Engineering Commons^™

Hybrid Thermosetting Polymer Nanocomposite Thin Films With Optimized Thermal Conductivity And Mechanical Reinforcement, Vinicius Alvarenga, Camila M. Maroneze, Matheus S. Dias, Bruno Milton Oliveira Silva, Jaime Taha-Tijerina, Christiano J. S. De Matos, Hélio Ribeiro

Informatics and Engineering Systems Faculty Publications

Epoxy-based thin films reinforced with graphene oxide (GO), hexagonal boron nitride (h-BN), and their hybrid combination (GO/h-BN) at low filler contents (<  1 wt%) were developed to advance thermosetting nanocomposites for high-performance thermal interface materials (TIMs). The incorporation of these 2D nanostructures led to marked and simultaneous increases in both the storage modulus (E′) and the glass transition temperature (Tg) for the individual and hybrid systems. These enhancements indicated strong interfacial interactions between the nanofillers and the epoxy matrix, promoting a more efficient crosslinking density and reinforcing the overall rigidity of the polymer network. Uniform thin films, processed under controlled conditions, exhibited efficient phonon transport without compromising their dielectric integrity, as demonstrated by steady-state and 3-ω thermal analyses. The incorporation of 0.5 wt% GO/h-BN resulted in up to …

Evaluating Square Gradient Theory For Correlation And Prediction Of Surface Tension, J. Richard Elliot

University Research

The ESD EOS [Elliott, Suresh, and Dohohue, IECR 1990, 29, 1476] is incorporated into the open-source Square Gradient Theory (SGT) library published by Mejia et al. [Mejia, Müller, and Chaparro-Maldonado, J. Chem. Inf. Model. 2021, 61, 1244]. The combined formalism is evaluated for accuracy compared to experimental measurements and empirical correlation methods. Earlier evaluations of the ESD EOS have shown it to provide accuracy like other EOSs for vapor pressure, vapor–liquid, liquid–liquid, and solid–liquid equilibria where the databases covered roughly 500 compounds and 100–200 mixtures each. For surface tension, a database of measured values for roughly 1000 compounds has been …

Comparative Evaluation Of Segmentation-Based And Pose-Assisted Head Temperature Estimation From Uas Thermal Imagery Under Controlled Conditions, Owais Ahmed, Justin A. Guye, Muhammad Hassan Tanveer, Adeel Khalid

Faculty Articles

This paper presents a vision-based framework for detecting humans and estimating head surface temperature from aerial thermal imagery acquired by Unmanned Aerial Systems (UAS). A comparative evaluation of recent object detection architectures was conducted to identify the most stable and reliable model for thermal human detection under varying flight altitudes. The selected framework integrates two head localization strategies, namely, segmentation-based mask slicing and pose-assisted keypoint localization, to extract head regions and compute per-pixel temperature values from radiometric metadata. The results show that cross-domain inference using pre-trained YOLOv11 models achieves reliable human detection across controlled outdoor environments. Between the two pipelines, …

Quantifying Dag-Ness: A Multi-Component Framework, Erik Csikos

Northeast Journal of Complex Systems (NEJCS)

Directed acyclic graphs (DAGs) are important structures across many disciplines, including mathematics and network science. They are especially useful in modeling causal and hierarchical relationships in a wide variety of applications. The primary
features of a DAG, directedness and acyclicity, are traditionally treated as binary. A graph is either DAG or it is not. Because of this, graphs are not usually interpreted as partially acyclic or partially directed. To address this gap in understanding, we
introduce a framework, consisting of five components, that will provide a continuous measure of DAG-ness. This measure will take into account edge acyclicity, node cyclicity, …

Examining The Use And Perceived Benefits Of Artificial Intelligence Tools In Higher Education: Student Perspectives, Musa Pinar, Haydar Cukurtepe, Aysegul Yayimli, Faruk Guder

Atlantic Marketing Association Proceedings

No abstract provided.

Sex-Based Effects Of Shock Energy Exposure In Warfighters, Melissa Sutter, Catherine Johnson

Mining Engineering Faculty Research & Creative Works

Personal armors were initially designed to fit against the male torso, as men previously filled roles requiring them, thus not made to accommodate the female anatomy. As a result, armor worn by female warfighters tends to have non-form fit in the waist, armpit, bust, and collarbone areas, causing reduced coverage. Shifting, riding up, air gaps, breathing difficulty, and physical discomfort have also been observed. Although this has been documented, the impact on the armor's protective capabilities has not been well studied. To address this, this study compared the protective capabilities of unisex armor for male and female warfighters from shock …

Preliminary Sonification Of Enso Using Traditional Javanese Gamelan Scales, Sandy Hs Herho, Rusmawan Suwarman, Nurjanna J. Trilaksono, Iwan P. Anwar, Faiz R. Fajary

Northeast Journal of Complex Systems (NEJCS)

Sonification—the mapping of data to non-speech audio—offers an underexplored channel for representing complex dynamical systems. We treat El Niño-Southern Oscillation (ENSO), a canonical example of low-dimensional climate chaos, as a test case for culturally-situated sonification evaluated through complex systems diagnostics. Using parameter-mapping sonification of the Niño 3.4 sea surface temperature anomaly index (1870–2024), we encode ENSO variability into two traditional Javanese gamelan pentatonic systems (pelog and slendro) across four composition strategies, then analyze the resulting audio as trajectories in a two- dimensional acoustic phase space. Recurrence-based diagnostics, convex hull ge- ometry, and coupling analysis reveal that the sonification …

Reducing Systemic Bias In Behavioral Targeting Using Explainable Ai: The Harmonia Complex Systems Approach, Ruchira Deokar, Preethi Nanjundan, Jossy P. George, Carlos Gershenson

Northeast Journal of Complex Systems (NEJCS)

Behavioral targeting is a key part of the modern advertising web's algorithmic engine. However, it is unclear whether optimization processes worsen bias, promote unchecked spread in filter bubbles or lower overall users' trust levels. This paper introduces HARMONIA (Holistic Adaptive Regulatory Model for Optimizing Non-transparent Intelligent Advertising), a comprehensive, data-driven Explainable Artificial Intelligence (XAI) framework aimed at transforming behavioral targeting via transparency, interpretability, and adaptive ethical regulation. This paper conducted a comprehensive Explorative Data Analysis (EDA) on the public Criteo Display Advertising Dataset, which contains over 45 million records, to identify patterns in high-dimensional user-ad interaction space. This analysis uncovered …

Relation Between Swelling Potential And Swelling Pressure For Different Types Of Expansive Clay Of New Cairo, Sherouk Hany Mohamed, Amr Radwan, Mohammed Rabie, Hussein Mostafa

HBRC Journal

The purpose of this paper is to present correlations that may help in predicting swelling pressure (P_S) and swelling potential (SP) for expansive clay, which can contribute to solving engineering problems such as cracking, shifting or other structural damage, that may occur, if the behavior of this type of soil is not taken into consideration. Therefore, in this research, five different samples of expansive clay soils were collected from different site locations in New Cairo, Egypt. Then, these samples were dried, pulverized and passed through sieve No. 40 (0.425 mm). The samples were prepared initially at maximum dry …

Indirect Carbonation Of Fbc Ash For Sustainable Production Of Caco3 And Reactive Pozzolanic Residues, Suhawn Ju, Heejung Jun, Seongho Han, Minseok Kim, Soohyun Song, Mingi Cho, Sukhoon Pyo, Jinyoung Yoon

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

This study investigates the potential of indirect carbonation for CO₂ sequestration and high-purity CaCO₃ production using fluidized bed combustion (FBC) fly ash (FFA) and bottom ash (FBA). XRF and XRD analyses revealed high reactive CaO contents derived from lime, portlandite, and anhydrite. Calcium extraction using 1- mol NH₄Cl achieved markedly higher efficiency than deionized (DI) water, yielding up to 17,586 mg/L of Ca²⁺ and producing 10.2 wt.% and 8.4 wt.% CaCO₃ from FFA and FBA, respectively, with CO₂ capture capacities of 45.0 and 36.8 kg per ton of ash. The precipitated CaCO₃ exhibited …

Performance Analysis Of A Converted Electric Underbone Motorcycle: A Combined Dynamometer And Road Test Approach, Dhimas Oki Permata Aji, Sigit Suwarto, Yunus Ari Rokhim

Journal of Mechanical Engineering Science and Technology (JMEST)

In developing countries, converting traditional underbone motorcycles to electric vehicles transforms sustainable transportation from a theoretical concept to a practical implementation. This paper describes the design and operational performance evaluation of an electric underbone motorcycle conversion system that integrates a 2.0 kW, 72 V BLDC motor and a 72 V, 20 Ah lithium-ion battery pack. Compared to previous studies, this paper combines, for the first time, both dynamometer and road tests as the basis for a comprehensive performance assessment of low-cost motorcycle conversion. The dynamometer test was conducted under laboratory conditions to evaluate the test system for torque, power output, …

Mechanisms Of Ventricular Catheter Obstruction, Mohamed Khalil Attie Ms, Christopher Roberts Ms, Carolyn Harris Phd

Medical Student Research Symposium

Background: Hydrocephalus is treated primarily with ventriculoperitoneal shunts, which fail over time mainly due to proximal ventricular catheter (VC) obstruction of the drainage holes. Prior computational fluid dynamics (CFD) studies based on idealized geometries have suggested that cerebrospinal fluid (CSF) preferentially enters distal holes due to lower resistance, thereby increasing the risk of obstruction at those locations. However, these models do not incorporate explanted VC data, patient-specific anatomy, or differences in catheter architecture.

Methods: To evaluate whether flow distribution matches failure sites, we compared obstruction patterns from 30 explanted catheters with CFD simulations of four commercial VC designs. For every …

A Comprehensive Review Of Wireless Charging Technologies: Inductive, Capacitive And Hybrid Power Transfer, Zahraa M.Y. Islam, Yasir M. Y. Ameen

AUIQ Technical Engineering Science

Wireless power transfer has attracted more and more attention as a potential solution to electric vehicle charging due to its safety, convenience and the potential to automate this process. This review paper gives an overview of inductive and capacitive wireless power transfer technologies, especially focusing on hybrid wireless power transfer systems that integrate both approaches. The basic operating principles in both inductive and capacitive power transfer are covered with an emphasis on their advantages and inherent limitations with respect to efficiency, voltage and current stress, the tolerance of misalignment and the power capability. Building upon this background, the paper is …

A Platform For Acquiring And Classifying Low-Noise Electrocardiogram Signals For Applications In Cardiovascular Monitoring, Begmamat Berdimurodovich Dushanov, Narzullo Mamatov Dr.

Technical science and innovation

The early screening and continuous monitoring of cardiovascular diseases need effective acquisition and smart processing of electrocardiogram (ECG) signals. In this article, we introduce a compact platform designed for the acquisition of low-noise ECG signals and classification of the signals using a one-dimensional convolutional neural network (1D-CNN). Our compact platform consists of a low-noise analog front-end (AFE), including an instrumentation amplifier and a chain of analog filters, along with a data acquisition component designed to ensure effective suppression of baseline wander and high frequencies. Our compact platform consumes a low amount of power and can therefore be used for continuous …

Using Machine Learning Algorithms To Clarify Relationships Between Soil Properties And Lead Stomach Bioaccessibility, Shehan Wijesinghe, Dibyendu Sarkar, Hadeer Saleh, Khalid Mustafa, Smitha Rao, Rupali Datta

Michigan Tech Publications

Featured Application: This paper has important applications in environmental health risk assessment and urban soil remediation planning. By demonstrating how machine learning can predict lead bioaccessibility in lead paint-contaminated soil, the study provides a scalable, cost-effective alternative to laboratory-based extraction methods. Such models could support rapid screening of contaminated sites, helping prioritize high-risk areas for intervention and allocate remediation resources more efficiently. This model is expected to advance data-driven decision-making for managing lead-contaminated soils and protect vulnerable urban populations from exposure. Lead contamination in urban soils, primarily from deteriorating lead-based paint, poses a significant health risk in the United States. …

Thermoacoustic Effects Of A Variable Equivalence Ratio In A Single Element Methane Combustor, Carter Green

Doctoral Dissertations and Master's Theses

Combustion instability is one of the leading factors in limiting the progress and innovations of liquid rocket engines and power plants. Under certain operating conditions, unsteady heat release and acoustic wave interactions can couple and lead to instabilities, such as self-sustaining pressure oscillations, that can lead to reduced combustor performance and potentially hardware damage. In this project, the thermoacoustic effects of controlling the equivalence ratio of a single-element natural gas combustor were modeled and analyzed. The project used Fidelity Pointwise for meshing, ANSYS Fluent for modeling, ERAU VEGA HPC for computing, and MATLAB for acoustic analysis. A numerical model of …

Threat-Analysis Oriented Digital Twinning Of Ml-Powered Future Autonomous Weapon Systems, Thomas Neubert

Doctoral Dissertations and Master's Theses

Warfare is undergoing a rapid transformation with the integration of artificial intelligence (AI) and machine learning (ML) into autonomous weapon systems (AWS) for perception, decision support, and control. As these systems become more software-defined, their cyber attack surface expands across sensing, communications, autonomy logic, and human-machine interfaces. As human oversight diminishes, ensuring the cybersecurity, resilience, and reliability of these systems becomes critical to mission success. This thesis investigates how a digital twin-driven threat modeling framework that integrates system-centric analysis with adversary-informed methodologies can support structured cybersecurity vulnerability evaluation and defensive strategy development associated with ML-powered AWS. First, the study analyzes …

Exploring Scms And Fibers For Structural Build-Up In 3d Printing Using Penetration Test, Shiva Kumar Goud Kasani

Miners Solving for Tomorrow Research Conference

Additive manufacturing with cementitious materials advances rapidly, but predicting structural build-up is critical for 3D printed structure buildability. Various supplementary cementitious materials (SCMs) and fibers are commonly used to enhance structural build-up in 3D printing. Evaluating their effects is necessary for successful printing. In this research, this effect is studied for common SCMs, including fly ash and silica fume, and fibers including polypropylene (0.375% and 0.75% by volume), steel (0.75% and 1.5% by volume), and hemp fibers (0.375% and 0.75% by volume). The Structural build-up was quantified through continuous static yield stress measurements (via vane rheometer, penetration, and slump) during …

Synthesis And Hydrothermal Evaluation Of Poly(Styrene Phosphonate) For Conformance Control In Geothermal Reservoirs, Sara Mccauley

Miners Solving for Tomorrow Research Conference

As atmospheric carbon dioxide levels continue to rise, geothermal energy has emerged as a promising energy alternative to fossil fuels. A barrier to widespread implementation and energy production efficiency is macro-heterogeneity of the rock matrix. Cracks, void spaces, and flow conduits divert fluid flow away from unswept portions of the geothermal reservoir and can cause cooling of the reservoir. Flow heterogeneity has been treated in oil reservoirs by injecting hydrogel particles that travel preferentially to ultra-high permeability zones and selectively block fluid flow in these regions. We are applying polymer hydrogels that withstand hydrothermal conditions of 225 up to 275°C …

Challenges And Best Practices Of Regional Innovation Ecosystems, Mahnaz Asgari Sooran

Miners Solving for Tomorrow Research Conference

Many places around the world are developing regional innovation ecosystems to spur regional economic. Many innovation ecosystems fail or barely maintain their initial momentum after a few years. In this paper, we identified challenges and best practices facing innovation ecosystems interviews with the innovation ecosystem stakeholders. We employed the MIT REAP (Regional Entrepreneurship Acceleration Program) model to categorize the five main stakeholders of the innovation ecosystem: entrepreneurs, universities, industry, risk capital, and government. Our initial results indicated the following: (a) Access to capital and talented workforce; (b) Stakeholder discovery process is one of the critical areas to understand the basic …

Simulating Thermal Diffusion Through Image-Derived Microstructures Of Ceramic Matrix Composites, Matik Heskin

Miners Solving for Tomorrow Research Conference

Thermal energy transport in materials can be effectively modeled using finite element software such as COMSOL. Experimentally measured or NIST–JANAF thermal conductivity data can be used to represent material behavior within these simulations. For heterogeneous or composite materials, effective properties are often approximated using rule-of-mixtures calculations. However, this overlooks the nuanced effects caused by complex microstructural geometry. To address this limitation, imaging and coding tools such as MATLAB can be used to process scanning electron microscopy (SEM) images. By thresholding the images to distinguish constituent materials, a representative mesh can be generated and imported into an FEM program. This approach …

Human Intention Prediction Using Cnn And Lstm Networks In Physical Human–Robot Interactions, Khosro Ghorbani Zadeh

Miners Solving for Tomorrow Research Conference

Advances in robotics and artificial intelligence have increased expectations for interactive robots in eldercare and assistive applications. A key challenge in creating safe and effective systems is accurately recognizing human intent and translating it into meaningful commands for robots to follow. Traditional physics-based models often fail to fully represent human force interactions due to their dynamic nature, while neural networks provide a promising alternative for predicting force-movement intentions. Multi-layer perceptrons (MLPs) show potential, however, they struggle with temporal dependencies and generalization. Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNNs) help address these limitations. This study compares these architectures …

Ai-Driven Frameworks For Mitigating Rockfall Hazards, Unstable Ground Condition And Improving Safety In Underground Mine Through Thermal Imaging, Akhrorbek Narmatov

Miners Solving for Tomorrow Research Conference

Scaling, the removal of loose rocks from excavation walls to prevent rockfalls is a critical safety procedure in underground mining operations. Approximately a quarter of fatal mining accidents are due to rockfalls. Detecting unstable rocks during scaling and assessing ground stability remain challenging due to limited visibility, dust, and environmental conditions.

Excavation disturbs the in-situ stress state, causing stress redistribution, fracture propagation, and the formation of discontinuities that lead to loose rock blocks. Ventilation airflow affects heat transfer at exposed surfaces, amplifying temperature contrasts between intact rock and fractured blocks associated with instability.

Current practices rely on manual inspection, requiring …

Toward Sustainable 3d Printable Cementitious Materials: Low-Carbon Design With Fiber Reinforcement, Nima Mahmoudzadeh Vaziri

Miners Solving for Tomorrow Research Conference

3D printing of cementitious materials, as an emerging construction technology, faces challenges in both mechanical performance and sustainability. Conventional mixture designs rely on high cement contents, leading to increased CO2 emissions, while printed elements often exhibit brittle behavior with limited crack resistance and reduced post-cracking performance. This study investigates the development of low-carbon 3D printed cementitious composites using environmentally friendly supplementary cementitious materials (SCMs) and fillers, combined with fiber reinforcement to enhance mechanical performance. Locally available SCMs and fillers were incorporated to significantly reduce cement content (>40%) and improve sustainability. Fiber reinforcement was introduced to mitigate brittleness and enhance …

Breath-Based Detection Of Liver Cancer Biomarkers Using An Swcnt-Fet Nanobiosensor: Quantumatk, Mohamed Mohieb Rashdan

Thesis/ Dissertation Defenses

There are still no tests to detect liver cancer in the early stages because it is a slow-growing and invasive type.

This study describes the use of a single-walled carbon nanotube-based field-effect transistor (SWCNT-FET) whose ability to detect hexanal, a volatile organic compound (VOC) found to be elevated in liver cancer, has been demonstrated through direct measurements from exhaled breath. The device is designed using QuantumATK with the semi-empirical Extended Hückel Hamiltonian framework in non-equilibrium Green’s function (NEGF) which shows realistic contact physics by using metallic SWCNT electrodes instead of common metal films. Through the analysis of two zigzag channels …

Scenario-Based Pareto Analysis For Multi-Objective Optimization Of Process Parameters To Improve Life Cycle Impacts: Case Study Of Ge Production, Dennis Dadzie

Miners Solving for Tomorrow Research Conference

Growing demand for critical minerals increases the need for clear evidence on the environmental burdens of their production. Life‑cycle assessment (LCA) quantifies impacts, but it does not by itself show how to navigate competing environmental performance improvement goals. We examine 63 process configurations for single‑crystal germanium made via chlorinated distillation using five indicators: global warming potential (GWP), water consumption (WC), fine particulate matter (FPM), terrestrial acidification (TA), and cumulative energy demand (CED). Across scenarios, WC is negatively correlated with GWP, weakly related to FPM, TA, and CED, while the other four indicators are strongly positively correlated. Pareto analysis highlights a …

Assessing Radon And Radon Progeny Deposition On Simulated Lung Filter System: Effects Of Cigarette And E-Cigarette Use Based On The Icrp Model, Manuela Isabel Arenas Alvarez

Miners Solving for Tomorrow Research Conference

This project investigates the potential interaction between radon exposure and e-cigarette aerosols, focusing on how radon progeny deposit in the lungs under combined conditions. An experimental system was developed to simulate regional lung deposition based on the International Commission on Radiological Protection (ICRP) model. The setup uses a filter-based design and a custom modular atomizer to generate stable aerosols, with four commercial plastic filters evaluated. Initial results demonstrate reproducible filtration behavior and a total deposition pattern matching ICRP predictions within 21% error. Ongoing work aims to improve agreement with regional deposition curves and enable combined radon–aerosol exposure experiments. This platform …

Preventive Maintenance Scheduling Using Artificial Intelligence And Decision Support Agent, Samiksha Aryal

Miners Solving for Tomorrow Research Conference

Preventive Maintenance models have traditionally relied on a time-based maintenance model, which uses fixed statistical distribution to represent the time-to-failure (TTF). The requirement of data-driven models and automated decision-making systems have become essential for modern manufacturing systems. The use of fixed statistical distribution limits the ability of existing models in producing solutions in real-time. Our model overcomes these limitations by implementing an empirical distribution to represent TTF. The empirical distribution is generated using a neural network which eliminates noise from the raw maintenance log. Renewal Reward Theorem (RRT) is implemented to efficiently provide maintenance threshold in real time. The use …

Robustness Of Fuzzy Artmap To Adversarial Attacks And Progressive Adversarial Training For Streaming Learning, Shane Cairns

Miners Solving for Tomorrow Research Conference

Incremental learners deployed on streaming data must remain robust to evolving adversarial perturbations, yet most adversarial-robustness studies assume offline multi-epoch training with repeated access to historical data. We investigate adversarial robustness in Fuzzy ARTMAP, a prototype-based Adaptive Resonance Theory model that supports single-pass learning without replay. We propose WB-Softmax, a differentiable relaxation that aggregates category-level activations into class-level scores for gradient-based attacks. WB-Softmax PGD achieves 89–100% attack success on vanilla models, exceeding transfer and query-based baselines. We then study adversarial training under true streaming constraints by comparing offline versus online adversarial example generation and standard versus selective updates. Offline adversarial …

Assessing The Effects Of Scale-Dependent Representation Of River Networks On Hydrologic Prediction, Hari Dhital

Miners Solving for Tomorrow Research Conference

Accurate hydrologic prediction at relevant spatial scales is essential for flood risk management. This study explores how spatial scale affects model parameters and simulation outcomes in the Hillslope Link Model (HLM). This was motivated by HLM implementation within the Next Generation Water Resources Modeling (NextGen) framework for the U.S. National Water Model. Since NextGen alters HLM's spatial scale from hillslopes to catchments, we assess how this change affects runoff generation and routing. We implement HLM at both scales using identical, predetermined parameters without calibration to isolate spatial discretization effects. Using approximately ten years of precipitation and streamflow data from watersheds …