Engineering Commons^™

Cross-Layer Performance Analysis Of P-Edca, Claude Davis Robertson V

Computer Science and Engineering Master's Theses

Modern Wi-Fi applications require tight latency bounds and predictable throughput, and they rely on a mix of transport protocols (e.g., TCP Cubic, BBR, New Reno, and UDP) whose performance is highly sensitive to MAC-layer behavior. The forthcoming 802.11bn amendment introduces Prioritized EDCA (P-EDCA) to reduce latency for high-priority traffic, yet its cross-layer impact on transport performance remains insufficiently understood. This thesis evaluates the performance of TCP and UDP traffic operating over both EDCA and P-EDCA. Our results show that (i) both TCP and UDP traffic exhibit strong sensitivity to P-EDCA configuration, with uplink tail latency varying widely; (ii) by reducing …

Universal Sound Separation: Distance-Aware Mixture Simulation, Co-Occurrence Conditioning, And Chain-Of-Inference, Wonjun Park

Computer Science and Engineering Theses - Archive

Universal Sound Separation (USS) -- the task of disentangling arbitrary sound sources from a single-channel acoustic mixture -- remains an open challenge due to the ill-posed nature of the problem and the distributional gap between synthetic training data and real-world recordings. This thesis addresses three distinct bottlenecks in the USS pipeline: training data realism, inference strategy, and conditioning richness. We first present two knowledge-guided approaches to sound source separation. The first is a distance-aware mixing strategy that leverages Large Language Models (LLMs) to assign plausible loudness relationships between audio sources during training data synthesis. By querying an LLM about the …

Data-Driven Prediction Of Concrete Bridge Deck Corrosion Using Ground Penetrating Radar (Gpr), Nafisa Shafiullah

Civil Engineering Theses

Corrosion detection remains a crucial factor in the proper maintenance of Reinforced Concrete (RC) structures. While several studies have used Ground Penetrating Radar (GPR) for corrosion detection, quantitative models for prediction are still limited. This study presents an approach for the quantitative prediction of rebar corrosion in concrete using GPR data obtained from a prior experimental program involving accelerated corrosion. A total of 36 RC samples were cast, varying in cover depth, rebar diameter, and concrete porosity. The samples were subjected to an impressed current of 0.65 A in a 5% NaCl solution over three phases: 10, 20, and 30 …

Study Of Clustering Technique And Communication Topologies For Cooperative Control-Based Volt-Var Optimization, Gaurav Yadav, Yuan Liao, Dan M. Ionel

Electrical and Computer Engineering Faculty Publications

Introducing renewable distributed generation (DG) in the power distribution system causes rapid voltage fluctuations due to its intermittency. This intermittency renders conventional voltage regulation devices such as on-load tap changers (OLTCs) and capacitor banks (CBs) inefficient to regulate rapid voltage changes and leads to reduced equipment lifetime and high operation and maintenance costs. Hence, this calls for non-conventional methods to mitigate such voltage fluctuations. This paper presents a cooperative control-based method aimed to optimally control the reactive power of DG inverters to mitigate the voltage deviations by establishing communication among the DG nodes, and between DG and non-DG nodes. This …

Electromagnetic Formation Flying Using Alternating Magnetic Field Forces And Control Barrier Functions For State And Input Constraints, Sumit Suryakant Kamat, Thomas Michael Seigler, Jesse B. Hoagg

Mechanical Engineering Faculty Publications

This article presents a feedback control algorithm for electromagnetic formation flying with constraints on the satellites’ states and control inputs. The algorithm combines several key techniques. First, we use alternating magnetic field forces to decouple the electromagnetic forces between each pair of satellites in the formation. Each satellite’s electromagnetic actuation system is driven by a sum of amplitude-modulated sinusoids, where amplitudes are controlled in order to prescribe the time-averaged force between each pair of satellites. Next, the desired time-averaged force is computed from an optimal control that satisfies state constraints (i.e., no collisions and an upper limit on intersatellite speeds) …

Comparative Finite Element Method-Based Optimisation Of Coir Fibre Laminates: Aluminium Skins Versus Carbon Cloth Skins, Muhamed Swaleh Ahmed, Bernard Wamuti Ikua, Abel Nyakundi Mayaka

Mansoura Engineering Journal

Natural fibre composites offer a sustainable alternative to conventional composite materials. Their mechanical efficiency is influenced by laminate structure and skin material selection. This study presents a comparative finite element analysis and optimisation of coir fibre-reinforced laminates employing either aluminium skins or carbon cloth skins. COMSOL Multiphysics was used to determine their mechanical response. Optimisation was performed using the BOBYQA algorithm to enhance load sharing between the coir core and skin materials. Results indicated that aluminium-skinned laminates achieve superior compressive and flexural performance, achieving a peak compressive strength of 210 MPa and sustaining a flexural load of 0.65 kN at …

Elli’S Liquid Flow In A Wavy Channel With Slip Effect, Wall Properties, And Heat Transfer, P. Devaki, Yatin Sood

Mansoura Engineering Journal

The dual behavior of Elli’s fluid motivated us to work on it. The fluid behaves as both Newtonian/ non-Newtonian based on the low and high shear rates, respectively. The paper focused on the flow of Ellis fluid in a peristaltic channel with wall properties and heat transfer. The channel is symmetric in nature, and slip conditions are considered near the elastic walls. The governing equations of the flow are solved analytically using suitable boundary conditions, which yield velocity and temperature functions. The novelty of the paper is to analyze the nature of Newtonian/non-Newtonian fluids under the same conditions so that …

Numerical Simulation And Analysis Of Lid Driven Cavity Flow And Flow Around A Cylinder, Liberty Ammamoo Mr, Mohammad Uddin Dr

ASPIRE 2026

This paper explores a computational investigation of two classical fluid dynamics problems-lid driven cavity flow and flow around a cylinder- simulated at varying Reynolds numbers using Ansys Fluent (AF) and OpenFOAM (OF).The primary goal is to reproduce and compare the physical flow behavior observed in both solvers under matched boundary conditions, mesh configurations, and fluid properties, rather than to compare solver performance. Simulations for a square cavity case at Reynolds number of 10,100,10000, and for the flow around a cylinder case at Reynolds number of 180 were produced. The results capture key flow features including primary vortex formation, vortex shifting …

A. Vs. I In Ai: Is There A Threshold To "Engineered" Intelligence?, Joshit Mohanty

Engineering Management & Systems Engineering Faculty Publications

Despite artificial intelligence reshaping the world, its development generates uncertainties regarding future capabilities. AI simultaneously exists as an artifact of engineering design and as autonomous intelligence, creating an observer-participant feedback loop. This paper proposes that embodied AI faces a bandwidth-limited intelligence threshold T_h that it arises from B = min(C_sens,C_Act). However, Shannon capacity measures bits while intelligence operates on concepts, necessitating a dual-channel model separating physical bandwidth B_io from representational capacity B_rep. Intelligence emerges as multi-dimensional rather than scalar, with components exhibiting different bandwidth dependencies. Surpassing T_h requires either new sensing methods expanding B, enhanced representational frameworks, or reconceptualization within …

Teleoperated Robotic Arm With Vision-Based Imitation Learning, Favour E. Emmanuel, Hunter J. Donahue

Williams Honors College, Honors Research Projects

This report presents the design, development, and deployment of a teleoperated robotic arm system capable of vision-based imitation learning. The system uses a leader-follower architecture with myArm C650 and myArm M750 robots manufactured by Elephant Robotics. The leader arm movement is controlled by the operator, whereas the follower performs actions acquired from demonstrations. Data collection included synchronized joint-angle recording and multi- camera video streams capturing human demonstrations.

These demonstrations were processed with a deep learning imitation algorithm called Action Chunking with Transformers (ACT). The main capability of this algorithm is its ability to make future action predictions based solely on …

Areosense, Josephine Turney

Williams Honors College, Honors Research Projects

The AeroSense growing system is designed to make indoor aeroponic gardening easy and accessible for everyone. By combining sensors, automation, and AI, the system can monitor and adjust humidity, lighting, and nutrient levels to help plants thrive without requiring expert knowledge. The goal is to create a self-regulating garden that takes the guesswork out of growing fresh herbs and vegetables at home. The project involves building a working aeroponic prototype equipped with misters, pumps, and environmental sensors, all managed by a Raspberry Pi. Using computer vision and machine learning, AeroSense will be able to assess plant health and respond automatically …

Dynamic Thrust Testbed For Uav Electric Motors, Colin M. Flowers, Robert C. Johnson Jr., Carson P. Holt

Williams Honors College, Honors Research Projects

This project seeks to bring new testing capability to the Zips Aero Design Team through the design, manufacture, integration, and testing of a dynamic thrust testbed for UAV electric motors. The project centers upon the revival and modification of a past prototype aircraft for use as a testbed for in-flight thrust measuring and recording. The team currently lacks the ability to test dynamic thrust under the operating conditions and flight speeds that are encountered in competition. Project technical areas include component and product design, electrical and electronics, and fluid mechanics, including the use of SolidWorks, MATLAB, and ArduPilot. Aside from …

Parking Information And Supervision System, Joshua A. Thum, Alex J. Kinch, Jacob A. Dye

Williams Honors College, Honors Research Projects

In densely populated areas, finding parking can be an arduous and time-consuming struggle, especially in large and tall parking decks. Drivers would benefit from a convenient way to find an open parking spot without having to scour the entire lot first. The goal of this project is to sense available parking spots in a parking garage or parking lot using physical object detection and visual detection with computer vision verification, and display the open spots to drivers entering the lot. This information will be displayed locally at the lot and in an app, with the latter allowing someone to see …

High-Speed Non-Pneumatic Tire (Npt) Design For Speeds Above 60 Mph, Jacob Grams, Brady Maurer, Jake Groewa

Williams Honors College, Honors Research Projects

This project focuses on developing a high-speed non-pneumatic tire (NPT) capable of safely operating at speeds greater than 60 mph, a performance range where most existing airless tire designs fail due to structural instability and performance limitations. The objective of this work is to design, analyze, and prototype a structurally optimized honeycomb-based tire structure with improved load distribution, deformation control, and durability. Multiple geometries were evaluated using finite element analysis (FEA) to assess stress and maximum resultant (total) displacement behavior under loading conditions, and a material selection study was performed to identify a suitable material for the design. The final …

Robotic Air Hockey Table, William Forcey, Andrew Piunno, Kaden Carpenter, Xander Zavatchen

Williams Honors College, Honors Research Projects

Air hockey, a popular arcade game, is traditionally designed for two players. This limits the game’s accessibility for individuals who wish to practice or enjoy it as a single player. To solve this problem, a robotic system was implemented to play air hockey against a human player. The speed and acceleration of the puck and mallet were measured from a game played between humans to inform the required movement capabilities of the robot. The robotic opponent implemented observes the location of the puck on the table using a camera and predicts where it will be in the future. A Cartesian …

Nissan Leaf Disassembly Tool And Test Stand Design, Mariah Z. Hodge

Williams Honors College, Honors Research Projects

The Akron Engineering Tribology Laboratory has developed a water-based lubricant and aims to test and observe if the water-based lubricant could work in an electric vehicle environment. As parameters for creating a test stand to mimic an electric motor environment are not readily available online, the goal of this senior design project is to take apart a used Nissan Leaf engine to define the parameters a test stand must meet to accurately recreate an electric motor environment. Knowing these parameters, a test stand will then be designed for testing the water-based lubricants. The purpose of building a test stand to …

Effect Of Snow Melt On Slope Stability, Gustav G. Gothberg

Williams Honors College, Honors Research Projects

This project explores the effect of snow melt on slope stability. The different types of slope failure are examined to determine which are most affected by snow melt. Then, the report examines the equations that geotechnical engineers use to determine the exact moment when a slope fails. Using GeoStudio modeling software, Slope/W, landslides caused by snow melt were modeled. GeoStudio was also used to explore methods of mitigating the effects of snow melt. This project also explores how to take advantage of these models to minimize the damage done by landslides.

The Effects Of Low-Frequency, Low-Intensity Ultrasound On Gene Expression In Macrophage-Endothelial Cell Co-Culture, Evelyn Hergenhan

Honors Theses

Introduction

Low-frequency, low-intensity ultrasound (LFLI US) has been shown to be a promising treatment for noninvasive accelerated chronic wound healing. However, the biological mechanisms of this ultrasound-assisted healing are not yet understood, limiting clinical adoption. The objective of this study is to characterize the effects of LFLI US on gene expression in a simulated chronic wound environment to gain a better understanding of the biological mechanisms underlying this therapeutic.

Methods

A simulated chronic wound environment consisting of endothelial cells and inflammatory M1 macrophages co-cultured in 3D was subject to LFLI US at 50, 100, or 150 mW/cm² Spatial-Peak, Temporal-Peak …

Comparative Evaluation Of Deep Learning Models: Resnet18, Minivgg, And Yolov8 For Five-Class Blood Cell Classification, Keita Sakurai

Master's Theses or Doctor of Nursing Practice

Accurate classification of blood cell types is a critical task in automated hematological analysis. This study presents a comparative evaluation of three deep learning architectures, ResNet18, MiniVGG, and YOLOv8, for five-class blood cell image classification. To ensure a fair comparison, all models were trained under standardized conditions, including a consistent 90:10 training–validation split, controlled dataset size, and fixed training epochs. ResNet18 was trained to establish a baseline using residual learning. MiniVGG employed a compact VGG-inspired design with regularization to balance efficiency and accuracy, while YOLOv8 leveraged a lightweight, pretrained classification backbone with integrated data augmentation. Experimental results demonstrate a clear …

Eletric Charging Arm Mechanism - E-Charm, Jacob A. Lewis, Gabriel A. Greer

Williams Honors College, Honors Research Projects

As demand for electric and hybrid vehicles continues to rise, many EV owners rely on home charging in their garages. Gabriel Greer and I’s Senior Design Project, the Electric Charging Arm Mechanism (ECHARM), addresses this by creating a robotic system that autonomously detects a vehicle’s charging port, connects to it, and returns to a rest position when charging is complete. ECHARM is designed as a six-axis robotic arm with wrist and shoulder joints driven by stepper motors through custom cycloidal drive gearboxes. A closed-loop control system using rotary potentiometers ensures precise motion control. At the end of the arm is …

Heat Input Control And Deep Learning-Based Indirect Measure Of Process And Deposition Stability In Wire Arc Additive Manufacturing, Alessandra Caggiano, Giulio Mattera, Yuming Zhang, Roberto Teti

Electrical and Computer Engineering Faculty Publications

A process qualification-oriented data-driven framework for Wire Arc Additive Manufacturing (WAAM) integrating qualification data, process monitoring and feedback control, is presented. A proportional control strategy regulating heat input by varying the Contact Tip–to–Workpiece Distance (CTWD) is developed to enhance process stability, ensure consistent layer geometry and maintain the qualified heat-input conditions for process qualification. To assess the control strategy stability, deep learning-based CTWD soft sensing from high-frequency welding signals is combined with an uncertainty-aware process quality index. The framework is validated on Invar 36 alloy, but it supports extension to other alloys and arc welding-based additive processes.

Work-In-Progress: Evaluating Feasibility Of Band Matrix Solvers For Scaling Up Extreme Learning Machine Method, Anton Akusok, Kaj Mikael Björk, Amaury Lendasse, Leonardo Espinosa Leal

Engineering Management and Systems Engineering Faculty Research & Creative Works

This work presents the results of the potential of band linear system solvers for improving the scalability of the Extreme Learning Machine (ELM) method at large model sizes. The model is tested on the standard MNIST dataset with a range of solvers provided by the SciPy Python library. The results are analyzed taking into consideration the overall performance and the performance impact of band solvers across different matrix bandwidths, as well as the performance versus runtime analysis. The findings show potential in applying the proposed method to very large ELM models with narrow band matrices.

Investigation Of Factors Influencing Electric Vehicle Adoption In Indonesia: Ev Owners’ Perspectives, Desrina Yusi Irawatia, Nur Aini Masruroh, Nur Mayke Eka Normasari

ASEAN Journal on Science and Technology for Development

Electric vehicle (EV) uptake in Indonesia remains markedly below policy benchmarks. This study applies the Unified Theory of Acceptance and Use of Technology version 3 (UTAUT3), an extension of UTAUT2 that incorporates personal innovativeness as an additional construct to examine its impact on both behavioral intention and actual EV adoption within the Indonesian context. Unlike studies that typically survey the general public, this study focuses on actual EV users and owners, providing more representative and responsive insights into real-world EV usage. A total of 208 respondents participated, with 135 from the Jabodetabek area and 73 from Surabaya. The UTAUT3 framework …

Explaining The Unseen: Multimodal Vision-Language Reasoning For Situational Awareness In Underground Mining Disasters, Mizanur Rahman Jewel, Mohamed Elmahallawy, Sanjay Kumar Madria, Samuel Frimpong

Computer Science Faculty Research & Creative Works

Underground mining disasters produce pervasive darkness, dust, and collapses that obscure vision and make situational awareness difficult for humans and conventional systems. To address this, we propose MDSE, Multimodal Disaster Situation Explainer, a novel vision-language framework that automatically generates detailed textual explanations of post-disaster underground scenes. MDSE has three-fold innovations: (i) Context-Aware Cross-Attention for robust alignment of visual and textual features even under severe degradation; (ii) Segmentation-aware dual pathway visual encoding that fuses global and region-specific embeddings; and (iii) Resource-Efficient Transformer-Based Language Model for expressive caption generation with minimal compute cost. To support this task, we present the Underground Mine …

A Deep Neural Approach To Network-Based Obfuscated Malware, Meera Parmar, Sunil Gautam

ASEAN Journal on Science and Technology for Development

The rising prevalence of obfuscated malware poses a critical threat to network security, undermining traditional detection methods and jeopardizing data integrity and system reliability in an increasingly connected world. This growing danger highlights the urgent need for advanced solutions to protect against evolving cyber risks. This research intro-duces a novel framework to enhance malware detection, employing a hybrid architecture that integrates spatial and temporal analysis with attention mechanisms. The approach leverages a large dataset subsample, focusing on key feature selection and augmentation to improve robustness against evasion techniques. This innovative framework offers a significant advancement in identifying malicious network traffic, …

Sadqn-Based Residual Energy-Aware Beamforming For Lora-Enabled Rf Energy Harvesting For Disaster-Tolerant Underground Mining Networks, Hilary Kelechi Anabi, Samuel Frimpong, Sanjay Madria

Mining Engineering Faculty Research & Creative Works

The end-to-end efficiency of radio-frequency (RF)-powered wireless communication networks (WPCNs) in post-disaster underground mine environments can be enhanced through adaptive beamforming. The primary challenges in such scenarios include (i) identifying the most energy-constrained nodes, i.e., nodes with the lowest residual energy to prevent the loss of tracking and localization functionality; (ii) avoiding reliance on the computationally intensive channel state information (CSI) acquisition process; and (iii) ensuring long-range RF wireless power transfer (LoRa-RFWPT). To address these issues, this paper introduces an adaptive and safety-aware deep reinforcement learning (DRL) framework for energy beamforming in LoRa-enabled underground disaster networks. Specifically, we develop a …

A Literature Review And Conceptual Framework For Sustainability In Open-Pit Mine Planning, Raymond Kudzawu-D'Pherdd, Kwame Awuah-Offei, Esteban Koberg De La Cruz, Marcos Goycoolea, Andrea Brickey, Alexandra M. Newman

Mining Engineering Faculty Research & Creative Works

This paper presents a comprehensive literature review and a conceptual framework for integrating environmental sustainability into strategic mine planning, focusing on open pits. Despite growing interest, easily discernible sustainability metrics remain elusive in early mine-planning stages, and are included as a post-processing step, if at all, rather than integrated a priori into a mine plan via, e.g., optimization. Through a literature review, we identify efforts regarding how environmental dimensions, such as emissions, water use, and land rehabilitation, are addressed across mine planning phases. We propose the Environmental Stewardship and Sustainability Framework for Mine Planning, which: (i) embeds sustainability into decision …

Part Ii: Industrial Information Integration Review 2020-2025, Jinzhi Li

Information Technology & Decision Sciences Faculty Publications

Industrial Information Integration Engineering (IIIE) has become increasingly essential for improving operational efficiency and harmonizing heterogeneous industrial systems through advanced digital integration approaches. Fueled by rapid advancements in Industry 4.0 technologies—including digital twins, artificial intelligence, immersive interfaces, and IoT infrastructures—IIIE is substantially transforming traditional enterprise architecture and integration frameworks. This systematic review synthesizes recent developments and emerging trends, with particular attention to the accelerating adoption of digital twins and the deepening convergence between operational technologies (OT) and information technologies (IT) across multiple sectors. While notable progress has been made, significant challenges persist, especially in developing resilient integration architectures and fully …

When Words Flow Like Water: How The Enbridge Line 3 Pipeline Environmental Impact Statement Failed To Prevent Hydrogeologic Harm In Minnesota, Carly Gutzmann

Journal of Earth and Life Science

For the aquifers of Minnesota, the environmental impact statement (EIS) was a promise of protection that never left the page. An environmental impact statement is meant to be an aid in the decision making process in order to ensure that projects consider potential environmental harms that may occur. However, they are often used instead as another regulatory box to check, rather than as active considerations when planning. As such, a project plan can be flawed from the start—if project developers only consider environmental impacts after they have already put considerable time, effort, and funding into their project as-is, they may …

Safety Aware Continual Reinforcement Learning-Based Output Tracking Control Of Nonlinear Continuous-Time Systems, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

An output feedback (OF)-based control scheme utilizing both a scalable multilayer neural network (MNN) observer and actor–critic MNN via integral reinforcement learning (IRL)/adaptive dynamics programming (ADP) approach for a class of nonlinear systems with output constraints is introduced. The proposed observer, critic, and actor MNN weight updates are derived using a singular value decomposition (SVD) of MNN activation function gradient along with output error, Bellman and control input errors, respectively. Next, the approach incorporates continual learning (CL), utilizing a penalty function in the weight update laws for both actor–critic MNNs to consolidate knowledge from previous tasks and enhance learning in …