Digital Commons Network^™

Understanding Parental Beliefs And Home Environment In Early Childhood Mathematics: A Perspective From The Theory Of Planned Behavior, Zhengqing Li

Electronic Theses and Dissertations

This study examines the dynamics of parental beliefs and their influence on intentions to engage in the home math environment (HME) for early childhood mathematics learning, using the Theory of Planned Behavior (TPB) as a framework. Specifically, it explores how behavioral, normative, and control beliefs, along with background factors, shape parents' intentions to support children in formal and informal math practices at home. Employing a quantitative approach, the research utilizes a self-designed questionnaire to evaluate the TPB model's applicability and identify key predictors of parental intentions.

The findings reveal that parents' attitudes, perceived social norms, and perceived behavioral control significantly …

Vorticies In The Nonlinear Optical Fluid, Patrick C. Ford

Electronic Theses and Dissertations

In this dissertation, we review the dynamics of the propagation of a laser through a nonlinear medium, and the dynamics of a self-interacting superfluid phase, and show a mathematical analogy between them. We identify an equivalence that allows direct comparison of the properties and dynamics of the optical fluid with those of the Bose-Einstein condensate. Next, we describe some experimental techniques and methods for data capture and analysis on the way to presenting a novel experimental apparatus that has allowed us to study non-equilibrium nonlinear vortex dynamics in the optical fluid, and that will allow more general future studies of …

Leveraging Artificial Intelligence To Strengthen Human Resilience Against Phishing Attacks, Muhammad Mavins

Cybersecurity Undergraduate Research Showcase

Phishing attacks are a major cybersecurity threat, tricking people with fake emails, scam websites, and social engineering tactics. As these attacks become more advanced, traditional security measures are no longer enough to stop them. This paper looks at how Artificial Intelligence (AI) can help detect and prevent phishing while also making people more aware of these threats. Using machine learning (ML), natural language processing (NLP), and behavioral analysis, AI can examine email content, sender behavior, and metadata to spot phishing attempts. AI-powered cybersecurity training can also teach people to recognize and respond to phishing by using personalized phishing tests and …

An Adaptive Simulated Startup Financial Modeling Mentor Using A Large Language Model To Address Shortages In Skilled Advisors: Architecture And Design Considerations, Joseph Benjamin R. Ilagan, Jose Ramon S. Ilagan, Lois Abigail To, Zachary Matthew C. Alabastro

Quantitative Methods and Information Technology Faculty Publications

Entrepreneurship education (EE) aims to deliver various entrepreneurial outcomes. One such entrepreneurial outcome (EO) is entrepreneurial intent (EI), which has been touted as one of the most significant determinants of a new business. Entrepreneurial mentoring (EM) has been linked and indirectly measured for its relationship with improved EO and EI. In countries in the Global South, such as the Philippines, there are only a few qualified instructors and mentors for entrepreneurship. Due to the lack of qualified faculty to do mentoring in universities, this study aims to turn to computer-based alternatives to address the under-resourcing of qualified human faculty. This …

Anniversary Surprise Creates Ole Miss Scholarship, Bill Dabney

University of Mississippi News

OXFORD, Miss. – A gift to the University of Mississippi doubled as a surprise to alumni Sandy and John Black, honoring their 60 years of marriage while providing tuition assistance to Ole Miss students.

Investigating Key Structures In Protective Scenes For Llms, Eben M. Weisman

University Honors Theses

This research delves into the realm of "protective scenes" within Large Language Models (LLMs), exploring their impact on bias mitigation, deception, and context preservation. The study investigates the use of roleplay prompting human-like behavior and reasoning in LLMs, focusing on the Character-LLM framework's concept of protective scenes with graduated levels of protection. By combining insights from psychology, cognitive science, and computational analysis, this research aims to develop a framework for understanding how protective scenes influence roleplay performance in LLMs, ultimately contributing to the development of more reliable and ethical AI systems.

Avoiding The Dreaded Packet: The Impact Of Guided Notes On Student Confidence And Quality Of Poetic Annotations In An 11th Grade Ap Language And Composition Classroom., Kaleigh D. Phelps

Virginia English Journal

This article presents findings from an action research study conducted in a 11th Grade AP Language and Composition classroom on the impact of guided notes on confidence and quality of student work. The data indicates a substantial need for transfer skills in the English classroom.

Reading The Players: Developing Critical Consumers Of Sports Media, Katie Dredger, Katherin Garland, Crystal L. Beach

Virginia English Journal

Sports media is ubiquitous, and English Language Arts (ELA) teachers can use topics around current sporting activities and events in the classroom to engage readers and to teach skills of critical media literacy. Serving as a primer on critical media literacy, this article, grounded in educational theory, gives practical and easily accessible texts and creative lesson ideas to spark engagement, build community, encourage collaboration and foster achievement in secondary ELA classrooms.

Synthetic Protein Mimetic Based Therapies For Neurodegeneration, Nicholas H. Stillman

Electronic Theses and Dissertations

Protein-protein interactions (PPIs) are crucial for the regulation of a majority of, if not every fundamental cellular process. Despite their role in regular biological processes, dysregulated and/or aberrant protein-protein interactions (aPPIs) are often related to the onset of disease including cancer, viral infection, and amyloid diseases. aPPIs have historically been deemed ‘undruggable’ due to their large surface area and lack of a binding cavity; however, today, more than 40 disease-related aPPIs have been targeted with small molecules and several of those have reached clinical trials.

A class of synthetic protein mimetics called oligopyridylamides (OPs) has been shown to inhibit disease-related …

Multi-Sensor Integration And Machine Learning For High-Resolution Classification Of Herbivore Foraging Behavior, Bashiri Iddy Muzzo, Kelvyn Bladen, Andres Perea, Shelemia Nyamuryekung’E, Juan J. Villalba

Wildland Resources Student Research

This study classified cows’ foraging behaviors using machine learning (ML) models evaluated through random test split (RTS) and cross-validation (CV) data partition methods. Models included Perceptron, Logistic Regression, Support Vector Machine, KNearest Neighbors, Random Forest (RF), and XGBoost (XGB). These models classified activity states (active vs. static), foraging behaviors (grazing (GR), resting (RE), walking (W), ruminating (RU)), posture states (standing up (SU) vs. lying down (LD)), and posture combinations with rumination and resting behaviors (RU_SU, RU_LD, RE_SU, and RE_LD). XGB achieved the highest accuracy for state classification (74.5% RTS, 74.2% CV) and foraging behavior (69.4% CV). RF outperformed XGB in …

On Large Language Models In National Security Applications, William N. Caballero, Phillip R. Jenkins

Faculty Publications

The overwhelming success of GPT-4 in early 2023 highlighted the transformative potential of large language models (LLMs) across various sectors, including national security. This article explores the implications of LLM integration within national security contexts, analyzing their potential to revolutionize information processing, decision-making, and operational efficiency. Whereas LLMs offer substantial benefits, such as automating tasks and enhancing data analysis, they also pose significant risks, including hallucinations, data privacy concerns, and vulnerability to adversarial attacks. Through their coupling with decision-theoretic principles and Bayesian reasoning, LLMs can significantly improve decision-making processes within national security organizations. Namely, LLMs can facilitate the transition from …

Failure Mode And Effects Analysis Applied To Central Venous Catheter Placement, James R Duncan, Daniel Harwood, Bruno Maranhao, Ellen Wertenberger, Jacob Grant, Mona Ostman

2020-Current year OA Pubs

Despite diligent efforts, complications continue to occur during the placement of central venous catheters (CVCs). Healthcare Failure Mode and Effect Analysis has been promoted as a process improvement tool and this review describes the strategic application of Failure Mode and Effects Analysis (FMEA) to CVC placement. The objective is to demonstrate the utility of FMEA first as a tool for identifying quality or safety issues and second for guiding mitigation efforts.

Nuanced Relationships Between Teacher Collaboration And Job Satisfaction, Olha Ketsman, Todd Reeves

Mid-Western Educational Researcher

This explanatory correlational study examined nuanced relationships between teacher collaboration and teacher job satisfaction in two school districts in Illinois. A total of N=231 K-12 teachers responded to established measures of teacher job satisfaction and teacher collaboration from the 2018 Teaching and Learning International Survey (TALIS). Structural equation modeling revealed a small positive relationship between one form of collaboration among teachers—professional collaboration in lessons—and job satisfaction with the profession specifically. However, two other forms of collaboration, namely teacher exchange and coordination and professional learning community collaboration, were statistically unrelated to teachers’ satisfaction with both the workplace and the profession …

Session Iib: Natural Sciences Presentation 4 - Extraction Of Essential Oils Form Star Anise And Oxidation To P-Anisic Acid, Tuyet "Snow" Nguyen

Life of the Scholar Multidisciplinary Conference

No abstract provided.

Modeling The Impact Of Nato Policy Actions On Taliban Disinformation Campaigns With Lotka-Volterra Models, Timothy Tarter, Bella Santos

Graduate Research Conference (GSIS)

In this paper, we use an adaptation of the Lotka-Volterra Predator-Prey framework (via Affilit Et. Al.) to model the relationship between Taliban disinformation campaigns and NATO’s attempts to counter them. We find that aggression is a significantly preferred strategy over stagnation; this result should prompt decisionmakers to take strong stances against disinformation campaigns while maintaining a healthy defense against retribution. This leads us to propose the NATO Afghan Youth for Change program, which provides scholarships to individuals throughout the Afghan diaspora to become NATO influencers - a role which will both advance their personal goals and mitigate the spread of …

The Shorthorn: September 25, 1923

The Shorthorn Newspaper Collection: 1920s

No abstract provided.

Soft Law, Activism, And Climate Displacement: Rethinking International Protections For The Environmentally Displaced, Guljannat Huseynli, Andrea G. Brown

Graduate Research Conference (GSIS)

Climate change is displacing millions of people globally, yet those forced to migrate due to environmental factors remain unprotected under existing international refugee law. This paper argues that legal recognition for climate refugees can emerge not through immediate treaty reform but through the evolution of soft law and norm creation. Drawing on constructivist theory, it examines how activism, international organizations, and legal precedents contribute to shifting global norms. Through case studies such as Ioane Teitiota v. New Zealand and the Fridays for Future movement, the paper shows how strategic litigation and advocacy can build momentum for future legal protections. It …

The Shorthorn: May 22, 1923

The Shorthorn Newspaper Collection: 1920s

No abstract provided.

The Shorthorn: May 01, 1923

The Shorthorn Newspaper Collection: 1920s

No abstract provided.

The Shorthorn: December 12, 1922

The Shorthorn Newspaper Collection: 1920s

No abstract provided.

Glass Delta, Manish Rami

Software

A Python script to calculate the effect size Glass' delta in a two group experiment with different standard deviation.

Reservoir Storage In Mid-March: Where Do We Stand?, Jack Schmidt, John Fleck, Kathryn Sorensen, Eric Kuhn, Katherine Tara

The Traveling Wilburys of the Colorado River

No abstract provided.

Component Order Edge Connectivity, Vertex Degrees, And Integer Partitions, Michael R. Yatauro

Theory & Applications of Graphs

Given a finite, simple graph G, the k-component order connectivity (resp. edge connectivity) of G is the minimum number of vertices (resp. edges) whose removal results in a subgraph in which every component has an order of at most k − 1. In general, determining the k-component order edge connectivity of a graph is NP-hard. We identify conditions on the vertex degrees of G that can be used to imply a lower bound on the k-component order edge connectivity of G. We will discuss the process for generating such conditions for a lower bound of 1 or 2, and we …

Digital Stratification: Comparing Digital Literacy Practices Among Aboriginal And Mainstream Children In Australian Homes, Huan Gao, Gui Ying Annie Yang-Heim

Faculty Publications - College of Education

This qualitative study examines the home digital literacy practices of Aboriginal and Mainstream elementary-age children in Australia, highlighting how socio-economic and cultural factors influence these practices. This study integrates conceptural framework such as capital, digital capital, and social reproduction theory to analyze conversational interviews conducted with six children. Our findings reveal significant disparities in digital capital accumulation, primarily driven by socio-economic differences and varied access to digital resources. Mainstream students typically possess more digital capital, which allows them to navigate the digital landscape more effectively and perpetuate systemic inequalities. The enduring digital divide reinforces existing economic and social hierarchies, exacerbating …

Persistence, Mentorship, And Educational Achievement: Exploring The Daca Student Experience, Patricia F. Mejabi

Education Doctorate Dissertations

The study aimed to understand demographic, cultural, and ecological factors, as well as supportive assets like mentorship on the academic persistence and educational achievement of Deferred Action for Childhood Arrivals (DACA) students. DACA protects qualified individuals who arrived in the United States as children from deportation and grants them lawful permission to seek employment and educational opportunities.

Interviews of DACA students, and mentors and advocates of DACA students, were conducted to identify similarities, differences, and common themes. Despite DACA protection positively impacting the students' financial and academic success, limited socioeconomic conditions created a need for guidance or mentorship to help …

Optimizing Parameters For Efficient Computation With Fully Homomorphic Encryption Schemes, Cavi̇dan Yakupoğlu Karaağaç, Kurt Rohloff

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, we aim to provide a parameter selection approach for the BFVrns scheme, one of the prominent fully homomorphic encryption (FHE) schemes. Selecting parameters for lattice-based FHE schemes poses a practical challenge for both experts and nonexperts. To solve this problem, we introduce a hybrid approach that combines theoretical approach with experimental analysis. First, we employ regression analysis to examine the impact of parameters on both performance and security. The varying behavior of FHE parameters in terms of performance, security, and ciphertext expansion factor (CEF) makes parameter selection more challenging. To address this issue, we employ a multi-objective …

Decomposition Lstm With Dual Multi-Head Self-Attention For Wind Turbine Drivetrain State Forecasting, Haikun Jia, Huini Sun, Shuang Bai

Turkish Journal of Electrical Engineering and Computer Sciences

Due to the clean and renewable nature of wind energy, accurate prediction of rotor loads and operating states for wind turbine units has become of paramount importance. Currently, traditional methods relying on expert analysis combined with instrument testing for qualitative reasoning are both time-consuming and labor-intensive, and their accuracy guarantees are limited. In response to wind farm data entailing the interweaving of data from multiple sources and the diverse interrelations across various features and time steps, this study introduces a method for predicting rotor loads and operating states. Initially, we employ an iterative multi-scale seasonal-trend decomposition block to capture latent …

Fuzzy-Virtual Inertia Control To Improve The Frequency Response Of Multi-Area Power Systems, Nourelhouda Djaraf, Yacine Daili, Abderrahim Zemmit, Abdelghani Harrag

Turkish Journal of Electrical Engineering and Computer Sciences

Virtual inertia control (VIC) is essential for power systems dominated by electronic devices to compensate for the lack of inertia and ensure frequency regulation. However, most existing VICs often focus solely on optimizing the virtual inertia parameter to adapt to the high penetration of renewable energy sources (RESs) without considering the damping factor. This oversight can lead to significant fluctuations and power mismatches, especially in interconnected systems where the coordination between MGs is sensitive and essential, and there is a risk of propagation of deviations between MGs, which makes the control more complex. To address these issues, this paper presents …

Enhancing Spatial-Temporal Video Prediction With Ts-Vq-Vae: A Novel Encoder-Processor-Decoder Approach, Mei Feng, Fan Li

Turkish Journal of Electrical Engineering and Computer Sciences

Video prediction is a significant and actively researched area within the data science community. Its primary objective is to generate future video frames based on historical frames, finding applications in diverse domains such as human motion prediction, climate change analysis, and traffic flow forecasting. Traditional methods combine Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to capture complex correlations in spatial-temporal signals. Recent methods improve video prediction accuracy by introducing external information such as optical flow, semantic maps, and human pose data. However, these methods have limitations, such as not fully exploring the intermediate states of learning representations, overlooking …

Conversational Open-Domain Question Answering For Resource-Constrained Languages, Emrah Budur, Tunga Güngör

Turkish Journal of Electrical Engineering and Computer Sciences

The growing interest in Conversational AI has led to the development of Conversational OpenQA systems as a crucial step for meeting users' information needs in real world scenarios. Conversational OpenQA systems enhance standard OpenQA performance by leveraging conversation history of the users. However, building effective Conversational OpenQA systems requires large-scale Conversational OpenQA datasets, often limited to the English language, hindering progress in low-resource languages. We present a robust Conversational OpenQA system enhanced by conversational context, designed for languages with limited resources and exemplified in our case study for Turkish. To address data limitations in a cost-effective way, we repurpose existing …