Other Electrical and Computer Engineering Commons^™

Multi-Modal Tensor Fusion For Alzheimer’S Disease Recognition, Mason Li, Tiffany Le, Jiajing Huang, Yuxin Wen

Engineering Faculty Articles and Research

Accurate and early diagnosis of Alzheimer’s disease (AD) is critical for effective intervention, disease monitoring, and patient care. Traditional diagnostic approaches rely on a single modality, such as clinical assessments, neuroimaging, or genetic markers, which may fail to capture the complex, multifaceted nature of AD. Multimodal learning has therefore been explored to integrate complementary information across data sources. However, conventional fusion strategies, including early feature concatenation and late decision-level fusion, often model modalities independently and fail to capture high-order cross-modal interactions. To address these limitations, we propose a multimodal tensor fusion network (MTFN) that integrates heterogeneous data sources, including visual …

Enhanced Cuckoo Search-Based Optimization For Single Distributed Generation Placement And Sizing In Radial Distribution Systems, Samson Oladayo Ayanlade, Abdulrasaq Jimoh, Richard Oladayo Olarewaju, Ignatius Kema Okakwu, Israel O. Adejumobi, Joseph B. Samson, Oluwadare A. Adebisi, Oluwadare O. Akinrogunde

Al-Bahir

This paper presents an Enhanced Cuckoo Search Algorithm (ECSA) to optimally place and size Distributed Generation (DG) in radial distribution systems to minimize real power loss within operating constraints. The proposed ECSA has exponentially decaying adaptive Lévy flights, constraint-aware solution repair with dynamic penalty coefficients, and diversity-directed stochastic replacement to enhance search robustness and convergence speed. It was tested with 30 independent runs on the IEEE 33-bus, IEEE 69-bus, and a practical Nigerian 32-bus distribution network. The simulations show that the ECSA lowers the active power loss of the IEEE 33-bus system from 201.58 kW to 102.75 kW (49.03%), and …

Sustainabake, Kevin Kunta Swanson Ii

Electrical Engineering

This senior project outlines the development of an oven that utilizes renewable energy to operate safely and effectively. It aims to test building an oven using mostly basic hardware students acquired during their time at Cal Poly and provide a starting point for those interested in creating a solar-powered oven. As our society continues to innovate and increasingly relies on electricity, it is important to place more emphasis on how we can make our lives sustainable to take care of our environment without introducing excessive pollutants. Food preparation is a daily activity that typically involves significant energy consumption, making this …

Flexible Fault-Tolerant Multi-Die Fpga-Based Architectures For Varying Space Environments, Yosof Ali Seif El Din Ali Maklad

Theses and Dissertations

It is well-known fact that spacecraft’s electronic components operate in an extreme harsh and varying space environments, beside changing orbit or passing through Van Allan Belts during orbital course results of radiation levels change. This thesis focuses on SRAM-based FPGA systems on-board of such spacecrafts, that are commonly utilized in space applications’ critical applications due to their capabilities and flexibility to reconfigure, since these systems are vulnerable to frequent negative impacts of ionizing radiation, thus inducing soft and hard errors leading to disastrous failures that could jeopardize the entire spacecraft. The soft errors’ effects are frequent yet can be mitigated, …

Code-Net++: An Attention-Guided Deep Learning Framework With Grad-Cam-Based Explainability For Covid-19 Detection Using Chest X-Ray Images, Fareesa Amina, Dr Krishnanaik Vankdoth

Mansoura Engineering Journal

Chest radiograph imaging has emerged as a practical and scalable diagnostic modality for respiratory diseases, including COVID-19. However, accurate discrimination of COVID-19 manifestations from other pulmonary abnormalities remains challenging because of low contrast, imaging noise, and overlapping radiographic patterns. This work presents CODE-NET++, an enhanced attention-guided deep learning framework with Grad-CAM-based explainability for reliable COVID-19 detection using chest X-ray images. The proposed framework integrates adaptive trilateral filtering for image enhancement, Reverse Edge Attention Network (RE-Net) for lesion-aware segmentation, and an Enhanced LinkNet architecture with dilated convolutions for multiscale feature extraction and classification. Grad-CAM-based explainable artificial intelligence visualization is incorporated to …

Μmodules: A Low-Cost, Eurorack-Compatible Modular Audio Synthesis System, Nolan K. Juneau

Honors Theses and Capstones

The modular audio synthesizer is one of the fastest-growing industries in contemporary music technology. Unlike a traditional audio synthesizer, a modular synthesizer allows for the user to directly control the signal path and effects of the synthesized sound, allowing for a workflow that is completely customizable to an individual musician and their creative vision. However, the modules and cases currently in production for the common “Eurorack” design standard can be prohibitively expensive to new users, often costing thousands of dollars for even a small system. The µModules project aims to eliminate this financial barrier to modular synthesis by using inexpensive …

Advancing Task-Oriented Dialog Systems: Scalability, Generalization, And Evaluation, Adib Mosharrof

Theses and Dissertations--Computer Science

Task-oriented dialog (TOD) systems enable conversational interfaces for complex tasks like flight booking and restaurant reservations. However, deploying TOD systems at scale faces three critical barriers: scalability, generalization, and evaluation. Scalability is primarily restricted by the human-annotation bottleneck, as current systems depend on vast quantities of manually labeled data for every new domain, making deployment prohibitively expensive. Generalization remains a persistent challenge, as systems optimized for known domains often suffer significant performance degradation when encountering new, unseen ones. Existing evaluation metrics measure response quality and fluency, but fail to measure functional task success. As TOD systems are deployed across diverse …

Control System Emendation And Ai-Driven Optimization For Enhancing A Smart Residential Microgrid, Anthony Nyoyoko

Master’s Theses

This thesis began with a simple idea: to restore the control system of a smart residential microgrid to respond intelligently to electricity prices while remaining safe, reliable, and practical on low-cost hardware. At the start, the goal was to design an economically aware microgrid that could look at electricity prices from the PJM market and make better operational decisions than traditional rule-based control. The motivation was straightforward. As residential renewable energy adoption increases, microgrids are expected to do more than just supply power. They are expected to respond to price volatility, integrate renewable generation, and operate reliably using embedded controllers …

Texels: A Programmable Textile Interface For Replicating Textures, Maya E. Eusebio

Honors Undergraduate Theses

Self-moving fabric interfaces have massive potential for applications in fields ranging from art to haptic feedback to deployable space structures. However, current systems of implementation face the impracticalities of bulkiness, burnout, and energy consumption on top of limiting designs that can only contract uniformly or create one pre-programmed shape. For this technology to bring the change that it promises, we must break the barriers of usability and sustainability to make it a practical choice. This thesis aims to develop a scalable model of fabric that designers, programmers, and anyone else can acquire or create with accessible materials, integrate into design …

State-Dependent Queueing For Adaptive Signal Control: A Simulation-Based Performance Evaluation, Shaimaa Alseddiek, Usama Elrawy Shahdah, Hala B. Nafea, Hossam El-Din Moustafa, El-Said Ahmed Marzouk, Mohamed M. Ashour

Mansoura Engineering Journal

Urban traffic congestion persists as a critical challenge to transportation system efficiency, sustainability, and safety. Traditional queuing models utilizing fixed service rates inadequately represent the dynamic feedback between congestion and capacity in real vehicular flow. State-Dependent Queuing Models (SDQMs) address this limitation by modelling service rate as a function of queue length or density. This research advances SDQM application for adaptive traffic signal control through development of a calibrated state-dependent departure rate implemented within a microscopic simulation environment using SUMO and TraCI. Six control strategies including fixed-time, actuated, and two SDQM variants were evaluated across traffic demands ranging from undersaturated …

Biosecure-Llm Framework: Protecting Llms From Cyberbiosecurity Threats And The Case For Independent Ai Safety Governance, Xavier-Lewis Palmer, Lucas Potter, Srdjan Lesaja, Sotirios Karathanasis, Mohammad Ghasemigol

Computer Science Faculty Publications

Large Language Models (LLMs) are becoming critical infrastructure in scientific, healthcare, and governmental contexts. As frontier AI laboratories increasingly partner with government agencies, a fundamental question arises: Who should control the safety and policy-enforcement layers that constrain model behavior? Current safety mechanisms (LLM guardrails) are typically designed for generic "harmlessness" and operate by detecting semantic patterns and refusing requests. However, they are inadequate governance instruments because they cannot implement auditable, domain-specific controls tied to external regulatory policy objects (e.g., control lists or rules governing personally identifying information). Even a perfectly aligned model is not able to express institution-specific policy without …

Development Of Periodic Plasmonic Nano-Structures For Enhanced Labeled Bio-Sensing Systems, Kyle Zackary Smith

Graduate Theses, Dissertations, and Problem Reports (ETD)

The biomedical industry has seen sustained growth over the past half century, with a continually increasing demand for flexible, easy-to-use, and cost-effective tools. One large area of commercial interest has been point-of-use or point-of-care diagnostics, using optical based Lab-On-Chip (LOC) style systems. Label and label-free fluorescence detection systems are common benchtop modalities that have seen recent integration into these portable, cost-effective LOC applications. However, despite their maturity, there are still opportunities to improve device characteristics, specifically in reference to throughput, limit-of-detection (LOD), and hybrid integration (along with associated costs).

Optical research avenues at WVU have focused on improving these systems …

Cache-Conscious Sparse Matrix Dense Matrix Multiplication On Gpus, Haoqiang Guo

LSU Doctoral Dissertations

Over the past decade, high-performance deep learning has evolved into a critical research domain, driven by the demand for efficient models and high inference throughput. Deep learning architectures have shifted from stacked convolutional layers to transformer-based models, while pruning techniques and graph-structured data have established sparse matrix–dense matrix multiplication (SpMM) as a fundamental kernel—particularly in graph neural networks (GNNs). Modern GPUs, with their massive parallelism and high-bandwidth memory, offer immense potential for accelerating these workloads. While SpMM implementations using the compressed sparse row (CSR) format remain common to avoid conversion overhead, preprocessing-based methods have recently demonstrated superior potential. In GNN …

Ai-Optimized Resource Management In Next-Gen Wireless Networks, Fatemeh Lotfi

All Dissertations

Next-generation wireless networks must deliver highly adaptive, scalable, and intelligent connectivity to satisfy the heterogeneous demands of emerging services, including enhanced mobile broadband, massive machine-type communications, and ultra reliable low latency applications. The Open Radio Access Network (O-RAN) paradigm has emerged as a key enabler of this vision, introducing openness, virtualization, and artificial intelligence (AI)-driven control into the RAN ecosystem. O-RAN’s disaggregated architecture facilitates multi-vendor interoperability and empowers intelligent management through the RAN Intelligent Controller (RIC). However, achieving real-time, autonomous, and generalized optimization in such a dynamic environment remains a significant challenge due to its distributed nature, non-stationary traffic, and …

Series Resonant Converters With Medium Voltage Sic Mosfets For Electric Aircraft Applications, Xinyuan Du

Graduate Theses and Dissertations

To develop high-performance high- power-density MV power converters, the emerging silicon carbide (SiC) devices are more attractive than their silicon (Si) counterparts, since the fast switch frequency brought by the SiC can effectively reduce the volume and weight of the filter components and thus increase the converter power density. From the converter topology perspective, with the MV dc distribution, the single stage isolated dc/dc converter are suitable for next-generation electric aircraft system due to soft switching and high power density. In this work, comprehensive static and dynamic characterizations were conducted for the latest 6.5 kV silicon carbide (SiC) MOSFETs from …

Design And Testing Of A Gallium Nitride Power Amplifier For High-Temperature Radar Applications, Walker Landry Harbison

Graduate Theses and Dissertations

This thesis offers the design, fabrication, and evaluation of a gallium nitride (GaN) power amplifier integrated circuit (IC) intended for high-temperature radar applications. Radar systems are used in many different applications, such as defense, aerospace, and weather. For their function, these systems require high power, efficiency, and reliability under a wide range of operating conditions. Taking advantage of the material properties of GaN, including its high breakdown voltage, wide bandgap, and thermal conductivity bolstered by the use of silicon carbide in the substrate, this work focuses on examining amplifier performance in both ambient and elevated temperature conditions. The PA was …

Parentcoach: Designing An Mhealth Parenting App To Enhance Parental Involvement In Adhd Support, Franceli L. Cibrian, Nancy Herrera, Jesus A. Beltran, Lucas M. Silva, Mikaela Pulse, Kayla Anderson, Cassie Zeiler, Luc Rieffel, Daniel I. Lee, Sabrina E. B. Schuck, Kimberley D. Lakes

Engineering Faculty Articles and Research

Introduction: Parents play a vital role in supporting self-regulation and managing behaviors in children with Attention-Deficit/Hyperactivity Disorder (ADHD). However, many face barriers to accessing consistent, evidence-based support. Mobile health (mHealth) technologies offer a promising way to deliver flexible, low-burden guidance for parents on best practices and strategies to support their children's self-regulation. However, designing them is non-trivial.

Objective: This paper introduces ParentCoach, a mobile application designed to support parents of children with ADHD through brief daily lessons, reflection prompts, and skill-building activities.

Methods: ParentCoach was developed in two phases: (1) secondary analysis of qualitative data from over 30 families …

User Interface And Watchstation Improvements Required For Multi-Vehicle Usv Operations, Val Schmidt, Joshua Bergeron

Faculty Publications

In October 2024, the University of New Hampshire and NOAA’s Uncrewed Systems Office embarked on a mapping mission in the Gulf of Maine, simultaneously operating two DriX Un-crewed Surface Vehicles. Goals of the project were focused on testing hypotheses related to concepts of operation, including the safety of operations, cognitive loading of operators, management of vehicle endurance, vehicle logistics, maintenance and field support, refueling and a host of others.

Design Considerations For Conversational Agents To Assess The Social-Emotional Well-Being Of Young Children In Low-Income South African Communities, Lucretia A. Williams, Elizabeth A. Ankrah, Catherine E. Draper, Caylee J. Cook, Franceli L. Cibrian, Jesus A. Beltran, Kimberley D. Lakes, Gillian R. Hayes

Engineering Faculty Articles and Research

A variety of digital technologies have been used to support early childhood development (ECD) programs in low-income South African communities. Even though technology has provided opportunities to increase access to health interventions, the lack of trust and socio-economic constraints under which these tools would need to work pose complex challenges. We examine home visitors’ work processes, experiences, and preferences of a conversational agent to support their work of administering social-emotional well-being assessments to young children ages 0-5. Analysis of the results of focus groups with 51 home visitors indicates the need for designing conversational agents that support ECD in the …

Ai-Powered Accessibility Tracker For Inclusive Public Spaces, Yenny Ma, Kevin Beltran

College of Engineering Summer Undergraduate Research Program

This research project will develop and evaluate a smartphone-based, AI-powered system to crowdsource and analyze accessibility features and barriers in public spaces. Using computer vision and geospatial mapping, the system will identify and categorize issues such as uneven sidewalks, missing or inadequate curb ramps, damaged tactile paving, obstructive overhangs, and the absence of visual or auditory wayfinding cues. The overarching goal is to generate a dynamic, real-time accessibility map that empowers individuals with diverse mobility, sensory, and cognitive needs to navigate public spaces more safely and confidently. The project will integrate technologies and methods from applied machine learning, mobile computer …