Digital Commons Network^™

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 …

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, …

In-Situ Investigations Of Calcium-Magnesium-Aluminosilicates (Cmas) Infiltration Effects On Thermal Barrier Coatings Under Extreme Environments Replicating Jet Engines, Zachary Stein

Doctoral Dissertations and Master's Theses

Calcium-magnesium-aluminosilicate (CMAS) particulates, such as sand or volcanic ash, are ingested by gas turbine jet engines during operation. When operating within high abundance regions, these particulates negatively interact and degrade the high temperature thermal barrier coatings (TBC) protecting underlying superalloy turbine blades vital to engine operation. These CMAS particulates melt within the engine and infiltrate into the ceramic coatings. In electron-beam physical vapor deposited (EB-PVD) TBCs, the CMAS within the intercolumnar gaps stiffens the coatings and causes thermomechanical induced high stress concentrations, risking crack formation. While molten, the CMAS thermochemically alters and destabilizes the coating, also risking coating failure. Premature, …

Parameter Informed Reinforcement Learning For Vehicle System Identification, Nathan Schaff

Doctoral Dissertations and Master's Theses

Accurate system identification is essential for modeling and controlling vehicle dynamics. This dissertation explores the application of Parameter Informed Reinforcement Learning (PIRL) as a novel approach to system identification (SYSID). PIRL integrates prior system knowledge, such as physical parameters, into reinforcement learning (RL) frameworks to improve estimation accuracy. The study begins with an overview of traditional SYSID methods and then introduces PIRL as a modification of standard RL. The research applies PIRL to short-period aircraft dynamics, demonstrating its effectiveness in both offline and online learning frameworks. The dissertation then further explores PIRL’s utility in an indirect model reference adaptive control …

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 …

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 …

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 …

Experimental And Theoretical Characterization Of Molten Salt Thermal Conductivity, Jacob C. Numbers

Theses and Dissertations

Molten salts form an ideal heat transfer fluid for advanced energy generation systems, including molten salt reactors (MSR). Accurate characterization of molten salt thermal conductivity is needed to confidently predict transient thermal behavior and optimize salt properties. Measurements are hindered by salts' challenging material properties, which---in the case of the needle probe device---induced unaccounted physical changes that limited its accuracy and repeatability. Sparse thermal conductivity data in general is exacerbated by a limited fundamental understanding of molecular energy transfer in liquids. This work extends the experimental capacity for compositional studies using the needle probe and proposes a theoretical model for …

Development And Validation Of 2nn-Meam Interatomic Potential For Sc And Al-Sc Alloys Thermodynamics Solidification And Intermetallic Ordering, Avik Mahata

Mechanical Engineering Faculty Publications

We present a second-nearest-neighbor Modified Embedded Atom Method (2NN–MEAM) potential for Scandium (Sc) and Aluminum-Scandium (Al–Sc) alloys that unifies cohesive, thermodynamic, and solidification behavior within a single transferable framework. The Sc component accurately reproduces cohesive energy, lattice constants, defect energetics, and the experimental melting point obtained from two-phase coexistence, demonstrating reliable description of both hcp and liquid phases. The Al–Sc binary interaction parameters were fitted using the L1₂–Al₃Sc reference and benchmarked against first-principles and calorimetric data. The potential reproduces the strong negative formation enthalpy of Al₃Sc (–0.45 eV atom⁻¹), correct relative stability …

Time Series Modeling Of Land Use And Land Cover Classification Using Remote Sensing, Ahmed A. F. Abd El Hamed, Fawzi H. Zarzoura, Mahmoud El-Mewafi

Mansoura Engineering Journal

Understanding land use / land cover changes is essential for planning sustainable development. It represents the transformation of the land due to human activities, which is related to sustainable development that aims to achieve the needs of the present generations without affecting the future. Land use / Land cover is studied in Al Alamein region, northern Egypt, with supervised classification methods using satellite images from Landsat 8 and Sentinel - 2A in 2023 and analyzes the accuracy assessment, which shows Maximum likelihood is better in both sensors achieving overall accuracy (91.80% and 91.02%) and kappa coefficient (0.814 and 0.8799). Then …

High-Resolution Lidar Observations Of Sedimentation-Induced Size Sorting Of Droplets Near A Laboratory Cloud Top, Fan Yang, Yong Meng Sua, Zipei Zheng, Jesse Anderson, Hamed F. Sadi, Jae Min Yeom, Suryadev Pratap Singh, Pei Hou, Will Cantrell, Ernie Lewis, Alex Kostinski, Raymond Shaw

Michigan Tech Publications

No abstract provided.

Improving Road Safety Through Multimodal Deep Learning For Driver Drowsiness Detection, Hadel A. Hussain, Mohammed A. Subhi, Ahmed S. Al Tmeme, Ahmed D. Radhi, Marwan Ali Albahar

Iraqi Journal for Computer Science and Mathematics

One of the most common causes of road accidents globally is driver drowsiness and it needs solutions that are reliable and can be applicable in numerous real-life situations. We present this paper with the aim of developing a deep-learning system that is capable of reliably detecting drowsiness in diverse and varied conditions across different drivers, environments, and sensor types. Our system is known as Multimodal Attention Network (MMAN), which combines information of eye and head movement, heart-rate and breathing pattern, and vehicle-dynamics signal. MMAN has a gradient-reversal layer that enables the layer to be domain-adaptive such that it does not …

Deep Learning-Based Fog-Cloud Approach Intrusion Detection System In Iomt, Yahya Rbah, Mohammed Mahfoudi, Mohammed Fattah, Younes Balboul, Said Mazer, Moulhime Elbekkali

Iraqi Journal for Computer Science and Mathematics

The Internet of Medical Things (IoMT) creates an interconnected environment linking humans, devices, sensors, and systems, enhancing healthcare services through advanced technologies. Nonetheless, these IoMT devices are susceptible to cyberattacks, which can endanger patient safety and healthcare services. To identify and mitigate cyberattacks in IoMT, techniques such as threat intelligence, log monitoring, and intrusion detection systems are employed. As attackers evolve their strategies, there is a growing trend towards leveraging artificial intelligence to achieve more predictive and accurate attack detection. Since IoMT devices are inherently low-power, they require minimal computing resources. Existing intrusion detection systems are generally trained in the …

Multitaskvenationnet: A Multi-Task Deep Neural Network With Strip Pooling And Hybrid Upsampling For Leaf Vein Segmentation, Ishak Ariawan, Ahmad Ashari, Moh. Edi Wibowo

Iraqi Journal for Computer Science and Mathematics

Leaf vein segmentation is a critical task in plant phenotyping and species classification, yet it remains challenging due to the hierarchical, curvilinear nature of veins and interference from complex backgrounds. Existing methods face three key limitations. First, they lack directional context modeling, leading to blurred vein boundaries and the omission of fine venation. Second, they fail to effectively capture global dependencies, limiting semantic coherence across spatial regions. Third, they do not incorporate explicit mechanisms for detecting vein discontinuities, which is essential for complete topological understanding. To address these challenges, we propose MultiTaskVenationNet (MTV-Net), a multi-task deep segmentation framework that integrates …

Performance Of Adaptive Wingtips On A Tailless Supersonic Business Jet, Khushi Piparava

2025 Fall Honors Capstones Projects - Archive

The growing interest in supersonic business travel has renewed focus on efficient, low-drag configurations that can achieve high performance while maintaining stability and structural integrity. This research investigates the aerodynamic and structural implications of adaptive folding wingtips on a tailless supersonic business jet (SBJ) concept designed under the SkyBreaker senior design program. Using a conceptual aerodynamic model based on linearized supersonic theory, the Polhamus leading-edge suction analogy, and an empirical compression-lift correlation, the study evaluates how varying wingtip droop angles influence lift, drag, lift-to-drag ratio (L/D), and static stability. The analysis was performed parametrically in MATLAB, using geometry inputs derived …

Analytical Assessment Of Pedestrian Crashes On Low-Speed Corridors, Therezia Matongo, Deo Chimba

Civil and Architectural Engineering Faculty Research

This study presents a comprehensive statewide analysis of pedestrian-involved crashes recorded in Tennessee between 2002 and 2025. We evaluated the influence of roadway, traffic, environmental, and socioeconomic factors on pedestrian crash frequency and severity with substantial components focused on lighting impacts including dark and nighttime. A multi-method analytical framework was implemented, combining descriptive statistics, non-parametric tests, regression analysis, and advanced machine learning techniques including the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the gradient boosting model (XGBoost). Results indicated that dark and nighttime conditions accounted for a disproportionate share of severe crashes—fatal and serious injuries under dark conditions reached over 40%, …

Portable Skin Imaging Light-Box For Clinical Grade Skin Scans, Kayandra Lewis, Cayden Skidmore, Komi Atitsogbe Golo

Senior Design Project For Engineers

This project focuses on designing and developing a modular, portable skin-imaging light box to improve the consistency and accuracy of smartphone-based dermatological imaging. As AI-driven skin assessment tools grow in capability, a major limitation remains the variability in lighting, angle, and color fidelity in user-captured photos. To address this challenge, the team created a fold-flat, low-cost light box that attaches securely to a wide range of smartphones and provides uniform, high-CRI illumination suitable for clinical-grade analysis. Research into lighting technologies, human factors, smartphone specifications, and AI diagnostic tools guided the engineering decisions, ensuring the design aligned with real-world telemedicine and …

Orbital Reliable Printed Circuit Boards, Thomas Maxwell Starnes, Keegan Blake Jordan, Ian Griffith, Grant Monroe Pesqueira, Vishal Navin Patel

Senior Design Project For Engineers

Deep Interstellar Solutions is proposing a device to produce custom, serviceable printed circuit boards (PCBs) in low Earth orbit. This technology uses blank PCBs that are laser-etched and prepared for electrical components, then stored in the module. This method of PCB production allows for rapid repairs or prototyping without the need for subsequent resupply missions. By implementing this technique, future missions will achieve greater autonomy, sustainability, and resource efficiency. The goal of this development is to pioneer the creation of custom circuitry for use in deep-space missions where resupply is neither cost-effective nor timely.

Spike Timing Depended Plasticity Produces Unsupervised Learning Of Synergistic Muscle Feedback In A Synthetical Neural Network, Mark Allen Pupkiewicz

Dissertations and Theses

This study investigates how type Ia feedback from muscle spindles can be organized into groups representing agonistic muscle pairs through Spike Timing Dependent Plasticity (STDP). A single degree of freedom joint is actuated with four biologically modeled muscles forming two agonistic pairs. In order to emulate the sensory dynamics of biological muscle spindles, sensors in the model record the active length and velocity states of each muscle, the two primary factors eliciting type Ia afferent responses. In biological networks, synapses from Ia sensory neurons frequently activate interneurons representing agonistic muscle sources. This research investigates whether this organization can emerge in …

Workstation Redesign, Mclean Dowell, Anna Seville, Luz Corral Parra, Farah Talib

Senior Design Project For Engineers

Tellerex is a leading ATM refurbishing and repair company operating from Atlanta, Georgia. Due to its rapid growth, the company is facing challenges pertaining to their parts repair and refurbishing lab. Tellerex aims to fulfill orders by 4:00 pm on the day they are placed, guaranteeing their clients same-day shipping. Orders often build up throughout the day, causing lab technicians to stress, rush through orders, and lose organization.

Tellerex has requested our help regarding one of their repair/refurbishment labs. Our goal is to redesign the lab workspace through human ergonomics and Lean Six-Sigma principles. The company wants us to create …

Collaborative Research: Fair + R: Building The Future Of More Reproducible Water Research Through Community Best Practices, Software Tools, Cohort Building, And Policy Change., James H. Stagge, David E. Rosenberg, Sierra Young

Civil and Environmental Engineering Faculty Publications

This project aims to create a pathway towards a future, ten years from now, when a majority of published research across geosciences is not only FAIR (Findable, Accessible, Interoperable, and Reusable), but reproducible by a third party. Building on the Center for Open Science framework for cultural change, this project is organized around four scaffolded goals: improving infrastructure and tools, building community support, aligning incentives, and minimizing barriers to policy change. We will systematically analyze 300-500 publications from leading hydrology and water resources journal to quantify changes in reproducibility rates since 2017 and identify the tools and practices that best …

Space Agriculture: A Comprehensive Systems-Level Review Of Challenges And Opportunities, Hassan Fazayeli, Aaron Lee M. Daigh, Cassandra Palmer, Santosh Pitla, David Jones, Yufeng Ge

Biological Engineering Faculty Publications

As humanity prepares for prolonged space missions and future extraterrestrial settlements, developing reliable and resilient food-production systems is becoming a critical priority. Space agriculture, the cultivation of plants beyond Earth (particularly on the Moon and Mars), faces a constellation of interdependent environmental, biological, and engineering challenges. These include limited solar radiation, elevated ionizing radiation, large thermal variability, non-Earth atmospheric pressures, reduced gravity, regolith substrates with low nutrient-holding capacity, high-CO₂/low-O₂ atmospheres, pervasive dust, constrained water and nutrient availability, altered plant physiology, and the overarching need for closed-loop, resource-efficient systems. These stressors create an exceptionally challenging environment for plant …

Engr 204 – Electrical Circuits Project Assignment: Exploring A Key Concept From The Textbook, Liubov Kreminska

Open Educational Resources

This assignment requires students to select a major concept from the ENGR 204 Electrical Circuits textbook and explore it through historical research, conceptual explanation, problem-solving, and real-world application. The project is structured to promote understanding through multiple means of representation, engagement, and expression, following Universal Design for Learning (UDL) principles. Students will describe the history and importance of the chosen concept, explain its main ideas using written or visual aids, solve representative and advanced problems related to the topic, and demonstrate how the concept appears in real-world engineering contexts. The submission must include clearly labeled sections, supporting visuals or simulations, …

Engr 204: 8-Week Op-Amp Major Project Series, Liubov Kreminska

Open Educational Resources

This submission outlines a collection of electronic design projects that can be completed within an 8-week timeframe, progressing from beginner-friendly circuits to advanced real-world applications involving op-amp design. Each project includes a week-by-week plan, required equipment, and key technical challenges. Through these projects, students gradually develop competence in signal processing, circuit stability, noise reduction, calibration, filter design, audio electronics, and bio-signal amplification. The structured timeline ensures systematic learning while allowing hands-on experimentation, troubleshooting, and refinement. The projects serve both as academic exercises and as practical foundations for more advanced electronic system design.

Optimizing Xo Throughput At Imerys, Derek Beasley, Brennan Chandler, Baris Erarslan, Cynthia Grogin

Senior Design Project For Engineers

This project is conducted in collaboration with Imerys to optimize the performance of the VSI (Vertical Shaft Impactor) system at their Plant 4 facility, focusing on improving the production of XO, a fine material used in products such as textured coatings, acid neutralization, and water filtration systems. The VSI operates continuously, producing several materials at the Marble Hill, Georgia location, including #1 Chip, #2 Chip, OZ, XO, Z, and 30–50. The main focus of this project is to increase the throughput of XO, as it requires both throughput improvement and product quality consistency to meet growing market demand. Imerys’ quality …

Iphone-Based Image Refocusing, Katie Jeong, Daniel Niu

Electrical and Systems Engineering Capstone Design Projects

In this project, we show that we can change the focus of a picture after we take it by using real optical physics instead of fake software blur. Modern phones try to create “portrait mode” effects, but those results are often not physically correct. Our approach uses multiple photos taken from slightly different positions to figure out the directions that light rays came from in the scene.

To collect the photos, we move an iPhone sideways on a slider in small, precise steps. Since we know exactly how far the phone moved for each picture, we can track how objects …

The Safety Kuznets Curve: Context In Occupational Safety, Andy Knickerbocker

ASEM Capstones

2025 ASEM 620 Capstone Project

The Role Of Artificial Intelligence In Reducing Internet Crimes Against Children, Malyssa Shaw

Student Scholar Symposium Abstracts and Posters

When generative artificial intelligence (AI) first surfaced and broke into the public sphere, my immediate concern was in its development, implementation, and harmful applications. I was not surprised when deepfake technology rapidly advanced alongside these new developments and impacted women and children worldwide. Disproportionately, they have been made victims of intimate media forgery as early as the 1990s, with an unprecedented uptick in recent years as a direct result of these developments. In response, I wrote "Deepfake, Real Harm: Protecting Children in the Age of AI", analyzing data specifically regarding child sexual abuse material (CSAM) created with artificial intelligence while …

Business Financial Information Systems, Lirie Koraqi, James Jolovski Prof.

International Journal of Business and Technology

An information system is a combination of software, hardware, and telecommunication networks to collect useful data, especially in an organisation. Many businesses use information technology to complete and manage their operations, interact with their consumers, and stay ahead of their competition. Some companies today are completely built on information technology.

Well designed and implemented business information systems should provide the information management and outside parties need to make informed and timely decisions about the operating health of the company. Business considers the need to have information available to assess the profitability of a new product they are selling or their …