Engineering Commons^™

Computational Fluid Dynamics And Fluid Structure Interaction Modeling In Healthy Vertebral Arteries: A Comparative Study, Bryce Clinkenbeard

Electronic Theses and Dissertations

Cerebral perfusion is critical for maintaining proper brain function, with each cerebrovascular artery playing an integral role in the overall cerebrovascular system. When these arteries become damaged or develop plaque, cardiovascular disease (CVDs) such as atherosclerosis can arise, leading to conditions like arterial stenosis. While CVDs are most prevalent in older individuals, they are also observed in young adults, particularly those engaged in high-endurance occupations such as military service. Diagnosis and prediction of CVDs often rely on imaging modalities supported by computational fluid dynamics (CFD) which account for low resolution in fluid flow. CFD models assume rigid arterial walls, which …

Development Of An Embedded Iot Board For Real-Time Floor Estimation Of Autonomous Robots, Carter J. Sorensen

Electronic Theses and Dissertations

As service robots become more prevalent in multi-story environments such as hospitals, hotels, and laboratories, accurate floor-level detection is critical to ensuring operational reliability. Consider a robot tasked with delivering medical samples in a multi-story laboratory. Without accurate feedback, a robot exiting on the wrong floor could introduce delays, disrupt workflows, or compromise sample integrity. Internet of Things (IoT) technologies offer a way to address these risks by providing real-time error detection and corrective capability. However, current IoT-based floor estimation systems often require invasive modifications to building infrastructure—particularly elevator control panels. These approaches introduce challenges related to cost, liability, backward …

An Advanced Hexacopter For Autonomous Exploration Of Mars: Attitude Control And Navigation Strategies, Laura Sopegno

Electronic Theses and Dissertations

Mars exploration has recently witnessed major interest within the scientific community. Unmanned robotic platforms offer reliable solutions to acquire and collect data and information from the Red Planet. Particularly, rovers, landers, and orbiters have significantly shaped planetary exploration on the Moon and Mars, contributing significantly to past missions while also highlighting limitations in their capacity to cover diverse terrains over wide ranges. Given current advances in Unmanned Aircraft Systems (UASs), Unmanned Aerial Vehicles (UAVs) offer promising alternatives for future scientific missions.

It is argued that hexacopters, with their relatively compact design and redundancy, present a promising …

Reducing Attention Complexity In Graph Transformers Through Subgraph Partitioning, Ranjan Kumar Choubey

Master’s Dissertations

This dissertation addresses the challenge of scaling Graph Transformers by proposing a subgraph-based strategy to reduce attention complexity. The proposed framework preserves representational power while making attention computation tractable for largescale graphs. The method begins by partitioning the input graph into K subgraphs using the METIS algorithm. Each subgraph is encoded using a combination of local structural features from a Graph Convolutional Network (GCN) and global positional cues from Laplacian Positional Embeddings (LPEs). These embeddings are fused via a trainable projection function to form subgraph tokens. A supergraph is constructed to model interactions among subgraphs, allowing attention to be applied …

Optimized Wireless Power Transmission For Low-Cost, Energy-Efficient Internet Of Things Devices In Residential Environments, Daniel Brook Hatch

Theses and Dissertations

Wireless power transmission (WPT) offers a promising solution for powering devices in locations where traditional electrical outlets are inaccessible, such as ceilings or outdoor environments. By utilizing electromagnetic waves, such as light, WPT enables power delivery without the need for physical connections. With line-of-sight (LoS) as its primary limitation, this technology offers significant flexibility and potential for a wide range of applications, making it a compelling focus for research and innovation. Despite the advancements in WPT technologies, their practical application for powering Internet of Things (IoT) devices in real-world scenarios remains underexplored. Many IoT devices are installed in locations where …

Sae Baja Drivetrain Capstone 2024-2025, Leslie Alvarez Cisneros

University Honors Theses

This thesis reviews the 2024-2025 Baja SAE Drivetrain capstone project. The Baja SAE competition mimics real world engineering problems where teams of students design and build off-road vehicles that can handle tough, rough terrain. The objective of this capstone was to design a functional and reliable drivetrain system for the vehicle, within the constraints of a limited budget and the SAE competition guidelines. As part of a 12-member capstone team divided into three subgroups: frame, suspension, and drivetrain. As part of a four person drivetrain team, we picked up where the 2023-2024 team left off by relying on their past …

Piloted Autonomous Crisis Reconnaissance Robot 2.0 (Pacrr 2.0), Awawu Alimi, Urmika Ghosh, Marissa Kuo, Jonathan Santosa, Ethan Wyrick

Electrical and Computer Engineering Senior Theses

PACRR 2.0 (Piloted Autonomous Crisis Reconnaissance Robot, version 2) builds upon the original low-cost, autonomous-capable quadruped platform by enhancing both mobility and environmental perception for first-responder applications such as search and rescue, gas leak detection, and mapping of confined or hazardous areas. In PACRR 2.0, we integrate an RGB-D camera with analytic inverse kinematics and frame-based motion planning to achieve precise foot placement and stable quasi-static gaits even on sloped or uneven terrain. An NVIDIA Jetson processor runs high-level control and mapping alongside a Raspberry Pi 4 to manage motor control. Through simulation, we demonstrate robust 3D map generation and …

Predictive Analysis Of Crash Severity And Modeling Of 85th Percentile Speed For Rural Highways Of Arkansas Using Artificial Intelligence (Ai), Sagun Basel

Student Theses and Dissertations

Crash severity is a significant aspect of transport safety as its contributing factors assist engineers and designers in designing safer roads. The focus of this project is to predict crash severity, analyze crash parameters, and modeling of the 85th percentile speed (V85) selected rural roads (i.e., Interstate-555, East Johnson Avenue Highway, and Red Wolf Blvd) in Arkansas, using Artificial Neural Network (ANN) models. MATLAB® was used to predict the V85 and compare it with the actual V85 collected from field instrumentation. Besides the speed data, weather (e.g., rainfall), road geometry, light conditions, and traffic volume were used as input in …

A Modular Simulation Environment And B-Spline Trajectory Generation Methods For Multi-Agent Uav Systems, Landon D. Shumway

Theses and Dissertations

Multi-agent UAV systems present a complex challenge requiring solutions to numerous subproblems. This research addresses two key issues: simulation testing and path planning. A modular simulation environment is developed, enabling users to run diverse mission scenarios with heterogeneous UAV teams and to implement custom dynamic models and guidance laws. Additionally, two novel B-spline trajectory generation methods are proposed. The first generates time-synchronized B-spline paths for UAVs with arbitrary initial and final states in 2D space, accommodating scenarios where agents must follow predetermined speed profiles. The second guidance method converts spline paths between MINVO, Bézier, and non-uniform B-spline representations, leveraging the …

Evolutionary Influences On Oceanic Islands Parasites: Phylogeography, Genetic Structure, And The “Island Rule” Of Common Ground Doves (Columbina Passerina) And Their Lice, Paige Jordan Brewer

Student Theses and Dissertations

Organisms on oceanic island archipelagos often exhibit strong genetic signatures and adaptations. Here, we focus on Common Ground Doves (Columbina passerina) and their parasitic lice, Physconelloides body lice and Columbicola wing lice, across the Caribbean islands to examine phylogeography, population genetics, and the “Island rule”. We used genome-wide sequences and found C. passerina doves and their lice exhibited unique dispersal patterns and phylogenetic relationships; however, similar population structure. We also found distinct patterns of genetic diversity between Physconelloides and Columbicola, likely caused by variations in their dispersal abilities. Additionally, we measured C. passerina specimens and their lice to compare island …

Optimizing The Use Of Sustainable Additives In Subgrade Soil Stabilization, Orchi Mallick

Student Theses and Dissertations

Subgrade soil critically impacts pavement lifespan, where poor conditions lead to premature failure. This study evaluates soil stabilization of AASTHO classified, A-4 and A-6 soil, using sustainable additives: Rice Husk Ash (RHA), Reclaimed Fly Ash (RFA), and a traditional stabilizer Hydrated Lime (HL). Laboratory tests (Atterberg Limits, Modified Proctor, California Bearing Ratio (CBR), and Free Swell) were conducted on untreated and treated soils with RHA (3%, 6%, and 9% by weight), HL (1%, 3%, and 5% by weight), RFA (4%, 6%, and 8% by weight), and combinations of HL + RHA. Results showed all stabilizers improved strength and reduced swell. …

Online Hyperparameter Tuning For Llm Optimization, Ethan Lin, Nathan Yu, Jeromy Chang

Computer Science and Engineering Senior Theses

Large Language Models (LLMs) are becoming increasingly popular in modern society. However, despite their popularity, the deployment of LLMs in real-world scenarios is extremely challenging due to substantial computational costs and memory constraints. Edge devices, like smartphones and IoT devices, lack resources needed to run these models locally, instead offloading computations for cloud computing. Cloud computing requires users to send their data over the internet leading to numerous privacy and security concerns. In some domains, such as health and finances, sending such sensitive information is not an option. Existing solutions to compress or increase inference speed include Small Language Models …

The Dpe Shortage And How To Fix It, Paul Dye

Honors Theses

The following content delves into the current issues surrounding the FAA’s designated pilot examiner (DPE) system, which, while functional, is increasingly strained by growing demand and outdated policies. Through firsthand experience, survey data, and analysis of current practices, the paper emphasizes some of the most pressing problems, including scheduling inefficiencies, inconsistent examiner expectations, manual eligibility checks despite the widespread use of digital logbooks, and a lack of meaningful oversight or feedback mechanisms for both DPEs and CFIs.

A major focus is the outdated scheduling process, which remains largely decentralized and prone to double-booking, cancellations, and long wait times, especially for …

Multi Trajectory Guided Model Inversion Attacks, Indrajit Nandi

Master’s Dissertations

Recent advancements in deep learning have brought significant concerns regarding the privacy of training data due to overfitting and memorization, as well as a lack of defense mechanisms. In model inversion attacks, where Attackers aim to reconstruct original private training samples (i.e images) just by using the DNN model’s last layer output. Traditional black-box MI attacks face three key challenges: (1) Non-convex optimization landscapes often trap reconstructions in poor local minima, degrading output quality. (2) Black-box scenarios require excessive queries to approximate gradients, raising detection risks. (3) Unconstrained pixel-space optimization generates unrealistic artifacts since the inverse mapping lacks natural image …

Pathways To Efficient And Equitable Solutions For Large-Scale Routing Problems, Abhay Sobhanan

USF Tampa Graduate Theses and Dissertations

This dissertation addresses large-scale optimization problems in transportation emerging from hierarchical decision-making, equitable workload allocation, and innovative routing logistics. It presents three sets of contributions, each detailed in a separate chapter, and offers computational tools and insights to advance both the theory and practice of transportation systems.

The first work introduces a deep learning-enhanced genetic algorithm framework for solving the Hierarchical Vehicle Routing Problems (HVRPs). Traditional optimization approaches to such problems require extensive evaluation of multiple lower-level routing solutions and are computationally intensive. Our innovative method integrates a genetic algorithm with a pretrained graph neural network, which is trained on …

Monochromatic Empty Triangles In Two-Colored Point Sets, Adrish Paik

Master’s Dissertations

A key problem in combinatorial geometry is the identification of properties of a subset of a point set which has properties like convexity, monochromaticity, and emptiness. This thesis actual works on this sides of combinatorial geometry: efficiently finding empty monochromatic triangles in two-colored point sets on the plane. While earlier research focused on counting empty triangles in point set without any color, our work takes an optimal algorithm to explicitly detect them. By using geometric insights and visibility-based techniques. We then address a relaxed but equally compelling variant: monochromatic triangles containing at most one point of the opposite color. For …

Detection Of Fake News In Short Videos: A Multimodal Approach, Mona Kumari

Master’s Dissertations

The rise of generative models and affordable video editing tools has fueled the spread of fake and manipulated videos, undermining information reliabilityespecially on social media. Traditional detection methods, focused on single modalities like visual artifacts or text cues, often struggle with diverse, user-generated content. This dissertation presents a unified framework for fake video detection that integrates multimodal semantics, narrative structure, and propagation behavior. Visual, audio, text, and OCR features are extracted using pretrained models (CLIP, Wav2Vec2), and segment-level graphs are built to model narrative flow using Graph Attention Networks (GATv2Conv). User engagement dynamics are modeled via a bidirectional LSTM. A …

Santa Clara Radio Astronomy Project (Scrap) Iv - Data Processing, Noah Abe, Wesley Durbano

Computer Science and Engineering Senior Theses

The Santa Clara Radio Astronomy Project (SCRAP) IV: Data Processing is the fourth year of a multi-year project that aims to provide SCU with a fully functioning radio telescope in a costefficient manner. The project aims to provide this radio telescope as a hands-on tool that can be used not just for scientific discovery, but also for SCU academic use in a wide variety of different subjects, such as electrical engineering and physics. This year, our SCRAP team aimed to bolster the long-term operation of the telescope, which is a key feature it must have for it to be considered …

Xmr: Extensible Model Representation, Jason Cisneros, Lucas Van Der Heijden

Computer Science and Engineering Senior Theses

In safety critical industries, such as aerospace, verification and validation are crucial steps in system development. Validation begins with decomposing a system into its requirements. These requirements are used to create the high level model of the system. The low level system that is created from this must then be verified. Manually ensuring that the system being verified exactly matches the validated design is tedious, time consuming, and error prone. To solve this, we have created an open source tool that can automatically generate the code from UML models. This enables going from the high level model to the low …

Deepfake Detection, Timothy Tong, Abem Lucas

Computer Science and Engineering Senior Theses

From elections, to wars, to people’s personal lives, deepfakes have become ever more present, blurring the distinction between reality and fiction. Many deep learning-based deepfake detection methods lack generalizability. They often overfit to deepfake generation techniques in their training distribution, and fail to detect deepfake generation techniques outside of their training distribution. One approach to solve the generalization problem has been to use Vision Language Models, such as the pretrained CLIP model, to extract features that generalize across different deepfake generation techniques, including diffusion and GAN images. However, most CLIP approaches only consider image level features for detection, such as …

Exploring Novel Methods For Real-Time Multi-Camera People Tracking In Machine Learning, Johan Kou, Connor Vallero

Computer Science and Engineering Senior Theses

Multi-camera people tracking is the process of tracking persons and their paths, continuously across different camera fields of view. It can help track suspects across large areas, and assist individuals in emergency situations. The current state-of-the-art (SOTA) method involves using geometric-consistent constraints, information on the appearance of subjects, and pose estimation for dealing with occlusion issues. This current SOTA works well, but is still lacking in its ability to handle occlusion and perform well in real-time applications on a network. With occlusion, the IDs assigned to persons can be accidentally swapped in high density areas, or places where there are …

Vintage Game Emulator, Andrew Katchour, Ashwin Raman

Computer Science and Engineering Senior Theses

This project explores the integration of artificial intelligence into retro-style arcade titles to enhance the gameplay, while still preserving the nostalgic aesthetic and overall mechanics of the titles. By using Pygame to explore clones of the existing video game titles, we modified the existing games to develop AI into the games using various AI algorithms. The system introduces adaptive enemy behavior that responds to the players actions and also introduces an additional player to some games that will play alongside the player as well. This helps to create a more engaging and unpredictable gaming experience. The AI logic is implemented …

An Ai-Driven Microfinance Platform To Enhance The Growth Of Small Businesses, Abdullah Naveed, Yunzhou Wang

Computer Science and Engineering Senior Theses

Microfinance provides financial services to businesses which do not have access to regular banking institutions. There have been many digital applications developed to support microfinance schemes globally. However, the applications currently on the market do not yet fully leverage technology features, which are already being widely used in traditional banking. In conjunction with the Miller Center of Social Entrepreneurship at Santa Clara University, we have developed an application utilizing the latest technologies to help small businesses and lenders in all stages of a microfinance project.

Variable Natural Language Translator For Video Games, Gabriel Bernini, Cole Propach

Computer Science and Engineering Senior Theses

In the field of video games, developers work to immerse players in a variety of ways. In one genre of video games, 2D exploration, or Metroidvania as its colloquially known, developers try to immerse players by letting them explore large worlds with the hope to overcome isolation. Often these worlds are sparse or dead worlds where the player is alone, but by exploring more of the world familiarity with the space is achieved and this isolation can be overcome. We hope to innovate in this genre by utilizing a new way to simulate and overcome this isolation, through language learning. …

Compliant Mechanisms For Scalable Systems And Precision Deployment, Jared Rodney Hunter

Theses and Dissertations

Compliant mechanisms offer advantages in precision applications where size, scaling, and environmental effects render traditional mechanisms inadequate or likely to fail. However, designing compliant mechanisms and integrating them into larger, more complex systems remains a challenging problem. This thesis presents work that addresses this issue with analytical models and experiments on flat springs, scalable compliant mechanisms, and origami arrays. Storing and releasing energy in tiny, flat compliant mechanisms opens the door for the design of innovative actuators and products in space-constrained situations. Scaling compliant mechanisms allows novel systems to be made that can operate across scales. By designing for scalability …

Modeling And Simulation Of Tensegrity Structures With Continuous Cables, Austin R. Brown

Theses and Dissertations

This thesis presents a novel approach for modeling and simulating tensegrity structures with continuous cables. A Python-based simulation framework package was developed to address limitations in existing tensegrity modeling software, particularly the inability to model cables passing through multiple nodes. The framework utilizes virtual work methods to solve for equilibrium configurations of 2D, 2.5D and 3D tensegrity systems. Key features include: • A YAML-based input system for easy definition of tensegrity topologies. • Algorithms for handling continuous cables spanning multiple nodes. • Optimization techniques to find stable equilibrium states. • Capability to simulate 2.5D structures wrapped around cylindrical surfaces. • …

Llm Music Creation And Recommendation Applications, Curtis Robinson, Allan Yang, Thomas Liu

Electrical and Computer Engineering Senior Theses

This thesis explores the application of large language models (LLMs) in music analysis, creation, and interaction, focusing on their potential to reshape traditional workflows in the music domain. The study begins by contextualizing the role of artificial intelligence in music technology, particularly emphasizing the emergence of LLMs like GPT and their unique capabilities in multimodal and musical contexts. A comprehensive survey of current research and toolsets highlights both creative and analytical implementations, ranging from text-based music generation to music information retrieval. The core contribution is an experimental framework that integrates LLMs with music processing libraries, enabling novel interactions such as …

The Grd Companion, Julius Gamboa, Muti Shuman, Tro Hovasapian

Electrical and Computer Engineering Senior Theses

This project introduces the design and development of the GRD Companion. This gesture-controlled reminder device aims to support individuals with special needs in their daily routines, in the hope of them being more independent. The system we designed integrates a Raspberry Pi Zero 2 W, PAJ7620U2 gesture sensor, and audio playback components, all housed in a custom 3D-printed case. Some of our key design priorities included accessibility by relying only on gesture recognition to control the device, eliminating screens and buttons, as well as portability, enabling all users to carry the device anywhere. The device is paired with our WaveLink …

Documentation-Aware Code Generation Via Retrieval Augmented Generation, Daniel Amirtharaj, Rahmin Norwood

Computer Science and Engineering Senior Theses

Modern large language models (LLMs) increase the speed of software development but frequently hallucinate code, forcing developers to debug and rewrite generated code manually. This project introduces Documentation-Aware Code Generation, a retrieval-augmented generation (RAG) framework that injects authoritative documentation into the LLM prompt to reduce hallucinations in generated code. We build an ingestion pipeline that scrapes, cleans, chunks, and embeds official API documentation into a Pinecone vector database, then design a retrieval and re-ranking pipeline that retrieves the most relevant snippets for each user query. Results show that augmenting prompts with documentation lowers code hallucination by up to 60%. The …

Sideque$T, Akshay Nichani, Anusha Kankipati, Afra Mahammad, Lucas Jablon

Computer Science and Engineering Senior Theses

In recent years, the gap between traditional education and the current labor market has widened dramatically: in 2024, 11. 5 % of California’s 16-24 year olds were neither in school nor employed, alongside a net decline of roughly 3 million students nationwide in the last decade and more than 4 million members of Generation Z left the job despite having conventional degrees. These trends underscore a growing disconnect between academic credentials and market-ready skills and a pressing need for alternative pathways to gainful work. We introduce SIDEQUE$T, a secure, user-friendly online marketplace engineered to bridge this divide. By allowing job …