Prediction Of Glass Transition Temperature Of Polymers Using Structure-Based Models,
2025
The University of Akron
Prediction Of Glass Transition Temperature Of Polymers Using Structure-Based Models, Nicholas Wolfe
Williams Honors College, Honors Research Projects
The focus for this study is prediction of glass transition temperatures of polymers using machine learning models. The preprocessing of the data included the generation of descriptors, the scaling of the data, the principal component analysis for dimensionality reduction, and the clustering of the data. Three methods of property predictions were utilized including Linear Regression, Random Forest, and a Feedforward Neural Network. The dataset consisted of over 7000 polymers each with their respective glass transition temperatures. This study found that the Random Forest model returned the best results followed by the Feedforward Neural Network then the Linear Regression model. Each …
Automatic Scoring Cornhole Board System,
2025
The University of Akron
Automatic Scoring Cornhole Board System, Eric Diffendal, Jonah Harsh, Connor Lengel, Brett Sukie
Williams Honors College, Honors Research Projects
The objective is to create a self-scoring cornhole board that can detect and calculate each team's score based on the bags thrown each round and to be created at a low cost/eventually being sold at the current cost of a normal board. When playing cornhole, the game is simple: throw a bag on the board; however, the scores are variable (deduct and add) across each round. The most common issue when playing cornhole is miscalculations of the scores and forgetting the correct scores. Thus, this invention will make gameplay easy for all to play.
Automatic Cat Caretaker,
2025
The University of Akron
Automatic Cat Caretaker, Connor Mcclenathan, Ryan Anderson, Andrew Tate
Williams Honors College, Honors Research Projects
This project will involve developing and constructing a self-cleaning litter box with feeding and watering functions attached. The machine will have a user interface for setting both the feeding and watering times, as well as how much to fill the food and water bowls at the same time. The project will involve the use of motors for the cleaning, feeding, and watering functions, sensors to detect when to perform those functions, and a microcontroller to process all the data and to tell the motors when to perform their respective functions. This project's goal is to make the task of caring …
Trace Flight Computer,
2025
The University of Akron
Trace Flight Computer, Zachary Stratton, Vandad Mossavand Varkaneh, Nicholas Ely
Williams Honors College, Honors Research Projects
In the world of collegiate rocketry, there are currently no commercial-off-the-shelf flight computers capable of being fitted to liquid engine rockets with thrust vectoring control. Currently, amateur rocketeers utilize unreliable Arduino-based systems or expensive drone computers. The objective of this project is to design a flight computer capable of data collection and filtering, telemetry transmission, and real-time controls of critical safety systems using readily available commercial-off-the-shelf components to allow rocketeers to complete their designs within a reasonable budget. The system will collect data from two IMUs, a barometric altimeter, and a magnetometer, then filter the collected data using custom Kalman …
Monitoring A Small Network With Snmp,
2025
The University of Akron
Monitoring A Small Network With Snmp, Dillon Taynor
Williams Honors College, Honors Research Projects
This project takes a look at the implementation of three distinct free Network Monitoring Systems (NMSs) and their usage of monitoring a small, virtualized network using the Simple Network Management Protocol (SNMP). The 3 free NMSs are PRTG, LibreNMS, and Zabbix. The network is virtualized within Cisco Modeling Labs. A literature review on relevant media is conducted alongside a review of the three NMSs based on installation difficulty, user friendliness, reporting ability, and their ability to respond to changes in the network. A brief discussion on the difference between an SNMPv2 and SNMPv3 packet is included as well.
Autonomous Landscape Exploration Rover Using Imaging Surface Navigation (Alexis),
2025
The University of Akron
Autonomous Landscape Exploration Rover Using Imaging Surface Navigation (Alexis), Noah Jones, Dominic Salupo
Williams Honors College, Honors Research Projects
The objective is to develop a small-form-factor rover prototype that can be used to prove out a novel traversal method for use on extraterrestrial surfaces. The novel traversal method being proposed is LIDAR/CV-enhanced navigation, provided by a detachable flight vehicle that can communicate with the rover. On planets with thin atmospheres, cold gas thrusters or similar may be needed, but for the scope of this project more traditional flight/propulsion methods will be used.
Silent Sabotage: Identifying And Preventing Cyber Attacks From Inside Actors,
2025
The University of Akron
Silent Sabotage: Identifying And Preventing Cyber Attacks From Inside Actors, Autumn Groen
Williams Honors College, Honors Research Projects
Cyber-attacks are becoming increasingly common and damaging as technology advances each year. Many businesses cannot afford the latest security technologies, and even with the highest security measures, there can still be room for employee error or insider threats that are not taken into account. It is crucial to keep these factors in mind when securing a business network of any size or financial standing.This project will aim to simulate a business environment by first building a small network with three routers and a switch, and implementing some of the common best practices for network hardening from credible organizations like NIST …
Vector Estimation For Continuous Tracking Of Observed Radio Signals (V.E.C.T.O.R.) Lunar Navigation System,
2025
The University of Akron
Vector Estimation For Continuous Tracking Of Observed Radio Signals (V.E.C.T.O.R.) Lunar Navigation System, Dimitry Melnikov, Evan Bartel, Andrew Burrier, Goran Gjorgievski
Williams Honors College, Honors Research Projects
NASA's Artemis program requires precise navigation capabilities to establish the first sustained presence on the lunar surface. However, as launches bring necessary orbital infrastructure, the Artemis program will face a critical period during which reliable lunar navigation is not possible. To address this challenge, the V.E.C.T.O.R. system tracks assets, such as rovers and astronauts, as User Terminals relative to a pre-existing cell tower, or Base Station. To do so, the system leverages existing Base Station hardware to calculate the location of User Terminals in conjunction with existing communications infrastructure.
Improving The Robustness Of Compressed Deep Learning Models Against Class Imbalance,
2025
Wayne State University
Improving The Robustness Of Compressed Deep Learning Models Against Class Imbalance, Baraa Saeed Ali
Wayne State University Dissertations
Deep Learning (DL) models are deployed ubiquitously, as they power a wide range of critical applications, including image classification, fraud detection, autonomous vehicles, robots, and NLP. However, their massive size and huge memory footprint (overparameterization) represent a serious challenge to the efficient deployment of such models, especially in resource-scarce environments such as wearable devices, smartphones, edge devices, and embedded systems. Therefore, model compression techniques are typically used to shrink the model size to the currently available computational and memory budget and to accelerate training and inference without sacrificing model accuracy and performance. Therefore, the DL research community considers model compression …
Fuzzing Drones For Anomaly Detection: A Systematic Literature Review,
2025
Singapore Management University
Fuzzing Drones For Anomaly Detection: A Systematic Literature Review, Vikas Kumar Malviya, Wei Minn, Lwin Khin Shar, Lingxiao Jiang
Research Collection School Of Computing and Information Systems
Drones, also referred to as Unmanned Aerial Vehicles (UAVs), are becoming popular today due to their uses in different fields and recent technological advancements which provide easy control of UAVs via mobile apps. However, UAVs may contain vulnerabilities or software bugs that cause serious safety and security concerns. For example, the communication protocol used by the UAV may contain authentication and authorization vulnerabilities, which may be exploited by attackers to gain remote access over the UAV. Drones must therefore undergo extensive testing before being released or deployed to identify and fix any software bugs or security vulnerabilities. Fuzzing is one …
Development And Evaluation Of Machine Learning Models For Early Pediatric Sepsis Prediction,
2025
Wright State University
Development And Evaluation Of Machine Learning Models For Early Pediatric Sepsis Prediction, Ancita M. Andrade
Browse all Theses and Dissertations
Sepsis is a leading cause of pediatric mortality, claiming more lives in the United States annually than all childhood cancers combined. Early identification in Emergency Departments (EDs) remains challenging, as the current Phoenix criteria establishes an updated international consensus definition for sepsis, however is not designed for use as a screening tool. This study aimed to develop predictive models identifying pediatric patients at risk of sepsis within 24 hours of admission. Multiple tree-based and deep learning models were trained utilizing clinical and laboratory data from the initial four hours of presentation. Both the LightGBM and LSTM architectures demonstrated superior performance, …
Wearable Sensor Data Analysis For Machine Learning-Based Detection Of Posture And Autonomic Responses,
2025
Wright State University
Wearable Sensor Data Analysis For Machine Learning-Based Detection Of Posture And Autonomic Responses, Chaitanya Vardhini Anumula
Browse all Theses and Dissertations
This study investigates how Iyengar yoga postures influence autonomic nervous system (ANS) activity by analyzing multimodal physiological signals collected via wearable sensors. The physiological mechanisms underlying Iyengar yoga’s therapeutic effects remain under-explored at the granular, pose-level. Using data collected from 16 participants, this research evaluates whether machine learning models can distinguish between baseline, parasympathetic-dominant, and sympathetic-dominant states based on wrist-worn sensor data. The goals were to explore whether subtle postural variations elicit measurable autonomic responses and to identify which sensor features most effectively capture these changes. Participants performed a sequence of yoga poses while wearing synchronized sensors measuring electrodermal activity …
Impact Of Graph Structures For Rag Outcomes In Llms,
2025
Wright State University
Impact Of Graph Structures For Rag Outcomes In Llms, Chris Davis Jaldi
Browse all Theses and Dissertations
Explainability, interpretability and adaptability (EIA) remain three central motivations for next-generation Artificial Intelligence (AI), especially as Large Language Models (LLMs) continue to engage with ever-increasing knowledge bodies. As the landscape pushes toward controllable agentic Retrieval-Augmented Generation (RAG) systems where AI agents engage in iterative, guided reasoning, a critical question arises as to the extent to which the knowledge design itself shapes these models' reasoning behavior. This work conducts a systematic evaluation of how different conceptualizations and representation of the identical knowledge affect an LLM's path-based reasoning capabilities. Through the introduction of controlled variations along graph structural complexity, linguistic and semantic …
Re-Parameterizing Adversarial Reprogramming In Low-Dimensional Subspace For Efficient Software Vulnerability Detection,
2025
Wright State University
Re-Parameterizing Adversarial Reprogramming In Low-Dimensional Subspace For Efficient Software Vulnerability Detection, Hootan Alavizadeh
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Software vulnerabilities are a major cause of security breaches, making effective detection critical. Traditional learning-based methods require large datasets and significant computational resources, which are often impractical due to high annotation costs and data scarcity. To address this, we propose an innovative system, RearVul, which Re-parameterizes adversarial reprogramming in a low-dimensional subspace for software vulnerability detection. Unlike conventional approaches, RearVul repurposes a pre-trained classification model using adversarial reprogramming, enabling detection with minimal modifications. It learns a universal perturbation applied to program representations, preserving the original model’s feature extraction capabilities while adapting it to a new domain. Furthermore, we introduce a …
Subjective Readiness Forecasting Using Supervised Machine Learning And Wearable Device Data,
2025
Wright State University
Subjective Readiness Forecasting Using Supervised Machine Learning And Wearable Device Data, Nathaniel Michael Weiland
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Recent advances in wearable technology allow continuous monitoring of physiological and behavioral data, opening new opportunities for real-time assessments of readiness and well-being. However, creating predictive models that generalize across diverse users remains challenging, especially in high-stakes settings like the military, where preventable injuries, illnesses, and stress-related performance declines are frequent. This research assesses the feasibility of using supervised machine learning models trained on wearable device data to predict subjective readiness indicators—recovery, stress, injury, and illness. Data from over 10,000 users in the OHWS (Optimizing the Human Weapons System) program combined daily check ins with physiological metrics from Garmin, Polar, …
Dataset Generation For Routing Policy Study In Ad Hoc Wireless Networks,
2025
Wright State University
Dataset Generation For Routing Policy Study In Ad Hoc Wireless Networks, Vishnu Vishnu Priya
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Ad Hoc wireless networks, with their decentralized architecture and dynamic topology, present challenges in reliable and energy-efficient routing. While machine learning (ML) and reinforcement learning (RL) offer promising solutions, progress is limited by the lack of realistic, high-fidelity datasets. This research introduces a simulation-based framework for generating four diverse datasets representing combinations of node mobility (mobile vs. static) and spatial distribution (random vs. clustered). Each dataset captures critical metrics such as Signal-to-Interference-plus-Noise Ratio (SINR), bottleneck rate, and power consumption across multi-hop paths. A lookahead-based greedy routing algorithm with scenario-aware power control is implemented to emulate practical behavior. Supervised ML models, …
Isometric Centroid Encoder (Ice) And Synthetic Data Generation Approaches For Biological Datasets,
2025
Wright State University
Isometric Centroid Encoder (Ice) And Synthetic Data Generation Approaches For Biological Datasets, Prathyusha Kanakamalla
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This thesis addressed two main challenges in biological data analysis: structure-preserving dimensionality reduction and synthetic data generation for small sample datasets. I proposed the Isometric Centroid Encoder (ICE), a supervised dimensionality reduction method that preserves pairwise distances between class centroids during dimension reduction. Unlike existing methods like Centroid Encoder and Super Encoder, ICE explicitly maintains geometric relationships between biological classes, achieving nearly perfect structure preservation at C dimensions (where C equals the number of classes) with strong performance even in 2D and 3D spaces. Additionally, I compared three generative models (VAE, LSH-GAN, and scDiffusion) for synthetic data generation on small …
Detecting Wireless Security Threats Through Ieee 802.11 Frame Field Anomalies,
2025
The University of Akron
Detecting Wireless Security Threats Through Ieee 802.11 Frame Field Anomalies, Aria Young
Williams Honors College, Honors Research Projects
It is not uncommon for most public spaces to offer Wi-Fi, while it is convenient and affordable, there are significant security risks due to its open nature. Rogue access points pose a security threat to many networks because they have the potential to bypass security measures and intercept traffic containing sensitive information. The attempt to formulate a method that one hundred percent guarantees the detection of a rogue access point has proven to be an intricate and complex problem for many to tackle, as there are numerous ways a rogue access point can be configured. This project aims to demonstrate …
Ultrasonic Sensor-Based Sound Synthesis Using Raspberry Pi Pico W,
2025
The University of Akron
Ultrasonic Sensor-Based Sound Synthesis Using Raspberry Pi Pico W, Niraj Jaishwal
Williams Honors College, Honors Research Projects
At the intersection of Human Computer Interaction and digital art, this project transforms simple motion into musical expression. It explores an interactive real-time sound synthesis system using ultrasonic sensors to generate continuous audio. The objective is to design a system that maps physical distances into musical parameters such as pitch and amplitude, which will create a responsive audio environment. Two ultrasonic sensors are used in combination with the Raspberry Pi Pico W microcontroller running CircuitPython and Adafruit Audio Hat for real-time sound output. One sensor controls the pitch of the generated tone, while the other controls volume. This enables expressive …
Personalized Physics Learning Through Ai: Insights From Problem Generation, Chatbot Dialogues, And Intelligent Tutoring Systems,
2025
University of Texas at Arlington
Personalized Physics Learning Through Ai: Insights From Problem Generation, Chatbot Dialogues, And Intelligent Tutoring Systems, Atharva Dange
Physics Dissertations - Archive
Artificial intelligence (AI) is poised to transform science education, yet questions remain on how best to integrate these technologies into teaching and learning. This dissertation investigates the use of AI-driven tools in university physics courses through three complementary studies. In the first study, a generative language model (ChatGPT) was used to create novel physics homework problems aligned with course objectives. Analysis showed that, after expert vetting, AI-generated questions can foster higher-order problem-solving and reduce student reliance on solution memorization, though careful instructor oversight is required to ensure accuracy. The second study embedded an AI chatbot as a learning aid in …
