Engineering Commons^™

Use Of Mid-Infrared Spectroscopy For Estimating Soil Chemical, Physical, And Hydrological Properties In Mississippi And Texas, Kanthake Yasas Bandara Gamagedara

Theses and Dissertations

Accurate and efficient estimation of soil properties is essential for advancing sustainable agriculture, water management, and soil survey applications. Traditional laboratory methods and pedotransfer functions (PTFs) are widely used but are often constrained by high costs, time requirements, and limited scalability. As an alternative, mid-infrared (MIR) and visible–near-infrared (vis–NIR) spectroscopy provide cost-effective, rapid, and non-destructive approaches for soil analysis. However, variability among spectrometer types, geographic regions, and soil scanning conditions poses challenges to model transferability and generalizability. This dissertation evaluated strategies to overcome these challenges and enhance the prediction of soil chemical, physical, and hydrological properties in Mississippi and Texas. …

Electrospun Nanofiber Creation With Varying Polymer-Solvent Combinations For Air Filtration, Lancaster Jace Hill

Theses and Dissertations

This study aims to analyze various polymer-solvent combinations for electrospun creation of nanofiber media and to determine the best-suited solution for lab-grade electrospinning. Suitable solutions allow for controlled morphology of fiber diameters and for efficiency of media creation. The principal variables are solvent, concentration, and voltage. Humidity and temperature play a secondary variable role. The solution must withstand an electric field of ≤30 kV and be insoluble in water to maintain desired morphology and structure. Manipulation of the solutions and variables allow for fiber diameter optimization and beading minimization. High temperature filter applications require efficiency in intense heat and preservation …

Electrochemical Detection Of No And Ca2+ During Cold Atmospheric Plasma Treatment Of Acute Wounds: Sensor Selectivity And Stability In The Plasma-Bio-System, Jonathan E. Thomas, Kristina Pattison, Suneel Kumar, Gagana Karkada, Duncan Trosan, Aunic Goodin, Jason Rainone, Dnyaneshwari Rananavare, Vandana Miller, Francois Berthiaume, Katharina Stapelmann

Kimmel Cancer Center Faculty Papers

Cold atmospheric plasmas (CAP) are a versatile tool in medical applications like wound healing. Its therapeutic benefits are partially attributed to the generation of biologically active reactive oxygen and nitrogen species (RONS). Characterization of RONS, however, typically only occurs after treatment. Here we report the first real-time in situ detection of CAP-generated nitric oxide (NO), and the simultaneous detection of cellular calcium ions (Ca²⁺) release using electrochemical sensors during CAP treatment of murine wounds. In vivo, NO rose rapidly within the first minute of CAP treatment but accumulated less overall than in PBS, reflecting reactions with wound-bed targets. In situ …

Technological Disruption And Regulatory Response: The Case Of Decentralised Finance, Jakub Wisła, Jolanta Bartoszewska

Journal of Banking and Financial Economics

This article examines responses to the regulatory challenges posed by decentralised finance (DeFi), a fast-evolving domain of blockchain-based financial innovation. It investigates the factors shaping divergent regulatory strategies, with a focus on the European Union’s comprehensive cryptoasset framework and selected comparative insights. Adopting a qualitative legal methodology – combining doctrinal-functional analysis, multivocal literature review, and two case studies – the authors explore how regulatory responses are influenced by three key variables: legal tradition, the financial function performed by blockchain-based solutions, and the level of technological and institutional autonomy. The case studies – Bitcoin as a payment instrument and cryptoassets as …

Study Of Isocyanate-Free Vegetable Oil-Based Polyurethane Coating With A Silicon-Based Compound For Coating Properties, Ajay Kumar

Electronic Theses & Dissertations

The development of sustainable and environmentally friendly polyurethane coatings has garnered significant attention in recent years. This research focuses on the development of isocyanate-free coatings derived from carbonated soybean oil (CSBO) using a solvent- and catalyst-free approach. The coatings were synthesized by reacting CSBO with ethylenediamine (EDA) and varying weight percentages of 3-aminopropyltriethoxysilane (APTES), which were added to enhance the coating property, as it contains silicon in it, to evaluate their mechanical and thermal properties. Fourier Transform Infrared Spectroscopy (FTIR) confirmed the successful formation of urethane linkages, with a significant reduction in C=O peak intensity after 10 days of curing, …

The Effects Of Nanobubble Fertigation And Soil Conditioners To Improve Nutrient Dynamics, Soil Microbial Activity, And Chili Productivity, Betty Natalie Fitriatin, Euis Ahah Rokayah, Elsa Naila Elmyra, Tualar Simarmata, Nicky Oktav Fauziah, Hanif Fakhrurroja

Jurnal Kultivasi

Drip fertigation is a fertilization method that integrates nutrient delivery with an irrigation system, which is capable of optimizing the direct delivery of nutrients to the root zone. This experiment aims to investigate the effect of drip fertigation with nanobubble technology, and soil conditioners on the population of Phosphate-Solubilizing Bacteria (PSB) and Azotobacter spp., available phosphorus, total nitrogen, growth, and yield of red chili. The study used a Strip Plot Design with two factors and three replications. The first factor was nutrient application (solid NPK fertilizing as control; drip fertigation; and drip fertigation with nanobubble technology), and the second factor …

Quantifying Benefits Of Biochar With Variable Absorption Capacity As A Partial Cement Replacement In Concrete, Benjamin Shannon

Theses and Dissertations

Extensive research has been conducted on biochar-incorporated concrete. However, no concrete mixture design guideline is currently available for implementing biochar incorporation in practice. The objective of this study was to correlate biochar absorption capacity with the compressive strength of biochar-incorporated concrete, to quantify the benefits of biochar and develop mix design guidelines. Biochar with varying absorption capacities was incorporated into concrete at 10%, 20%, and 40%. Strength and moisture loss were recorded over the 90-day curing period of the biochar-incorporated concrete. Results revealed three main findings: (1) in 10%, 20%, and 40% biochar mixes, the normalized strengths ranged from 0.65–0.85, …

Analysis Of Trends From Mass Concrete Case Studies, Bradford Songer

Theses and Dissertations

While conventional mass concrete is well understood, high strength and ultra high performance concrete present unique challenges when placed in large volumes. This thesis compiles and analyzes thermal data from mass high strength and ultra high performance concrete placements collected over the past eight years by the U.S. Army Corps of Engineers in support of military construction projects. The datasets span a wide range of material types and volumes. The analysis identifies trends in temperature development, temperature differentials, and the influence of mixture constituents on heat generation. This thesis contributes to the improved understanding of thermal behavior in mass concrete. …

Exploring The Impact Of Incorporating Artificial Intelligence Integrated Systems In The Workplace, Catherine Cruz Agosto Noda

Theses and Dissertations

This study focuses on assessing the impact of incorporating systems integrated with in the workplace by assessing the constructs of usability, cognitive load, and trust. The constructs are assessed by generation and experience level to determine which factors are relevant in a workplace setting. A workplace scenario was simulated by asking participants to complete tasks where they assumed the role of a warehouse manager assigned with assessing two scheduling systems – one with artificial intelligence and one without artificial intelligence. The participants were presented with three tasks of increasing difficulty for each prototype. Both quantitative and qualitative measures were used …

Optimizing Military Fighter Jet Selection: A Decision Analysis Approach For Nuclear-Capable Aircraft, Eni Kelechi Ofong

Theses and Dissertations

This research investigates the strategic decision-making process involved in selecting a nuclear-capable fighter aircraft for NATO (North Atlantic Treaty Organization) nations in Europe. In adaptation to the continuously changing technology landscape and the necessity for enhanced deterrence capabilities, this study evaluates three potential aircraft: the legacy Panavia Tornado (PA-200), the widely deployed F-16 Fighting Falcon (F-16), and the advanced F-35 Lightning II (F-35). Each platform presents distinct advantages and limitations regarding operational performance, mission adaptability, cost-effectiveness, and long-term sustainability. To systematically assess these alternatives, the study employs various decision analysis frameworks, including Multi-Criteria Decision Analysis (MCDA), single dimensional value function …

Considerations For Cottonseed Oil As A Feedstock For Renewable Fuels, John Elmore

Theses and Dissertations

As the world population grows and the standard of living improves in developing countries, global energy demand will continue to rise, with energy use in the developing world expected to increase dramatically more than the per capita reductions in developed countries from efficiency improvements. Nearly a third of the total global energy demand is used for transportation, resulting in a substantial contribution to greenhouse gas (GHG) emissions. While the demand for energy rises, initiatives and regulations are underway to mitigate the amount of GHG emissions to Earth’s atmosphere. As efforts progress in industry, governments, and society to reduce the total …

Development And Validation Of A Machine-Learned Actuator Line Model For Rotors, Joshua L. Bowman

Theses and Dissertations

This dissertation develops and validates a machine‑learned (ML) actuator line model (ALM) as an advancement in rotor modeling that can be applied to diverse engineering applications. The model addresses two standard ALM limitations: dependence on pre‑tabulated lift and drag coefficients and the inability to represent unsteady inflow. The ML‑ALM is trained on a hydrokinetic blade‑resolved simulation database of blade‑element forces under unsteady conditions, and is queried at run time to supply axial, tangential, and spanwise forcing at each actuator element. Validation covers solitary rotor performance and wake predictions against experimental data, and verification in an inline configuration against blade‑resolved simulations …

Novel Experimental Techniques For Pressure Transients, Luliang Zhang

Theses and Dissertations

This dissertation introduces novel experimental techniques for analyzing pressure transients, focusing on dynamic strain and pressure measurements to advance the understanding and application of Pulse Pressure Amplification in percussive devices. The research evaluates a high-speed linescan extensometer utilizing linescan Digital Image Correlation (DIC) on a Kolsky Bar to obtain strain data at high strain rates. This data is critical for accurate material characterization and simulations to model dynamic behavior. Additionally, a novel method for measuring dynamic pressure waves in pipe systems has been developed, enabling direct assessments of pressure amplification in devices such as tapered pipe systems. The findings contribute …

Lecun-Pso Hybrid Initialization Of Neural Network Using Asymmetric Gait Features For Classification Of Parkinson’S Disease, Michael Joseph Carter

Theses and Dissertations

Parkinson's disease (PD) is a complex condition with a wide range of clinical symptoms. It is a progressive neurological disorder that has afflicted an estimated 1 million people in the US and 10 million worldwide. The diagnosis of PD is typically based on the presence of clinical features, with no specific diagnostic test or biomarker. The methods of assessment for PD are also used, in whole or in part, for similar symptom diseases such as Multiple Sclerosis, Essential Tremors, Multiple System Atrophy, Supranuclear Palsy, Dementia with Lewy bodies and Huntington’s disease. Many of the current clinical tests have low sensitivity …

Physics-Informed Neural Network For Maximum Detectable Distance Estimation In Mobile Gamma Spectrometry, Nancy A. Ibrahim

Theses and Dissertations

Accurate estimation of the Maximum Detectable Distance (MDD) is critical for environmental remediation, nuclear incident response, and public safety. Conventional approaches assume stationary detectors and rely on computationally intensive simulations, limiting their applicability for mobile, real-time surveys. Mobile gamma spectrometry introduces additional complexities due to detector motion, variable acquisition times, and heterogeneous backgrounds. This study addresses the central question of how effectively a Physics-Informed Neural Network (PINN) can estimate MDD for mobile gamma spectrometry, while maintaining both accuracy and computational efficiency under dynamically changing environmental conditions. A multi-phase approach was employed, combining field data collection, computational modeling, and operational tool …

Leveraging Google Earth Engine For Computationally Efficient Pixel-Level Analysis And Vector Delineation From Satellite Data., Rishita Garg

Theses and Dissertations

Analyzing large-scale, high-resolution satellite imagery is a computationally intensive task requiring time and computing resources. This can be accelerated using cloud computing platforms such as Google Earth Engine (GEE) where computational and storage requirements can be scaled based on demand. However, cloud-based platforms for processing high-resolution imagery remain underutilized in environmental applications such as agriculture, and forest health. This thesis explored the application of GEE to two geospatial problems in agricultural conservation and disease mapping in forestry: 1) Extraction of agricultural field boundaries from Sentinel-2 satellite imagery, for use in conservation, precision agriculture, land management, and organization, etc., and 2) …

Study On Vehicle-Pedestrian Interaction Autonomy By Risk Potential Theory, Riku Kikuta

Theses and Dissertations

Vehicle–pedestrian interaction is a critical aspect of autonomous vehicle (AV) development, as socially acceptable AVs must account for pedestrian intention and behavior. Risk Potential (RP) theory provides a framework to build human-like AVs by modeling expert driver risk perception, but conventional RP models treat pedestrians as static obstacles and neglect their dynamics. This dissertation extends RP theory by incorporating pedestrian velocity and orientation into three new models: the RP velocity model, the RP related-velocity model, and the RP Pedestrian Potential Position (PPP) model. These models were implemented in the Navigating All Terrains Using Robotic Exploration (NATURE) autonomy stack and tested …

A Case Study On Redesigning Classroom Activities And Assessments For Generation Z Students, Sushma Shrinivasan

Theses and Dissertations

This dissertation investigates the dynamic interplay between pedagogical strategies, learner diversity, and emerging educational technologies through three interconnected studies. Study 1 compares Traditional instruction, Problem-Based Learning (PBL), and Simulation-Based Learning (SBL), revealing that while PBL and SBL enhance student performance—particularly PBL—their impact on perceived learning varies. Notably, SBL reduced perceived learning despite strong outcomes, underscoring the affective and metacognitive complexities of active learning. Study 2 examines the role of demographic factors such as gender, ethnicity, employment, and first-generation status, finding no significant main effects but identifying a key two-way and three-way interactions, suggesting that instructional effectiveness is influenced by the …

Integrated Experimental, Numerical, And Machine-Learning Framework For The Analysis Of Spray Dynamics In Diesel And Gasoline Direct-Injection (Gdi) Engines, Yassine El Marnissi

Theses and Dissertations

The regulation of diesel and gasoline direct injection (GDI) during cold starts has become subject to stricter numerical limits by both the Environmental Protection Agency (EPA) in the US and the European Commission (EC). For diesel engines, the EPA’s Clean Trucks Plan (Model Year 2027+) sets a certification NOₓ limit of 0.035 g/bhp-hr and an in-use fleet average limit of 0.050 g/bhp-hr, along with a PM limit of 0.005 g/bhp-hr, representing an 82.5% reduction in NOₓ compared to the former 0.2 g/bhp-hr standard. For gasoline engines, US standards regulate cold-start pollutants such as hydrocarbons (HC) ranging from 0.03 to 0.08 …

Concerted Rattling-Induced Strong Anharmonicity And Phonon Coherence Lead To Ultralow Glasslike Thermal Conductivity In Tlagte, Shantanu Semwal, Yi Xia, Chris Wolverton, Koushik Pal

Mechanical and Materials Engineering Faculty Publications and Presentations

Ordered crystalline compounds exhibiting ultralow and glass-like thermal conductivity are both fundamentally and technologically important, where phonon quasi-particles dominate their heat transport. Understanding the microscopic mechanisms that govern such unusual transport behavior is necessary to unravel the complex interplay of crystal structure, phonons, and collective excitations of these quasi-particles. Here, we use state-of-the-art first-principles calculations based on quantum density functional theory to investigate the origin of experimentally measured unusually low and glassy thermal conductivity in semiconducting TlAgTe that possesses disconnected chains of Tl atoms within its three-dimensional crystalline framework made up of distorted AgTe4 tetrahedra. Utilizing a unifying framework of …

Dynamic Urban Air Mobility Systems Modeling And Simulation, Amer M. Ibrahim

Tennessee State University Alumni Theses and Dissertations

The use of electrical vertical takeoff and landing (eVTOL) aircraft to provide efficient, high-speed, on-demand air transportation within a metropolitan area is an increasingly popular topic, which is expected to bring fundamental changes to cities. The concept of Urban Air Mobility (UAM) has the potential to make meaningful door-to-door trip time savings compared with other transportation. The capability to manage many of these eVTOL aircraft safely in a congested urban area presents an unprecedented challenge in air traffic management. In order to enable safe and efficient autonomous on-demand free flight operations in UAM, a computational guidance algorithm with collision avoidance …

Pria: Process Risk Identification And Analysis, Raymond Fasano

Nuclear Engineering ETDs

This dissertation proposes and evaluates two approaches, with-in a Process Risk and Analysis (PRIA) framework, that advance data-driven hazard discovery in complex cyber-physical systems. First, a transferability-based clustering method groups subspace-identified segments into operational modes, prioritizing cross-predictive performance over raw feature proximity. Second, a Neural Switching Linear Dynamical System (NeuralSLDS) model anchors learning in identified state-space models with Bayesian residuals, calibrated predictive uncertainty, and context-aware operating mode transitions. Together, these methods generate physics-informed, probabilistic world models that can support model-in-the-loop analysis of hazardous trajectories. The approach is validated on a simulated point-kinetics reactor and a centrifugal chiller dataset, demonstrating coherent …

Conditional Generative Adversarial Network Framework For Iot Anomaly Detection, Henry Onyeka

Tennessee State University Alumni Theses and Dissertations

The growing scale and complexity of Internet-of-Things (IoT) edge networks complicate anomaly detection, particularly in identifying sophisticated Distributed Denial of Service (DDoS) attacks and zero-day behaviors under highly dynamic and imbalanced traffic conditions. This thesis proposes SD-CGAN, a Conditional Generative Adverserial Network optimzied with Sinkhorn Divergence as a geometry-aware one-class framework for robust IoT anomaly detection. SD-CGAN trains solely on benign traffic flows to learn a stable representation of normal traffic. To address class imbalance and improve the variety of the sample, we combine SD-CGAN with CTGAN-based synthetic data augmentation. Replacing the adversarial objective function with Sinkhorn Divergence yields smooth …

Warehouse Reconfiguration With Ats Lab, Ed Cantor, Dana Pazhouhesh, Mathew Oshinski, Samantha Sanchez

Senior Design Project For Engineers

The ATS Lab Warehouse Reconfiguration project is a collaborative effort between Kennesaw State University’s Department of Industrial and Systems Engineering and ATS Lab, located in Marietta, GA. The goal of this project is to redesign the current warehouse layout to enhance operational efficiency, reduce travel time, and implement sustainable inventory management practices, including 5S and Kanban. Aaron Roob, ATS Operations Manager, and Franklin Hungerford, Continuous Improvement Manager, led this initiative. Our team, “Sick Sigma’s,” is composed of Ed Cantor, our Project Manager, who is working as an intern at ATS during this process; Dana Pazhouhesh (Process Engineer); Matthew Oshinski (Quality …

Bilstm-Based Zero-Aware Traffic Forecasting Using Lidar Data For Intersection Safety, Md Atiqur Rahman Mallick

Tennessee State University Alumni Theses and Dissertations

LSTM retains information from long-term data and is highly effective in generating time-based forecasts. Recently, BiLSTM has enhanced the precision of traffic predictions by assimilating information from both antecedent and subsequent directions via bidirectional data flow. BiLSTM demonstrates exceptional efficacy in the analysis of long-term traffic data. Our study presents a custom forecasting model that leverages advanced LiDAR sensor technology in combination with state-of-the-art deep learning techniques to improve road conditions. Eight LiDAR sensors were strategically deployed along the 26th Clarksville Pike corridor to collect high-resolution traffic data—including vehicle speed and count/flow—over the period from September 1, 2024 to November …

Privacy-Preserving Data Sharing For Learnable Encryption Artificial Intelligence In E-Health, Al Amin

Tennessee State University Alumni Theses and Dissertations

Healthcare AI requires large datasets for clinical-grade performance, yet privacy regulations prevent direct inter-institutional data sharing. While traditional federated learning (FL) enables collaborative training without centralizing data, it suffers from four critical limitations: accuracy degradation, gradient leakage vulnerabilities, high communication costs, and limited interpretability. Accordingly, the overarching research goal is to design a privacy-first FL framework for e-health that preserves clinical-grade accuracy on obfuscated data while substantially reducing information leakage, minimizing communication overhead, and enabling interpretable decision support without sharing weights, gradients, or raw pixels. This thesis systematically addresses these challenges through a three-method framework that progressively enhances privacy, efficiency, …

Design And Development Of Rechargeable Cement-Based Batteries For Energy Storage Within Infrastructure, Dandan Yin

Tennessee State University Alumni Theses and Dissertations

This dissertation presented the design, fabrication, and evaluation of rechargeable cement-based batteries (CBB) for energy storage within infrastructure. The study aimed to integrate electrochemical energy storage directly into cementitious materials, enabling multifunctional and sustainable building systems. Nickel–iron electrodes and cement-based solid electrolytes to form durable, solid-state systems. The electrochemical impedance spectroscopy, cyclic voltammetry, and galvanostatic charge–discharge tests，along with microscopic testing and mechanical testing analyses, were conducted to assess battery performance. The carbon fiber mesh CBB achieved stable cycling over 100 cycles with quasi-reversible redox behavior and a maximum areal energy density of 7.6 Wh m⁻². Nickel foam electrodes, with their …

Power Resilience In Utah's Water Sector: A Survey Of Stakeholder Practices, Preferences And Potential, Tyler Christopher Peterson

Theses and Dissertations

Drinking water and wastewater services are vulnerable to disruptions because they rely heavily on the electric grid. As a result, power outages can lead to water outages, creating cascading failures that compromise sanitation, firefighting, healthcare, and daily routines. Although an important topic, there are little to no studies of water and wastewater power resilience at a geographic or state level. In this study we investigate the extent of existing backup power and renewable energy integration as well as the motivations and barriers around their power resilience. We collect our data through semi-structured interviews with staff at 19 urban and rural …

Climate-Driven Flood Risk Mapping And Adaptive Strategy Modelling For Coastal Tamil Nadu, Sakthi Kiran Dr Mr

Theses and Dissertations

Background: Tamil Nadu’s coastal corridor (Cuddalore–Sirkazhi; ~2,740 km²) experiences recurring floods driven by climate change, rapid urban expansion, and inadequate drainage across low-lying deltaic terrain. Existing flood assessments remain largely reactive and rely on static methods that fail to incorporate future climate projections, demographic growth, and evolving urban patterns.

Methods: This research develops a dynamic, climate-resilient flood risk framework integrating (i) long-term hydroclimatic trend analysis (1984–2023), (ii) satellite-based flood hazard mapping using multi-temporal Sentinel-1A and RISAT-1A SAR, (iii) CORDEX REMO2015 (RCP 4.5)–driven HEC-RAS 2D hydrodynamic modelling, (iv) machine-learning-based susceptibility modelling (RF, DT, SVM), and (v) scenario-based evaluation of structural mitigation …

Mechanical Quality Of Hemp Fiber As Influenced By Tillage, Cover Crop, And Nitrogen Management In Regenerative Organic Systems, Parinaz Heydar, Alyssa Pierce, Gabriella Fioravanti, Ronald Kander

School of Design and Engineering Papers

Industrial hemp (Cannabis sativa L.) is an emerging crop for renewable fiber materials. For farmers, finding a balance between agronomic performance and economic return is crucial, especially when targeting specific markets like the textile industry, which values not just fiber quantity, but overall quality. This field study, conducted at the Rodale Institute in Kutztown, Pennsylvania, assessed the effects of tillage (till vs. no till), cover crop (with cover vs. no cover), and nitrogen (N) rate (0, 50, 100, 150 kg ha⁻¹) on hemp fiber yield, N concentrations in leaf and stalk, and mechanical performance under regenerative organic conditions. Fiber mechanical …