Digital Commons Network^™

Multiobjective Optimization Framework For Renewable Energy Iot Networks Balancing Security, Energy Efficiency, And Communication Reliability, Muhammad Hjouj Btoush, Ashraf S. Mashaleh, Amjad Gawanmeh

Turkish Journal of Electrical Engineering and Computer Sciences

The deployment of Internet of things (IoT) networks powered by renewable energy sources presents unique challenges in balancing security requirements, energy efficiency, and communication reliability. This paper presents a comprehensive multiobjective optimization framework for secure renewable energy IoT nodes that addresses fundamental trade-offs between these competing objectives. We develop a mathematical model incorporating energy harvesting dynamics, security protocols, and communication performance metrics across various environmental scenarios. The proposed framework employs a modified NSGA-II algorithm to identify Pareto-optimal configurations for different deployment contexts. Through extensive simulation analysis, we demonstrate that hybrid energy sources (solar-wind combinations) with lightweight security protocols achieve optimal …

Predictive Current Control Approach For Grid-Integrated Multifunctional Converter Under Source And Load Disturbances, Ravi Kumar Majji, Tirumalasetty Chiranjeevi, Chilukoti Varaha Narasimha Raja, Nagulapati Kiran

Turkish Journal of Electrical Engineering and Computer Sciences

This paper discusses and presents a model predictive control (MPC)-based predictive current control technique for a solar photovoltaic (PV)-integrated grid system during dynamic operation. This control technique employs extension pq (EPQ) theory to estimate reference currents and utilizes an MPC framework for tracking reference currents. Various MATLAB/Simulink simulations were conducted for solar PV generation (source disturbances) and dynamic loading. The results of the OPAL-RT OP4510 real-time simulation are also presented. A multifunctional grid-integrated converter (MFGC) integrates solar active power into the utility grid while achieving unity power factor, reactive power compensation, current balancing, and harmonic suppression. EPQ optimizes mathematical calculations, …

Machine Learning Assisted Development Of Al0.2cufemnni High Entropy Alloy Through Selective Laser Melting, Hareharen K Mr

Theses and Dissertations

High Entropy Alloys (HEAs) are an emerging class of advanced materials that have gained significant attention due to their exceptional mechanical strength, thermal stability, and structural performance. Unlike conventional alloys based on a single principal element, HEAs are composed of multiple elements in a near-equiatomic ratio. Despite these advantages, designing HEAs with tailored properties is difficult because of the enormous number of possible combinations and the limitations of traditional trial-and-error methods. To overcome these challenges, this study presents a machine learning (ML) based approach to accelerate the design and development of an HEA.

In this work, a newly designed composition, …

Machine Learning Approaches For Predicting Biochemical Oxygen Demand And Ammonium Nitrogen: A Decade-Long Weekly Field Study At A Full-Scale Water Resource Recovery Facility, Hoda Khoshvaght, Ratish Ramyad Permala, Amir Razmjou, Mehdi Khiadani

Research outputs 2022 to 2026

Unlike previous studies that rely on high-frequency (15-min or hourly) datasets, this study is among the first to use low-frequency (weekly) data to evaluate the performance of linear and nonlinear machine learning (ML) algorithms for predicting biochemical oxygen demand (BOD) and ammonium nitrogen (NH4⁺-N) in the primary and secondary treatment effluents from the Subiaco Water Resource Recovery Facility (WRRF) in Western Australia. Various feature selection methods, including filters, wrappers, and embedded methods, were employed to identify the most effective approach that achieves the highest model performance while enhancing computational efficiency. The results demonstrate that a reduced set of …

Feasibility-Aware Deep Reinforcement Learning For Sustainable Timber Procurement Under Hurricane Demand Uncertainty, Jarod Wright

Theses and Dissertations

The timber supply chain connects landowners and mills to provide wood products but faces challenges from stochastic demand, seasonal variations, and disruptions such as hurricanes. Fur- thermore, sustainability concerns like transportation emissions create trade-offs in procurement. This study proposes a feasibility-aware Deep Reinforcement Learning framework for sustainable timber procurement and inventory control under joint demand–hurricane uncertainty. We develop a stochastic mathematical model capturing mill-landowner interactions, seasonal demand, hurricane- driven pricing, and carbon emissions. The problem is formulated as a constrained Markov decision process and solved using Proximal Policy Optimization with a feasibility-enforcing layer. A Mississippi-based case study with 2,100 landowners …

Machine Learning-Based Decision Support Models With Applications In Postsecondary Education, Marco Paolo Anglesio

Theses and Dissertations

This dissertation investigates the deployment of machine learning methodologies in an industrial engineering framework for the development of advanced decision support systems in the context of enrollment management. Drawing on techniques from educational data mining, the research addresses three key phases in the lifecycle of traditional and non-traditional students. First, it analyzes student retention using predictive classification models designed to identify individuals at elevated risk of attrition. Second, it employs temporal convolutional networks for time series forecasting, estimating aggregate enrollment levels over highly variable, finite planning horizons on the basis of partially observed data and using an asymmetric loss function. …

Developing And Evaluating U.S. Army Bridging For Ship Simulation, Jacob C. Hodges

Theses and Dissertations

This research investigates the intricacies of ship simulation and developmental processes for integrating wet gap crossing capabilities into a simulated environment. The US Army Mark III Bridge Erection Boat (BEB) and Improved Ribbon Bridge (IRB) were modeled in commercial off the shelf (COTS) and Government Co-Owned (GCO) navigation software suites to determine their performance capabilities and limitations. Each model was constructed using naval architecture concepts to accurately capture their hydrostatic and hydrodynamic effects before being validated against available performance data and expert elicitation from expert US Army watercraft operators. Models were configured and tested in simulated river flows with current …

The Effects Of Experiential Learning On Engineering Self-Efficacy: A Study Of The Impact Of Inperson And Virtual Internships, Co-Ops, And Research Experiences, Sunny Bharat Patel

Theses and Dissertations

This dissertation examined the relationship between participation in Engineering Learning Experiences (ELEs) and engineering self-efficacy, with particular attention to differences among ELE types (internships, cooperative education, and undergraduate research) and delivery modalities (in-person versus hybrid/virtual). Grounded in social cognitive theory, this study sought to better understand how work-related experiential formats influence students’ confidence in their ability to succeed in engineering tasks and professional contexts. As engineering programs and industry increasingly adopt flexible and technology-mediated environments, examining how these experiences shape beliefs about engineering capability is both timely and necessary. Using a mixed-methods approach, quantitative analyses compared self-efficacy outcomes across students …

Descriptive Analysis Of Career Planning And Industry Insight (Cognitive Component) Among Final-Year Mechanical Engineering Education Students, Fadliyanti Firdausia, Purnomo Purnomo, Eddy Sutadji, Tommy Tanu Wijaya, Muhammad Idris Effendi

Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan

This study aims to analyze the level of understanding of final-year Mechanical

Engineering Education students regarding career planning and industry insight as

cognitive components in preparing for the workforce. The study employed a quantitative

approach with a descriptive method involving 58 eighth-semester students who had

completed industrial internships. Data were collected using a Likert-scale questionnaire

consisting of 20 items on career planning and 18 items on industry insight, and were

analyzed using descriptive statistics, including mean scores and percentages. The results

indicate that students’ understanding of career planning falls into the high category, with

a mean score of 3.78, while …

Trussworthy - A Lunar Module Truss System, Anthony Wehrli, Sebnem Kalayci, Tyler Williams, Sofia Lopez-Linares Perez, Connor Mcdonagh, Presley Robb

Undergraduate Research and Scholarship Symposium

TrussWorthy is a modular truss-based construction platform designed to support the gradual development of sustainable infrastructure on the lunar surface. Aligned with NASA’s Moon to Mars objectives, the system emphasizes in-situ resource utilization (ISRU) by transforming lunar regolith into structural components through sintering and additive manufacturing. By reducing dependence on Earth-supplied materials, TrussWorthy aims to lower launch costs while enabling scalable, long-term construction capabilities. The design integrates autonomous excavation, 3D printing, and robotic assembly, building on technologies expected from upcoming Artemis and Commercial Lunar Payload Services missions. Engineered to withstand extreme thermal cycling, vacuum conditions, and reduced lunar gravity, the …

2025, Significant Natural Disasters And Global Carbon Capture, Utilization, And Storage—Annual Progress Report, Shangli Shi, Yun Hang Hu

Michigan Tech Publications

This annual review summarizes the progress of carbon capture, utilization, and storage (CCUS) technologies in 2025. During this year, the growth rate of atmospheric CO2 concentrations slowed, yet anthropogenic CO2 emissions continued to rise. At the same time, the increasing frequency of severe natural disasters underscored the urgency of climate action and further intensified global efforts to advance CCUS deployment. Scientific interest in CCUS expanded markedly, with the annual number of related publications increasing by 18.5% compared with 2024, reaching 63935. Meanwhile, the total number of operational commercial CCUS facilities worldwide grew by 54%, accompanied by an approximate 25% increase …

Sorption And Thermal Conductivity Of Concrete Containing Aggregates Of E-Waste, Rakesh Kumar Saini, Praveen Kumar

Journal of Sustainable Construction Materials and Technologies

In many parts of the world, substantial energy is used to maintain comfortable temperatures in inner parts of the buildings for living and working. Construction materials with low thermal conductivity, if used in the exterior walls and façade etc. in such structures can be useful in lowering the energy demand. On the other hand, moisture ingress through sorption is a common factor contributing in degradation of concrete structures with time. Constituents of concrete may be engineered to some extent to get both the desired attributes, lower thermal conductivity and sorption than normal concrete. The rapid increase in electronic waste, or …

Thermal Transient Analysis Of Mahogany Wood Biomass Pyrolysis: The Role Of Zeolite Catalyst Variations On Temperature Distribution, Yusri Yusri, Widya Wijayanti, Mega Nur Sasongko

Journal of Mechanical Engineering Science and Technology (JMEST)

Biomass pyrolysis is a thermochemical process that converts waste into fuel. The use of zeolite catalysts can enhance efficiency by accelerating biomass decomposition. To demonstrate its effect, thermal simulations were conducted using ANSYS Thermal Transient to analyze temperature distribution, reaction rates, and catalyst effectiveness in the pyrolysis process. This study aims to improve thermal efficiency and temperature uniformity by analyzing the effect of 10% and 20% zeolite mixtures on heat distribution and heating rates at input temperatures of 650 K, 750 K, and 850 K, using the 2D axial symmetry method. The simulation was performed under specific boundary conditions: input …

The Use Of Tactile Stimulations To Mitigate Somatic Anxiety Responses: A Pilot Study, Abigail C. Robbins

Masters Theses

Anxiety is the body’s response to detected danger or stress. Physiological responses include shallow breathing, increased heart rate, sweating, shaking, and muscle tension. Roughly 33.7% of the population experiences anxiety, with approximately 40 million adults in the United States being affected by the disorder. Anxiety can create severe personal, social, and economic burdens. Traditional treatments of anxiety disorders such as medication and psychotherapy can be effective, but present multiple barriers such as cost, accessibility, and side effects. As a result, there is a growing industry for non-invasive, low-cost solutions that can help individuals regulate their physiological anxiety responses and reduce …

A Review Of Magnesium-Based Stents: Manufacturing Strategies And Future Trends, Amir Motaharinia, Amir Sanati Nezhad, Jeremy Goldman, H. R. Bakhsheshi-Rad, J. Drelich

Michigan Tech Publications

Coronary artery disease is often treated with vascular stents to restore the blood flow. Recently, there has been growing interest in biodegradable metal stents, especially those made from magnesium (Mg). This review starts by explaining the complex pathophysiology of atherosclerosis and the current treatment options. It then discusses stents, including their potential benefits, capabilities, and limitations, as they represent the gold standard for percutaneous coronary intervention in treating atherosclerosis. Given the vital role of stents, we provide a thorough review of the manufacturing techniques involved, such as wire forming, subtractive manufacturing, and additive manufacturing, with a specific focus on stents …

High-Surface-Area Ficus Leaf-Extracted Cuo-Zno-Nio Ternary Nanocomposites For Rapid Adsorption-Assisted Uv-A Degradation Of Direct Blue 15, Kafa’A H. Ali, Mohammed A. Atiya, Ahmed K. Hassan

Karbala International Journal of Modern Science

Direct Blue 15 (DB15) is a long-lasting synthetic dye that pollutes water and is difficult to remove during wastewater treatment. Conventional treatments fail to remove DB15 adequately due to rapid electron-hole recombination, which necessitates photocatalysts with reduced recombination rates for effective dye removal. The study aims to synthesize and evaluate a CuO-ZnO-NiO ternary system as an integrated adsorption and UV-A photocatalysis platform for DB15 removal. Ficus leaf-extracted CuO-ZnO-NiO nanocomposites with four Cu:Zn:Ni ratios (1:1:1, 1:1:2, 1:2:1, 2:1:1) were prepared by co-precipitation, followed by extensive chemical and physical characterization and dye-removal performance measurements. The CuO-ZnO-NiO nanocomposite exhibited hexagonal zinc oxide, cubic …

Fault Location In Dc Microgrids Using Traveling Waves, Sajay Krishnan Paruthiyil

Electrical and Computer Engineering ETDs

In DC power systems, rapid fault location is crucial for maintaining reliable operation, particularly with the prevalence of DC-DC converters. This study investigates fault location techniques in DC systems utilizing Traveling Waves (TWs). Following data normalization, multi-resolution analysis employs discrete wavelet transform to capture high-frequency patterns of TW's wavelet coefficients. Parseval's theorem is utilized to quantify the energy of these coefficients. First, a curve-fitting technique is employed to estimate fault locations in DC microgrids. Then, two transfer learning approaches are proposed: first approach integrates Parseval energy curves into a Gaussian process estimator, while second employs feedforward neural network for fault …

Comprehensive Analysis Of Spray Development And Low Temperature Combustion Characteristics In A Cvcc With Nvh Of Renewable Aerospace Fuels: Hefa & Ft Synthetic Kerosene (S8) Compared To Jet-A & Ulsd, Coleman Norton

Honors College Theses

A comprehensive analysis was conducted to research the viability of Hydroprocessed Esters and Fatty Acids (HEFA) and S8 Synthetic Kerosene fuels as a drop-in replacement for conventional petroleum-based fuels, Jet-A and ULSD (Ultra Low Sulfur Diesel). Global transportation remains heavily dependent on liquid fossil fuels, while renewable aerospace fuels offer a promising pathway to reducing life cycle greenhouse gas emissions and pollution. However, the combustion performance and long-term feasibility of these fuels remain insufficiently characterized. This study performed a thorough assessment of each fuel's thermophysical and combustion properties. Thermophysical characterization encompassed viscosity, freezing point, energy density, spray atomization, and volatility. …

Improving Human Visual Search: Enhancing Lung Cancer Nodule Detection In Medical Images, Christopher Khajira

Masters Theses

Human visual search involves the identification of relevant signals within information-rich environments, which is a fundamental problem in visual perception. While detection accuracy and response time are commonly used to evaluate performance in visual search, these measures do not reveal the underlying cognitive and computational structure that produces observable behavior. A key challenge lies in distinguishing between competing processing architectures, particularly in complex visual domains where different models can produce similar behavioral outcomes. This study addresses this challenge by developing a computational experimental framework for analyzing visual search behavior using System Factorial Technology (SFT). The experimental framework integrates naturalistic medical …

Meeting The Moment With Ai-Employer Informed Education, Brent Terwilliger, John Faraca

Publications

As artificial intelligence transforms aviation, aerospace, and autonomy-related sectors, higher education must adapt to meet evolving workforce demands. This session shares emerging findings from a nationwide study led by Embry-Riddle Aeronautical University, focused on employer perceptions of AI adoption, responsible use, and workforce preparedness in domains including uncrewed systems, space systems, robotics, and advanced air mobility. Based on a structured survey and follow-up interviews, the presentation explores how organizations are using AI tools, from generative platforms to enterprise systems, and defining effective and inappropriate use in operational contexts. Participants will gain insight into critical concerns (e.g., data privacy, compliance, security, …

Karstic Cavities Underground Investigation: Gpr And Geotechnical Data Correlation, Mehrez Jamei, Mabrouk Abdelkader, Anwar Ahmed, Yahya Alassaf

Journal of Sustainable Mining

This paper focuses on the methodology involving ground penetration radar (GPR) for detecting and localizing random cavities in underground limestone soil, in conjunction with geotechnical data. A GPR survey was conducted alongside field and laboratory geotechnical tests at a field where mining activities are now promoted (Saudi Arabia Northern Borders Province). The paper presents correlations between the instantaneous amplitude of the reflected electromagnetic (EM) waves and rock quantification distributed (RQD), recovery rock parameter (REC), and uniaxial compressive strength (UCS). The GPR investigation proved to be an efficient nondestructive geophysical method for determining: 1) the …

Scalable Advanced Control Of Building Hvac Systems Using Physics-Informed Machine Learning, Xuezheng Wang

Dissertations - ALL

Buildings account for approximately 40% of total energy consumption in the United States, with HVAC systems representing the single largest energy end-use. Advanced control strategies such as model predictive control (MPC), reinforcement learning (RL), and differentiable predictive control (DPC) have demonstrated significant energy savings in individual studies, yet their widespread adoption remains limited by the lack of scalable, control-oriented dynamic models, the absence of consensus on control strategy selection, and the gap between single-zone research and multi-zone real-building deployment. This dissertation addresses these barriers through an integrated research program spanning physics-informed machine learning (PIML) model development, advanced control evaluation, and …

Incorporating Sustainable Strategies And Practices Into The City Improvements Plan Of Madisonville, Kentucky To Better Suit It For The Changing World, Cade R. Howell

Honors College Theses

This project aims to make the case for city improvements in Madisonville, Kentucky by using successful strategies implemented by other cities across the region. These strategies include sidewalk improvements, the installation of roundabouts and parking garages, increased walkability and beautification, and a restructuring of the types of cars predominantly used in the area. The strategies would be implemented from least expensive to most expensive, and in a way that gets the communities involved as much as possible. By using these strategies, Madisonville can better prepare itself for a more sustainable future.

Beyond Accuracy: Machine Learning Models For Predicting Presence Of Permanent Molar Caries In U.S. Children And Adolescents With Fairness Consideration, Pritam Deb, Lin Li, Christina R. Scherrer

Faculty Articles

Background

Although predictors of dental caries have been previously explored, a comprehensive understanding of factors influencing permanent‐molar decay in U.S. children and adolescents, especially with respect to racial and ethnic biases remains limited. This study aims to develop and evaluate machine‐learning (ML) models incorporating algorithmic fairness to predict caries in permanent molars.

Methods

Data from the National Health and Nutrition Examination Survey (NHANES) were analyzed, using the 2011–2014 cycles for training and validation and the 2015–2016 cycle for testing. The primary outcome was decayed, missing, and filled teeth (DMFT) in at least one permanent molar, dichotomized to represent the presence …

Manufacturing Process Of A Wooden Tortilla Press: Idea To Production, Olivia R. Marque

Honors Theses

The purpose of this thesis is to document the design, development, and manufacturing of a wooden tortilla press completed as a capstone project through the Center for Manufacturing Excellence (CME). Following the technical details of this thesis is a personal reflection by one team member, Olivia Marque. The project follows a structured product development process that begins with problem definition and concept development, progresses through design, prototyping, and jig fabrication, and culminates in a full production run on the CME shop floor. A multidisciplinary team, including engineers, a marketer, and an accountant, collaborates throughout the project to support both technical …

Designing A Wearable Gait Feedback System For Parkinson’S Disease Patients, Heath M. Stevens, Capri H. Lobotzke, Spencer J. George

Honors Theses

Parkinson’s disease is a progressive neurological disorder that commonly causes a shortened stride length, reducing mobility and increasing fall risk. While current treatments, such as oral medication, can reduce symptoms, they do not provide real-time feedback to correct gait and often result in “off” periods when symptoms return. Physical therapists report that simple reminders to lengthen stride can help patients recover from “off” periods and maintain normal walking patterns, but there is no current at-home way to simulate this effective therapy. Recognizing this gap in at-home support, our biomedical engineering senior design team at the University of Mississippi sought to …

Manufacturing Of A Wooden Tortilla Press: Idea To Production, Glenn H. Walker

Honors Theses

The purpose of this thesis is to document the design, development, and manufacturing of a wooden tortilla press completed as a capstone project through the Center for Manufacturing Excellence (CME). The project follows a structured product development process that began with problem definition and concept development, progressed through design, prototyping, and jig fabrication, and culminated in a full production run on the CME shop floor. A multidisciplinary team, including engineers, a marketer, and an accountant, collaborated throughout the project to support both technical development and manufacturing execution. Project planning and scheduling were established early and maintained throughout the project to …

Manufacturing Process Of A Wooden Tortilla Press: Idea To Production, Colleen Nolan, Ben Bird, Olivia Marque, Emma Palmer, Hayden Walker

Honors Theses

The purpose of this thesis is to document the design, development, and manufacturing of a wooden tortilla press completed as a capstone project through the Center for Manufacturing Excellence (CME). The project follows a structured product development process that began with problem definition and concept development, progressed through design, prototyping, and jig fabrication, and culminated in a full production run on the CME shop floor. A multidisciplinary team, including engineers, a marketer, and an accountant, collaborated throughout the project to support both technical development and manufacturing execution. Project planning and scheduling were established early and maintained throughout the project to …

Designing A Collaborative Uav-Ugv System For Autonomous Challenge Completion, Ember Reysen

Honors Theses

The coordination between Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs) holds significant potential for completing complex tasks such as disaster response and construction surveillance by leveraging the strengths of aerial flight and stable on-ground transportation. Unfortunately, coordination between UAVs and UGVs is extremely complex and task-dependent, leading to limited understanding of autonomous collaboration. This thesis explores the process of designing an UAV-UGV collaborative system capable of aerially scouting a target destination, relaying its coordinates to a ground vehicle, and performing a precision landing for unison travel. I utilize computer vision techniques via OpenCV for target marker identification, ROS …

Development Of A Putting Green Manufacturing Process, Tabitha R. Webster

Honors Theses

Our Capstone project investigates the end to end design, development, and production of a 6‑foot long portable putting green marketed for individuals seeking a high quality, competitively priced golf product for home or office use. The capstone project examines the full lifecycle of product creation applying manufacturing principles learned through the center of manufacturing’s coursework. From the initial concept through engineering design, market research, prototyping, manufacturing optimization, and final production the project emphasizes cross‑functional collaboration across engineering, business, and accountancy majors. Methods used to gather data included marketing surveys, CAD drawings, time studies during production runs, value stream mapping, and …