Physical Sciences and Mathematics Commons^™

How Do Simulated Phishing Attacks Impact Cybersecurity Awareness And The Enhancement Of Security Protocols Among Faculty Members In A University Environment?, Navnoor Sandhu

University Honors Program Senior Projects

Phishing attacks are cyber threats where attackers deceive users into performing actions that compromise the user’s security and benefit the attacker. In 2024 alone, phishing attacks have resulted in estimated damages of around 800 million dollars [1]. In response, many institutions have implemented internal simulated phishing attacks to enhance their employees' cybersecurity awareness. This training exercise has been proven beneficial in improving cybersecurity awareness on an enterprise scale[4]. This study aims to evaluate the potential effectiveness of a simulated phishing attack within a university setting, which is a relatively unseen practice thus far. Universities, like other secure organizations, store sensitive …

Inversion Numbers Of Oriented Graphs, Sam Harris

Theses, Dissertations and Culminating Projects

This thesis investigates recent results and conjectures regarding inversion numbers of oriented graphs. We define the inversion number of an oriented graph G as the minimum size of a decycling family of subsets of vertices of G. We focus on three areas: the maximum inversion number of a graph on n vertices, the inversion numbers of dijoins of two oriented graphs, and computational algorithms for deciding the inversion number. The main contribution of this thesis is a proposed construction of a graph with higher inversion number than that of any other currently known construction. We also provide explicit, rather than …

Reevaluating The Role Of Ruppia Maritima: Recruitment Dynamics And Habitat Use By Blue Crabs (Callinectes Sapidus) And Associated Benthic Fauna In A Mid-Atlantic Seagrass Community, Delaney St. Pierre

Theses, Dissertations and Culminating Projects

The value of seagrasses as essential fish habitat is well recognized, but limited data exist on the value of one particular species, Ruppia maritima (widgeon grass), as habitat for fish and invertebrates. During the summer of 2024, I evaluated R. maritima, Zostera marina (eelgrass) and mixed beds to assess their relative value as habitat in Barnegat Bay, New Jersey. Results from throw traps indicated significant monthly differences for pipefish, gobies, blue crabs, grass shrimp, and sand shrimp, driven by active recruitment events. When evaluating habitat type, we found no taxa that were significantly more abundant in Z. marina habitat as …

Analysis And Mathematical Recomposition Of The Art Of The Fugue, Joshua Cellar

Theses, Dissertations and Culminating Projects

The Art of the Fugue is a collection of 18 fugues and cannons written by Johann Sebastian Bach in the 1700s. Each piece starts with a single theme which is transformed, developed and mixed in fascinating mathematical combinations resulting in a distinctive musical style. In this paper, we use the method introduced in [7] to analyze 14 pieces from The Art of the Fugue. We focus on the variation of motifs from one piece to another as well as the complexities of mathematical transformations present throughout the entire collection. We also demonstrate how using maps of transformations and the rules …

Gaussian Process Regression And Nested Sampling For Planetary Parameter Prediction, Alexandro Balarezo

Physics

In this project, we implemented a Gaussian Process (GP) regression framework using MATLAB to model two planetary (Earth) parameters, the surface temperature and albedo, as functions of planetary rotation rate and insolation (the amount of sunlight impinging on the planet). We used simulation data from the NASA ROCKE-3D general circulation model developed by the NASA Goddard Institute for Space Studies (GISS). The GP model generates a joint multivariate Gaussian distribution that is entirely captured by a covariance matrix and the output of a training data set. The covariance matrix is determined by the input data and the three hyperparameters a …

A Synoptic Analysis Of Hurricane Andrew, Alice E. Schipper, Mark R. Sinclair

Student Works

Hurricane Andrew was a historic Category 5 storm that made landfall in southern Florida on the morning of 24 August 1992. Andrew’s landfall brought massive destruction, with entire neighborhoods in the city of Homestead, Florida destroyed. There were 250,000 people left homeless in the US over its entire track, and cost US$25 billion in damage, the costliest hurricane in United States history up to that point. A synoptic analysis was completed to study the tropical and subsequent extratropical phases of this destructive storm. During Andrew’s tropical phase it was found that strong vertical shear initially impeded development. As this dissipated, …

2024 Annual Operations And Maintenance Report, Butte-Silver Bow Department Of Reclamation And Environmental Services

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Quasipseudometric Value Functions With Dense Rewards, Khadichabonu Valieva

Honors Theses

Goal-conditioned reinforcement learning (GCRL) serves as an extension of reinforce- ment learning (RL) that focuses on goals that can be adjusted, making it useful for many applications, especially in complex robotics tasks. Recent research has established that the optimal value function of GCRL, denoted as Q∗(s, a, g), has a quasipseudometric structure. This finding has led to the development of targeted neural architectures that respect such a structure. However, prior analyses have predominantly focused on sparse reward settings, which are known to increase challenges related to sample complexity. In this work, I with the guidance of my advisor show that …

Mathematical Melodies: The Exploration Of Music Using Fourier Signal Analysis, Courtney Francois

Honors Theses

Upon initial inspection, mathematics and music appear to be distinct disciplines lacking any connections to one another. However, many complex intersections lie beneath the surface. This paper seeks to explore these connections through the analysis of the Fourier series and the Fourier transformation of musical sound signals. Orthogonal functions of various frequencies are used to approximate and recover sound signals. Following the examination of the basis of Fourier signal analysis, MATLAB is utilized to visualize the connectedness of mathematics and music through sound signals from varied musical instruments and by performing Fourier signal analysis to the sound signals. Then, the …

Privacy-Aware Ai-Based Agricultural Monitoring Using Internet Of Drones, Md Benozir Hossain

Honors Theses

Artificial Intelligence (AI) has become a vital tool for agricultural farming. AI-based image processing models utilizing different machine learning (ML) algorithms and deep learning (DL) offer advanced functionalities in disease detection, yield estimation, land use, etc. This thesis examines AI-driven techniques utilizing Convolutional Neural Networks (CNN) with the addition of Federated Learning (FL) to analyze satellite and drone images for agricultural insights, especially in detecting Cotton diseases. The AI models improve agricultural farming in many ways, such as using data to make critical decisions, reducing labor costs, pest infestations, etc. Moreover, these models allow farmers to minimize yield losses by …

Tailoring The Morphology Of Block Copolymers Via Solvent-Vapor Annealing, Bayleigh Madelin Loving

Honors Theses

Triblock polystyrene-polyisobutylene-polystyrene (PS-PIB-PS) copolymers have widespread applications from thermoplastic elastomers to protective coatings for ballistic applications. The incompatibility between the soft PIB and hard PS phases leads to phase separation and subsequent formation of morphological domains like lamellae and cylinders. The structures are stabilized by physical crosslinks, which can greatly improve the toughness of the triblock systems by preventing chain pullout during tensile deformation. We tailored the morphologies (achieving different morphologies with the same block copolymer) by changing the annealing conditions of the block copolymers. Solvent vapor annealing was used to selectively activate the mobility of a particular block, causing …

A Spectroscopic Survey Of Atmospheres Of Super-Earths, Luke Brust

Honors Theses

Recent research has made it possible to use spectroscopy to analyze the composition of the atmospheres of exoplanets, planets that orbit other stars. Most projects thus far have focused on the atmospheres of gas giants, as it is less challenging to observe them with available equipment. This project studies the atmospheres of four Super- Earths, planets that have a mass greater than the Earth but smaller than Neptune. This is accomplished by processing the raw spectroscopic data from the Hubble Space Telescope and modeling the atmosphere using the program 𝝉-Rex3. This survey found clear results from two of the selected …

Globally Adaptive Exponential Integrators For Stiff Systems Of Odes, Anzhelika Vasilyeva

Honors Theses

This thesis introduces a novel method for solving systems of Ordinary Differential Equations (ODEs) resulting from the spatial discretization of Partial Differential Equations (PDEs). The proposed approach builds upon an existing technique that employs Krylov projection, which requires evaluating a matrix function at each timestep. The innovation of the new method lies in its reuse strategy, which shifts the perspective from direct matrix function evaluation to polynomial interpolation. Numerical experiments conducted on constant and variable coefficient heat equations, with both smooth and discontinuous initial data, demonstrate the computational time advantage of the new approach. The results indicate that this method …

Synthetic Efforts Towards An Analog Of Ly426965, Macy Sproles

Honors Theses

The 5-hydroxytryptamine_1A (5-HT_1A) receptor is a key target in the treatment of various neuropsychiatric conditions, and the development of selective antagonists offers promising therapeutic potential.²⁴ This study aimed to develop a synthetic analog of LY426965, a selective 5-HT_1A receptor antagonist. The synthetic route was initiated from dimethyl-2-phenylmalonate, employing pig liver esterase (PLE) as an enantioselective biocatalyst to achieve regioselective hydrolysis of one ester moiety in the malonic diester intermediate.¹⁷ Through a series of stereochemically controlled transformations, a new intermediate was successfully synthesized. Although the target molecule was not obtained, a new compound was synthesized …

From Seasonality To Causality: Understanding Urban Water Usage Using Statistical And Machine Learning Models, Kelsey Hawkins

Electrical Engineering and Computer Science (MS) Theses

This study examines the relationship between climate conditions and residential water usage, focusing on how seasonal and environmental changes influence water consumption. Utilizing data from over 100,000 households across three micro-climate zones for over a five-year period, we apply statistical analysis and machine learning techniques to assess the impact of temperature, precipitation, evapotranspiration, and location on water usage. By integrating climate and billing data, this research provides a data-driven approach on water usage behaviors in Irvine, CA, in collaboration with Irvine Ranch Water District (IRWD).

Our analysis utilizes time series modeling, including a Seasonal Autoregressive Integrated Moving Average (SARIMA) and …

Implementation Of Residual Tandem Neural Networks For Photonic Inverse Design, Ponthea A. Zahraii

Electrical Engineering and Computer Science (MS) Theses

Deep-learning approaches can greatly benefit the modeling and design of nanophotonic and optical structures. Traditional full-wave simulations are time and resource-intensive, which can act as a bottleneck in photonic design. On the other hand, deep-learning approaches for designing the response of nanophotonic geometries can be computationally inexpensive and produce accurate and efficient results. In this project, we specifically investigate the case of optical forces near meta-structures. We propose using an inverse design approach with residual blocks to account for the deep nature of this architecture and inherently address the non-uniqueness problem. A tandem approach, which consists of two interconnected models, …

Survey On Application Of Large Language Models In Network Attack And Defense, Prisha Purohit

Honors Theses

The emergence of Large Language Models (LLMs) has significantly transformed the technological and cybersecurity landscape, introducing both unprecedented opportunities and formidable challenges. With the public release of ChatGPT in 2022, LLMs have gained global prominence, redefining natural language processing capabilities and enabling advancements across various fields. In cybersecurity, these models represent a dual-use technology: while they offer powerful tools for threat detection, automated analysis, and security training, they also pose risks when leveraged by malicious actors for phishing, social engineering, and the creation of evasive malware. This thesis presents a comprehensive literature review exploring the dual roles of LLMs in …

Synthesis Of Single Chain Polymer Nanoparticle Networks By Reinitiating Raft Polymerization, Dallas Donovan

Honors Theses

Hydrogel materials, which are polymer networks comprised mostly of water, hold significant promise for biomedical applications due to their compatibility with biological systems. Conventional hydrogel materials are often brittle and weak, but most applications in biomedical systems require materials to be strong and tough. The topology of a polymer network dictates its mechanical properties. An important strategy for designing tougher hydrogels is the release of stored length, such as from the unfolding of polyprotein cross-linkers. Inspired by the success of the strategy, we report progress towards a fully synthetic design using single chain nanoparticles (SCNPs) into a hydrogel. SCNPs, which …

Improving Research Software Engineering In Mathematics, Abram Miller

Honors Theses

Research Software Engineering is critical to modern mathematical research, enabling the creation, maintenance, and dissemination of computational tools that bridge theory and practice. However, the field faces systemic challenges, including insufficient funding, lack of institutional recognition, and gaps in training and infrastructure. This thesis investigates these challenges through two approaches: (1) a comparative survey study focused on mathematicians and (2) hands-on contributions to an open-source research software project.

The Improving Research Software Engineering in Mathematics survey, conducted from September 2024 to January 2025, adapts the survey framework developed by Carver et al. in A survey of the state of the …

Reconfigurable Python Autopilot Software For Rc Aircraft, Kate Doiron

Honors Theses

No abstract provided.

Linear Polydicyclopentadiene Copolymers: Synthesis And Thermal Properties, Connor Lewis

Honors Theses

No abstract provided.

“I Can Run At Night!”: Using Augmented Reality To Support Nighttime Guided Running For Low-Vision Runners, Yuki Abe, Keisuke Matsushima, Kotaro Hara, Daisuke Sakamoto, Tetsuo Ono

Research Collection School Of Computing and Information Systems

Dark environment challenges low-vision (LV) individuals to engage in running by following sighted guide—a Caller-style guided running—due to insufficient illumination, because it prevents them from using their residual vision to follow the guide and be aware about their environment. We design, develop, and evaluate RunSight, an augmented reality (AR)-based assistive tool to support LV individuals to run at night. RunSight combines see-through HMD and image processing to enhance one’s visual awareness of the surrounding environment (e.g., potential hazard) and visualize the guide’s position with AR-based visualization. To demonstrate RunSight’s efficacy, we conducted a user study with 8 LV runners. The …

The Food Truck: A Multi-Product Newsvendor With Trans-Shipment Cost, Samuel Ajibola

Electronic Theses and Dissertations

The Newsvendor Problem is a key model in supply chain management that focuses on determining the optimal order quantity to minimize costs under uncertain demand. This thesis introduces the Food Truck Problem, an extension of the Newsvendor model that incorporates nonlinear transshipment costs for inventory transportation. In this context, a Food Truck must determine the optimal stock levels for multiple products while minimizing costs related to stock shortages, excess inventory, and transportation. Unlike traditional Newsvendor models, our approach explicitly considers a quadratic transshipment cost, which necessitates the use of Lagrangian duality and Karush-Kuhn-Tucker (KKT) conditions for analysis. Moreover, we apply …

Cranial Ontogeny Of The Extinct Dwarf Tapir Tapirus Polkensis; With Comparison To That Of The Extant Tapirus Bairdii (Tapiridae, Perissodactyla), Johannah Orendorff

Electronic Theses and Dissertations

Tapirus polkensis is the smallest known species of tapir to ever live, and the largest deposit of their fossils is currently located at the GFS in Gray, TN. Phylogenetics suggest that the extant T. bairdii may be the sister taxon to T. polkensis, although they differ greatly in their morphology. Variation exists among adult T. polkensis specimens, with patterns not present in T. bairdii. For this study, as series of 2D GMAs, with TPSs, were rendered on 10 skulls of T. polkensis and 48 skulls of T. bairdii, across both species’ ontogenetic series. Analyses confirmed that growth …

Learning Behaviors In Physics-Informed Deep Learning, Alex Glover

Electronic Theses and Dissertations

Physics-informed deep learning is a methodology in artificial intelligence aimed at combating the large training data requirement and the barrier of domain awareness that deep learning architectures commonly face in applications. Stochastic modeling integrated into the predictive models provides that domain knowledge. Variations of the Intelligent Driving Model impact the learning behaviors of the joint-training architecture. This thesis examines the effect of substituting the standard linear Intelligent Driving Model with a modified nonlinear version, as applied to real human driving behavior on the I-80 interstate. The experimentation also critically evaluates the complications that impede the viability of this architecture in …

Kinetic Analysis Of Hydrolysis And Hydrothermal Conversion Of Methyl Cellulose To Dodecane, Joseph Olembo Were

Electronic Theses and Dissertations

Environmental pollution due to emission of greenhouse gases and increasing global energy demand are some of the concerns associated Analysis with the use of fossil fuels. These concerns have triggered the exploration of sustainable and efficient methods for renewable energy production. One such method is the conversion of cellulosic biomass to hydrocarbon fuels using hydrogen bronze metals. Cellulose is the most abundant biomass globally, and thus its utilization can lead to more sustainable energy production. Previous studies have reported the conversion of cellulose to hydrocarbons at high temperatures and hydrogen pressure. This work focuses on the conversion of methyl cellulose …

A Kinetic Analysis On Hydrolysis And Hydrothermal Conversion Of Cellulose To Dodecane, Joel Nyangoka Onyancha

Electronic Theses and Dissertations

Cellulose, the most abundant biomass on Earth, offers a promising pathway for alternative energy through conversion into alkane hydrocarbons. Traditional methods rely on high temperatures and high-pressure hydrogen, often derived from petroleum. In this study, we investigated the conversion of Microcrystalline Cellulose using hydrogen metal oxides (bronzes) under milder conditions. Following ASTM E3417-24 hydrolysis protocols, we employed hydrogen bronzes with toluene for product extraction. This approach enabled conversion at lower temperatures without pressurized hydrogen. Products were analyzed using Gas Chromatography Mass Spectrometer for identification and Gas Chromatography Flame Ionization Detector for quantification. Our findings revealed the formation of a possible …

Numalyze: Numerical Analysis Web Application, Dev Kapupara

Electronic Theses, Projects, and Dissertations

Numalyze is an online platform that allows users to run and apply different numerical methods in real time. The application is built using Python and the Flask web framework. It provides an interface where users input mathematical functions and parameters to see the results for root-finding and integration methods, and to also perform reductions on matrices. By using a light-weight web framework and self-coded algorithms which removes dependency on massive external libraries—this application connects theoretical concepts to their practical implementation. It enables students and researchers to visualize the series of steps that each algorithm takes to compute results. Moreover, the …

Explainable Ai (Xai) For A Machine Learning Heart Disease Prediction Model, Sai Abhishek Sanchula

Electronic Theses, Projects, and Dissertations

Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, necessitating the development of accurate and interpretable machine learning (ML) models for early diagnosis and risk assessment (World Health Organization, 2021). While ML algorithms such as logistic regression, decision trees, support vector machines (SVM) (Cortes & Vapnik, 1995), and deep learning models (LeCun et al., 2015) have demonstrated high predictive accuracy, their adoption in clinical practice is hindered by their black-box nature (Rudin, 2019). Explainable AI (XAI) techniques, including SHapley Additive Explanations (SHAP) (Lundberg & Lee, 2017), Local Interpretable Model-agnostic Explanations (LIME) (Ribeiro et al., 2016), and feature importance analysis …

Time Series Deep Learning Approach For The Intermittent Operational Performance Of A Wellhead Water Treatment And Desalination System, Michael G. Clement

Electronic Theses, Projects, and Dissertations

Distributed water treatment and desalination (DWTD) systems are becoming significant for serving disadvantaged communities that are geographically segregated from centralized water distribution networks. However, given the remote nature of the communities, these systems must operate autonomously adapting to intermittent operations due to varying water use patterns and unavailability of continuous manual labor support. Machine Learning models describing and forecasting system performance are critical, allowing for model-based control, performance forecasting, fault detection, and determination of causal relationships among process attributes. Accordingly, graph convolutional neural networks with an attention mechanism (GATConv) were developed to describe the intermittent operational profiles of a wellhead …