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Predicting Milk Quality with Machine Learning
No full textMilk is a critical component of diets around the world, offering essential nutrients such as protein, calcium, and vitamin B12. However, in many low-income and rural regions, milk quality is often compromised due to poor storage conditions, lack of pasteurization, and even intentional adulteration. Low-quality milk poses serious health risks, including bacterial infections, toxin exposure, and long-term organ damage. These challenges highlight the need for reliable, accessible methods to assess milk quality without relying on costly laboratory testing.
In this study, we propose a data-driven approach to predict milk quality using ordered logistic regression. The dataset used, sourced from Kaggle, includes 1,059 samples with both numerical (pH, temperature, color) and categorical (odor, taste, fat, turbidity) predictors. Our target variable is milk grade, categorized as low, medium, or high quality. We perform thorough exploratory data analysis to understand feature distributions and correlations, implement baseline and penalized (lasso) logistic regression models, and conduct diagnostics to check key assumptions such as proportional odds and linearity in the logit.
Our findings show that temperature, color, and odor are among the strongest predictors of milk grade, and that the proportional odds assumption does not hold—justifying our use of multinomial logistic regression instead. This work demonstrates the feasibility of building an interpretable, low-cost milk quality classifier using simple sensory-based features. Such a tool can help improve food safety, especially in underserved regions, by providing actionable insights into milk quality before it reaches consumers
Night Code: Decoding Nighttime Health Through Data
No full textSleep plays a crucial role in maintaining overall health, yet many adults struggle to achieve adequate rest due to lifestyle and health factors. In our project, we explore how variables such as stress levels, BMI, physical activity, blood pressure, and occupation impact sleep patterns using the Sleep Health and Lifestyle Dataset from Kaggle. Through statistical analysis, we examine these relationships, identify trends, and address challenges such as collinearity and interaction effects.
Our project reveals that stress levels negatively affect both sleep duration and quality, while physical activity shows a positive correlation with improved sleep outcomes. Additionally, BMI and blood pressure demonstrate moderate associations with sleep, emphasizing the role of cardiovascular health in sleep patterns. We also explore how different occupations contribute to variations in sleep habits. By applying transformations and interaction terms, we refine our model to enhance predictive accuracy.
This research is relevant to young adults as they transition into professional life, offering insights into the long-term impact of lifestyle choices on sleep health. Understanding these factors can help inform personal wellness strategies, workplace policies, and public health initiatives. By highlighting the significance of sleep, we hope to contribute to ongoing discussions on health and well-being, ultimately encouraging individuals to adopt habits that promote restful and restorative sleep.https://stars.library.ucf.edu/hip-2025spring/1006/thumbnail.jp
Stay ahead of your health: screen and educate
Full text linkThis service-learning project aims to promote the importance of preventative healthcare screenings, focusing on Ankle-Brachial Index (ABI) testing for detecting Peripheral Artery Disease (PAD) and Electrocardiograms (EKGs) to monitor heart health. Through this initiative, I have developed and distributed 50 educational brochures to inform patients about the significance of these screenings in identifying cardiovascular risks early and taking preventive measures to avoid more serious health complications.
The project has involved collaborating with Orlando Health Clinic LLC, to distribute these materials to various communities. The goal is to empower individuals with knowledge about their health, encourage proactive measures, and reduce the risk of cardiovascular diseases through early detection and lifestyle changes.https://stars.library.ucf.edu/hip-2025spring/1032/thumbnail.jp
Between a Rock and a Wet Place: Analyzing Mangrove Expansion on Intertidal Oyster Reefs
Full text linkAs global temperatures rise due to climate change, tropical mangroves have spread poleward and now impact many other ecosystems, including salt marshes and oyster reefs in central Florida. A recent study documented a 198% increase in mangrove numbers on intertidal reefs of the eastern oyster (Crassostrea virginica) since 1984 in the Indian River Lagoon (IRL). Our field research project had two goals. First, to collect 2025 data as part of a long-term study to understand the current dimensions, densities, and spatial distributions of red mangroves (Rhizophora mangle) on intertidal oyster reefs in Mosquito Lagoon (north IRL), and second, to compare our results to earlier surveys to determine the rate of change. Data was collected across 10 reefs in Mosquito Lagoon in the spring of 2025 and compared to the same reefs surveyed in spring 2023 and spring 2024. Previous results indicate a 6% annual increase in the number of mangroves per reef per square meter. As climate change continues to cause ecosystem shifts within the IRL, it is important to understand the relationships among foundational species so resource managers can better predict and protect the future of these vital ecosystems.https://stars.library.ucf.edu/hip-2025spring/1047/thumbnail.jp
AI Companionship Technologies: Technical Architecture and Human Impact in the Digital Age
Full text linkThis research investigates the multifaceted challenges and opportunities presented by AI companionship technologies, an emerging frontier in human-computer interaction. The project\u27s core purpose was to develop a comprehensive framework for responsible AI companionship systems, integrating insights from computer science, psychology, and ethics to address critical concerns related to user dependency, privacy, and the authenticity of AI interactions. Key activities included analyzing AI companionship as a complex adaptive system, revealing emergent properties and the need for interdisciplinary design approaches, and designing practical solutions to enhance digital resources at UCF Career Services. A key learning was the necessity of bridging technical AI development with ethical considerations and user-centered design to maximize positive impact and mitigate potential risks, a principle I apply across my work in AI, cybersecurity, and related fields.https://stars.library.ucf.edu/hip-2025spring/1061/thumbnail.jp
Enlightened Approaches: AI without the Dark Side
No full textWe\u27ve heard the hype, but can GenAI really foster student mastery- or will students use it only as a shortcut for cheating? In this session, we\u27ll enlighten and delight with responsible, fun, effective AI that supports authentic learning while addressing concerns such as bias and academic integrity. Through real-world examples and interactive demos, we\u27ll look at AI-powered tools that provide personalized feedback, build critical thinking, and promote meaningful engagement. We\u27ll also explore ethical strategies to integrate AI without dimming students\u27 understanding. Whether you\u27re skeptical or ready to glow, this session will shed light on AI\u27s potential and its pitfalls
AI in IB
No full textDiscover how Artificial Intelligence (AI) is transforming the Integrated Business (IB) program at UCF! This session will explore innovative ways faculty are incorporating AI tools like text and video generators, business simulations, and creative problem-solving modules to enhance student engagement and real-world application. Attendees will gain actionable insights into leveraging AI for curriculum design, classroom activities, and skill-building in business education. Join us for an engaging discussion on how AI is shaping the future of teaching and learning in higher education
Engage, Create, Teach: Interactive Lesson Planning with Chat GPT
No full textThis practical and interactive workshop will empower faculty to quickly create engaging, student-centered lessons aligned with learning outcomes, student assessment, and effective teaching strategies. By exploring Chat GPT\u27 s capabilities, participants will discover how to save time and put the fun back in student-centered lesson planning. With plug-and-play prompts and customizable scripts, faculty will leave with tangible tools they can immediately apply to their own courses
Transformative Assignments: The Answer is in the Room
No full textEducators crowdsourcing ideas in the era of AI has led to exciting curriculum innovations. Join us for an interactive session where we consider frameworks for revising assignments. Bring an idea you would like to explore or an existing lesson you would like to transform, and prepare to connect with other educators to collaborate on curriculum updating. Examples which inspired you during this year’s conference are very welcome! We will demonstrate Turnitin’s new student writing space, Clarity, and we are most interested in creating discussion space for your ideas because we know the answer is in the room
More than Meets the Chat: Transformative Math with AI-Assisted Support
No full textLet\u27s get real: Students will use artificial intelligence, specifically AI-chatbots, when learning online. They will especially use them for discussion forums, a ubiquitous staple in online learning yet with a long-standing challenge of low student participation. In math education, the dreaded word-problem notoriously triggers anxiety for students and yet, is routinely seen as the discussion prompt. So, let\u27s get modern! Employing the use of AI-chatbots can super-charge motivation, increase the cognitive presence and improve the learning potential of asynchronous forums and other areas of study. Join for a strategy-rich, interactive session engaging in AI-assisted discussion and course activity