Digital Commons Network^™

Simulated Intelligence, Surveillance, And Play, Atienah Cape

Theses - ALL

This MFA thesis explores modern panopticism and the feeling of being watched by creating and installing Four Real Friends, an interactive robotic artwork inspired by the 1998 Furby. The project looks at how surveillance technologies are not just outside forces, but part of daily life, often feeling familiar, playful, and even social. The installation uses hardware design, custom circuits, computer vision, and real-time data display to collect and process how visitors interact in the gallery. Its nostalgic and friendly look encourages people to take part, while still showing how data is collected and displayed as it happens. This makes surveillance …

Symmetries Of Legged Locomotion: Theory And Applications In Animals And Robots, Jiayu Ding

Dissertations - ALL

Legged locomotion in animals and robots is naturally modeled as a hybrid dynamical system: smooth body evolution is repeatedly interrupted by discrete contact events such as touchdown and liftoff. Although symmetry is a powerful organizing principle in smooth dynamical systems, a comparably systematic symmetry framework for hybrid legged locomotion remains underdeveloped. This dissertation develops such a framework for a scoped class of periodic hybrid locomotion models and uses it to relate theoretical gait analysis, animal locomotion studies, and robotic gait generation. The dissertation first extends symmetry notions from autonomous dynamics to hybrid legged systems and distinguishes symmetries of the hybrid …

Designing A Collaborative Uav-Ugv System For Autonomous Challenge Completion, Ember Reysen

Honors Theses

The coordination between Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) holds significant potential for completing complex tasks such as disaster response and construction surveillance by leveraging the strengths of aerial flight and stable on-ground transportation. Unfortunately, coordination between UAVs and UGVs is extremely complex and task-dependent, leading to limited understanding of autonomous collaboration. This thesis explores the process of designing an UAV-UGV collaborative system capable of aerially scouting a target destination, relaying its coordinates to a ground vehicle, and performing a precision landing for unison travel. I utilize computer vision techniques via OpenCV for target marker identification, ROS …

Evaluating Team Formation Strategies With Algorithms, Ethan E. Lopez, Andy Vo

Student Scholar Symposium Abstracts and Posters

Effective teamwork is essential for collaborative learning, yet forming compatible student groups remains a persistent challenge. This study explores how algorithmic team-building methods influence students’ social and academic compatibility overtime. To support this investigation, we designed a visual survey system called “The Disco Ball." Evaluating work ethics, lifestyles, behaviors, and communication styles, students were initially assigned to project teams using one of three conditions: (1) random assignment (control), (2) a “most matches” condition maximizing similarity between students, and (3) a “diverse communication styles” condition designed to balance differing interaction preferences. After an initial collaboration period, students were given the opportunity …

Comparing Llm Architectures In Street Fighter Iii, Andrew Hinh, Hyemin Doo, Jack Wu

Computer Science and Engineering Senior Theses

We built a browser-based Street Fighter III benchmark for comparing large language models (LLMs) and visionlanguage models (VLMs) under real-time constraints. The game runs through a Gymnasium-like control loop that exposes both frames and structured state while the agent emits button actions. We deploy the system on Modal and stream matches overWebRTC, which lets us compare ability, latency, and cost in one setting instead of spreading them across unrelated benchmarks. Because the benchmark is narrow, architectural tradeoffs that are easy to blur in offline evaluation show up quickly during live play.

Rgfc: Registry Grounded Function Calling With Stage-Decomposed Evaluation, Ritvik Garimella, Vedant Khandelwal, Anvi Kohli, Amit Sheth

Publications

Tool-calling evaluations often report whether the final call matches a reference answer, but this single outcome merges different failures: choosing a function outside the available registry, violating the selected schema, or filling arguments with values not supported by the user request. These failures matter more when models must choose from larger tool registries. We introduce RFCD, a registry-scaled function-calling benchmark built from BFCL, Glaive Function Calling v2, and Tool-Call-Data, with standardized JSON-schema registries ranging from 5 to 3,000 functions. We also introduce TAAG, a deterministic stage-decomposed evaluator for registry conformance, structural completeness, and argument grounding. Across six locally served sub-4B …

Lightweight Attestation Techniques For The Industrial Internet Of Things, Syed Owais Athar

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The Industrial Internet of Things (IIoT) has transformed critical infrastructure by integrating programmable logic controllers (PLCs) with connected sensors, actuators, and supervisory systems. While these advancements enhance operational efficiency, they also increase exposure to sophisticated cyber-physical threats, particularly through malicious modifications of PLC programs. Existing attestation methods either impose significant computational burdens by performing continuous verification or rely on detailed physical models that are often impractical to maintain across heterogeneous environments.

The first part of this thesis focuses on DuAtt, a dual-layer attestation scheme that integrates a physical process–based anomaly detection mechanism with a targeted attestation of the PLC program. …

Design And Verification Of The Multi-Slit Solar Explorer Camera Field Programmable Gate Arrays, Jordan M. Johnson

All Graduate Reports and Creative Projects, Fall 2023 to Present

The Multi-Slit Solar Explorer, or MUSE, is a NASA mission that will take images of the Sun to study solar flares and the solar corona. The mission will provide insight into the mechanisms behind space weather. The mission consists of two cameras: the Spectrograph (SG), and the Context Imager (CI). The Utah State University Space Dynamics Laboratory is providing both cameras for the mission.

This report describes a part of the design and verification process for a central component on these cameras known as the Field Programmable Gate Arrays (FPGAs). These FPGAs are programmed to acquire, handle, and send images …

A Maintenance-Aware Machine Learning Framework For Network-Level Highway Pavement Condition Prediction, Jin Hwan Kim, Guk Gon Song, Youngguk Seo

Faculty Articles

This study develops and validates maintenance-aware machine learning models for predicting the Highway Pavement Condition Index (HPCI) on the Korean expressway network. Multiple regression and tree-based models were trained and tested using the pavement condition surveys archived in the Highway Pavement Management System (HPMS). A stacking regressor that integrates random forest, gradient boosting, and extreme gradient boosting as base learners exhibited the most robust predictions. Performance metrics indicated that the stacking ensemble achieved a mean absolute error of 0.21, a root mean square error of 0.31, and a coefficient of determination exceeding 0.73 on the testing dataset. Also, the residuals …

Culturally Inclusive Usability Engineering (Ciue): A Framework For Evaluating Cultural Inclusion In Study Abroad Platforms, Louis Muhammad

Master's Theses

Study abroad programs provide students with opportunities to develop global com- petence and intercultural understanding. However, the digital platforms that support these programs often fail to communicate information that reflects the cultural and faith-based needs of diverse student populations. While prior research in Human-Computer Interac- tion (HCI) and usability engineering has explored cross-cultural and accessible design, cultural and religious considerations are rarely integrated into usability engineering pro- cesses. This thesis introduces the Culturally Inclusive Usability Engineering (CIUE) frame- work, which extends traditional usability engineering by integrating culturally informed con- siderations into the system development lifecycle. CIUE begins by identifying the …

Database State Reconstruction And Audit Log Reconciliation For Data Systems Security, Mahfuzul I. Nissan

LSU New Orleans Theses and Dissertations

Modern organizations rely on diverse database management systems to store critical data across heterogeneous storage architectures. These platforms complicate forensic investigations because database engines vary profoundly in their layouts, encodings, and update policies. Malicious insiders can exploit this architectural opacity to alter data and disable audit logging undetected, leaving investigators with an untrusted view of database activity. Furthermore, building custom forensic solutions for every database version is fundamentally unscalable.

This dissertation advances data-system security through a tamper-aware, cross-layer framework that reconstructs database states and detects unauthorized operations even when audit logs are manipulated. By unifying the analysis of physical storage …

A Machine Learning-Based Apogee Prediction Methodology For Experimental Student Rockets, Price Hamilton Drawdy

Senior Honors Theses

The ability to predict the maximum altitude of a rocket (apogee) in real-time is incredibly useful for collegiate-level competition rockets. This project creates a machine learning-based real-time apogee prediction methodology. Three model types were tested: linear regression, random forest, and a 3-layer multi-layer perceptron (MLP) neural network. These models were trained on a large dataset of simulated flights. All models performed well on simulated test flights, with the linear regression model showing most promise for use on edge compute. More development and real-world testing are necessary to determine how applicable this method is for real-time operation. Nevertheless, this methodology provides …

Analyzing The Writing Style Of Generative Ai When Prompted With Writing Samples, Samuel Mcdowell

Senior Honors Theses

Authorship attribution is an important topic in today’s world of Large Language Models (LLMs). It is the technology that helps to verify the author of a written work. This study explores whether LLMs can successfully mimic an individual’s writing style if they are given a text sample. A dataset of human-written texts was collected and used to prompt several LLMs to generate new texts that attempt to replicate the original author’s stylistic characteristics. The generated texts were then tested with modern authorship attribution models to determine whether they would be identified as being written by the original author. The results …

A Full System Co-Simulation Platform For Evaluating Edge Machine Learning Inference Using Compute-In-Memory, Belsen Lee

Electrical Engineering and Computer Science (MS) Theses

We present a full-system co-simulation platform for evaluating embedded machine learning (ML) inference using compute-in-memory (CIM). CIM architectures aim to reduce data movement overhead by performing matrix operations in memory, but end-to-end benefits depend on system-level integration costs that are difficult to assess with isolated hardware models alone. To address this gap, we develop an integrated RISC-V QEMU-SystemC co-simulation environment that allows standard embedded Linux to interact with a transaction-level CIM accelerator model via memory-mapped I/O, direct memory access (DMA), and interrupts. To evaluate performance, we benchmark an MNIST image inference workload and a synthetic fully connected neural network, comparing …

Leveraging Code Embeddings To Identify And Address Blind Spots In Benchmark Creation, Charles Moloney

School of Computing: Dissertations, Theses, and Student Research

Formal software verification remains critical for early vulnerability detection, yet benchmarking these tools is costly and often reliant on centralized datasets such as SV-COMP. While such repositories enable standardized evaluation, they introduce risks of overfitting and bias, particularly due to first-party benchmark contributions. To address these limitations, we extend ARG-V, our tool for generating SV-COMP-compatible benchmarks from real-world Java code, with a novel approach of using code embedding techniques to selectively sample from mined code. By leveraging Nomic Embed Code and a cosine-based Minimum Hyperspherical Energy (MHE) objective, we systematically select and transform benchmarks from scraped GitHub code that …

Application Of Maritime Non-Line-Of-Sight Relay Attack On Wireless Digital Communication, Nathan Meyer

School of Computing: Dissertations, Theses, and Student Research

As wireless communication becomes increasingly prevalent, securing information over wireless channels is an ongoing challenge, especially in maritime environments where communication depends on radio links. While higher layer wireless attacks have been widely studied, lower level physical-layer relay attacks in maritime settings have received less attention. This thesis presents a simulation of a maritime relay attack in a beyond line-of-sight wireless environment for study. A three antenna communication model is developed where a legitimate transmitter sends a digital wireless signal, an attacking antenna intercepts, modifies, and retransmits the signal, and a final receiver observes both the direct and relay transmission. …

Ai-Assisted Frame Selection For Sports Photography Using Computer Vision And Multi-Modal Image Metrics, Sahana Ganesh

Honors Scholar Theses

This project focuses on the design and development of an AI-assisted frame selection system that automatically analyzes sequences of sports images and ranks frames based on overall photographic and contextual value. Additionally, we will focus on providing insights into the Computer Vision and Artificial Intelligence techniques used to build it.

The application utilizes computer vision and machine learning techniques to evaluate multiple dimensions of image quality and content. These include technical image quality metrics such as sharpness, motion blur, and exposure; compositional metrics such as subject placement and visual balance; and semantic understanding through detection of players, ball location, pose, …

Autonomous Deficiency Detection And Vision-Language Summarization For Underground Infrastructure On Embedded Edge Systems, Johny Lopez

LSU New Orleans Theses and Dissertations

Aging underground infrastructure poses significant risks to public health and environmental safety, yet structural condition assessment remains bottlenecked by labor-intensive manual CCTV inspections. This thesis proposes a comprehensive algorithmic framework enabling fully autonomous, real-time deficiency detection, geometric assessment, and natural language reporting on resource- constrained edge computing platforms. Three core components address this challenge. First, RAPID-SCAN, a novel semantic segmentation architecture utilizing a Dynamic Feature Pyramid Network and Channel-Spatial Attention, achieves real-time, pixel-precise defect localization with dramatically reduced parameters. Second, an Edge-Optimized Vision-Language Model pipeline employing LoRA and 4-bit QLoRA quantization compresses Phi-3.5 for local deployment, en- abling autonomous technical …

Faster Than The Speed Of Bram: In-Memory Computing For Next Generation Fpgas On The Edge, Nathaniel Joseph Fredricks

Graduate Theses and Dissertations

Traditional computer systems are hitting the Memory Wall as machine learning applications are bottlenecked by the bandwidth between separate memory and compute units. Current FPGA architectures are able to bypass this bottleneck with block RAMs (BRAMs) that provide on-chip, in-fabric storage. However, their potential as the foundation of computing components is often overlooked; machine learning accelerators implemented on FPGAs face additional delays when transferring data between memory and compute units. These penalties arise from BRAM bandwidth limitations and movement of data through the reconfigurable fabric. To support FPGA-based accelerators on the edge and break the Memory Wall, reconfigurable architectures must …

Asynchronous Polymorphic Logic Locking, Kelby Haulmark

Graduate Theses and Dissertations

This work presents Asynchronous Polymorphic Logic Locking (APLL), a logic locking methodology that integrates polymorphic logic within the Multi-Threshold NULL Convention Logic (MTNCL) paradigm. APLL achieves Boolean satisfiability-attack resilience through a fault-based logic stripping approach followed by logic restoration, while leveraging the analog, dual-functionality of polymorphic gates to impede reverse engineering and removal attacks. In contrast to comparable SAT-resistant logic locking techniques, APLL provides inherent resistance to reverse engineering, reducing the viability of a broad class of attacks that rely on access to the locked netlist. A complete automated design flow is developed, enabling the transformation of combinational circuits into …

Parallelism In Java, Matt Vierow

Departmental Honors & Graduate Capstone Projects

Parallelism and multithreading have become an important facet of programming in recent years. Much work has been done in programming languages such as C and C++ with libraries such as OpenMP. However, less effort has been made to create parallelism tools in higher level languages such as Java. This is important because most programmers learn the basics in languages such as Python and Java that lack parallel tools like OpenMP. This means they must directly manage threads which requires knowledge of object-oriented programming and design.

This project sought to incorporate some elements of OpenMP into Java to allow newer programmers …

Uav-Based Sensor Integration For In-Situ Lake Water Quality Monitoring, Alec R. Campbell

Biological and Agricultural Engineering Undergraduate Honors Theses

Surface water monitoring is often constrained by limited spatial and temporal coverage due to the labor-intensive nature of traditional sampling methods, particularly in environments that are difficult to access or pose safety risks. Unmanned aerial vehicles (UAVs) offer a promising solution by enabling more frequent, spatially distributed, and cost-effective data collection. This study presented the design, development, and field evaluation of a UAV-based system for real-time, in-situ water quality monitoring. The system integrated multiple sensors, including oxidation-reduction potential (ORP), RGB spectrometry, pH, electrical conductivity (EC), dissolved oxygen (DO), and a multispectral spectrometer within a UAV platform.

Field testing was conducted …

Comparative Analysis Of Secure Messaging Systems: Peer-To-Peer Vs Client-Server Architecture, Maddie Luth

Theses/Capstones/Creative Projects

This research serves as an honors extension of a capstone project sponsored by Northrop Grumman, focused on the development of a secure messaging application, LockTalk. The study evaluates the performance of peer-to-peer and client-server network architectures within a messaging system. It compares these architectures based on key factors such as security, privacy, and reliability. The results are used to determine the most suitable architecture for implementation in LockTalk, with particular emphasis on protecting sensitive communications. This work highlights the trade-offs involved in selecting a network architecture and provides guidance for developing secure and efficient messaging platforms.

Effectiveness Of Quiz-Based Interventions In Virtual Reality Lectures On Learning, Mason T. Prather

Master's Theses

This thesis examined whether quiz-based interventions affect learning during an immersive virtual reality (VR) lecture and whether quiz timing strategy matters when prompts are delivered on a fixed timer or through gaze/Region of Interest (ROI)-based attention timing. The study used an eye-tracking virtual reality headset and a game engine-based classroom application. The final completed cohort included 29 participants assigned to three between-subjects conditions: No Intervention (n = 10), Timer-Based Intervention (n = 9), and Attention-Based Intervention (n = 10). All participants viewed the same virtual reality lecture and completed the same 15-item post-lecture assessment. Mean learning scores were 44.00% for …

Protocol-Aware Enforcement-Point Postcards And Collector Feedback For Ot/Ics Forensic Readiness And Closed-Loop Defense, Haden Fowler

Electrical Engineering and Computer Science Undergraduate Honors Theses

In this work, we apply P4-programmable switches to Operational Technology (OT) and Industrial Control System (ICS) traffic with the objective of turning enforcement decisions into structured forensic evidence that can also support fast, scoped feedback. OT investigations often rely on later correlation of endpoint logs, passive packet traces, and historian data, but those sources can be incomplete, hard to align in time, and missing the decision made at the enforcement point. We address this gap by implementing a P4-based enforcement switch that parses Modbus/TCP write traffic, applies protocol-aware policy checks, and exports protocolaware postcards to a collector. The collector stores …

Stretch Web Teleoperation Keyboard Final Report, Aaron Chou, Francisco Irazaba

Computer Engineering

This project added keyboard controls to the Hello Robot Stretch Web Teleop interface. The goal was to make the robot easier to control from a web browser without needing a gamepad or separate terminal-based keyboard program. The new interface allows users to control different parts of the robot with customizable key bindings.

Low-Cost Rf Exposure Monitoring With Tinyml Prediction, Sanad Sahawneh

Nanoscale Science & Engineering (discontinued with class year 2014)

The proliferation of wireless technologies has produced a dense, increasingly heterogeneous radio-frequency (RF) environment that surrounds modern life. While regulatory bodies such as the Federal Communications Commission (FCC) and the World Health Organization (WHO) maintain exposure guidelines, the tools that ordinary people, educators, and small institutions can use to actually observe RF exposure in their own spaces remain expensive, specialized, and largely confined to professional laboratories. Spectrum analyzers and calibrated field probes routinely cost between five hundred and one hundred thousand dollars per unit, placing continuous local monitoring out of reach for most environments where exposure questions are most natural …

Learning Adaptive Control For Safe Collaborative Autonomous Driving, Fabian Alexis Hernandez

Theses and Dissertations

Connected autonomous vehicles improve urban driving through collaborative perception via Vehicle-to-Everything (V2X) communication. Frameworks such as V2Xverse leverage this collaboration for planning and perception, yet their controllers rely on fixed parameters that cannot adapt to varying traffic. Control Barrier Functions (CBFs) enforce safety by constraining actions within a safe set, but a fixed barrier gain imposes a single operating point: conservative settings reduce throughput while permissive settings under-react to hazards.

This research proposes an adaptive CBF framework that learns state-dependent, class-specific barrier gains via constrained Reinforcement Learning (RL). A compact policy outputs separate gains for vehicles, pedestrians, and bicycles, parameterizing …

Design Of A Low-Power Magneto-Inductive Magnetometer, Rowan Antonuccio

All Graduate Theses and Dissertations, Fall 2023 to Present

Measuring magnetic fields in space helps scientists understand phenomena that can affect satellite communications and navigation systems on Earth. This research develops a new low-power magnetic field sensor for spacecraft that improves upon existing designs by moving the sensitive parts away from electrical interference and using energy-efficient digital electronics for precise measurements. The sensor’s power-efficient design is particularly important for small satellites, where power is limited and must be carefully managed. It will fly on future NASA missions to study disturbances in Earth’s upper atmosphere that can disrupt radio signals and GPS. This work contributes to our ability to better …

A Novel Approach To Creativity Assessment: Forced Pairwise Ranking With Large Language Models, Phillip R. Gregory Jr

Master's Theses

Assessing creativity at scale remains a persistent challenge in cognitive science, as human raters are costly, slow, and often inconsistent in their judgments. This thesis introduced a novel framework for automated scientific creativity assessment using forced pairwise ranking, in which fine-tuned large language models compared response pairs and determined which was more creative. Five empirical studies were conducted using Llama-2-7B and Llama-2-13B models adapted via LoRA fine-tuning and benchmarked against human scored responses from the Scientific Creative Thinking Test. A regression baseline achieved Pearson �� = .74 on the test set, matching the human inter-rater ceiling reported in the literature. …