Engineering Commons^™

Ai Photography-Based Gradation Feasibility Study For Streams And Rivers In Davidson County, Tn, Nolen Ritzel, Lauren Baker

Student Scholar Symposium

Artificial Intelligence (AI) has demonstrated significant potential in engineering applications, specifically in soil gradation analysis using two-dimensional imagery. While studies have shown experimental success, AI-based soil gradation methods are not widely used in industry due to the lack of field research performed. Moreover, the current methodology is suitable but lacks advancement. The motivation behind the research was to aid in bridging this gap between experimental research and industry application by determining whether existing AI tools can and/or should be applied to bank soil in streams and rivers in the Greater Nashville Area. Several locations next to streams and rivers distributed …

Exoskeleton Senior Design Project, Joel Isaacson, Josh Brake, Barre Seguin, Lydia Tollerson, Rachel Mayhugh, Richard Pearce

Student Scholar Symposium

In recent years, the demand for wearable technology has grown significantly, driven by advancements that allow electronics to become increasingly compact. Among these innovations are exoskeleton suits, which enhance user strength, reduce fatigue, and help prevent injuries. This project explores the capabilities of exoskeletons in augmenting human strength. Specifically, we developed an exoskeleton arm designed to rotate a valve 360 degrees using a torque wrench set to 150 ft-lbs.

Xibalbay, Guatemala Water Distribution System Design, Nolen Ritzel, Lauren Baker, Robert Trey Owen, Jessamine Reckard, Joelle Noble, Sara Berry-Brown

Student Scholar Symposium

This study presents the design and validation of a water distribution system for Xibalbay, Guatemala, in collaboration with the Peugeot Center and a local Guatemalan engineering firm, ADICAY. The project aimed to ensure reliable water access while maintaining residual pressures to the US standard, between 20 to 120 psi. The proposed design was a two pressure-zone system with pumps in series. A comprehensive hydraulic model was developed using WaterGEMS to analyze system pressures, pump performance, and tank levels under various conditions. Limited on-site testing was performed by this team due to construction delays and electricity issues at the time of …

Investigating The Impact Of Humanitarian Engineering Projects Across Demographic Groups, René Marius, Ruth Fessehaye

Student Scholar Symposium

This poster presents a statistical analysis of a research project studying the impact of humanitarian engineering projects (HEPs) on the views of diversity, equity, and inclusion (DEI). The authors aim to investigate the deeper effects of HEPs across engineering students, alumni, and professionals. Data from participants were gathered through a survey, using both qualitative and quantitative methods, to assess participants’ attitudes toward DEI in engineering.

The survey included two instruments: the Engineering Professional Responsibility Assessment (EPRA) and the Views on Diversity, Equity, and Inclusion in Engineering (VDEIE). The EPRA measured participants’ perspectives on professional responsibility, while the VDEIE focused on …

Blast Resistant Structure, Juan Henriquez-Hernandez

Student Scholar Symposium

No abstract provided.

Fasttree-Guided Genetic Algorithm For Credit Scoring Feature Selection, Rashed Bahlool, Nabil Hewahi Prof., Youssef Harrath Dr.

Research & Publications

Feature selection is pivotal in enhancing the efficiency of credit scoring predictions, where misclassifications are critical because they can result in financial losses for lenders and exclusion of eligible borrowers. While traditional feature selection methods can improve accuracy and class separation, they often struggle to maintain consistent performance aligned with institutional preferences across datasets of varying size and imbalance. This study introduces a FastTree-Guided Genetic Algorithm (FT-GA) that combines gradient-boosted learning with evolutionary optimization to prioritize class separability and minimize falserisk exposure. In contrast to traditional approaches, FT-GA provides fine-grained search guidance by acknowledging that false positives and false negatives …

Cybernest: A Step Forward For Training Cybersecurity Professionals, Justin Mott

Theses and Dissertations

The growing complexity of cyber threats has exposed a critical gap between academic cybersecurity education and the operational demands of the workforce. This thesis presents a pilot study for a use-case of CyberNEST, a simulation-based training platform that integrates adversary emulation and threat-informed learning to create realistic, hands-on experiences for cybersecurity students.(17) The system was designed to replicate Security Operations Center (SOC) environments and incident response workflows, allowing participants to investigate, analyze, and respond to simulated attacks under authentic conditions. This pilot-study performed training simulations using the CyberNEST platform, developed by Brigham Young University, with students, collecting data from pre- …

Power Solutions For Large Loads: Mastering Electrical Supply For New Industrial Facilities, Chris Boyer, William Bourgeois, Skyler Bryant

Mavs Open Press Open Educational Resources - Archive

The next 25 years will see unprecedented growth in U.S. electricity demand, driven primarily by data centers for AI and industrial electrification. This surge presents unique challenges for power generation, especially for large loads requiring hundreds of megawatts to gigawatts from a single location. Conventional grid expansion is inadequate, prompting the need for innovative, flexible, and sustainable solutions. This book explores the opportunities, challenges, and hybrid generation strategies to support the evolving landscape of large-scale electric loads.

Integration Of Renewable Energy Networks Into Smart Grid Infrastructure: A Matlab/Simulink-Based Simulation Approach, Saturday Noghayin Osaretin

Electrical Engineering Theses

The rising demand for sustainable and resilient energy systems has accelerated the transformation from traditional power grids toward smart grids integrated with renewable energy networks. This thesis explores the integration of solar energy sources into smart grids to replace conventional fossil-fuel-based generation. A simulation model is developed using MATLAB/Simulink to evaluate the operational performance, stability, and adaptability of the proposed smart grid architecture. Key challenges, including intermittency, synchronization, and bidirectional power flows, are identified, and corresponding solutions, such as energy storage systems, are proposed to address these issues. Simulation results demonstrate enhanced grid stability, reduced carbon footprint, and improved power …

A Comprehensive Review Of Dental Diseases Detection And Classification Based On Artificial Intelligence Techniques, Nermeen N. Noaman, Yasmin M. Alsakar, Naira E. Elazab, Waleed M. Mohamed, Mohamed E. Ezzat, Mohammed M. Elmogy

Mansoura Engineering Journal

In dentistry, many diseases, such as gum, cavities, and oral cancer, affect people of all ages. Early treatment and diagnosis are crucial for minimizing dental diseases' effect on overall health and saving money in the long run. Traditional dental diagnosis methods, such as manual probing and visual inspection, are time-consuming and can be subject to human errors. Hence, a computer-aided diagnosis system based on computer vision and artificial intelligence (AI) techniques is needed. The considerable progress in computer vision and AI techniques offers many possibilities in dental diagnosis based on dental X-ray imaging modalities. Dental X-rays are used to diagnose …

Evaluating Traffic Safety And Geometric Characteristics Using Machine Learning Ensemble Techniques: A Case Study Of Egyptian Rural Multi-Lane Divided Roads, Sania R. Elagamy, Ahmed N. Awaad, Usama E. Shahdah, Sherif M. El-Badawy, Marwa E. Elbany, Eman K. Ali

Mansoura Engineering Journal

Crash prediction models are essential for evaluating traffic safety by analyzing crash occurrence, frequency, or severity. Recently, machine learning techniques have gained prominence in statistical regression modeling and data analysis. This study assesses the effectiveness of machine learning in predicting crashes on Egyptian rural multi-lane divided roads using limited regional data. Supervised machine learning ensemble techniques were applied to predict crash-prone segments (classification) and estimate the total number of crashes per segment (regression). A comparative analysis aims to identify the most suitable method. The Synthetic Minority Oversampling Technique (SMOTE) addressed data imbalance, while K-means Clustering (KC) enhanced regression model accuracy, …

Geolocation Algorithms And On-Orbit Calibration For Atmospheric Waves Experiment, Eric Mckinney, Keith Blonquist, Zack Hatfield, Connor Waite, Brooke Wursten, Pedro Sevilla, Ludger Scherliess, Harri Latvakoski, Greg Cantwell

Space Dynamics Laboratory Publications

1 - Overview

• Motivation: Atmospheric gravity waves can degrade navigation, tracking, communications, and geolocation system signals. They can also affect satellite/debris orbit and reentry predictions.
• NASA's Atmospheric Waves Experiment (AWE) is currently on ISS measuring atmospheric gravity waves in the OH airglow layer at ~87 km altitude
• Impact: Improved space weather understanding, estimation, and forecasting

Hybrid Machine And Deep Learning Framework For Secure Fog-Based Vanets, Hadeer Kamal, Amira Y. Haikal, Mahmoud M. Saafan

Mansoura Engineering Journal

As a conventional implementation of intelligent transportation systems (ITS), a Vehicular Ad-hoc Network (VANET) facilitates smart communication between vehicle nodes and network infrastructures. Nevertheless, the distributed and dynamic characteristics of VANETs make them vulnerable to numerous cyberattacks like DOS and spoofing. Rapid detection of these threats is crucial. It is essential to respond promptly to mitigate threats before they impact vehicle coordination or infrastructure functionality. In this context, fog computing presents an effective solution. Transferring computational tasks from centralized cloud servers to fog nodes allows for quicker detection within the VANET environment. This research utilizes computational resources for swift and …

Integration Of Algae In Buildings: Challenges And Opportunities, Marwa Said Saad, Mostafa Refaat, Ashraf Nessim

Mansoura Engineering Journal

Buildings produce 40% of energy-associated CO2 emissions and 35% of worldwide energy use which makes it one of the main factors of global warming. The use of bioactive materials on building façades is a creative way to address the aforementioned problems. The biotechnical potential of microalgae architecture to achieve net-zero energy architecture while simultaneously advancing ecological sustainability and occupant well-being has drawn attention. This paper aims to analyzing and investigating techniques of integration of algae in architecture showing the challenges and opportunities of this implementation. Analytical and Comparative analytical method were used in this paper, Initially, a thorough literature review …

Integrating Multimodal Analysis For Chemical Detection In Victorian Bookcloth: Correlations, Advantages, And Limitations, Leila Ais, Abigail L. Hoermann, Jafer Aljorani

Student Scholar Symposium

The detection of heavy metals in Victorian textiles presents a set of unique analytical challenges that cannot be addressed through usage of a single modality. Here, we detail a novel multimodal analytical approach that integrates distinct yet complementary instrumentation: inductively coupled plasma-optical emission spectroscopy (ICP-OES) offering precise quantitative elemental analysis, portable X-ray fluorescence (pXRF) enabling rapid, affordable, and non-destructive detection, electron dispersive spectroscopy – scanning electron microscopy (EDS-SEM) mapping elemental distributions and sample topography, and X-ray diffraction (XRD) revealing crystalline structures. This comparative study highlights the strengths and limitations of each analytical technique, demonstrating how their combined use provides a …

Evaluating The Impact Of Precast Vs. Cast-In-Place Concrete: A Life Cycle Assessment Of A Parking Garage In Nashville, Robert Trey Owen

Student Scholar Symposium

Concrete is one of the most widely used building materials in the construction industry, generating $64 billion in revenue, according to the Concrete Financial Insights Index. Given the material’s extensive use, construction professionals seek ways to optimize construction project budgets and schedules. Precast concrete, which is manufactured offsite and then transported to the project when needed, is a potential solution for these goals. This research aims to quantify the benefits of precast concrete over typical cast-in-place methods using a life cycle analysis for a parking garage structure located in Nashville Tennessee.

The data for the two materials will be compared …

Making Robotic Reinforcement Learning More Efficient: Analyzing The Serl Framework, Faris Jugovic, Cleiver Ruiz-Martinez, Ryan Vander Stelt

Student Scholar Symposium

Teaching robots through reinforcement learning (RL) has made great progress, but real-world training is still difficult. Robots need lots of practice to learn, rewards can be hard to define, and resetting the environment after each attempt is often a challenge. The Sample-Efficient Robotic Reinforcement Learning (SERL) framework helps solve these issues by offering a ready-to-use, open-source software package that makes RL more practical for real-world robotics.

This project explores SERL and how it improves robotic RL by making learning faster and more efficient. SERL includes smarter ways to reuse training data, automatic methods for understanding rewards from images, and a …

Improving Home Affordability In Greater Nashville Through Construction Efficiency And Innovations, Nate Mclain

Student Scholar Symposium

Engineering Greater Nashville Home Affordability

Long Term Financial Analysis For Opry Mills Hotel And Resort, Eli Lockert

Student Scholar Symposium

In 2024 a Lipscomb Senior Design team completed a design project for the Opryland Hotel. The project, aimed at reducing humidity levels in the large greenhouse-like atrium and overall power usage, included multiple phases and equipment. This research continues the work of that team in an effort to determine whether the proposed system is a cost-effective approach. The research specifically evaluates the system outlined in the Opryland Final Design Report, completed in April of 2024. Using a holistic approach, this study employs life-cycle cost analysis (LCCA) to assess the economic feasibility of the proposed system through various empirical methods. A …

Nazi Weapons: Bad People, Good Technology, Fabian Grabski

Undergraduate Research Symposium

This project explores the integration and historical significance of three iconic World War II-era German weapons: the V-2 rocket, the STG-44, and the MG-42. Each of these weapons helped revolutionized military technology in its own right, reshaping the battlefield dynamics and influencing future weapon design. The V-2 rocket, as one of the first long-range guided missiles, marked the dawn of modern missile technology, while the STG-44 is recognized as a precursor to the modern assault rifle, blending the characteristics of both submachine guns and rifles. The MG-42, with its high rate of fire and advanced design, set the standard for …

Optimization Of Research Pipeline To Characterize The Effects Of Atp-Sensitive Potassium Channels Mutations On Native Skeletal Muscle Fibers And Evaluate Potential Drug Therapy, Yuezhou Chen

McKelvey School of Engineering Graduate Student Theses & Dissertations

The ATP-sensitive potassium (KATP) channel is a critical metabolic sensor in skeletal muscle, yet its definitive molecular composition and functional roles remain contested. In this study, I conclusively demonstrate that the Kir6.2/SUR2 complex forms sarcolemmal KATP channel in mouse fast-twitch muscle. Genetic knock-out (KO) of Kir6.2 (Kcnj11−/−) or SUR2 (Abcc9−/−) resulted in a similar phenotype with increased fatigue resistance and a pathological rise in unstimulated resting tension at high-frequency stimulation. In contrast, SUR1 (Abcc8−/−) KO was ineffective. Furthermore, a CRISPR/Cas9 knock-in mouse model of a human SUR2A truncation variant (KCGV/KCGV) recapitulated the abnormal force accumulation, demonstrating that even loss-of-function of …

Development Of A Multispectral Collagen Detection Dermatology Device For Delineation Of Non-Melanoma Skin Cancers, Anmol Jarang

McKelvey School of Engineering Graduate Student Theses & Dissertations

To diagnose and manage skin disease, clinicians primarily use visual inspection aided with dermatoscopes, which are cross-polarized magnifiers. In recent years, digital cross polarized multispectral imaging systems have been developed to quantitatively assess skin disease. For example, systems like the one developed by Yaroslavsky et al., which utilize red and blue filters, can non-invasively assess the collagen network in the dermis(Yaroslavsky et al., 2003). Visualization of collagen network disruption can make it easier to visualize the boundaries of skin cancers like keratinocyte carcinoma, and therefore easier to excise completely. Current systems use external bandpass filters in front of cameras to …

Enhancing Aerosol Scattering Measurements: Performance Evaluation And Quality Assurance Of Airphoton Integrating Nephelometers In The Surface Particulate Matter Network, Kamlendra Singh Pathak

McKelvey School of Engineering Graduate Student Theses & Dissertations

Integrating nephelometers are key instruments for quantifying aerosol light scattering, a fundamental parameter governing the direct radiative effect of aerosols on climate and visibility, and for interpreting satellite observations of aerosol optical depth. The AirPhoton integrating nephelometer quantifies aerosol light scattering by measuring total scattering from the sample air and subtracting a clean-air reference that represents Rayleigh scattering, instrument wall scattering, and detector background noise. Measurement accuracy depends on rigorous calibration and regular performance evaluation to account for instrumental drift and environmental influences. This study presents a field performance evaluation of the AirPhoton integrating nephelometer within the global Surface Particulate …

Expansion Limits Of Meshed Split-Thickness Skin Grafts, Haomin Yu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Split-thickness skin grafts are widely used to treat chronic wounds. Procedure design requires surgeons to predict how much a patch of the patient's own skin expands when it is meshed with rows of slits and stretched over a larger wound area. Accurate prediction of graft expansion remains a challenge, with current models overestimating the actual expansion, leading to suboptimal outcomes. Inspired by the principles of mechanical metamaterials, we developed a model that distinguishes between the kinematic rearrangement of structural elements and their stretching, providing a more accurate prediction of skin graft expansion. Our model was validated against extensive data …

Integrating Large Language Models And Single-Cell Omics Analysis For Target Discovery In Pancreatic Ductal Adenocarcinoma, Zixi Xu

McKelvey School of Engineering Graduate Student Theses & Dissertations

The elucidation of cell-type–specific signaling networks is central to understanding pancreatic ductal adenocarcinoma (PDAC) and to nominating mechanistically grounded therapeutic targets. We present a Text-to-Target framework that integrates large language models (LLMs) with single-cell omics to couple literature-derived hypotheses to cell-type–resolved expression evidence. Using publicly available datasets, we construct malignant ductal epithelial and lineage-matched acinar meta-cell cohorts from PDAC and perform differential expression analysis to obtain a robust catalogue of disease-associated transcriptional changes. In parallel, an ensemble of LLMs is prompted in a schema-constrained manner to retrieve cell-type–specific targets, pathways, and mechanistic annotations from the biomedical literature. After normalization and …

Implementing Controls To Mitigate The 2013 Target Data Breach: A Cost Benefit Analysis, Pricilia R. Fajong

Dissertations, Theses, and Projects

In 2013 Target had a data breach, which compromised 40 million credit/debit card accounts and 70 million customer records. The attackers exploited a vulnerability in a third-party vendor (Fazio Mechanical Services), to gain access to Target's systems. The breach cost Target over $250 Million (USD) in legal fees, investigation expenses, and reputational damage (Jones, 2025). Based on inflation rate, the 2013 Target data breach would cost over $340 Million (USD) today. In this study, a cost-benefit analysis was done to determine whether it would have been more cost-effective for Target to have invested in security controls rather than paying for …

Comparative Analysis Of Machine Learning And Statistical Models For Railroad–Highway Grade Crossing Safety, Erickson Senkondo, Deo Chimba, Masanja Madalo, Afia Yeboah, Shala Blue

Civil and Architectural Engineering Faculty Research

Railroad-highway grade crossings (RHGCs) are critical points of conflict between roadway and rail systems, contributing to over 2000 crashes and 250 fatalities annually in the United States. This study applied machine learning methods (ML) techniques to model and predict crash frequency at RHGCs, using a comprehensive dataset from the Federal Railroad Administration (FRA) and Tennessee Department of Transportation (TDOT). The dataset included 807 validated crossings, incorporating roadway geometry, traffic volumes, rail characteristics, and control features. Five ML models—Random Forest, XGBoost, PSO-Elastic Net, Transformer-CNN, and Autoencoder-MLP—were developed and compared to a traditional Negative Binomial (NB) regression model. Results showed that ML …

Construction Of A Unified Knowledge Graph For Cyber Threat Intelligence, Moaz Usama Hassan Mr, Khaled , Nagaty, Noura Elmaghawry

Computer Networks

The rapid expansion and variety of cyber-threat information put enormous pressure on security operations centers (SOCs) that must convert unstructured data into understandable signals and make decisions upon it. This paper develops a Cyber-Threat-Intelligence (CTI) framework that integrates vulnerability information, product inventories, and weakness taxonomies into a domain-specific knowledge graph via automatic fusing. The proposed solution covers 284,296 CVEs, 101,644 CPE identifiers, and 965 CWE weaknesses, generating more than 800,000 typed edges linking threats, assets, tactics, and mitigations in an integrated CTI Knowledge graph. The graph was cross validated against four external standard datasets achieves full coverage of ATT&CK CAPEC, …

Evaluating The Performance Of The Primary Heat Exchanger In A Sco2 Brayton Cycle While Firing Solid Fuels, Brian Jeffrey Schooff

Theses and Dissertations

The sCO2 closed-loop Brayton cycle is an alternative to the standard steam-Rankine cycle for generating electrical power from a heat source. The sCO2 Brayton cycle is advantageous because it can be more efficient, use less water, and have smaller turbomachinery than the steam-Rankine cycle. While there are several research groups advancing the technology necessary to utilize the sCO2 Brayton cycle on an industrial scale, none of these groups use solid fuel combustion as the heat source. A Brigham Young University-led project developed and tested a pilot-scale sCO2 Brayton cycle unit (1.6 MWth) using natural gas, pulverized coal, and pulverized biomass …

Fpga-Accelerated Computational Photon Counting, Chibueze Onyeador

McKelvey School of Engineering Graduate Student Theses & Dissertations

Fluorescence Lifetime Imaging Microscopy (FLIM) is a powerful tool for biomedical re- search. It leverages fluorescence of biological samples to visualize and characterize biological dynamics and molecular interactions. FLIM utilizes fluorescence lifetime, the average time a molecule stays in its excited state after absorbing a photon, to investigate the dynamics of biological samples.

Ultra-fast and precise (ps-ns) timing fluorescence acquisition techniques suffer from different trade-offs. Some methods suffer from high dead times, decreased accuracy in fluorescence lifetime calculations, and high data volumes and transfers. Finding a new method that can provide the best performance while experiencing low dead times, adequate …