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A Report On Health Care Access By The United States Citizens., Kelvin Njuki, Emil Agbemade Feb 2025

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 …

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Modeling The Relationship Between Calories And Activity Metrics: A Regression Analysis With Variable Selection, Felix Yeboah Feb 2025

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 …

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Ucf Libraries Promotion Criteria, Jason D. Phillips Feb 2025

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.

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Four Nations Hockey, Richard C. Crepeau Feb 2025

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.

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Super Bowl, Richard C. Crepeau Feb 2025

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.

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Optimized Hiv/Aids Resource Allocation In Ohio: A Linear Programming Approach, Godfred Ahenkroa Kesse Feb 2025

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 …

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Agenda 2025-02, Staff Council Feb 2025

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.

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Instruction In Synthesis Writing Can Be Augmented By Giving Students A Generative Ai Prompt, Drew Loewe Jan 2025

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.

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Uncovering Acoustic Biomarkers To Classify Parkinson Disease Through Machine Learning, Felix Yeboah Jan 2025

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 …

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Evaluation Of Variable Selection Techniques On The Genetic Architecture Of Flowering Time In Maize, Felix Yeboah Jan 2025

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).

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Comparison Of Two Strategies Of Screening Experiments: Single-Shot Experiment Vs. Two-Stage Screening Experiment, Kelvin Njuki, Emil Agbemade Jan 2025

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 …

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Advanced Machine Learning Techniques For Cardiovascular Disease Risk Prediction, Godfred Ahenkroa Kesse Jan 2025

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 …

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Predicting Blood Glucose Levels: A Linear Regression Approach For Non-Invasive Monitoring, Godfred Ahenkroa Kesse Jan 2025

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. …

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Handwritten Digit Recognition Using Naive Bayes And K-Nearest Neighbor Models, Godfred Ahenkroa Kesse Jan 2025

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 …

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Variable Selection Using Lasso Regression, Godfred Ahenkroa Kesse Jan 2025

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 …

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Classification And Evaluation Of Machine Learning Algorithms On The Mnist Dataset, Felix Yeboah Jan 2025

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.

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Meeting Minutes 01-15-2025, Staff Advisory Council Jan 2025

Meeting Minutes 01-15-2025, Staff Advisory Council

Staff Advisory Council Meeting Documents

No abstract provided.

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Ucf Pegasus Plan - 1st Grade - Maps & Globes, Cecilia Nuss, Mackenzie Luley, Jessenia Diaz, Alyssa Arnott, Miranda Howley Jan 2025

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.

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Case Report: Adult Patient With Acquired Apraxia Of Speech Secondary To A Stroke In Broca's Area, Richard Zraick Jan 2025

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 …

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Mnemonic To Paraphrase A Source And Cite In Apa 7th Edition, Lily Dubach Jan 2025

Mnemonic To Paraphrase A Source And Cite In Apa 7th Edition, Lily Dubach

UCF Created OER Artifacts

This open educational resource illustrates the input-output flow from a prompt typed into ChatGPT 4o (a generative AI developed by OpenAI) to elicit a mnemonic to help students understand how to paraphrase a source and cite it in APA 7th edition.

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Predicting Superconducting Critical Temperature From Composition-Derived Features: A Transparent Linear And Regularized Regression Study, Md Ahiduzzaman Jan 2025

Predicting Superconducting Critical Temperature From Composition-Derived Features: A Transparent Linear And Regularized Regression Study, Md Ahiduzzaman

Data Science and Data Mining

We study prediction of superconducting critical temperature (Tc) from 81 composition-derived descriptors across 21,263 materials. To keep the analysis transparent and repro- ducible, we focus on linear models: Ordinary Least Squares (OLS), Ridge, Lasso, and Elastic Net (ENet). All models share a single evaluation protocol (5-fold cross-validation with standardized inputs) and are compared on RMSE, MAE, and R2. On this feature set, OLS attains the best cross-validated performance (RMSE = 17.6 K, MAE = 13.3 K , R2 = 0.735), with Lasso/ENet essentially tied next (RMSE ≈ 17.7 K , R2 ≈ 0.734); Ridge underperforms (RMSE = 18.9 K , …

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Comparative Analysis Of Lasso, Ridge, And Elastic Net For Variable Selection In High-Dimensional Maize Data, Md Ahiduzzaman Jan 2025

Comparative Analysis Of Lasso, Ridge, And Elastic Net For Variable Selection In High-Dimensional Maize Data, Md Ahiduzzaman

Data Science and Data Mining

In high-dimensional genomic data analysis, traditional linear regression techniques often struggle due to the presence of a large number of predictor variables relative to observations. Penalized regression methods such as LASSO, Ridge, and Elastic Net have emerged as effective solutions by imposing regularization, which helps in managing multicollinearity and enhancing prediction accuracy. This study applies these techniques to the Maize dataset to model the time to male flowering, selecting relevant genetic markers as predictors. Our findings suggest that Elastic Net is particularly effective for high-dimensional data with correlated variables, achieving a balance between prediction accuracy and variable selection. The results …

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Sir Francis Drake, Pirate Or Privateer, Sarah Green Jan 2025

Sir Francis Drake, Pirate Or Privateer, Sarah Green

High Impact Practices Student Showcase Fall 2025

This project explores the early life of Sir Francis Drake and the legacy he left. I will be focusing on how he operated as both a loyal servant to Queen Elizabeth I and a controversial figure in the eyes of Spain and Ireland. Using sources, I examine how his actions were framed as patriotic service, even though they often involved looting and destruction. Some key focuses that I go into are his failed voyages; one with John Hawkins and the Portuguese, and the other focus is the raid on Nombre de Dios. I also look at his role in Ireland …

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Agenda 2025-01, Staff Council Jan 2025

Agenda 2025-01, 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.

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Qualities Of Instructors Adult Second Language Learners Identify As Being Most Effective In Supporting Their Language Skills In Intensive English Programs, Nick Myrca Gauthier Jan 2025

Qualities Of Instructors Adult Second Language Learners Identify As Being Most Effective In Supporting Their Language Skills In Intensive English Programs, Nick Myrca Gauthier

Graduate Thesis and Dissertation post-2024

This qualitative research discusses the importance of the pedagogical and social qualities of instructors in the academic achievement of adult second language (L2) learners enrolled in intensive English programs (IEP). Its primary goal is to comprehend the role of social traits such as empathy, patience, approachability, supportiveness, and respectfulness and of pedagogical traits such as building trust, motivation, and minimizing language learning anxiety when instructing adult L2 learners. Within the framework of this study, a semistructured interview format was used to gather the lived experiences of seven participants who were either enrolled or had been enrolled in a university’s intensive …

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Handwritten Digit Recognition Using Machine Learning Classifiers, Md Ahiduzzaman Jan 2025

Handwritten Digit Recognition Using Machine Learning Classifiers, Md Ahiduzzaman

Data Science and Data Mining

This project explores and compares the performance of various machine learning classifiers for handwritten digit recognition using the MNIST dataset. The classifiers include Logistic Regression, k-Nearest Neighbors, and Convolutional Neural Networks. Each classifier is evaluated based on accuracy, precision, recall, F1-score, and confusion matrix analysis.

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Journeys Across Worlds, Carolina Guzman Jan 2025

Journeys Across Worlds, Carolina Guzman

Graduate Thesis and Dissertation post-2024

Journeys across Worlds is a collection of five short stories that transport readers into otherworldly landscapes. Each narrator embarks on a transformative journey, encountering adventure, wonder, and self-discovery. In “Through Borrowed Eyes,” a blind sorceress wields a powerful curse to see through the eyes of others, only to realize the cost of her magic may be too great. “A Gaze Across Dreams” follows a lonely Dreamweaver who, after an eternity of being unseen, is suddenly perceived by a lucid dreamer. The collection concludes with “Where the Skies Are Blue,” a tale of two sisters navigating a post-apocalyptic world, where the …

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The Unindexed Marginalia Of Historical American Cookery Books Digital Public History Project: Domestic Technical Communication Labor Contributions, Alessandra Zinicola Lopez Jan 2025

The Unindexed Marginalia Of Historical American Cookery Books Digital Public History Project: Domestic Technical Communication Labor Contributions, Alessandra Zinicola Lopez

Graduate Thesis and Dissertation post-2024

This dissertation includes a traditional written portion, and a non-traditional digital humanities public history online digital archive project created through Omeka which showcases examples of hand-written recipes found within commercial cookbooks, called marginalia. The understanding of modern technical communication is affected by the perceived history of the field and currently, that history is biased toward non-domestic pursuits. The project explores what collecting, digitizing, and archiving examples of historical hand-written marginalia found within commercially printed American receipt books indicate about the presence, participatory nature, value, and contributions of domestic technical communications and their user-authors in the 19th century. The examples collected …

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Multidimensional Approaches In Bug Detection For Parallel Programming And Text-To-Code Semantic Parsing, May Alsofyani Jan 2025

Multidimensional Approaches In Bug Detection For Parallel Programming And Text-To-Code Semantic Parsing, May Alsofyani

Graduate Thesis and Dissertation post-2024

This dissertation applies deep learning and large language models to two domains: parallel programming fault detection and text-to-code translation, aiming to enhance software reliability and natural language-driven code generation. Due to their unpredictable nature, concurrency bugs-particularly data race bugs— present significant challenges in fault detection for parallel programming. We investigate deep learning and LLM-based approaches for detecting data race bugs in OpenMP programs. Our proposed methods include a transformer encoder and GPT-4 through prompt engineering and fine-tuning. Experimental results demonstrate that the transformer encoder achieves competitive accuracy compared to LLMs, highlighting its effectiveness in understanding complex OpenMP directives. Expanding this …

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Improving Smart Home Access Control Mechanisms To Account For Community-Based Sharing Beyond The Home, Leena Alghamdi Jan 2025

Improving Smart Home Access Control Mechanisms To Account For Community-Based Sharing Beyond The Home, Leena Alghamdi

Graduate Thesis and Dissertation post-2024

The rapid proliferation of smart home devices has reshaped daily living, offering convenience and enhanced security. However, extending access to these devices beyond household boundaries introduces significant challenges, including balancing privacy, security, and usability. Through three studies, this dissertation investigates these challenges and proposes solutions to improve access control mechanisms for sharing smart home devices with external individuals. First, we conducted 26 co-design interviews with 50 smart home device owners to understand their perspectives on co-monitoring in emergencies with trusted external contacts. Participants emphasized benefits such as enhanced safety, reduced material loss, and peace of mind through swift responses and …

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