Engineering Commons^™

Advancing Sustainable Road Construction With Cold Mix Rap And Rejuvenator, Abeeb G. Oyelere

Shelby Hall Graduate Research Forum Presentations

Presentation slides for a presentation given at the 1st annual Shelby Hall Graduate Research Forum at the University of South Alabama.

Choosing Robust Leadership: Encompassing The Best-Of-N Model And Swarm Intelligence Optimization For Heterogeneous Multiple Autonomous Unmanned Aerial Vehicle Systems, Kudamuhandiramlage Harith Kolitha Warnakulasooriya

Shelby Hall Graduate Research Forum Presentations

Presentation slides for a presentation given at the 1st annual Shelby Hall Graduate Research Forum at the University of South Alabama.

Improving The Viability Of Continuous Fiber Reinforced Composite Materials In Extreme Temperature Applications And Additive Manufacturing, Ryan A. Warren

Shelby Hall Graduate Research Forum Presentations

Presentation slides for a presentation given at the 1st annual Shelby Hall Graduate Research Forum at the University of South Alabama.

Danzens: A Toolkit For Sensing, Labeling And Visualizing Dance Movements, Yanelly Mego, Concepción Valdez, Hector M. Camarillo-Abad, Franceli L. Cibrian

Engineering Faculty Articles and Research

Wearable technology offers new opportunities for analyzing complex movements like dance, where precision, coordination, and feedback are key. In this demo, we present DanZens, a novel toolkit for real-time motion analysis in dance, leveraging wearable sensors to provide accessible and actionable feedback. Combining DanceTag to capture and annotate movements with DanceVis to visualize performance differences, DanZens uses Sony Mocopi sensors to analyze motion and generate intuitive heat maps through Dynamic Time Warping (DTW). This system enables precise, cost-effective comparisons between two people doing dance-related movements, offering personalized feedback and eliminating the need for expensive biomechanical labs. Designed to advance pervasive …

Harmonicthreads – An Interface That Supports Accessibility In Musical Interaction, Ellie Nguyen, Miyuki Weldon, Franceli L. Cibrian

Engineering Faculty Articles and Research

Traditional musical instruments often can create boundaries due to their cost, training, mobility, and cognitive requirements, making musical expression inaccessible. To address this challenge, we developed HarmonicThreads, a novel pervasive computing interface consisting of a responsive, flexible fabric. HarmonicThreads provides a tactile and auditory experience, allowing users to easily create and control sounds. Using embedded sensors and real-time processing, HarmonicThreads interprets the user's natural movements and interactions to create adaptable musical outputs. This enables context-aware musical interaction, demonstrating the potential of pervasive interfaces in reducing barriers and making musical expression more accessible.

Advances In Theory And Computational Methods For Next-Generation Thermoelectric Materials, Junsoo Park, Alex M. Ganose, Yi Xia

Mechanical and Materials Engineering Faculty Publications and Presentations

This is a review of theoretical and methodological development over the past decade pertaining to computational characterization of thermoelectric materials from first principles. Primary focus is on electronic and thermal transport in solids. Particular attention is given to the relationships between the various methods in terms of the theoretical hierarchy as well as the tradeoff of physical accuracy and computational efficiency of each. Further covered are up-and-coming methods for modeling defect formation and dopability, keys to realizing a material's thermoelectric potential. We present and discuss all these methods in close connection with parallel developments in high-throughput infrastructure and code implementation …

Industry Applications Society And Conferences [President’S Message], Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

No abstract provided.

Quantum Finite Automaton Using Ternary Rotation Quantum Gates And Chrestenson Family Quantum Gates, Yuchen Huang, Marek Perkowski, Xiaoyu Song, John M. Acken

Electrical and Computer Engineering Faculty Publications and Presentations

Quantum automata can solve certain problems with a smaller state space than classical automata. We developed a quantum finite automaton using ternary rotation quantum gates and the Chrestenson family of ternary quantum gates. The main idea of this paper is to show how to combine rotation ternary quantum circuit-based QuantumFinite Automaton and quantum reversible circuit-based Deterministic Finite Automaton to build a more powerful machine. The combined machine can enable more complex language and pattern recognition. The developed quantum finite automaton and resulting combined machine can be used for robotics applications such as language, gesture, and motion recognition.

Development And Validation Of An Artificial Intelligence System For Surgical Case Length Prediction, Adhitya Ramamurthi, Bhabishya Neupane, Priya Deshpande, Ryan Hanson, Kellie R. Brown, Kathleen K. Christians, Douglas B. Evans, Anai N. Kothari

Electrical and Computer Engineering Faculty Research and Publications

Background

Accurate case length estimation is a vital part of optimizing operating room use; however, significant inaccuracies exist with current solutions. The purpose of this study was to develop and validate an artificial intelligence system for improved surgical case length prediction by applying natural language processing and machine-learning methods.

Methods

All inpatient elective surgical cases longer than 30 minutes completed between 2017 and 2023 at a single, quaternary care hospital were considered. Data were split into training, test, and hold-out validation for model training and testing. Linear regression, CategoricalBoost, and feed-forward neural network each were trained and used embeddings created …

Industry Applications Society And Conferences [Presidents Message], Ayman El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

No abstract provided.

Preparation Of Mg-Doped Coffee Waste For Efficient Removal Of Methylene Blue And Lead From Water, Pengfei Li, Liang Zhao, Long Li, Kehan Xu, Jibran Iqbal, Zhenbang Tian, Xing Xing, Hui Li, Yaping Hou, Jie Wang, Manman Xu

All Works

Water pollution, particularly from industrial sources, poses severe environmental and health risks, necessitating cost-effective and sustainable solutions. This study investigates the preparation and application of magnesium-doped coffee waste biochar (Mg-CW) for the removal of methylene blue (MB) and lead ions (Pb2+) from water. Mg-CW, synthesized via one-step pyrolysis at 300°C, demonstrated remarkable adsorption capacities of 1024.88 mg/g for MB and 349.59 mg/g for Pb2+. Adsorption efficiencies were optimal at pH 12 for MB and pH 5 for Pb2+, attributed to enhanced electrostatic interactions and complexation mechanisms. Regeneration studies revealed that Mg-CW retains over 95% adsorption efficiency after multiple cycles, highlighting …

Assessing The Perceived Safety Of Cyclists With Virtual Reality, Vahid Balali

Mineta Transportation Institute

In 2022, 7,522 pedestrians and 1,084 bicyclists were killed and approximately 67,000 pedestrians and 46,195 bicyclists injured in motor vehicle crashes on public roadways in the United States, according to the Insurance Institute for Highway Safety (IIHS). The transportation industry is faced with a pressing need to bolster the safety of these vulnerable road users. This research develops models of design and environmental factors that influence bicyclists’ and pedestrians’ perception of safety using Virtual Reality (VR) technology and ultimately informs transportation infrastructure design to better accommodate nonmotorized travelers. The goal of the bicycle element of this research is to develop …

Smart Highway Construction Site Monitoring Using Artificial Intelligence, Mehran Mazari, Yahaira Nava-Gonzalez, Ly Jacky N. Nhiayi, Mohamad H. Saleh

Mineta Transportation Institute

Construction is a large sector of the economy and plays a significant role in creating economic growth and national development,and construction of transportation infrastructure is critical. This project developed a method to detect, classify, monitor, and track objects during the construction, maintenance, and rehabilitation of transportation infrastructure by using artificial intelligence and a deep learning approach. This study evaluated the performance of AI and deep learning algorithms to compare their performance in detecting and classifying the equipment in various construction scenes. Our goal was to find the optimized balance between the model capabilities in object detection and memory processing requirements. …

Toward Sustainability: A New Construction Method For Electrically Heated Rigid Pavement Systems, Mohamed Abdel-Raheem, Mohammad Anis

Civil Engineering Faculty Publications

Damage caused by snow and ice to airport pavements in colder regions of the United States presents a persistent and economically significant challenge. This research explores an innovative construction method using an electrically conductive composite (ECC) composed of waterborne polyurethane and graphite powder (Gp). The ECC is applied to a Portland cement concrete substrate through a parallel stripe technique, using two types of “exposed” specimen. The study thoroughly examines the resistive heating performance of these specimens under various conditions, focusing on critical factors such as Gp concentrations in ECC, stripe thickness, spacing, and applied voltages. ECC was prepared with varying …

Computational Model Of Coarctation Of The Aorta In Rabbits Suggests Persistent Ascending Aortic Remodeling Post-Correction, Ashley A. Hiebing, Matthew A. Culver, John F. Ladisa, Colleen M. Witzenburg

Biomedical Engineering Faculty Research and Publications

Coarctation of the aorta (CoA) is a common congenital cardiovascular lesion that presents as a localized narrowing of the proximal descending aorta. While improvements in surgical and catheter-based techniques have increased short-term survival, there is a high long-term risk of hypertension and a reduced average lifespan despite correction. Computational models can be used to estimate aortic remodeling and peripheral vascular compensation, potentially serving as key tools in developing a mechanistic understanding of the interplay between pre-treatment dynamics, post-treatment recovery, and long-term hypertension risk. In this study, we developed a lumped-parameter model of the heart and circulation to simulate CoA. After …

Examining The Impact Of The Covid-19 Pandemic On Older Adults' Activity Participation And Mode Usage In A Rural State: A Case Study Of Arkansas, Arna Nishita Nithila, Suman Kumar Mitra, Alishia Juanelle Ferguson, Michelle Gray, Jennifer D. Webb

Civil Engineering Faculty Publications and Presentations

The objective of the study was to investigate the impact of the COVID-19 pandemic on the activity participation and mode usage of older adults residing in Arkansas, a predominantly rural state. Leveraging primary data collected from 832 older adult participants, the study employed Latent Class Analysis (LCA) to capture older adults' heterogeneity in travel behavior and found three distinct classes: Pandemic-affected minimal travelers, Unaffected non-commuter car users, and Unaffected commuter car users, showing different levels of their activity participation, mode usage during the pandemic and varying the pandemic's impact on their trips. To understand these variations in light of the …

Structure-Property Relations Of Binary Ferrite Melts, C. J. Benmore, C. Shi, O. L.G. Alderman, J. P. Harvey, D. Lipke, J. K.R. Weber

Materials Science and Engineering Faculty Research & Creative Works

Molten ferrite systems are used in the smelting and refining processes in steelmaking, to reduce the loss of metals in slags and to accelerate reaction rates. Here, high-energy x-ray diffraction experiments have been performed on aerodynamically levitated molten spheres of 43BaO-57FeOX and 43SrO-57FeOX at 1873 K using laser beam heating. The composition was varied within the range of x = 1-1.5 by changing the oxygen partial pressure of the levitation gas. The corresponding x-ray pair distribution functions have been interpreted using empirical potential structure refinement (EPSR) modeling. In oxygen-rich melts (x = 1.5), our EPSR models indicate very similar structures …

Prototyping Various Mppt Techniques Used In Wind Energy Conversion Systems For Response Time Monitoring, Amro Kawashty, Sameh O. Abdellatif, Gamal Ebrahim, Hani Ghali

Electrical Engineering

This paper focuses on prototyping various maximum power point tracking (MPPT) techniques used in wind energy conversion systems (WECS) for response time monitoring. MPPT plays a crucial role in optimizing the power extraction from wind turbines by dynamically adjusting their operating conditions to track the maximum power point. The response time of an MPPT algorithm determines how quickly it can adapt to changes in wind conditions and maximize power output. In this study, we implement and compare multiple MPPT techniques on an emulated WECS. Several commonly used MPPT techniques, such as perturb and observe (P&O), incremental conductance (IncCond), and tip …

Evaluation Of Health Monitoring Parameters For Automotive Pneumatic Elastomeric System Using Soft Pressure Sensors For Enhanced Vehicle Performance., Md Jarir Hossain, Sarah Suresh Kamath, Jong Min Park, Heung-Seok Oh

University Research

In the rapidly evolving automotive industry, the need for reliable and efficient pneumatic elastomeric components necessitates cutting-edge health monitoring methods, given that the pneumatic components are directly connected to dampening properties, ride comfort, vehicle safety, and stability. A novel approach for pneumatic elastomeric component health monitoring utilizing ionic liquid (IL)-based soft sensor technology has been proposed, which has the promise to enable real-time health monitoring and prognostics of vehicle systems. The proposed polymer sensor leverages the distinctive characteristics of flexibility, stretchability, and high sensitivity. These properties are critical for precisely measuring load, vertical displacement, air pressure, force locations, and load …

Beyond The Blue Skies: A Comprehensive Guide For Risk Assessment In Aviation, Leila Halawi, Mark Miller, Sam Holley

Publications

Risk assessment in aviation is a critical process that safeguards the safety and reliability of operations. Aviation operations encompass inherent risks, from mechanical failures to human errors and environmental factors. The significance of these risks may be severe, leading to accidents, injuries, and loss of life. Recognizing and mitigating risks is supreme in this dynamic environment, where emerging technologies and innovation constantly reshape this industry. This chapter includes an in-depth explanation of risk management and analysis, leading to the core elements of risk assessment specifically for aviation operations. We will describe the process and explore some of the applications and …

Power System Operations Modeling And Optimization Using Pyomo, Ahmad Heidari, Rui Bo

Graduate Student Research & Creative Works

"The energy sector has witnessed transformative advancements over the past few decades. Power systems, which form the backbone of modern society, have grown increasingly complex with the integration of renewable energy sources, energy storage, and emerging technologies. As these systems evolve, so does the need for efficient operation and optimization strategies to ensure reliability, sustainability, and economic performance.

Optimization plays a central role in solving real-world challenges such as balancing power generation and demand, minimizing operational costs, and managing grid constraints. However, many existing resources tend to focus either on theoretical aspects of optimization or rely on expensive, proprietary software …

Flow Dynamics Of Agricultural Waste Nanofibers: Shear, Temperature, And Oscillatory Insights, Bilge N. Altay, Burak Aksoy, James Atkinson, Christopher Lewis, Carlos Diaz-Acosta, Raymond Francis

Articles

The rheology and fiber size of corn stover (CS) and cleaned cotton gin trash (CGT) cellulose nanofibers (CNFs) were studied including behaviors at both moderate and extremely high shear rates, to simulate industrial processes ranging from mixing and pumping to high-speed coating, printing, and extrusion. Particle size analyzer showed that 99% of CS fibers measured around 226 nm, while 85% of CGT fibers were approximately 143 nm. Both CS and CGT CNFs formed gel-like suspensions, and shear flow tests revealed that all samples exhibited shear-thinning behavior, allowing easy flow under shear forces. Gels with higher solid content (1%) demonstrated extended …

Deployable Origami Structure, David J. Garcia, Robert Bettinger

AFIT Patents

The present invention relates to deployable origami structures and methods of making and using same. Such deployable origami structures can be folded into a compact state utilizing origami, yet easily deployed as the structures comprise pseudo-elastic connectors. Additive manufacturing techniques can be used to make such deployable origami structures as such techniques can lower cost and structure weight.

Processing Parameter-Performance Nexus In 3d Printing Of Nanostructured Chiral Photonics, Kyle George, Nader Taheri-Qazvini, Peter D. Olmsted, Monirosadat Sadati

Faculty Publications

Precisely crafted hierarchical architectures found in naturally derived biomaterials underpin the exceptional performance and functionality showcased by the host organism. In particular, layered helical assemblies composed of cellulose, chitin, or collagen serve as the foundation for some of the most mechanically robust and visually striking natural materials. By utilizing structured materials in additive manufacturing techniques such as extrusion-based 3D printing, the intrinsic deformation process can be used to implement bottom-up design of printed constructs, offering the potential to create intricate macroscale geometries with embedded nanoscale functionality. In this study, comprehensive rheological and rheo-optical characterization of structurally colored, photocurable liquid crystalline …

Potential Of Individual Upper-Limb Muscles To Contribute To Postural Tremor: Simulations From Neural Drive To Joint Rotation, Spencer A. Baker, Landon J. Beutler, Daniel B. Free, Dario Farina, Steven Knight Charles

Faculty Publications

Background: It is unclear which muscles contribute most to tremor and should therefore be targeted by tremor suppression methods. Previous studies used mathematical models to investigate how upper-limb biomechanics affect muscles’ potential to generate tremor. These investigations yielded principles, but the models included at most only 15 muscles. Here we expand previous models to include 50 upper-limb muscles, simulate tremor propagation, and test the validity of the previously postulated principles. Methods: Tremor propagation was characterized using the gains between tremorogenic neural drive to the 50 muscles (inputs) and tremulous joint rotations in the 7 joint degreesof- freedom (DOF) from shoulder …

Immersive Modeling To Communicate And Manage Risks Of Water Shortages, David Rosenberg, Erki Porse

Civil and Environmental Engineering Faculty Publications

Our project goal is to use immersive online collaborative modeling as a tool for active learning to communicate and manage users conflicting risks of water shortages because decisions now to manage risk effect future risk. State-of-the art river basin forecasting tools provide probabilistic estimates of streamflow at hourly to annual scales. Water resource models quantify tradeoffs and risk across hundreds or thousands of scenarios of inflow and demand forecast out decades. Our project objectives are: 1) Formulate extreme scenarios for reservoir inflows without probabilities one to three years out that pose imminent risk of water shortages. 2) Hold immersive model …

Comparative Evaluation Of Linear Regression, Cross Validation And Regularization Approaches In Multivariate Data Analysis, Ransford Owusu, Felix Yeboah, Francis Effah Boateng

Data Science and Data Mining

This study evaluates linear regression and its enhanced variants incorporating cross-validation and regularization techniques for high-dimensional, multivariate datasets. We address challenges such as multicollinearity and overfitting. Methods including Ridge, LASSO, and Elastic Net are compared against ordinary least squares regression. Empirical analysis using an automobile dataset for fuel efficiency prediction shows that while OLS regression captures basic relationships, its limitations are mitigated through regularization and cross-validation, resulting in improved model interpretability. The findings provide a comprehensive framework for predictive modeling in complex data environments and offer insights into statistical methodology and practical applications in the automobile industry.

Lab: Developing Explainable Multimodal Ai Models With Hands-On Lab On The Life-Cycle Of Rare Event Prediction In Manufacturing, Chathurangi Shyalika, Ruwan Wickramarachchi, Revathy Venkataramanan, Dhaval Patel, Amit Sheth

Faculty Publications

In the age of Industry 4.0 and smart automation, unplanned downtime is costing industries over $50 billion annually. Even with preventive maintenance, industries like automotive lose more than $2 million per hour due to downtime caused by unexpected or "rare'' events. The extreme rarity of these events makes their detection and prediction a significant challenge for AI practitioners. Factors such as the lack of high-quality data, methodological gaps in the literature, and limited practical experience with multimodal data exacerbate the difficulty of rare event detection and prediction. This lab will provide hands-on experience to learn how to address these challenges …

Classification Of Microcontroller Integrated Circuit On The Pocket Of Jedec Tray Using Convolutional Neural Network In Embedded Machine Learning System, Mark Pallones, King Harold A. Recto

Electronics, Computer, and Communications Engineering Faculty Publications

One serious issue in the microcontroller manufacturing environment is the mixing of microcontroller unit (MCU) parts, leading to the wastage of materials, dissatisfied customers, and the implementation of non-value-adding activities to address it. More adverse effects include negative feedback from customers, loss of confidence, and impact on business growth. One root cause traces back to the final testing of the manufacturing back-end process when reusing unemptied standard JEDEC matrix trays for good and bad units in the test handler. Currently, emptying the JEDEC matrix tray and inspecting it is a manual process prone to human error due to high-volume test …

Additive Manufacturing Applications In Mission-Critical Operations: A Review, Arup Dey, Olusanmi Adeniran, Monsuru Ramoni

Manufacturing & Industrial Engineering Faculty Publications

Additive manufacturing (AM) is used to fabricate complex components from a wide variety of materials in an additive manner. AM brings several benefits, such as reduced lead times, on-demand production, creation of complex customized designs without tooling requirements, and remote design sharing. However, the use of AM for critical components is limited in large missions due to quality and reliability concerns, as is the case with many manufacturing technologies. Enhancing the acceptance of AM-built parts for mission-critical components can be achieved by producing highly reliable parts, establishing robust quality standards, and continually improving part properties. This review article comprehensively explores …