JBC Commons (New College of Florida)
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Bathroom 2
No full textA student is sitting on the toilet with a Newspaper on their lap. They appear to be in a bathroom in a Pei dorm room.https://digitalcommons.ncf.edu/ncsa-p/1002/thumbnail.jp
Behind Pei 2
No full textThis image shows some construction project that was taking place behind the Pei dorms and next to the tennis courts. It seems to be something to do with piping or plumbing.https://digitalcommons.ncf.edu/ncsa-p/1004/thumbnail.jp
Student Catalog 1964-1965
No full textTwenty page student catalog featuring photographs of students who were entering their first year at New College
Facebook (1984)
No full textThirteen page student catalog (known as the Facebook) featuring photographs of students who were entering their first year at New College. Some text of this student catalog is not legible due to the phsyical construction of the publication
New College 2008-2009
No full textSixteen student catalog (known as the Facebook) featuring photographs of students who were entering their first year at New College
Facebook 2005-2006
No full textTwenty four page student catalog (known as the Facebook) featuring photographs of students who were entering their first year at New College
MICROPLASTIC INGESTION IN PIPEFISH IN THE SARASOTA BAY
No full textMicroplastics are ubiquitous in the environment today. Their spread has been an uncontrollable side effect of the vast amounts of plastic waste leaked into the environment annually. Microplastics can have devastating impacts on ecosystems and the organisms that inhabit them. Marine life can ingest these microplastics either intentionally through the accidental misidentification of a prey item or passively through their presence in or around prey items. However, there have been no studies on microplastics in syngnathids, a focal species, within Florida waters. In this thesis I investigate the passive ingestion of microplastics in Syngnathus scovelli from the Sarasota Bay and the biological and abiological factors that may affect the size and quantity of those microplastics
SimpliSite: Simplifying Website Management and Bookings for Small Businesses
No full textSmall businesses often face barriers when trying to establish an effective online presence. Many business owners lack the time, technical knowledge, or resources to manage a professional website, and existing platforms like Wix or Shopify often overwhelm them with features they don’t need, or hide essential tools behind expensive plans. SimpliSite was created to simplify the website-building experience for service-based businesses such as salons and barber shops. This project focuses on delivering a platform that not only helps users design and manage their websites without needing to code, but also supports essential business operations such as appointment scheduling, staff assignments, and real-time content editing. When users begin building their site with SimpliSite, they’re greeted with a simple, guided interface and a set of pre-designed page templates covering everything from services and bookings to galleries and contact information. Content is edited directly on the page, and updates are reflected immediately, reducing the need for navigating complex settings or configurations. Customers can book appointments with specific staff members through a streamlined scheduling system that’s built into the site, while business owners can manage availability and view analytics through a unified dashboard. The platform focuses not only on ease of use but also on performance and discoverability, ensuring that websites load quickly and are optimized for search engines. Built using modern web technologies including Preact, Deno Fresh, MySQL, and Firebase, SimpliSite ensures reliable performance and scalability. Ultimately, SimpliSite aims to provide small businesses with a practical, user-friendly alternative to traditional website builders, bridging the gap between functionality and simplicity by addressing the specific needs of service-based industries
USING MACHINE LEARNING AND AERIAL IMAGERY TO DETECT MACROALGAE
No full textCoastal ecosystems are essential for biodiversity and ecological services; they are increasingly under threat from human activity. Within these systems, macroalgae (submerged aquatic vegetation, or SAV) play a vital role. For that reason, assessing the condition and presence of SAV is important for understanding coastal ecosystem health. Traditional field surveys for SAV are limited in spatial and temporal resolution. In contrast, high-resolution Aerial (AUV) imagery, when combined with Convolutional neural networks, provides a great opportunity for analyzing this critical habitat at the necessary scales. Neural networks are computer models of interconnected nodes that learn to map inputs to outputs by adjusting connection weights during training. However, the challenge of analyzing the resulting large datasets presents a bottleneck for many potential coastal applications. A dataset was compiled from Aerial imagery captured over Lido Key, Sarasota, Florida. Images were preprocessed into standardized patches and manually labeled and sorted into three categories: SAV, Sand/Water, and Terrestrial Vegetation . The performance of two neural network architectures was comparatively evaluated for this 3-class classification task: a baseline Multi-Layer Perceptron (MLP) and a Convolutional Neural Network (CNN) inspired by the LeNet-5 architecture with modern enhancements. The results showed that the MLP was severely overfitting during training and had poor generalization to the unseen test set (Accuracy ≈ 0.582). This meant that the MLP was not suitable for reliable SAV detection. The opposite was true for the modified LeNet-5 CNN; it performed effectively on the test set (Accuracy ≈ 0.997). For the target class, \u27SAV,\u27 the CNN had perfect precision (1.00) and near-perfect recall (0.99). This means that the modified LeNet-5 CNN with transfer learning was extremely good at accurately identifying and detecting patches containing SAV with few false positives and negligible false negatives. The findings underscore the ability of convolutional neural networks (CNNs) to better utilize the spatial nature of image data than multilayer perceptrons (MLPs) for this ecological task. The CNN developed here is a presence detection filter that can significantly reduce the effort needed to screen the numerous standard Aerial images for the presence of coastal macroalgae. This automated step can direct the relevant expert’s attention to the right places and make the workflow much more efficient and scalable
SEXUAL TRAUMA AND SELF-TRANSCENDENCE: PERCEPTIONS OF THE SELF AND TRAUMA HEALING AFTER SEXUAL ASSAULT
No full textPrevious research has explored connections between PTSD and social support, specifically for sexual assault (SA) related PTSD, as well as connections between social support and self-transcendence. Self-transcendence has also been found to be beneficial for overall well-being. The current study assesses the relationship between self-transcendence and Post-Traumatic Stress Symptoms, or PTSS. This was done through an online survey sent out to social media groups and forums. The survey consisted of a PTSS scale, a self-transcendence scale, items on mitigating/aggravating factors of their SA(s), as well items on spirituality/religiosity and other demographic items. The results found no correlations between self-transcendence and PTSS. Significant correlations were found for recurrence and PTSS, number of years since first SA with years since most recent SA, spirituality and self-transcendence, spirituality and PTSS, spirituality and PTSD diagnosis threshold, and religiosity and spirituality (N = 78). The correlation approached significance for self-transcendence and dissociation, which was a specific aspect of PTSS/D that was hypothesized to have a relationship. Results suggest mixed possibilities on the potential benefits of self-transcendence as well as possible negative implications, which calls for continued research on self-transcendence and PTSS/D