Digital Commons Network^™

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 …

Ai-Based Music Mood Analysis With Historical And Real-Time Data, Biswash Bhattarai

Williams Honors College, Honors Research Projects

The Music Mood Analyzer Dashboard identifies and visualizes the emotional tone of songs using audio features like tempo, energy, and valence. It classifies tracks into moods such as happy, sad, or calm and presents insights through an interactive dashboard. The project combines music analysis and data visualization to help users understand how sound relates to emotion.

Proceedings Of The Eleventh Annual Indiana Stem Education Conference: Stem Journeys, William S. Walker Iii, S. Selcen Guzey

Indiana STEM Education Conference

The Proceedings of the Eleventh Annual Indiana STEM Education Conference are edited by the Center for Advancing the Teaching and Learning of STEM (CATALYST, https://www.education.purdue.edu/catalyst/) at Purdue University. The theme for the 2026 conference is STEM Journeys, celebrating the multiple pathways and experiences that advance student learning in STEM education.

Breech Baby, Madison Kaufman, Cassidy Allen, Lilian Mills

Williams Honors College, Honors Research Projects

Our project aims to develop a non-invasive device to assist in turning breech babies to a head down position before delivery. Pregnant women facing breech presentations often need safe and effective solutions, yet current options like external cephalic version (ECV), maternal positioning techniques, and cesarean sections can present challenges. Key barriers include variability in maternal and fetal anatomy, patient comfort, compliance, and training for healthcare providers, along with cost and insurance concerns.

Our innovative device will address these issues by providing clear guidance and support throughout the process. It will prioritize minimizing discomfort and risk, ensuring adaptability for various stages …

Network Merge, Alexander York

Williams Honors College, Honors Research Projects

This project will be simulating the merge of two company's networks. Company A will contain two sties connected with a VPN, and will extend this VPN to one site for Company B. This project will focus on researching how merging a network works, how routes are commonly redistributed across different routing protocols, and how each site can run their own but link servers(DHCP, DNS, etc.). Both sites will be secured from both outside and inside attacks through passwords and other network security features such as VLANs & BPDU Guard.

Breaking The Vapor Barrier And Scale: Revolutionizing Steel Quenching With Ultrasound Technology, Anthony O. Santos

Williams Honors College, Honors Research Projects

The quenching process is a fundamental heat treatment used to enhance material properties by heating steel to its austenitizing temperature and rapidly cooling it to form high-strength martensite. However, this process is often hindered by two surface barriers: the Leidenfrost effect (vapor blanket) and oxide scale. These cooling limitations restrict the use of steel in high-performance aerospace applications due to inconsistent material properties and unpredictable engineering properties. This research investigates the use of fully submersible, 50-watt 40 kHz ultrasound technology to improve cooling rates in a Jominy test [4]. Through numerical simulations and experimental validation, the study demonstrates that acoustic …

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 …

A Dual-Domain Face Forgery And Deepfake Detection Framework, Neha Pradyumna Bora, Pradyumna Mulchand Bora, Rushikesh Sanjay Kumavat, Raunak Manoj Gangwal, Prit Sandesh Jain, Hardik Vijay Ostwal

Mansoura Engineering Journal

Concerns about media authenticity, privacy, and information security arising from rapid advances in deepfake technology have made it increasingly important to detect manipulated facial content reliably. The primary goal of our work was to develop a deepfake detection model with high generalization across multiple datasets. To achieve this, we developed a hybrid detection approach that combines spatial visual texture analysis and frequency-domain analysis to detect manipulated facial images. Our approach includes convolutional spatial feature extraction from facial images and frequency—domain representations of the same images obtained by applying the fast Fourier transform. To help alleviate concerns about overreliance on frequency—domain …

Multi-Method Energy Optimization: Linear Programming, Hmm Modeling And Arduino-Based Simulations, A.E. El-Alfy, Eman Elayat, M. A. E. Sheta

Mansoura Engineering Journal

This paper presents the simulation and optimization of hybrid energy systems integrating renewable energy and storage technologies. Linear Programming (LP) is utilized to minimize operational costs, while a Hidden Markov Model (HMM) improves reliability by accurately predicting energy flow. Hardware-in-the-loop simulation in Proteus demonstrates efficient energy trading, significantly reducing dependence on conventional sources. The results from a 24-hour analysis show that the system achieves an 87.14% load factor, indicating high efficiency in utilizing the system's rated capacity, 26.23 system reliability, and a 20% improvement in cost efficiency and enhanced sustainability, providing a robust and practical framework for hybrid energy solutions …

Dielectric And Thermal Ageing Characteristics Of Al₂O₃ Nanofluid-Impregnated Cellulose For Power Transformer Applications, Shaymaa A. Qenawy, Basma Eltlhawy, Hussein M. Waly

Mansoura Engineering Journal

As nanotechnology progresses, nanofluids have emerged as promising candidates for transformer insulation due to their enhanced dielectric and thermal properties. This study evaluates the degradation behavior of a mineral oil-cellulose system compared to an alumina (Al₂O₃) nanofluid-cellulose system. Accelerated thermal ageing tests were conducted at 120°C for a 20-day duration, simulating approximately 20 years of field service. Key findings reveal that the nanofluid-impregnated paper exhibited superior mechanical longevity, characterized by a 3% reduction in the tensile strength deterioration rate relative to mineral oil samples. Initially, the AC breakdown voltage (BDV) of the nanofluid was 10.85% higher …

Preserving The Identity Of Historic Coptic Orthodox Monasteries In Egypt Under Contemporary Pressures: Case Studies Of St. Bishoy And St. Anthony Monasteries, George Medhat Adeeb, Mohamed Khairy Amin, Mohamed Ahmed Al-Sherbiny

Mansoura Engineering Journal

Historic Coptic Orthodox monasteries in Egypt (HCOMEs) represent an important component of Christian heritage, integrating architectural value with enduring spiritual traditions that reflect both tangible and intangible dimensions. However, contemporary development and changing functional demands are generating transformations that may affect their identity if not carefully managed. Despite extensive scholarship, limited research has systematically examined these transformations through a structured evaluative approach. This study addresses this gap by developing and applying an analytical and evaluation framework to examine how contemporary pressures influence the historical, architectural-spatial, and spiritual identity of HCOMEs, and to assess the effectiveness of monastic responses. The framework …

Self-Lubricating Nano-Coatings For Tribological Applications: Materials, Mechanisms, And Ai-Driven Design Approaches, Viral Panara, Vikas Panchal, Satayu Travadi, Harmish Bhatt, Madhav Oza

Mansoura Engineering Journal

Self-lubricating coatings with nanostructured structures are becoming crucial in order to decrease friction and wear in critical tribological systems like precision tools, biomedical implants, aerospace actuators, and engines. In this review, the most representative nano-engineered solid lubricants such as transition metal dichalcogenides, diamond-like carbon, hexagonal boron nitride, graphene, MXenes and hybrid multilayer architectures are discussed. The focus of the discussion is on the most important tribological mechanisms like lamellar sliding, oxidative adaptation, tribofilm formation, transfer-film development, and nano-asperity contact evolution. It also summarizes the most significant deposition techniques, such as cathodic arc physical vapor deposition, chemical vapor deposition, plasma-based deposition, …

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 …

Advancing Ultrahigh Carbon Steel Characterization: A Metaheuristic-Tuned Deep Learning Approach, Walaa Omar El-Farouk Badr, Hossam El-Din Mostafa, Rania Elbana

Mansoura Engineering Journal

Accurate classification of ultrahigh carbon steel (UHCS) microstructures is essential for elucidating processing-structure-property relationships and enhancing material performance. While convolutional neural networks (CNNs) offer powerful automated classification, navigating their complex, high-dimensional hyperparameter spaces present a significant computational bottleneck. To advance automated materials characterization, this study proposes a metaheuristic-tuned deep learning approach for robust and efficient microstructure classification. Two architectures, VGG16 and MobileNetV2, were evaluated under both pretrained and fine-tuned configurations, with Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Ant Colony Optimization (ACO) applied for systematic hyperparameter tuning. Results show that GA substantially improves the performance of fine-tuned VGG16, achieving …

Mathematical Analysis Of The Slip Flow Due To A Cylinder Oscillating In Different Directions With Independent Amplitudes, Alana Sankar, Karim Rahaman

Mansoura Engineering Journal

This study examines the incompressible viscous fluid flow in an infinitely long cylinder, with slip occurring at the cylinder’s surface, undergoing longitudinal and torsional oscillations of independent amplitudes. The proposed governing equations are solved subject to the Basset slip condition. Analytical expressions for the velocity field, shear stresses, drag force on the cylinder, work done and the drag coefficient are obtained. Velocity components, drag and work done are illustrated graphically. The magnitude of the velocity increases as slip decreases and as the frequency of oscillations increases. Drag increases in both directions as the slip decreases and as the frequency of …

A Multi-Valued Fixed Point Theorem For Quasi-Contractions On A Cone Metric Space, Regina Mahadewsing, Sreedhara Rao Gunakala, Vikash Ramcharitar, Reddappa Bandi, Akhenaton Daaga, Thameem Basha H

Mansoura Engineering Journal

A set-valued (multi-valued)  mapping  assigns to each  a nonempty closed and bounded subset . Using this notion, the present work broadens classical fixed point theory by proving a fixed point theorem for multi-valued quasi-contractive mappings in cone metric spaces. The developed argument extends several earlier results that were restricted to single-valued maps and more familiar set-valued settings, thereby providing a wider analytical framework within ordered Banach-space structures. These contributions enrich fixed point theory in generalized metric environments and can be relevant to problems in nonlinear analysis and optimization

Performance Of Foamed Concrete Before And After Fire Conditions: A Review, Poles Bahgat, Mohamed Kohail, A. Fathy, A. Afifi

Mansoura Engineering Journal

Foamed concrete is defined as a type of concrete distinguished by its workability, low density, and insulating properties. It is used as building material. The objective of this review is to discuss the physical and mechanical characteristics and fire sensitivity of foamed concrete. Density influences the strength of concrete. The strength of concrete is between 2 and 3.5 MPa, which increased with the addition of gold mining waste, reaching approximately 35 MPa at optimal replacement levels.  There is a 60-70% reduction in strength for lightweight concrete with a density of 400-1200 kg/m³ compared to conventional concrete. The fire sensitivity of …

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 …