Digital Commons Network^™

A Report On Health Care Access By The United States Citizens., Kelvin Njuki, Emil Agbemade

Data Science and Data Mining

Access to health care is a critical factor in ensuring public health. This study analyzes data from the National Health Interview Survey (NHIS) for the years 2015–2018 to examine the relationship between health care coverage, affordability, and costs among U.S. families. Re-sults indicate that families with at least one member covered by health insurance were more likely to afford medical care and incur lower health care costs. Despite a high proportion of families with health care coverage during this period, the number of insured family members declined over the years. These findings underscore the importance of health care coverage in …

Exploring Generative Artificial Intelligence (Ai) Applications In Fashion: Ethical Concerns In Human-Like Technology, Melissa Kathryn Gonzalez

Faculty Scholarship and Creative Works

No abstract provided.

Modeling The Relationship Between Calories And Activity Metrics: A Regression Analysis With Variable Selection, Felix Yeboah

Data Science and Data Mining

Physical activity monitors have become integral to daily routines, with wearable devices such as the Apple Watch and Fitbit offering continuous data on users’ physical activity. This study compares the measurement accuracy of these devices by examining how they record parameters relevant to fitness and health. Employing multiple linear regression, we modeled the relationship between calories expended and a set of explanatory variables, including heart rate, steps, distance, age, activity level, weight, and device type. Evaluation of all possible variable combinations identified heart rate, steps, distance, weight, and watch type as the most effective predictors of calorie expenditure. Although the …

Ucf Libraries Promotion Criteria, Jason D. Phillips

Library Faculty

At UCF, library faculty are promoted on the basis of their professional effectiveness and their demonstrated record of achievement. As noted above, performance of Professional Responsibilities is the most important factor in promotion, as this accounts for the majority of a librarian’s annual responsibilities. Achievements in Research/Scholarship/Creative Works and Service are also required, with standards delineated later in the document.

Four Nations Hockey, Richard C. Crepeau

On Sport and Society

The Four Nations Hockey Tournament begins today. The National Hockey League and two television networks are touting this as a matchup as the best-on-best of Hockey. Of course, it is not. It is the best hockey players in the National Hockey League from four countries. The four are Canada, Sweden, Finland, and The United States.

Super Bowl, Richard C. Crepeau

On Sport and Society

In the beginning, it was no larger than a snowflake. Then, it grew to the size of a snowball. Within a few years, it resembled a Midwest snowstorm. Now, it is nothing short of an avalanche.

Optimized Hiv/Aids Resource Allocation In Ohio: A Linear Programming Approach, Godfred Ahenkroa Kesse

Data Science and Data Mining

This study employs a linear and integer programming approach to optimize HIV resource allocation in Ohio, aiming to minimize new infections and enhance the impact of limited resources. With the advances in HIV prevention and treatment, Ohio faces challenges in addressing disparities in access to healthcare, particularly among high-risk populations. The proposed model integrates data on infection rates, transmission patterns, demographic factors, and cost-effectiveness to provide a decision-support framework for policymakers. Using epidemiological data and equity constraints, the model prioritizes high-risk regions and populations while ensuring fair resource distribution. Results indicate that increased funding allocations significantly enhance the potential to …

Agenda 2025-02, Staff Council

Staff Advisory Council Meeting Agendas

A meeting agenda is a list of the topics that will be discussed during a meeting, along with other details. The agenda is usually shared with participants before the meeting so they can prepare. The agenda's purpose is to give participants a clear outline of what should happen in the meeting, who will lead each task, and how long each step should take.

Building And Defending Lgbtq+ Collections, Jason D. Phillips, Jordan Ruud

Faculty Scholarship and Creative Works

This chapter explores the critical role of collection development policies in libraries, particularly in supporting and defending LGBTQ+ collections. The authors argue that a robust, regularly updated, and transparent collection development policy is essential for ensuring equitable representation and resisting censorship. They emphasize that such policies must account for the needs of historically underserved communities, including LGBTQ+ populations, and serve as tools for advocacy and defense against internal and external challenges.

Using real-world examples, the chapter highlights the consequences of outdated or ineffective policies, including instances of hidden censorship and administrative interference in material acquisition. The authors advocate for retrospective …

At What Cost? The Personal Stakes Of Intellectual Freedom, Jason D. Phillips, Jordan Ruud

Faculty Scholarship and Creative Works

This chapter explores the emotional, professional, and political costs faced by librarians advocating for LGBTQ+ inclusion and intellectual freedom within libraries. Through personal narrative and critical reflection, the authors introduce the concept of "queer battle fatigue"—a framework for understanding the cumulative psychological toll on LGBTQ+ individuals who are consistently placed in advocacy roles within predominantly cisheteronormative institutions. A case study of a drag storytime event at a university library illustrates the social backlash, institutional pressures, and moral injury experienced by organizers, demonstrating how well-intentioned programming can become flashpoints for political controversy. The authors highlight the intensifying hostility toward LGBTQ+ representation …

Introduction, Jason D. Phillips, Jordan Ruud

Faculty Scholarship and Creative Works

This introductory chapter sets the stage for a collection addressing the censorship and resistance surrounding LGBTQ+ materials in libraries. The editors, drawing from personal experiences and professional challenges, reflect on the increasing sociopolitical hostility toward LGBTQ+ communities and the parallel rise in restrictions within library spaces. They argue that libraries cannot remain neutral as targeted attacks on marginalized groups intensify, and they position this book as both a chronicle of current struggles and a practical toolkit for resistance. Highlighting contributions from a diverse group of librarians across various library types and geographic locations—including voices from Canada, Ireland, and the Philippines—the …

The Scoop, Vol. 11 Issue 11, February 2025, Health Sciences Library

Volume 11

Latest news and updates from the Health Sciences Library in our monthly newsletter for February 2025. Please see page 2 for a text-only version of this issue!

Enemies Within The Gates: Contending With Internal Censorship Challenges, Jason D. Phillips

Faculty Scholarship and Creative Works

This chapter explores the rarely discussed but impactful issue of internal censorship within academic libraries, focusing on challenges to LGBTQ+ materials. Drawing on personal experiences at a regional public university in the American South, the author recounts multiple instances where library staff and leadership acted in ways that undermined the inclusion of LGBTQ+ resources. These incidents ranged from quietly removing or hiding books to resisting the addition of LGBTQ+ periodicals and graphic novels, and even denying purchase requests without explanation. The chapter underscores how fear of controversy, personal bias, and institutional conservatism can result in "soft censorship," despite the profession's …

How To Use Copilot And Chatgpt To Create Rubrics, Lina Eskew

Teaching Repository of AI-Infused Learning

This entry explores how AI can assist instructors in creating assignment rubrics that follow a transparency framework. By leveraging AI to generate clear and detailed criteria, instructors can eliminate ambiguity to ensure that students understand what is expected of them.

Instruction In Synthesis Writing Can Be Augmented By Giving Students A Generative Ai Prompt, Drew Loewe

Teaching Repository of AI-Infused Learning

This entry describes an AI-augmented strategy to assist students in synthesis writing, specifically in a general education writing course. The approach uses an instructor-created generative AI prompt to give additional in-process feedback on drafts, helping students identify and address common synthesis challenges such as patchwriting and sequential reporting. Preliminary results suggest that students using the AI prompt demonstrated increased confidence and improved synthesis skills, as indicated by both their self-reports and better assignment performance compared to previous semesters.

Ai-Integrated Cross-Disciplinary Liberal Arts Colloquium, Diana S. Perdue, Niloofar Gholamrezaei, Jennifer Krusinger, Shannon Hogan

Teaching Repository of AI-Infused Learning

What began organically as an AI-focused collaboration between faculty in different disciplines along with researchers in the college’s Center for Instructional Innovation, has evolved into college-wide pedagogical workshops and the development of a studio model that affects courses, programs, and paradigms for faculty scholarship.

Lessons from these collaborations inform understandings of how key features of liberal arts education can be supported through intentional AI-integration within a Cross-Disciplinary Liberal Arts Colloquium. More specifically, this colloquium offers recommendations on adapting a collaborative, interdisciplinary, and reflective studio model to in-person, online, and hybrid educational environments facilitated through a Technological Pedagogical Content Knowledge (TPACK) …

Uncovering Acoustic Biomarkers To Classify Parkinson Disease Through Machine Learning, Felix Yeboah

Data Science and Data Mining

The early detection of diseases profoundly influences treatment efficacy, and accurate classification methodologies are essential for effective disease identification. In this project, we examined fve different classifers—Logistic Regression, Gaussian Naive Bayes, K Nearest Neighbor (KNN), Extreme Gradient Boosting (XGBoost), and Support Vector Machines—and evaluated their performance in detecting Parkinson’s disease (PD) based on voice features. The study aims to identify the best classifier for detecting PD. XGBoost performed the best, with an accuracy of 91% on the full dataset. After variable selection, KNN had the best performance with an accuracy of 91%. These findings suggest that Machine learning algorithms(classifiers) can …

Evaluation Of Variable Selection Techniques On The Genetic Architecture Of Flowering Time In Maize, Felix Yeboah

Data Science and Data Mining

In this project, we investigate several variable selection procedures to give an overview of how well they perform on a genomic dataset using three different penalized regression approaches. Comparisons between different methods were performed. These methods include Ridge, lasso, and Elastic Net. We utilized 4494 observations with 7389 SNPs gene scores to predict time to male flowering (dtoa). We assessed the performance of these three models in terms of mean square error. Not surprisingly, Lasso and Elastic Net perform better than Ridge Regression. Overall, Elastic Net performed better in predicting the time of male flowering (dtoa).

2025 Ucf Book Arts Competition Official Entry Form, Special Collections & University Archives

Libraries' Documents

No abstract provided.

Comparison Of Two Strategies Of Screening Experiments: Single-Shot Experiment Vs. Two-Stage Screening Experiment, Kelvin Njuki, Emil Agbemade

Data Science and Data Mining

Experiments involving many factors are often complex, time-consuming, and expensive. Screening out the least important factors helps the experimenter(s) allocate the limited resources efciently to the most important factors. Supersaturated and orthogonal array designs are among the designs used to conduct screening experiments. Supersaturated designs (SSDs) are those where the number of runs (observations) is less than the number of factors, while orthogonal array (OA) designs are those where at least the columns are orthogonal to each other. In this study, we conduct a simulation study to compare two strategies of screening experiments. Strategy one is a single shot experiment …

Video Spotlight - Paraphrasing Made Easy, Diamond R. Williams

Libraries' Documents

No abstract provided.

Advanced Machine Learning Techniques For Cardiovascular Disease Risk Prediction, Godfred Ahenkroa Kesse

Data Science and Data Mining

of mortality, necessitating advanced predictive models to aid early detection and prevention. This study explores the application of machine learning techniques, including Lo- gistic Regression, K-Nearest Neighbors (KNN), Random Forest, and XGBoost, to predict CVD risk using a dataset of 69,997 observations encompassing demographic, clinical, and lifestyle factors. Data preprocessing involved one-hot encoding of cat- egorical variables and scaling to ensure compatibility with all models. Model performance was evaluated using metrics such as accuracy, precision, recall, F1-score, and AUC-ROC. Among the models, XGBoost demonstrated the highest accuracy at 74%, leveraging its gradient-boosting framework to effectively handle feature interactions and imbalanced …

Predicting Blood Glucose Levels: A Linear Regression Approach For Non-Invasive Monitoring, Godfred Ahenkroa Kesse

Data Science and Data Mining

Accurate monitoring of blood glucose levels is vital for the management of diabetes, a chronic condition affecting millions worldwide. This study explores a linear regression approach to estimate glucose levels non-invasively using a dataset enriched with demographic, physiological, and sensor-based variables. Following rigorous data preparation, including normalization and encoding, a Box-Cox transformation was applied to address violations of regression assumptions, stabilizing variance and improving model validity. Stepwise selection and hypothesis testing were employed to refne the model, retaining signifcant predictors such as AGE, GENDER, HEARTRATE, and DIABETIC, while excluding variables like NIR Reading and LAST EATEN for their minimal contribution. …

Handwritten Digit Recognition Using Naive Bayes And K-Nearest Neighbor Models, Godfred Ahenkroa Kesse

Data Science and Data Mining

This paper explores the performance of two fundamental classifcation algorithms. It uses Naive Bayes and K-Nearest Neighbors (KNN), framing it within the context of digit recognition of the MNIST dataset. The MNIST dataset has 70,00 grayscale images of handwritten digits, offering a standard for assessing classifcation models. This paper focuses on key performance metrics such as precision, accuracy, recall, and F1score to examine the effciency of each model. The results reveal that Naive Bayes has moderate accuracy and misclassifcations because of its notion of feature independence. The paper concludes that the KNN model performs better with the optimal k-value of …

Variable Selection Using Lasso Regression, Godfred Ahenkroa Kesse

Data Science and Data Mining

This study employs Lasso regression to analyze highdimensional genetic data for predicting flowering time in maize, specifically Days to Anthesis (DtoA). Lasso, or Least Absolute Shrinkage and Selection Operator, is a form of linear regression that introduces an L1 penalty to the model, encouraging sparsity by shrinking some coefficients to zero. This attribute makes Lasso ideal for feature selection in large datasets, as it highlights the most influential predictors while discarding irrelevant variables. Unlike Ridge regression, which applies an L2 penalty to minimize the squared magnitude of coefficients, Lasso’s L1 penalty induces sparsity, providing a clearer interpretation of the selected …

Classification And Evaluation Of Machine Learning Algorithms On The Mnist Dataset, Felix Yeboah

Data Science and Data Mining

This paper discusses the use of machine learning algorithms in classifying the MNIST handwritten dataset. The MNIST dataset consists of 28x28 grayscale handwritten images with 10 classes from 0 to 9. The dataset was normalized by scaling the pixel values to a range between 0 and 1 by dividing each pixel value by 255. We compare and evaluate the K-nearest Neighbor and Naive Bayes algorithm based on performance metrics such as accuracy, error rate, f1-score, and precision. The K-nearest Neighbor algorithm achieved better performance in all the evaluation criteria.

Know Your Library - Mango Languages, Diamond R. Williams

Libraries' Documents

No abstract provided.

Meeting Minutes 01-15-2025, Staff Advisory Council

Staff Advisory Council Meeting Documents

No abstract provided.

Ucf Pegasus Plan - 1st Grade - Maps & Globes, Cecilia Nuss, Mackenzie Luley, Jessenia Diaz, Alyssa Arnott, Miranda Howley

Pegasus Plans: Social Studies Unit Plans for Florida Teachers

During this unit, students will explore and create various maps and globes through multimedia resources, Hands-on activities, and assessments. The daily lessons cover topics such as a compass rose, cardinal directions, map titles, and physical features on maps and globes. By the end of this unit, students will be able to identify key elements and locate physical features of maps and globes. Through the use of songs, hands-on activities, games, books, and class discussions, students will be engaged throughout the unit.

Case Report: Adult Patient With Acquired Apraxia Of Speech Secondary To A Stroke In Broca's Area, Richard Zraick

UCF Created OER Artifacts

This open educational resource (OER) is a case report about an adult patient with acquired apraxia of speech secondary to stroke in Broca's area. This case report was originally developed for SPA 6236: Motor Speech Disorders, School of Communication Sciences & Disorders, University of Central Florida, by Richard Zraick, Ph.D., CCC-SLP, F-ASHA. The content was based on output from ChatGPT and generated with the prompt: “Create a fictional case report for an adult patient with acquired apraxia of speech secondary to cerebrovascular accident in Broca’s area.” Others are free to reuse this OER to distribute, remix, adapt, and build upon …