University of Central Florida
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Preserving Nature, Building Community
Get PDFThe scope of my project included volunteering at the Oakland Nature Preserve and restoring the park grounds after the effects of hurricanes Helene and Milton. My key activities were clearing downed trees, clearing trails of leaves, and marking them with logs so that the preserve could continue to be a place for people to enjoy nature. In interacting with the staff and other volunteers, I learned about the importance of community in supporting important causes. Additionally, it made me more inspired to reduce my carbon footprint and be more sustainable in my efforts to combat climate change, as well as raising awareness to inspire others to enact change as well.
You can view the video presentation at https://www.canva.com/design/DAGj49FKSEo/h4Xzwva70YNWln8n4UPr0A/watch?utm_content=DAGj49FKSEo&utm_campaign=designshare&utm_medium=link2&utm_source=uniquelinks&utlId=h0dcb7c34a0https://stars.library.ucf.edu/hip-2025spring/1020/thumbnail.jp
Introduction to Prompt Engineering
Get PDFThis presentation explores the fundamentals of effective prompt engineering, which involves well-crafted instructions for AI models to generate meaningful responses. Effective prompts can be written using frameworks like CLEAR and TRACI. The CLEAR Framework focuses on conciseness, logical structure, explicitness, adaptability, and reflection, while TRACI emphasizes task, role, audience, creation, and intent.
Additionally, the presentation addresses ethical considerations and best practices in prompt engineering, including academic integrity, attribution and transparency, and the importance of evaluation and assessment. By mastering these techniques, users can optimize their interactions with AI models, ensuring accuracy, relevancy, and minimizing bias
Enemies Within the Gates: Contending with Internal Censorship Challenges
Get PDFThis 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\u27s commitment to intellectual freedom.
Phillips contextualizes these events in a broader framework, highlighting the importance of proactive collection development policies, faculty outreach, and open internal communication. By emphasizing the library’s role in representing marginalized communities—especially in geographically and culturally isolated areas—the chapter advocates for vigilance, allyship, and strategic advocacy to protect diverse collections. Ultimately, the piece serves as both a cautionary tale and a guide for librarians seeking to uphold the principles of inclusion and access in their institutions
Florida Frontiers Radio Program #588
No full textSEGMENTS | Opera Orlando\u27s \u27Treemonisha\u27 | Mythic Weedon Island | Florida International Universit
Handwritten Digit Recognition using Machine Learning
Get PDFHandwritten Digit Recognition (HDR) remains a fundamental benchmark in pattern recognition and machine learning due to its practical applications and inherent classification challenges posed by diverse handwriting styles. This study investigates and compares two classical statistical classifiers—Gaussian Naive Bayes (GNB) and Linear Discriminant Analysis (LDA)—to recognize the digits from the MNIST dataset. Both models assume underlying normality in feature distributions and offer computational efficiency, making them suitable for high-dimensional input such as image pixels. Using 60,000 training and 10,000 test samples, we evaluate model performance through accuracy, precision, recall, F1 score, and confusion matrices. The results reveal that while GNB achieves moderate accuracy (55.58\%), LDA significantly outperforms it with an accuracy of 87.30\%, demonstrating superior capability in distinguishing visually similar digits. Our analysis further highlights the limitations of GNB’s independence assumption and underscores LDA’s strength in capturing shared variance across classes. These findings reinforce the effectiveness of LDA as a robust baseline for HDR tasks, especially when interpretability and computational simplicity are desired
Data Science Job Salary Prediction Using Linear Regression
Get PDFIn the evolving landscape of data science, accurate salary prediction plays a crucial role in shaping career expectations, informing educational strategies, and guiding organizational hiring decisions. This study investigates the key factors influencing entry-level data science salaries in the United States by applying a multiple linear regression model to a recent dataset spanning from 2020 to 2024. Through data preprocessing, transformation, and diagnostic evaluation, we identify how job roles, experience levels, employment types, work arrangements, residency status, and company size impact compensation. Despite challenges such as outliers, heteroscedasticity, and non-normal residuals, model refinements like the Box-Cox transformation and variable selection enhance predictive performance. The final model, while modest in explanatory power, offers actionable insights into salary determinants and lays the groundwork for future predictive modeling improvements in the domain
Self-Objectification as a Form of Empowerment and its Relationship to Identity, Self-Perception, and Self-Efficacy
No full textThis study aimed to investigate the interactions between self-objectifying tendencies in college students, their beliefs in how their sexuality/sexual agency can be used to their advantage, and their self-perception as it relates to identity, self-esteem, and self-efficacy beliefs. College students (N = 274) took an anonymous online self-report survey battery in exchange for course credit. The presence of what is termed “sex is power” beliefs were found to be a significant moderator between the effects of self-objectifying practices and self-perception. Participants with sex-is-power beliefs were able to use self-surveying behaviors without igniting identity distress as one might do in the absence of such beliefs. Using the information found in this study, the goal is to help understand how growing sex-positivity can mitigate the effects of historically detrimental objectification practices
Patient Perceptions of Cognitive Assessments Among Older Adult Minority Populations: An Integrative Review
No full textThe acceptance of cognitive assessments by older minority adults is minimally acknowledged, contributing to healthcare disparities in minority mental health. This limited recognition may play a role in the gap in the adoption and use of these assessments. Cognitive screening tools are vital in detecting early mental deterioration in older adult care. However, cultural, linguistic, and educational differences influence perceptions of these assessments, impacting their effectiveness and utilization. This integrative review aims to understand perceptions of elderly minority populations (aged 65 and older) toward completing cognitive assessment tools.
An integrative review was conducted following Joanna Briggs Institute (JBI) guidelines. A systematic search of peer-reviewed literature published between 2014 and 2025 was performed across three academic databases. Search terms included any minority population (Hispanic, Black, African American, Asian, Pacific Islander) above 65 years of age. Inclusion criteria focused on studies examining perceptions, attitudes, and experiences of elderly minority populations toward cognitive assessments. Two independent reviewers screened a total of 370 abstracts across three databases. A total of 215 article abstracts were read for inclusion, reduced to 11 articles for full review. After a full-text review was conducted, 4 articles were removed due to not meeting the established criteria. The extracted data highlighted key themes such as the practicality, accessibility, and cultural relevance of cognitive assessments.
The usability of cognitive tools was emphasized across different cultural backgrounds; however, seldom were patients asked about perceptions regarding completing the assessments, resulting in lower performance. Findings supported a variation in the adoption and perceived effectiveness of different cognitive tools. This was influenced by educational background, language proficiency, and cultural norms. Adopting patient-centered approaches and using culturally appropriate instruments may improve early cognitive impairment detection and healthcare outcomes for elderly minority populations.
This study emphasizes the importance of tailoring cognitive assessments to patient preferences, enhancing clinical effectiveness and patient engagement in dementia care. The limited involvement of patients in developing these assessments highlights the need for more inclusive research approaches that incorporate culturally appropriate tools. Future research should explore diverse populations and direct patient involvement in cognitive assessment development