Digital Commons Network^™

Detection And Management Of Attacks On Synchronized Networks, Michael T. Spearman

Honors Theses and Capstones

The Precision Time Protocol (IEEE 1588) provides sub-microsecond clock synchronization across packet-switched networks and has become foundational infrastructure in 5G fronthaul, industrial control systems, and financial exchanges. Despite its criticality, most deployed PTP networks operate without active security monitoring, and no standardized detection mechanism exists for the class of attacks that deliberately stay below conventional jitter thresholds. This thesis investigates whether hardware-level ptp4l offset logs alone are sufficient to reliably detect two such attacks, slowly wandering packet delay injection and rogue master spoofing, and whether detection can occur before severe synchronization failure.

A hardware-in-the-loop testbed was constructed using two hosts …

Deep Learning Approaches For Voltammetric Analysis Of Coffee, Ryan Koes

Honors Theses

This thesis investigates deep learning approaches for voltammetric analysis of brewed coffee using a low-cost electrochemical system and screen-printed electrodes (SPEs). Traditional analytical methods, such as high-performance liquid chromatography (HPLC) and gas chromatography-mass spectrometry (GC-MS), provide precise quantification of key compounds but require expensive instrumentation and specialized expertise, limiting accessibility. While SPEs offer a more accessible alternative, they yielded poor results with traditional processing; however, when combined with a neural network, the system proved more effective. In experiments with 132 coffee samples, mean errors for caffeine, CGA, and TDS predictions were 52.98 ppm, 70.48 ppm, and 0.08%, respectively. These findings …

Combining Haptic Feedback With Electromyography To Study Knee Injury In Stationary Cycling, Christopher Kirby

Honors Theses

Patellofemoral Pain Syndrome (PFPS) is the most prevalent overuse injury in cycling, often linked to altered neuromuscular activation patterns of the quadriceps and hamstrings. While sensory feedback has successfully modified cyclists posture, there is a critical lack of evidence-based interventions targeting the underlying muscle activation imbalances associated with chronic knee pain. This study aimed to develop and validate a novel, real-time biofeedback system that utilizes electromyography (EMG) to trigger vibrotactile cues, aiming to shift muscle onset timing earlier in the pedal stroke to mitigate PFPS-related imbalances. A closed-loop system was engineered by integrating a Delsys EMG system with a SageMotion …

Design And Analysis Of Energy Recovery Methods For Reduced Aircraft Emissions, Joshua C. Hauck

Honors Theses

Aircraft flights are an increasingly popular mode of transportation. However, their harmful impacts on the environment are a growing concern. Many engineers have worked to develop fully electric aircraft to address this issue. Although they are much more sustainable than conventional aircraft, electric aircraft encounter severe limitations imposed by current battery technology. One alternative route engineers have taken is developing energy recovery methods (ERMs). These are marketed as devices that reduce aircraft fuel consumption without significantly changing their structure and functionality, making them an excellent short-term solution. However, there is little to no consideration of the tradeoffs induced by the …

Sewer Pipe Condition Assessment Using An Ensemble Machine Learning Framework For Infrastructure Decision Support, Mahnaz Rouhi

Civil Engineering Dissertations

Aging wastewater infrastructure presents significant challenges for municipalities across the United States, with many sewer networks approaching or exceeding their design life. Conventional inspection methods, such as closed-circuit television (CCTV), are limited by subjectivity, cost, and inefficiency. To address these challenges, this study develops an ensemble machine learning framework for assessing the structural condition of sewer pipelines using inspection records enriched with geospatial attributes.

The primary objective of this research is to enhance predictive accuracy, interpretability, and decision-support for risk-based asset management. The scope of the study encompasses 4,802 CCTV inspection records from Dallas, TX, and Tampa, FL, integrating physical, …

Videoscoop: A Non-Traditional, Domain-Independent Framework For Video Analysis, Umme Hafsa Billah

Computer Science and Engineering Dissertations

Due to the proliferation of cameras in handheld devices and the widespread use of CCTV, images and videos have become a preferred alternative for capturing and disseminating information. Automated analysis for understanding image or video contents (e.g., objects, activities, backgrounds, situations of interest, etc.) is critical for many applications such as Civic Monitoring, Surveillance (in general), monitoring activities in Assisted Living environments, and many more. Image and Video Analysis (IVA) research has been ongoing for several decades, resulting in numerous techniques for algorithmically analyzing and understanding image and video contents.

Image Analysis (IA) has advanced in several areas, including object …

Deep Learning For Wireless Communications, Swarada Ajit Kulkarni

Electrical Engineering Dissertations

The rapid evolution of wireless communication imposes stringent requirements for ultra-reliable, low-latency transmission in dynamic, interference-prone environments. Traditional model-driven signal processing struggles to adapt to nonlinear hardware effects, time-varying channels, and complex interference patterns. Deep learning (DL) offers a transformative, data-driven alternative, enabling end-to-end optimization and robust adaptation under uncertain propagation conditions.

This dissertation investigates deep learning architectures for intelligent and resilient wireless communication through three complementary contributions. The first introduces a Vision Transformer (ViT)-based modulation classification framework that leverages self-attention to capture local and global dependencies in spectrogram representations of Quadrature Amplitude Modulation (QAM) signals. The ViT achieves superior …

Training A Cellpose Model For T-Cell Cytoplasm And Nucleus Segmentation, William Laws, Matthew Lindley, Irene Georgakoudi

Wetterhahn Science Symposium Posters

Accurate single-cell segmentation of cytoplasm from nucleus in autofluorescence images is critical for quantifying cellular metabolism using the optical redox ratio (FAD / FAD+NAD(P)H). However, automated cytoplasmic segmentation of T cell two-photon excitation fluorescence images remains challenging due to low signal-to-noise ratio, small cell size, and variability in cell brightness across imaging conditions. Here, we present a pipeline combining a custom-trained Cellpose-SAM model with an adapted cytoplasmic post-processing algorithm (CPPA) for automated single-cell metabolic analysis of T cell NAD(P)H autofluorescence images. Raw 2048×2048 pixel images were spatially binned 4×4 in MATLAB to improve signal-to-noise ratio and reduce processing time. A …

Fiber-Reinforced Composites For Vaginal Tissue Engineering Applications, Samyuktha S. Kolluru, Abir Hamdaoui, Annabella M. Mascot, Siobhan S. Sutcliffe, Jerry L. Lowder, Michelle L. Oyen, Samantha G. Zambuto

Mechanical Engineering Faculty Publications

The vagina is a fibromuscular tube-shaped organ that plays critical roles in menstruation, pregnancy, and female sexual health. Vaginal tissue constituents, including cells and extracellular matrix components, contribute to tissue structure, function, and prevention of injury and pathology. However, much microstructural function remains unknown, including how the fiber-cell and cell–cell interactions influence macromechanical properties. A deeper understanding of these interactions will provide critical information needed to reduce and prevent vaginal pathologies. Our objective for this work is to design a novel tissue-mimicking biomaterial for vaginal tissue engineering, and characterize its biological and mechanical performance in the vaginal microenvironment. We successfully …

Field-Based Device To Test Possible Tbis, Colin Laidlaw, Lauren Powers

Student Research Design & Innovation Symposium

Traumatic brain injury (TBI) remains a major cause of death in the United States. In emergency field care, first responders must quickly assess neurological status and determine appropriate patient transport. The Glasgow Coma Scale (GCS), the primary neurological assessment used in the field, correctly identifies TBI only about 40 percent of the time. In Rhode Island, state protocols require all patients with suspected TBI to be transported to a Level I trauma center. This creates challenges when trauma resources are limited or when symptoms are subtle and difficult to evaluate in the field. To address this issue, a reaction time …

6 Degrees Of Freedom Robotic Arm, Vansh Garg , ‘26, Eric Chen , ‘26, Kaw Moo , ‘26

Senior Theses, Projects, and Awards

This project involved the design, fabrication, and testing of a 6 degree of freedom robotic arm. The goal was to demonstrate that a low-cost, 3D-printed system could achieve useful strength, modularity, and basic manipulation for simple pick-and-place tasks. Potential applications include education, prototyping, hobbyist robotics, and low-precision automation.

The mechanical system uses 3D-printed arm links, cycloidal gearboxes, belt-driven transmission, bearings, and a modular end effector. These components were selected to balance cost, manufacturability, and performance, with gear reduction used to increase available joint torque. The electrical system provides motor actuation, power distribution, and controller integration, while the software enables command-based …

Multi-Scale Sensor-Aware Variational Autoencoders For Adaptive Iot Security: Integrating Drift Calibration And Cyberattack Detection, Md Kamal Hossain, Iftekhar Ahmad, Daryoush Habibi

Research outputs 2022 to 2026

Existing approaches to Industrial Internet of Things (IoT) anomaly detection treat sensor drift calibration and cyberattack detection as separate problems, overlooking their strong interdependence and the compound failure modes that arise when drift dynamics are exploited by stealthy adversaries. Industrial Internet of IoT sensor networks therefore require a unified framework that jointly models both phenomena. This paper proposes the first unified multi-scale sensor-aware variational autoencoder (MS-VAE) framework that jointly models sensor drift and malicious activity within shared latent representations, enabling integrated calibration and security monitoring. The framework introduces three key components: (i) a multi-scale latent architecture that captures short-term anomalies …

Application Of Passive Samplers For Exploring Remedial Progress In The Torch Lake Aoc And Interlake Variability Of Pcbs, Cailin B. Bishop

Dissertations, Master's Theses and Master's Reports

This study evaluates changes in dissolved polychlorinated biphenyl (PCB) concentrations in Torch Lake, Michigan, an Area of Concern shaped by decades of legacy contamination and evolving restoration policy. Passive samplers deployed across sites and seasons (2024–2025) show total PCB concentrations ranging from below detection to 110 pg/L (mean = 16.8 pg/L), representing an approximate 90% decline since 2005. Comparisons with regional reference lakes indicate no statistically significant difference (p = 0.84), suggesting concentrations may approach background atmospheric levels despite continued variability. Congener profiles indicate a shift toward lower-chlorinated PCBs, though interpretation of higher-chlorinated congeners is limited by slow sorption kinetics. …

Development And Calibration Of A 2-D Diesel Oxidation Catalyst Filter (Docf) Model With Spatially Varying Washcoats Using Spacims And Engine Loading Data, Thomas K. Price

Dissertations, Master's Theses and Master's Reports

Diesel engine exhaust contains regulated species, including carbon monoxide, hydrocarbons, nitrogen oxides, and particulate matter (PM). Meeting increasingly stringent emission standards typically requires multiple aftertreatment components, motivating the development of multifunctional devices that reduce system size, cost, and catalyst usage. Computational models are essential for guiding this design process; however, existing models primarily focus on single-function devices and rarely capture the behavior of multifunctional systems with multiple catalyst washcoats. This work presents a physics-based model of a wall-flow diesel oxidation catalyst filter (DOCF), a multifunctional device that integrates the roles of a diesel oxidation catalyst and a diesel particulate filter …

On The Vibrational Dynamics Of Wind Turbine Blades: The Oscillatory Response To Gust Pulses, And The Physical Mechanisms Behind Them, North A. Yates

Dissertations, Master's Theses and Master's Reports

An easily noticed trend in the utility-scale wind turbine industry is that the size of the machines has continued to increase over time. While this may have benefits in terms of increasing the power generation for a single turbine, a major drawback is the rate with which the weight of the turbine blades grow. To ensure these larger machines can be utilized, efforts are being put forth to create lighter blades. This may fix the weight issue, but brings on a new one; these lighter blades can also be more flexible than previously studied ones. It is, therefore, vitally important …

Cats 2.0: Leveraging Large Language Models And Graph Databases For Robust Arabic Sms E-Commerce Systems, M. Samir Abou El-Seoud, Daoud M. Daoud 2

Computer Science

Arabic SMS-based e-commerce platforms pose unique challenges due to the spontaneous and noisy nature of user-generated text (e.g., abbreviations, dialectal Arabic, or “Arabizi” transliterations). In this paper, we present Classified Ads Text Service (CATS) 2.0, an improved classified ads system that combines probabilistic large language models (LLMs) with deterministic graph-based knowledge representations to achieve robust understanding and matching of Arabic SMS content. Building on earlier work that emphasized the importance of integrating sublanguage analysis with content-oriented methods, our approach uses a hybrid pipeline: an LLM interprets free-text messages and extracts structured information, which is then inserted into a Neo4j graph …

Machine-Learning- And Iot-Based Approach For Predicting Water Quality Using Data Classification And Explainable Ai Technique, M. Samir Abou El-Seoud, Omar H. Karam 2, Hosam El-Sofany 3

Computer Science

Maintaining water quality is crucial for both public health and environmental sustainability. This study proposes a machine-learning- (ML-) and Internet-of-Things- (IoT-) based approach to water quality prediction that utilizes explainable artificial intelligence (XAI) and data classification techniques. The proposed approach integrates IoT devices to enhance real-time data collection, facilitating continuous monitoring and early anomaly detection. Ten different ML classifiers—Decision Trees, K-Nearest Neighbors, XGBoost, Naïve Bayes, Logistic Regression, AdaBoost, Random Forests, Support Vector Machines, Voting, and Multi-Layer Perceptron—were evaluated to find out which one works best for predicting water quality. We used three distinct approaches for feature selection: analysis of variance …

Eeg And Imu Gait Signal Processing: A Comparative Assessment Of The "Reza" Exponential Filter And Classic Filters, Reza Pousti, Daniel M. Russell, Derek C. Monroe, Christopher K. Rhea

Rehabilitation Sciences Faculty Publications

Noise degrades both EEG and gait signals, and classical IIR filters (Butterworth, Chebyshev, elliptic) involve trade-offs between passband flatness, ripple, and roll-off. This study compared a novel exponential "Reza" filter with these designs for neural and locomotor data. We analyzed an open-source mobile brain-body imaging dataset with EEG and gait data from 49 healthy adults (EEG: 256-channel, 512 Hz; IMUs: six APDM Opals, 128 Hz). EEG channels were grand-averaged and band-pass filtered at 0.5-50 Hz, while IMU axes were averaged and band-pass filtered at 0.5-5 Hz. The outcomes were signal-to-noise ratio SNR (dB) and band-integrated Welch PSD (EEG:0.5-50 Hz; IMU:0.5-5 …

Using A Record Player Inspired Probe System To Investigate Adhesion And Friction Of Tire Rubber At Micrometer Length Scales, Kyle J. Galigher, Brendan Schmitt

Williams Honors College, Honors Research Projects

We will be using the principles behind how a record player turns physical grooves into electrical signals to develop a device that can be used to measure the surface of tires. The device will be capable of measuring the surface roughness of rubber samples from both new and worn tires, in order to compare the differences between them. It will be operable at varying speeds, and will produce electrical signals that correspond to the bumps along the surface of the rubber. The design will be carried out and optimized with the use of SolidWorks modeling, finite element analysis, motion analysis, …

Active Altitude Control For High Powered Rockets, Henry Allen, Jason Secora, Charles Williams, Donavon Sanchez, Caleb Nedoma

Williams Honors College, Honors Research Projects

The International Rocket Engineering Competition (IREC) is the premier collegiate high power rocketry competition in the world hosted by the Experimental Sounding Rocket Association (ESRA). The Akronauts Rocket Design team has been competing in IREC since 2015 and have won several awards. The main goal of IREC is to launch a rocket to a specified altitude of 10k, 30k, or 45k ft while carrying a payload and successfully recover with little to no damage.

The control of a typical high-powered rocket is purely passive; the center of pressure of the rocket must be behind the center of gravity with respect …

A 1d Symmetric Interior Penalty Discontinuous Galerkin Solver In Rust, William Aey

Williams Honors College, Honors Research Projects

This honors project will build a 1D Symmetric Interior Discontinuous Galerkin (SIPDG) solver in Rust for Stum-Liouville type problems such as the Poisson equation, with Robin, Dirichlet, and Neumann boundary conditions. The work will cover the full pipeline: starting from the strong form of the PDE, deriving the DG weak form, implementing element and interface operators, and assembling or apply the discrete operator. Rust's safety and concurrency (e.g, via Rayon) will be used to explore serial and parallel performance. A test-driven development approach will be used to maintain a strong suite of tests. The project will result in a documented …

Determining Critical Micelle Concentrations Of Standard Surfactants And Rhamnolipids, Kathryn E. Kunz

Williams Honors College, Honors Research Projects

My proposed project will study the critical micelle concentration (CMC) of rhamnolipids using the pendant-drop and drop-weight methods. First, the critical micelle concentrations of ionic and nonionic common surfactants will be tested. Sodium Dodecyl Sulfate (SDS) will be used as an ionic surfactant and Tween 20 will be used as a nonionic surfactant. The critical micelle concentrations will be determined using the pendant-drop and drop-weight methods. The experimental results from the standard surfactants compared to their accepted values will be tested to assist with determining a more suitable approach. Completing the tests will provide a better understanding of critical micelle …

Ai-Based Porosity Detection In Babbitt Bore Turning, Kaylee Leggett, Hannah Adams Gemmell, Kaisa Shingleton

Williams Honors College, Honors Research Projects

For this project, an external company reached out to the University of Akron requesting assistance with defect detection during their vertical turning operations. As babbitt is removed in a vertical turning process, it occasionally reveals defects, mainly porosity, which can lead to costly downstream failures of the part. Current inspection techniques involve use of dye penetrant, which is time consuming, labor intensive, unergonomic, and a source of human error. The goal of the project is to create an alternative inspection method using an AI-based machine-learning model. After the turning operation, a camera is deployed to perform an in-place inspection, taking …

Design New Stage For Vacuum Pin On Disk, Miranda Boyd

Williams Honors College, Honors Research Projects

For my senior design project, I am redesigning the moving stage for the vacuum pin-on-disk test used in the Akron Engineering Tribology Lab. This system is used to evaluate bearings and lubricants for aerospace applications under controlled vacuum conditions. The current stage design limits flexibility when adjusting for different testing parameters, so my goal is to develop a new movable stage that allows for varying weights and loads to be applied accurately and safely. The redesigned stage will improve test efficiency, adaptability, and precision, ensuring the system can accommodate a wider range of experimental conditions and materials while maintaining compatibility …

Printer For Music Box, Chad Lewis, Caleb Murawski, Zion Smith, Bryan Tibbs

Williams Honors College, Honors Research Projects

The traditional method of creating music box sheet music involves manually punching holes into a paper strip using a hand-operated hole punch. This process involves precise knowledge of each note’s location and the ability to achieve perfect accuracy for hours.

The goal of this system is to automate this process, significantly reducing the time required while greatly improving the accuracy of the resulting music box playback. The user simply uploads a MIDI file of their choice into a user-friendly application. Here, the file is modified based on the user’s needs and sent to an automated hole-punching system to punch the …

Crashheart, Ellie Riekert, Kennady Skidmore, Madison Furino

Williams Honors College, Honors Research Projects

This project aims to develop an XR (extended reality) iPad training system to improve pediatric crash cart preparedness among nurses and clinical staff at Akron Children’s Hospital. In emergencies such as respiratory failure or shock, quick and accurate access to crash cart supplies is vital, yet opportunities for hands-on practice are limited. Current nurse training relies on PowerPoint instruction or costly physical simulations, reducing engagement and skill retention. Our interactive XR solution replicates the crash cart’s layout and contents, allowing users to practice identifying and retrieving critical items in a realistic environment without using physical supplies. The system will be …

Seat Belt Data Collection Methods: A Comparison Between States And National Guidelines, Madison R A Richards

Williams Honors College, Honors Research Projects

Thousands of fatalities related to vehicle crashes occur every year. One method to reduce fatalities is to encourage seat belt use compliance. To promote statistics regarding seat belt use, there first must be reliable data on seat belt compliance and this comes from good survey design.

This report is a comparative analysis of seat belt data collection methodologies for Ohio, Michigan, and Indiana, in addition to an evaluation of how each state aligns with standards set by the National Highway Traffic Safety Administration (NHTSA). The framework for this analysis focuses on NHTSA’s five core survey design requirements: selection of observation …

Security Onion Ids Case Study: Detecting And Investigating Threat Traffic Using Suricata, Zeek, And Pcap Evidence, Daryna Myroniuk

Williams Honors College, Honors Research Projects

A key component of cybersecurity is network intrusion detection, which is used to examine network traffic for any malicious activity. Many organizations deploy intrusion detection systems (IDS) but still face challenges such as validating detections, investigating alerts in a timely manner, and producing clear and repeatable evidence of what has occurred, especially when live traffic capture may be limited to risks, permissions, or privacy concerns. The goal of this project was to use Security Onion, which includes Suricata and Zeek to create and demonstrate a controllable and manageable evidence-based IDS investigation workflow. This project is focused on deploying and validating …

Rapid Skin Stapler, Emma J. Patterson, Allison M. Milligan, Morgan E. Dunlap

Williams Honors College, Honors Research Projects

Severe burn injuries frequently require split-thickness skin grafts, with metal surgical staples serving as the current standard for fixation. While staples provide rapid and secure placement of graft material, they also introduce significant challenges. Removal is painful, time-consuming, and often requires sedation in pediatric patients, leading to added risk, resource strain, and poor patient experience. These drawbacks highlight the need for improved fixation methods that maintain graft stability while reducing procedural burden. This project applies the engineering design process to address these challenges through identification of user needs, translation into design inputs, risk assessment, and development of a prototype aimed …

Lunar Regolith Densometer, Liam Lee, Vincent Innocenzi

Williams Honors College, Honors Research Projects

Testing of extraterrestrial rovers is a growing concern as lunar exploration as an industry is becoming increasingly commercialized. Currently, the way rover testing is conducted is on a soil regolith which is already available. The structure of the soil, however, is harmful to humans and requires a full bunny suit and respirator to be worn during the conduction of the experiment. This limitation, along with the expensive price tag, prevents college university students and companies from establishing a rover test area in labs. The goal of the overall project is to create a safer testing environment by mimicking the soil-to-tire …