Digital Commons Network^™

Structural Controllability For Switched Linear Ensemble Systems, Yi Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

No abstract provided.

Towards The Performance Characterization Of A Robotic Multimodal Diagnostic Imaging System, George Papaioannou, Christos Mitrogiannis, Mark Schweitzer, Nikolaos Michailidis, Maria Pappa, Pegah Khosravi, Apostolos Karantanas, Sean Starling, Christian Ruberg

Publications and Research

Characterizing imaging performance requires a multidisciplinary approach that evaluates various interconnected parameters, including dosage optimization and dynamic accuracy. Radiation dose and dynamic accuracy are challenged by patient motion that results in poor image quality. These challenges are more prevalent in the brain/cardiac pediatric patient imaging, as they relate to excess radiation dose that may be associated with various complications. Scanning vulnerable pediatric patients ought to eliminate anesthesia due to critical risks associated in some cases with intracranial hemorrhages, brain strokes, and congenital heart disease. Some pediatric imaging, however, requires prolonged scanning under anesthesia. It can often be a laborious, suboptimal …

How Extreme Rainfall And Failing Dams Unleashed The Derna Flood Disaster, Ayman Mokhtar Nemnem, Ahad Hasan Tanim, Audrika Nahian, Sadik Khan, Erfan Goharian, Jasim Imran

Faculty Publications

On September 11, 2023, Storm Daniel unleashed unprecedented rainfall over the Wadi Derna watershed, triggering one of the most devastating floods in modern history, striking Derna, a coastal city in Libya. This study reconstructs the disaster using an integrated modeling approach that combines satellite imagery, hydrologic, hydraulic, and geotechnical simulations, machine learning, eyewitness accounts, and digital elevation data to assess the impact of cascading dam failures. Our findings reveal that the region’s dams, even if structurally sound, would have provided minimal protection against the extreme runoff. However, their failure unleashed a destructive surge wave, amplifying the disaster’s magnitude and devastation. …

How Extreme Rainfall And Failing Dams Unleashed The Derna Flood Disaster, Ayman Mokhtar Nemnem, Ahad Hasan Tanim, Audrika Nahian, Sadik Khan, Erfan Goharian, Jasim Imran

Faculty Publications

On September 11, 2023, Storm Daniel unleashed unprecedented rainfall over the Wadi Derna watershed, triggering one of the most devastating floods in modern history, striking Derna, a coastal city in Libya. This study reconstructs the disaster using an integrated modeling approach that combines satellite imagery, hydrologic, hydraulic, and geotechnical simulations, machine learning, eyewitness accounts, and digital elevation data to assess the impact of cascading dam failures. Our findings reveal that the region’s dams, even if structurally sound, would have provided minimal protection against the extreme runoff. However, their failure unleashed a destructive surge wave, amplifying the disaster’s magnitude and devastation. …

A Proposed Metals Recovery Assessment Protocol To Evaluate Mine Waste For Critical Minerals And Rare Earth Recovery Prior To Site Remediation, Claire Mbia

Graduate Theses & Non-Theses

The Metals Recovery Assessment (MRA) protocol involves collecting and evaluating information to assess the possibility for recovery of critical or rare earth minerals at mine sites to offset remediation or redevelopment costs associated with land reuse at Superfund or closed mine sites. This protocol provides a tool to implement metals recovery in conjunction with property reuse, and may involve a review of available records, visual inspections of the site, sample collection and discussions with local government officials and community members. The selection for metals recovery would be intended to both achieve metals reduction which may be required for the protection …

Predicting Sorption Of Diverse Organic Compounds In Soil-Water Systems: Meta-Analysis, Machine Learning Modeling, And Global Soil Mapping, Jiachun Sun, Kai Zhang, Huichun Zhang

Faculty Scholarship

In recent decades, the environmental detection of various organic compounds (OCs) has highlighted the limitations of conventional soil-water sorption models, which simplify complex experimental conditions and often overlook OCs with polyfunctional and ionizable structures. To address these shortcomings, we compiled a comprehensive soil-water sorption dataset encompassing 20,945 data points for 419 OCs with various functional groups and 1037 different soils. Meta-analysis of the dataset revealed the trends of soil sorption associated with OC substructures, soil properties, and solution conditions. Machine learning models employing the XGBoost algorithm, in conjunction with MACCS fingerprints and experimental conditions, were developed to cover the entire …

Breaking New Ground: Division Directly In Memory, M. Hassan Najafi, Mehran Shoushtari Moghadam

Faculty Scholarship

In-memory computing (IMC) has emerged as a promising paradigm for overcoming the limitations of traditional von Neumann architectures by reducing data movement and enhancing computational efficiency. Despite significant advancements in this area, implementing complex arithmetic operations, such as division, directly within memory has remained an elusive challenge. This paper introduces a pioneering technique for performing division operations directly in memory, representing the first successful integration of such functionality into the IMC framework. Our approach leverages an innovative circuit based on an unconventional model of computing–stochastic computing (SC). Our technique extends the computational capabilities of IMC systems and paves the way …

Role Of Fluid-Structure Interactions In Mechanosensation During Hovering Flapping Flight, Menglong Lei, Chengyu Li

Faculty Scholarship

Insect wings, known for their intricate structure and function, inherently deform during flapping motion. These deformations can be classified into chordwise cambering, spanwise bending, and root-to-tip twisting, arising from non-uniform venation distribution, aerodynamic loading, and wing inertia. Crucially, such deformations play a vital role in enhancing both aerodynamic performance and mechanosensory function. To investigate the complex interplay between wing structure, unsteady aerodynamics, and mechanosensation, we developed a fully coupled three-dimensional fluid-structure interaction (FSI) solver. This framework integrates an in-house Navier-Stokes equations solver for resolving the flow field with the open-source Vega FEM code to solve the solid structure dynamics. Our …

A Continuous-Heat-Flux Phase Change Model For Simulating Realistic Two-Phase Unsaturated Evaporation Processes, Thanh Hoang Phan, Cho Ning Huang, Chirag R. Kharangate

Faculty Scholarship

Accurately modeling liquid-vapor mass transfer rates is essential for optimizing cryogenic fluid management processes critical to advancing future space missions. This study introduces a continuous-heat-flux phase change model proposed to simulate conditions observed in realistic two-phase unsaturated evaporation phenomena. The mass transfer rate across the two-phase interface is calculated directly based on the local interfacial continuous heat flux on both liquid and vapor phases, effectively accounting for superheated, saturated, and subcooled liquid effects without requiring any empirical tuning parameters. Moreover, phase change occurs exclusively within interfacial cells, ensuring the sharp representation of deformed evaporating interfaces with high accuracy. The proposed …

Design And Assembly Of A Lightweight, Multi-Cannula Tetrode Drive For Bilateral Hippocampal And Acc Recordings, Homero Phelps, Jasmine Sidhu, Jonathan V. Trinidad, Talha Soluoku

Undergraduate Research Symposium Posters

Implants and Electrophysiology:

Electrophysiology is the study of the electrical properties of cells and tissues, neuronal implants enable high-resolution recordings of neuron action potentials and their locations in the brain.

Data gathered is key in investigating/mapping cognition and effects of neurological pathologies on regular neural systems.

Hyperdrive Model:

Previous model was restricted to two implant sites, and displayed frequent tetrode deformation

Hyperdrive was modified to support four implant sites and 16 independently movable tetrodes using 3D modeling software, while keeping its weight below 1.5 grams.

Targets:

Researchers targeted the hippocampus (CA1, CA3) and ACC, using the novel bilateral model

Re-Analysis Of The Anthropogenic Effect Of The Covid-19 Global Lockdown On Night-Time Lunar Surface Temperatures, W. Schonberg, S. Haque

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

A study by Durga Prasad and Ambily observed an anomalous decrease in the lunar surface temperatures during the period April–May 2020, which they then attributed to the anthropogenic effects of the COVID-19 global lockdown effect. We have re-examined their data and while the anomalous decrease in the lunar surface temperature during April–May 2020 appears in our analysis as well, so does another significant dip in early 2018. Furthermore, the decline to the minimum observed during April–May 2020 is seen to begin in 2019, that is, quite some time before the COVID-19 event that led to the global lockdown and the …

Using Scaffolding, Gamification, And Self Awareness To Create Responsive Ux/Ui In Cad Software To Nurture Metacognition In Novice Users, Obed Ibrahim Gonzalez

Graduate Theses and Dissertations

Computer-aided Design (CAD) software represents a significant shift from manual and analog design processes to digital workflows, offering substantial utility, accuracy, and productivity benefits. However, CAD software often presents a steep learning curve, particularly for novice users who are new to the software or possess only basic knowledge. Traditional CAD curricula have predominantly focused on technical problem-solving—teaching tools and systems—while often neglecting strategic knowledge that encompasses reflection, planning, and refining, which are essential components of metacognition. Metacognition is crucial for transforming novices into experts who use fewer and more complex commands, employ sophisticated planning, and achieve their goals more efficiently. …

Intelligent Crowdsourcing Based On Online Social Networks, Adedamola Adesokan

Electrical and Computer Engineering ETDs

The prevalence of Online Social Networks has completely changed how individuals communicate and cooperate. This dissertation explores the integration of intelligent crowdsourcing mechanisms into OSNs, focusing on game theory, reinforcement learn- ing, and social network dynamics to enhance the allocation of tasks, participation by users, and distribution of rewards. It proposes several models that utilize trust- based models, hedonic coalition games, and influencer dynamics for optimization of crowdsourcing. The major challenges to be addressed include task selection, reward distribution, and incentivizing participation, taking into consideration aspects re- lated to social influence, trust, and user engagement. The models so proposed have …

Sensors And Sensibilities: Exploring Interactions For Habitat Comfort With An Environmental-Physiological Sensing Eyewear In The Wild, Sailin Zhong, Patrick Chwalek, Nathan Perry, David Ramsay, Clayton Miller, Denis Lalanne, S. Hamed Alavi, A. Joseph Paradiso

Research Collection College of Integrative Studies

Buildings increasingly incorporate sensing and actuation techniques to automate the regulation of temperature, lighting, ventilation, and more. This trend seeks to minimize human intervention, justified by the promise of enhancing energy optimization. However, it has been widely acknowledged that loss of control over environmental conditions can lead to a diminished perception of comfort and compromised long-term user awareness and satisfaction. How can we envision building systems that can interact with building inhabitants and engage them at the “right” time and place? In this work, we address this challenge through three key contributions: 1) AirSpecs, a novel smart glasses-based system that …

Design And Implementation Of A Notification System For The Purpose Of Improving Communication Between Nurses And Patients, Aindrila Bhattacharya

2025 Spring Honors Capstone Projects - Archive

Communication is an important part of how nurses administer treatment to their patients. Without proper communication, it is difficult for the nurses to connect with their patients and vice versa. This paper will be going into some previous literature about communication between patients and nurses in general, communication with respect to pediatric patients and how notification systems have been implemented in the past. It will then discuss the methodology and implementation of a notification system for a medical app. The medical app is meant to facilitate communication from the side of the patient to the nurse, while the notification system …

Controlling A Mobile Inverted Pendulum And Optimizing Leaning Angle To Apply Force Using Reinforcement Learning, Aryan Mediratta

2025 Spring Honors Capstone Projects - Archive

Reinforcement Learning is a Machine Learning paradigm that involves simulating learning through rewards and penalties in intelligent systems. This technique is often employed in robotics when traditional control methods are insufficient or when human intuition does not provide a good solution on how to control robot systems, This project involves training a Segway-style Mobile Inverted Pendulum (MIP) robot to balance and push a box forward. The BeagleBone Blue board is used that includes a built-in Inertial Measurement Unit (IMU) and encoder ports. These sensors enable the system to measure its current state. The goal is to find the optimal leaning …

Integration Of Notes Section With Access Management, Inshaad Merchant

2025 Spring Honors Capstone Projects - Archive

This research explores the development of a notes section with access management, specifically designed to assist Computer Science and Engineering students to revisit and revise all the notes and key points highlighted in their tutoring sessions. While the senior design project focuses on the CSE Student Success Center application that allows students to schedule tutoring sessions, manage appointments, and manage their profiles within this application, the Honors capstone project adds on a specific section for students to save all their notes and important video links and attachments to continue their learning outside of the tutoring sessions. A centralized platform for …

Tutortech: A Web App For A Smarter And More Efficient Tutoring System, Smarika Pathak

2025 Spring Honors Capstone Projects - Archive

The Computer Science and Engineering (CSE) department faces challenges with managing its tutoring services, especially tracking attendance, booking sessions, and overall management of the tutoring system - all of which severely limits the ability for tutors to connect and engage with students. To help overcome these issues, TutorTech, a web-based application that provides improved management of the tutoring system and supports more engaging learning experiences between students and tutors was designed. Through this project, the aim was to optimize the TutorTech search capabilities - assisting students to find tutors based on skills, while also considering the effect of user interface …

Beyond The Hard Hat: Examining Barriers Of Women In Construction, Allison Pham

2025 Spring Honors Capstone Projects - Archive

The construction industry is falling behind in female representation, with women only making up 11.2% of the industry. The existing labor shortage is further exacerbated by the limited interest among women to pursue a career in construction. The purpose of this research is to investigate the factors that contribute to the lack of women in the construction industry and explore how HR strategies can attract and retain women in construction careers. Environmental, Social, and Governance (ESG) reports from three different industries were used to analyze the percentage of men and women employees. Multivariate regression analyses were conducted to examine whether …

Development Of A Cost-Effective Daq For Measuring Brake Performance In Race Cars, Adrin Alias

2025 Spring Honors Capstone Projects - Archive

This project explores the feasibility of creating a cost-effective data acquisition (DAQ) system for high-speed, real-time brake performance testing of Formula SAE racecars. The research addresses the limitations of the current MoTeC DAQ system currently employed by the team, which is costly and time-consuming to set up for on-car testing. The team will use a brake dynamometer for steady-state comparisons of different brake pad compounds (senior design project), but evaluating real-world performance requires on-car testing. By systematically comparing various hardware platforms, sensors, communication protocols, and storage solutions, this project aims to balance cost-efficiency with reliability and performance. The research evaluates …

Computational Modeling Of Torque Arm And Load Cell Interactions In Uta Racing Brake Dynamometer, Anthony A. Aiyedun

2025 Spring Honors Capstone Projects - Archive

The UTA Racing Team is developing a brake dynamometer to measure the coefficients of friction of various brake pads and calipers under controlled conditions. The dynamometer simulates on-track braking scenarios, testing brake pads at temperatures up to 1300ºF and pressures similar to racing environments. Its primary goal is to generate accurate friction vs. temperature graphs for various brake pad and rotor combinations, addressing the need for dedicated testing equipment. This project creates an ANSYS simulation of the torque arm and load cell interaction. The computational model accurately represents the relationship between applied torque and measured load cell force, incorporating precise …

A Data Driven Approach To Student Success: Visualizing Engagement And Performance Metrics, Araohat Kokate

2025 Spring Honors Capstone Projects - Archive

Many tutoring centers lack tools to analyze and visualize key performance metrics, limiting data driven decision making. This study develops a data visualization feature for the CSE Student Success Center App at the University of Texas at Arlington, enabling administrators to track student engagement, tutor performance and session trends. Using the data of students and tutors, the feature provides interactive dashboards for real-time insights. Administrators can monitor attendance patterns, tutor workloads and booking trends, optimizing resource allocation. Findings indicate that real-time data visualization enhances decision-making, reducing manual effort while improving operational efficiency. This can further help improve student support services. …

Multimodal Emotion Recognition For Human-Robot Interaction Across Neuro-Diverse Populations., Ruchik Mishra

Electronic Theses and Dissertations

This dissertation explores the integration of multimodal data streams and artificial intelligence pipelines to understand human affect in neurotypical and children with Autism Spectrum Disorder (ASD). This dissertation captures human affect in the context of human-robot interaction. For this, multiple studies have been presented with both children with ASD and neurotypical adults. This dissertation makes four contributions: 1) The first study introduces autonomy during perspective-taking teaching sessions by making verbal content generation through large language models (LLMs). This system is the first of its kind for teaching perspective-taking in a semi-autonomous manner under the supervision of domain experts. Furthermore, this …

Synthetic Dataset Generator To Assist In Training Of Multilayer Perceptron Based Neural Network, Megan Leach

Electrical Engineering and Computer Science Undergraduate Honors Theses

Synthetic dataset generation attempts to solve the issue of needing large datasets to train models and observe behaviors in both a cost and time effective way. This project aims to highlight the value of synthetic data creation and how it was useful when training a neural network model by creating a synthetic dataset generator for a specific model in order to evaluate its behavior in difference scenarios. The model that was used in this project was created to select high-quality papers while maximizing the diversity of authors based on race, gender, and country characteristics, essentially mimicking a review process. The …

Investigation And Characterization Of Silicon Carbide Power Mosfets, Vincent Hassman

Electrical Engineering and Computer Science Undergraduate Honors Theses

As engineers constantly seek to make solar power systems smaller, cheaper, and more efficient, technological enhancements in the electronics that run them are required. One of the most fundamental electronic components of any solar system is the inverter, which takes DC current from the solar cell and turns it into AC current that is supported by the grid. This is done with metal oxide semiconductor field effect transistors (MOSFETs). Through more advanced MOSFET technology, inverters can switch at a higher frequency, increasing efficiency and reducing size and cost.

MOSFET performance can be enhanced by swapping the traditional silicon substrate with …

Improvement Of Hanford Waste Vitrification Algorithms With Machine Learning, Uncertainty Quantification, And Gradient-Based Optimization, Lagrande L. Gunnell

Theses and Dissertations

Over 200 million liters of nuclear waste is stored in tank farms in Hanford, Washington, USA. An ongoing effort to immobilize non-solid nuclear waste is through waste vitrification, where waste is mixed and melted with glass-forming chemicals (GFCs) to form a waste glass. Algorithms to determine the ideal mixing recipes are formalized as constrained optimization problems to maximize waste loading in the glass product, with constraints on several properties of the glass melt and final product. These properties are on the glass melt, such as viscosity, electrical conductivity, and corrosion rates, as well as the final glass product, such as …

Stop Design: Rethinking The Approach To Public Transit's Architecture, Elizabeth M. Nielsen

Architecture Masters of Science Program: Theses

Public spaces are the foundation of our social health and wellbeing, but are often designed without considering the needs of the public, creating spaces that people do not feel encouraged to use. Just as public space design as a whole often falls short of serving the public, the same can be said for a subset of public space design, public transit stops. While they are public spaces created for the purpose of waiting, their design rarely reflects this.

Well-designed public transit stops are capable of both maintaining existing ridership and drawing in new riders. Most commonly, this design occurs at …

Computation-Driven Design And Synthesis Of Molecular Sensors For Surface-Enhanced Raman Spectroscopy In Liquids, Junhu Zhou

Dartmouth College Ph.D Dissertations

The reliable detection of molecules in liquid environments is a continuing challenge in chemical sensing and biological diagnostics. While surface-enhanced Raman spectroscopy (SERS) is well-recognized for its high sensitivity and molecular specificity, conventional platforms – based on colloidal nanoparticles or patterned substrates – have shortcomings. These conventional configurations struggle with signal reproducibility, non-uniform hotspot distribution, and, critically, restricted accessibility for large targets such as proteins and exosomes.

This thesis develops a computation-guided approach to developing next-generation SERS sensors capable of overcoming these persistent obstacles. At the heart of the study is the design and fabrication of metal-insulator-metal (MIM) nanoparticles, where …

Propasafe: A Bert-Based Offline Tool For Propaganda Detection, Vivek Sharma, Mohammad Mahdi Shokri, Shweta Jain, Sarah Ita Levitan, Elena Filatova

Publications and Research

In an era marked by the rapid consumption of digital news, the proliferation of propaganda poses significant threats to democratic values and informed decision-making. We propose a novel framework that prioritizes user privacy while assisting in the automatic detection of propaganda in news articles, allowing users to sift through the rhetoric to read the relevant objective news. As a demonstration of this framework, we present Propasafe, a BERT-based browser extension designed to alert users to propagandist tones in news articles. By highlighting instances of propaganda-like language in real-time, Propasafe empowers users to critically engage with news content, promoting objective understanding …

Toward The Application Of Natural Language Processing In Electronic Health Record Analysis For Taxonomy Development, Latoya Mcdonald

All Dissertations

Electronic health records (EHRs) are pivotal resources for nurse practice because they increase the timeliness and reliability of patient information at the point of care and support access by multiple healthcare providers and the individual patients themselves. However, it is widely recognized that data extraction from EHRs is challenging due to the variability in the language used in clinical care notes and the lack of standardized terminology across healthcare systems. The broad objective of this dissertation is to develop taxonomy-based classification models for nursing care by applying feature engineering approaches to EHRs that include nursing care of ostomy patients following …