Engineering Commons^™

Slait - Secure Language Assembly Inspector Tool, Michael Bratcher, Maria Linkins-Nielsen

Electrical Engineering and Computer Science Student Publications

Develop a secure web-based platform that enables users to:

• Upload assembly programs through a browser
• Select instruction inspection points
• Execute code inside an isolated sandbox
• Capture register and flag state changes
• Visualize execution behavior step-by-step

Breach Buddy: Compact Ugv, Zane Hicks, William Stanish, Kyle Gillenwater, Luis Garbanzos

Electrical Engineering and Computer Science Student Publications

This project addresses the challenges of obtaining real-time intelligence in hazardous environments, where personnel face significant risks and many existing systems face significant drawbacks.

Aurora Display - Autonomous Dashboard For Smart Spaces, Isabella Bretthauer, Zach Collins

Electrical Engineering and Computer Science Student Publications

Aurora Display is a low-cost, API-driven digital signage platform for public environments. Built on Raspberry Pi 4B, it retrieves and normalizes real-time data from multiple sources and displays it through a modular tile interface. Local caching and fallback states ensure continuous, autonomous operation. A working prototype demonstrates adaptable deployment, sustainable operation, and continuous real-time, context-aware, information delivery.

Skin Cancer Detection App, Nicholas Rincon-Speranza, Lawson Darrow, Nikiraj Konwar, Christian Stevens

Electrical Engineering and Computer Science Student Publications

Skin cancer is one of the most common cancers, and early detection greatly improves outcomes.

Many people do not have quick or easy access to a dermatologist for an initial screening.

Our goal was to build a mobile app that can analyze a lesion image and provide a fast preliminary prediction on device.

This is not meant to replace a doctor, but to serve as an accessible screening aid that encourages earlier follow-up.

Diode-Pumped Solid-State (Dpss) Laser, Ryan Farrar, Kiahna Taylor, Jules Stone, Finn Mcmanus, Zoe Kreisler, Reis Knowles

Electrical Engineering and Computer Science Student Publications

The objective of this project is to create a working Nd:YAG laser design using an 808nm laser instead of a traditional flashlamp. The reason for the 808nm laser is to enable controlled lasing, and furthering accuracy & efficiency relative to a flashlamp.

Edge Vision, A. Dookeran, L. Kahveci, K. Voelstad Bogen, M. Yanke

Electrical Engineering and Computer Science Student Publications

Assisted feeding requires real-time detection of: 

• Food locations of varying types 
• Mouth positions of where to feed. The system shall accurately detect and return the coordinates of the aforementioned while being able to execute on the NVIDIA Jetson Orin Nano.

Electric Vehicle, Terence Lee, Troy Stephens, Corbin Williams

Electrical Engineering and Computer Science Student Publications

This project focuses on the research, design, and implementation of a traction inverter for the M- 9000-MACHE "Eluminator" electric motor. The work transitions the control and power stages from previous custom prototypes to industrial-grade evaluation platforms to achieve a stable motor spin. This phase integrates a Silicon Carbide (SiC) MOSFET power stage with a real-time TI C2000 control architecture, serving as a critical step in a multigenerational research initiative to develop a modular electric vehicle traction framework.

Rapid Reach, Rishi Ammanabrolu, Alex Dumbell, Peyton Hay, Ashley Hurtado, Ryan Matthews, Mac Mchale, Sean Miller, Dan Zschau

Electrical Engineering and Computer Science Student Publications

Survival of out-of-hospital cardiac arrest depends on rapid heart defibrillation, yet automated external defibrillator (AED) retrieval, high acquisition costs, and maintenance requirements often limit unit availability. Consequently, the delay inherent in traditional manual retrieval and EMS arrival frequently prevents aid from reaching victims in time.

Chess Observation Based Operable Technology (Cobot), Brandon Goerz, Jeremy Hay, Luke Jacobsen, Sean Kalkiewicz, Logan Steele

Electrical Engineering and Computer Science Student Publications

This project aims to develop an autonomous robotic chess system capable of interpreting board state and physically executing moves. With a focus in real time against a human opponent. Utilizing integrating computer vision, game logic, user friendly GUI, and a robotic arm.

Srcis: Human-Robot Collaboration In Urban Search And Rescue Operations, Younghoon Cho, Yavanni Ensley, Jaylin Ollivierre

Electrical Engineering and Computer Science Student Publications

Search and Rescue Coordinated Intelligence System (SRCIS) is a human-agent system designed to:

• Improve the effectiveness of real-time search and rescue operations.
• Integrate human judgement with robotic autonomy and capabilities
• Enable coordinated action and adaptive response in dynamic environments.

Revu: Project Development Platform, Arisa Laloo, Chervelle Pierre

Electrical Engineering and Computer Science Student Publications

The development of Artificial intelligence (AI) tools has created new challenges for instructors.

Revu is designed to encourage students to build a deeper understanding of their projects through consistent interaction.

Ortega Observatory Weather Station, L. Collins, B. Erskine, L. Houck, E. Kornbau

Electrical Engineering and Computer Science Student Publications

The team’s mission was to create an automated weather station with a convenient display to give information on conditions that affect the ability to observe such as rain and wind, in addition to performing necessary maintenance or repair on the Ortega Observatory and aiding in the construction of the PCB that will control the telescope movement arms.

Nocap: Article Fact-Checking With Ai, Thomas Chamberlain, Anthony Ciero, Varun Doddapaneni, Joshua Pechan

Electrical Engineering and Computer Science Student Publications

Fact checking media is important for properly obtaining information

Create a website that uses AI knowledge to allow users to fact check an article

Give these articles an authenticity score and report on what is fact or fiction

Aggregate scores of articles by the same publisher in a database allowing users to view their scores and article authenticity reports

Competitive Programming Primer, Jon Ayuco, Pedro Marcet, Ivan Marriott

Electrical Engineering and Computer Science Student Publications

Helps first-year CS/SWE Students that are confused on how advanced algorithms work.

Professors can give a visual aid in-class.

Encourages unsure students interested in Competitive Programming a low-risk place to practice

Remotely Controlled Car Via Lte/Wi-Fi, Nicholas Shenk, Christian Prieto, Joseph Digafe, Donoven Nicolas

Electrical Engineering and Computer Science Student Publications

PROBLEM 

• Professionals must enter dangerous environments just to gather information 
• Existing robotic systems are expensive and complex
• Communication links are often unreliable or high-latency
• Limited real-time feedback reduces decision-making ability

Cali: Cobot Autonomous Living Interface, Nicholas Santamaria, Heber Lopez, Berke Celal Dogan

Electrical Engineering and Computer Science Student Publications

The CALI (Cobot Autonomous Living Interface) system is an assistive robotic platform designed to help individuals with limited mobility eat independently. CALI integrates computer vision, neural networks, and robotic motion control to detect food items on a plate and deliver them safely to a user. By combining AI perception with precise robotic control, the system demonstrates a practical application of assistive robotics.

Cardiac Image Reconstruction From Low-Dosage Spect Scans Via Deep Learning (Cirfldssvdl), Evan Gunderson, Timothy Shane, Alexander Thoms

Electrical Engineering and Computer Science Student Publications

● Single-Photon Emission Computed Tomogrophy (SPECT) scans are a type of medical scan ● A patient is injected with a radiotracer, which emits gamma rays that are detected by gamma cameras that rotate around the patient ● Using a series of images collectively referred to as a sinogram, a 3D reconstruction of the patient is created using techniques such as Maximum Likelihood Expectation Maximization (MLEM) ●MLEM takes a long time, but using a neural network can speed up the reconstruction process and allow for a lower dosage of radiotracer to be used

Microgravity Simulator, Aruna Dookeran, Alexander Montano, Elias Orellana, Aiden Smart

Ocean Engineering and Marine Sciences Student Publications

Microgravity significantly affects biological growth, but space-based experiments are costly and difficult to access. Ground-based systems provide an alternative; however, many require continuous manual supervision to maintain operating conditions.

Advances In The Design Of Bio-Organic Resistive Switching Memory, Muhammad Awais, Yi Sheng Wong, Feng Zhao, Kuan Yew Cheong

Electrical and Computer Engineering Faculty Research & Creative Works

Bio-organic materials have garnered significant attention as sustainable candidates for non-volatile resistive switching memory (RSM) because of their specialized chemical, structural, and environmental advantages. This review presents a design-centered perspective on bio-organic RSM by outlining the key device components required for effective device engineering, including electrode materials, memristive thin films, intermediate layers, substrates, and electrical measurement strategies. Each component is discussed in detail with respect to the material properties and operational parameters that influence overall device performance, such as functional groups, interfacial interactions, and processing conditions. The review further analyses the critical roles of electrode pairing, interfacial chemistry, additive incorporation, …

A Trojan Attack On Tdma Synchronization In Energy-Harvesting Wireless Networks, Ethan Berei

ONU Student Research Colloquium

This paper investigates a Trojan attack targeting the time-division multiple access (TDMA) synchronization mechanism in single-hop energy-harvesting wireless networks. The attack compromises a single node, which subtly skews its transmission timing to operate outside its assigned time slot, causing localized transmission overlaps and triggering repeated network-wide resynchronization events. This behavior shortens the synchronization interval, significantly increases control-plane traffic, and leads to higher energy consumption and delay in energy-constrained networks. The attack is modeled within a finite state machine (FSM) framework and experimentally evaluated under varying energy-harvesting conditions. Experimental results show that the number of synchronization events can increase by up …

​ Planning, Control, And State Estimation For Chain-Style Modular Robots​, Sebastian Theiler, Yucheng Nie, Joshua P. Kevil

Electrical and Systems Engineering Capstone Design Projects

Traditional robots have fixed shapes, limiting their ability to adapt to complex or dynamic environments. Modular robotic systems are composed of identical robot modules that can connect and disconnect to form different structures. This allows the robots to form bridges to cross voids and split apart to fit into tight corridors. However, while previous modular robotics research heavily emphasizes reconfiguration planning, comprehensive motion planning remains underexplored. We introduce a novel, end-to-end framework for the planning, state estimation, and control of chain-style modular robot swarms. Our system includes a custom network flow planner that maps polygonal environments into a Reeb graph …

Integration Of Bayesian Networks And Neural Networks For High-Dimensional Data Analysis, Cooper Schmer

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

High-dimensional biomedical datasets, such as omics data, present significant challenges for predictive modeling due to noise, redundancy, and computational complexity. This thesis proposes a hybrid framework that integrates Bayesian Networks (BNs) and Artificial Neural Networks (NNs) to improve classification performance of such data sets while reducing input dimensionality. Central to this work is a novel feature selection method based on d-separation, a structural property of Bayesian networks that encodes conditional independence relationships.

The proposed approach introduces a count-based d-separation metric to quantify the relevance of variables to a target outcome, along with a thresholding scheme to balance feature selection robustness …

Piano Aid, Christopher G. Sayers, Tyler Baugus, Gabby Taunton

Create@State

Pianos provide recreational and educational value and is a cornerstone of the culture experienced worldwide today. Despite the many benefits and enrichment music brings these benefits are often inaccessible or difficult to learn by most people but especially to those of the Deaf and Hard of Hearing (DHH) community due to its innate auditory nature. While adaptive instruments have been proposed to address this gap, many remain conceptual or fail to reach production because of high development costs and limited commercial markets. This project presents an economically feasible alternative in the design of an adaptive digital piano that enables both …

Physiobridge: Physiology-Constrained Self-Supervised Foundation Model For Cross-Device Ecg–Ppg Learning With Conformal Risk Control, Abbas Alzubaidi, Ali Al-Shuwaili, Ali Al-Bayaty

Electrical and Computer Engineering Faculty Publications and Presentations

Wearable and bedside sensors continuously generate electrocardiograms (ECG), photoplethysmograms (PPG), and related physiological waveforms that could enable earlier detection of deterioration and more personalized care. However, current deep learning pipelines in biomedical signal processing often remain taskand device-specific, degrade under domain shift (new hospitals, sensors, skin tones, motion), and provide limited uncertainty information for safety-critical decisions. We propose PhysioBridge, a foundation-model approach that learns a shared representation space for ECG and PPG via self-supervised pretraining and explicit physiology constraints, then supports downstream adaptation with distribution-free risk control. PhysioBridge introduces (i) multi-rate patch tokenization that preserves clinically meaningful morphology across heterogeneous …

Improving The Circuit Realization Of Grover’S Quantum Search Algorithm By Replacing Hadamard With √ × Gates, Ali Al-Bayaty, Ali Al-Shuwaili, Abbas Alzubaidi, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

Jozsa, Bernstein-Vazirani, and Grover, utilize Hadamard gates to create uniform superposition states for the input qubits of an oracle. However, Hadamard gates are non-native (non-supported) gates in all real quantum computers. For this reason, Hadamard gates are considered cost-expensive gates when realizing (transpiling) such algorithms into a real quantum computer. This paper introduces a new methodology for cost-effective transpilation of Grover’s algorithm into real quantum computers, by replacing all Hadamard gates with √ X gates. In quantum computing, the Hadamard and √ X gates create uniform superposition states of a qubit on the Xaxis and Y-axis of the Bloch sphere, …

Techno-Economic Analysis Of Hybrid Systems As A Solution For Electricity Supply During The Dry Season At The Bakaru Run-Of-River Hydropower Plant, Zamharir Aditya Febri, Mohammad Akita Indianto, Sheila Tobing

Journal of Materials Exploration and Findings

Within the South Sulawesi power system (Sulbagsel), the Bakaru Hydro Power Plant serves as a key facility expected to provide consistent and reliable electricity supply. However, since the Bakaru plant operates under a Run of River scheme, its energy output is highly dependent on river discharge rates. In 2024, a significant decrease in water flow was recorded between August and October, which led to a drastic reduction in power generation. To address this challenge, a hybrid energy system is proposed to ensure continuous load coverage, particularly during the dry season. The optimal configuration of this hybrid system was modeled and …

Temperature Determination And Scene Change Artifact Mitigation When Using Fourier-Transform Spectroscopy On Targets With Time-Varying Temperature, Kode A. Wilson, Michael L. Dexter, Benjamin F. Akers, Anthony L. Franz

Faculty Publications

Fourier-transform spectroscopy is a widely used technique for determining the spectral and thermal properties of a target. However, target temperature variations during measurement can compromise the spectral accuracy. Temperature fluctuations induce oscillations superimposed on the target spectrum. These oscillations, referred to as scene-change artifacts, degrade the spectral accuracy. The literature is divided, with theoretical predictions suggesting negligible artifacts and growing experimental evidence reporting significant artifacts. This paper presents a theory and experimental validation of scene-change artifacts originating from target temperature variations. Traditionally, the interferogram offset is assumed to be constant, an invalid assumption for a changing scene. The error is …

Leveraging Convolutional Neural Networks For Through-The-Wall Radar Imaging: Challenges, Impacts, And Future Directions, Tumaini Edgar, Abdulla F. Ally, Abdi T. Abdalla

Tanzania Journal of Engineering and Technology (TJET)

Through-the-wall radar imaging (TWRI) is an essential technology for military and rescue applications; however, its performance in detecting and visualizing high-quality images of targets behind walls is significantly degraded by multipath reflections and signal attenuation. This paper reviews the current state of TWRI and its challenges, and explores the transformative potential of deep learning, particularly convolutional neural networks (CNNs), in addressing these challenges. Peer-reviewed articles published from 2018 to 2024 were analysed to examine CNN applications in addressing TWRI challenges. The analysis reveals that using CNNs, TWRI systems can be more effective by filtering wall distortions, reducing noise, lowering computational …

Emergent Dynamics In Multiplex Social Networks: Agent-Based Modeling Of Information Diffusion For Misinformation Control, Harshvardhan Prabhakar Ghongade, Anjali Ashokrao Bhadre, Shivani Agarwal, Harjitkumar Uttamrao Pawar, Harshal Subhash Rane

Northeast Journal of Complex Systems (NEJCS)

Information misrepresentation is widespread in multi-layered social networks which provide multiple avenues to communicate information. As such, it presents significant opportunities for both information integrity and public discourse to be undermined by disinformation. This paper outlines a new agent-based model, developed to capture emergent dynamics of multi-layered social networks and to help identify technical means to mitigate information misrepresentation in complex systems. A key component of this research includes a novel Multi-Layer Information Diffusion Model (MLIDM), integrating both cross-layer communication among agents, as well as heterogeneous agent behaviors and adaptive intervention strategies. Our methods employ a three-stage process to model …

Efficient Intrusion Detection For Iomt: Integrating Machine Learning, Feature Selection, And Fuzzy Logic, Ghaida Mansour Balhareth

Electronic Theses and Dissertations

The internet of medical things (IoMT) has transformed healthcare by enabling real-time patient monitoring, remote diagnoses, and effective data exchange among connected medical devices and clinical systems. The increasing reliance on interconnected medical equipment has also intensified cybersecurity risks, as resource-constrained devices and wireless communication channels are vulnerable to attacks such as man-in-the-middle, spoofing, data injection, and ransomware. Intrusion Detection Systems (IDSs) play a critical role in mitigating these threats; however, traditional IDS approaches often struggle with high-dimensional IoMT data, class imbalance, and uncertainty in traffic patterns, which can increase false alarms and reduce reliability in safety-critical environments. This dissertation …