Physical Sciences and Mathematics Commons^™

Smartphone Loss Prevention System Using Ble And Gps Technology, Noshin Tasnim

Electronic Thesis and Dissertation Repository

Being an all-in-one gadget, smartphones play a vital role in our everyday lives. However, millions of people suffer every year by losing their phones. A lost phone creates a huge security threat and data loss possibility to the users. Some preventive measures are available to protect from unauthorized access. Moreover, there are some post-loss solutions to track down, retrieve data from a lost locked phone, and protect the privacy and security of lost phone data, but those have some drawbacks as well. Considering the situation, our proposed system offers a preventive solution which will protect the smartphones from getting lost. …

Global Cyber Attack Forecast Using Ai Techniques, Nusrat Kabir Samia

Electronic Thesis and Dissertation Repository

The advancement of internet technology and growing involvement in the cyber world have made us prone to cyber-attacks inducing severe damage to individuals and organizations, including financial loss, identity theft, and reputational damage. The rapid emergence and evolution of new networks and new opportunities for businesses and technologies are increasing threats to security vulnerabilities. Hence cyber-crime analysis is one of the wide range applications of Data Mining that can be eventually used to predict and detect crime. However, there are several constraints while analyzing cyber-attacks, which are yet to be resolved for more accurate cyber security inspection.

Although there are …

Connectome-Constrained Artificial Neural Networks, Jacob Morra

Electronic Thesis and Dissertation Repository

In biological neural networks (BNNs), structure provides a set of guard rails by which function is constrained to solve tasks effectively, handle multiple stimuli simultaneously, adapt to noise and input variations, and preserve energy expenditure. Such features are desirable for artificial neural networks (ANNs), which are, unlike their organic counterparts, practically unbounded, and in many cases, initialized with random weights or arbitrary structural elements. In this dissertation, we consider an inductive base case for imposing BNN constraints onto ANNs. We select explicit connectome topologies from the fruit fly (one of the smallest BNNs) and impose these onto a multilayer perceptron …

Predicting Network Failures With Ai Techniques, Chandrika Saha

Electronic Thesis and Dissertation Repository

Network failure is the unintentional interruption of internet services, resulting in widespread client frustration. It is especially true for time-sensitive services in the healthcare industry, smart grid control, and mobility control, among others. In addition, the COVID-19 pandemic has compelled many businesses to operate remotely, making uninterrupted internet access essential. Moreover, Internet Service Providers (ISPs) lose millions of dollars annually due to network failure, which has a negative impact on their businesses. Currently, redundant network equipment is used as a restoration technique to resolve this issue of network failure. This technique requires a strategy for failure identification and prediction to …

Data-Driven Exploration Of Coarse-Grained Equations: Harnessing Machine Learning, Elham Kianiharchegani

Electronic Thesis and Dissertation Repository

In scientific research, understanding and modeling physical systems often involves working with complex equations called Partial Differential Equations (PDEs). These equations are essential for describing the relationships between variables and their derivatives, allowing us to analyze a wide range of phenomena, from fluid dynamics to quantum mechanics. Traditionally, the discovery of PDEs relied on mathematical derivations and expert knowledge. However, the advent of data-driven approaches and machine learning (ML) techniques has transformed this process. By harnessing ML techniques and data analysis methods, data-driven approaches have revolutionized the task of uncovering complex equations that describe physical systems. The primary goal in …

The Effect Of Hydrogen Peroxide On The Corrosion Dynamics Of Carbon Steel, Kwang Soak Gabriel O'Donnell

Electronic Thesis and Dissertation Repository

The Used Fuel Container (UFC) is a key barrier in Canada’s nuclear fuel disposal plan. Understanding the radiation-induced corrosion of the carbon steel (CS) vessel is critical for predicting the long-term integrity of the UFC. Developing a mechanistic understanding of CS corrosion and the effect of solution parameters is essential.

This work investigates the effects of H₂O₂, the key radiolytic oxidant, on CS corrosion dynamics in small, stagnant solutions. Elementary processes are identified, corrosion rates are calculated, and the effects of H₂O₂ concentration are investigated. Corrosion was studied by quantifying the concentrations of …

Generating Polynomials Of Exponential Random Graphs, Mohabat Tarkeshian

Electronic Thesis and Dissertation Repository

The theory of random graphs describes the interplay between probability and graph theory: it is the study of the stochastic process by which graphs form and evolve. In 1959, Erdős and Rényi defined the foundational model of random graphs on n vertices, denoted G(n, p) ([ER84]). Subsequently, Frank and Strauss (1986) added a Markov twist to this story by describing a topological structure on random graphs that encodes dependencies between local pairs of vertices ([FS86]). The general model that describes this framework is called the exponential random graph model (ERGM).

In the past, determining when a probability distribution has strong …

Data Heterogeneity And Its Implications For Fairness, Ghazaleh Noroozi

Electronic Thesis and Dissertation Repository

Data heterogeneity, referring to the differences in underlying generative processes that produce the data, presents challenges in analyzing and utilizing datasets for decision-making tasks. This thesis examines the impact of data heterogeneity on biases and fairness in predictive models. The research investigates the correlation between heterogeneity and protected attributes, such as race and gender, and explores the implications of such heterogeneity on biases that may arise in downstream applications.

The contributions of this thesis are fourfold. Firstly, a comprehensive definition of data heterogeneity based on differences in underlying generative processes is provided, establishing a conceptual framework for understanding and quantifying …

On Computing Optimal Repairs For Conditional Independence, Alireza Pirhadi

Electronic Thesis and Dissertation Repository

This thesis focuses on the concept of Conditional Independence (CI) and its testing, which holds immense significance across various fields, including economics, social sciences, and biomedical research. Notably, within computer science, CI has become an integral part of building probabilistic and causal models. It aids efficient inference and plays a key role in uncovering causal relationships.

The primary aim of this thesis is to broaden the scope of CI beyond its testing aspect. We introduce the pioneering problem of data repair, designed to adhere to particular CI constraints. The value and pertinence of this problem are highlighted through two contrasting …

Weakly-Supervised Anomaly Detection In Surveillance Videos Based On Two-Stream I3d Convolution Network, Sareh Soltani Nejad

Electronic Thesis and Dissertation Repository

The widespread adoption of city surveillance systems has led to an increase in the use of surveillance videos for maintaining public safety and security. This thesis tackles the problem of detecting anomalous events in surveillance videos. The goal is to automatically identify abnormal events by learning from both normal and abnormal videos. Most of previous works consider any deviation from learned normal patterns as an anomaly, which may not always be valid since the same activity could be normal or abnormal under different circumstances. To address this issue, the thesis utilizes the Two-Stream Inflated 3D (I3D) Convolutional Networks to extract …

Towards Clinical Microscopic Fractional Anisotropy Imaging, Nico Jj Arezza

Electronic Thesis and Dissertation Repository

Microscopic fractional anisotropy (µFA) is a diffusion-weighted magnetic resonance imaging (dMRI) metric that is sensitive to neuron microstructural features without being confounded by the orientation dispersion of axons and dendrites. µFA may potentially act as a surrogate biomarker for neurodegeneration, demyelination, and other pathological changes to neuron microstructure with greater specificity than other dMRI techniques that are sensitive to orientation dispersion, such as diffusion tensor imaging. As with many advanced imaging techniques, µFA is primarily used in research studies and has not seen use in clinical settings.

The primary goal of this Thesis was to assess the clinical viability of …

Towards Automated Mineral Identification In Martian Rocks From X-Ray Diffraction Patterns, Luke Tambakis

Electronic Thesis and Dissertation Repository

The CheMin (Chemistry and Mineralogy) instrument on the Curiosity rover has provided a rich set of X-ray diffraction (XRD) patterns from Martian rocks and regolith. These XRD patterns have allowed geologists to make exciting new discoveries about the mineralogy and the geological history of Mars. These discoveries pave the way for further Martian exploration and provide a deeper understanding of Martian geology. The Curiosity rover is very slow by design, travelling at about 4 cm/s. New, faster rovers are being developed to increase scientific throughput and exploration. XRD is valuable for future missions as it can produce new discov- eries …

Application Of Crystal Engineering In Multicomponent Pharmaceutical Crystals: A Study Of Theory And Practice, Soroush Ahmadi Nasrabadi

Electronic Thesis and Dissertation Repository

Multicomponent crystallization, a prominent strategy in crystal engineering, offers the ability to modify the physicochemical properties of crystals by introducing a secondary component to their lattice structure. Such multicomponent crystals have found widespread application in the pharmaceutical industry. This thesis explores the experimental screening, characterization, application, and theoretical prediction of multicomponent crystals of Active Pharmaceutical Ingredients (APIs).

The first case study investigates a new solvate of Dasatinib which exhibits high instability at room temperature and transforms into a different polymorph upon desolvation. The crystal structure of this compound is obtained, revealing insights into its transient nature and the potential application …

Investigating Novel Luminescent Materials Towards Applications In Light Emitting Electrochemical Cells, Kenneth Chu

Electronic Thesis and Dissertation Repository

The search for new and better luminescent materials is becoming increasingly important, as there are significant cost-savings in using luminophores that are brighter and more efficient. Carbon quantum dots (CQDs) and other luminescent materials such as Pt-Ag nanoclusters and TADF compounds are an extremely appealing alternative to existing light-emitting materials, as they are low-cost, easy to synthesize, and non-toxic.

This thesis explores the properties and performance of different luminescent materials to be used in light-emitting electrochemical cells (LECs). In this work, we focused on LECs as their low cost and ease of fabrication aligns well with the ethos of CQDs …

Petrophysical Properties Of The Hed Meteorites And The Bushveld Igneous Complex: Implications For Future Asteroid Prospecting Missions, Lukas Louwerse

Electronic Thesis and Dissertation Repository

In this work, I make a quantitative and mineralogical comparison of Howardite-EuctriteDiogenite (HED) meteorites with terrestrial samples from the Bushveld Igneous Complex (BIC) to assess how geophysical surveys of 4 Vesta or of V-type asteroids could detect BIClike ore deposits. Petrophysical methods in this work include bulk and grain density, derived porosity (using helium pycnometry, the Archimedean method, and X-ray micro-computed tomography), magnetic susceptibility, induced polarization and resistivity, and P-wave velocity. Mineralogical methods in this work include optical microscopy, micro X-ray diffraction, micro X-ray fluorescence element mapping, and electron beam methods. Howardite NWA 15199 was classified as part of this …

Effect Of Morphology And An Upstream Tall Building On A Street Canyon Flow, Haoran Du

Electronic Thesis and Dissertation Repository

The effects of the morphological model and the existence of an upstream tall building on the turbulent street canyon flow and the overlying boundary layer are investigated in a wind tunnel, using Stereoscopic Particle Image Velocimetry (S-PIV) measurements. The velocity variances, Reynolds shear stress, and turbulent kinetic energy are found to be larger than in a similar idealized street canyon model. Increasing building height results in a decrease in vertical mass fluxes across the opening of the canyon, at least in the canyon portion directly downstream of the building. The interaction between the large-scale structures in the overlying boundary layer …

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 …

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.

Study On The Self-Repairing Effect Of Nanoclay In Powder Coatings For Corrosion Protection, Marshall S. Yang, Jinbao Huang, Hui Zhhang, James Noel, Yolanda S. Hedberg, Jian Chen, Ubong Eduok, Ivan Barker, Jeffrey D. Henderson, Chengqian Xian, Haiping Zhang, Jesse Zhu

Chemistry Publications

Powder coatings are a promising, solvent-free alternative to traditional liquid coatings due to the superior corrosion protection they provide. This study investigates the effects of incorporating montmorillonite-based nanoclay additives with different particle sizes into polyester/triglycidyl isocyanurate (polyester/TGIC) powder coatings. The objective is to enhance the corrosion-protective function of the coatings while addressing the limitations of commonly employed epoxy-based coating systems that exhibit inferior UV resistance. The anti-corrosive and surface qualities of the coatings were evaluated via neutral salt spray tests, electrochemical measurements, and surface analytical techniques. Results show that the nanoclay with a larger particle size of 18.38 µm (D50, …

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 …

Skin Permeation Studies Of Chromium Species - Evaluation Of A Reconstructed Human Epidermis Model., L Hagvall, M Munem, M Hoang Philipsen, M Dowlatshahi Pour, Yolanda S. Hedberg, P Malmberg

Chemistry Publications

A reconstructed human epidermis (RHE) model, the EpiDerm, was investigated and compared to human skin ex vivo regarding tissue penetration and distribution of two chromium species, relevant in both occupational and general exposure in the population. Imaging mass spectrometry was used in analysis of the sectioned tissue. The RHE model gave similar results compared to human skin ex vivo for skin penetration of Cr

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), …

Investigating The Structure Of The Oxide On Ni-Cr-Mo Alloys While Presenting A Method For Analysis Of Complex Oxides Using Quases, Adam M. Morgan, Jeffrey D. Henderson, Brad A. Kobe, Mark Biesinger, James J. Noel

Chemistry Publications

X-ray photoelectron spectroscopy (XPS) is a technique that is widely used to studythin oxide films because of its extremely high surface sensitivity. Utilizing theQUASES (Quantitative Analysis of Surfaces by Electron Spectroscopy) software pack-age developed by Sven Tougaard (University of Southern Denmark), a user canobtain additional information that is not extracted in conventional XPS analysis, spe-cifically the composition as a function of depth. Presented here is the QUASES analy-sis of four Ni-Cr-Mo alloys performed while testing various inelastic mean free path(IMFP) determination methods in the context of providing a framework for the analy-sis of complex oxides in QUASES. Ni-Cr-Mo alloys are …

Sex Differences In The Clinical Presentation Of Early Psychosis In A Primary Care Setting, Brooke Carter, Rebecca Rodrigues, Jennifer Reid, Suzanne Archie, Amanda L Terry, Lena Palaniyappan, Arlene G Macdougall, Aristotle Voineskos, Saadia Hameed Jan, Liisa Jaakkimainen, Branson Chen, Neo Sawh, Kelly K. Anderson

Epidemiology and Biostatistics Publications

Primary care is an important part of the help-seeking pathway for young people experiencing early psychosis, but sex differences in clinical presentation in these settings are unexplored. We aimed to identify sex differences in clinical presentation to primary care services in the 1-year period prior to a first diagnosis of psychotic disorder. We identified first-onset cases of non-affective psychotic disorder over a 10-year period (2005-2015) using health administrative data linked with electronic medical records (EMRs) from primary care (n = 465). Detailed information on encounters in the year prior to first diagnosis was abstracted, including psychiatric symptoms, other relevant behaviours, …

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 …

Explainable Software Defect Prediction From Cross Company Project Metrics Using Machine Learning, Susmita Haldar, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

Predicting the number of defects in a project is critical for project test managers to allocate budget, resources, and schedule for testing, support and maintenance efforts. Software Defect Prediction models predict the number of defects in given projects after training the model with historical defect related information. The majority of defect prediction studies focused on predicting defect-prone modules from methods, and class-level static information, whereas this study predicts defects from project-level information based on a cross-company project dataset. This study utilizes software sizing metrics, effort metrics, and defect density information, and focuses on developing defect prediction models that apply various …