Engineering Commons^™

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 …

Investigation Of Low-Pressure Mercury Lamp System Configurations And Xenon Excimer Lamp System Development As Vacuum Ultraviolet Sources For Optimal Photolytic Degradation Of Poly-/Perfluoroalkyl Substances, Eman Zuhair Alhamdan

All Dissertations

PFAS are persistent synthetic chemicals, with unique properties that enable them to easily enter and accumulate in water sources. Their public health impacts have raised concern and highlighted the need for effective treatment. Numerous techniques for PFAS removal from water have been studied, few have proven the ability of breaking down PFAS rather than separating and concentrating it. Many of these methods are chain-length dependent, showing slower degradation rate of short-chain PFAS and requiring substantial amounts of energy, and chemical agents that may produce byproducts.

Among available PFAS destruction methods, direct photolysis by high-energy UV with wavelength below 200 nm …

Learning Global Context For Sparse Activity Recognition In Lengthy Recordings With Limited Dataset Size, Zeyu Tang

All Dissertations

This dissertation describes methods to analyze lengthy recordings of data in order to detect sparsely occurring activities. The narrative below describes the progression of research that led to the development of these methods and their generalization into a unified framework. My research started with designing models for dietary monitoring, including detecting meals from day-long recordings and detecting intake gestures from meal-length recordings. Both tasks share some common characteristics: (a) the target event takes only a small portion of data recordings, and (b) there is global context within full-length data recordings that can help a model make better decisions. After finishing …

Experimental And Computational Investigation Of The Effects Of Neck Musculature During Head Impacts In American Football, Anthony P. Marino

All Dissertations

Anthropometric test devices (ATDs) are human surrogate models used to represent the human body response in the context of compliance and safety testing. These devices are used in multiple industries, including automotive and aerospace, and have recently been incorporated into impact testing for the evaluation of helmet performance in American football. The Hybrid III 50^th percentile male ATD head and neck assembly is the most commonly used surrogate for these tests, although it was developed for automotive frontal crash scenarios that induce an inertial force on the body, leading to head and neck motion primarily in the sagittal plane. …

Versatile Exoskeleton Control Paradigms For Agile Human Locomotion: Task-Agnostic And Stability-Augmented Assistance, Miao Yu

All Dissertations

Lower-limb exoskeletons have shown great potential for assisting human locomotion, but designing controllers that provide assistance across diverse locomotor tasks and under external perturbations remains a major challenge. Many existing controllers for steady-state walking rely on pre-defined reference trajectories, which constrain voluntary human motion and limit adaptability across tasks. Moreover, they usually assume stable walking, while their performance under unstable conditions remains largely unexplored. In addition, existing gait stability augmentation controllers are often reactive rather than proactive to unstable conditions. In this dissertation, we propose control frameworks that preserve voluntary human motion while addressing two major challenges: providing task-agnostic assistance …

Quantifying The Value Of Adaptability: Bridging Real Options Analysis And Adaptable Building Design, Miranda Grice

All Dissertations

As the demands of the built environment continually evolve, buildings are expected to meet changing occupancy needs, or otherwise they become obsolete. Despite positive research on the benefits of adaptable building design, there is a knowledge gap regarding the long-term economic benefits of these designs. Practical methods are needed to determine if premium costs associated with adaptable designs are justified by the economic benefits inherent in adaptability. Therefore, this dissertation provides a discussion on the application of the financial theory of options analysis to the design of adaptable buildings. Additionally, a model and accompanying tool are presented as a solution …

Decision Making For Large-Scale Problems Under Uncertainty And Conflict, Benjamin J. Hamlin

All Dissertations

Large-scale decision-making problems appear in many areas including long-range forecasting such as energy generation forecasting. Many such problems are subject to conflicting objectives and uncertain data, and can be modeled as linear optimization problems. We study novel theoretical results and algorithms for large-scale linear decision problems under conflict and uncertainty. First, we propose a parametric Benders decomposition algorithm for solving large-scale linear optimization problems with multiple objectives or deterministically uncertain objectives. Second, we extend the parametric Benders decomposition to a multi-stage setting, developing a parametric stochastic dual dynamic programming algorithm, which enables decision-making when conflicts and uncertainty have planning impacts …

Modernizing Plastics And Composites Manufacturing Using Hybrid Modeling Techniques, Luke Shannon

All Dissertations

Plastics and composites manufacturing encompasses a broad family of processes, including injection molding, resin transfer molding, compression molding, and extrusion, that together account for the vast majority of polymer and composite component production worldwide. These processes are inherently challenging due to the multi-physics nature of polymer processing, the vast possible combinations of resins, reinforcements, and additives, and the strong dependence of final part properties on process history. Among these processes, injection molding is one of the most widely deployed, producing high-volume components across automotive, medical, consumer electronics, and packaging industries. However, accurately monitoring and predicting process behavior in injection molding …

Optimal Allocation Of Flexible Servers In Healthcare Systems, Tong Zhang

All Dissertations

This dissertation investigates the optimization of worker allocation in healthcare systems, focusing on flexible staffing models and the strategic prioritization of healthcare tasks. This research explores the dynamics among pre-operative, operative, and post-operative care units under various cost and service-rate constraints, using a series of models that represent realistic healthcare scenarios within a comprehensive framework for improving patient flow and reducing waiting costs.

In Chapter 2, we model and analyze cross-trained nurse allocation policies within an inpatient surgical system. We model the surgical system as a tandem clearing queueing system and formulate Markov decision processes under different business rules governing …

Development Of A Mixing-Controlled Combustion Model For 0d Engine Modeling: Using High-Order Models To Guide The Formulation Of Reduced-Order Models, James Gohn

All Dissertations

Vehicles are becoming increasingly complex to comply with the increasingly stringent regulations placed on all market sectors while still maintaining performance requirements. This increased complexity leads to increases in the cost and time it takes to develop and produce these next generation vehicles. To meet demand therefore, it becomes necessary to evaluate numerous design iterations using computer models. There are multiple levels of models that may be necessary for different purposes or use cases. All levels of modeling for virtual prototyping, however, require a level of validation and predictive ability to be useful. To this end, the following thesis presents …

Board-Level Operating System Infrastructure In Rust, Lydia Klaus

McKelvey School of Engineering Graduate Student Theses & Dissertations

Memory and multi-threading problems are the cause of many exploits and security vulnerabilities, and errors of this nature are easy to cause in programming languages such as C and C++. Despite this, these languages are still heavily used for systems programming and underpin the majority of operating system kernels. This is partially due to a lack of suitable replacements; however, Rust is becoming more prominent as an option for systems programming. This language features a much more stringent approach to memory and multi-threading safety. It also aims to support a wide range of hardware targets, including microcontrollers, which have long …

Side-To-Side Differences In Three-Dimensional Femoral Head Coverage Associated With Initial Symptom Development In Patients With Bilateral Developmental Dysplasia Of The Hip, Jiayi Sun

McKelvey School of Engineering Graduate Student Theses & Dissertations

Developmental dysplasia of the hip (DDH) is characterized by insufficient acetabular coverage of the femoral head and is a recognized cause of hip pain, instability, and early osteoarthritis. Although bilateral deformity is common, symptoms often first develop in only one hip. The purposes of this study were: (1) to determine whether, in patients with bilateral DDH, side-to-side differences in three-dimensional (3D) femoral head coverage vary according to radiographic symmetry defined by the lateral center-edge angle (LCEA); and (2) to determine whether hips that appear radiographically symmetric still demonstrate focal 3D asymmetry.

This retrospective imaging-based study included patients with bilateral DDH …

Analysis Of Oscillating Flow Over A 2-D Airfoil With Flow Reversal, Colter Couillard-Rodak

McKelvey School of Engineering Graduate Student Theses & Dissertations

Finite-state models are useful tools in modeling the aerodynamics of rotorcraft in flight simulators. 2-D and 3-D finite-state models have been developed and compared to closed form solutions, however these models are currently unable to handle situations where the freestream changes directions and the rotor re-enters its own wake. A 2-D finite state model was previously developed that includes a parameter that accounts for the change in free stream. This model, however, contains an inherent stability issue at the instant that the velocity changes direction.

The effects of this instability can be mitigated in certain flow conditions. A purely oscillatory …

Establishing Caenorhabditis Elegans As A Platform For Bioaccumulation And Selectivity Screening Of Anthelmintic Compounds, Jiarui Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

To address the cuticular barrier in anthelmintic discovery, this study establishes a bifurcated framework in Caenorhabditis elegans. First, HPLC-based quantification of 14 PIM inhibitors revealed that cuticular penetrance is primarily dictated by phylogenetic lineage (Clade V) rather than ecological niche. Specifically, C. elegans demonstrated a significant pharmacokinetic correlation with the hookworm Ancylostoma ceylanicum (Clade V) but not the whipworm Trichuris muris (Clade I), validating it as a superior surrogate model for hookworm bioaccumulation. Within this small molecule inhibitor library, SGI-12was identified as a lead candidate with superior potency against C. elegans and bioaccumulation. Second, target validation using a C. …

Multiscale Architecture Governs Stability In Suction-Actuated Variable Stiffness Catheters, Sheridan Lee

McKelvey School of Engineering Graduate Student Theses & Dissertations

Endovascular procedures require devices with widely varying mechanical properties: flexibility for navigating tortuous vessels and rigidity for stable therapeutic delivery. Suction-actuated variable stiffness sheaths address this challenge by incorporating axial wire string arrays that mechanically couple under suction to increase flexural rigidity. However, prototype devices achieve stiffening ratios below theoretical predictions, suggesting that interlayer mechanics and string positioning play a critical role. This study investigates whether interweaving polytetrafluoroethylene (PTFE) tape within the string array enhances flexural rigidity modulation and curvature stability. Prototype devices with varying wrap configurations were fabricated and evaluated using flexural testing, curvature stability testing, and mathematical modeling. …

Conditioning Hierarchical Diffusion Transformers On Rf Circuit Parameters, Ethan Morton

McKelvey School of Engineering Graduate Student Theses & Dissertations

As modern ML techniques have become increasingly advanced, they have begun to be integrated into wireless RF systems for classification, identification, and spectrum management. Deep Neural Networks (DNNs) enable RF system operators and designers to design more flexible systems with greater robustness to errors and attacks. However, neural networks require significant amounts of properly annotated data to train. Current data labeling methods lack the ability to obtain reliable true labels for circuit properties such as carrier frequency offset (CFO), power amplifier (PA) non-linearity, and in-phase/quadrature (IQ) imbalance. This thesis investigates the efficacy of a novel architecture, RF-Diffusion, for generating high-quality …

Data-Driven Multimodal Mri Representation Learning For Subtype Discovery And Disease Progression Modeling In Parkinson’S Disease, Zihan Zhou

McKelvey School of Engineering Graduate Student Theses & Dissertations

Parkinson’s disease (PD) exhibits substantial clinical and neuroanatomical heterogeneity, limiting robust patient stratification and clinically meaningful progression modeling from MRI. We propose a unified multimodal 3D generative representation-learning framework that learns an interpretable latent space from co-registered baseline T1/T2 MRI with an edge-aware channel. Confound-corrected latent embeddings support unsupervised subtype discovery, while disease duration provides weak supervision to orient a continuous progression axis. On an independent external cohort (PPMI, N=171), the discovery-trained subtype structure shows significant partial replication (ARI=0.35; permutation test p=0.001) and enables longitudinal clinical stratification: mixed-effects modeling reveals subtype-dependent MDS-UPDRS III progression, with the strongest effect in subtype …

Computational Fluid Dynamics (Cfd)-Based Performance Prediction Of Transcatheter Microvascular Plugs In Single-Ventricle Patients, Zhuhuan Zou

McKelvey School of Engineering Graduate Student Theses & Dissertations

Transcatheter palliation using fenestrated Modified Micro Vascular Plugs (MVP) has emerged as a promising, minimally invasive alternative to surgical pulmonary artery banding (PAB) for high-risk neonates with single-ventricle physiology. However, clinical applications are currently limited by the difficulty in predicting the resulting pulmonary-to-systemic flow ratio () and the lack of a standardized approach for selecting the optimal fenestration size. This study utilizes patient-specific computational fluid dynamics (CFD) to quantitatively evaluate the impact of varying fenestration diameters on circulatory balance. Patient-specific 3D models of the pulmonary artery (PA) were reconstructed from imaging data for two clinical cases using SimVascular. Transient CFD …

Reconfigurable Antennas Using Varactors On A Planar Parasitic Layer And Pin Diodes On A Dome Parasitic Layer, Andrew J. Hendricks

All Graduate Theses and Dissertations, Fall 2023 to Present

This research explores two types of reconfigurable, steerable antennas. These antennas change their beam direction based on electric input signals. The antennas have a layer that overlays the main antenna circuit board. The layer has small copper rectangles (pixels) that may be connected using either varactor diodes (which behave as voltage-controlled capacitors) or PIN diodes (electronic switches). The first antenna can steer in the xz-plane in any direction within about 23° from boresight (straight up from the antenna) and in the yz-plane to about 29° from boresight. The antenna uses varactor diodes on a planar layer. The second …

Freshwater Mussel Reintroduction And Recolonization Habitat Modeling Using Hydraulic, Sediment And Geomorphic Parameters, Megan Elizabeth Dinicola

All Graduate Theses and Dissertations, Fall 2023 to Present

Freshwater mussels are an important group of aquatic animals that live within the riverbed, but their populations have been drastically reduced by habitat alteration and other anthropogenic activities. In an effort to bolster populations, river managers and biologists are using mussel reintroductions as part of their restoration efforts but there are gaps in our understanding of where to reintroduce mussels within a river to see them create self-sustaining populations. This research helps shrink this gap by better understanding the physical habitat needs and population expansion potential of subadult freshwater mussels, or the size of mussel that hatcheries grow for reintroduction, …

Designing A Steel Bridge: A Structural Overview, Andrew Orr

Honors Theses

The American Society of Civil Engineers (ASCE) and American Institute of Steel Construction (AISC) host the Student Steel Bridge Competition (SSBC), a nation-wide competition where students design, fabricate, and construct a model bridge based on a provided rule set. A group of Arkansas State University civil engineering students participated in that competition in Spring 2026.

Extracting Wildfire Influence From Natural Streamflow Variability To Inform Post-Fire Peak Flow Predictions, Haley Anne Canham

All Graduate Theses and Dissertations, Fall 2023 to Present

Wildfire is a natural process, however, wildfire occurrence, severity, and size is increasing globally along with large storms. Despite the expectation that floods will be larger after wildfire, a large range in post-fire flood size has been observed. This creates challenges for emergency managers to prepare for flooding in areas where wildfire might occur. Aside from wildfire, many other factors influence the size of floods, making it difficult to isolate the influence of wildfire. This work finds that factors including wetter versus drier years and seasons can alter the size of a flood, effectively hiding the influence of wildfire. Additionally, …

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 …

An Experimental Study Of The Morphology Of Dna-Carbon Nanotube Hybrid Structures In Direct Dna Sequencing, Avery P. Davis

Biomedical Engineering Undergraduate Honors Theses

Hybrid structures formed between single-stranded DNA (ssDNA) and single-walled carbon nanotubes (SWCNT) have emerged as promising components in future direct DNA sequencing technologies due to their unique morphological and electronic properties. The nanoscale configuration of these hybrids, including the DNA wrapping angle, pitch, and contour behavior, directly influences their potential for stable electronic readout. This thesis presents an experimental study of DNA-SWCNT hybrid morphology using a fixed, reproducible wrapping protocol designed to minimize environmental variability and isolate the influence of DNA nucleotide sequence on hybrid structure. As described in prior work, this protocol produces well-dispersed hybrids suitable for high-resolution imaging. …

A New Approach To Generate Combinatorial Patterns In Logical Analysis Of Data And Its Application To Predict College Retention, Salihah Ahmed E. Jaafari

Theses and Dissertations

Student retention and degree completion remain central challenges for higher-education institutions, with significant implications for student success, institutional effectiveness, and public accountability. While advances in predictive analytics have enabled earlier identification of students at risk of withdrawal, many commonly used machine learning approaches suffer from limited interpretability, constraining their practical usefulness for advising, intervention, and policy decision making. This dissertation addresses the problem of predicting student persistence by developing and evaluating optimization based, interpretable classification models within the Logical Analysis of Data (LAD) framework. Building on existing LAD formulations, this research introduces two novel pattern generation models, the Best Term …

Hdra-Fusion: Hybrid Detection With Routed Architecture For Manipulation-Aware Ai Face Forgery Detection, Omar Ebeid

Theses and Dissertations

With the rapid advancements in artificial intelligence-based image generation and manipulation tools, it is extremely difficult to detect if an image is genuine or artificially crafted. Despite extensive research in this area, existing image detection systems suffer from three major problems: suboptimal cross-dataset generalization due to shortcut learning of dataset-specific patterns, unreliable probability estimates due to domain shift, particularly in cross-manipulation evaluation settings, and an inability to detect images manipulated by multiple types of manipulations within a single detection framework. To address these limitations, we propose HDRA-Fusion (Hybrid Detection with Routed Architecture), a framework built on the conclusion that different …

Design And Simulation Of Anti-Resonant Hollow-Core Fiber For Sensing Applications, Pravallika Kante

Theses and Dissertations

This thesis presents the design and simulation of an 8-tube single-ring anti-resonant hollow-core fiber for sensing applications, with particular emphasis on methane gas detection at the fundamental absorption wavelength of 3.3 µm. Conventional solid-core silica optical fibers exhibit strong multi-phonon material absorption beyond 2.5 µm, rendering them fundamentally unsuitable for efficient light guidance and direct gas sensing at mid-infrared wavelengths. Anti-resonant hollow-core fibers overcome this limitation by guiding light predominantly through an air-filled hollow core via the anti-resonant reflecting optical waveguide mechanism, in which the thin silica glass walls of the cladding tubes act as Fabry-Pérot etalons that confine the …

Mitigating Inertial Measurement Unit Drift In Quadcopter Trajectory Tracking Using Kalman Filter Sensor Fusion With Global Positioning Measurements, Juan Sandro Caballero Aguilar

Graduate Theses and Dissertations

Unmanned Aerial Vehicles (UAVs) like quadcopters are widely used in civilian and military applications such as farming, photography, search and rescue missions, and autonomous navigation and motion. The performance and stability of these systems depend on accurate state estimation, which provides real-time information about the vehicle’s position, velocity, and orientation. However, achieving reliable state estimation is challenging due to sensor noise, measurement uncertainty, and inaccurate modeling. Common navigation sensors such as the Global Positioning System (GPS) and Inertial Measurement Units (IMUs) exhibit complementary characteristics. GPS provides absolute position measurements but suffers from noise, multipath effects, and low update rates, while …

Multi-City Travel Routing Tool: Reducing Travel Costs And Time Spent Planning Using Apis, Trey R. Merreighn

Industrial Engineering Undergraduate Honors Theses

Travel planning is a time-consuming and ever-changing problem that can diminish the travel experience and greatly increase expenditure, if not done correctly. It is important to have an easy travel planning experience so you can enjoy the travel experience more and not waste time where it is not needed. This thesis aims to minimize the costs and time spent on travel planning using APIs and simple optimization models, creating a travel planning tool. This travel planning tool was developed in Java with the main API being Amadeus, this was combined with a greedy best-permutation heuristic to create the main route …

Reflective Analysis Of Industrial Engineering Leadership Skills Applied In Being A Capstone Team Leader, Sarah Nesmith

Industrial Engineering Undergraduate Honors Theses

This paper presents a reflective analysis of leadership skills that I, Sarah Nesmith, have acquired and applied as an honors student serving as a capstone team leader within the Industrial Engineering program at the University of Arkansas. My senior capstone project is in partnership with Walmart’s Transportation and Optimization Department and focuses on identifying the root and contributing causes of empty miles (miles driven without freight on a truck) and exploring backhaul opportunities. The ultimate goal is the development of a tool or method that can identify these opportunities to save money while maintaining service level. As the appointed team …