Computer Engineering Commons^™

Breaking New Ground: Division Directly In Memory, M. Hassan Najafi, Mehran Shoushtari Moghadam

Faculty Scholarship

In-memory computing (IMC) has emerged as a promising paradigm for overcoming the limitations of traditional von Neumann architectures by reducing data movement and enhancing computational efficiency. Despite significant advancements in this area, implementing complex arithmetic operations, such as division, directly within memory has remained an elusive challenge. This paper introduces a pioneering technique for performing division operations directly in memory, representing the first successful integration of such functionality into the IMC framework. Our approach leverages an innovative circuit based on an unconventional model of computing–stochastic computing (SC). Our technique extends the computational capabilities of IMC systems and paves the way …

Retracted: Data Envelopment Analysis Using Stochastic Frontier Analysis And Bootstrap Confidence Intervals, Fahad F. Alqahtani

Iraqi Journal for Computer Science and Mathematics

Evaluating company growth potential has moved away from traditional financial focused ratios and ratios analysis that has origins in the early twentieth-century economics. However, these conventional methods might not be accurate in measuring such efficient factors as this combined proposed framework of Data Envelopment Analysis (DEA) and improved mathematical models do. The present research focuses on the prospect of growth of companies through evaluating the performance of 40 DMUs in terms of efficiency DEA and MMTs. DEA is used to determine the efficient DMUs while SFA underline the factors such as investment on research and development, effective marketing strategies and …

A Hybrid Technique For Approximating The Solution Of Fractional Order Partial Integro-Differential Equations, Ahmed K. Mohsin, Fajir A. Abdulkhaleq, Osama H. Mohammed

Iraqi Journal for Computer Science and Mathematics

In this paper, we discuss the numerical solution of fractional order partial integro-differential equations. The type of fractional derivative used is a Caputo derivative. The method proposed in this paper known as transform optimal perturbation iteration method. This method combines the optimal perturbation iteration method and the Laplace transform in order to converge to the exact solution. The proposed method is highly efficient and provides the means of controlling the approximate solutions convergence. Illustrative examples prove that the suggested approach is very accurate when compared with the exact solution and the results of the existing methods.

Dna Storage Of Images: From Pixels To Molecules, Cihan Ruan

Engineering Ph.D. Theses

DNA storage is rapidly emerging as a transformative solution for long-term, ultra-dense, and energy-efficient archival systems. This dissertation builds upon a deep understanding of image compression principles to design encoding frameworks that are uniquely attuned to the biochemical constraints of DNA storage. By fusing insights from traditional coding with molecular-level design, we develop a series of technically advanced solutions tailored for this emerging medium.

Our first contribution introduces Dynamic DNA-Fountain, a constrained codec that maps H.266 /VVC-compressed bitstreams to quaternary DNA sequences, optimizing for both information density and biochemical synthesis constraints. Building upon this foundation, we shift focus toward robustness—leveraging …

Adaptive Oversight In Action: Proposing Context-Aware Governance For Ai In Cybersecurity, Russell S. Cunningham

Boise State Graduate Student Projects

Artificial intelligence is increasingly woven into cybersecurity operations, shaping everything from threat detection to automated incident response. While these technologies improve speed and scalability, they also raise urgent questions about governance, ethical use, and operational risk. Although frameworks such as the NIST AI Risk Management Framework, ISO/IEC 42001, the EU AI Act, IEEE's Ethically Aligned Design, and OECD AI Principles each offer structure, they tend to address only parts of the problem. Most focus on compliance or ethics but rarely both, and few are tailored to the high-pressure, risk-sensitive environments found in cybersecurity.

To bridge these gaps, this research proposes …

Gpu-Based Visual Effects System, Matthew Jaffe

Programming Theses and Dissertations

The objective of my thesis is to create a robust and efficient VFX system that can be used to edit and add particle effects to games. This system utilizes a compute shading pipeline to simulate millions of particles in real time. The behavior of particles is widely customizable through many different properties which can be manipulated changed over the lifetime of particles and introduce procedural randomness. There are many ways to customize the motion of the particles with various forces and collision. Additionally, particles can be rendered as billboarded quads, full meshes or partial meshes with different settings to further …

Design And Implementation Of A Notification System For The Purpose Of Improving Communication Between Nurses And Patients, Aindrila Bhattacharya

2025 Spring Honors Capstone Projects - Archive

Communication is an important part of how nurses administer treatment to their patients. Without proper communication, it is difficult for the nurses to connect with their patients and vice versa. This paper will be going into some previous literature about communication between patients and nurses in general, communication with respect to pediatric patients and how notification systems have been implemented in the past. It will then discuss the methodology and implementation of a notification system for a medical app. The medical app is meant to facilitate communication from the side of the patient to the nurse, while the notification system …

Controlling A Mobile Inverted Pendulum And Optimizing Leaning Angle To Apply Force Using Reinforcement Learning, Aryan Mediratta

2025 Spring Honors Capstone Projects - Archive

Reinforcement Learning is a Machine Learning paradigm that involves simulating learning through rewards and penalties in intelligent systems. This technique is often employed in robotics when traditional control methods are insufficient or when human intuition does not provide a good solution on how to control robot systems, This project involves training a Segway-style Mobile Inverted Pendulum (MIP) robot to balance and push a box forward. The BeagleBone Blue board is used that includes a built-in Inertial Measurement Unit (IMU) and encoder ports. These sensors enable the system to measure its current state. The goal is to find the optimal leaning …

Integration Of Notes Section With Access Management, Inshaad Merchant

2025 Spring Honors Capstone Projects - Archive

This research explores the development of a notes section with access management, specifically designed to assist Computer Science and Engineering students to revisit and revise all the notes and key points highlighted in their tutoring sessions. While the senior design project focuses on the CSE Student Success Center application that allows students to schedule tutoring sessions, manage appointments, and manage their profiles within this application, the Honors capstone project adds on a specific section for students to save all their notes and important video links and attachments to continue their learning outside of the tutoring sessions. A centralized platform for …

Development Of A Cost-Effective Daq For Measuring Brake Performance In Race Cars, Adrin Alias

2025 Spring Honors Capstone Projects - Archive

This project explores the feasibility of creating a cost-effective data acquisition (DAQ) system for high-speed, real-time brake performance testing of Formula SAE racecars. The research addresses the limitations of the current MoTeC DAQ system currently employed by the team, which is costly and time-consuming to set up for on-car testing. The team will use a brake dynamometer for steady-state comparisons of different brake pad compounds (senior design project), but evaluating real-world performance requires on-car testing. By systematically comparing various hardware platforms, sensors, communication protocols, and storage solutions, this project aims to balance cost-efficiency with reliability and performance. The research evaluates …

A Data Driven Approach To Student Success: Visualizing Engagement And Performance Metrics, Araohat Kokate

2025 Spring Honors Capstone Projects - Archive

Many tutoring centers lack tools to analyze and visualize key performance metrics, limiting data driven decision making. This study develops a data visualization feature for the CSE Student Success Center App at the University of Texas at Arlington, enabling administrators to track student engagement, tutor performance and session trends. Using the data of students and tutors, the feature provides interactive dashboards for real-time insights. Administrators can monitor attendance patterns, tutor workloads and booking trends, optimizing resource allocation. Findings indicate that real-time data visualization enhances decision-making, reducing manual effort while improving operational efficiency. This can further help improve student support services. …

Ddos Detection And Mitigation Using Multiple Programmable Switches For Industrial Network Security, Seth Howard

Electrical Engineering and Computer Science Undergraduate Honors Theses

Given the exponential growth in our infrastructure’s reliance on digital systems and large interconnected networks to operate, cybersecurity efforts have not been able to keep up with vulnerabilities attackers can exploit. Specifically, their reliance on industrial network protocols in Supervisory Control and Data Acquisition (SCADA) systems. These protocols are great in terms of the functionality they provide, but are severely lacking in terms of security, leaving the networks vulnerable to cyberattacks. One of the more common protocols, Distributed Network Protocol 3 (DNP3), is particularly vulnerable to Denial-of-Service type attacks. In this work we explore the use of P4-based programmable networks …

Performance Of Inline Compression With Software Caching For Reducing The Memory Footprint In Pysdc, Emily Lattanzio

All Theses

The volume of data required for High Performance Computing (HPC) applications is growing faster than the memory storage available to store the required data, leading to performance bottlenecks in transferring data. Whether sending data from main memory to computation nodes or between parallel processes during runtime, the more data there is to send, the longer it will take to for that data to be sent from one location to the next. Hence the need for inline data compression, which reduces the amount of allocated memory needed by storing the largest data structures in a compressed format and decompressing/recompressing single variables …

Modality Distillation Using A Sam-Guided Multimodal Teacher For Unimodal Wildfire Segmentation And Temperature Prediction, Michael N. Marinaccio

All Theses

Wildfires are one of the world’s most devastating natural disasters that affect the environment, communities, and more critically, humans that live in and around those communities. Due to the threat of large-scale destruction in landscapes and human inhabited areas, it has become increasingly more important to develop wildfire detection, management, and suppression strategies to mitigate and prevent these negative outcomes. Wildfire research encompasses many different areas. Most notably, the development of communication, navigation, remote sensing, and monitoring systems. In wildfire monitoring, limitations discovered in-ground and satellite observation have shifted the focus toward Unmanned Aerial Vehicle (UAV) based wildfire research, which …

Vision-Based Multimodal Frameworks For Human Behavioral Analysis: Applications In Group Activity Understanding And Public Health, Naga Venkata Sai Raviteja Chappa

Graduate Theses and Dissertations

Group Activity Recognition (GAR) has emerged as a crucial problem in computer vision, with wide-ranging applications in sports analysis, video surveillance, and social scene understanding. Unlike traditional action recognition focused on individuals, GAR requires understanding complex spatiotemporal relationships between multiple actors, their interactions, and the broader context in which these activities occur. This complexity introduces unique challenges, including the need for accurate actor localization, modeling of inter-actor dependencies, and understanding of temporal evolution in group behaviors. While recent advances have shown promise, existing approaches often rely heavily on extensive annotations such as ground-truth bounding boxes and action labels, creating significant …

Cross-Dataset Fairness Evaluation Of Transformer-Based Sentiment Models, Sara Zuiran

Theses and Dissertations

With the growing exploration of Natural Language Processing (NLP) systems in decision-making environments, it is essential to evaluate technical and ethical aspects of the dataset and the NLP model to improve fairness. To assess fairness, the thesis examines demographic imbalances in sentiment classification models by evaluating transformer-based models fine-tuned on the Stanford Sentiment Treebank version 2 dataset (SST-2) against the demographically annotated Comprehensive Assessment of Language Model dataset (CALM). This work identifies performance disparities in sentiment prediction across demographic groups by examining sensitive attributes such as gender and race. The study evaluates both the RoBERTa and MentalBERT transformer models using …

Design And Implementation Of Asynchronous Communication In Multi-Chiplet Systems: A Comparative Study Of Pseudo-Crossbar And Bus Architectures, Matthew Clemence

Graduate Theses and Dissertations

System-on-Chip (SoC) complexity continues to present challenges in global clock distribution and power management. The Globally Asynchronous Locally Synchronous (GALS) approach addresses these issues by enabling asynchronous communication between locally synchronous chiplets. This thesis details the design and implementation of two GALS architectures employing asynchronous handshaking protocols through Multi-Threshold CMOS NULL Convention Logic (MTNCL). The first architecture, a pseudo-crossbar, uses arbiters and multiplexers/demultiplexers (MUX/DEMUX) for prioritized and dynamic communication between chiplets. The second, a bus-based approach, employs D-latches to manage communication sequentially with predetermined interrupts. This research explores the detailed implementation, functional distinctions, scalability, and integration trade-offs inherent to each …

From In-The-Head To In-The-World: Frameworks For Understanding And Applying Computational Thinking, Justin Olmanson, Gretchen K. Larsen, Azadeh Hassani

Department of Teaching, Learning, and Teacher Education: Faculty Publications

In the five decades since Papert coined the term Computational Thinking (CT), it has become a core framework for thinking about learning, problem-solving, design, and creativity. Although CT is most commonly, and initially, associated with the cognitive orientations involved in coding and learning to code, it also includes situated and critical processes related to computational problem solving. Herein we unpack ways researchers in different fields and points in time have organized CT. We include creative coding as a uniquely generative lens for rethinking CT, outlining its potential as an expressive, constructionist, and culturally situated practice. In doing so, we explore …

Autonomous Search And Rescue: Real-Time Drone And Robotic Dog Integration, Robert Alexander

Electrical Engineering and Computer Science (MS) Theses

Common robotic navigation techniques often utilize GPS to set up the robot’s reference frame, which is not possible in environments, such as indoor facilities, underground passages, and disaster zones, where GPS is not available. This research explores the integration of a Boston Dynamics Spot robot with a Tello drone to form a non-GPS-based autonomous navigation system. By leveraging coordinate transformation logic, this study enables real-time aerial reconnaissance and ground-based waypoint navigation without reliance on GPS. The methodology includes software development using the Spot SDK and Tello APIs, a virtual networked solution for integration, and an experimental setup to validate navigation …

Reconfigurable Python Autopilot Software For Rc Aircraft, Kate Doiron

Honors Theses

No abstract provided.

Computer Vision In Soccer: Yolov11 Analytics Engine For Quantifying Game Strategy, Connor S. Maurer

Data Science Undergraduate Honors Theses

Single-shot object detection capabilities significantly reduce computational overhead for real-time computer vision in sports analytics at 60 FPS. YOLO11’s lightweight CNN gives promising accuracy while meeting the low-latency demand of dynamic soccer matches. As data-driven approaches take over the sport of soccer, efficient player tracking systems become critical for informing coach’s strategies. I prototype the ETL (Extract, Transform, Load) process of data collected from a single- shot detection program and evaluate its viability for estimating player fatigue. YOLO11 detects players, the ball, and other characteristics, with the output transformed by homography to estimate the positions in the real world. These …

Towards Mitigation Of The Light Network Load Performance Penalty Of The Network Link Outlier Factor (Nlof), Jaime Merin Guzman

Open Access Theses & Dissertations

Detecting and localizing faults in communication networks is critical to maintaining reliable and efficient network operations. The Network Link Outlier Factor with Most Likely Link (NLOF: MLL) algorithm has demonstrated its potential to automate this task but suffers from significant performance degradation under low network load conditions, where limited network flow data reduces its ability to localize faults. This thesis proposes and evaluates the performance of a synthetic traffic generation algorithm to be used with NLOF:MLL. This algorithm strategically injects synthetic flows that supplement the insufficient real network flows, thereby improving NLOF:MLL's performance under low-load conditions. Specifically, we select network …

Improving Home Security Through User Centered Device Positioning, Lalith Nadipalli

Theses and Dissertations

In today’s world, where technology is advancing rapidly and security threats are becoming more complex, the need for effective home safety measures is more critical than ever. Homeowners are increasingly turning to a variety of smart devices, such as smoke detectors, carbon monoxide detectors, and security cameras, to protect their living spaces against potential dangers like burglary, fire, and environmental hazards. These devices offer essential protection, acting as both early warning systems and visual surveillance tools. However, their effectiveness largely hinges on how well they are placed within the home. Proper placement of these safety devices ensures that they provide …

Advancing Efficiency Of Unstructured Mesh Processing With Localized Data Structures, Guoxi Liu

All Dissertations

Unstructured meshes are widely used to represent complex shapes and data in visualization tasks, such as medical imaging, engineering design, and geometric modeling. However, their unevenly distributed elements make them memory-intensive and time-consuming to process, especially as mesh sizes grow. This research focuses on improving the efficiency of processing large unstructured meshes by reducing memory usage and speeding up computations. This doctoral dissertation introduces three methods to address these challenges. The first approach divides the mesh into smaller partitions and processes it piece-by-piece, reducing memory requirements by up to 10 times. The second approach uses the processor's parallel computing capabilities …

Ai-Powered Inspection: A Computer Vision System For Efficient Defects Detection In Underground Infrastructures, Rasha Alshawi

LSU New Orleans Theses and Dissertations

Undetected defects in culverts and sewer pipes pose significant risks to public safety, leading to infrastructure collapses, flooding, and transportation disruptions. Traditional manual inspections are time-consuming, costly, and prone to human error, while existing automated methods struggle with occlusions, irregular defect shapes, class imbalances, and high computational demands. To address these challenges, this dissertation develops advanced semantic segmentation systems that automate defect detection, significantly improving efficiency and accuracy.

This research introduces a series of innovative models designed to overcome these challenges in underground infrastructure inspection. Using dual-attentive mechanisms, sparsely connected blocks, and depth-separable convolutions, these models improve segmentation performance and …

Design Considerations Of A Gpu, Nicholas M. Devilliers

Electrical Engineering and Computer Science Undergraduate Honors Theses

With the current era of AI technology, the era of single instruction multiple data has become an increasingly viable solution to accelerate training. The problem is that while software to use GPUs and other hardware accelerators, designing GPUs and ASIC devices has become increasingly more expensive and there aren’t great examples of generic GPUs that anyone can use and modify. In this thesis, there are four design considerations that will be discussed and how they affect the result of a generic GPU. The four considerations that were talked about in the thesis are, word width, arithmetic type, number of stages, …

Towards A Configurable Platform For The Design And Evaluation Of P4 Network Systems And Applications, Joseph B. Wilkin

Electrical Engineering and Computer Science Undergraduate Honors Theses

Due to the difficulties of running experiments on production networks, researchers often use platforms such as network emulators and testbeds to test their applications before applying them to the real world. There exists a need for a networking platform of this sort designed specifically for running P4 code and for evaluating P4-based experiments. In this work, we design and develop such a platform for use within our lab group based on the Mininet network emulator and its corresponding graphical user interface, MiniEdit. We have successfully integrated the BMv2 software switch into MiniEdit to allow users to build topologies for running …

Key-Based Authentication Scheme For Evtol Drones Using Chebyshev Chaotic Maps, Eduardo A. Hernandez Escobar

Master's Theses

The development of electric Vertical Take-Off and Landing (eVTOL) drones signifies a substantial advancement in urban air mobility, ready to transform transportation models in densely populated regions. These advanced drones, distinguished by their capacity to function in limited spaces and their minimized environmental impact, are set to transform individual, shipping, emergency services, and public safety activities. Nonetheless, like any transformational technology, the implementation of eVTOL systems presents many challenges, especially in the realm of cybersecurity. Adding many devices and entities to an eVTOL network increases the risk of privacy and security attacks. This paper proposes a key-based authentication scheme that …

Exploration Of Polymorphic Gate-Based Watermarking In Asynchronous Circuits, Stephanie Stock

Graduate Theses and Dissertations

With the increasing demand for new state-of-the-art integrated circuits (ICs), intellectual property (IP) reuse has become more commonplace to both accelerate the design process and lessen the non-recurring engineering costs of a design. Reuseable IP poses significant security risks, not only to the creator of the IP, but also to the consumer purchasing the IP. For an IP vendor, this risk can come from illegal distribution, cloning, or overuse. For the purchaser, counterfeit IPs may be purchased from an unvetted vendor, leading to a substandard design, malfunctions, IP infringement, or security vulnerabilities. Hardware watermarking is a method to protect designers …

The Impact Of System Transparency On Perceived System Reliability, Perceived System Usability, And Information Clarity In Self-Driving Car Systems, Uditkumar Nair

Theses and Dissertations

In human-computer interaction (HCI), the development of autonomous vehicle (AV) technology has created new difficulties, especially in building user confidence as well as understanding of system functioning. The effect of system transparency on user- centered outcomes, such as perceived usability, perceived system reliability, and information clarity, is examined in this thesis. In order to evaluate their experiences in both ordinary and high-stakes driving situations, participants engaged with both system- transparent user interfaces (TUIs) and non-transparent user interfaces (NTUIs) across a number of experimental scenarios. In order to assess how well each interface conveyed system logic and actions, the study included …