Digital Commons Network^™

Data Literacy Competencies In Context: Employee Perspectives From The Workplace, Patricia Condon, Wendy G. Pothier

Faculty Publications

Data literacy is essential in today’s workplace, and professionals across roles and experience levels recognize its value. This article reports on findings from interviews with 16 supply chain and logistics professionals. The study examines how seven proposed data literacy competencies align with workplace needs, how employees address the data literacy gap, and how librarians can support workforce readiness. Findings highlight opportunities for libraries to bridge the data literacy gap through instruction and resources development that integrate technical and non-technical data skills with information literacy.

Social And Commercial Crowdfunding Through The Lens Of The Theory Of Planned Behaviour And Financial Well-Being, Joanna Adamska, Urszula Mrzygłód

Journal of Banking and Financial Economics

A unique feature of crowdfunding is that it relies on numerous individuals contributing financially to the project, which sets it apart from traditional financing channels. Unlike banks, where funding decisions are subject to strict prudential criteria and the creditworthiness of the borrowing entity, crowdfunding projects appeal to various worldviews and values held by potential backers. Therefore, the financial decision to support the crowdfunding project becomes a unique problem in personal finance. This study aims to analyse the psychological and financial factors influencing crowdfunding participation, comparing social and commercial projects using the Theory of Planned Behaviour (hereinafter: TPB) and subjective financial …

Application Of Artificial Intelligence Techniques To Improve Leadership Decision Making With Uncertainty, Michael David Parrish

Doctoral Dissertations

"Every good leader is a good manager, but not every good manager is a good leader. The difference between the leader and the manager is critical decision-making. Today’s decision-making environment is characterized as Volatile, Uncertain, Complex, and Ambiguous (VUCA). With the exponential increase in the technical capabilities of systems, the human has become the weakest link in the use of such systems. To remain relevant, good leaders must continuously adapt to new advances in technology and processes.

The research contributions of this work provide several unique and novel solutions for leaders to utilize artificial intelligence tools to improve and optimize …

Raft-Based Polymer And Nanoparticle Materials For Traumatic Brain Injury Treatment And Diagnostics, Aaron Priester

Doctoral Dissertations

"Traumatic brain injury (TBI) is a leading cause of death and disability worldwide. Neurodegenerative diseases that develop post-TBI can be, in part, attributed to DNA and cell-damaging reactive oxygen species (ROS) and lipid peroxidation products (LPOx). This thesis focused on overcoming the limits of current TBI material treatment approaches by employing a RAFT (reversible-addition fragmentation chain transfer) polymer approach that incorporated novel therapeutic, diagnostic and peptide-targeting monomers. An improved nanoparticle synthesis approach was also developed. Thiol and thioether-containing monomers neutralize both ROS and LPOx while Gd-containing monomers with enhanced magnetic resonance imaging (MRI) contrast provide diagnostics and material tracking in …

Shock Wave And Vortex Ring Dynamics From Explosively Driven Shock Tunnels, Rachel Louise Bauer

Doctoral Dissertations

"Blast and shock tubes are frequently used to create shock waves to study their effects and impacts on structures, humans, and personal protective equipment. These tubes are also found in other industries including wind tunnels for aerodynamic testing, jet engines for propulsion research, spacecraft reentry simulations, and industrial applications such as material testing and high-velocity impact studies. Despite their widespread use, there is no standard design, with variations in geometry, size, and energy sources. Current research only evaluates the peak pressure of the shock wave produced and does not consider the effects of changing the size or geometry of the …

The Evolving Use Of Strategic Planning Tools In The Manufacturing Environment: Implications For Quality 4.0 And Beyond, Richard Lee Wilson

Doctoral Dissertations

"Having a strong strategic plan is critical for success for any business no matter the size of the organization, the product or service they provide, or the industry they serve. There are many methods businesses use to develop their strategic plans. One such method is known as Hoshin Kanri, which has been in use for decades. However, recent years have seen an increase in artificial intelligence, big data, data analytics, and other technology tools to create cyber physical systems on the manufacturing floor. The increase in technology in manufacturing to integrate cyber systems with physical systems spawned a new industrial …

Leveraging Deep Learning Models And Social Media Data For Enhanced Situation Awareness In Disaster Management, Ademola Abdulganiyu Adesokan

Doctoral Dissertations

"In recent years, social media has become a crucial source of real-time data for disaster management, supporting emergency responses when traditional channels like 911 are overcrowded and overwhelmed. It offers authorities valuable data for developing effective strategies, especially when swift actions are essential to save lives. However, the informal language, ambiguous meanings, and irrelevant content on social media pose challenges to accurate classification and hinder the efficient extraction of disaster-relevant information, leading to inefficiencies in emergency response efforts.

This research focuses on seven key questions: i) How can we detect, classify, and analyze hate and offensive tweet emotions during large-scale …

Vibration Modeling Of Rectangular Plates And Application To Solar Cell Dust Mitigation, Jeremiah John Rittenhouse

Doctoral Dissertations

"Many engineering structures can be modeled as rectangular plates, including solar cells. Carefully controlled plate vibration can be useful to solve an engineering problem, such as lunar dust accumulation on solar cells, which blocks light and reduces power generation. For this application, plate vibration at resonance is studied and used experimentally to eject lunar dust from a solar cell.

Piezoelectric actuator placement on the inactive side of a solar cell to induce vibration dust mitigation from the active side of the cell is presented in this work. Three solar cell prototypes were created and tested for efficacy, resulting in an …

Characterization And Modeling Of Properties Of Unsaturated And Partially Damaged Cement-Based Materials, Rezwana Binte Hafiz

Doctoral Dissertations

"Transport properties, governing the resistance of cement-based materials to harmful substances are essential considerations for long-term performance. This study addressed the often-overlooked dimension of transport properties in unsaturated cement-based materials, crucial as most concrete structures face variable environmental conditions, leading to partial saturation. A two-scale model was introduced, enhancing our comprehension of transport properties in conditions reflecting real-world scenarios. Empirical correlation representing bulk paste characteristics was established, facilitating the upscaling of properties to mortar and concrete. The model was extended to predict the transport properties of mortar as well.

Environmental factors can contribute to the degradation of cement-based materials, with …

Photoionization Of Spin-Polarized Rydberg Atoms Out Of A Continuous Wave Optical Dipole Trap, Kevin Lee Romans

Doctoral Dissertations

"Recent research has demonstrated the need for a fully differential experiment on the photoionization of ⁶Li Rydberg atoms in a continuous wave (cw) laser field, as this would provide a new path forward for studying never before accessible atom-light interactions. Rydberg atoms are back in the focus of intense research due to their peculiar properties, which make them interesting candidates for quantum optics and information applications. In this work, we study the ionization of such Rydberg atoms, due to their interaction with a trapping laser field, by utilizing a reaction microscope (ReMi) capable of measuring photoelectron momentum distributions with …

Parallel Algorithms For Large Scale Dynamic Graph Analysis, Arindam Khanda

Doctoral Dissertations

A complex system of interacting entities in contemporary scenarios, be it biological, technological, or social, can be represented using graphs. Dynamic graphs, unlike their static counterparts, are ones in which the underlying topology changes over time. These networks act as a model for numerous systems, from transportation to social interactions, capturing the ever-evolving nature of real-world phenomena. However, the inherent temporality of these networks presents a unique set of challenges and the traditional static graph algorithms often fall short in efficiency and applicability. In our research, we delve into the complexities presented by large dynamic networks and suggest various methodologies …

Multi-Level Explainability In Radiomic-Based Classification Of Multiple Sclerosis And Ischemic Lesions, Nighat Bibi, Kathleen M. Curran, Ronan P. Killeen, Jane Courtney

Research Outputs: 2025-Present

Differentiating multiple sclerosis (MS) from ischemic stroke lesions on MRI remains a clinical challenge due to their similar appearances as white matter hyperintensities. We propose a radiomics-based machine learning framework that integrates multi-level explainable AI (XAI) techniques to support transparent and clinically meaningful lesion classification. Radiomic features are extracted from standardized MRI scans and used to train multiple classifiers, with Random Forest achieving the best performance (accuracy: 91.24%, F1: 86.54%). The framework incorporates four complementary explanation layers: global insights using SHAP, local interpretability via LIME, counterfactual reasoning with DiCE, and clinical narrative generation using GPT-based language models. This layered approach …

Teacher Delivered Block Construction Training Improves Children's Mathematics Performance, Emily K. Farran, Katie A. Gilligan-Lee, Denis Mareschal, Marija Živković, Santa Bartušēvica, Derek Bell, Tim Jay, Camilla Gilmore

Research Outputs: 2025-Present

There is robust evidence for a causal association between spatial thinking and mathematics achievement. However, most research has been lab-based, with spatial training delivered by researchers. We present a teacher delivered, whole-class 6-week spatial training study that involved professional development for practitioners coupled with teacher-led LEGO® block construction training for 6- to 7-year-olds. Using a quasi-experimental design, N = 409 children completed the training and N = 103 children formed a business-as-usual control group. For spatial ability and mathematics, but not spatial language, children in the training condition showed improved performance relative to controls. This finding extends evidence of the …

Case Report: Molecular Characterization Of Adult Atypical Teratoid Rhabdoid Tumor And Review Of The Literature, Miguel A Hernandez-Rovira, Michelle Connor, Robert C Osorio, Emilie Russler-Germain, Robert Schmidt, Gabrielle W Johnson, Julie Silverstein, Sonika Dahiya, Nyssa Fox Farrell, Mia C Weiss, Gregory J Zipfel, Jiayi Huang, Dimitrios Mathios

2020-Current year OA Pubs

BACKGROUND AND IMPORTANCE: Atypical teratoid rhabdoid tumors (ATRTs) are typically aggressive pediatric tumors with a median survival of 11 months. Due to the paucity of cases in adults, the clinical behavior of these pathologies is not well understood. Here we present the case of a 41-year-old female patient with postoperative hyperprogression of a sellar ATRT and provide a detailed description of the molecular composition of this tumor, the protocol used to treat this patient, and the ultimate outcome of this patient.

CLINICAL PRESENTATION: The patient is a 41-year-old woman who presented with headaches and double vision. MRI revealed a sellar/suprasellar …

Sensorimotor Faculties Bias Choice Behavior, Jan Kubanek, Lawrence H Snyder, Richard A Abrams

2020-Current year OA Pubs

Decision-making is a deliberate process that seemingly evolves under our own volition. Yet, research on embodied cognition has demonstrated that higher-order cognitive processes may be influenced, in unexpected ways, by properties of motor and sensory systems. Here we tested whether and how decisions are influenced by handedness and by asymmetries in the auditory system. Right- and left- handed participants performed an auditory decision task. In the task, subjects decided whether they heard more click sounds in the right ear or in the left ear, and pressed a key with either their right or left index finger, according to an instructed …

Sift Feature-Based Relative Altitude Estimation Enhanced With Siamese Network, Shirin Nasr-Esfahani, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In GPS-denied environments or when GPS signals are unreliable or unavailable, alternative methods of accurate localization with coordinate generation become critical. To address localization, the scale-invariant feature transform (SIFT) algorithm, along with its numerous adaptations, is extensively utilized in computer vision and remote sensing for matching image features to identify objects and perform localization. This article presents a novel approach for estimating the relative altitude of unmanned aerial vehicles (UAVs) using SIFT features' scale (size), omitting the need for additional data like camera intrinsic parameters, as well as extensive image datasets are also required for training. Furthermore, the approach enhances …

Enhanced Multidimensional Harmonic Retrieval In Mimo Wireless Channel Sounding, Yanming Zhang, Wenchao Xu, A. Long Jin, Tianquan Tang, Min Li, Peifeng Ma, Lijun Jiang, Steven Gao

Electrical and Computer Engineering Faculty Research & Creative Works

This paper introduces a recursive parallel dynamic mode decomposition (RPDMD) scheme tailored for multidimensional harmonic retrieval (MHR), specifically applied to MIMO wireless channel sounding. The RPDMD algorithm is devised to address the complexities inherent in multidimensional scenarios, leveraging the dynamic mode decomposition (DMD) framework within a recursive parallel structure. Initially, the observed tensorial multidimensional harmonic data is transformed into a two-dimensional matrix format along the r-th dimension. Subsequently, DMD dissects this matrix data into eigenvalues and their associated modes. The real and imaginary components of the DMD eigenvalues yield damping factors and frequencies in the r-th dimension, respectively. Furthermore, recursive …

Précis Of The Edge Of Sentience: Risk And Precaution In Humans, Other Animals, And Ai, Jonathan Birch

Animal Sentience

We often face grave practical decisions that seem to hinge on whether a system is sentient. This family of cases includes invertebrate animals, people who are unresponsive after brain injury, fetuses, neural organoids, and now AI technologies. We must decide what to do despite ongoing disagreement about the nature of sentience. In our state of uncertainty, we should pragmatically transform the question from “Is it sentient?” to “Is it a sentience candidate, an investigation priority, or neither?”. When a system is a sentience candidate, it is negligent to fail to consider precautions. We should instead evaluate precautions for their proportionality …

Consciousness Of Octopuses—On Their Own Terms, Jennifer Mather

Animal Sentience

Because cephalopods are so different from the vertebrate lineage, their possible consciousness must be assessed on the basis of their heritage and abilities. Cephalopods have evolved in water, a denser medium than air, and their perception is adapted to it. They have inherited the molluscan mantle cavity and hydrostatic muscle type, which has led to a more distributed motor control system despite a centralized brain, and have evolved a completely novel skin display system. Using these abilities, octopuses can form concepts, plan for the future, generate a cognitive map, and self-monitor for apparent pain and manipulate communication. Most cephalopods use …

Design Of Fast Start-Up High-Q Oscillator For Wireless Sensor Nodes Transceiver Frequency Reference, Abdolraouf Rahmani

Student Works (2020-2029)

With the prevalence of wireless sensor networks and the Internet of Things (IoT), optimizing power in battery-powered wireless nodes is crucial due to the inconvenience and cost of replacing batteries in remote areas. Synchronized power modulation between "Sleep" and "Active" states, known as burst mode activation, allows nodes to conserve power. However, frequent transitions between these states consume significant energy, highlighting the need to reduce the start-up time of the slowest component, the high-Q crystal oscillator. Additionally, to ensure improved synchronization within the network and a cost-effective IoT device manufacturing, the device should be produced with low start-up time variations …

Transfection Of Ionizable Lipid Nanoparticles On Raw 264.7 And Mda-Mb-231, Lavanya Bhargava

Masters Theses

"This thesis investigates the preparation, characterization, and transfection efficiency of various ionizable lipid nanoparticles (LNPs) formulated for the delivery of mRNA encoding enhanced green fluorescent protein (EGFP) in RAW 264.7 macrophages and MDA-MB-231 breast cancer cell lines. The ionizable cationic lipid studied are ALC-035, C12-200, C14-4, PPZ-A10, DLin-MC3-DMA. The study addresses the need for effective gene delivery systems to provide a safe and versatile platform that protects and transports nucleic acids into target cells. LNPs were synthesized using microfluidic mixing methods, incorporating lipid components such as the cationic lipids, DSPE, DOPE, cholesterol and PEG lipids to achieve controlled particle sizes, …

Lidar From The Skies: A Uav-Based Approach For Efficient Object Detection And Tracking, Baya Cherif

Masters Theses

"Recently, there has been a growing interest in deploying the Light Detection and Ranging (LiDAR) technology to gain traction in the autonomous vehicle industry, its applications are expanding into areas like smart cities, agriculture, and renewable energy. This work proposes an advanced approach to enhance aerial traffic monitoring using Li- DAR. We aim to provide accurate, real-time object detection and tracking from an aerial perspective by integrating Unmanned Aerial Vehicle (UAV) with LiDAR, culminating in a smart UAV-integrated LiDAR (A-LiD) sensor for traffic surveillance. We introduce an adapted version of one of the newest methods of the cutting-edge 3D object …

Automated Generation Of Malware Metadata Signatures, Joel Schott

Masters Theses

In advanced, targeted malware attacks, the custom software tools used to package and send malicious files and messages can lead to distinctive metadata values that facilitate creation of a malware metadata signature. Manual creation of these signatures requires expert domain knowledge and is time-consuming and error-prone. Our goal is to automate this process. We created several methods of automatically generating malware metadata signatures for ZIP files and emails. We evaluated these methods by comparing signatures generated with these methods to existing expert-created signatures. We found automated methods for ZIP files and emails that are capable of generating metadata signatures that …

Fetal Acidosis Prediction Using Attention Enhanced Convolutional Neural Networks, Anusha Adhikari

Masters Theses

This study explores the integration of spectral mixtures of fetal heart rate (FHR) and uterine contraction (UC) signals to enhance the prediction of fetal acidosis, utilizing the CTU-CHB dataset. Several classification models were trained using two distinct oversampling techniques and inputs, demonstrating that models incorporating spectral mixtures significantly outperform those using raw signals. These models, particularly when combined with convolutional neural networks (CNNs) and attention mechanisms, achieved a notable F1-score of 0.98, with the highest model achieving an area under the Receiver Operating Characteristic (ROC) curve of 0.95. The research employs a variety of techniques including short-time Fourier transform and …

Long Short-Term Memory (Lstm) -Based Neural Network Model For Optimizing Composite Manufacturing Process Using Autoclave, Sourav P. Bolar

Masters Theses

The combination of high pressure and controlled heat plays a critical role in ensuring the uniform curing of composite materials, leading to parts with superior mechanical properties. In this study, three composite samples of IM7/CYCOM 5320-1, each cut into 12x12-inch squares, were placed in an autoclave at three different locations, spaced 6 inches apart. Sixteen thermocouples were randomly distributed across the setup to monitor the curing process as the autoclave temperature was systematically ramped up and down while maintaining constant pressure, creating a fully controlled curing environment. The primary objective was to optimize the curing locations to reduce machine runtime …

Influence Of Alloy Composition On The Process Robustness Of Steels Consolidated Via Laser-Directed Energy Deposition, Jonathan Kelley

Masters Theses

"To ensure consistent quality of additively manufactured parts, it is advantageous to identify alloys which can meet performance criteria while being robust to process variations. Toward this end, this work investigated the effect of alloy composition on the robustness of steels consolidated via laser-directed energy deposition (L-DED). Ultra-high-strength low-alloy steel (UHSLA) and pure iron powders were mixed in-situ to produce 10 compositions containing 10-100% UHSLA by mass. JMatPro material simulations roughly predicted phases and mechanical properties. Two sets of experiments were used to evaluate the sensitivity of as-built hardness (all 10 compositions) and tensile properties (5 select compositions) to process …

Development Of A Method To Measure Blast Overpressure Exposure Using Orthogonal Sensor Orientations, Nicholas Kuehl

Masters Theses

Measuring and recording blast exposure to military personnel from shoulder-fired weaponry or improvised explosive devices to correlate health outcomes like mild traumatic brain injury has been a goal for many years. As such, many wearable sensors have been developed and tested for accuracy and reliability. Despite this, knowing the sensor orientation in relation to the blast source is important to fully correlate the actual personnel exposure to clinical outcomes. This research investigates whether pressures recorded at three independent orientations in the x, y and z planes can be combined to a representative pressure that is independent of orientation. Important metrics …

Critical Behavior Ofthedilutedquasi-Onedimensionalquantum Ising Model, Logan Bradley Sowadski

Masters Theses

We explore the phase transition in the diluted quasi-one-dimensional quantum Ising model. We begin by giving an introduction to the Ising model followed by derivations of the properties and observables. A brief overview of Monte-Carlo simulations is also given focusing on two algorithms that make simulations for physically realizable systems possible, the Metropolis and Wolff algorithms. We finally discuss the concept of random disorder in the system and the effects this can have on the bulk of the system.

These concepts are then directly applied to a quasi-one-dimensional Ising model. Motivated by recent experiments on the spin-chain material cobalt niobate, …

Constraint Programming For Optimized Degree Paths, Mitchell Lee Skaggs

Masters Theses

This work presents a degree planning tool developed as part of the Pervasive Cyberinfrastructure for Personalized eLearning and Instructional Support (PERCEPOLIS) project which generates complete, valid, and personalized degree paths at any point from admission to graduation. This eliminates tedious calculation and double-checking, allowing advisors to focus on a student’s long-term plans and students to proactively explore potential degree paths. The original research contribution of this work is the use of a unified model for academic requirements to automatically translate complex, real-world curricula into a constraint programming model that can be quickly optimized based on personalized student criteria.

Automatically translating …

Frequency-Tracker And Power Supply For Piezoelectric Lunar Dust Removal Actuator, Praneeth Uddarraju

Masters Theses

"This work presents a reconfigurable phase-locked loop (PLL)-based control system for the resonant excitation of piezoelectric actuators aimed at automated removal of particulate contaminants from photovoltaic (PV) surfaces—particularly in extraterrestrial environments such as the lunar surface. Regolith or lunar dust buildup on solar panels is a serious hazard to the effectiveness of energy harvesting on extended missions. By using high-frequency structural excitation and inertial forces the suggested system removes surface impurities. Tunable Sallen-Key low-pass filters for reliable feedback conditioning are used in conjunction with a digitally implemented PLL on an FPGA (XLR8 platform) to precisely lock the drive frequency to …