Digital Commons Network^™

Studying Causal Inferences For Student Success In Higher Education, Prabesh Shrestha

Theses and Dissertations

Higher education institutions strive to support students in achieving their academic goals through targeted interventions and data-driven strategies. This study analyzed 19 variables, spanning student demographics, enrollment patterns, and institutional interventions, to identify predictors of students completing all enrolled courses in a semester. Using random forest, logistic regression, and bootstrap forest models, we assessed variable importance and derived causal estimates to determine their impact. Results from causal analysis indicate positive effects from session type, term load, referrals, kudos, flags, and scholarships, while negative impacts were associated with location, course delivery method, enrollment status, advisor contact, and registration interval. These findings …

Achieving More Accurate And Interpretable Fraud Detection With Double Machine Learning, Jeremy Andrew Berry

Theses and Dissertations

Fraud detection remains a critical challenge across industries such as insurance, healthcare, finance, and government. Global losses from fraud and financial crime are estimated in the trillions annually, including billions in healthcare and insurance fraud alone. While effective for prediction, traditional machine learning methods often lack causal interpretability and struggle to adapt to evolving fraud tactics. This dissertation investigates the application of Double Machine Learning (DML), an emerging causal inference technique, to enhance both the accuracy and interpretability of fraud analytics. The research compares DML against established causal inference approaches, leveraging a meta-learning framework to evaluate model performance on accuracy, …

Teachers’ Emotional Appraisals And The Reframing Of Student Change In Post-Pandemic Schools, Rachel Gaines, Mei-Lin Chang, Kristen Mosley

Faculty Articles

Introduction:

The return to “normal” schooling after the COVID-19 pandemic reactivated many of the emotional, instructional, and moral tensions teachers experienced during emergency remote teaching. Yet, little is known about how teachers’ emotional appraisals of post-pandemic classrooms intersect with deficit-oriented “learning loss” discourses. Guided by appraisal theory and Frenzel’s reciprocal model of teacher emotions, this qualitative study examined how mid- and late-career teachers interpreted perceived changes in students and how these appraisals shaped their emotions, emotion regulation, and adoption of or resistance to deficit framings.

Methods:

Ten K–12 teachers from the southeastern United States participated in semi-structured interviews. Data were …

Enviromental Dna (Edna) Tools For Invasive Mosquitofish (Gambusia Affinis) Surveillance At The Shoshone Pupfish (Cyprinidon Nevadensis Shoshone) Refugium, Yusuf Olamilekan Umar

UNLV Theses, Dissertations, Professional Papers, and Capstones

Spring-fed aquatic ecosystems of the North American Southwest and U.S. Great Basin hosts a plethora of endemic fish species due to the effects of hydrologic fragmentation that resulted from Pleistocene aridification. Threats to endemic fishes worldwide include human intentional or unintentional release of exotic species into their habitats. Early detection of invasive species, while corrective actions are still possible, is critical for management, yet traditional survey methods are often disruptive to sensitive ecosystems, costly, and limited in sensitivity. The recent development of environmental DNA (eDNA) approaches offers powerful alternatives for invasive species monitoring in aquatic systems. In this study, a …

Measuring And Modeling Nonlinear Vibrations In Structures With Mechanical Joints, Suzanna Gilbert

Theses and Dissertations

Many assembled structures have bolted or riveted joints. Aside from providing a convenient method of assembly, mechanical joints have an important effect on the structure's dynamic response to its environment. Friction and microslip within the joints help to damp out unwanted vibration. However, the joints also introduce nonlinearity into the response. Most notably, the natural vibrational modes of the structure no longer have constant natural frequencies and damping ratios. Rather, they shift as a function of vibration amplitude. Several methods exist to characterize the dynamics of nonlinear systems, yet they are generally validated on simple benchmark structures, and many still …

Breaking Barriers: Understanding Factors Constraining Women’S Career Choices And Progression In The South African Construction Industry, Abimbola Olukemi Windapo, Olugbenga Timo Oladinrin, João Alencastro, Dineo Mbekwa, Christiana Ekpo, Muhammad Qasim Rana, Amanda Filtane

School of Art, Design and Architecture

Purpose – This paper examines the barriers constraining women's career choices and progression within the South African construction industry. Design/methodology/approach – The study employed a mixed-methods research approach, utilizing a questionnaire survey of construction industry workers listed in the Construction Professions Register, the Builders Collective and the Housing Assembly Organization. It also used interviews to validate the quantitative data. The data collected were analysed using descriptive and inferential statistics, including factor analysis. Findings – The study found that 39 of the 46 barriers identified have normalized values greater than 0.5 and, therefore, are classified as critical. From a ranking perspective, …

The Development Of Children's Beliefs About The Purpose Of Life Events, Amal Salem Shamkhi, Ghada Ali Hadi

Alustath Journal for Human and Social Sciences

The current research aims to identify: 1- Children's beliefs about the purpose of life events according to the variables: A- Age (5, 6, 7, 8, 9, 10) years. B- Gender (males - females) 2- Statistically significant differences in children's beliefs about the purpose of life events according to the variables: A- Age (5, 6, 7, 8, 9, 10) years. B- Gender (males - females). The current research sample included (240) boys and girls from kindergartens and government primary schools in Dhi Qar Governorate, aged (5, 6, 7, 8, 9, 10) years, with (40) boys and girls for each age group, …

Level Of Confidence In The Writing Performance Of Arabic Language Students At King Khalid University, Mahmoud Helal Abdel Baset Abdel Kader

Alustath Journal for Human and Social Sciences

The aim of the current research is to identify the degree of confidence in the written performance of Arabic language students at King Khalid University in the Kingdom of Saudi Arabia. To achieve this goal, the researcher used the descriptive method. Due to its suitability to the nature of the current research and its goal, the researcher then prepared the necessary tools to achieve the goal of the research. These tools were: a measure of confidence in the appropriate written performance of students of the Arabic language at a university. Then the researcher sought to ensure the stability and validity …

Replacement And Reputation, Navin Kartik, Elliot Lipnowski, Harry Pei

Cowles Foundation Discussion Papers

Does electoral replacement ensure that officeholders eventually act in voters’ interests? We study a reputational model of accountability. Voters observe incumbents’ performance and decide whether to replace them. Politicians may be “good” types who always exert effort or opportunists who may shirk. We find that good long-run outcomes are always attainable, though the mechanism and its robustness depend on economic conditions. In environments conducive to incentive provision, some equilibria feature sustained effort, yet others exhibit some long-run shirking. In the complementary case, opportunists are never fully disciplined, but selection dominates: every equilibrium eventually settles on a good politician, yielding permanent …

Advancing Cybersecurity Practice: Explainable Machine Learning For Network Intrusion Detection, Adam Grabowski, Shengjie Xu

Journal of Cybersecurity Education, Research and Practice

This research investigates explainable artificial intelligence (XAI) integration within machine learning (ML)-based intrusion detection systems (IDS), focusing on distinguishing malicious from benign network activities. We employed Random Forest and XGBoost models evaluated on widely recognized datasets, including NSL-KDD and UNSW-NB15, using both binary and multi-class classification tasks. The objective was to enhance cybersecurity operations through improved model transparency and interpretability. By integrating SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-Agnostic Explanations), the study offers comprehensive global and local insights into model decision-making processes. Results demonstrate SHAP's effectiveness in providing a broad, dataset-wide understanding of feature interactions and importance, while …

Cybercamp: An Experience Report On The Transformations Of An Intensive Cybersecurity Summer Camp For High School Students, Jose R. Ortiz Ubarri, Kariluz Dávila Diaz Ph.D., Rafael A. Arce Nazario

Journal of Cybersecurity Education, Research and Practice

The Cybercamp is a Cybersecurity summer camp for high school students that has been held for the last nine years at a Hispanic Serving Institution. Since its inception in 2016 the Cybercamp has undergone several transformations in response to budget reductions and the COVID pandemic, to finally become its current version: a rich, hands-on learning experience that we believe is easily replicable even in resource-challenged environments.

In this paper, we document the transformations of the Cybercamp and discuss the developed curriculum and materials in hopes that others will reuse, adapt, and improve upon them. In the Cybercamp, we apply active …

Patterns Of Llm Weaponization: A Comparative Analysis Of Exploitation Incidents Across Commercial Ai Systems, George Antoniou

Faculty and Staff Publications & Presentations

This comparative study examines patterns of Large Language Model (LLM) weaponization through systematic analysis of four major exploitation incidents spanning 2023-2025. While existing research focuses on isolated incidents or theoretical vulnerabilities, this study provides the first comprehensive comparative framework analyzing exploitation patterns across state-sponsored cyber-espionage (Anthropic Claude incident), academic security research (GPT-4 autonomous privilege escalation), social engineering platforms (SpearBot phishing framework), and underground criminal commoditization (WormGPT/FraudGPT ecosystem). Through comparative analysis across eight dimensions—adversary sophistication, target selection, exploitation techniques, autonomy levels, detection evasion, attribution challenges, defensive gaps, and capability democratization—this research identifies critical cross-case patterns informing defensive prioritization. Findings reveal three …

The Evolution Of Southern Ocean Net Primary Production In A Changing Climate: Challenges And Opportunities, Alessandro Tagliabue, Thomas Ryan-Keogh, Alex Baker, Thomas S. Bibby, Chris Follett, Maeve C. Lohan, Alberto Naveira-Garabato, Daniel J. Mayor, Angela Milne, C. Mark Moore, Simon Ussher

School of Geography, Earth and Environmental Sciences

Net primary production in the Southern Ocean plays a critical role in governing ecosystem production, the biological carbon pump, and global biogeochemical cycles. Recent work has advanced our understanding of novel factors regulating Southern Ocean net primary production and the regional physiological adaptations employed by Southern Ocean phytoplankton in terms of their photosynthetic strategies and resource acquisition. Here we assess trends in Southern Ocean net primary production from different remote sensing algorithms and bgc-Argo floats to compare them to the latest Earth System Models used to forecast future changes under three different future climate scenarios. Overall, remote sensing and bgc-Argo …

Opinions Of The Uk General Public And Stroke Survivors In Using Artificial Intelligence And ‘Opt-Out’ Models Of Consent In Medical Research: A Qualitative Study, William Heseltine-Carp, Mark Thurston, Michael Allen, Daniel Browning, Megan Courtman, Aishwarya Kasabe, Emmanuel Ifeachor, Stephen Mullin

Peninsula Medical School

Background Artificial intelligence (AI) in healthcare often requires large, confidential clinical datasets. However, a recent UK government survey revealed that 20–40% of the public remain sceptical of its use in health research due to concerns about data security, patient–practitioner communication and commercialisation of data. A greater understanding of public attitudes is therefore needed, particularly in the context of stroke research.In this article, we describe the patient and public involvement work undertaken for the AI-Based-Stroke-Risk-fActor-Classification-and-Treatment (ABSTRACT) project, which aims to train AI models to predict future stroke risk from the electronic health records of 1 18 736 patients.Aims We aimed to …

The Tax Adviser, Volume 3, Number 10, October 1972, American Institute Of Certified Public Accountants

Tax Adviser

No abstract provided.

Final Accumulation Trust Regulations: Explained, Evaluated And Exemplified, Bernard Barnett

Tax Adviser

No abstract provided.

Fault Structure, Deformation Mechanisms, And Why Fault Zones Matter To Society, Elizabeth S. Petrie, David A. Ferrill, Kelly K. Bradbury, James P. Evans

Geosciences Faculty Publications

Faults are widespread geologic structures that form in sediment and all rock types, occur in all tectonic regimes, and can be a blessing or a curse to society. Faults and fault zones act as conduits for underground movement of water and as plumbing systems for aquifers and springs essential for human habitation in many semi-arid and arid regions worldwide. Faults also provide pathways for natural oil and gas migration and high-permeability zones in hydrocarbon reservoirs, as well as barriers contributing to trapping and reservoir compartmentalization. By enhancing permeability in many geothermal energy systems, faults can be essential for fluid circulation …

Enhancing Advanced Persistent Threat Detection With Federated Learning And Neural Networks For Secure Cloud Computer Environment, Baydaa Flayyih Hasan, Wafaa Ayoub Kassara, Bushra Raad Zahi

Mesopotamian Journal of CyberSecurity

Rapid internet expansion and global cloud storage use have heightened the risk of stealthy, persistent, multi-stage Advanced Persistent Threats (APTs). Distributed and resource-limited cloud environments make identifying these stealthy and dynamic threats difficult for traditional Intrusion Detection Systems (IDSs). This paper present FedNN-APT, a Federated Learning (FL) and hybrid Neural Network (NN) APT detection system to overcome these difficulties. High detection accuracy and distributed, privacy-preserving training over several cloud devices are achieved by this approach. FedNN-APT integrates Gated Recurrent Units (GRUs) and Convolutional Neural Networks (CNNs) to learn temporal and spatial APT behavior features effectively. The framework trains local models …

A Novel Of Bounded Zeghdoudi Distribution: Estimations, Simulation And Applications, Mohammed Elgarhy, Hanene Hamdani, Laxmi Prasad Sapkota, Ahmed M. Gemeay

Mesopotamian Journal of CyberSecurity

In this article, we introduce a new unit Zeghoudi distribution, which is called the bounded Zeghoudi distribution (BZD), an innovative modification of the Zeghoudi distribution (ZD). This new suggested distribution retains the original ZD’s simplicity while improving modeling flexibility and accuracy for data constrained to the unit interval. The BZD displays numerous significant characteristics, including decreased, left-skewed, right-skewed, and unimodal probability density functions, but the hazard rate function can be J-shaped, U-shaped, and bathtub-shaped. Some important statistical features of the BZD, such as moments, mean, variance, moment generating function, lower and upper incomplete moments, mean residual life, mean inactivity time, …

Content Aware Intra And Inter Prediction Using Texture And Motion Analysis, Yashaswi Karthik Reddy Danda

Theses

Modern video codecs rely on highly optimized block based intra and inter prediction frameworks,  in which block partitioning is determined through exhaustive rate distortion optimization (RDO)  searches. These exhaustive searches evaluate many possible block configurations to identify the  partitioning that minimizes overall rate distortion cost, and they have proven extremely effective  across diverse visual content. This thesis explores a complementary perspective by investigating  whether block partitioning can be guided more directly by content characteristics specifically,  texture complexity for intra prediction and motion complexity or motion density for inter  prediction.  For intra prediction, we introduce a texture adaptive approach that utilizes …

The Effect Of Phosphate Fertilizer And Organic Matter On Phosphorus Status, Ph, And Cabbage Yield In Andisols, Mahfud Arifin, Emma Trinurani Sofyan, Anni Yuniarti, Rina Devnita, Sastrika Anindita

Jurnal Kultivasi

Andisols are characterized by high phosphorus (P) retention, which often limits P availability for crops. This study aimed to analyze the independent and interactive effects of P fertilizer and organic matter (i.e. manure and rice straw compost) on P retention, total P, available P, P uptake, soil pH, and cabbage yield. This research was conducted in pot experiments in plastic house, applying P fertilizer (0, 90, 180, 270 kg ha-1) and organic matter (20 kg ha-1 of chicken, sheep, cow manures and rice straw compost) on Andisols planted with cabbage. The experiment used a factorial randomized design. The results showed …

Application Of Adversarial Volumetric Cnns To 3d Face Generation Using Latent Space Gaussian Embeddings, Ali Raad Abdulkareem, Marwa Jabberi, Islem Jarraya, Tarek M. Hamdani, Khmaies Ouahada, Adel M. Alimi

Iraqi Journal for Computer Science and Mathematics

Although 3D face generation is extensively studied in computer vision, most existing methods prioritize reconstructing 3D geometry from available 2D or 3D inputs rather than generating novel faces directly from latent representations. To bridge this gap, we present the application of Adversarial Volumetric Convolutional Neural Networks (AVCNN), a tailored adaptation of the vanilla 3D Generative Adversarial Network (3D-GAN), to 3D face generation using latent space Gaussian embeddings. We first assemble a custom 3D facial dataset to provide the requisite facial characteristics and to ensure sufficient coverage of geometric variation across identities. The generator, implemented as a decoder, maps latent space …

Retracted: Fuzzy Backstepping Approach To Stabilizing Fuzzy Parabolic Partial Differential Equations, Zainab John, Fadhel S. Fadhel, Samsul Ariffin Abdul Karim, Teh Yuan Ying

Iraqi Journal for Computer Science and Mathematics

In this work,\floatquery[-14pc]AU: Please provide ORCID ID for remaining authors. we study the solvability and stability of the fuzzy reaction-diffusion equation and the fuzzy diffusion equation with nonhomogeneous boundary conditions. Firstly, we derive the fuzzy exact solutions by converting the nonhomogeneous boundary condition to a homogeneous condition, then we prove the instability of the solution by using simulation approach with the help of Maple program. From this, we have decided to implement the fuzzy backstepping approach to developed the stabilization of the fuzzy parabolic partial differential equations. By using this approach together with the generalized Hukuhara (gH) derivative, we were …

Investigating Teacher Perceptions Of Strategies That Led To Success Of Long-Term English Learners Passing English Assessment Exams, Whitney Hodges

Ed.D. Dissertations

Long term English learners are those who have been enrolled in United States public schools for at least five to seven years yet have not exited language services via passing scores on language assessments. Those students have less opportunity to take preferred elective courses in middle and high school, and less opportunity to take higher level course work. This impacted the students, teachers, and instructional leaders when it came to scheduling, fulfilling graduation requirements, and meeting schoolwide and statewide growth and achievement goals. Previous researchers provided strategies for helping newcomers learn a language, and move from basic interpersonal communication skills …

A Bump Hunting Approach To Finding Interpretable Data Pockets, Tushar Ojha

Electrical and Computer Engineering ETDs

This dissertation approaches the problem of extracting simple interpretations from local regions of data. This is sometimes called bump hunting because the local regions of interest have a high concentration of a particular output value. This work develops a bump hunting method for discrete-valued tabular data where each bump is modeled by a rectangular region of the input data space so its rule-based description admits a simple logical interpretation that can inform decisions. This method is designed for labeled data where each input feature has a distinct meaning that may or may not be related to the output, and the …

Fedchae: Federated Learning With Client Clustering And Hybrid Adaptive Engagement, Chaeeun Park

Electrical and Computer Engineering ETDs

As machine learning adoption expands, data privacy concerns have grown significantly. Federated Learning (FL) addresses this challenge by allowing clients to train locally and share only their model parameters with the server. However, conventional FL methods such as FedAvg suffer from high communication overhead, as all clients must participate in every global round.

This paper proposes FedChae (Federated Learning with Client Clustering and Hybrid Adaptive Engagement) to balance communication efficiency and model accuracy. FedChae alternates between Grouping Rounds, where all clients perform clustering, and Conventional Rounds, where one client per cluster updates the model.

Simulations with 100 clients using Multi-class …

2025 Fall - Commencement Program, Office Of The Registrar, East Tennessee State University

ETSU Commencement Ceremonies and Programs

No abstract provided.

Macadams Gift Names Gate 30 At Vaught-Hemingway Stadium, Bill Dabney

University of Mississippi News

OXFORD, Miss. – Kristen and Nat MacAdams' recent gift to the University of Mississippi is being honored by the Ole Miss Athletics Foundation with a lasting family tribute.

176th Commencement, Fall

Commencement Programs

Commencement program (graduate and undergraduate exercises) for fall 2025

Kakeya Sets Over The Heisenberg Group, Gabriel Jacob Gress

Mathematics & Statistics ETDs

The Hausdorff dimension of Kakeya sets is an interesting problem where the two-dimensional case can be proven directly, but even obtaining bounds on the higher dimension analogues can require highly technical machinery. The difficulty of the general case has inspired analysts to look at Kakeya sets from non-Euclidean viewpoints.

In this paper, we explore a construction of the Kakeya set in the first Heisenberg group H^1. By utilizing the sub-Riemannian manifold of H^1 we can apply tools in geometric measure theory which at this time cannot be applied in R^3. We restate and provide a detailed proof for a sharp …