7424 research outputs found
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Puppy
Get PDFThroughout this submission, I will discuss the overall process of creating my short thesis film, Puppy. An overall summary of my production approach and a detailed account of the specifics of how each production element occurred will also be provided along with visuals from the set. I will also discuss my education and experiences from my time at the University of New Orleans
Impacts of Risk Perception on Elderly Vulnerability: An Exploration of Effects on Disaster Preparedness in Assisted Living Facilities
Get PDFDisasters are increasing in intensity and frequency. With this expectation, it is important for communities to be proactive in disaster preparedness to ensure the safety of their citizens. Vulnerable populations need special consideration in disaster planning. The elderly are one of these vulnerable groups. By 2025 one-quarter of the U.S. population will fall into the 65 or older age category. Age itself does not make a person vulnerable. It is physical and cognitive change that often accompany aging which can make a person vulnerable. The importance of elderly vulnerability and risk perception cannot be overlooked. The casualty data alone can demonstrate the severity of the issue, and with an increasing elderly population, the issue will only grow. Perception plays a key role in how a person prepares for risk and thus affects level of vulnerability. Understanding perception of risk is a crucial part of disaster planning. Many factors contribute to perception especially in vulnerable populations. Understanding the factors allows emergency management professionals to address the issues they can and better accommodate those they cannot correct. The purpose of this study is to explore risk perception in the elderly and how it might affect their disaster preparedness. Focus groups were conducted at an assisted living facility. While this study was in progress Hurricane Ida made landfall in Louisiana in August 2021. This provided a unique opportunity to conduct before and after research to examine the difference in risk and disaster perceptions in the elderly. Focus groups were reconvened at the same assisted living facility for comparison. In addition, elder care and disaster management experts were interviewed regarding existing elder-focused disaster preparedness plans and the challenges of keeping the elderly safe. Results indicate changes in risk perception pre- and post-storm, as well as differences in perceptions between the elderly and elder care and disaster management experts. Additionally, Hurricane Ida highlighted some failings in communications and senior housing regulations. These findings indicate that risk perception play a role in vulnerability, and, as such, a greater consideration needs to be given to the elderly’s perception of risk in disaster preparedness
Self-train Semi-supervised Contour Detection for Automated Monitoring of Surface Water Across the Globe
Get PDFSurface water is a critical resource that requires constant monitoring due to drastic impacts of human use, climate change, and severe weather phenomena. Existing monitoring techniques are limited and vary in their efficacy. It is proposed, here, that contour detection in the visible range is better for monitoring dynamic and long-term changes to surface water bodies. For that purpose, a semi-automated method for collecting and labeling water contours from Landsat-8 and Sentinel-2 images is presented. Due to the need for human inspection, the method has thus far generated 14K labeled images from more than 200,000 images. Given the cost of data labeling, a deep semi-supervised self-learning system is proposed, which performs learning in two stages, known as the teacher-student model. The teacher is trained on the accurate human-labeled data, then used to pseudo-label the remaining unlabeled data. The student is trained on both human-labeled and machine pseudo-labeled data. A uniquely designed multi-scale UNet classifier that uses fewer parameters and is developed and shown to be more accurate than other state-of-the-art (SOTA) classifiers for both teacher and student. Random augmentations are used to ”noise” the student model and improve its generalization, and normalization schemes are used to blend the human-labeled loss with the machine-labeled loss. Without the self-training, the multi-scale UNet classifier has 69.2% F-score over the SOTA systems, that improves to 73.58% with self-training
Disrupting Energy: The Effects of Oil Extraction on Early Gulf Coast Oilfield Unionization, 1905-1920
Get PDFIts Time for Representation, Diversity, Equity, and Justice at Theater UNO
Get PDFThis document will provide evidence of how white supremacy culture traumatizes Black artists by lowering esteem and devaluing their work. The Black experience in America is traumatic enough, the theater should be a place that allows African Americans of all different educational backgrounds, classes, beliefs, etc. to receive a cathartic experience, abuse free. This case study involves directing Black content, Katori Hall’s “Hoodoo Love”, at a predominantly white institution in hopes of uplifting African Americans and enlightening the rest
Fluctuating Parasite Prevalence Is Not Linked to Patterns of MHC Class II-ß Diversity in an Island Endemic Reptile
Get PDFFew studies have explored the evolutionary mechanisms that maintain adaptive immunogenetic diversity in nature. We took advantage of museum samples to test for evidence of parasite-mediated fluctuating selection at MHC Class II-ß loci in an endemic island reptile. The Saban anole Anolis sabanus is commonly infected with three species of malaria (Plasmodium). Proportions of each parasite species detected in anole blood samples fluctuated over space and time, suggesting competitive interactions between parasites or differences in vector ecology. Our analyses of parasite prevalence and MHC Class II-ß allelic variation found that malaria infection was not associated with patterns of host immunogenetic diversity. We found that infection was contingent on sex, with males being more likely to test positive for malaria. These results indicate that malaria parasites do not impose significant selective pressures on A. sabanus or that genetic drift in this island population overwhelms the effects of parasite-mediated selection
Wilting Magnolias
Get PDFWhile each story is innately different, they all aim to evaluate the terse topic of relationships. These characters are sometimes fierce, often hilarious, and always honest. From overcoming abuse in a family to a commentary on mental health in romantic partnerships, and even a glimpse into the supernatural, these stories offer a realistic gaze into fiction
Levee Seepage Identification from Aerial Images using Machine Learning
Get PDFLevees protect from natural disasters that can threaten human health, infrastructure, and biological systems by protecting low-lying lands near or below sea level from flooding. However, seepage in those levees undermines their structural integrity, leading to failures. Today the United States has approximately over a hundred thousand miles of levee, many of which are reaching or have surpassed their initial design life. Given the concern, there is a need to develop reliable, rapid, and non-intrusive levee monitoring systems to detect the presence of seepage. This study explores the use of Deep Convolutional Neural Network (DCNN) integrated with Discrete Cosine Transform (DCT) and Thepade’s Sorted Block Truncation Coding (TSBTC) to detect seepage in aerial images. It also compares existing models that achieved good results for the classification of aerial images using decisions trees, Support Vector Machines, and k-means clustering. Our model detected seepage with great accuracy, with fewer resources, and faster speed when compared
Teaching Activism: The Feminist Pedagogical Possibilities of Why We Fly
Get PDFYoung adult fiction possesses the pedagogical power to educate young readers about activism, and more recently, authors of the genre have answered the call from young aspiring activists to deliver narratives that are reflective of and relevant to their own lives and communities. Published in October of 2021, the novel Why We Fly illustrates the complexities of participating in social justice activism while also providing entertaining and inspiring characters. In honor of Colin Kaepernick, authors Kimberly Jones and Gilly Segal craft the fictional hero Cody Knight who encourages the text’s young protagonists to look at the world around them to identify injustice. Using critical feminist theory in an analysis of the text, I highlight the ways in which the novel guides readers to understand movement building and community outreach while also requiring them to reflect on their complicity in systems of oppression. From a feminist perspective, the young adult novel Why We Fly is a narrative that would enable teachers to present students with the opportunity to analyze systems of oppression and power structures, develop a critical consciousness, and question ways we privilege knowledge and ways of knowing
ncRNA-protein Interaction Prediction using Language-based Features
Get PDFNoncoding RNAs (ncRNAs) play a significant role in several fundamental biological processes by binding to RNA-binding proteins (RBPs); hence, it is necessary to study ncRNA-protein interaction (RPI). Several classic and deep-learning machine learning models have been pro-posed to predict RPI. These models first need to collect features of RNA and protein, such as physicochemical properties, secondary and tertiary structure, et cetera, before feeding them into the model. More recently, after the advancement of high throughput sequenc-ing and the improvement in Natural Language Processing (NLP), transformer models like BERT-RBP and Evolutionary Scaling Model (ESM) can be trained to automatically extract feature representations, containing both low and high-level information, from RNA and pro-tein sequences directly. This method could make manual feature collection optional. Hence, in this study, we compare the performance of such language-based features against manually created features to predict the interaction probability between a protein and an RNA