Physical Sciences and Mathematics Commons^™

Usability-Driven Security Enhancements In Person-To-Person Communication, Tarun Kumar Yadav

Theses and Dissertations

In the contemporary digital landscape, ensuring secure communication amid widespread data exchange is imperative. This dissertation focuses on enhancing the security and privacy of end-to-end encryption (E2EE) applications while maintaining or improving usability. The dissertation first investigates and proposes improvements in two areas of existing E2EE applications: countering man-in-the-middle and impersonation attacks through automated key verification and studying user perceptions of cryptographic deniability. Insights from privacy-conscious users reveal concerns about the lack of E2EE support, app siloing, and data accessibility by client apps. To address these issues, we propose an innovative user-controlled encryption system, enabling encryption before data reaches the …

The Effect Of Mechanical Strain On The Electronic Conductivity Of Α- Fe2o3: A Density Functional Theory Study, Sheriff Naziru Abdulmutalib

Theses and Dissertations

Hydrogen has emerged as a promising future energy carrier due to its ability to produce zero carbon dioxide (CO2) emissions when burned. However, the limited natural abundance of hydrogen necessitates the development of cost-effective and environmentally friendly methods for large-scale hydrogen production. Among the different hydrogen production approaches, photoelectrochemical water splitting, which employs a photoanode material in a cell using solar energy to split water into hydrogen and oxygen, is the focus of this work. α-Fe2O3 (hematite) is a photoanode material that shows a promising future for hydrogen generation in a photoelectrochemical cells due to its cheapness, availability, and its …

Analyzing Novel Metal Alloys For Glucose Sensing And Electrocatalysis, Anna Grace Boddy

Theses and Dissertations

In pharmaceutical and medicinal chemistry, metals and metal alloys often receive less attention compared to biological or organic compounds due to many factors including toxicity in the body for drug development or the cost of these metals. However, metals can play an important role in pharmaceuticals, having an impact on original cancer drugs, such as platinum used for head and neck tumors. Electrocatalysis is also another topic that receives less attention over topics such as chromatography in pharmaceuticals due to its potential toxic catalysts and voltages that could be harmful to the body. Electrocatalytic sensors can play an important role …

Open System Neural Networks, Bradley Hatch

Theses and Dissertations

Recent advances in self-supervised learning have made it possible to reuse information-rich models that have been generally pre-trained on massive amounts of data for other downstream tasks. But the pre-training process can be drastically different from the fine-tuning training process, which can lead to inefficient learning. We address this disconnect in training dynamics by structuring the learning process like an open system in thermodynamics. Open systems can achieve a steady state when low-entropy inputs are converted to high-entropy outputs. We modify the the model and the learning process to mimic this behavior, and attend more to elements of the input …

Developing Machine Learning And Time-Series Analysis Methods With Applications In Diverse Fields, Muhammed Aljifri

Theses and Dissertations

This dissertation introduces methodologies that combine machine learning models with time-series analysis to tackle data analysis challenges in varied fields. The first study enhances the traditional cumulative sum control charts with machine learning models to leverage their predictive power for better detection of process shifts, applying this advanced control chart to monitor hospital readmission rates. The second project develops multi-layer models for predicting chemical concentrations from ultraviolet-visible spectroscopy data, specifically addressing the challenge of analyzing chemicals with a wide range of concentrations. The third study presents a new method for detecting multiple changepoints in autocorrelated ordinal time series, using the …

Penalized Interpolating B-Splines And Their Applications, Kylee L. Hartman-Caballero

Theses and Dissertations

One of the most studied data analysis techniques in Numerical Analysis is interpolation. Interpolation is used in a variety of fields, namely computer graphic design and biomedical research. Among interpolation techniques, cubic splines have been viewed as the standard since at least the 1960s, due to their ease of computation, numerical stability, and the relative smoothness of the interpolating curve. However, cubic splines have notable drawbacks, such as their lack of local control and necessary knowledge of boundary conditions. Arguably a more versatile interpolation technique is the use of B-splines. B-splines, a relative of Bézier curves, allow local control through …

Photoluminescence Of Beryllium-Related Defects In Gallium Nitride, Mykhailo Vorobiov, Mykhailo Vorobiov

Theses and Dissertations

This study explores the potential of beryllium (Be) as an alternative dopant to magnesium (Mg) for achieving higher hole concentrations in gallium nitride (GaN). Despite Mg prominence as an acceptor in optoelectronic and high-power devices, its deep acceptor level at 0.22 eV above the valence band limits its effectiveness. By examining Be, this research aims to pave the way to overcoming these limitations and extend the findings to aluminum nitride and aluminum gallium nitride (AlGaN) alloy. Key contributions of this work include. i)Identification of three Be-related luminescence bands in GaN through photoluminescence spectroscopy, improving the understanding needed for further material …

Symmetry Analysis Of The Canonical Connection On Lie Groups:Co-Dimension Two Abelian Nilradical With Abelian And Non Abelian Complement, Nouf Alrubea Almutiben

Theses and Dissertations

We consider the symmetry algebra of the geodesic equations of the canonical
connection on a Lie groups. We mainly consider the solvable indecomposable four,
five and six-dimensional Lie algebras with co-dimension two abelian nilradical, that
have an abelian and not abelian complement. In this particular case, we have only
one algebra in dimension four namely; A4,12 , and three algebras in dimension five
namely; A5,33, A5,34, and A5,35 In dimension six, based on the list of Lie algebras in
Turkowski’s list, there are nineteen such algebras namely; A6,1- A6,19 that have an
abelian complement, and there are eight algebras that …

Stealthy Control Logic Attacks And Defense In Industrial Control Systems, Adeen Ayub

Theses and Dissertations

Industrial control systems (ICS) play a crucial role in monitoring and managing critical infrastructure, including nuclear plants, oil and gas pipelines, and power grid stations. Programmable logic controllers (PLCs) are a fundamental component of ICS, directly interfacing with physical processes and implementing control logic programs that govern operations. Due to their significance in controlling critical infrastructure, PLCs often become prime targets for attackers seeking to disrupt these systems. Exploitable vulnerabilities in PLCs render them susceptible to such attacks. While many attacks on PLCs leave a large footprint in network traffic and are detectable by intrusion detection systems (IDS), this dissertation …

Adaptive Multi-Label Classification On Drifting Data Streams, Martha Roseberry

Theses and Dissertations

Drifting data streams and multi-label data are both challenging problems. When multi-label data arrives as a stream, the challenges of both problems must be addressed along with additional challenges unique to the combined problem. Algorithms must be fast and flexible, able to match both the speed and evolving nature of the stream. We propose four methods for learning from multi-label drifting data streams. First, a multi-label k Nearest Neighbors with Self Adjusting Memory (ML-SAM-kNN) exploits short- and long-term memories to predict the current and evolving states of the data stream. Second, a punitive k nearest neighbors algorithm with a self-adjusting …

Optimizing Deep Inspiration Breath Hold Technique For Personalized Breast Cancer Radiotherapy, Srinidhi Rajagopalan

Theses and Dissertations

The purpose of this research is entrenched in advancing the practice of 3D Conformal Radiation Therapy (3D CRT) for breast cancer patients by meticulously evaluating the impact of different Deep Inspiration Breath Hold (DIBH) techniques on dosimetric parameters. This study aims to ascertain the quantitative benefits of varied breathing techniques, primarily focusing on the 'Ultimate DIBH' method's efficacy in sparing critical organs such as the heart and lungs.

The comprehensive analysis of different DIBH techniques in this research is not merely an academic exercise but is geared towards substantiating the hypothesized advantages of these techniques with empirical data. By generating …

Mathematical Modeling Of Phage-Bacteria Population Dynamics, John Lawrence D. Palacios

Theses and Dissertations

Bacteriophages are viruses that infect and replicate within bacteria. Lytic phages cause the bacterial cell to burst, killing the bacteria. These types of phages can be used to treat patients with antibiotic-resistant bacterial infections. As a step in developing successful treatment protocols, we aim to understand the population dynamics of phages and bacteria using an in vitro model. We model the dynamics using the Campbell model, which consists of a delay differential equation (DDE), as a base model. We extended the model by including the emergence of phage resistance. We then compared the DDE model with a parallel ordinary differential …

Towards Machine Learning-Based Control Of Autonomous Vehicles In Solar Panel Cleaning Systems, Farima Hajiahmadi

Theses and Dissertations

This thesis presents a machine learning (ML)-based approach for the intelligent control of Autonomous Vehicles (AVs) utilized in solar panel cleaning systems, aiming to mitigate challenges arising from uncertainties, disturbances, and dynamic environments. Solar panels, predominantly situated in dedicated lands for solar energy production (e.g., agricultural solar farms), are susceptible to dust and debris accumulation, leading to diminished energy absorption. Instead of labor-intensive manual cleaning, robotic cleaners offer a viable solution. AVs equipped to transport and precisely position these cleaning robots are indispensable for efficient navigation among solar panel arrays. However, environmental obstacles (e.g., rough terrain), variations in solar panel …

Adaptable And Trustworthy Machine Learning For Human Activity Recognition From Bioelectric Signals, Morgan S. Stuart

Theses and Dissertations

Enabling machines to learn measures of human activity from bioelectric signals has many applications in human-machine interaction and healthcare. However, labeled activity recognition datasets are costly to collect and highly varied, which challenges machine learning techniques that rely on large datasets. Furthermore, activity recognition in practice needs to account for user trust - models are motivated to enable interpretability, usability, and information privacy. The objective of this dissertation is to improve adaptability and trustworthiness of machine learning models for human activity recognition from bioelectric signals. We improve adaptability by developing pretraining techniques that initialize models for later specialization to unseen …

Large Language Models, Prompting, And Synthetic Data Generation For Continual Named Entity Recognition, Charles I. Cutler

Theses and Dissertations

With the ever-growing amount of textual data, the task of Named Entity Recognition (NER) is vital to Natural Language Processing (NLP), a field which focuses on enabling computers to understand and manipulate human language. NER enables the extraction of information from unstructured text. Accurate information extraction is crucial for applications ranging from information retrieval to systems for question-answering. To ensure that NER models are robust to changes in data distributions and capable of recognizing new entity types, one may consider expanding the capabilities of an existing model. Continual learning is a paradigm within machine learning. It studies the objective of …

Asymmetric Cuh-Catalyzed Reductive Coupling Of Allenamides With Carbonyl And Imine Electrophiles, Stephen Collins

Theses and Dissertations

The carbon scaffold of many drugs and natural products contain multiple stereogenic centers bearing heteroatoms. As a result of this, chemists have long sought methods to efficiently install these multi-heteroatom functionalities. Reductive coupling reactions have been extensively studied over the past decades, and the allylation of carbonyls via the reductive coupling approach has been a key method for generating chiral allylic alcohols. This work utilizes inexpensive Cu for the asymmetric reductive coupling of allenamides with carbonyls or imines to simultaneously install two heteroatoms (either oxygen and nitrogen or nitrogen and nitrogen, respectively) onto the product. These molecules have a polarity …

Paley Graphs, Prime Graphs, And Crossword Puzzles, Robert D. Jacobs Jr.

Theses and Dissertations

In this paper, we will talk about many different mathematical concepts. We will prove theorems about Paley graphs, prime graphs, and crossword puzzles. It will be very fun.

The results in the section about Paley graphs include structure theorems about the subgraph induced by the quadratic residues, the subgraph induced by the non-residues and a few related subgraphs. The main is to better understand the “independence structure” of the Paley graph itself. No good upper bound on the independence number of Paley graphs is known. Theorems about these subgraphs, and various counts aim at future improvement of upper bounds for …

Bayesian Estimation Of Hierarchical Linear Models From Incomplete Data: Cluster-Level Non-Linear Effects And Small Sample Sizes, Dongho Shin

Theses and Dissertations

We consider Bayesian estimation of a hierarchical linear model (HLM) from small sample sizes. The continuous response Y and covariates C are partially observed and assumed missing at random. With C having linear effects, the HLM may be efficiently estimated by available methods. When C includes cluster-level covariates having interactive or other nonlinear effects given small sample sizes, however, maximum likelihood estimation is suboptimal, and existing Gibbs samplers are based on a Bayesian joint distribution compatible with the HLM, but impute missing values of C by a Metropolis algorithm via a proposal density having a constant variance while the target …

Mathematical Modeling And Analysis Of Inflammation And Tissue Repair: Lung Inflammation And Wound Healing In Corals Under Stress, Quintessa Hay

Theses and Dissertations

A variety of insults, including tissue injury and/or exposure to pathogen, elicit an immune response in many organisms. An improperly regulated immune response can result in deleterious effects to the organism. Here we present models for lung injury in young and old mice and models for wound healing in coral reefs.

It is well known that the immune response becomes less effective in older individuals. This is of particular interest in pulmonary insults such as ventilator induced lung injury (VILI) or lung infection. We extended a mathematical model for the inflammatory response to VILI and used experimental data to select …

Measuring The Properties Of Rod-Shaped Bacteria By Single-Entity Electrochemistry, Ashley Tubbs

Theses and Dissertations

Antibiotic-resistant bacteria pose a significant and escalating threat to hospitals around the world, necessitating the development of rapid and sensitive detection methods. Single-entity electrochemistry has emerged as a promising approach for detecting and identifying such bacteria, and monitoring the efficacy of antibiotics in real-time. Herein, we employ the translational diffusion equation for circular cylinders to predict the collision frequency of rod-shaped bacteria, informing our experimental setup. Our work demonstrates that lab-fabricated Pt ultramicroelectrodes can sensitively detect bacteria at femtomolar concentrations under migration-controlled conditions. Further, we present a method implemented in MatLab to automate the analysis of step-like signals observed in …

Graph Coloring Reconfiguration, Reem Mahmoud

Theses and Dissertations

Reconfiguration is the concept of moving between different solutions to a problem by transforming one solution into another using some prescribed transformation rule (move). Given two solutions s₁ and s₂ of a problem, reconfiguration asks whether there exists a sequence of moves which transforms s₁ into s₂. Reconfiguration is an area of research with many contributions towards various fields such as mathematics and computer science.
The k-coloring reconfiguration problem asks whether there exists a sequence of moves which transforms one k-coloring of a graph G into another. A move in this case is a type …

Blockchain For Computational Integrity And Privacy, Rahul Raj

Theses and Dissertations

This study proposes a blockchain based system that utilizes fully homomorphic encryption to provide security of data in use as well as computational integrity. This is achieved by leveraging the attributes of blockchain which provides availability and data integrity combined with homomorphic encryption that provides confidentiality. The proposed system is designed to perform statistical operations, including mean, median and variance, on encrypted data, thus providing confidentiality of data while in use. The computations are performed on the smart contract, residing on the blockchain which provides computational integrity. The results indicate that it is possible to perform fully homomorphic computations on …

Mathematical Analysis Of Eukaryotic Pericentromere, Puranjan Ghimire

Theses and Dissertations

The centromere is crucial for chromosomal stability and their proper segregation during cell division in eukaryotes. Surrounding the centromere are pericentromeres, made of repetitive DNA elements called pericentromeric repeats, varying from 10 in fission yeast to thousands in humans. These repeats form densely packed heterochromatin, where genes are usually silenced. The silencing mechanism across different pericentromeric repeats remains unclear.

Despite variations in sequence and length, pericentromeric repeats are conserved across eukaryotes, indicating their functional importance. This dissertation presents mathematical models to quantify gene silencing in fission yeast and humans. In fission yeast, my model predicts that silencing occurs only with …

Problems In Graph Theory With Applications To Topology And Modeling Rna, Rayan K. Ibrahim

Theses and Dissertations

In this thesis, we explore four projects. In the first project, we explore $r$-neighbor bootstrap percolation on a graph $G$. We establish upper bounds for the number of vertices required to percolate in the case that $r=2$ for particular classes of graphs. In the second project, we study the structure of graphs with independence number two. We prove a lower bound on the number of edges of such graphs, related to an upper bound on the number of edges in a triangle-saturated graph, and give a sufficient forbidden induced subgraph condition for independence number two graphs. In the third project, …

Towards Energy-Efficient Edge Computing For Tiny Ai Applications, Vamsi Krishna Bhagavathula

Theses and Dissertations

As artificial intelligence (AI) applications become more common on the edge of networks, like Raspberry Pi servers, it is crucial to optimize their energy use. This research project investigates how AI algorithms affect energy efficiency and resource usage on Raspberry Pi servers. Two models were created: one predicts resource usage, and the other predicts power consumption of AI algorithms on Raspberry Pi. Several factors are considered like CPU and memory use, algorithm speed, dataset size, and types of algorithms and datasets. Using regression-based methods, we model how these factors affect energy use. By converting categorical factors into numerical ones, we …

Towards Effective Developer Communication In Open Source Software Via Emotional Awareness, Mia Mohammad Imran

Theses and Dissertations

Emotions play an integral yet understudied role in open-source software development, profoundly shaping critical collaborative processes such as knowledge sharing, decision-making, and team dynamics. However, accurately detecting and analyzing emotions in developer communications poses significant challenges due to the lack of visual and auditory cues in text-based interactions. This dissertation investigates techniques to enhance the understanding and modeling of emotions within the textual artifacts of open-source projects. We conduct an extensive evaluation of existing emotion classification tools using a novel dataset of annotated GitHub comments. An error analysis reveals deficiencies in handling implicit emotional expressions and figurative language. We demonstrate …

Machine Learning Assisted Optimization For Calculation And Automated Tuning Of Antennas, Lauren Linkous

Theses and Dissertations

The Antenna Calculation and Autotuning Tool (AntennaCAT) software suite represents a significant advancement in the field of antenna design by automating the entire design, CAD, simulation, and optimization process compatible with several EM simulation software suites. It is the first comprehensive implementation of machine learning in this context. In particular, this work includes the capability to create and export structured datasets from the aforementioned EM software for iterative improvement and includes an expandable selection of optimizers.

Understanding The Origin, Evolution, And Dynamics Of Transneptunian Binaries, Benjamin C N Proudfoot

Theses and Dissertations

This dissertation discusses research that focuses on understanding transneptunian objects (TNOs) using a variety of techniques and approaches. In Chapter 1, I introduce the main concepts used throughout this dissertation and discuss the current understanding of the transneptunian region. In Chapter 2, I discuss my efforts to understand how Neptune's late stages of migration affect the Haumea family, the only known collisional family in the transneptunian region. Using advanced simulations of Neptune migration, I find that the Haumea family can plausibly form before the termination of giant planet migration and show that this extensively mixes the family. The simplest explanation …

Progress Towards The Development Of Asymmetric Conditions For Intramolecular Heteroatom/Dehydro-Diels-Alder Reactions For Synthesizing Furo[3,4-C] Pyranones And Anticancer Podophyllotoxins, Peter Mpaata

Theses and Dissertations

Furo[3,4-c] pyranone is a unique bicyclic molecular structure found in bioactive sesquiterpene isobolivianine and in artificial cytotoxic stilbene derivatives. The structure of furo[3,4-c] pyranone is analogous to cyclopenta[c] pyran structure found in potent cytotoxic iridoids like catapol. Chiral substrates for intramolecular hetero-Diels-Alder (IHDA) reaction have been synthesized in yields ranging from 39% to 81%. These compounds undergo [4+2] cycloaddition via ambimodal/ bispericyclic process to give a mixture of furo[3,4-c] pyranone in yields ranging 40-70% and aryl tetralin lactone derivatives. Density functional theory (DFT) calculations have been performed to gain insight into the mechanism leading to the formation of these compounds. …

Simulating Government Institutions In Networked Societies, Michael Richards

Theses and Dissertations

Modern human societies give rise to the expression of complex group dynamics between the members of said society due to the abundance of continued interactions. Of particular interest are how institutions affect these interactions between societal members, alter the resulting group dynamics, and impact society as a whole through their rules. Simulating these dynamics allows for greater insight into how these institutions function and allows researchers to pose interesting questions and test hypotheses within a laboratory setting. We present a novel approach to simulating institutions, particularly governments, within a networked society. This approach builds upon the Junior High Game, which …