Digital Commons Network^™

Debatrix, Vivienne Lu, Huy Ngo, Luke Ponssen, Jonathan Preiss, Ryan Rani

Computer Science and Engineering Senior Theses

Developing public-speaking skills remains a persistent challenge in formal education, constrained by limited instructional time and the lack of scalable, individualized feedback. Existing automated tools address only narrow aspects of this problem, offering text-based coaching against rigid rubrics that fail to capture argument quality, evidence use, or real-time rebuttal skill. This thesis presents Debatrix, an AI-powered platform that enables K-12 students, university learners, and independent self-studiers to debate an intelligent opponent. The system combines automatic speech recognition, large language model-driven rebuttal generation, and a multi-dimensional rhetorical analysis engine that evaluates argument structure, evidence integration, and persuasive technique. Users receive explainable …

Engineering: What Are We Doing?, Matthew Kuperus Heun

University Faculty Publications and Creative Works

Keynote speech at 2026 Christian Engineering Society Conference and 2026 Association for Christians in Mathematical Sciences Conference

Coupled Ferroelectricity And Phonon Chirality, Xiang-Bin Han, Cong Yang, Rui Sun, Xiaotong Zhang, Thuc Mai, Zhengze Xu, Aryan Jouneghaninaseri, Xiaoning Jiang, Rahul Rao, Yi Xia, Multople Additional Authors

Mechanical and Materials Engineering Faculty Publications and Presentations

Recognizing the coupling between ferroelectricity and chirality in optically active ferroelectrics opens a route for manipulating chirality via ferroelectricity under an external electric field, enabling control over chirality-dependent quantum states. Here, we report the experimental demonstration of the coupling between ferroelectricity and phonon chirality in the molecular ferroelectric triglycine sulfate. By electrically switching the crystal chirality, we achieve reversible and device-compatible control of phonon chirality, as revealed by in situ time-resolved magneto-optical Kerr effect measurements. The Kerr rotation reverses with electric-field switching, while phonon chirality vanishes in the paraelectric phase and is tunable in the racemic ferroelectric state. Furthermore, density …

A Faith And Technology Resource Hub: Building The Christian Engineer’S Bookshelf, Gayle Ermer, Derek Schuurman

University Faculty Publications and Creative Works

A wealth of material related to the interactions between faith and technology has been generated over time to help Christian engineers reflect on and evaluate their work and technology development more generally. However, there is currently no central location where this large variety of resources can easily be accessed. This paper will describe the process of developing a faith and technology resource hub. The vision for the hub is that it will include a comprehensive searchable directory of resources addressing faith and technology, as well as a browsable, organized, curated, and annotated set of webpages containing links to particularly important …

From Theory To Practice: Investigating Process Safety Skills Acquisition And Bridging The Industry Readiness Gap, Brittany Butler-Morton

Theses and Dissertations

Process safety management is vital to companies operating highly hazardous materials or processes, and it is of interest to the engineering community as poor process safety judgments can have catastrophic results. Process safety judgments consider more than the prioritization of safety, as they are often influenced by elements like production, spending, reputation, and time. As such, it’s important to prepare engineering students nearing graduation for the complexity of these judgments and narrow the Theory-to-Practice gap for students entering industry. This work sought to identify 1) how the Theory-to-Practice gap is manifesting in process safety judgments, and 2) how the application …

Zirconium Metal-Organic Cages: Synthetic Development Of Chromium-Functionalized Ligands, Jim P. Heller, Jonathan E. Pines, Miguel I. Gonzalez

Wetterhahn Science Symposium Posters

Metal-organic cages (MOCs) are a class of highly porous molecules composed of inorganic clusters bridged by highly tunable organic ligands. The synthesis and development of various ligands could allow for more selective and efficient catalysts. Specifically, Chromium-based homogeneous catalysts have recently been commercialized due to their high selectivity in the production of 1-hexene and 1-octene. This project aims to synthesize reusable heterogeneous catalysts composed of chromium-functionalized zirconium MOCs deposited on mesoporous supports.

The current focus of this project is to synthesize and purify the "SNS Ligand." This ligand can coordinate to chromium via its S—N—S moiety. This project specifically focuses …

A Distinctly Christian Understanding Of The Technical Details In Engineering, Paul Griffioen

Faculty Work Comprehensive List

Within engineering disciplines, much attention has been given to developing pedagogical techniques and practical applications that are distinctly Christian. However, not as much attention has been given to understanding technical engineering content from a distinctly Christian perspective. The main reason is that the technical details of engineering seem to be the same for both Christians and non-Christians. After all, does being a Christian have any impact on the content of specific technical details like integration and finite element analysis? Since the vast majority of time in engineering jobs, research, and teaching is spent on specific technical details, this is a …

Evaluating Soil Health And Crop Yield In Louisiana Agricultural Systems: Impacts Of Best Management Practices And Prediction Models, Hector J. Mendoza Lagos

LSU Doctoral Dissertations

The adoption of conservation management practices is critical for improving soil health, enhancing nutrient use efficiency, and sustaining crop productivity in row crop systems in Louisiana. This study evaluated the role of conservation agronomic practices, soil biochemical indicators, and machine learning predictive models to improve soil nutrient dynamics, soil health indicators, microbial communities (MC), and crop productivity on a corn (Zea mays L.) research plot scale and in a commercial forty-hectare cotton (Gassypium hirsutum L.)-corn-soybean (Glycine max L.) rotation system in northeast Louisiana. The objectives of the study were to evaluate soil nutrient dynamics and MCs under …

Measuring Stock Market Inefficiency Using A Multilayer Composite Efficiency Index: A Case Of The Egyptian Exchange, Patrick K. Owido, Hiroki Sayama

Northeast Journal of Complex Systems (NEJCS)

Financial markets play a critical role in resource allocation. Their performance depends on the decisions of millions of independent investors constantly reacting to one another. Their informational efficiency remains a subject of debate across economic systems. When informational efficiency is present at the weak form, historical price information should not consistently predict future returns. Several empirical tests of this hypothesis often focus on the behavior of aggregate market indices, and use individual efficiency proxies such as autocorrelation, GARCH-type volatility, or entropy-based measures to measure efficiency. This has often yielded mixed results, particularly in emerging markets. Here we show that testing …

Wake-On-Anomaly Federated Architecture For Privacy-Preserving Poultry Health Early Warning, Mahmoud Aziz Louati

Masters Theses

Highly pathogenic avian influenza outbreaks, respiratory disease, heat stress, and silent equipment failures share one operational reality: they are detected too late because today’s poultry-health workflow is reactive, manual, and dependent on producers volunteering commercially sensitive data. This thesis presents a wake-on-anomaly federated architecture that addresses both the detection-latency problem and the privacy–adoption deadlock that has so far prevented cross-farm collaboration. The architecture is organized in two tiers. Tier 1 is a lightweight LSTM autoencoder that continuously screens four routine telemetry channels (water, feed, house temperature, activity proxy) and emits a per-window reconstruction-error score. A debounced k-of-m trigger with cooldown …

Isometric Force Characterization Of Braided Pneumatic Actuators, Ben Bolen, Mohammad Elzein, Lawrence Pang, Alexander Hunt

Mechanical and Materials Engineering Faculty Publications and Presentations

Artificial muscles such as braided pneumatic actuators (BPAs) offer many advantages for robotic systems, including high durability and strength-to-weight ratios. However, their use in robotic systems is still extremely limited, in part due to their poor force, length, and pressure characterization. In this work, a test setup is created to compare force produced by Festo fluidic BPAs with leading models. Our analysis of the data has resulted in (1) the development of new equations to calculate force as functions of pressure and contraction for Festo BPAs with uninflated diameters of 10 mm and 20 mm, and (2) a novel equation …

Mining And Sustainable Development In Sierra Leone: The Role Of Institutional Quality, Ibrahim Massaquoi

Journal of Sustainable Mining

While mining can drive economic growth, create jobs, and promote infrastructural development, it also poses risks to the environment, human health, and social well-being. Therefore, to achieve sustainable development, responsible mining is crucial. This study empirically examines the role of institutional quality in the mining-sustainable development nexus in Sierra Leone. With the use of the planetary pressures-adjusted human development index (PHDI) as a comprehensive measure of sustainable development, the study is able to integrate economic, social, and environmental dimensions. The autoregressive distributed lag (ARDL) model confirms the existence of both short-run and long-run dynamics. The results of the study show …

A Hybrid Deep Learning Framework For Multi-Class Retinal Disease Classification, Ali M. Duhaim, Abbas M. Al-Bakry

AUIQ Technical Engineering Science

Ocular diseases such as diabetic retinopathy, glaucoma, and cataract remain major causes of vision loss worldwide, creating an increasing demand for accurate and reliable automated diagnostic systems. Although deep learning techniques have demonstrated strong performance in retinal image analysis, their clinical adoption is still limited by challenges related to predictive reliability, robustness, and interpretability. This study presents HEFR-Net (Hybrid EfficientNet-B3 and ResNet-50 Feature-Fusion Network), a hybrid deep learning framework designed for multi-class classification of retinal fundus images. The proposed architecture integrates EfficientNet-B3 and ResNet-50 through feature-level fusion, enabling the model to capture both fine-grained texture patterns and high-level structural characteristics …

Advances In Research On Eco-Geological Environment Monitoring Of Underground Coal Mining Areas Based On Airborne Remote Sensing, Li Jun, Zou Zhaohui, Zhang Chengye, Wang Yi, Cheng Yang, Xu Lianhang, Zhang Jinhe, Liu Chuanrui, Liang Lixia

Coal Geology & Exploration

Background Timely and effective monitoring of the current status of eco-geological environment holds great significance for scientific decision-making regarding both geological environment protection and ecological restoration in underground coal mining areas. Owing to its advantage of large-scale and rapid monitoring, airborne remote sensing technology has emerged as an important approach to the eco-geological environment monitoring of mining areas. Advances This study first clarifies relevant concepts of eco-geological environment monitoring, as well as the monitoring requirements and contents specific to underground coal mining areas. Accordingly, it presents a summary of the advances in research on airborne remote sensing technology for the …

Entropy-Constrained Closure For Steady, Quasi-One-Dimensional Flow Of Ideal Gases, Andrew A. Oliva

Michigan Tech Publications

An entropy-constrained closure is developed for steady quasi-one-dimensional flow of a calorically perfect ideal gas. Net irreversibility is represented by a prescribed entropy change between the inlet and outlet or, equivalently, by a stagnation pressure ratio together with the stagnation temperature ratio implied by the energy balance equation. The thermodynamic constraint, enforced through Gibbs relation together with conservation of mass and energy, yields an algebraic mapping from the inlet flow state, area ratio and prescribed stagnation property ratios to the outlet flow state. The momentum balance is retained only as an auxiliary post-processing relation and may be used to infer …

Key Techniques And Application Of The Zdy15000ldk High-Power Automatic Directional Drilling Rig, Li Quanxin, Zhang Gang, Fang Peng, Xing Wang, Yao Ke, Zhang Rui, Zhang Boyang, Zhao Xuefeng, Shi Yang, Sun Hanyu, Jia Qian

Coal Geology & Exploration

Objective For deep mining of coal mines, conventional directional drilling rigs face challenges including high labor intensity, limited control accuracy, a low intelligence level, and failure to meet the demand for efficient gas drainage. Meanwhile, high-power automatic drilling rigs encounter technical bottlenecks in automation, control accuracy, and process intelligence in this context. To address these issues, this study proposed an integrated and systematic solution—the ZDY15000LDK high-power automatic directional drilling rig. Methods Using a compact structural layout, a drill rod handling system was developed, consisting of a drill rod loading/unloading manipulator with four degrees of freedom and an automatic drill rod …

Injectable, In Situ Forming Peptide Nanofiber Reinforced Composite Hydrogels For Age-Related Macular Degeneration, Shambhavi Bagewadi Ms

Theses and Dissertations

Cell therapy for age-related macular degeneration (AMD) is limited by the absence of a functional substrate such as Bruch’s membrane (BM), which is critical for retinal pigment epithelial (RPE) cell survival and integration. Although preformed substrates have been explored, their implantation can disrupt the fragile retinal architecture, compromise ocular immune privilege and increase infection risk. To address these limitations, an injectable hydrogel capable of forming in situ was developed. The hydrogel consists of thiol-modified hyaluronic acid (HA-SH) and polyvinyl alcohol (PVA). Peptide nanofibers were incorporated to enhance structural reinforcement. Three self-assembling peptides - RADA-16, GAGA and GAGA-YIGSR were designed and …

Electrical Grid Architectures For Smart Cities From Digitalized Power Systems To Ai-Enabled Urban Energy Ecosystems, Ehab Bayoumi

Mechanical Engineering

Smart cities increasingly depend on electrical grid infrastructures capable of operating under high levels of digitalization, decentralization, and intelligence while maintaining reliability, security, and governance at the city scale. However, conventional power systems, historically designed for centralized generation and passive operation, are poorly aligned with the operational complexity, multi-actor coordination, and cross-sector integration characteristic of urban energy systems. This review develops an architecture-first perspective on smart-city electrical grids, tracing their evolution from digitalized power networks to decentralized and AI-enabled urban energy ecosystems. Rather than focusing on individual technologies, the study evaluates grid architectures using a multi-layer framework that integrates physical …

Bridging Images And Language In Radiology: A Comprehensive Prisma Systematic Review Of Transformer Vision-Language Models And Clinical Readiness, Mohammad T. Khasawneh Dr., Sadaf Tabatabaee

Systems Science and Industrial Engineering Student Scholarship

Transformer vision-language models (VLMs) promise end-to-end automation of radiology reporting and related multimodal tasks. However, evidence remains fragmented across datasets, architectures, evaluation practices, and levels of clinical validation, limiting fair comparison and safe translation into practice. Following PRISMA 2020/PRISMA-S, search engines including PubMed, IEEE Xplore, Web of Science, and Google Scholar were systematically searched for peer-reviewed, English-language studies published between 2019 and 2025 that used paired radiology images and free-text reports. Dual reviewers screened records and extracted data using a locked schema covering datasets, modalities, architectures, training objectives, evaluation metrics, and indicators of clinical readiness. Free-text model descriptions were normalized …

Stoker-Fired Laboratory Boiler As A Tool For Optimising The Solid Fuel Combustion Process, Przemysław Rompalski, Justyna Guzy-Proc, Mariusz Kieczek

Journal of Sustainable Mining

This paper presents the results of quality testing performed on a stoker-fired laboratory boiler to present the technical potential of the boiler as a tool for optimising the combustion process of prepared solid fuels (granulate, energy blend) in the context of current demands related to the decarbonisation policy. The comprehensive testing of such fuels at a laboratory scale makes it possible to gain deep insights into the quality parameters of the fuel, flue gas and combustion waste, as well as to determine the combustion process parameters before the fuel is introduced for combustion in broader power engineering and household boilers. …

How Fe(Ii)/2-Oxoglutarate Oxygenase Chooses Chlorination Over Hydroxylation: Electric Field-Driven Ligand Exchange Governs C-Cl Formation, Simahudeen Bathir Jaber Sathik Rifayee, Midhun George Thomas, Anandhu Krishnan, Kritika Gupta, Carter Davis, Tatyana Karabencheva-Christova, Christo Z. Christov

Michigan Tech Publications

Non-heme Fe(II)/2-oxoglutarate (2OG)-dependent halogenases catalyze highly selective C-H halogenation. BesD is a non-heme Fe(II)/2OG halogenase that performs regio- and stereoselective chlorination of the l-lysine (l-Lys) substrate. Understanding the mechanism by which halogenation is favored over canonical hydroxylation is essential for guiding enzyme engineering efforts aimed at converting hydroxylases into halogenases. Here, we combine molecular dynamics (MD) and hybrid quantum mechanics/molecular mechanics (QM/MM) calculations to elucidate the origin of chlorination selectivity in BesD and variants derived from a homologous hydroxylase. Our results indicate that, although the initial inline Cl-Fe(III)-OH intermediate is inherently predisposed toward hydroxylation, it undergoes a two-step isomerization in …

Field Monitoring And Geometric Representation Of A Uhpc-Repaired Bridge Structure, Robert Lawler

Honors Scholar Theses

Ultra-High Performance Concrete (UHPC) has shown promise in bridge rehabilitation broadly, but its application to steel gusset plate repair represents a novel use case with limited prior research. Therefore, when the Commodore Isaac Hull Bridge in Derby, Connecticut, was issued an emergency declaration due to gusset plate section loss, a UHPC repair was implemented. This project represented the first known field implementation of this type of UHPC gusset plate repair, marking a significant advancement in the rehabilitation of deteriorated steel bridge components. To support long-term performance assessment and ensure the success of the repair, field monitoring efforts were also incorporated …

Decision Making At Triage Classification Using Svm With Smote Technique, Mehanas Shahul, Pushpalatha Kp

Northeast Journal of Complex Systems (NEJCS)

The efficient functioning of triage gates in overcrowded emergency departments (EDs) occurs in the context of the complex adaptive system (CAS) framework, where diverse system elements – patients, medical personnel, resources, patients’ inflow patterns, and patients themselves – simultaneously and dynamically influence the decision process. This study addresses the automated incorporation of machine learning triage algorithms as part of the system triage process to support automated classified risk-level recognition based on a limited set of vital signs. Patients are dynamically subsumed under high and low-risk categories enhanced by sensitivity, which enables optimal diagnosis and triage response to the critical clinician …

Uncovering Discrete States From Multimodal Psychophysiological Data Using Gaussian Latent Dirichlet Allocation (Glda), Congyu Wu, Aaron Fisher, David Schnyer

Northeast Journal of Complex Systems (NEJCS)

In this article we explore and validate the utility of an unsupervised probabilistic model, Gaussian Latent Dirichlet Allocation (GLDA), for discovering discrete states from repeated, multimodal psychophysiological samples collected from multiple individuals. Psychology and medical research heavily involves measuring potentially related but individually inconclusive variables from a cohort of participants to derive diagnosis, necessitating clustering analysis for state identification. Traditional probabilistic clustering models such as Gaussian Mixture Model (GMM) assume a global mixture of component distributions, which may not be realistic for observations from different patients. The GLDA model borrows the individual-specific mixture structure from a popular topic model Latent …

The Reliability Of Yolo Object Detection On The Amd Versal In A Proton Radiation Environment, Jacob D. Brown

Theses and Dissertations

Object detection is an important operation for satellites to be able to perform, and in outer-space missions it is crucial that machine learning models perform inference on satellite images accurately and reliably. Where size, weight, power, and other constraints exist, meeting this goal for accurate and reliable object detection is challenging. Additionally, soft errors caused by radiation further disrupt and degrade the operation of object detection in satellites. This thesis studies the performance of a deep learning model on an embedded device, the AMD Versal, in the presence of soft errors. The well-known and high-performing YOLO convolutional neural network was …

Replication And Architectural Enhancement Of Omni Aggregation Networks, Matteo Calviello

Rose-Hulman Undergraduate Research Publications

Single Image Super-Resolution (SISR) reconstructs high-resolution images from low-resolution inputs, a capability valuable across many application domains. This thesis focuses on the replication and architectural enhancement of the Omni Aggregation Network (OAN), a lightweight super-resolution architecture designed to balance reconstruction quality with computational efficiency through a novel omni-axis self-attention mechanism.

Independent replication remains a persistent challenge in machine learning research, and this work addresses that issue directly. Initial replication attempts trailed the original reported results by approximately 6-10% in performance metrics before several undocumented implementation details were identified. After correcting these discrepancies, the replicated implementation achieved results within 4% of …

Accelerating Wound Healing Rates With Cucurbita Pepo Leaf Extract Loaded Electrospun Poly(Methyl Methacrylate)/Halloysite/Chitosan/ Caco₃ Composite Nanofibers Through In Vitro And In Vivo Assessments, Samar A. Salim

Nanotechnology Research Centre

Cucurbita pepo leaf extract (CPE) was incorporated into electrospun poly(methyl methacrylate)/ halloysite/chitosan/ CaCO₃ (PMMA/Hal/CS/CaCO₃) composite nanofibers to develop a novel biomaterial for accelerating wound healing rates. The different nanofibrous scaffolds were successfully fabricated and characterized through scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD). SEM analysis revealed uniform, smooth nanofibers, while FTIR and XRD confirmed the integration of CPE into nanofiber matrix, indicating an amorphous structure and effective dispersion of the extract. In vitro agar well-diffusion and antibiofilm assays revealed that the optimized formulation exhibited potent antimicrobial activity against wound-associated pathogens. The nanofibers composite based on …

Real-Time Fraud Detection, Haidi Aly Fahmy, Abdelhadi Nait-Zerrad, Shiva Krishana Reddy Ravuula, Sangwhan Cha

Harrisburg University Other Works

Financial fraud detection is a high-volume, high-velocity analytics problem. Traditional rule-based systems are often easy to deploy, but they are limited by static thresholds, delayed response, high false-positive rates, and weak explainability. This report presents a formalized end-to-end Big Data architecture for real-time fraud and anomaly detection in financial transaction streams.

The proposed architecture ingests transaction events through AWS Kinesis, enriches them through an Apache Flink stream-processing layer, scores them with an XGBoost classifier, explains model outputs using SHAP, and converts structured evidence into human-readable summaries through a controlled GPT explanation layer. Results are persisted through a hybrid storage strategy …

Sentience, Sheetal Agrawal

Masters Theses

The increasing urgency for sustainable and adaptive systems has driven research toward embedding intelligence directly into materials rather than relying solely on external sensing and control systems. This thesis explores how smart material1 embedded systems can be designed to recognize and respond to environmental signatures, defined as measurable patterns such as temperature fluctuations and mechanical forces. Central to this investigation is the integration of shape memory alloys, particularly Nitinol, with geometry-based actuation mechanisms that amplify material behavior into functional system responses.

The central argument is that designing with smart materials is a design problem, not primarily a materials science problem …

Power Consumption Prediction And Energy Forecasting Using Machine Learning Models, Sheik Mohideen Shah S Mr

Theses and Dissertations

Power consumption trends are essential to be identified in the energy grid areas to analyze the utilization, deficiency, and the measures to be taken for an effective and comfortable usage of energy. There are two scenarios in which the power consumption can be analyzed, namely identification and prediction. Identification deals with the post-utilization analysis of energy trends, whereas prediction deals with prior analysis of various factors of energy utilization, including the cost, supply details, shortages, and the need for new energy resources. In the existing models, the power consumption-related data are collected through smart meters, and the energy forecasting methods …