Engineering Commons^™

Using Facial Recognition For Selective Pose Detection, William J. Parker

Master's Theses

Pose detection involves locating and identifying key body points for all individuals within a frame. This enables the ability to convert the pose into a digital format, which can then be recorded and analyzed for a variety of purposes. Advancements in the field have already opened applications in areas such as digital fitness coaches, fall detection, and virtual reality. Existing approaches primarily focus on tracking all detected individuals, which limits the practical applications when attempting to analyze a single or specific subject when there are other people in frame. Previous work has discussed integrating identification, but these approaches use identification …

Quantum Algorithm Emulation Using Fpgas, Samuel Petruescu

Master's Theses

Field Programmable Gate Arrays (FPGAs) have been used in most of the physics sub-fields for various unique purposes. This includes particle physics, quantum optics, and, more recently, quantum computing. FPGAs boast many benefits over previous experimental and computational setups. They are versatile, easy to program, and cost-effective, leading to an understandable desire to incorporate them into the new field of quantum computing. While FPGAs have been used to help control the readout and control of physical qubits, they can also be a good tool for improving algorithm simulations, which is the focus of this paper. Different algorithms have different computational …

Sirilla: Predicting Traffic Flow Via Stacked Decentralized Federated Learning, Andrew Selvia

Master's Theses

Billions of people today rely on traffic predictions to optimize their travels. Digital mapping services deliver accurate predictions by learning from vast troves of historical data. Impressive as these systems are, their assumptions do not always apply. They depend on an endless flow of sensitive user data to a central authority, a stable Internet connection, and trustworthiness on both sides of the traditional client-server model. This thesis explores a novel architecture which bucks those assumptions. In the proposed model, traffic data remains on edge devices which individually train models via federated learning. Beyond the obvious privacy benefits, this architecture enables …

Structural Differential Privacy In Graph Neural Networks, Bibek Giri

Master’s Dissertations

Graph Neural Networks (GNNs) have demonstrated impressive performance across a range of graph-based learning tasks. However, their application to domains with sensitive relational data raises serious privacy concerns, as the graph structure itself may leak confidential information. This thesis investigates a decentralized framework for enforcing edge-level local di!erential privacy (LDP) in graph-structured data. We introduce two mechanisms that perturb a node’s neighborhood in a privacy-preserving yet utility-aware manner. The first approach replaces randomly selected neighbors with feature-similar nodes from the 2-hop neighborhood, ensuring structural realism while preserving degree. The second approach eliminates the need for explicit 2-hop propagation and dummy …

Shock Induced Droplet Aerobreakup For Newtonian And Non-Newtonian Fluids, James Leung

LSU Doctoral Dissertations

This research investigates shock-induced aerodynamic breakup (aerobreakup) of fluids with different stress-strain behaviors. The central hypothesis is that shear stress from highspeed gas flow manifests differently depending on a fluid’s strain response, influencing droplet breakup morphology, fragment size distribution, and drag-induced acceleration. To test this, experiments and simulations were performed on μm–mm sized droplets of Newtonian (water) and shear-thinning fluids (nanofluids or xanthan gum). Two experimental setups were used: an open-ended shock tube and a closed conventional shock tube. In the openended setup, a normal shock impacts a stationary droplet held by an acoustic levitator. Droplet breakup and gas dynamics …

Dynamic Sparsification In Secure Gradient Aggregation For Federated Learning, Bikash Samanta

Master’s Dissertations

Secure aggregation is a critical component of privacy-preserving federated learning. However, existing fixed-sparsity approaches often incur unnecessary communication overhead. We present DynamicSecAgg, a novel framework that introduces dynamic sparsity while preserving coordinate-level privacy. Our method achieves significant improvements in communication efficiency while maintaining — and in some cases improving — model accuracy across both IID and non-IID user distributions. The framework maintains information-theoretic privacy guarantees via adaptive gradient thresholding and polynomial-based aggregation, proving particularly effective under heterogeneous data settings. These results establish dynamic sparsity as a key optimization for efficient and privacy-preserving federated learning.

Cloud-Assisted Multi-Channel Data Broadcasting, Debabrata Maji

Master’s Dissertations

The convergence of Internet of Things (IoT) and cloud computing has transformed technology, impacting commerce, industrial production, data management, etc. Multi- Channel Broadcast Encryption (MCBE), first introduced by Phan et al. (ASIACCS 2013), is a cryptographic encryption primitive used for both IoT and Cloud that permits a sender to e!ciently and securely encrypt several messages for di”erent groups of receivers. After thoroughly exploring the existing literature, we observe that none achieves the robust provable security within the standard model. This paper addresses this gap, aiming to achieve adaptive INDistinguishable under full-IDentity Chosen-Ciphertext Attack (IND-ID-CCA) security by constructing an e!cient identity-based …

From Devices To The Cloud: Digital Forensics In The Changing Social Media Landscape, Joseph Brown

LSU Master's Theses

This thesis presents a comprehensive digital forensic analysis of emerging and alternative social media platforms, including Truth Social, Threads, Bluesky, Nextdoor, and Neighbors. These platforms, which range from politically aligned alt-tech networks to hyperlocal neighborhood apps, present unique forensic challenges and security vulnerabilities. Across all case studies, established forensic techniques were applied using a hybrid methodology combining mobile device analysis, network traffic monitoring, and API interrogation. Findings include the discovery of plaintext credentials, session tokens, and other sensitive artifacts, particularly in platforms with weaker security postures such as Truth Social, Bluesky, Nextdoor, and Neighbors. Threads, by contrast, demonstrated greater resilience …

Multi-Party Key Establishment For Resource-Constrained Devices, Supriyo Banerjee

Master’s Dissertations

As the number of IoT (Internet of Things) devices continues to grow, ensuring secure communication among them has become increasingly important. Traditional pairing schemes rely on centralized architectures, which are vulnerable to temporary or permanent failures due to operational malfunctions of their central hubs or gateways. To address these challenges, decentralized communication is essential. However, existing decentralized pairing schemes suffer from high pairing times and significant computational overhead. Given the diverse capabilities of IoT devices, ranging from high-performance edge devices to resource-constrained sensors, many of these schemes become impractical in real-world scenarios. Therefore, we require a lightweight pairing scheme. Our …

Turning Data Into Guardrails-Decoding Financial Vulnerability Through Behavioural Signs, Debanwita Hajra

Master’s Dissertations

This report presents the work I did during my internship at Hongkong and Shanghai Banking Corporation (HSBC), Kolkata. As a financial institution, the strength of the bank is fundamentally rooted in the behavior and reliability of its customers. Understanding this behavior is not only desirable; it is essential for the security, risk mitigation and future strategic planning of the bank. To do this, banks must invest in a thorough analysis of the financial behavior of their customers to detect early signs of risk and act accordingly. I worked in the Finance Support Team within the Data and Analytics division, where …

Peak Connection Strength Of Reduced Beam Section Moment Frame Connections, Jonathan T. Tshibanda

Theses and Dissertations

In the design of reduced beam section (RBS) moment frame connections, the peak connection strength factor (𝐶𝑝𝑟) is used to estimate the expected maximum moment at the reduced section in the capacity-based design of moment-resisting frames. Current design provisions in AISC 358-22 define C𝑝𝑟 as the average of the yield and ultimate strengths of the beam material divided by the yield stress, resulting in a standard value of 1.15 for A992 steel. However, experimental studies have often reported higher values, occasionally exceeding 1.40. This study reevaluates the 𝐶𝑝𝑟 factor using experimental data from 35 existing RBS tests specimens along with …

Performance Analysis Of University Wifi Using 802.11e Information Elements, Douglas Christopher Hales

Theses and Dissertations

Wireless networks, including IEEE 802.11 (WiFi), continue to become more important for many uses, including university classrooms. Factors that impact the performance of these networks have changed greatly over time, with increased scale at which they are used, and growing dependence of latency sensitive applications. In order to better understand the performance of current WiFi networks, a methodology was created to capture and analyze beacon frames with optional 802.11e information elements (IE), using Quality of Service enhanced Basic Service Set or QBSS load (channel utilization) and station count. This methodology is able to collect channel use more frequently than many …

Incorporating Industry-Standard Technical Writing Into A Materials Testing Laboratory, Caleb Levi Head

Theses and Dissertations

The fluid analysis and materials testing laboratories are crucial for engineering students to learn experimental procedures and data interpretation. Engineers spend a significant portion of their workday on report writing, yet many feel their undergraduate education did not adequately prepare them for this task. At the University of Arkansas at Little Rock, students were given an industry-influenced lab report template to expand their knowledge of the necessary information required in technical writing, thereby teaching and improving their technical writing skills actively. These reports were evaluated qualitatively and quantitatively against previous submissions over two semesters in the mechanical engineering fluids and …

Algorithmic Optimization Of Filter Bank: Harnessing Rapid Convergence And Its Applications, Keerthana B Ms

Theses and Dissertations

A novel optimization framework is proposed for the design of both uniform and non-uniform filter banks, aimed at improving the accuracy and computational efficiency of biomedical signal classification tasks, with a particular emphasis on the detection of sleep disorders and Alzheimer’s disease.The proposed algorithm is grounded in multirate signal processing theory and aims to achieve Near Perfect Reconstruction (NPR) with minimal computational overhead. The process begins with the optimization of a uniform cosine-modulated filter bank (CMFB), achieved through iterative frequency-domain analysis and parameter tuning. This is followed by the derivation of a non-uniform filter bank via selective merging of bandpass …

Algorithmic Optimization Of Filter Bank: Harnessing Rapid Convergence And Its Applications, Keerthana B

Theses and Dissertations

A novel optimization framework is proposed for the design of both uniform and non-uniform filter banks, aimed at improving the accuracy and computational efficiency of biomedical signal classification tasks, with a particular emphasis on the detection of sleep disorders and Alzheimer’s disease. The proposed algorithm is grounded in multirate signal processing theory and aims to achieve Near Perfect Reconstruction (NPR) with minimal computational overhead. The process begins with the optimization of a uniform cosine-modulated filter bank (CMFB), achieved through iterative frequency-domain analysis and parameter tuning.

This is followed by the derivation of a non-uniform filter bank via selective merging of …

Magnetically Impelled Arc Butt Welding And Straight Tube Butt Welding Analysis Of Boiler Grade Tube Joints, Santhosh Kumar S

Theses and Dissertations

Boiler-graded tubes of T11, T12, T91, and T92 materials with a thickness of 4.5 mm thick and 44.5 mm outer diameter were selected for the Straight Tube Butt Welding process using Hot Wire (STBW-HW) and Cold Wire (STBW-CW) conditions. Moreover, the research investigates and compares the welding characteristics of dissimilar T11 and T91 boiler-graded tubes using STBW - HW & Magnetically Impelled Arc Butt (MIAB) welding techniques. Similar and dissimilar welding was performed in STBW – HW & CW conditions.

In dissimilar welding, the tensile strength was higher in the T11-T91 STBWHW joints of 663 MPa than in the T12-T92 …

Rethinking Green Building Development Through Policy And Operational Metrics: Insights From Baton Rouge And Beyond, Oluwafemi Awolesi

LSU Doctoral Dissertations

This dissertation explores the challenges and opportunities associated with the development, adoption, and performance of green buildings in regions with relatively low certification uptake, drawing insights from Baton Rouge and its parish system as a case study. It addresses three primary research questions: (1) How can the adoption rate of green buildings be enhanced? (2) How do certified buildings perform compared to their non-certified counterparts? (3) What operational metrics can be applied to better evaluate building performance in the future?

Using a mixed-methods approach, the study examines stakeholder perceptions in East Baton Rouge, Louisiana, investigates energy performance, indoor environmental quality, …

Integrated Evaluation Of Airtightness, Acoustics, Thermal Performance, And Life-Cycle Carbon Emissions In Code-Compliant Wood-Framed And Thin-Shell Concrete Dome Residential Structures, Eduardo Ibanez Vasquez

Theses and Dissertations

The residential construction industry faces increasing demands for energy-efficient and sustainable housing solutions. In the U.S., residential buildings significantly contribute to energy consumption and greenhouse gas (GHG) emissions, highlighting the need for enhanced building envelope performance. This study compares four residential structures: a traditional code-compliant wood-framed structure built in 1970, a traditional code-compliant wood-framed structure built in 2016, a modular code-compliant wood framed structure built in 2024, and a thin-shell concrete dome built in 2022. The analysis focuses on airtightness, acoustic insulation, passive thermal performance, and life-cycle carbon emissions, including both embodied (cradle-to-gate) and operational energy use. Field-based methods included …

Fundamental Exploration Of Soot Formation And Morphology From A Molecular Modeling Perspective, Khaled Mosharraf Mukut

Dissertations (1934 -)

Soot formation remains one of the least understood phenomena in combustion science, posing significant challenges due to its complex physicochemical nature and considerable environmental and health impacts. This dissertation presents a comprehensive molecular-level investigation into the fundamental mechanisms governing soot inception, particle growth, and morphological evolution through state-of-the-art reactive molecular dynamics (RMD) simulations of acetylene pyrolysis. A novel computational analysis utility, Molecular Arrangement and Fringe Identification and Analysis from Molecular Dynamics (MAFIA-MD), was developed to accurately characterize soot particle formation, providing detailed insights into chemical composition, internal structure, and surface characteristics. Critical physicochemical markers defining the boundary between gas-phase species …

Empirical Analysis Of Incentivized Energy Assessment Recommendations And Iiot Cost-Effectiveness In U.S. Smes, Fatemeh Ghafari

LSU Master's Theses

The industrial sector in the United States accounted for 33% of total energy consumption in 2022. Small and medium-sized enterprises (SMEs), which comprise 99.9% of U.S. businesses present a critical opportunity for energy efficiency improvements. Although energy audits provide actionable Assessment Recommendations (ARs) to reduce consumption, high implementation costs remain a key barrier to adoption.

While prior studies have explored rebate programs, most are limited to residential and commercial sectors or focus narrowly on specific technologies or geographic areas for the industrial sector. The objective of this study is to empirically investigate the “Incentivized Assessment Recommendation” (IAR) trends and to …

Communication Assistance Using A Large Language Model, Justin Y. Li

Electrical and Computer Engineering Senior Theses

The number of people diagnosed with Autism Spectrum Disorder is growing annually at a rapid pace. Autistic people are known to have multiple problems with communication, requiring assistance and coaching which is already limited in availability due to the amount of training required. At the same time, there has been a recent exponential rise in usage of LLMs like ChatGPT which is widely available. This project aims to prototype a solution using ChatGPT to provide communication assistance to those diagnosed with autism. The project would record voice input through a microphone and transcribe it into text. The text would be …

A Predictive Framework For Early Detection And Personalised Monitoring Of Parkinson’S Disease Using Artificial Intelligence And Large Language Models, Priyadharshini S

Theses and Dissertations

Parkinson’s Disease (PD) is a multifaceted and progressive neurodegenerative disorder that presents a spectrum of motor and non-motor symptoms. Early and accurate diagnosis is essential for effective disease management and improved patient outcomes, yet remains clinically challenging due to symptom overlap and diagnostic limitations. This thesis proposes a comprehensive and interpretable artificial intelligence (AI)-driven diagnostic framework that aims to transform the early detection, personalised monitoring, and treatment recommendation process for PD. The proposed solution integrates deep learning, radiomics, evolutionary optimisation, and large language models (LLMs), ensuring a highly accurate and clinically adaptable system.

The research begins by analysing T2-weighted 3D …

Fresh And Mechanical Properties Of Self-Compacting Concrete Using Kaolin Limestone Blend And Hybrid Slag Blend, Selesca Devi S

Theses and Dissertations

This study examined the consequences of mono and hybrid natural fibers on the mechanical and fresh properties of self-compacting concrete (SCC), in response to the growing demand for environmentally friendly building materials. In mono fiber, Abaca fiber (AF) at 0.25% and 0.5% dosage, basalt fiber (BF) from 0.25% to 2% at 0.25% increments, and sisal fiber (SiF) from 0.25% to 1.5% at 0.25% increments were evaluated through slump flow diameter, T500, compressive and tensile strength. AF at 0.25% ensured good flow with 6.6% and 4.16% higher compressive and tensile strength over 0.5% AF. SiF up to 1% improved strength but …

Mode Engineering And Functional Enhancement In Piezoelectric-On-Silicon Mems Resonators With Magnetic Field Sensing Applications, Ugur Guneroglu

USF Tampa Graduate Theses and Dissertations

This dissertation significantly advances the field of micro-electro-mechanical systems (MEMS) resonators by exploring novel post-fabrication tuning techniques, electrode configuration effects, and innovative sensor applications for thin-film piezoelectric-on-silicon (TPoS) resonator devices. Driven by the increasing demand for tunable, high-precision and robust MEMS resonators in radio frequency (RF) applications such as sensing, timing, and filtering, this research aim to provide foundational knowledge and practical solutions for overcoming existing technological limitations. The dissertation is organized into three main research thrusts, each addressing critical challenges and opportunities in the design, fabrication, and application of TPoS MEMS resonators.

The first research thrust investigates an innovative …

Retrospective Study And Predictive Modeling Of The Impact Of Social Determinants Of Health On Sepsis Outcomes, Mwembezi Aaron Nyelele

LSU Doctoral Dissertations

Sepsis, a life-threatening organ failure caused by the body’s abnormal and harmful response to an infection, remains a major global and national health challenge. In the United States, it contributes significantly to hospital mortality and imposes a substantial economic burden, with billions spent annually on treatment. Early diagnosis is difficult due to the nonspecific nature of sepsis symptoms, often leading to delays in care and poorer outcomes. As the incidence and severity of sepsis rise, identifying factors that influence outcomes is increasingly critical. Emerging research has shown that Social Determinants of Health (SDOH), including economic stability, education, neighborhood and built …

Towards Leveraging Social Media Data For Fostering Collaborations Among Non-Profits, Monazil Chowdhury

LSU Doctoral Dissertations

Nonprofit organizations serve a crucial role in tackling a wide range of significant social, environmental, and economic issues. But it is often hard to get a clear picture of their work because their information is spread out and it is difficult to see how they are collaborating. To address this issue we developed a web-based tool to collect scattered data—from a variety of sources, such as the IRS, social media, and the Census, into one easy-to-use resource. The tool begins by taking IRS records and geocoding each nonprofit’s physical address With its coordinates. It then retrieves census tract information from …

Security Analysis Of Encrypted Mempool, Prabal Das

Master’s Dissertations

With the rapid growth of Decentralized Finance (DeFi), the challenge of Maximum Extractable Value (MEV) has become increasingly significant-particularly on Ethereum. MEV allows malicious actors to manipulate transaction order within blocks, enabling exploitative strategies such as frontrunning and sandwich attacks. In response, recent research has proposed encrypted mempools, which conceal trans- action content until after ordering is finalized, thereby reducing the exploitable surface for MEV. This thesis investigates encrypted mempool, specifically the Shutter protocol, a threshold encryption-based approach designed to mitigate MEV by hiding transac- tion contents during the mempool phase. We analyze its core architecture, under- lying cryptographic mechanisms, …

Advancing Eye-Gaze Writing Systems With Computer Vision, And Dynamic Text Suggestions, Walid Abdallah Shobaki

Theses and Dissertations

Eye gaze writing, a novel interaction modality, has the potential to revolutionize communication for individuals with limited mobility. In our research, we investigated the deep learning algorithms efficiency for real-time eye gaze writing. We have compared many algorithms' performance in many computer vision areas, such as object detection in which we used first YOLOv8, the second algorithm SSD, and the third algorithm is Faster R-CNN, the second computer vision area is the image segmentation in which we used DeepLab and U-Net, and the last computer vision area is self-supervised learning we have used SimCLR algorithm. By evaluating these models on …

Design & Development Of Efficient Biometric Authentication And Key Agreement Schemes For Wireless Body Area Network, Aarthi S

Theses and Dissertations

Wireless Body Area Networks (WBANs) play a vital role in continuous health monitoring, where sensitive biometric and physiological data must be protected from privacy breaches and emerging quantum-based threats. Conventional security mechanisms are often inadequate due to resource constraints, scalability issues, and vulnerability to advanced attacks. To address these challenges, this research proposes a lightweight, scalable, and future-proof security framework tailored for WBAN applications, focusing on secure communication, privacy preservation, and quantum resilience.

An anonymous Certificate-Based Signcryption–Mutual Authentication and Key Agreement (CBS-MAKE) protocol is introduced to secure extra-body communications while ensuring patient anonymity. The protocol integrates Elliptic Curve Cryptography with …

The Design And Effect Of Continuum Robot Compliance On Locomotion, Parsa Molaei

LSU Doctoral Dissertations

Continuum robots, due to their compliant structures and ability to navigate through constrained environments, offer significant advantages in applications requiring safe physical interaction and dexterous motion. However, challenges related to limited structural stiffness, payload capacity, and precise control remain open problems in the field. This dissertation presents novel contributions aimed at addressing these limitations through two main actuation units of continuum robots: tendon-driven continuum robots (TDCRs) and concentric tube robots (CTRs). In the first part, we focus on methods to improve the stability and modify the stiffness of the TDCR. A tendon decoupling strategy is introduced for planar TDCRs. The …