Physical Sciences and Mathematics Commons^™

Assessing The Spatio-Temporal Behaviours Of Incomplete Surface Temperatures Using Thermal Remote Sensing And Gis, Derrick Kessie

Electronic Thesis and Dissertation Repository

This study aimed to better understand the spatiotemporal behaviors of "incomplete" surface temperatures, a subset of all the active surfaces in urban areas, that are relevant for outdoor thermal comfort assessments. This study answered the following questions: 1. What is the temperature of "incomplete surfaces" that are most relevant in urban thermal comfort assessments, and what is its spatiotemporal behavior in different urban neighborhoods? 2. How are the relevant incomplete temperatures related to nadir view remotely sensed surface temperatures (Tplan)? By combining distributions of wall temperatures from TUF-3D, an urban energy balance model, and horizontal surface temperatures from airborne remotely …

Advances In Copula Estimation And Distribution Theory, Yishan Zang

Electronic Thesis and Dissertation Repository

This dissertation initially features distributional results related to copulas. Four distinct copula density estimation methodologies, including Bernstein’s polynomial approximation, are proposed and criteria for the selection of their tuning parameters are provided. These four approaches were found to produce similar density estimates, which validates their suitability. Moreover, the copula associated with a Wiener process and its running maximum is determined, and an illustrative numerical example is presented. The principal properties of Spearman’s, Kendall’s, Blomqvist’ and Hoeffding’s measures of association as well as their representations in terms of copulas are also discussed. Then, a novel method that is based on an …

Decoy-Target Database Strategy And False Discovery Rate Analysis For Glycan Identification, Xiaoou Li

Electronic Thesis and Dissertation Repository

In recent years, the technology of glycopeptide sequencing through MS/MS mass spectrometry data has achieved remarkable progress. Various software tools have been developed and widely used for protein identification. Estimation of false discovery rate (FDR) has become an essential method for evaluating the performance of glycopeptide scoring algorithms. The target-decoy strategy, which involves constructing decoy databases, is currently the most popular utilized method for FDR calculation. In this study, we applied various decoy construction algorithms to generate decoy glycan databases and proposed a novel approach to calculate the FDR by using the EM algorithm and mixture model.

Polynomial Density Of Compact Smooth Surfaces, Luke P. Broemeling

Electronic Thesis and Dissertation Repository

We show that any smooth closed surface has polynomial density 3 and that any connected compact smooth surface with boundary has polynomial density 2.

Framework For Assessing Information System Security Posture Risks, Syed Waqas Hamdani

Electronic Thesis and Dissertation Repository

In today’s data-driven world, Information Systems, particularly the ones operating in regulated industries, require comprehensive security frameworks to protect against loss of confidentiality, integrity, or availability of data, whether due to malice, accident or otherwise. Once such a security framework is in place, an organization must constantly monitor and assess the overall compliance of its systems to detect and rectify any issues found. This thesis presents a technique and a supporting toolkit to first model dependencies between security policies (referred to as controls) and, second, devise models that associate risk with policy violations. Third, devise algorithms that propagate risk when …

Evaluating The Likelihood Of Bug Inducing Commits Using Metrics Trend Analysis, Parul Parul

Electronic Thesis and Dissertation Repository

Continuous software engineering principles advocate a release-small, release-often process model, where new functionality is added to a system, in small increments and very frequently. In such a process model, every time a change is introduced it is important to identify as early as possible, whether the system has entered a state where faults are more likely to occur. In this paper, we present a method that is based on process, quality, and source code metrics to evaluate the likelihood that an imminent bug-inducing commit is highly probable. More specifically, the method analyzes the correlations and the rate of change of …

Internal Yoneda Ext Groups, Central H-Spaces, And Banded Types, Jarl Gunnar Taxerås Flaten

Electronic Thesis and Dissertation Repository

We develop topics in synthetic homotopy theory using the language of homotopy type theory, and study their semantic counterparts in an ∞-topos. Specifically, we study Grothendieck categories and Yoneda Ext groups in this setting, as well as a novel class of central H-spaces along with their associated bands. The former are fundamental notions from homological algebra that support important computations in traditional homotopy theory. We develop these tools with the goal of supporting similar computations in our setting. In contrast, our results about central H-spaces and bands are new, even when interpreted into the ∞-topos of spaces.

In Chapter …

The Effect Of Solution Parameters On The Interfacial Chemical Dynamics Of Early-Stage Corrosion, Brianna K. Rector

Electronic Thesis and Dissertation Repository

Corrosion is a key long-term degradation process for metallic components in nuclear industry infrastructure. Accurately predicting the corrosion rate of a component in its service environment is considered a grand challenge in the corrosion community. Corrosion is a multi-step electrochemical process, with elementary steps involving mass transfer across more than one stage. Due to the multi-step, multi-phase nature of corrosion systems, predicting corrosion behaviour over time is complex. Existing corrosion models can describe electron transfer and mass transport steps independently, under narrow sets of conditions or over a specified duration but cannot account for the changes that occur over time …

Addressing The Impact Of Time-Dependent Social Groupings On Animal Survival And Recapture Rates In Mark-Recapture Studies, Alexandru M. Draghici

Electronic Thesis and Dissertation Repository

Mark-recapture (MR) models typically assume that individuals under study have independent survival and recapture outcomes. One such model of interest is known as the Cormack-Jolly-Seber (CJS) model. In this dissertation, we conduct three major research projects focused on studying the impact of violating the independence assumption in MR models along with presenting extensions which relax the independence assumption. In the first project, we conduct a simulation study to address the impact of failing to account for pair-bonded animals having correlated recapture and survival fates on the CJS model. We examined the impact of correlation on the likelihood ratio test (LRT), …

Complex-Valued Approach To Kuramoto-Like Oscillators, Jacqueline Bao Ngoc Doan

Electronic Thesis and Dissertation Repository

The Kuramoto Model (KM) is a nonlinear model widely used to model synchrony in a network of oscillators – from the synchrony of the flashing fireflies to the hand clapping in an auditorium. Recently, a modification of the KM (complex-valued KM) was introduced with an analytical solution expressed in terms of a matrix exponential, and consequentially, its eigensystem. Remarkably, the analytical KM and the original KM bear significant similarities, even with phase lag introduced, despite being determined by distinct systems. We found that this approach gives a geometric perspective of synchronization phenomena in terms of complex eigenmodes, which in turn …

An Approach To Lunar Regolith Particle Detection And Classification Using Deep Learning, Hira Nadeem

Electronic Thesis and Dissertation Repository

Lunar regolith, unconsolidated rock on the lunar surface, is made up of various particles. Understanding the quantities and locations of these particles on the lunar surface is of particular interest to planetary scientists for mission planning and science objectives. There is a limited supply of lunar regolith samples available on Earth for planetary scientists to characterize. Lunar rover missions over the next decade are expected to provide high-resolution images of the lunar surface. Deep learning can be leveraged to analyze lunar regolith from image data. An object detection model using transfer learning was developed to identify and classify particles of …

Dynamically Finding Optimal Kernel Launch Parameters For Cuda Programs, Taabish Jeshani

Electronic Thesis and Dissertation Repository

In this thesis, we present KLARAPTOR (Kernel LAunch parameters RAtional Program estimaTOR), a freely available tool to dynamically determine the values of kernel launch parameters of a CUDA kernel. We describe a technique for building a helper program, at the compile-time of a CUDA program, that is used at run-time to determine near-optimal kernel launch parameters for the kernels of that CUDA program. This technique leverages the MWP-CWP performance prediction model, runtime data parameters, and runtime hardware parameters to dynamically determine the launch parameters for each kernel invocation. This technique is implemented within the KLARAPTOR tool, utilizing the LLVM Pass …

Investigating Improvements To Mesh Indexing, Anurag Bhattacharjee

Electronic Thesis and Dissertation Repository

The MEDLINE database currently comprises an extensive collection of over 35 million citations, with more than 1 million records being added each year [28]. The abundance of information available in the database presents a significant challenge in identifying and locating relevant research articles on a given search topic. This has prompted the development of various techniques and approaches aimed at improving the efficiency and effectiveness of information retrieval from the MEDLINE database. A search engine devoted to the research publications on MEDLINE is called PubMed. MeSH, or Medical Subject Headings, is a restricted vocabulary used by PubMed to categorize each …

The Magnetic Field Of Protostar-Disk-Outflow Systems, Mahmoud Sharkawi

Electronic Thesis and Dissertation Repository

Recent observations of protostellar cores reveal complex magnetic field configurations that are distorted in the innermost disk region. Unlike the prestellar phase, where the magnetic field geometry is simpler with an hourglass configuration, magnetic fields in the protostellar phase are sculpted by the formation of outflows and rapid rotation. This gives rise to a significant azimuthal (or toroidal) component that has not yet been analytically modelled in the literature. Moreover, the onset of outflows, which act as angular momentum transport mechanisms, have received considerable attention in the past few decades. Two mechanisms: 1) the driving by the gradient of a …

Data-Driven Predictive Maintenance: Hvac Health Prognostics Using Power Consumption And Weather Data, Ruiqi Tian

Electronic Thesis and Dissertation Repository

Data-driven predictive maintenance for heat, ventilation, and air conditioning (HVAC) systems has gained much popularity over recent years due to the increasing availability of integrated internet of things (IoT) sensors capable of reporting HVAC internal operational data. Most existing predictive maintenance methods are designed to analyse these internal operational data for maintenance decision making. However, these methods are not applicable to HVAC systems that are not equipped with internal IoT sensors. Consequently, we propose an AutoEncoder and Artificial Neural Network based HVAC Health Prognostics framework (AE-ANN-HP) that classifies the health condition of HVAC systems using only daily power consumption and …

Modelling Cell Population Growth, Mahmood Mazarei

Electronic Thesis and Dissertation Repository

The growth of biological matter, e.g., tumor invasion, depends on various factors, mainly the tissue’s mechanical properties, implying elasticity, stiffness, or apparent viscosity. These properties are impacted by the characteristics of the tissue’s extracellular matrix and constituent cells, including, but not limited to, cell membrane stiffness, cell cytoskeleton mechanical properties, and the intensity and distribution of focal adhesions over the cell membrane. To compute and study the mechanical properties of tissues during growth and confluency, a theoretical and computational framework, called CellSim3D, was developed in our group based on a three-dimensional kinetic division model.

In this work, CellSim3D is …

A Highly Charged Topic: Intrinsically Disordered Proteins And Protein Pka Values, Carter J. Wilson

Electronic Thesis and Dissertation Repository

Intrinsically disordered proteins (IDPs) are known not only for their roles in disease but also for their conformational flexibility, which makes them elusive for experimentation. We consider the role played by theory and simulation in resolving important questions pertaining to IDP structure and dynamics, as well as the nature of the charged residues (e.g., glutamate, lysine, etc.) that enrich them. Specifically, we investigated how the deep learning trained AlphaFold2 (AF2) predictor estimates disorder content, revealing both strong performance in relation to conventional approaches and an important relationship between the AF2 confidence metric and IDP dynamics. We also assessed how modern …

Control Of Shear Layers Using Heating Patterns, Shoyon Panday

Electronic Thesis and Dissertation Repository

The presence of spatially modulated flows is universal in nature. Distributed heating and surface roughness are the most common elements to cause non-uniformity in the flows. Spatially distributed heating leads to fundamentally distinct convection, different from the classical Rayleigh-Bénard instability. Interestingly, the onset of convective motion due to horizontal temperature gradients requires no critical conditions – a forced response. At the same time, surface roughness is known to significantly influence flow behaviours and heat transfer characteristics. The current work aims to analyze modulated flows and assess their potential as a mixing technique for low Reynolds number flows. Spanwise modulations (perpendicular …

Multiple Endpoints In Randomized Controlled Trials: A Review And An Illustration Of The Global Test, Lindsay Cameron

Electronic Thesis and Dissertation Repository

A randomized controlled trial is often used to provide high quality evidence regarding treatment interventions. Due to the complex nature of many diseases, trials usually select multiple primary outcomes to capture the efficacy of the interventions. In this thesis, we conducted a literature search to determine the prevalence of the different types of multiple outcomes that have been used in randomized controlled trials. We also reviewed the corresponding statistical methods used to deal with such outcomes. In addition, we described the benefits of using global tests as a statistical method when there are multiple primary outcomes in order to answer …

New Aspects Of Scattering Amplitudes, Higher-K Amplitudes, And Holographic Quark Gluon Plasmas, Bruno Giménez Umbert

Electronic Thesis and Dissertation Repository

We present new results on different aspects of quantum field theory, which are divided into three main parts. In part I, we find and prove a new behavior of massless tree-level scattering amplitudes, including the biadjoint scalar theory, the U(N) non-linear sigma model, and the special Galileon, within specific subspaces of the kinematic space. We also derive new formulas for the double-ordered biadjoint scalar and $\phi^p$ amplitudes, which can be obtained as integrals over the positive tropical Grassmannian and under limiting procedures on the kinematic invariants. This reveals surprising connections with cubic amplitudes. We also present alternative versions of the …

A Computational Framework For Identifying Relevant Cell Types And Specific Regulatory Mechanisms In Schizophrenia Using Data Integration Methods, Kayvan Shabani

Electronic Thesis and Dissertation Repository

Combining multiple data types can help researchers gain deeper insight into the subject of the study compared to analyzing only one dataset in many cases. Biological researchers can also benefit from these methods of integration. For instance, GWAS data that gives information about variations in the DNA cannot provide us with much information about the specific biological components that are significant in the trait of interest. However, when combined with sequencing data such as chromatin accessibility data or gene expression data, they can help us find the significant biological elements in the trait of interest. In this study, I perform …

Denoising-Based Domain Adaptation Network For Eeg Source Imaging, Runze Li

Electronic Thesis and Dissertation Repository

Electrophysiological source imaging (ESI) is a widespread and no-invasive technique in neuroscientific research and clinical diagnostics. It provides a well-established and high temporal resolution of source activity and gives the brain signal by analyzing the corresponding EEG signal.

However, it is still a major challenge to deal with the domain shift problem between the datasets of different subjects or sessions in ESI problem. Furthermore, the variable noise included in the EEG signals inevitably influence the accuracy of localization of source activity.

In this paper, we propose a novel denoising autoencoder-based unsupervised domain adaptation (DAE-UDA) algorithm to tackle these problems. To …

Citation Polarity Identification From Scientific Articles Using Deep Learning Methods, Souvik Kundu

Electronic Thesis and Dissertation Repository

The way in which research articles are cited reflects how previous work is utilized by other researchers or stakeholders and can indicate the impact of that work on subsequent experiments. Based on human intuition, citations can be perceived as positive, negative, or neutral. While current citation indexing systems provide information on the author and publication name of the cited article, as well as the citation count, they do not indicate the polarity of the citation. This study aims to identify the polarity of citations in scientific research articles using pre-trained language models like BERT, ELECTRA, RoBERTa, Bio-RoBERTa, SPECTER, ERNIE, LongFormer, …

Topographic Effects Of Shallow Crustal Earthquakes In The Greater Vancouver Region, Alex Vanderhoeff

Electronic Thesis and Dissertation Repository

Vancouver has a high seismic risk due to the proximity of the city to the Cascadia subduction zone offshore, the soft sediments the metropolitan region overlies, and the mountainous topography nearby. The soft sediments and mountainous topography could cause an increase in shaking due to the sedimentary basin, topographic resonance and constructive/destructive interference, respectively. Numerical three-dimensional (3D) wave propagation simulations (WPS) were run using a finite difference scheme developed by Peterson and Sjogreen (2012), Seismic Waves, 4^th order, to perform simulations of large shallow crustal rupture scenario earthquakes using the 1994 M6.7 Northridge, California earthquake slip distribution. The …

A Hybrid Continual Machine Learning Model For Efficient Hierarchical Classification Of Domain-Specific Text In The Presence Of Class Overlap (Case Study: It Support Tickets), Yasmen M. Wahba

Electronic Thesis and Dissertation Repository

In today’s world, support ticketing systems are employed by a wide range of businesses. The ticketing system facilitates the interaction between customers and the support teams when the customer faces an issue with a product or a service. For large-scale IT companies with a large number of clients and a great volume of communications, the task of automating the classification of incoming tickets is key to guaranteeing long-term clients and ensuring business growth.

Although the problem of text classification has been widely studied in the literature, the majority of the proposed approaches revolve around state-of-the-art deep learning models. This thesis …

Source-Free Domain Adaptation For Sleep Stage Classification, Yasmin Niknam

Electronic Thesis and Dissertation Repository

The popularity of machine learning algorithms has increased in recent years as data volumes have risen, algorithms have advanced, and computational power and storage have improved. EEG-based sleep staging has become one of the most active research areas over the last decade. Labeling each sleep stage manually is a labor-intensive and time-consuming process that requires expertise, making it susceptible to human error. In the meantime, training models on an unseen dataset remains challenging due to physiological differences between subjects and electrode sensor configurations. Unsupervised domain adaptation approaches may provide a solution to this problem by borrowing knowledge from a labeled …

Ai Applications On Planetary Rovers, Alexis David Pascual

Electronic Thesis and Dissertation Repository

The rise in the number of robotic missions to space is paving the way for the use of artificial intelligence and machine learning in the autonomy and augmentation of rover operations. For one, more rovers mean more images, and more images mean more data bandwidth required for downlinking as well as more mental bandwidth for analyzing the images. On the other hand, light-weight, low-powered microrover platforms are being developed to accommodate the drive for planetary exploration. As a result of the mass and power constraints, these microrover platforms will not carry typical navigational instruments like a stereocamera or a laser …

Reducing Negative Transfer Of Random Data In Source-Free Unsupervised Domain Adaptation, Anthony Wong

Electronic Thesis and Dissertation Repository

In domain adaptation, a model trained on one dataset (source domain) is applied to a different but related dataset (target domain). The most cutting-edge method is unsupervised source-free domain adaptation (SFDA), in which source data, source labels, and target labels are not available during adaptation. This thesis explores a realistic scenario where the target dataset includes some images that are unrelated to the adaptation process. This scenario can occur from errors in data collection or processing. We provide experiments and analysis to show that current state-of-the-art (SOTA) SFDA methods suffer significant performance drops under a specific domain adaptation setup when …

The Synthesis And Characterization Studies Of Modified Nucleobase In Pna And Dna, Gyeongsu Park

Electronic Thesis and Dissertation Repository

Nucleic acids have been extensively studied not only for their importance in biological systems as the medium of genetic information but also for their potential uses in therapeutic, diagnostic and other biological applications. As such, modified oligonucleotides and oligonucleotide analogues have drawn the attention of researchers from various disciplines. Modification of oligonucleotides can enhance their desired characteristics and engender unique properties, such as fluorescence, giving rise to a variety of applications. Peptide nucleic acid (PNA) is an oligonucleotide mimic with a pseudo-peptide backbone based on N-(2-aminoethyl)glycine that is renowned for high target binding affinity and resistance to enzyme degradation. …

Use Of Electrochemical Techniques And Statistical Analysis To Investigate The Pitting Probability Of Copper, Sina Matin

Electronic Thesis and Dissertation Repository

The development of a safe permanent disposal plan is essential for the long-term disposal of used fuel bundles. Nuclear Waste Management Organization (NWMO) has been investigating the deep geologic disposal of nuclear waste which offers the optimum passive safety system with a negligible probability of release of radionuclides into the environment.

The proposed used fuel containers (UFC) for the permanent disposal of high-level nuclear waste in Canada is comprised of a carbon steel vessel coated with a 3 mm corrosion-resistant copper layer deposited using a combination of electrodeposition and cold spray deposition. Although copper is often considered to be thermodynamically …