Digital Commons Network^™

Thermal Radiation Effects On Particles From Plasma Arc Radiation, Reece Davis, Joseph Mcgee

Williams Honors College, Honors Research Projects

Understanding the radiation heating and transport of both microparticles and nanoparticles is a phenomenon that is critical for both space and Earth sciences. In space, these particles are heated by plasma arcs within ionized space clouds or solar flares and can be present the path of deep space missions and orbital satellites. While on Earth, processes such as forest fires, nuclear fusion, and microchip manufacturing include the plasma arc heating of particles. These particles lay within the Mie Scattering Regime and Rayleigh Scattering Regime and emit radiation differently based on their diameter. New mathematical and computational modeling has been conducted …

Akron Soap Box Derby Super Kids Car, Alexis Schultz, Cooper Sites, Sean Stevenson

Williams Honors College, Honors Research Projects

This project aims to redesign the All-American Soap Box Derby Super Kids vehicle to enhance safety, accessibility, and performance while maintaining full compliance with official regulations. The Super Kids program enables children with physical and cognitive disabilities to race alongside a co-pilot, but the current vehicle design presents challenges in stability, entry/exit accessibility, and control—especially following recent regulation changes that increased vehicle speed. The redesigned car will focus on improved ergonomics, lightweight construction, and structural integrity within a $1,000 budget and a 165 lb weight limit.

An iterative engineering design process will guide the project through research, CAD modeling, FEA …

Predictive Structural Modeling In Ansys And Destructive Testing For Composite Structures, Dylan Matthews, Grant Abraham, Andrew Raineri

Williams Honors College, Honors Research Projects

Composite structures are central to the performance and reliability of Zips Racing’s Formula SAE vehicles, yet the team currently relies on historical data and partially unvalidated assumptions when selecting carbon fiber layups. This project aims to establish a quantitative, experimentally validated framework for designing composite components through the integration of simulation modeling, physical fabrication, and destructive mechanical testing. Analytical laminate theory models developed in MATLAB and laminate simulations created in Ansys ACP will be used to predict stiffness, strength, and failure characteristics for a range of candidate layups. These predictions will be validated through controlled testing of fabricated composite coupons …

Clear Skies, Avery C. Munn

Williams Honors College, Honors Research Projects

Air quality impacts public health, environmental sustainability, and quality of life. However, accurate and easily accessible short-term air quality forecasting is challenging to find. This project, Clear Skies, presents a machine learning–based system for forecasting next-day Air Quality Index (AQI) levels across regions in Ohio. By using historical pollutant data with variables such as temperature, humidity, wind speed, and atmospheric pressure, the system finds relationships that traditional statistical models often don’t show.

Machine learning models are evaluated alongside AI techniques to find the environmental factors that influence AQI predictions. This helps reduce the “black box” nature of many AI systems …

Parametric Study Of Yields And Properties Of Corn Stover-Derived Hydrothermal Liquefaction Products By Using Statistical Approaches, Isamu Umeda, Meicen Liu, Jiefu Wang, Yi Zheng, Zhiwu Wang, Jaya Shankar Tumuluru, Sandeep Kumar

Civil & Environmental Engineering Faculty Publications

Hydrothermal liquefaction (HTL) of lignocellulosic biomass produces multiple product fractions, including solid residue (SR), heavy bio-oil (HBO), aqueous phase (AP), and light bio-oil (LBO). This study mainly applied principal component analysis (PCA) and regression modeling to predict AP solution weight, LBO weight and fuel characteristics, and HTL wastewater biodegradability, as well as to improve prediction accuracy for SR and HBO under various operating conditions (temperature: 250–350 °C, residence time: 5–60 min, and the combined solid loading of three batches: 15–45 g). A complementary relationship between SR and AP weights found in PCA enabled the estimation of AP weight based on …

Physics-Based Multi-Hazard Fragility Modeling Of Low-Rise Wood-Frame Buildings Under Hurricane-Induced Wind And Surge, Mumtasirun Nahar, Abdullah M. Braik, Mohammad Syed, Maria Koliou, Petros Sideris

Civil & Environmental Engineering Faculty Publications

Coastal buildings are exposed to concurrent hurricane-induced wind and storm surge, yet their vulnerability is commonly assessed using separate single-hazard models that neglect hazard interaction. This study developed a physics-based finite element framework to evaluate the performance of a low-rise light wood-frame building under simultaneous wind and surge-wave loading. A detailed three-dimensional model was constructed using a sub-assembly strategy that explicitly represented framing members, sheathing systems, and critical connections. Structural response was evaluated across a hazard space defined by wind speed, still-water depth, and flow velocity, and component- and system-level fragility functions were derived using Monte Carlo simulation and generalized …

Quantifying Hemodynamics In Implantable Cardiac And Renal Support Devices Using Computational Modeling, Alexander D. De Oliveira

Summer Research Program Abstracts

No abstract provided.

Applying Transfer Learning For Street-Scale Nuisance Flood Forecasting In Coastal-Urban Environments, Binata Roy, Jonathan L. Goodall, Diana Mcspadden, Chetan Kumar, Steven Goldenberg, Yidi Wang, Malachi Schram

Data Science Faculty Publications

An important challenge with Machine Learning (ML) is its transferability; that is, whether an ML model trained on one set of data can be applied to a second set of data without requiring full retraining of the model. Transfer Learning (TL) addresses this challenge by transferring knowledge learned in the source domain (the data it was trained on) to the target domain (a second set of data that is statistically different but related, which the model was not trained on). This study investigates the use of TL for street-scale nuisance flood forecasting by exploring whether an ML model trained for …

Towards Developing A Career Technology Fit Framework And Analyzing Its Influence On Work-Related Outcomes Among It Professionals, Gunjan Tomer

Journal of International Technology and Information Management

With growing attrition rate and significant demand for skilled IT professionals, the importance of studying their behaviour has become important for both academia and industry. Despite ample amount of research, there is still a gap between theory and practice. Based on our qualitative study conducted on Indian IT professionals we propose that technology allocation might contribute in understanding the behaviour of IT professionals. We found that IT professionals evaluate the technology allocated to them based on their individual career motives. This evaluation, either positive or negative, influences their job outcomes. Further, we explored the factors that make a technology preferable …

High Technology And The Developing State: The Arrival Of Supercomputers In India, Ramesh Subramanian

Journal of International Technology and Information Management

While India has made vast strides in information technology in the last few decades, its success is mainly attributed to its software, rather than its hardware sector. In fact, India’s attempts at developing computer hardware that can match international standards have largely been unsuccessful. A notable exception is its development of a series of supercomputers that match and exceed many international standards. This paper looks at an interesting period in India’s computing history – namely the 1980s and 1990s – focusing on its development of an indigenous supercomputer. During that period, supercomputers were thought to be the sole privy of …

Responsible People Analytics For Remote-Work Decisions: A Machine-Learning Benchmark For Classifying Perceived Productivity, Ruth Menjivar, Nima Molavi, Narges Mashhadi Nejad

Journal of International Technology and Information Management

This study examines whether employee-perception survey data can support responsible people-analytics decisions about remote-work productivity. Using the public New South Wales (NSW) Remote Working Survey 2021 (N=1,512), the study benchmarks statistical and machine-learning classifiers for self-reported perceived productivity classes (same, less, or more productive when working remotely relative to onsite work), not objective output, under default, class-weighted, and resampling protocols. Main evidence comes from 5×5 repeated stratified cross-validation using macro F1 and balanced accuracy with fixed model specifications. Class-balanced separability is modest. Random Forest, CatBoost, and LightGBM form a leading cluster with overlapping confidence intervals (macro F1 ≈0.51–0.52). Affective/well-being items, …

The Value Of Personal Data Ecosystems: A Flemish Media Sector Case Study, Maarten De Mildt, Melanie Verstraete, Sofie Verbrugge, Didier Colle

Journal of International Technology and Information Management

Personal Data Stores (PDSs) have been proposed as a privacy-preserving approach to data sharing that increases individual control over personal data while enabling new forms of cross-organizational collaboration. This collaboration leads to the emergence of Personal Data Ecosystems (PDEs). Despite growing interest in PDEs, limited research has examined how the organizational and economic barriers identified in prior studies manifest in practice. This paper investigates these challenges through a case study of the Flemish media sector within the Solid4Media project, which explores the use of PDSs to support data sharing and personalization across media organizations. Using a qualitative research design, data …

Chronofy: A Temporal-Logical Decay Architecture For Information Validity In Time-Aware Retrieval-Augmented Generation, Muntaser Syed, Marius Silaghi, Sheikh Abujar, Sharun Akter

Electrical Engineering and Computer Science Student Publications

Retrieval-Augmented Generation (RAG) systems retrieve and integrate external knowledge to ground large language model (LLM) outputs. However, current RAG architectures treat all retrieved facts as equally valid regardless of temporal provenance, leading to temporal hallucination, where plausible but obsolete facts corrupt the output. A clinical lab reading from yesterday is actionable; the same reading from six months ago is noise. We present Chronofy, a three-layer neuro-symbolic framework implementing the Temporal-Logical Decay Architecture (TLDA) that embeds temporal validity directly into the representation, retrieval, and reasoning layers of RAG systems. Layer 1 reserves a dedicated temporal subspace within Matryoshka embeddings to make …

Epistemic Edge: Subjective Logic Guardrails For Llm-Driven Iot Actuation, Muntaser Syed, Marius Silaghi

Electrical Engineering and Computer Science Student Publications

Deploying large language models (LLMs) as decision-making agents in safety-critical Internet of Things (IoT) systems introduces risks that purely behavioral guardrails, such as action whitelists, cannot fully address. This paper presents Epistemic Edge, a four-tier neuro-symbolic pipeline that augments LLM-driven actuation with subjective logic (SL) uncertainty quantification, temporal decay, and dual guardrails combining epistemic threshold checks with behavioral whitelists. We evaluate seven locally-deployed models: three PrismML Bonsai 1-bit models (1.7B, 4B, 8B), three 4-bit quantized models (Qwen3-8B, Llama 3.2-3B, Phi-3.5-mini), and the DeepSeek-R18B reasoning model, across eight ablation conditions and five IoT actuation scenarios (2,800 controlled trials). We further validate …

Effect Of Cu Content On Microstructure, Morphology, And Antibacterial Properties Of Ti-Cu Alloy Thin Films, Chittra Kedkaew, Phalakorn Khwansungnoen, Tanattha Rattana

Journal of Metals, Materials and Minerals

Ti-Cu alloy thin films exhibit considerable potential for the development of advanced antibacterial surfaces, particularly for biomedical applications. In this research, Ti-Cu binary alloy thin films with a wide range of Cu content from 25.8 at% to 77.8 at% were deposited using magnetron co-sputtering with pure Ti and Cu as the targets. The composition of Cu in the films can be controlled by the applied power of Cu targets. This study investigated the effect of Cu content on the microstructural, morphological, and antibacterial properties using X-ray diffraction (XRD), Field emission scanning electron microscopy (FESEM), Atomic force microscopy (AFM), X-ray photoelectron …

Effects Of Various Heat Treatment Cycles On Mechanical Properties And Wear Resistance Of 65mn Carbon Steel, Amir Abbas Mojahedi, Seyed Abdolkarim Sajjadi, Fatemehsadat Sayyedan

Journal of Metals, Materials and Minerals

The aim of the present study is to investigate the effect of various heat treatment cycles on mechanical properties and wear resistance of 65Mn carbon steel. For this purpose, five different heat treatment cycles including normalizing, austenitizing, quenching, and tempering were performed at different austenitization temperatures and tempering times. Subsequently, effects of the parameters on tensile strength, toughness, hardness, and wear resistance of the heat-treated samples were investigated. X-ray diffraction (XRD) and scanning electron microscopy (SEM) equipped with energy dispersive X-ray spectroscopy (EDS) were employed to analyze microstructure of heat-treated samples. To study the wear resistance of the samples after …

Enhancing Aqueous Solubility Of A Psoralen Derivative Via Cyclodextrin Inclusion Complexation : In Silico And In Vitro Study, Gulzaib Basharat, Saba Ali, Pattharamon Chaikhun, Choosak Jaroenrit, Kuakarun Krusong, Thanthapatra Bunchuay, Tanatorn Khotavivattana, Thanyada Rungrotmongkol

Journal of Metals, Materials and Minerals

N-(4-Bromobenzoyl)-8-methoxypsoralen-4-amine (BNB) is a psoralen derivative with potent cytotoxic activity against breast cancer cells but with limited pharmaceutical application and therapeutic potential due to its extremely low aqueous solubility. To overcome this limitation, β-cyclodextrin (βCD) and its derivatives dimethyl-βCD (DMβCD), hydroxypropyl-βCD (HPβCD), and sulfobutylether-βCD (SBEβCD) were investigated as carriers to enhance BNB's aqueous solubility via cyclodextrin inclusion complexation. A combined computational–experimental strategy was employed, integrating molecular docking, 500-ns all-atom molecular dynamics simulations in quintuplicate runs (2.5 µs in total), and experimental validation by phase solubility analysis, scanning electron microscopy (SEM), and differential scanning calorimetry (DSC). Docking and simulations revealed …

Eco-Friendly Pva-Walnut Shell-Based Triboelectric Nanogenerator For Biomechanical Energy Harvesting And Self-Powered Touch Sensing, Sabita Tripathy, Gayatri Mohapatra, Arjun Kumar, Manoj Kumar Debnath

Journal of Metals, Materials and Minerals

The growing demand for sustainable power in wearable electronics necessitates eco-friendly energy harvesting alternatives. Herein, a polyvinyl alcohol-walnut shell (PVA-WS) composite was developed as a biodegradable triboelectric active layer for a single-electrode triboelectric nanogenerator (TENG). Walnut shell powder, a lignocellulosic agricultural byproduct, was incorporated into PVA at an optimised 3 wt%, enhancing surface micro-roughness and charge trapping capability as confirmed by SEM and XRD analyses. The fabricated device yielded a peak output voltage of 130 V, short-circuit current of 390 nA, and maximum power of 20 μW at 500 MΩ under 1 Hz excitation, while also successfully harvesting biomechanical energy …

Surface Characteristics Of Montmorillonite Reinforced Cellulose Membranes Derived From Pineapple Waste, Naufal Rizky Amasda, Heru Suryanto, Aminnudin Aminuddin, Uun Yanuhar, Nanda Lidya Cinta Aulia Sari, Agus Suyetno, Komarudin Komarudin, Fajar Nusantara, Gaguk Jatisukamto, Aulia Surya Ramadhan

Journal of Metals, Materials and Minerals

This study aims to investigate the effect of montmorillonite on the surface characteristics and porosity of bacterial nanocellulose (BNC) membranes derived from pineapple peel waste. The bacterial cellulose was synthesized using Acetobacter xylinum using pineapple peel extract as medium component. Bacterial nanocellulose membrane (BNC) was obtained by crushing and homogenizing bacterial cellulose in a high-pressure homogenizer. BNC membrane was reinforced with montmorillonite content of 2 wt% to 8 wt%. The membrane was characterized for its properties using SEM, FTIR, surface roughness tester, tensile tester, water holding capacity test, and BET analysis. The results showed that montmorillonite was well-dispersed within BNC …

C.A.S. Full Assessment Report: State Of Florida Government Portal, Delante Clark

Graduate Scholarship and Creative Works

The purpose of this assessment is to evaluate the cognitive overhead, transparency, and attentional integrity of

official State of Florida digital interfaces using the Cognitive Attentional Standards (C.A.S.) platform.

While the Florida Digital Bill of Rights (FDBR) establishes strict regulatory guardrails for consumer data

transparency, tracking opt-outs, and attentional safeguards, the State of Florida explicitly exempts its own

government agencies, public universities, and non-profit entities from complying with these rules.

This assessment serves to investigate the tension between legislative intent and government execution. By

analyzing public sector websites through the C.A.S. platform, this project will establish a “state-enforced vs.

state-executed” …

Towards Optimal And Resilient Ac/Dc Microgrids: Control Design, Analysis, And Implementation, Jun Zhang

Electronic Theses and Dissertations

Microgrids serve as a small-scale power grid for utilizing renewable energy to enhance energy reliability, sustainability, and resilience. As an autonomous system, an islanded microgrid can disconnect from the utility grid and operate independently by maintaining system voltage and frequency. However, this new feature introduces coordination problems among distributed generators (DGs), such as 1) how to make sure the voltage profile and current sharing in DC microgrid with different types of converters; 2) how to reduce the impact of cyberattack when the system coordination is performed based on communication, and 3) how to calculate the steady state under a droop …

Brrbox, Shawn J. Myers, Lane Cline, Michael Davis, Christian Secrest

Williams Honors College, Honors Research Projects

This report details the project known as “The BRRBOX”, a reusable, insulated thermoelectric cooler developed to keep internal temperatures at refrigeration levels or cooler for at least 48 hours. The cooler will track its internal temperature during this period and be able to give the data at the end of its delivery cycle to keep up with food and pharmaceutical standards during delivery. The BRRBOX uses Peltier-based cooling alongside vacuum insulation panels and fans to achieve efficient thermal control. An onboard microcontroller will monitor temperature, record the data, and adjust the cooling output to minimize power consumption. The box will …

Automatic Pet Feeder Network, Daniel J. Herttna, David A. Bechtel, Alexander Deskovich

Williams Honors College, Honors Research Projects

This project will describe the design process and research behind the Automatic Pet Feeder Network, otherwise known as The Petwork. The system consists of a tank to hold the food, a latching system to drop the food at the desired time, a weight sensor to verify that the proper amount of food has been dispensed, a power supply unit that steps down 120V AC standard wall outlet power, & a microcontroller that will interpret the user's input from a mobile phone application. The networking portion is covered by having a primary and a secondary feeder. The mobile application will communicate …

Unmanned Aircraft Vehicle Safety Reporting And Analysis Of Incidents Utilizing Machine Learning, Cody Harrison

2026 Research Poster Competition

Unmanned Aerial Vehicles (UAVs) are rapidly evolving and being integrated into a wide range of applications, from commercial deliveries to police surveillance and recreational use. As UAVs become more prevalent, the complexity of operations and potential for incidents or accidents will continue to increase. Understanding why these incidents and accidents occur is critical to ensure safe and reliable drone operations as the industry continues to grow. To combat these issues, it is invaluable to analyze UAV incidents quantifiably to identify leading causes and risks in a streamlined and efficient matter. Current manual reporting systems often struggle with the sheer volume …

Flair- Flow-Level Anomaly Intrustion Recognition, Joseph Dumond

2026 Research Poster Competition

Industrial control systems (ICS) and industrial Internet of Things (IIoT) networks support critical infrastructure such as power generation, water treatment, and manufacturing. As these systems become more connected, they are increasingly exposed to cyber threats. However, many existing intrusion detection approaches rely on detailed packet inspection or supervised machine learning techniques that require labeled attack data and extensive tuning, making them difficult to deploy in real industrial environments.ICS networks typically generate highly regular and predictable communication patterns due to periodic control logic and deterministic device behavior. Because of this structure, abnormal or malicious activity often appears as a disruption to …

Make It Maritime: A Simulation-Based Engineering Design Challenge Using Multimodal Technologies, Jessica M. Johnson, Jennifer Renne, Jason Dudley

Virginia Digital Maritime Center (VDMC) Faculty Publications

This paper presents The Incredible Bulk, a multimodal, simulation-based engineering challenge that introduces Grades 4–12 to maritime careers and digital transformation. Students assume the roles of different maritime careers to assemble aircraft carrier bulkhead systems using: VR for spatial orientation and task preview; a 3D model as visual work instruction; paper blueprints for part identification and dimensioning; 3D-printed components for hands-on assembly; and an AR app for quality assurance/inspection. Grounded in constructionism and cognitive apprenticeship, the plan–build–inspect loop externalizes thinking and situates coached, authentic practice that advances engineering design, systems thinking, and technological literacy.

Potential Of Stamp Sands As Cemented Tailings, Samuel Sukaria

Dissertations, Master's Theses and Master's Reports

Worldwide mine tailings ponds and reservoirs occupy some 534 billion m³ of space with the volume expected to increase as economic demand for minerals increases over the next decades. These reservoirs produce adverse effects on local communities and ecosystems through structural failure resulting in mass flooding events, drainage of pollutants into water supply and emissions of airborne particulate matter. Methods developed to find use for tailings include extraction of residual minerals and aggregates in construction materials. The latter method has already been used in mining operations to stabilize mining reservoirs and stopes, and as placement for temporary road work …

Investigation Of The Impact Of The Shape Of The Wings On Formula E Racing Car Performance: Enhancements For Optimal Aerodynamics, Ednie Marthe Adlaikah Jozil

Honors Undergraduate Theses

The aerodynamic performance of a Formula E chassis significantly dictates its overall race efficiency, directly impacting crucial parameters such as battery range and thermal management. This thesis investigates the external aerodynamics of the baseline Gen 2 Formula E car and evaluates the performance gains of two novel aerodynamic packages: a "Fully Modified" configuration and a "Flat Rear Wing" design. Computational Fluid Dynamics (CFD) simulations were conducted to analyze drag coefficients (Cd), downforce generation, and vehicle wake structures at race-relevant free-stream velocities (e.g., 37 m/s and 89 m/s). To ensure numerical robustness, the computational setup was validated using a smooth sphere …

Unlocking Green Potential In Indonesian Small Medium Enterprises: Challenges And Opportunities For Sustainable Vermicelli Production, Togar W. S. Panjaitan, Karina Agustin, Prayonne Adi, Jani Rahardjo, I Nyoman Sutapa

ASEAN Journal on Science and Technology for Development

Due to limited initiatives and support, the transition to green manufacturing among small and medium enterprises (SMEs) in developing countries remains challenging. Through a critical literature review and case study of the Indonesian vermicelli industry, this study highlights the importance of collaboration and strong policies to address this. Other findings also reveal that the energy intensity and emissions in the sector exceed best practice benchmarks, with the cooking and drying stages contributing significantly to emissions due to high energy consumption. Lack of government regulations, company awareness, and understanding of applicable practices and technologies creates challenges in green manufacturing. The study …

Hybrid Model For Phishing Website Detection Using Transfer Learning, Atul Dubal, Mansi Subhedar, Santosh Dhamala, Manasi Patil

ASEAN Journal on Science and Technology for Development

The rapid digitization of human activities has intensified reliance on internet-based platforms, creating fertile ground for cybercriminal exploits such as phishing. Despite advancements in detection mechanisms, phishing attacks continue to evolve, leveraging sophisticated visual mimicry to deceive users. This paper proposes a robust vision-based phishing detection system using ensemble deep learning to analyse webpage screenshots. The framework integrates transfer learning with pre-trained VGG16 and DenseNet121 models, extracting complementary low-level texture features (edges, gradients) and high-level hierarchical patterns (logos, layouts). These features are fused through a custom classifier with dropout regularization to mitigate overfitting. A balanced dataset of 3,000 webpage screenshots …