Physical Sciences and Mathematics Commons^™

Towards Visual Inertial Navigation With Fixed Tetrahedral Targets, Joao Leonardo Silva Cotta

Theses and Dissertations

This dissertation presents a robust method for 6DoF position estimation under impaired visual conditions utilizing a minimum 4-point Perspective-n-Point (P4P) solver designed for tetrahedral targets. Using SO(3) × R 3 instead of SE(3), the method uses a Lie group-based formulation to discriminate between rotation and translation, thereby enabling computationally efficient, resource-conscious op- optimization while preserving correct geometric behavior. Designed using the contemporary C++17 library ShomerTarget, the solver is analytically formulated and assessed under pragmatic robotic conditions. Particularly in low-light and high-dynamic environments, experiments on embedded systems, UAVs, and NASA’s Astrobee show that the proposed solver attains enhanced accuracy compared to …

Effects Of Reflective Journaling And Nudges On Academic Motivation And Engagement, Lakshmi Satya Sai Veda Mahita Uppuluri

Theses and Dissertations

This study investigates the effects of reflective journaling and motivational nudges on academic motivation and engagement among college students. Grounded in Self- Determination Theory (SDT), the research examines how different interventions influence intrinsic motivation, and academic behaviors such as class attendance, participation, and preparation. The study employed a between-group experimental design with three conditions: a control group, a journaling group, and a journaling group that also received daily motivational nudges. Results showed that students in the journaling groups—particularly those who received nudges—experienced a significant increase in academic motivation. While changes in academic engagement were not significant, the effect size suggested …

Stochastic Analysis With Operational Calculus In Reliability, Hend Hamdan Al-Jahani

Theses and Dissertations

Our dissertation models several reliability systems subject to occasional random shocks of random magnitudes W1,W2,..occurring at times tau0, tau2,..In Model 1, the underlying system becomes inoperational if it wears out due to aging specified by a monotone increasing continuous function Delta identifying system's wear at any time t>=0 . The system is deemed inoperational if delta crosses a sustainability threshold at some moment T=(delta )^-1(D). The precise time T is difficult to identify making the realistic failure time randomly delayed and thus identified at some opportune observation epoch. The system can also fail due to damages by external shocks, …

Personality Trait Recognition Through Deep Neural Temporal Modeling Of Non-Verbal Behavior, Kushal Vangara

Theses and Dissertations

Personality research seeks to explain the wide range of human behaviors through stable, measurable traits. Human interactions are inherently rich and multidimensional, and analyzing behavioral data offers a promising path to uncover personality insights. The increasing convergence of psychology, computer science, and machine learning has fueled interest in computational approaches to personality assessment. Advances in sensing technologies have made it possible to capture fine-grained information about individuals’ behaviors and interactions in naturalistic and controlled environments. Automated audio-visual analysis techniques extract relevant behavioral cues, which machine learning models then interpret to infer underlying personality traits. This work provides a comprehensive overview …

How Will Artificial Intelligence Impact The Roles, Skills, And Design Processes Of Ux Professionals In The Next 5 Years?, Olivia Behan

Informatics

Artificial intelligence (AI) is changing the way we think about user experience (UX) design. This thesis explores how AI could impact the roles, skills, and design processes of UX professionals over the next five years. The research conducted consists of a mixed-methods approach, combining an online survey administered through Qualtrics to 50 survey respondents and a case study, which included individually interviewing 3 UX professionals over Zoom, to gather data and personal insights. The results show that while AI has the power and potential to make some parts of UX work faster, like research analysis, prototyping, and automating redundant tasks, …

Geometric Algebra For Field Theory In Curved Spacetime, Kevin Rhine

All Graduate Reports and Creative Projects, Fall 2023 to Present

Physics seeks to understand the universe by uncovering the fundamental laws that govern matter, energy, space, and time. At its heart lies the challenge of unification: finding a mathematical framework that consistently describes these interactions across all scales, from the subatomic to the cosmological.

This thesis explores geometric algebra, a mathematical language that unifies algebra and geometry, as a tool for advancing this understanding. By extending this framework to curved spacetimes, where gravity influences the structure of space and time, we investigate its ability to describe physical phenomena such as electromagnetism and general relativity. A notable contribution includes the geometric …

Aleci: An R Package For Non-Parametric Confidence Intervals On Accumulated Local Effects Plots, Matthew R. Lister

All Graduate Reports and Creative Projects, Fall 2023 to Present

Machine learning models can take a collection of inputs and craft an output. The mathematical formulas these models use to calculate their outputs easily become too complex or time consuming for a human to analyze. Collectively, we refer to these as black box models. Accumulated local effects plots (ALE) are a method for adding interpretability and visibility into the effects that individual variables contribute to the predictions made by black box models. The method designed by D.W. Apley calculates equally spaced point estimates of the response value to construct a graph across the range of the variable of interest. AleCI …

Jwst Reveals The Diversity Of Nuclear Obscuring Dust In Nearby Agn: Nuclear Isolation Of Miri/Mrs Data Cubes And Continuum Spectral Fitting, Omaira González-Martín, Daniel J. Díaz-González, Mariela Martínez-Paredes, Almudena Alonso-Herrero, Enrique López-Rodríguez, Begoña García-Lorenzo, Cristina Ramos Almeida, Ismael García-Bernete, Donaji Esparza-Arredondo, Sebastian F. Hoenig, Santiago García-Burillo, Chris Packham, Nancy A. Levenson, Alvaro Labiano, Miguel Pereira-Santaella, Francoise Combes, Anelise Audibert, Erin K.S. Hicks, Lulu Zhang, Enrica Bellocchi, Richard I. Davies, Laura Hermosa Muñoz, Masatoshi Imanishi, Claudio Ricci, Marko Stalevski

Faculty Publications

We investigate the capabilities of the mid-infrared instrument (MIRI) of JWST to advance our knowledge of active galactic nucleus (AGN) dust using the spectral fitting technique on an AGN collection of 21 nearby (z < 0.05) AGN (7 type-1 and 14 type-2) observations obtained with the medium resolution spectroscopy (MRS) mode. This collection includes publicly available AGN and data from the collaboration of Galactic Activity, Torus, and Outflow Survey (GATOS). We developed a tool named MRSPSFisol that decomposes MRS cubes into point-like and extended contributions. We found statistically good fits for 12 targets with current AGN dust models. The model that provides good fits (χ²/dof< 2) for these 12 targets assumes a combination of clumpy and smooth distribution of dust in a flare-disc geometry where the dust grain size is a free parameter. Still, two and one AGN statistically prefer the disc + wind and the classical clumpy torus model, respectively. However, the currently available models fail to reproduce 40 per cent of the targets, likely due to the extreme silicate features not well reproduced by the models and signatures of water-ice and aliphatic hydrocarbon absorption features in most targets. New models exploring, for instance, new chemistry, are needed to explain the complexity of AGN dust continuum emission observed by JWST.

Chemistry Education At The University Of Southern Mississippi Through Computation And Active Learning Methods, Sadie Pitre

Honors Theses

Education is one of the pillars of society. It evolves alongside scientific progress, shaping how students learn and engage with complex topics. The incorporation of new educational standards at The University of Southern Mississippi (USM) was implemented in two parts: through computational chemistry laboratory exercises for teaching laboratories and through the synthesis of organic molecules for research projects in an upper-level spectroscopy class. The goal of these projects is to improve learning of abstract and/or complex topics beyond the teaching methods traditionally utilized in the undergraduate laboratory and in the classroom.

Computational chemistry, which uses theoretical calculations to model molecular …

A Comprehensive Performance Comparison Of Machine Learning And Federated Learning For Intrusion Detection In Vehicular Ad-Hoc Networks Using Can-Bus Data, Tim Leonhardt

Honors Theses

Federated Learning (FL) is a Machine Learning (ML) approach that decentralizes training across distributed devices, eliminating the need to centralize data. Unlike traditional ML, where models are trained on aggregated data, FL sends a global model to multiple nodes for local training, with updated parameters transmitted back to the server for aggregation. This process preserves data privacy, making FL ideal for sensitive applications like cybersecurity. However, FL introduces challenges such as data heterogeneity, communication overhead, and difficulties in achieving model convergence, which can impact performance.

This study investigates a fundamental assumption in ML and FL research: that the superior performance …

Cache-Augmented Generation In Rag Pipelines: Fast And Memory-Efficient Approach To Multi-Agent Knowledge Query Systems, Yaju Gopal Shrestha

Honors Theses

This thesis presents an implementation and evaluation of Cache-Augmented Generation (CAG) for knowledge query systems, building upon the approach introduced by Chan et al. (2024). Traditional Retrieval-Augmented Generation (RAG) systems (Lewis et al., 2020) face challenges including high latency, excessive memory usage, and complex infrastructure requirements. By implementing a cache-augmented architecture that preloads relevant knowledge and eliminates real-time retrieval, our approach significantly improves response time while reducing resource requirements. The research demonstrates the effectiveness of CAG through a comprehensive implementation for The University of Southern Mississippi's chatbot system, achieving a 49.02% improvement in response time compared to traditional RAG approaches. …

Cellular Telemetry For Real-Time River Flow Velocity Data From Fluvial Acoustic Tomography Loggers, Joshua Lee Seymour

Honors Theses

Streamflow is a critical element in understanding watershed processes and the effects of land use on those processes because it is the primary medium through which water, sediment, nutrients, organic material, thermal energy, and aquatic species move. Fluvial Acoustic Tomography (FAT) systems offer accurate direct measurements of river section-averaged flow velocity by measuring reciprocal acoustic travel times between at least two acoustic nodes positioned on opposite riverbanks. However, similar to many in-situ sensors used in estuarine and riverine environments, FAT loggers require manual data retrieval, which is time-consuming, labor-intensive, and limits real-time access and increases maintenance costs. This project presents …

The Numerical Method For Finding All The Zeros Of A Function F (X) On An Interval [A,B], Franissa Simon

Honors Theses

In this study, we develop a simple mathematical method for finding all the roots of a function on a specified interval. Existing classical numerical methods, including the Bisection Method, Secant Method, and Newton Method, cannot find all the zeros of a function f (x) on an interval [a,b]. Popular numerical root solvers like Matlab’s ‘fzero’, Maple’s ‘fsolve’, and SageMath’s ‘find_root’ typically yield only a single zero. This thesis explores a proposed interval computation bisection method, a systematic approach based on the traditional Bisection Method and interval computation. Unlike traditional bisection, which relies on the intermediate value theorem, this approach uses …

Investigation Into The Effectiveness Of G-C3n4 For The Degradation Of Indigo Dye In Aqueous Solution Via Electrocatalysis, Rolando R. Barron Jr

Theses and Dissertations

Indigo dye (IUPAC 2-(3-hydroxy-1H-indol-2-yl)indol-3-one) is one of the most used dyes in the textile industry worldwide with more than 40,000 tons produced each year. It can elicit adverse physiological responses in humans including vomiting, diarrhea, and other gastrointestinal conditions, and it is toxic in large amounts. There is also evidence to suggest that indigo is a teratogen and genotoxic in aquatic life. Environmentally, the enormous amount of indigo used in the textile industry has caused rivers and waterways to run blue as well as severely impacting aquatic and plant ecosystems. The chemicals used in its synthesis are also …

Joint Modelling Of Longitudinal Egfr Trajectory And Time To Acute Kidney Injury In Lung Transplant Patients, Samiha Zakir

Theses and Dissertations

Progressive declines in estimated glomerular filtration rate (eGFR) often precede acute kidney injury (AKI), yet the relationship between eGFR trends and AKI risk remains unclear. This study investigates longitudinal eGFR changes and their association with AKI in 459 lung transplant patients followed for up to 7 years (n = 6419). We applied a piecewise linear mixed-effects model to evaluate eGFR trajectories and a Cox proportional hazards model to assess time to AKI. A joint model was used to explore the interplay between longitudinal and survival processes. Key covariates included gender, age at transplantation, antibody-mediated rejection (AMR), and pre-transplant eGFR. Males …

Hydrothermal Synthesis Of Single-Crystal Magnetic Oxides, Bhakti Patel

All Dissertations

Multifunctional materials are systems that have two or more properties of interest. Some of these features are polar axes, chirality, magnetic ions, triangular arrangements, and/or magnetically silent building blocks. Various combinations of these properties can result in chiral ferromagnetism, multiferroic magnetoelectric behavior, antiferromagnetism, and quantum spin liquids and spin ices. By tuning these structure-property relations, quantum computing, memory, and sensors may be created. Large single crystals allow for a better understanding of the magnetic behavior of these crystals since they can be oriented in a magnetic field. Inorganic single crystals have a wide range of applications but growing high-quality single …

Biophysical Studies Of Nucleic Acid - Small Molecule Recognition, Andrea Conner

All Dissertations

The presented work is a collection of studies performed to examine small molecule recognition of nucleic acids. Recognition of nucleic acids was examined using two types of small molecules: aminoglycosides and Hoechst dyes. Chapter One focuses on established experimental techniques (i.e. absorbance, isothermal titration calorimetry, flow cytometry, cell microscopy, etc.) in small molecule recognition of nucleic acids. The emphasis of studies in the group has been on two focus areas. (i) Thermodynamic characterization of mixed A-form and B-form DNA or RNA conformation with aminoglycosides, particularly neomycin-class. (ii) Characterization of new Hoechst-morpholine (HT-MO) derivatives’ interactions with nucleic acids.

Focus area (i) …

Exploring The Pedagogical Impact Of Software Development Live Streams: Informal Learning Opportunities For Software And Game Developers, Ella Kokinda

All Dissertations

Live streaming is an increasingly popular medium for throwing back the curtain on software development where streamers and viewers share their knowledge and experiences. Popular platforms like Twitch and YouTube enable developers to stream live coding sessions where people around the world can engage in real-time collaboration, feedback, knowledge sharing, and skill development. This work investigates the pedagogical implications and learning opportunities present in software and game development live streaming while focusing on the role of streaming as a learning environment and collaborative community. We begin by exploring summer camps as an informal learning opportunity for STEM education, highlighting the …

Countering Deficit Narratives Through A Blackcrit Lens By Examining Case Studies Of Black College Mathematics Students’ Classroom Experiences, Akhenaton Wilbourn

All Dissertations

This dissertation examines the lived experiences of 11 Black college mathematics students at their predominantly white institution (PWI) through the lens of Black Critical Theory (BlackCrit) to counter deficit narratives about the racial achievement gap (RAG) in mathematics education courses. Deficit narratives often attribute disparities between Black and white students’ mathematical performance to assumed deficiencies in Black students’ abilities rather than systemic inequities, historical marginalization, and ongoing anti-Blackness in educational settings (Cobb & Russell, 2015; Kress, 2021). Using multiple case studies, this study explores how anti-Blackness manifests in mathematics classrooms, how students navigate tensions between multiculturalism, neoliberal educational policies, and …

Probing The 'Mev Gap': Discovery And Characterization Of Persistent And Transient Mev-Gev Gamma-Ray Sources With The Fermi Large Area Telescoope, Scott Joffre

All Dissertations

The MeV Gap is a moniker for the energy regime E~0.1-100 MeV that has lacked sensitive observations for the last 20 years. This is not out of scientific disinterest, but observational challenges. The only instrument currently available to make observations in the MeV Gap is the Fermi Large Area Telescope (LAT). For the first time ever, Fermi-LAT has been leveraged to push its observational capabilities to its absolute lower energy limit to end this 20-year observational gap. Observing the MeV sky is imperative for identifying some of the most luminous galaxies in the Universe known as blazars. The brightest blazars …

The Effect Of Nuclear Isomers On S-Process Nucleosynthesis, Jaad Tannous

All Dissertations

s-Process nucleosynthesis is a process in which stars produce elements of mass range A = 57 to 210. Since the days of B2FH, immense work has gone into quantifying and computing s-process yields and pathways. We expand upon said work along two fronts. The first front sets up the framework for proper treatment of nuclear isomers in network calculations. We apply the framework to study 85Kr, which is a pivotal isotope in the s-process chain that affects the abundance yields of Strontium and Rubidium isotopes. In particular, we are interested in the ratio of 88Sr/86Sr and 87Rb which are important …

Synthesis Of Nanoparticles In Silicate Matrix And Stimuli Responsive Nanocomposite Polymer Films, Dimuthu Edirisinghe

All Dissertations

Interactions between aqueous metal ions and soluble silicates lead to the formation of insoluble metal silicate complexes that form nanoparticles via condensation polymerization. Metal silicates function as nanoreactors, effectively condensing metal ions into nano-sized particles that can undergo further chemical transformations. Core-shell nanostructures present an intriguing strategy for integrating materials with different properties. The silicate shell around the silver nanoparticles can be successfully infused with other metal ions, enabling subsequent reactions to tailor their properties. Silver nanoparticles exhibit strong interactions with light, surpassing other chromophores, including noble metal nanoparticles, due to their highly efficient surface plasmonic resonance. The unique optical …

Decomposition And Coordination For Multiobjective Optimization: A Framework And Methodology, Philip J. De Castro

All Dissertations

In this work, we consider finding Pareto efficient solutions for complex multiobjective optimization problems (MOPs). Complex MOPs are unique in the literature because they have many more objective functions than is typically considered. In fact, such complex MOPs will have 30+ objective functions. This large problem size presents computational and coginitive difficulties. Computationally, standard techniques for solving MOPs are often ineffective and cognitively it is difficult for a decision maker (DM) to handle all of the information provided in such a large problem. To address these challenges, we develop a decomposition and coordination framework. This framework will allow us to …

Charge And Spin Transport In Nanowires With Spin-Orbit Coupling, Ryan Perrin

All Dissertations

Nanowires exhibiting Fermi-level pinning have strong radial electron confinement and thus can be modeled as a two-dimensional electron gas wrapped around the core. In III-V semiconductor structures, two forms of spin-orbit coupling are generated by breaking inversion symmetries in the crystal (Dresselhaus) and the overall structure of the nanowires (Rashba). The first goal of this thesis is to understand the single-particle energy spectrum in nanowires with variable cross sections and the quantum oscillations that can be driven in them by the application of a magnetic field parallel to the axis of the wire. To this end, the eigenfunctions and eigenvalues …

Strengthening The Bonds Between Us: An Empirical Investigation Of Morale In Human-Ai Teams And The Socially Supportive Ai Teammates Who Empower It, Rohit Mallick

All Dissertations

This dissertation investigates how artificial intelligence (AI) can be designed to improve the collective emotion within a team. A team's collective emotion, or morale, describes how motivated, optimistic, and enthusiastic the group is in accomplishing its goals. We conducted four studies that compared different social support strategies that AI teammates can provide to the team. Study 1A found that AI teammates who communicate with emotions can better motivate human team members and promote awareness of team dynamics and environmental changes. Study 1B found that human teammates become more motivated and happier when their AI teammates express joy and are close …

The Role Of The Neutral Wind In Observations Of High-Latitude Ionospheric Energy Transfer, Andrew M. Pepper

All Dissertations

Joule heating results from the collisional interaction between ions and neutrals and serves as a crucial mechanism for energy transfer between Earth's magnetosphere and ionosphere-thermosphere system, particularly at high latitudes. This dissertation investigates the modulation of Joule heating by altitude-resolved neutral winds, electric fields, and conductivity variations through multi-instrument observational analysis and modeling that incorporates both in-situ and ground-based sources to measure the main drivers of ion-neutral coupling. The observations presented consistently demonstrate a dual regulatory effect of the neutral wind on energy deposition that varies systematically with both geomagnetic activity level and proximity to auroral boundaries. In regions characterized …

Oculomics: Current Concepts And Evidence, Zhuoting Zhu, Yueye Wang, Ziyi Qi, Wenyi Hu, Xiayin Zhang, Yujie Wang, Joshua Ong, Ethan Waisberg, Mouayad Masalkhi, Alex Suh, Yih Chung Tham, Carol Y Cheung, Xiaohong Yang, Honghua Yu, Zongyuan Ge, Wei Wang, Bin Sheng, Yun Liu, Andrew G Lee, Alastair K Denniston, Peter Van Wijngaarden, Pearse A Keane, Ching-Yu Cheng, Mingguang He, Tien Yin Wong

Faculty, Staff and Student Publications

The eye provides novel insights into general health, as well as pathogenesis and development of systemic diseases. In the past decade, growing evidence has demonstrated that the eye's structure and function mirror multiple systemic health conditions, especially in cardiovascular diseases, neurodegenerative disorders, and kidney impairments. This has given rise to the field of oculomics-the application of ophthalmic biomarkers to understand mechanisms, detect and predict disease. The development of this field has been accelerated by three major advances: 1) the availability and widespread clinical adoption of high-resolution and non-invasive ophthalmic imaging ("hardware"); 2) the availability of large studies to interrogate associations …

Search For A Diffuse Flux Of Photons With Energies Above Tens Of Pev At The Pierre Auger Observatory, A. Abdul Halim, P. P. Abreu, M. Aglietta, I. Allekotte, K. Almeida Cheminant, A. Almela, B. Fick, K. Nguyen, D. Nitz, Et Al.

Michigan Tech Publications

Diffuse photons of energy above 0.1 PeV, produced through the interactions between cosmic rays and either interstellar matter or background radiation fields, are powerful tracers of the distribution of cosmic rays in the Galaxy. Furthermore, the measurement of a diffuse photon flux would be an important probe to test models of super-heavy dark matter decaying into gamma-rays. In this work, we search for a diffuse photon flux in the energy range between 50 PeV and 200 PeV using data from the Pierre Auger Observatory. For the first time, we combine the air-shower measurements from a 2 km2 surface array consisting …

Multiobjective Linear Ensembles For Robust And Sparse Training Of Few-Bit Neural Networks, Ambrogio Maria Bernardelli, Stefano Gualandi, Simone Milanesi, Hoong Chuin Lau, Neil Yorke-Smith

Research Collection School Of Computing and Information Systems

Training neural networks (NNs) using combinatorial optimization solvers has gained attention in recent years. In low-data settings, the use of state-of-the-art mixed integer linear programming solvers, for instance, has the potential to exactly train an NN while avoiding computing-intensive training and hyperparameter tuning and simultaneously training and sparsifying the network. We study the case of few-bit discrete-valued neural networks, both binarized neural networks (BNNs) whose values are restricted to ±1 and integer-valued neural networks (INNs) whose values lie in the range {−P,…,P}. Few-bit NNs receive increasing recognition because of their lightweight architecture and ability to run on low-power devices: for …

Augsso: Secure Threshold Single-Sign-On Authentication With Popular Password Collection, Changsong Jiang, Chunxiang Xu, Guomin Yang

Research Collection School Of Computing and Information Systems

Single-sign-on authentication is widely deployed in mobile systems, which allows an identity server to authenticate a mobile user and issue her/him with a token, such that the user can access diverse mobile services. To address the single-point-offailure problem, threshold single-sign-on authentication (PbTA) is a feasible solution, where multiple identity servers perform user authentication and token issuance in a threshold way. However, existing PbTA schemes confront critical drawbacks. Specifically, these schemes are vulnerable to perpetual secret leakage attacks (PSLA): an adversary perpetually compromises secrets of identity servers (e.g., secret key shares or credentials) to break security. Besides, they fail to achieve …