Digital Commons Network^™

Love Affair With Thin Air: Mortality, Mastery, And The Consumerism Of Mountaineering, Kenneth Bates, Justine Rapp Farrell, Steven W. Kopp, Christopher Newman

Marketing Faculty Publications and Presentations

Mountaineering is arguably one of the most dangerous recreational challenges an individual may ever choose to undertake, yet millions of people annually venture above 8000 feet to challenge themselves in pursuit of personal goals, ideals, and support of individual values. But, why are consumers motivated to participate in such demanding and hazardous pursuits? This paper evaluates the psychological complexities surrounding adventure tourism as an act of consumerism, uncovering the pursuit of values, ideals, and identity transformation that is guided by one's own mortality salience. The present study seeks to examine consumer satisfaction beyond the simple pleasures of adventure and adrenaline …

An Examination Of Brand Avoidance Among Consumers Of Membership Business Models, Cara Peters, Bradley W. Brooks

Journal of Applied Marketing Theory

The purpose of this study is to examine how the increasingly prevalent business membership model is linked to potential brand avoidance. Based on a qualitative examination of consumer complaints from two organizations that utilize membership business models, this research demonstrates how consumer complaints are highly consistent with established brand avoidance antecedents. The findings offer a cautionary warning to business decision-makers who manage membership business models with consumers as well as to those who are considering implementing such an approach. The implications for these decision-makers are discussed.

The Role Of Apparel In College Student Athletic Affiliation, Robin Hardin, Michelle L. Childs

Journal of Applied Marketing Theory

Athletics is often considered the virtual front porch of a university, as it is often the most recognizable aspect of a college or university. This study examines how college students use apparel to affiliate with their university’s athletic brand. Results revealed three key factors influencing athletic-related merchandise preference: fashionable appeal, uniqueness, and official merchandise. Further analysis found that merchandise featuring official logos, colors, and recognizable branding elements significantly enhances consumers’ ability to associate with the university’s athletics brand. Gender differences emerged in preferences for fashionable items, with men showing greater interest. These findings provide valuable insights for marketers and university …

Armando’S Case: Diagnostic Emergent Literacy Assessment For Children With Complex Communication Needs, Bronwyn A. Harris, Tonya R. Moore, Ashley E. Pennell

Journal of Case Learning & Exceptional Learners

This practice-based case study is designed to offer a tutorial on how to adapt an informal, diagnostic emergent literacy assessment to meet the needs of students like six-year-old Armando, a Latino, multilingual learner with autism spectrum disorder (ASD) and complex communication needs (CCN) in an inclusive kindergarten classroom. Armando’s informal literacy assessment adaptations and outcomes are discussed, including descriptions of his emergent literacy skills observed through his engagement in literacy stations, small group reading instruction in his classroom, and his use of alternative and augmentative communication (AAC) in both instructional and assessment settings. This case study illustrates how traditional literacy …

Tracing The Journey Of Dissolved Organic Matter: From Leaf Litter Photodegradation To Microbial Processing In Tropical Streams, Samantha Nicole Sullivan

Chemistry & Biochemistry Theses & Dissertations

Dissolved organic matter (DOM) is a major reservoir of organic carbon in aquatic ecosystems and plays a central role in global carbon cycling through its transformation and remineralization to carbon dioxide (CO₂). As DOM moves from terrestrial environments into streams and rivers, its chemical composition is altered by a combination of microbial and photochemical oxidation processes that regulate both its reactivity and its persistence during transport. However, the molecular mechanisms governing these oxidative transitions, particularly in tropical ecosystems characterized by strong hydrologic seasonality and substantial inputs of plant-derived material, remain insufficiently resolved. This dissertation integrates ultrahigh-resolution mass spectrometry, optical characterization, …

Toward Personalizing Quantum Computing Education: An Evolutionary Llm-Powered Approach, Iizalaarab Elhaimeur

Computer Science Theses & Dissertations

Quantum computing education faces significant challenges due to its complexity and the limitations of current tools. This thesis introduces a novel Intelligent Teaching Assistant for quantum computing education and details its evolutionary design process. The system combines a knowledge-graph-augmented architecture with two specialized LLM agents: a Teaching Agent for dynamic interaction and a Lesson Planning Agent for lesson generation. The system is designed to adapt to individual student needs, with interactions meticulously tracked and stored in a knowledge graph. This graph represents student actions, learning resources, and their relationships, aiming to enable reasoning about effective learning pathways. We describe the …

Research To Practice Gap: Impact Of Principal Perceptions & Communication On Change Initiatives, Jennifer Sagendorf

Educational Leadership & Workforce Development Theses & Dissertations

The purpose of this study is to examine the experiences, perceptions, and practices of school principals related to evidence-based change initiatives and the continued divide between the findings of educational researchers and the use of these findings by school practitioners. Since the prevalent dichotomy of theory and practice is detrimental to school improvement efforts, it is important to examine the underlying values and beliefs that contribute to perpetuating this divide. For this qualitative phenomenological study, semi-structured interviews with seven elementary school principals provided first-hand accounts of the principals' lived experiences. Through an iterative process of coding, clustering, and cross-case analysis, …

Human Identification And Action Recognition Using Small Data And Deep Domain Adaptation, Alexander M. Glandon

Electrical & Computer Engineering Theses & Dissertations

Human identification and human action recognition problems are two important research areas for real-world security and surveillance applications. In both human identification and action recognition, it is necessary to operate by collecting small datasets in the field, possibly in a short time window of observation. This dissertation studies and develops computational modeling and high-performance machine learning (ML) and deep learning (DL) models for human identification and human action recognition using small amounts of data. These methods and computational models may be useful for different security and surveillance applications.

This dissertation on human recognition develops a ML computational model to estimate …

Aluminum As A Tracer Of Dust Deposition To The Ocean: A Case Study From The Bermuda Region, Tara Elizabeth Williams

OES Theses and Dissertations

Aluminum (Al), a major component of mineral aerosol (dust), partially dissolves in seawater and is widely used as a tracer for estimating time‐averaged dust fluxes to the ocean. Such estimates rely on dissolved Al (DAl) inventories in the surface mixed layer (SML), an assumed SML residence time of DAl (_TDAl), the fractional solubility of Al in dust (Al_S), and the mass fraction of Al in dust. In this study, dust flux estimated from seasonal, water-column DAl data from the Bermuda Atlantic Time-series Study (BATS) region are compared with direct dust flux estimated from contemporaneous measurements of …

Investigation Of Laser Based Flow Diagnostics With Metastable Argon, Sterling S. Gordon

Physics Theses & Dissertations

The overarching motivation of this work is the development of seedless, non-intrusive, laser-based diagnostics for supersonic airflow in wind tunnels. To advance this goal, this dissertation fo-cuses on three-photon excitation in a research-grade argon beam within a tabletop vacuum system, which offers a controlled environment for testing and refining the approach. The chosen excitation scheme drives argon atoms to the 3d[5/2]₃ state using a pulsed Ti:Sapphire laser system, enabling time-of-flight (ToF) measurements on atoms that subsequently undergo a multi-step decay to the metastable 4s[3/2]₂ state. Although full realization of this excitation scheme was hindered by technical …

Margalefidinium Polykrikoides Group Iii Va, Usa Strain Growth And Sac-Like Pellicle Cyst Dynamics, Eduardo Pérez Vega

OES Theses and Dissertations

Margalefidinium polykrikoides is a harmful cosmopolitan dinoflagellate that blooms in coastal waters. The effect of temperature and salinity on the growth of M. polykrikoides VA strain was examined using microscopy and growth models. M. polykrikoides Group III VA strain grew better at warmer temperatures and lower salinities than M. polykrikoides Group III NY strain, Group I Korea strain, and Japan strain (unknown group). Modelers need to use the temperature and salinity growth responses from M. polykrikoides Group III VA strain to better simulate and predict M. polykrikoides blooms in the Chesapeake Bay.

Dinoflagellates produce cysts as a strategy to withstand …

On The Scalability Of Anisotropic Mesh Adaptation On Distributed And Shared Memory Architectures For Numerical Approximations, Kevin Mark Garner Jr.

Computer Science Theses & Dissertations

Mesh generation is a critical component in numerical approximations of Partial Differential Equations (PDEs). One such example includes Computational Fluid Dynamics (CFD), as CFD simulations in turn are crucial for applications in many industries, such as personalized healthcare and the design of aerospace vehicles. Generating high quality meshes for large-scale CFD problems presents a significant bottleneck in the CFD workflow. This dissertation proposes “fast,” parallel 3D mesh generation methodologies that are designed to leverage the concurrency offered by emerging High-Performance Computing (HPC) architectures. First, a distributed memory method is presented that integrates a sequential state-of-the-art isotropic, advancing front local reconnection-based …

Machine Learning-Based Detection Of Covert Data Exfiltration Via Electromagnetic Side-Channel Emissions From Computer Memory In Air-Gapped Systems, Oladapo Akintoye Ajike

All Theses

Air-gapped computer systems are physically isolated from unsecured networks. Though isolated, they remain vulnerable to covert data exfiltration via electromagnetic side channels and other covert-channel attacks. This research presents a comprehensive approach to detecting electromagnetic data exfiltration by establishing a controlled laboratory environment using low-cost, readily available hardware components. The study shows a proof-of-concept covert data transmission system that exploits electromagnetic emissions from computer memory access patterns through software-controlled Random Access Memory (RAM) operations.

The research methodology involved developing a C++ transmitter program that modulates CPU and memory-intensive operations to generate detectable electromagnetic signals at 100 MHz frequency, and implementing …

Energy-Efficient Task Offloading Frameworks For Mixed Reality And Extended Reality In Edge Ai Environments, Mahin Khan Mahadi

All Theses

Mixed Reality (MR) and Extended Reality (XR) technologies are increasingly integrated into real-time applications such as remote maintenance, spatial navigation, and immersive learning. However, the computational intensity of deep learning workloads, especially object detection models like YOLO, poses significant challenges for wearable XR devices with limited processing power and battery life. To address these challenges, this thesis presents a comprehensive study of adaptive offloading strategies that optimize task execution between XR devices and edge servers.

We first proposed the Binary Spatial Allocation Framework (BSAF), which introduced a real-time binary decision mechanism for XR systems. The BSAF framework evaluates scene complexity, …

Mechanical Property And Thermal Stability Characterization Of Additively Manufactured Chicken Feather Fiber/Polybutylene Succinate (Pbs) Green Composites And In-Situ Pore Detection From Fdm 3d Printing Videos, Md Shariful Islam

All Theses

The poultry industry generates millions of tons of chicken feathers annually, most of which are underutilized and discarded as waste materials. Chicken feather fiber (CFF), primarily composed of keratin, possesses low density, biodegradability, and favorable mechanical properties, making it a promising reinforcement for sustainable composite materials. This research primarily focused on developing sustainable bio-composites using poultry waste, chicken feather fiber, and biodegradable polymers, specifically Polybutylene Succinate (PBS), for additive manufacturing applications. Composite filaments of varying fiber loadings (0.5, 1, and 2 wt%) were produced through filament extrusion and processed into test specimens using fused deposition modeling (FDM).

Mechanical properties were …

Comparative Evaluation Of Power And Timing Simulation-Based Side Channels For Hardware Trojan Detection, India Shazuliyah Jade Elkhazin

All Theses

Hardware Trojans are covert modifications to integrated circuits that alter function or leak information while avoiding traditional verification. This thesis presented a simulation-based side-channel study of the AES-T1800 benchmark, utilizing power and timing analyses. The methodology aligned value change dump signals with waveform windows to correlate internal switching with external power signatures and compared timing slack distributions between a Trojan Free build and a Trojan Intruded build after implementation in the design tool.

Power analysis revealed a clear and repeatable fingerprint during Trojan activation. In filtered traces, the Trojan Free run rose from about 0.8×10⁻⁷ W to a steady level …

Design And Analysis Of Low-Cost Lora Mesh Network For Reliable And Secured Precision Agriculture, Yamini Swetha Nadella

All Theses

Rural precision agriculture requires reliable, low-cost, and energy-efficient communication systems that can cover large farmland areas. Traditional wireless technologies, such as Wi-Fi, cellular, and satellite communication, are either expensive, consume too much power or are even unreliable in maintaining connectivity in large farmlands, which is a common case in rural precision agriculture. LoRa-based networks support long-range communication with extremely low power consumption, making them an appropriate solution for precision agriculture applications in rural farmland areas. Current LoRaWAN systems employ star topology, which also limits their ability to offer efficient, multi-hop connectivity in rural environments.

This thesis presents the design, implementation, …

Integrating Gis And Machine Learning To Uncover Spatial, Temporal, And Contributing Factors To Bicycle Crashes, Precious Kamsiyo Ejikeme

All Theses

The recent drive for a cleaner environment has led to an increase in greener modes of transportation, including the use of bicycles. These emerging trends have led to an increase in bicycle-related crashes. According to the CDC, an estimated 1,150 cyclists were killed in 2023, with 120,000 sustaining non-fatal injuries. Transportation planners and agencies are under pressure to make cycling safer by providing dedicated bike lanes and improving existing infrastructure. To accomplish this, it is very important to understand which factors contribute to bicycle crash severity across different roadways.

Despite recent advancements in modeling bicycle crash severity, most studies rely …

Integrating Gis And Machine Learning To Uncover Spatial, Temporal, And Contributing Factors To Bicycle Crashes, Precious Kamsiyo Ejikeme

All Theses

The recent drive for a cleaner environment has led to an increase in greener modes of transportation, including the use of bicycles. These emerging trends have led to an increase in bicycle-related crashes. According to the CDC, an estimated 1,150 cyclists were killed in 2023, with 120,000 sustaining non-fatal injuries. Transportation planners and agencies are under pressure to make cycling safer by providing dedicated bike lanes and improving existing infrastructure. To accomplish this, it is very important to understand which factors contribute to bicycle crash severity across different roadways.

Despite recent advancements in modeling bicycle crash severity, most studies rely …

The Future Is Now: Empowering Society Through Ai Literacy, Jason S. Wrench, Sanae Elmoudden

Milne Open Textbooks

Artificial Intelligence (AI) is no longer a futuristic concept—it is the reality of the present. From the algorithms shaping our social media feeds to the generative tools transforming our workplaces, AI has permeated every aspect of modern life. The Future is Now moves beyond the hype to provide a comprehensive roadmap for understanding, navigating, and shaping this technological revolution.

Demystifying the Machine

This textbook serves as a user-friendly guide to the “black box” of AI. It breaks down complex technical concepts—from machine learning and neural networks to large language models—making them accessible to students across all disciplines. By establishing a …

Interpersonal Communication: A Mindful Approach To Relationships 2nd Edition, Jason S. Wrench, Narissra M. Punyanunt-Carter, Katherine S, Thweatt

Milne Open Textbooks

Interpersonal communication is the way we connect with others. Whether engaging with a spouse, a coworker, a close friend, or a stranger, our daily lives are defined by the messages we send and receive. Interpersonal Communication guides students through the complex landscape of human interaction, helping them navigate relationships in the twenty-first century.

A Mindful Perspective

What distinguishes this textbook is its integration of mindfulness into the study of communication. Moving beyond simple skills training, the text encourages students to engage in mindful awareness and mindful practice. By learning to be fully present, open, and non-judgmental, students develop the …

Investigating The Cardiovascular And Autonomic Responses To Energy Drink Consumption: The Role Of Energy And Calorie Content, Sophia Schmidt

Honors Theses

Energy drinks (EDs) are among the most consumed functional beverages, often marketed to enhance focus, alertness, and physical performance. Despite their popularity, the combined cardiovascular and autonomic effects of caffeine and sugar during exercise remain poorly understood. The purpose of this study was to examine the acute cardiovascular, metabolic, and autonomic responses to sugar-sweetened (ED-S), non-nutritive sweetened (ED-NNS), and placebo beverages during submaximal cycling in healthy young males.

Nine male participants (age 22.2 ± 2.4 yrs; BMI 26.2 ± 2.9 kg/m²) completed three experimental visits in a randomized, repeated-measures design. Each visit involved ingestion of one drink (ED-S, ED-NNS, or …

Estimation Of 3d Facial Dynamics With Nonlinear Filters For Position Tracking, Thoa Thieu, Roderick Melnik

School of Mathematical & Statistical Sciences Faculty Publications

This study presents a comparative evaluation of three nonlinear state estimation filters, the Extended Kalman Filter (EKF), Unscented Kalman Filter (UKF), and Particle Filter (PF), for the task of 3D facial landmark tracking. Using a publicly available dataset, we assess each filter's performance under both deterministic (noise-free) and stochastic (noisy) conditions. Metrics such as mean squared error (MSE), convergence rates of state and covariance estimates, and consistency over time are used to quantify tracking performance. Results show that the EKF consistently outperforms the UKF and PF, achieving faster convergence and lower estimation error, particularly in scenarios characterized by mild nonlinearity. …

Variants Of Conway Checkers And K-Nacci Jumping, Glenn Bruda, Joseph Cooper, Kareem Jaber, Raul Marquez, Steven J. Miller

School of Mathematical & Statistical Sciences Faculty Publications

Conway Checkers is a game played with a checker placed in each square of the lower half of an infinite checkerboard. Pieces move by jumping over an adjacent checker, removing the checker jumped over. Conway showed that it is not possible to reach row 5 in finitely many moves by weighting each cell in the board by powers of the golden ratio such that no move increases the total weight.

Other authors have considered the game played on many different boards, including generalizing the standard game to higher dimensions. We work on a board of arbitrary dimension, where we allow …

Precision-Weighted Federated Learning, Jonatan Reyes, Lisa Di Jorio, Cecile Low-Kam, Marta Kersten-Oertel

Computer Science Faculty Publications

Federated learning (FL) using the federated averaging (FedAvg) algorithm has shown great advantages for large-scale applications that rely on collaborative learning, especially when the training data is either unbalanced or inaccessible due to privacy constraints. We hypothesize that FedAvg underestimates the full extent of heterogeneity of data when the aggregation is performed. We propose Precision-Weighted Federated Learning (PW) a novel algorithm that takes into account the second raw moment (uncentered variance) of the stochastic gradient when computing the weighted average of the parameters of independent models trained in a FL setting. With PW, we address the communication and statistical challenges …

Adaptive Von Mises–Fisher Likelihood Loss For Supervised Deep Time Series Hashing, Juan Manuel Perez, Kevin Garcia, Brooklyn Berry, Dongjin Song, Yifeng Gao

Computer Science Faculty Publications

Indexing time series by creating compact binary representations is a fundamental task in time series data mining. Recently, deep learning-based hashing methods have proven effective for indexing time series based on semantic meaning rather than just raw similarity. The purpose of deep hashing is to map samples with the same semantic meaning to identical binary hash codes, enabling more efficient search and retrieval. Unlike other supervised representation learning methods, supervised deep hashing requires a discretization step to convert real-valued representations into binary codes, but this can induce significant information loss. In this paper, we propose a von Mises–Fisher (vMF) hashing …

The Dissemination Potential Of Microsporidia Mb In Anopheles Arabiensis Mosquitoes Is Modulated By Temperature, Fidel Gabriel Otieno, Priscille Barreaux, Affognon Steeven Belvinos, Edward Edmond Makhulu, Thomas Ogao Onchuru, Anne Wambui Wairimu, Stancy Mandere Omboye, Cynthia Nyambura King’Ori, Bonoukpoè Mawuko Sokame, Anthony Kebira Nyamache, Jeremy Keith Herren

All Peer-Reviewed Publications

Microsporidia MB, a vertically transmitted endosymbiont of Anopheles mosquitoes, shows strong potential as a malaria control agent due to its ability to inhibit Plasmodium development within the mosquito host. To support its deployment in malaria transmission reduction strategies, it is critical to understand how environmental factors, particularly temperature, influence its infection dynamics. In this study, we investigated the impact of four temperature regimes (22 °C, 27 °C, 32 °C, and 37 °C) on Microsporidia MB prevalence and infection intensity by rearing mosquito larvae under controlled laboratory conditions. Our results demonstrate that elevated temperatures, especially 32 °C, significantly enhance both larval …

Freshwater Turtle Assemblages And Densities In Agricultural Ditches And Aquaculture Ponds Of Eastern Arkansas, Andrhea D. Massey, John D. Willson, Brett A. Degregorio

Biological Sciences Faculty Publications and Presentations

The Mississippi Alluvial Plain (MAP) of Arkansas is a landscape where many wetlands have been altered for use as aquaculture ponds or agricultural ditches. Commercial harvest of freshwater turtles within the MAP is not restricted or limited, with reported harvest numbers for 2019 alone exceeding 4000 for spiny softshell turtles (Apalone spinifera) and 39,000 for red-eared sliders (Trachemys scripta elegans). Herein, we attempt to provide baseline estimates of freshwater turtle densities and community composition in aquaculture ponds and agricultural ditches of eastern Arkansas, the habitat types most frequently trapped by commercial harvesters. We used a capture-mark-recapture approach over 3 summers …

Lack Of Multidisciplinary Collaboration In Stroke Rehabilitation In Pakistan: A Call For Integrated Care Models, Etisam Wahid, Shahzad Ahmad, Nimrah Humayoon

Pakistan Journal of Neurological Sciences (PJNS)

No abstract provided.

Cnn Based Deep Learning Modeling With Explainability Analysis For Detecting Fraudulent Blockchain Transactions, Mohammad Hasan, Mohammad Shahriar Rahman, Mohammad Jabed Morshed Chowdhury, Iqbal H. Sarker

Research outputs 2022 to 2026

In the era of growing cryptocurrency adoption, Blockchain has emerged as a leading player in the digital payment landscape. However, this widespread popularity also brings forth various security challenges, including the need to safeguard against fraudulent activities. One of the paramount challenges in this regard is the detection of fraudulent transactions within the realm of Bitcoin data. This task significantly influences the trust and security of digital payments. Yet, it's a formidable challenge given the relatively low occurrence of fraudulent Bitcoin transactions. While deep learning techniques have demonstrated their prowess in fraud detection, there remains a scarcity of studies exploring …