Engineering Commons^™

From Retrieval To Generation: Building And Evaluating An Ai Accompanist For Piano Duets With An Anticipatory Music Transformer, Sai Ruthvik Uppala

Masters Theses

Systems that accompany a live musician, such as ACCompanion, work by retrieval: they hold a written accompaniment and stretch its timing to follow the soloist, so they can only accompany music whose second part already exists as a score. This thesis asks whether that second part can instead be generated, and specifically whether a machine learning model can write an accompaniment for a piece whose score it has never seen. A player performs the primo, the melody; a model produces the secondo, the accompaniment; and a score follower places the generated notes against the live performance. If this works, a …

Creating An Updated Risc-V Platform With Hypervisor Support, Carter A. Glatt

Masters Theses

Virtualization has become an important methodology for implementing security and efficiency in embedded systems design. Virtualized environments provide flexibility and scalability of user-space environments, as hardware capabilities allow for multiple environments to run concurrently using the same hardware without impacting system performance or cost metrics. The ability to implement virtualized environments is fundamentally based on the instruction set architecture (ISA), which implements the necessary commands to facilitate the interface between physical hardware and virtual components.

RISC-V is an open-source ISA that can be used to generate platforms that support virtualization through the use of the H-Extension ISA. Previous research into …

Design And Characterization Of A 3d-Printed Dual Stacked Patch Antenna With Tunable Coupling For Uav Applications, Isabelle Lynn Brigman

Masters Theses

Antennas are a critical component of unmanned aerial vehicle (UAV) communication systems where compact size, light weight, and reliable operation across multiple frequency bands are critical. While microstrip patch antennas are attractive for UAV applications due to their low profile, low cost, and ease of fabrication, they are often limited by narrow bandwidth and fixed-frequency operation. To address these limitations, this thesis investigates a mechanically and electrically reconfigurable dual-stacked patch antenna fabricated using additive manufacturing techniques.

The proposed antenna consists of a slotted driven patch operating near 2.5 GHz with a second resonant mode near 5 GHz. A parasitic patch …

Investigation Of Inlet Turbulence Effects On Mixing Characteristics Of A Jet In Crossflow, Erin Jagger

Masters Theses

Gas flaring is widely used in the oil and gas industry to dispose of excess waste gas, and improving flare efficiency is critical for reducing emissions. Flare performance depends strongly on turbulent mixing between the flare gas and surrounding crossflow. While previous studies have examined the effects of crossflow velocity and low turbulence levels, the combined effects of crossflow turbulence intensity and integral length scale on mixing remains insufficiently understood.

This study uses a non-reacting jet in crossflow (JICF) configuration to represent the mixing process between the flare and crossflow interaction. Using computational fluid dynamics (CFD), Reynolds-Averaged Navier-Stokes (RANS) simulations …

A Cross-Dataset Vision Transformer Study For Brain Tumor Mri Image Classification, Sharon Kawira Mungania

Masters Theses

Brain tumor MRI classification is an important medical-imaging task because MRI scans contain complex anatomical patterns that can be time consuming to interpret manually. This study evaluates whether a pre-trained Vision Transformer can classify brain tumor MRI images consistently across datasets with different class structures. Three publicly available Kaggle datasets were used: Nickparvar, Br35H, and Figshare. Nickparvar and Figshare were treated as multi-class classification tasks, while Br35H was treated as a binary tumor/no-tumor task. Images were converted to three-channel format, resized to 384 × 384 pixels, normalized using ImageNet statistics, and augmented during training. The selected model was ViT-Base Patch …

Automating Distillation Column Internals Design Via Reinforcement Learning: A Hybrid Action Space Approach, Holden B. Broussard

Masters Theses

Distillation columns are the most used separation technique in all chemical fields. The design of column internals presents a hybrid action space problem, where trayed internal parameters are continuous and packed parameters are discrete; Hybrid meaning the action space consists of both discrete and continuous design parameters. Hybrid action spaces have presented a challenge in the reinforcement learning space, since the most robust algorithms are designed to handle specific action types. This research develops and validates a hierarchical multi-agent reinforcement learning framework that divides the action spaces into different agents. The Controller agent selects between internal types, the Soft Actor- …

A Simulation-Based Lean Six Sigma Framework For Process Optimization In Textile Manufacturing Toward Industry 4.0, Md Shafiqul Islam Chowdhury

Masters Theses

This study focuses on integrating simulation modeling with Lean Six Sigma (LSS) within the DMAIC (Define, Measure, Analyze, Improve, Control) framework for process optimization in textile manufacturing industry. Although traditional LSS framework such as Value Stream Mapping (VSM) and Root Cause Analysis are effective in identifying waste, they mainly rely on static and historical data which make their capability limited for real analysis or predictive decision making. As a result, many textile manufacturing processes still face challenges such as production delays, excessive work-in-process (WIP), high cycle time, and inefficient resource utilization. To address this issue, this research proposes a simulation-based …

Hyperdimensional Computing For Edge And Mobile Devices, Colin Eddy Dupuis

Masters Theses

This thesis presents a set of four Hyperdimensional Computing (HDC) frameworks and their Android application implementations to evaluate efficiency and feasibility on resource-constrained devices. These proposed methods target a range of application domains, including wearable health monitoring, mobile malware detection, and activity recognition utilizing both computer vision and multiple sensor streams as input. The proposed frameworks utilize HDC’s simple, lightweight arithmetic operations to convert raw data into high-dimensional representations for use in both binary and multi-class classification schemes. Each method utilizes unique encoding techniques tailored for each use case, demonstrating the flexible nature and specialization HDC offers as an emerging …

Geological Carbon Storage In Deep, Low Permeable Shale Reservoirs: Insights From The Haynesville Formation, Louisiana, Himakshi Goswami

Masters Theses

As global initiatives to mitigate greenhouse gas emissions intensify, depleted unconventional shale gas formations have emerged as critical candidates for large-scale geological carbon storage (GCS). This study investigates the feasibility, dynamic trapping mechanisms, and operational optimization of CO₂ sequestration in deep, low-permeability shale reservoirs, using the Upper Jurassic Haynesville Shale in northwest Louisiana as a comprehensive case study. Compositional reservoir simulation (CMG GEM 2021.10) was performed using the SPE Haynesville dataset, with CO₂ injected at a rate of 10,000 ft³/day across single and multiple depth intervals spanning 11,290–11,314 feet. Results demonstrate that multi-depth injection significantly improves residual trapping, reduces buoyancy-driven …

Mitigating Surfactant-Gas Interactions In Associated Gas Reservoirs: A Simulation And Machine Learning Guided Approach, Francis Dela Nuetor

Masters Theses

Surfactant flooding is a promising chemical enhanced oil recovery (EOR) method for mobilizing residual oil through interfacial tension reduction and wettability alteration. However, its performance in associated-gas reservoirs can be limited by salinity, gas composition, surfactant adsorption, and possible chemical instability. This study investigates the effect of salinity on surfactant flooding efficiency using an integrated reservoir simulation and machine learning workflow. A synthetic three-dimensional reservoir model was developed in ECLIPSE using a 10 × 10 × 3 Cartesian grid to simulate surfactant flooding over a 300-day production period under salinity conditions ranging from 100 to 50,000 ppm. Key outputs, including …

Optimizing Co₂ Wag Flooding Parameters For Enhanced Oil Recovery And Formation Damage Control In Asphaltene Reservoirs Using Soft Experimentation, Derrick Amoah Oladele

Masters Theses

CO₂ Water Alternating Gas flooding has become an important enhanced oil recovery process in increasing oil production in medium to heavy oil reservoirs. However, CO₂ injections have the potential to cause asphaltene destabilization, leading to precipitation, deposition, and pore plugging. This study evaluated and optimized the effect of CO₂ flooding parameters to maximize oil recovery and minimized formation damage. Eclipse 300 compositional reservoir simulator was used to assess the effect of CO₂ Water Alternating Gas (WAG) Injection Rate, WAG Ratio, and CO₂ Water Alternating Gas (WAG) Injection Pressure on the reservoir. Predictive models for Cumulative Oil Production (FOPT) and Asphaltene …

Wake-On-Anomaly Federated Architecture For Privacy-Preserving Poultry Health Early Warning, Mahmoud Aziz Louati

Masters Theses

Highly pathogenic avian influenza outbreaks, respiratory disease, heat stress, and silent equipment failures share one operational reality: they are detected too late because today’s poultry-health workflow is reactive, manual, and dependent on producers volunteering commercially sensitive data. This thesis presents a wake-on-anomaly federated architecture that addresses both the detection-latency problem and the privacy–adoption deadlock that has so far prevented cross-farm collaboration. The architecture is organized in two tiers. Tier 1 is a lightweight LSTM autoencoder that continuously screens four routine telemetry channels (water, feed, house temperature, activity proxy) and emits a per-window reconstruction-error score. A debounced k-of-m trigger with cooldown …

Sentience, Sheetal Agrawal

Masters Theses

The increasing urgency for sustainable and adaptive systems has driven research toward embedding intelligence directly into materials rather than relying solely on external sensing and control systems. This thesis explores how smart material1 embedded systems can be designed to recognize and respond to environmental signatures, defined as measurable patterns such as temperature fluctuations and mechanical forces. Central to this investigation is the integration of shape memory alloys, particularly Nitinol, with geometry-based actuation mechanisms that amplify material behavior into functional system responses.

The central argument is that designing with smart materials is a design problem, not primarily a materials science problem …

Somatic Prosthetics For Planetary Resonance, Disha Dharesh Kumar R

Masters Theses

This thesis investigates how industrial design can transcend extractive technological paradigms in favor of relational interfaces that foster planetary attunement. Framing the climate crisis as a 'crisis of imagination', the research challenges the Western bifurcation of nature and culture by drawing on Indic cosmologies- which recognize stones, plants, and ecosystems as conscious at different levels and participants in a shared cosmic field. By synthesizing research in Biosemiotics, Quantum Information Pansycishm, and Neuroscience, the project redefines intelligence as a distributed, more-than-human phenomenon.

The research materializes as a speculative design artifact: a device that functions as a somatic prosthetic for planetary resonance. …

Material Costs, Karima Weinman

Masters Theses

This thesis investigates how migration fatality and disappearance data can be reinterpreted through material craft to create a more reflective encounter with information. Working with the Missing Migrants Project's dataset, this project asks how design can communicate dimensions of human loss that conventional data visualization cannot reach.

The work situates contemporary border violence within a longer colonial history, arguing that the logics of surveillance and quantification that structured European imperial expansion persist in the databases that govern mobility in the Mediterranean today.

Terrazzo is a 15th-century Venetian flooring technique built from discarded fragments bound together into a unified surface. This …

The Use Of Tactile Stimulations To Mitigate Somatic Anxiety Responses: A Pilot Study, Abigail C. Robbins

Masters Theses

Anxiety is the body’s response to detected danger or stress. Physiological responses include shallow breathing, increased heart rate, sweating, shaking, and muscle tension. Roughly 33.7% of the population experiences anxiety, with approximately 40 million adults in the United States being affected by the disorder. Anxiety can create severe personal, social, and economic burdens. Traditional treatments of anxiety disorders such as medication and psychotherapy can be effective, but present multiple barriers such as cost, accessibility, and side effects. As a result, there is a growing industry for non-invasive, low-cost solutions that can help individuals regulate their physiological anxiety responses and reduce …

Experimental Measurements Of The Forces Acting On A Submerged Beam Using High-Speed Videography, Madelyn Burrell

Masters Theses

The interaction of structures and fluids is highly relevant in many fields but difficult to accurately and reliably characterize. This study demonstrates a novel method of simplifying such problems by analyzing the structural deformations directly, without needing to explicitly solve for the fluid aspect. Six cantilever beams of varying properties were submerged in still water and released from an initial deflection at the free end: the cases consisted of three beam shapes (one of uniform width, one with a narrower free end, and one with a wider free end), with an end mass attached or detached. High-speed videography was utilized …

Improving Human Visual Search: Enhancing Lung Cancer Nodule Detection In Medical Images, Christopher Khajira

Masters Theses

Human visual search involves the identification of relevant signals within information-rich environments, which is a fundamental problem in visual perception. While detection accuracy and response time are commonly used to evaluate performance in visual search, these measures do not reveal the underlying cognitive and computational structure that produces observable behavior. A key challenge lies in distinguishing between competing processing architectures, particularly in complex visual domains where different models can produce similar behavioral outcomes. This study addresses this challenge by developing a computational experimental framework for analyzing visual search behavior using System Factorial Technology (SFT). The experimental framework integrates naturalistic medical …

Capacity Reduction Factors For Steel Beam Ends With Holes, Kevin Saleh Makubuli

Masters Theses

The presence of holes at steel beam ends can decrease the nominal resistance (capacity) of beam ends. Codes such as AASHTO LRFD and AISC include equations for evaluating the nominal resistance of steel beam ends. While these equations are appropriate for as-designed beam ends, they may not apply to deteriorated beam ends, such as those with holes. Thus, this study aims to develop procedures to calculate the capacity of steel beam ends with holes. First, the FEA of an as-designed beam is performed for capacity evaluation (numerical result). The latter is compared with the analytical result (as-designed beam capacity) to …

Transformer Vulnerability To Geomagnetically Induced Currents Using Layered Soil Conductivity Models, Junior A. Sterling

Masters Theses

Geomagnetically induced currents (GICs) pose a significant threat to modern power transformers connected to long high-voltage transmission systems, particularly in regions with low subsurface electrical conductivity. During geomagnetic disturbances (GMDs), time-varying magnetic fields induce surface electric fields that drive quasi-DC currents through grounded transformer neutrals. These currents can bias transformer cores, leading to saturation, waveform distortion, and potential system instability. Despite extensive research, the role of regional Earth conductivity in shaping electric fields and transformer response remains an area requiring deeper investigation.

This study analyzes how contrasting Earth conductivity profiles influence GIC magnitude and transformer saturation risk using two representative …

Transient Mitigation In Dual Active Bridge Converter Using An Auxiliary Converter With High-Frequency Selective Control For Load Step-Down Condition, Sachith Dilshan Wijesooriya

Masters Theses

Dual Active Bridge (DAB) converters are widely utilized in applications such as electric vehicles, renewable energy systems, and solid-state transformers due to their high efficiency, galvanic isolation, and bidirectional power transfer capability. However, during rapid load transitions, DAB converters frequently exhibit significant output voltage overshoot and prolonged settling times, which increase device stress and adversely affect system reliability. This thesis proposes an auxiliary-circuit-based transient mitigation method to address these limitations. The auxiliary circuit, implemented as a bidirectional Buck–Boost stage, operates in Boost mode during load step-down events to absorb excess energy and suppress the resulting voltage overshoot. The design of …

Extremum Seeking Compensation And Quantification Of Position Sensor Offset Error In Speed-Controlled Permanent Magnet Synchronous Motors, Tessa Biondo

Masters Theses

Position sensor offset errors present a persistent challenge in speed-controlled permanent magnet synchronous motor drives operating under field-oriented control. Even small, constant offsets in the measured rotor position can reduce torque effectiveness, requiring increased current and voltage demand to maintain the commanded speed and resulting in degraded speed regulation performance across a range of operating conditions. These effects are particularly problematic in speed-controlled systems, where speed loop dynamics cause increased electrical effort and limit overall performance. Many existing detection and compensation approaches are either dependent on the system model, require offline calibration, or are primarily designed for torque-controlled operation. This …

Sdn Controller For Distributed Quantum Computing, Firas Selmi

Masters Theses

Quantum networks promise transformative capabilities for computation [1], but current hardware remains limited; state-of-the-art quantum processors still operate with only a few hundred qubits [2], far below the scale required for practical applications. This limitation motivates the use of Distributed Quantum Computing (DQC), where computation is performed across multiple interconnected nodes. However, efficient DQC requires global network awareness and orchestration, a role analogous to Software-Defined Networking (SDN) in classical systems. In this work, we investigate the impact of SDN-inspired control logic on quantum networks by executing a scaled distributed implementation of Shor’s algorithm to factor N = 15 over a …

A Modular Llm Approach To Argument Extraction In Philosophical Texts, Nate Miller

Masters Theses

Engaging with philosophical works is a rewarding but demanding task that challenges both human readers and computational systems designed to extract arguments from dense philosophical reasoning, and although large language models (LLMs) have made substantial progress in argument extraction, the most advanced models are often costly to run. As a result, there is growing interest in determining if multi-agent pipelines that divide a task into smaller stages can reduce cost while maintaining or improving performance.

This study investigates a modular multi-agent approach for extracting arguments from philosophical texts using LLMs, and compares its performance, cost, and runtime to both single-agent …

Investigating The Dynamic Rating Method: Effects Of Flood Wave Geometry On Discharge Estimation, Daniel James Read

Masters Theses

Rating curves are a vital tool to convert from observed stage to discharge in streamflow monitoring. Most gaging sites utilize a simple rating curve, which assumes a monotonic relationship between stage and discharge. In most cases, this assumption is valid; however, dynamic effects of flood waves often cause significant error in discharge estimation for mildly sloped streams. The dynamic rating method utilizes a numerical solution of the St. Venant Equations applied to time series stage data to compute discharge. Within this method, there is a flood wave parameter called the flood wave factor. The researchers designed a formal computational model …

Optimal Slotting In Hybrid Warehousing For Industry 4.0, Teng Yang

Masters Theses

In the era of Industry 4.0, the warehouse management system (WMS) employed by many firms prescribes hybrid storage, i.e., products with high turnover, called fast movers, are kept in random storage for a short time duration before being shifted to a dedicated storage area, while products with low turnover, called slow movers, remain in random storage. From dedicated storage, the products are dispatched to the customer. The challenge for managers is selecting the slot in dedicated storage to assign to each product while demand data change because of fluctuating market conditions; this problem is referred to as slotting in the …

Developing Discharge Estimation Algorithm Using Low-Cost Velocity Sensor And Machine Learning, Barkha Gautam

Masters Theses

Accurate river discharge estimation is essential for flood forecasting, water resources management, and hydraulic decision-making; however, continuous discharge records are unavailable at many river locations. Traditional stage-discharge rating curves are widely used but their reliability may decrease when channel conditions change or flow conditions vary rapidly. This study develops and evaluates Long Short-Term Memory (LSTM) models for discharge prediction using 15-minute time-series data from river monitoring stations in Missouri. Two model configurations, a baseline stage-only model and an enhanced stage-plus-velocity model, are developed and evaluated independently at two river sites to determine whether the inclusion of surface velocity improves discharge …

Calcium Based Carbon Negative Fillers And Additives: Effects On Hydration And Performance Of Low-Carbon Cement Systems, Smita Bhowmick Shithi

Masters Theses

Cement production is a major source of global CO₂ emissions creating an urgent need for carbon-negative fillers and functional additives that lower clinker use while maintaining cement performance. This thesis investigates the effects of organic mineral salts as fillers and additives on cement hydration, fresh properties, compressive strength and pore structure. In the first study, ordinary Portland cement (OPC) was partially replaced with calcium carbonate or calcium oxalate to enable a direct comparison under controlled particle size distribution (PSD). Rheology, flowability, hydration kinetics, phase evolution, mechanical performance and water absorption were evaluated. Calcium carbonate promoted early hydration through nucleation and …

Robust Broadband Characterization Of Flexible Absorbers, Sheet Material, And Liquids Using A Coaxial Structure, Joseph Christopher Stecher

Masters Theses

Modern high-frequency measurement systems require reliable calibration and sample positioning to ensure measurement fidelity. This thesis presents three studies addressing practical limitations in broadband material parameter extraction and instrumentation.

The first study introduces a modified Nicolson–Ross–Weir (NRW) technique for flexible, compression-sensitive materials from 100 MHz to 18 GHz. Rigid 3D-printed spacers ensure precise sample positioning, and a T-matrix–based de-embedding procedure removes spacer effects. Validation using microstrip measurements and full-wave simulation confirms accurate permittivity extraction across compression levels.

The second study extends NRW to sheet materials enabling accurate material characterization. Independent validation using toroidal inductors with leakage correction and parallel-plate capacitors …

Validating A Low-Cost Radio Frequency Characterization Framework For Development-Grade Software-Defined Radios In Short-Duration Cubesat Missions, Thomas Wayne Francois

Masters Theses

Software-defined radios (SDRs) and CubeSat platforms have reduced the cost and complexity of space-based communication systems, enabling broader participation in satellite missions. While low-cost radio hardware is increasingly accessible, the ability to characterize and validate its performance remains constrained by the high cost and limited access to traditional RF test equipment. This disparity creates a challenge for small satellite development teams, which must characterize communication-system technical performance with limited access to laboratory-grade instrumentation.

This thesis presents a low-cost RF characterization framework for assessing key radio-frequency performance metrics using readily available hardware and measurement techniques. The approach integrates frequency translation, SDR-based …