Engineering Commons^™

Research Days: Case Study: Creation Of A Student-Driven Radio Talk Show To Answer Cybersecurity Questions And Concerns To Boost Power Skills, Joel Leiva, Anthony Bayate, David Abiandu, Keith Fernandez

Center for Cybersecurity

Power skills are essential in any professional career. Oftentimes, college students don’t feel prepared enough to enter the workforce. Having good power skills in a group can greatly increase production and efficiency. This case study aims to develop these power skills in a group of college students through the creation of a student-driven radio talk show answering cybersecurity questions and concerns. A qualitative approach was used via the creation of the C.Y.B.E.R. radio show. This show enhanced the participants’ power skills such as collaboration, teamwork, and communication skills. The findings from this case study prove the alternate hypothesis of boosting …

Adopting Zero Trust Security In Cloud: A Comparative Study, Landy Jimenez

Center for Cybersecurity

Adopting Zero Trust Security in Cloud: A Comparative StudyLandy Jimenez, Dr. Jiaxin LeiDepartment of Computer Science & Technology, Kean UniversityAbstract:As organizations transition to cloud-native environments, ensuring security across distributed systems has become more difficult. Modern cyberthreats like insider breaches and lateral movement attacks have shown that traditional perimeter-based security strategies, which rely on implicit trust within internal networks, are inadequate. Zero Trust Architecture (ZTA) addresses these challenges by requiring continuous authentication, authorization, and encryption for every access request, regardless of network location. However, cloud native Zero Trust presents concerns about scalability, latency, and resource overhead.This study evaluates Zero Trust at …

The Impact Of Ai Ethics Education On Student Engagement And Ethical Perspectives, Diana Medina

Center for Cybersecurity

Artificial Intelligence (AI) has become a cornerstone of technological innovation. The world has come to see the many advancements AI has to offer and the impact it has on everyday life. The benefits of AI are promising, and institutions are learning how to implement AI to further advance productivity and efficiency. However, AI-based products may produce harmful or unjust consequences, especially when ethical considerations are not deliberated during the developmental stages. This study investigates student engagement and examines the impact in infusing ethical reasoning in AI education. With five participating computer science professors and two historians, ethics modules were introduced …

Stamp-V: Steganographic Traceability For ​ Ai-Generated Images With Multimodal Verification, Xinlei Guan, David Arosema, Tejaswi Dhandu, Meng Xu, Kuan Huang, Tida Umamheswara Rao, Bingya Shen

Center for Cybersecurity

The rapid growth of generative AI has intensified challenges in content moderation and digital forensics, particularly when benign AI-generated images are paired with harmful or misleading text. This contextual misuse undermines traditional moderation systems and complicates attribution, as synthetic images typically lack persistent metadata or device signatures. We introduce STAMP-V, a steganography-enabled provenance framework that embeds cryptographically signed identifiers into images at creation time and verifies provenance through multimodal harmful content detection. Our system evaluates five watermarking methods across spatial, frequency, and wavelet domains, and integrates a CLIP-based fusion model that performs multimodal harmful-content detection as part of the provenance …

Control And Stability Analysis Of Three-Phase Grid-Connected Inverters In Renewable Energy Systems, Yasser Ayeva

Electrical Engineering and Computer Science Faculty Publications and Presentations

The increase in demand for renewable energy sources such as solar and wind systems has led to widespread use and integration of a three-phase grid connected inverters in electric modern electric power systems. The inverters are essential to convert DC power into AC power and to control the delivered power to the grid. However, the use of the inverters in a renewable energy system has some challenges related to stability and control due to the presence of power electronic interfaces and filter dynamics. This paper analyzes the control and stability of three phase grid connected inverter through an LCL filter. …

A Software-Defined Radio Testbed For Mimo-Ofdm Communications, Chaz G. Maschman

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

In this thesis, we implement a testbed for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems via GNU Radio. Specifically, we implement a configurable framework for the construction of MIMO-OFDM software-defined radio (SDR) systems as a GNU Radio module. The GNU Radio MIMO-OFDM module consists of multiple algorithmic blocks necessary for implementation of a MIMO-OFDM system. This includes a library for the generation of orthogonal or pseudo-random pilot sequences, amendments to the Schmidl-Cox protocol for MIMO synchronization, and the creation of click-and-drag GNU Radio blocks implementing the conversion of arbitrary data sent via external programs to MIMO-OFDM frames, the initial …

Analysis Of Live Load Distribution Factors In Prestressed Concrete Girder-Bridges With Asymmetric Losses In Prestressing Strands, Mohamed T. Elshazli, Mohamed Elgawady, Ahmed Ibrahim

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Asymmetric loss of prestressing strands in concrete bridge girders presents a critical yet underrecognized threat to structural integrity, particularly in exterior girders subjected to impact or localized deterioration. This form of localized and unbalanced damage leads to eccentric reductions in prestressing force, rotation of the principal axis, and diminished flexural capacity, effects not explicitly addressed in current design standards such as the AASHTO LRFD Bridge Design Specifications. This study presents a comprehensive numerical investigation into the structural implications of such asymmetric damage, focusing on its effect on live load distribution factors (LLDFs) across prestressed girder bridges. A parametric study of …

Comparative Numerical Analysis Of Lead-Free Perovskite Solar Cells Using Scaps-1d, Md Shazarul Islam, Md Abdul Kuddus Sheikh, Hasina Huq

Electrical and Computer Engineering Faculty Publications

A comprehensive numerical study of lead-free perovskite solar cells was conducted using the SCAPS-1D simulation framework with the device architecture ITO/SnO2/Perovskites/NiOx/Au. The work investigates the replacement of the central Pb cation with Sn, Ge, and Bi, followed by absorber-layer thickness optimization to enhance device performance. The impact of systematic Pb substitution on key photovoltaic parameters was first evaluated. Among the candidates, FASnI3-based devices exhibited the most promising performance, achieving a power conversion efficiency (PCE) of 26.48%, with a short-circuit current density (Jsc) of 19.31 mAcm-2, an open -circuit voltage (Voc) of 1.57 V, and a fill factor (FF) of 87.29%. …

Aiw26s: Machine Learning Of Structured Data, Moumita Saha

Paul English Applied Artificial Intelligence (AI) Institute Publications

This workshop introduces the fundamentals of machine learning for structured data, focusing on tabular datasets and real-world applications. Participants explore key concepts such as data types, data preprocessing, feature engineering, and supervised learning methods. The session covers commonly used models, including linear regression, logistic regression, decision trees, and neural networks, along with evaluation metrics such as RMSE, accuracy, and confusion matrices. By the end of the workshop, participants will have gained a practical understanding of how to build, interpret, and evaluate machine learning models for structured data.

Active Listening And Reassurance In Text-Based Virtual Health Coaches, Ghulam Hussain

Dissertations

Conversational agents (CAs) have strong potential to support health and physical wellbeing through text-based coaching, but they remain limited in their ability to demonstrate supportive social behaviours that are important in human coaching interactions. In particular, relatively little is known about how Active Listening and Reassurance are perceived, modelled, and evaluated in text-based virtual healthcare coaching, or how such behaviours should be adapted to individual users.

This dissertation investigates how supportive interaction behaviours can enhance text based virtual health coaching, with an initial focus on Active Listening and Reassurance and a later theoretical emphasis on Active Listening. Across five unique …

From Our Stories, To Our Streets (Osos), Jennifer Lopez

Student Publications

Youth traffic safety persists as a critical planning challenge and public health concern in New Mexico, where pedestrian fatality rates consistently rank among the highest in the United States (National Highway Traffic Safety Administration, NTSA, Governors Highway Safety Association, GHSA, 2023; Baca, 2025). Students (children), due to their daily interactions with roadways, whether when they walk, bike, ride transit, or drive/get driven to and from school, are among the most vulnerable groups within the transportation system (Ferenchak, N. Wesley, M., 2017. For many students in Albuquerque, the commute to or from school is one of the most dangerous parts of …

Drones Detection Via Skeletonization And Small-Object-Aware Detr, Gissell Torres, Delio Rincon

Center for Cybersecurity

Detecting drones in video streaming environments remains challenging in computer vision due to scale variation and background complexity. Building up from prior work in real-time detection and skeletonization for streaming environments, this study aims to improve small object detection through Skeletonization and a Small-Object-Aware Detection Transformer framework, which uses DETR technology as a foundational step toward reliable motion prediction in dynamic aerial scenes. A transformer-based detection model was trained on a drone dataset converted to COCO format and evaluated using standard COCO metrics, including AP, AP50, and AP_small. Initial testing revealed low-confidence predictions, suggesting limitations in backbone freezing and training …

A Dataset Of Precipitate-Containing Multi-Principal Element Alloys, Anshu Raj, Xin Wang, Matthew Luebbe, Haiming Wen, Kun Lu, Shuozhi Xu

Materials Science and Engineering Faculty Research & Creative Works

We report a curated dataset that brings together composition, processing conditions, microstructural details, and mechanical properties for 396 combinations of alloy composition and processing condition drawn from 100 peer-reviewed research articles on precipitate-containing multi-principal element alloys (MPEAs). The dataset was created by first utilizing a generative large language model for information extraction, followed by expert review to ensure accurate recovery of materials data. Compositional information was taken directly from tables and text, while processing routes — including homogenization, rolling, recrystallization, and aging — were converted into uniform temperature and time metrics. Microstructural descriptors, including precipitate phases and sizes, were consolidated …

2026 (Spring) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the spring of 2026.

Near-Wall Void Distribution Characterization In Pebble Bed Reactor Using Gamma-Ray Ct And Dem Simulation, Ahmed Jasim, Mauricio Maestri, Abdullah Al Zubaidi, Omar Farid, Muthanna Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Accurate characterization of void-fraction distributions in pebble-bed reactors (PBRs) is essential for predicting flow, heat transfer, and neutronic behavior. High-fidelity experimental benchmark data for validating such predictions remain scarce, largely due to the challenges of non-invasive measurements. In this study, gamma-ray computed tomography (CT) was employed to measure radial and cross-sectional porosity in a laboratory-scale pebble bed containing 6cm graphite pebbles. A Discrete Element Method (DEM) simulation was implemented and validated against these measurements, then applied to the full-scale geometry of the Xe-100 high-temperature gas-cooled pebble-bed reactor. Analyses included radial and axial void-fraction profiles in the cylindrical section and conical …

Construction Of A Deffi Sprayer: Using 3d Printer Methodology And Techniques For Cost-Effective Analysis Using Desi Mass Spectrometry Imaging, Ryan Karst, Savvy Stevens, Luke Amos, Logan Koester, Ethan Newbold, Karson Whitaker

Symposium Projects

Using 3D Printer Methodology and Techniques for Cost-Effective Analysis using DESI Mass Spectrometry Imaging

Visual Pattern Mining With Similarity Metrics For Model-Free Trading In The Korean Futures Market, Juhyeon Jang, Jaeyun Kim, David Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

The fractal market hypothesis highlights multi-scale dynamics in financial time series and provides a theoretical foundation for pattern-based analysis. This study proposes a model-free visual pattern mining framework that transforms high-frequency market data into image representations to support intelligent decision-making. By converting 1-minute KOSPI200 futures data into candlestick chart and Bollinger band images, the method effectively captures structural patterns and volatility dynamics. The framework applies similarity metrics and Intersection over Union (IoU)-based visual comparison to identify historically similar patterns and generate intelligent trading signals without model training or complex parameter tuning. Experimental results demonstrate that combining visual features of candlestick …

Evaluating Human Rod Photoreceptor Function Using Pixelwise Intensity-Based Optoretinography, Gao Yang, Mina Gaffney, Robert F. Cooper

Biomedical Engineering Faculty Research and Publications

Purpose: More than 50 inherited retinal diseases are known, with rod photoreceptor functional loss serving as an early indicator in nearly half of them. The “optoretinogram” is a relatively new assay that detects optical changes in cells in response to stimuli. This tool has excellent potential for providing insights into the earliest functional changes of rod photoreceptors, with the potential to assist in the early detection, monitoring, and treatment of retinal diseases.

Methods: In this work, we obtained intensity-based optoretinograms (iORGs) from rod photoreceptors using an adaptive optics scanning laser ophthalmoscope. We explore the necessity of both individual rod identification …

Severity And Duration-Dependent Aortic Stiffening In A Rabbit Coarctation Model Identifies Constitutive Material Parameters As Promising Regional Biomarkers For Hypertension Progression, Arash Ghorbannia, Jamasp Azarnoosh, John F. Ladisa Jr.

Biomedical Engineering Faculty Research and Publications

Coarctation of the aorta (CoA) alters hemodynamics and drives regional remodeling, yet the influence of severity and duration on constitutive properties is undefined. We quantified mechanical responses from CoA to identify constitutive parameters capturing stiffening across clinical severities and durations. Mild (≤ 12 mmHg), intermediate (13–20 mmHg), and severe (> 20 mmHg) CoA was created in rabbits for short, long, and prolonged durations (~ 1, 3, or 22 weeks, respectively). Stress–stretch curves from proximal and distal regions were fit with multiple constitutive models (Linear Elastic, Neo-Hookean, Yeoh, Ogden, Mooney–Rivlin, Holzapfel). Model performance was evaluated by normalized RMSE and R², with …

Unveiling Value In Plastic Waste: Synthesis Of 1,3-Dioxolan-4-Ones From Polylactic Acid And Polyoxymethylene To Enhance Plastic Biodegradation, Mi-Hyun Lee, Joohyun Park, Hyeongyeong Lee, Woo Yeon Cho, Semin Son, Pyung Cheon Lee, In-Hwan Lee, Hye-Young Jang

Mechanical Engineering Faculty Publications

Catalytic plastic upcycling protocols are essential for resolving the environmental and economic challenges associated with massive plastic production and disposal, as they convert complex waste streams into value-added chemicals. We report an efficient acid-catalyzed upcycling strategy for transforming poly(lactic acid) (PLA) and polyoxymethylene (POM) plastic waste. This innovative process directly yielding dioxolanones (DOXs) can be extended to use POM with various naturally abundant α-hydroxy acids. This work significantly expands the high-value chemical portfolio derivable from common plastic wastes. Incorporation of the synthesized DOXs into the poly(L-lactic acid) (PLLA) backbone results in materials with enhanced thermal stability and superior biodegradability. Critically, …

Hybrid Deep Learning Model For Accurate Settlement Forecasting Of Metro Tracks Under Canal Diversion Engineering, Haijie He, Zhenlin Wang, Sifan Shen, Shiyu Sheng, Jing Zhang, Chuang He, Huafeng Shan, Qiongfang Zhang, Li Ai

Civil Engineering Faculty Publications

The structural stability of metro systems is essential for safe and reliable urban rail operation. Large-scale underground construction may influence existing metro lines, making accurate settlement prediction necessary. Traditional empirical and numerical methods often fail to capture long-term settlement behavior. This study predicts track bed settlement of Hangzhou Metro Line 1 using monitoring data collected during the Grand Canal diversion construction. A hybrid model (CEEMDAN-BWO-BiLSTM-ATT model) integrating Complete Ensemble Empirical Mode Decomposition with Adaptive Noise, Beluga Whale Optimization, Bidirectional Long Short-Term Memory, and an attention mechanism is developed. Results from four monitoring points along the up line show good performance, …

Intelligent Cost-Optimized Mix Design Prediction And Engineered Strength System For Geopolymer Concrete: A Machine Learning-Based Recommender System, Yuvaraj Natarajan, K.R. Sri Preethaa, V. Danushkumar, Syed Muhammad Oan Naqvi, M. Shyamala Devi, Karen Lozano, Bubryur Kim, Jinwoo An

Civil Engineering Faculty Publications

Geopolymer concrete is a promising low-carbon alternative to ordinary Portland cement concrete, but its practical use is limited by complex mix-design requirements and limited cost-aware decision-support tools. This study developed the Intelligent Cost-Optimized Mix Design Prediction and Engineered Strength System (iCOMPRESS), a machine learning-based recommender system that integrates 28-day compressive strength prediction, cost optimization, and compositionally diverse mixture recommendation. A database of 443 literature-derived mixtures was used to train a hyperparameter-optimized Random Forest model with domain-informed features related to binder chemistry, alkaline activation, water content, aggregates, and curing conditions. The model achieved a five-fold cross-validation mean absolute error (MAE) of …

Effect Of Curing Duration On Bridge Deck Concrete Performance, Zhaniya Omarova

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

This study evaluates the influence of curing duration on the performance of bridge deck concrete and investigates the feasibility of reducing curing periods without compromising structural and durability properties. Two concrete mixtures, a standard Nebraska Department of Transportation (NDOT) bridge deck mix (47BD) and an optimized reduced-cement-content mix (O47BD-R100), were evaluated under multiple curing durations Fresh, early-age, mechanical, durability, and shrinkage properties were assessed to characterize the effect of curing on concrete behavior. Internal relative humidity and temperature were monitored using embedded sensors to investigate moisture diffusion and its role in shrinkage development for lab specimens and full-scale slabs.

Results …

How Do Social Network Models Compare To All-To-All Models For Forecasting Tuberculosis Epidemics? A Mathematical Modeling Study, Masabho Peter Milali, Hae-Young Kim, George Corliss, Anna Bershteyn

Electrical and Computer Engineering Faculty Research and Publications

Background. Mathematical models guide tuberculosis (TB) target-setting, yet most assume homogeneous “all-to-all” mixing. We compared projected intervention impacts between an all-to-all compartmental model and a Barabási–Albert (BA) scale‑free social network model under otherwise identical disease assumptions.

Methods. We calibrated transmission parameters so both models produced similar baseline trends, then introduced vaccination (coverage 30–70%; efficacy 80–95%) and treatment (20–50% increases in recovery) after a 400‑day burn‑in. Outcomes were assessed 300 days post‑intervention.

Results. Under 60% coverage, increasing vaccine efficacy from 80% to 95% yielded smaller projected reductions in active TB with the network model than with all‑to‑all mixing. Treatment improvements showed …

Development And Acceptability Of A Patient Decision Aid For People With Degenerative Cervical Myelopathy: An International Mixed-Methods Study, Andrew R. Gamble, David B. Anderson, Marnee J. Mckay, Benjamin M. Davies, Sophie Macpherson, James Van Gelder, Tammy Hoffmann, Kirsten Mccaffery, Samuel X. Stevens, Carlo Ammendolia, Rohil V. Chauhan, Carl M. Zipser, Timothy F. Boerger, Lindsay A. Tetreault, Michael G. Fehlings, Elanor Dustan, Carolyn Nugent, Helen Holmgren, Andreas K. Demetriades, Justin M. Lantz, Rana Dhillon, Chris G. Maher, Joshua R. Zadro

Biomedical Engineering Faculty Research and Publications

Objectives To develop and user-test a patient decision aid for people diagnosed with degenerative cervical myelopathy and who are considering surgery.

Design Mixed-methods study describing the development of a patient decision aid.

Setting A draft decision aid was developed by a multidisciplinary steering group (including study authors with degenerative cervical myelopathy, health professionals and researchers) informed by the best available evidence, authorship consensus and existing patient decision aids.

Participants Patient-participants and health professional-participants who manage people with degenerative cervical myelopathy were recruited through social media and the steering group’s research and practice network. Quantitative questionnaires were used to gather baseline …

X-Ray Tomography Of Damage Dynamics In Advanced Materials Using A Laser Wakefield Accelerator, Vigneshvar Senthilkumaran, Nicholas F. Beier, Sylvain Fourmaux, Peter Kenesei, Sean Dobson, Joël Maltais, Alvaro R. Arce-Borkent, Tait Richards, Michael G. Lipsett, Le Zhou, John A. Moore, Amina E. Hussein

Mechanical Engineering Faculty Research and Publications

Additively manufactured (AM) metals offer the potential for customizable, cost-effective components, but qualification and certification are crucial. Key to this process is understanding pore dynamics under stress, typically analyzed using micro-computed tomography. This study introduces laboratory-scale “betatron” x-rays from laser wakefield acceleration as a high-throughput alternative for x-ray tomography of advanced materials, such as AM AlSi10Mg alloys. Coupled with 3D finite element modeling, this method provides detailed insights into stress-porosity interactions. The approach delivers high-resolution scans, revealing that pore shape and local triaxiality significantly influence fracture dynamics, supporting advanced material characterization. This work also demonstrates the potential and versatility of …

Natural Convection Of Cuo-Water Nanofluid Flow Along A Vertical Plate With Variable Thermophysical Properties And Discrete Heat Sources, Nepal Roy, Ioan Pop, Rama Subba Reddy Gorla

Faculty Publications

Effects of discrete heat sources along a vertical plate are of practical importance due their occurrence in electronic devices. For growing demand of electronic appliances and their advancement, cooling processes of them must be improved. As usual fluids have limited heat transfer, nanofluids made by dispersing nanoparticles into them are utilized to enhance thermal performance. However, flow characteristics and heat transfer of a nanofluid for discrete heat sources along a vertical plate need to be explored. For this reason, this study analyzes the natural convective heat transfer and flow behaviors of CuO-water nanofluid induced by discrete heat sources along a …

Radiation Protection Factor Research: The Keystone For Conventional-Nuclear Integration (Cni), Andrew W. Decker

Faculty Publications

This article briefly describes Defense Threat Reduction Agency (DTRA) vehicle Radiation Protection Factor (RPF) research and explains its critical role in enabling future Operations in a Nuclear Environment (ONE) and Conventional-Nuclear Integration (CNI) on behalf of the US Department of War (DoW).1 As such, the background and practical utility of RPF values is discussed, as well as the justification for renewed Army and DoW investment into RPF research to enhance Joint military planning, survivability, and lethality on tomorrow’s nuclear battlefields. Advances in DTRA RPF research directly strengthen US strategic and extended deterrence efforts and support all Agencies and Departments responsible …

Enhancing Co2 Adsorption And Co2/N2 Separation Performance By Incorporating Calcium In Mil-53 (Al), Hussein Rasool Abid, Hussein Znad, Nabil Majd Alawi, Farhan Lafta Rashid, Anmar Dulaimi, Amer Alanazi, Alireza Keshavarz, Stefan Iglauer, Shaobin Wang

Research outputs 2022 to 2026

Global warming is primarily driven by the rapid accumulation of carbon dioxide (CO₂) in the atmosphere. Metal–organic frameworks (MOFs) have emerged as promising materials for mitigating CO₂ emissions due to their tunable porosity, large surface area, and structural flexibility. Among them, MIL-53(Al) has attracted widespread interest owing to its excellent thermal and chemical stability. Recent studies show that modifying MOFs with secondary metals can significantly enhance their CO₂ adsorption performance. In this work, a one-pot synthesis method was employed to incorporate calcium (Ca), functioning as a Lewis basic metal, into the MIL-53(Al) framework to produce a series of bimetallic materials: …

Zwitterionic And Anionic Ultrafiltration Membrane Modification For Efficient, Fouling-Resistant Microalgae Harvesting, Victor Okorie Mkpuma, Mohadeseh Najafi, Javad Farahbakhsh, Masoumeh Zargar, Navid Reza Moheimani, Houda Ennaceri

Research outputs 2022 to 2026

Membrane surface modification is a promising strategy for fouling mitigation in membrane-based microalgae filtration, primarily by limiting the interactions between the membrane surface and the foulant particles. This study investigated the effectiveness of modified membranes in filtering Chlorella sp. MUR 269. First, three polyethersulfone membranes with varying pore sizes were evaluated to determine the influence of pore size on filtration performance and fouling behavior. The ultrafiltration membrane that exhibited the best performance was subsequently modified using two functional monomers: the zwitterionic [2-(methacryloyloxy)ethyl]dimethyl (3-sulfopropyl) ammonium hydroxide and the negatively charged mono-2-(methacryloyloxy)ethyl succinate (MMS). The filtration performance and fouling resistance of the …