Digital Commons Network^™

Implementation Of Unscented Kalman Filter-Based State Estimation For Multiple Spacecraft Using Global Positioning System Measurements, Bala Prenith Reddy Gopu

Theses and Dissertations

This study presents an implementation of state estimation for a drag-based rendezvous mission involving multiple chaser spacecraft and a single target, using Unscented Kalman Filtering (UKF) with Global Positioning System (GPS) measurements. The implemented method combines GPS navigation solutions with UKF to provide real- time state estimates of all spacecraft involved. Nonlinear least squares method is employed to process pseudorange and pseudorange rate measurements to determine receiver states, UKF utilizes these states as measurements to estimate absolute space- craft positions and velocities. This implementation also addresses practical challenges including raw GPS measurement processing, and varying GPS satellite geometries.

Improving Home Security Through User Centered Device Positioning, Lalith Nadipalli

Theses and Dissertations

In today’s world, where technology is advancing rapidly and security threats are becoming more complex, the need for effective home safety measures is more critical than ever. Homeowners are increasingly turning to a variety of smart devices, such as smoke detectors, carbon monoxide detectors, and security cameras, to protect their living spaces against potential dangers like burglary, fire, and environmental hazards. These devices offer essential protection, acting as both early warning systems and visual surveillance tools. However, their effectiveness largely hinges on how well they are placed within the home. Proper placement of these safety devices ensures that they provide …

C-Band Air To Ground Communication System For Uav, Mubark Alghamdi

Theses and Dissertations

C band spectrum 5030-5091 MHz is allocated for command-and-control communication services with unmanned aircraft systems. This document evaluates the possibility of using 3GPP 5G standards for provisioning of such services. Channelization of the spectrum and major system parameters are proposed. The performance of the proposed system in channel fading environment is evaluated using MATLAB based simulations. The evaluations examine SINR, and average throughput of the proposed system at different altitudes of the unmanned aircraft system. MATLAB simulations are used to evaluate system performance in free-space environments. Signal-to-Interference-plus-Noise Ratio (SINR) and Reference Signal Received Power (RSRP) are predicted at different UAS …

Characterizing Human Mobility Patterns In Saudi Arabia Using Cellular Data, Meshal Alnefaie

Theses and Dissertations

The study analyzes human mobility in Saudi Arabia. Using crowd-source data, Riyadh mobility is analyzed to find trends and highlight mobility patterns of individuals in Riyadh. Then, the mobility of Riyadh is compared with that of Jeddah and Dammam in a similar data collection and analysis. Four mobility metrics are utilized: Number of Visited Locations (NLOC), Number of Unique Locations (NULOC), Radius of Gyration (RGYR), and Distance Traveled (DTRV). The results show interesting outcomes about individuals in the three cities. Although these cities are far from each other, they observe the same mobility patterns. These findings have the potential to …

Developing End-To-End Imitation Learning For Asteroid Proximity Operations, Patrick David Quinn

Theses and Dissertations

Asteroid exploration remains a popular topic in the scientific community, however hurdles still exist for controlling spacecraft within the asteroid environment. Communication delays often require the usage of limited onboard computing hardware for navigation. Additionally, long mission timelines must be accommodated with highly efficient fuel use. Considering these issues, it is apparent that any guidance, navigation, and control (GNC) system in these spacecraft should emphasize both computational and fuel efficiency in its design. Furthermore, the integration of a robust state estimation system is necessary for the successful deployment of such systems. The development of a controller aiming to address these …

Towards Visual Inertial Navigation With Fixed Tetrahedral Targets, Joao Leonardo Silva Cotta

Theses and Dissertations

This dissertation presents a robust method for 6DoF position estimation under impaired visual conditions utilizing a minimum 4-point Perspective-n-Point (P4P) solver designed for tetrahedral targets. Using SO(3) × R 3 instead of SE(3), the method uses a Lie group-based formulation to discriminate between rotation and translation, thereby enabling computationally efficient, resource-conscious op- optimization while preserving correct geometric behavior. Designed using the contemporary C++17 library ShomerTarget, the solver is analytically formulated and assessed under pragmatic robotic conditions. Particularly in low-light and high-dynamic environments, experiments on embedded systems, UAVs, and NASA’s Astrobee show that the proposed solver attains enhanced accuracy compared to …

Advancing Precision And Autonomy In Agriculture And Medical Imaging Through Ai And Computer Visions, Tan-Hanh Pham

Theses and Dissertations

Deep learning has revolutionized numerous fields by enhancing precision, automation, and decision-making capabilities. This dissertation explores its applications in agriculture and medical image processing, introducing novel methodologies to improve accuracy and efficiency in these domains. These fields hold critical societal importance -- agriculture underpins global food security and sustainability, while medical imaging drives advancements in diagnostics and personalized healthcare, both benefiting significantly from data-driven innovations. In agriculture, deep learning is applied to precision spray systems through droplet analysis. Specifically, a generative model is designed to create synthetic droplet images, addressing the challenge of limited training samples, which are expensive …

Cross-Dataset Fairness Evaluation Of Transformer-Based Sentiment Models, Sara Zuiran

Theses and Dissertations

With the growing exploration of Natural Language Processing (NLP) systems in decision-making environments, it is essential to evaluate technical and ethical aspects of the dataset and the NLP model to improve fairness. To assess fairness, the thesis examines demographic imbalances in sentiment classification models by evaluating transformer-based models fine-tuned on the Stanford Sentiment Treebank version 2 dataset (SST-2) against the demographically annotated Comprehensive Assessment of Language Model dataset (CALM). This work identifies performance disparities in sentiment prediction across demographic groups by examining sensitive attributes such as gender and race. The study evaluates both the RoBERTa and MentalBERT transformer models using …

Early Breast Cancer Detection With Ultrasound Data Using Nmf, Rutvi Khamar

Theses and Dissertations

Early detection of breast cancer significantly influences patient outcomes. Dynamic Contrast-Enhanced Ultrasound (DCE-US) has shown promise in early detection by visualizing tumor vascularity and perfusion dynamics in real-time. This study evaluates the efficacy of DCE-US in distinguishing four stages of cancer progression: normal, hyperplasia, ductal carcinoma in situ (DCIS), and invasive cancer, using a transgenic mouse model that mimics human breast cancer. Ultrasound burst pulses, while commonly used to remove unbound contrast agents, can potentially damage human tissues. Using the pre-pulse data helps mitigate this risk, ensuring safer and more reliable measurements. A VEGFR2-targeted microbubble contrast agent was injected, and …

Effects Of Reflective Journaling And Nudges On Academic Motivation And Engagement, Lakshmi Satya Sai Veda Mahita Uppuluri

Theses and Dissertations

This study investigates the effects of reflective journaling and motivational nudges on academic motivation and engagement among college students. Grounded in Self- Determination Theory (SDT), the research examines how different interventions influence intrinsic motivation, and academic behaviors such as class attendance, participation, and preparation. The study employed a between-group experimental design with three conditions: a control group, a journaling group, and a journaling group that also received daily motivational nudges. Results showed that students in the journaling groups—particularly those who received nudges—experienced a significant increase in academic motivation. While changes in academic engagement were not significant, the effect size suggested …

Stochastic Analysis With Operational Calculus In Reliability, Hend Hamdan Al-Jahani

Theses and Dissertations

Our dissertation models several reliability systems subject to occasional random shocks of random magnitudes W1,W2,..occurring at times tau0, tau2,..In Model 1, the underlying system becomes inoperational if it wears out due to aging specified by a monotone increasing continuous function Delta identifying system's wear at any time t>=0 . The system is deemed inoperational if delta crosses a sustainability threshold at some moment T=(delta )^-1(D). The precise time T is difficult to identify making the realistic failure time randomly delayed and thus identified at some opportune observation epoch. The system can also fail due to damages by external shocks, …

The Prototype Of A Fully Automated Pressuremeter For Various Geotechnical Applications, Anuar Akchurin

Theses and Dissertations

The geotechnical engineering field requires high-quality in-situ testing equipment that ensures consistency in the test execution. This research focuses on developing and testing a prototype of a fully automated pressuremeter control unit to allow the industry to obtain reliable and controlled stress-strain data, thereby improving efficiency and reducing testing time.

The objectives of this work are to design and develop a system with the necessary components to perform the pressuremeter test, integrate the testing procedure into the state machine design, enable automated testing, and validate the results by comparing the stress-strain data with that obtained from the existing hand-operated pressuremeter …

Alternative Robust Design Formulation And Exploration Strategies For Managing Uncertainties In The Realization Of Complex Engineering Systems, Pooja Mukundan

Theses and Dissertations

The design of complex engineered systems often relies on simulation-based models, which inherently introduce uncertainties. Managing these uncertainties is critical to ensure robust system performance. From a decision-based design (DBD) perspective, robust design metrics such as the Design Capability Index (DCI) and Error Margin Index (EMI) are employed to formulate and solve problems under uncertainty. However, existing formulations of these metrics rely on first-order Taylor series approximations for variance estimation, which are often inadequate in the presence of highly nonlinear or multimodal performance functions.

This thesis proposes alternate formulations of DCI and EMI, which use the multiple-point method of variance …

Trends In And Factors Associated With Science Achievement Among Fourth Graders In Saudi Arabia: A Secondary Analysis Of Timss Data, Reda Massawe

Theses and Dissertations

This secondary analysis examined trends and factors associated with science achievement among fourth-grade students in Saudi Arabia using data from the Trends in International Mathematics and Science Study (TIMSS). Between 2007 and 2019, Saudi students consistently scored below the international average in science, with female students outperforming males by more than 30 points. The study addressed two issues: (1) reasons behind Saudi students’ underperformance and (2) limited research on contributing factors. TIMSS data from 2011, 2015, and 2019 were analyzed using descriptive, correlational, and regression methods. While trends across the years were explored, only 2019 data were used for detailed …

Trends In And Factors Associated With Science Achievement Among Eighth Graders In Saudi Arabia: A Secondary Analysis Of Timss Data, Roba Alzahrani

Theses and Dissertations

This secondary analysis examined trends in and factors influencing science achievement among eighth-grade students in Saudi Arabia, using data from the Trends in International Mathematics and Science Study (TIMSS). However, Saudi Arabia's performance on the TIMSS science assessments fell below the international average, from 2003 through 2019. In addition, gender differences in science achievement have been observed, with female students outperforming male students by 30 or more points. This study addresses two problems: factors associated with the lower performance of Saudi students on TIMSS science assessments compared to global standards, and the small number of studies which explored factors which …

An Analysis Of Face Morphing Presentation Attacks Against Facial Recognition Systems, Joshua Breininger

Theses and Dissertations

Security has been a problem for human society for as long as history has been recorded. The identification of people is an ongoing, ancient battle, with a variety of methods that only become more complex with time. The Romans performed censuses, ciphers have been used for thousands of years in the pursuit of security, and in modern day we own identifications and governments keep track of who lives in their country with citizenship and licenses. The question of ”Who are you?” is vital for society to function, which opens up a massive field of potential for how to ask that …

Co-Designing Manufacturing Systems For Robustness And Resilience: A Decision-Based Design Perspective, Mathew Baby

Theses and Dissertations

Manufacturing systems (MSs) comprise various stakeholders associated with the manufacture and supply of products required by customers and are interrelated by the flow of materials and information. The interrelated stakeholders make system-specific decisions and stakeholder-specific decisions across multiple levels of a decision hierarchy to satisfy many conflicting system-specific and stakeholder-specific requirements that define system and stakeholder performances. Given the stakeholder interrelations and conflicting nature of system-specific and stakeholder-specific requirements, system and stakeholder performances are correlated and conflicting.

In the Industry 5.0 era, there is an increased emphasis on the creation and equitable distribution of value among all the stakeholders in …

Autonomous Defect Detection In Additive Manufacturing, John Samuel Poindexter Iv

Theses and Dissertations

Additive manufacturing (AM) is the process of creating a product by applying layers of material to build up to the final product. AM has revolutionized the field of manufacturing and has allowed more complex products to be manufactured at reasonable cost, quicker manufacturing time, and optimized material usage. Traditional forms of manufacturing were based on subtractive manufacturing, where by a product would be created by removing material from its source. AM is a new manufacturing process and faces significant challenges when it comes to manufacturing due to defects. Defects can vary from type and severity and can overall weaken or …

Blink-Related Brainwaves As Digital Biomarkers For Cognition Assessment During Complex Tasks, Lexine Carmlixa Sibert-Jolissaint

Theses and Dissertations

Blink-related oscillations (BROs) are neurophysiological responses observed in electroencephalography (EEG) following spontaneous blinking, reflecting the brain processing of new visual information. Prior research has demonstrated BRO responses across various cognitive states, such as resting, cognitive loading, and sensory stimulation, highlighting their potential as a non-invasive biomarker of brain function. We conducted the first investigation of BRO responses during a verbal fluency (VF) task, which is a complex, dynamic task state combining memory, visual perception, executive function, and language processing. Using publicly available EEG data from 22 healthy adults, we measured BRO responses over the left anterior frontal region corresponding to …

Expressive And Interpretable User Engagement Prediction Using Multivariate Survival Processes, Akshay Aravamudan

Theses and Dissertations

The ability to characterize how information diffuses online is of paramount importance to stakeholders that are interested in tasks such as proposing solutions for mitigating and countering dis/misinformation, predicting user engagement of content in social media, planning marketing campaigns to roll-out products and planning dissemination of political campaign messaging among others. One such facet of learning the dynamics of information diffusion is the ability to predict user engagement or the popularity of a single piece of information as it spreads through an online medium. Existing works in this regard mainly either obfuscate user level information or utilize frameworks that are …

Personality Trait Recognition Through Deep Neural Temporal Modeling Of Non-Verbal Behavior, Kushal Vangara

Theses and Dissertations

Personality research seeks to explain the wide range of human behaviors through stable, measurable traits. Human interactions are inherently rich and multidimensional, and analyzing behavioral data offers a promising path to uncover personality insights. The increasing convergence of psychology, computer science, and machine learning has fueled interest in computational approaches to personality assessment. Advances in sensing technologies have made it possible to capture fine-grained information about individuals’ behaviors and interactions in naturalistic and controlled environments. Automated audio-visual analysis techniques extract relevant behavioral cues, which machine learning models then interpret to infer underlying personality traits. This work provides a comprehensive overview …

Estimation Of Breach Hydrograph Resulting From Dam Embankment Failure Due To Internal Erosion Or Overtopping: Comparison Of Simplified Methods With Real-Case Failure Data And Recommendations, Laurent Del Gatto, Jean-Robert Courivaud

5th International Seminar on Dam Protections Against Overtopping

The opening of a breach in an embankment dam, whether due to overtopping or internal erosion, is a critical failure mode for these structures. Estimating the resulting breach hydrograph is essential for assessing downstream risks. While no universal physical model covers all dam types, empirical formulas are commonly used. EDF analyzed 14 such formulas, comparing them with rupture data from 32 embankment dam failures. The best formulas - Froehlich 1995, Xu & Zhang 2009, and CLF 2020 - yield a “best estimate” for peak flow. However, due to variability, results should be interpreted cautiously. Consider estimating breach characteristics like width …

Sabrina Vs Steph: The Battle Between The Wnba And Nba, Naysha Mcgriff

Symposium of Student Scholars

The average salary of a Women’s National Basketball Association (WNBA) player is 110 times less than a National Basketball Association (NBA) player’s. Despite growing WNBA viewership, gender inequality in sports remains high, with critics claiming female athletes are less skilled. Gender bias in sports is severely understudied, making direct comparisons to men’s leagues unfair due to long-term lack of investment in women’s sports. This study investigates whether the perceived disparity in skill levels between WNBA and NBA players' is genuine or influenced more by external factors by developing an unbiased measure of player efficiency to compare athletic performance. This dataset …

Zeros Of L-Functions And Arithmetic, Micah Milinovich

Showcase of Research and Scholarly Activity

The PI currently holds two awards: NSF DMS 2401461 (Zeros of L-functions and Arithmetic) and NSF DMS 2101912 (The Distribution of the Zeros of L-functions and Related Questions). These awards concern research in number theory, a very active area of mathematics. L-functions have played a pivotal role in the modern development of number theory and they can be used to study a wide variety of problems. The tools used to study L-functions draw from many branches of mathematics including analysis, algebra, algebraic geometry, representation theory, and mathematical physics while number theory has important applications outside of mathematics to fields such …

2025 Nsf Career: Portable Wind Tunnel, Wen Wu

Showcase of Research and Scholarly Activity

As part of his NSF CAREER grant, Dr. Wu will collaborate with the University of Mississippi Museum to host the Art of Fluid exhibition. The exhibit will showcase artistic visualizations of fluid dynamics research and include live wind tunnel demonstrations. Dr. Wu will also launch a Mobile Fluid Exposition Program to engage high school students throughout north Mississippi, aiming to inspire interest in STEM through hands-on activities. The Center for Mathematics and Science Education (CMSE) will support this outreach effort.

Structure Disorder And Magnetic Behavior Of An Olivine-Type Cathode Material, Hamida Hassan, Madalynn Marshall

Symposium of Student Scholars

Our research investigates the structure disorder and magnetic behavior of Li(Mn,Fe)PO₄, an olivine-type material relevant for lithium-ion battery applications. Using single-crystal neutron diffraction at Oak Ridge National Laboratory, we precisely determined Mn and Fe occupancy, revealing a 56% Fe and 44% Mn distribution at the atomic 4c site within the Pnma space group. Additionally, we observed significant lithium site vacancies (78% occupied), influencing the material's electrochemical and magnetic properties. The varying Mn/Fe ratio affected spin reorientation transitions, shifting from antiferromagnetic alignment along the a-axis to the b-axis. Our findings provide crucial insights for optimizing olivine-based cathodes, enhancing energy …

Campus Navigator: A Mobile App For Seamless University Navigation, Hafsa Mohammed, Ali Rahimzadehfard, Rachab Wilson, Mathias Rossi, Turaj Ashuri, Amir Ali Amiri Moghadam

Symposium of Student Scholars

Navigation services play a big role in everyone’s daily lives, from directing them on new roads to guiding them through buildings. Outdoor navigation services have evolved from physical maps to digital ones like Google Maps for ease of use and accessibility. Upon conducting literature research, the team found that many navigation apps lack clear and accurate instructions for how to navigate university campuses such as Marietta campus. Due to the size of KSU’s Marietta campus and its buildings, effortless navigation has been a common challenge for students, faculty, and visitors alike. Additionally, all buildings are referred to by letters, numbers, …

Computational Study Of The Proton Transfer In The H7o3+ Cluster, Anna James, Martina Kaledin

Symposium of Student Scholars

Proton transfer (PT) from one molecule to another is among the most studied phenomena in chemistry. PT requires the bond cleavage and the formation of a new one, AH⁺ + B -> A+ BH⁺. In protonated water clusters, such a process consists of the interconversion of hydrogen bonds. Experimentally, such a process can be observed as a significant increase of a dipole moment. However, other vibrational transitions often occur with small changes in the dipole moment while large changes in polarizability. In this work, we study the PT process in a protonated water cluster, H₇O …

Overcoming Motor Imagery Bci Illiteracy: Adaptive Decoding And Knowledge Transfer In Eeg-Based Brain-Computer Interfaces, Zaid Shuqfa Shuqfa

Thesis/ Dissertation Defenses

Brain Computer Interface (BCI), Also known as brain-machine interface (BMI) is a mean of controlling machines without the need to activate peripheral nerves or muscles. It has received the attention of research for decades. Motor imagery-based BCI is a paradigm that is characterized by its user friendliness where users can generate control commands at their freewill, without waiting for a que from the BCI module. Motor imagery brain–computer interface (MI–BCI) has considerable potential in increasing the quality of the lives for people with mobility impairment and the healthy ones as well. Though, its diffusion in application still has many pitfalls …

Deep Learning Algorithms For Traffic Flow Predictions, Adegoke Ojeniyi, Prince Pal Singh, Ankita Vashisht, Swati Kumari, Karan Karan

AUIQ Technical Engineering Science

Given the growing complexity of urban transportation systems, precise traffic flow forecasting is essential for reducing not only issues of congestion but also, for boosting road safety and enhancing mobility management. This study integrates Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), Long Short-Term Memory (LSTM), and Recurrent Neural Networks (RNN) to present a hybrid deep learning framework for traffic prediction. Of these, the CNN-LSTM model is a reliable option for real-time traffic forecasting since it successfully captures both spatial and temporal dependencies, resulting in superior predictive performance. The dataset used to assess the framework includes 48,120 records from a traffic monitoring …