligence (AI) revolution estimated to cause millions in job losses throughout all sectors of the economy it is important to consider the broader societal impact that worker displacement and worker transition will have. Several studies have investigated the projected experience of low-skilled workers and the impact automation is predicted to have on their employment prospects, however, very few have focused on the effects on high-skilled workers. This paper attempts to fill this gap by evaluating policies for mitigating the expected negative impact of automation and AI-based technologies on Canada’s high-skilled workforce. Three policy options are presented which focus on retraining, portable benefits schemes, and maintaining the status quo. As AI is an ever-changing field of technology with capabilities not yet fully achieved this paper and the policy options presented within attempt to create proactive policies that will effectively address the negative labour market outcomes regardless of technological advances.

Document type: 
Graduating extended essay / Research project
File(s): 
Senior supervisor: 
Dominique Gross
Department: 
Arts & Social Sciences: School of Public Policy
Thesis type: 
(Project) M.P.P.

The healthy immigrant effect: A policy perspective

Author: 
Date created: 
2020-04-02
Abstract: 

The Healthy Immigrant Effect (HIE) is the term given to the phenomena of immigrants arriving to Canada with stronger health than their Canadian-born counterparts. However, immigrant health experiences a steep decline over time since migration to reach the Canadian-born population’s health levels or lower. This paper examines the HIE from a policy perspective in the Canadian context by centering on the barriers and facilitators of migrant health. Data was used from the 2018 Canadian Community Health Survey to observe variations among immigrants and the Canadian-born population in both self-perceived health status and the variables related to health service utilization using logistic and linear regression models. A comprehensive policy model is recommended to make immigrant health a priority for both federal and provincial governments, including a migrant sensitive health strategy complemented by mandatory cultural sensitivity training for providers and administrators, and the inclusion of migrant-specific variables in the national health census.

Document type: 
Graduating extended essay / Research project
File(s): 
Senior supervisor: 
Maureen Maloney
Department: 
Arts & Social Sciences: School of Public Policy
Thesis type: 
(Project) M.P.P.

War on drug resistance: Policy interventions to tackle antibiotic misuse in Canada

Author: 
Date created: 
2020-03-23
Abstract: 

Antimicrobial resistance is a growing threat in Canada with profound implications for public health and wellbeing. Widespread misuse of antibiotics has led to increasing numbers of drug-resistant “superbugs” capable of causing serious and potentially untreatable infections. Addressing antibiotic misuse is crucial in order to curb antimicrobial resistance, but there is a lack of coordinated policy action across the country. Furthermore, research on the predictors of antibiotic misuse in Canada is sparse, which hinders policy makers’ ability to develop targeted interventions. This study analyzes national survey data to shed light on the extent of antibiotic misuse in Canada, including uncovering socio-demographic predictors of public misuse. The findings are used to inform proposed policy recommendations that aim to reduce antibiotic misuse in order to better position Canada to tackle antimicrobial resistance in the years ahead.

Document type: 
Graduating extended essay / Research project
File(s): 
Senior supervisor: 
Dominique Gross
Department: 
Arts & Social Sciences: School of Public Policy
Thesis type: 
(Project) M.P.P.

Computational methods for analysis of single molecule sequencing data

Author: 
Date created: 
2020-03-26
Abstract: 

Next-generation sequencing (NGS) technologies paved the way to a significant increase in the number of sequenced genomes, both prokaryotic and eukaryotic. This increase provided an opportunity for considerable advancement in genomics and precision medicine. Although NGS technologies have proven their power in many applications such as de novo genome assembly and variation discovery, computational analysis of the data they generate is still far from being perfect. The main limitation of NGS technologies is their short read length relative to the lengths of (common) genomic repeats. Today, newer sequencing technologies (known as single-molecule sequencing or SMS) such as Pacific Biosciences and Oxford Nanopore are producing significantly longer reads, making it theoretically possible to overcome the difficulties imposed by repeat regions. For instance, for the first time, a complete human chromosome was fully assembled using ultra-long reads generated by Oxford Nanopore. Unfortunately, long reads generated by SMS technologies are characterized by a high error rate, which prevents their direct utilization in many of the standard downstream analysis pipelines and poses new computational challenges. This motivates the development of new computational tools specifically designed for SMS long reads. In this thesis, we present three computational methods that are tailored for SMS long reads. First, we present lordFAST, a fast and sensitive tool for mapping noisy long reads to a reference genome. Mapping sequenced reads to their potential genomic origin is the first fundamental step for many computational biology tasks. As an example, in this thesis, we show the success of lordFAST to be employed in structural variation discovery. Next, we present the second tool, CoLoRMap, which tackles the high level of base-level errors in SMS long reads by providing a means to correct them using a complementary set of NGS short reads. This integrative use of SMS and NGS data is known as hybrid technique. Finally, we introduce HASLR, an ultra-fast hybrid assembler that uses reads generated by both technologies to efficiently generate accurate genome assemblies. We demonstrate that HASLR is not only the fastest assembler but also the one with the lowest number of misassemblies on all the samples compared to other tested assemblers. Furthermore, the generated assemblies in terms of contiguity and accuracy are on par with the other tools on most of the samples.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Binay Bhattacharya
S. Cenk Sahinalp; Cedric Chauve; Faraz Hach
Department: 
Applied Sciences: School of Computing Science
Thesis type: 
(Thesis) Ph.D.

Evaluating and utilizing crowdsourced data and population surveys in bicycling safety research

Date created: 
2020-04-14
Abstract: 

Increased population level bicycling would benefit society by improving health outcomes and reducing fossil fuel emissions. A main factor preventing increased bicycling is concerns regarding safety. Traditional sources of bicycling safety data (police, hospital or insurance data) underreport incidents and are biased. Alternative sources of bicycling safety data, including crowdsourcing and population surveys, are untested and rarely utilized. Crowdsourced data will include incidents that go unreported to traditional sources, but the nature of any systematic biases in these data are poorly understood. Population surveys represent the only means of collecting detailed individual-level information regarding road users, but there is little consideration by researchers of how survey design choices may affect measured outcomes. When combined with spatial data, population surveys can contribute to understanding associations between rarely studied characteristics of road users and perceived or objective safety. In this thesis, I evaluate alternative sources of bicycling safety data, and contribute to different dimensions of bicycling safety knowledge, by evaluating bicycling safety data collection methods and identifying correlates of perceived and objective bicycling safety. Specifically, the chapters in this thesis address gaps in our understanding of (i) biases in crowdsourced bicycling safety data, (ii) the relationship between personal characteristics, infrastructure, and overall perceived bicycling safety, (iii) the impacts of survey design on measurements of bicycling behaviour, and (iv) bicycling crash risk for different sociodemographic characteristics, social environments (including attitudes and social norms), and neighbourhood-built environment features. In this thesis I provide two broad contributions: (i) showcasing the potential for crowdsourced data and population surveys to compliment traditional bicycling safety data and, provide answers to applied question in bicycling safety research; (ii) underscoring the value of linking a-spatial survey data to a geographic location to be able to assign measurements of a participants built environment and, be able to consider different scales of influence on the outcome. Future research in this area should focus on creating a linked crash database of self-report, crowdsourced, police, hospital and insurance data, as well as on the collection and integration of spatially resolved exposure estimates in travel surveys.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Meghan Winters
Department: 
Health Sciences: Faculty of Health Sciences
Thesis type: 
(Thesis) Ph.D.

Deconstructing supertagging into multi-task sequence prediction

Author: 
Date created: 
2020-04-07
Abstract: 

Supertagging is a sequence prediction task where each word is assigned a complex syntactic structure called a supertag. In this thesis, we propose a novel multi-task learning approach for Tree Adjoining Grammar~(TAG) supertagging by deconstructing these complex supertags to a set of related but auxiliary sequence prediction tasks, which can best represent the structural information of each supertag. Our multi-task prediction framework is trained over the same training data used to train the original supertagger, where each auxiliary task provides an alternative view of the original prediction task. Our experimental results show that our multi-task approach significantly improves TAG supertagging with a new state-of-the-art accuracy score of 91.39% on the Penn treebank supertagging dataset. We also show consistent improvement of around 0.4% in tagging accuracy by applying our multi-task prediction framework into various neural supertagging models without using any additional data resources.

Document type: 
Thesis
File(s): 
Senior supervisor: 
Anoop Sarkar
Department: 
Applied Sciences: School of Computing Science
Thesis type: 
(Thesis) M.Sc.