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A Page from Our Archives: Understanding Queer History in Georgia at Kennesaw State
No full textIn 1993, the play “Lips Together, Teeth Apart” was performed in Cobb County’s Marietta Theatre in the Square. The play contained themes of homosexuality, prejudice, and the fear of the HIV virus. The play became highly contentious, and it became the center of a countywide debate on whether the arts should continue to be funded. Eventually, on August 10, 1993, the Board of Commissioners decided to cut all funding for the arts in Cobb County. Our research aims to make a cohesive timeline leading to the eventual defunding of the arts, while also trying to find key people within this major debate. By finding these important people and understanding how each event transpired we can consider how censorship of the arts happens and how it effects local art communities and the LGBT community. With this information we can have a stronger awareness of the censorship of art today. The research strategies we have used are an investigative approach and thorough analysis. All data has been collected through archival newspaper clippings, broadcast reports, and the theatre’s archives. Our goal as undergraduates is to strengthen our understanding of research projects, while learning more about the history of the County we study in. The research provides us with new context over the censorship of art and will allow us to better combat this suppression of artistic freedoms
FutureFit Guidance System
Get PDFThe fields of education and career counselling have been completely transformed by the quick development of artificial intelligence (AI) technologies. The objective of this project is to develop an AI-powered career advising system that leverages cutting-edge technology to provide personalized job recommendations aligned with the user\u27s skills, interests, and career goals. The system provides a user-friendly and interactive platform for career exploration by using Natural Language Processing (NLP) models with web application developed with Flask (backend) and React (frontend).
The main goal of this project is to overcome the shortcomings of conventional career guidance approaches, which frequently do not offer personalized solutions and do not cater to individual preferences, abilities, and goals. By utilizing AI algorithms, natural language processing techniques, and machine learning models, our application seeks to deliver precise assessments of interests, match skills effectively, and create customized educational pathways. The project involves designing, developing, and implementing AI-powered features, including interest evaluation, skill analysis, and personalized recommendations. The approach includes gathering data via user contributions, preparing the data for analysis, and developing a comprehensive system architecture that consists of frontend interfaces, backend servers, and database management
Design and Development of Peptide Therapeutics Targeting the Alpha-Synuclein Fibrils in Parkinson Disease
No full textParkinson’s Disease (PD) has the highest rate of increased death and disability of any neurological disorder, as well as being the second most prevalent neurological degenerative disease in the world according to the WHO. The symptoms are derived from the build-up of Lewy bodies (LB) leading to neuron degeneration, affecting both motor functions and memory recollection. Alpha-Synuclein protein is believed to be one of the sources for oligomerization and fibril formation. The aim of this research is to design and develop peptide analogs targeting alpha-synuclein to prevent oligomerization and fibril formation. Various analogs were computationally designed from a potent peptide to improve the crossing of blood-brain barrier and oral bioavailability. Molecular docking was employed to determine the binding affinity and interaction with Alpha-Synuclein. The peptides had docking scores ranging from -146.79 to -130.46. Analog 8 (-146.79) containing two phenylalanine in a helical turn showed the highest binding affinity and interaction at the docking sites. Based on the modelling results, this peptide was synthesized using the solid phase synthesis protocol using Liberty Blue peptide synthesizer. In this protocol, a high swelling rink-amide resin with a loading capacity of .6 mmol/g and 100-200 mesh size was used. After the peptide synthesis, the peptide-resin complexes were cleaved with a cocktail containing high amount of trifluoracetic acid. The cleaved peptides were filtered and precipitated by adding cold ether. Then, the precipitate dissolved with acetic acid and freeze-dried overnight to form peptide powders. The synthesis of the peptide was confirmed by mass spectrometry. Three intense peaks were detected at m/z 406.23, 608.83, and 1216.66 which correspond to [M+3H]3+, [M+2H]2+, and [M+H]1+ charge states, respectively. The experimental mass is precisely agreed with the theoretical mass of the peptide. In future, biological assays of this and other favorable peptides will be carried out
Human-AI Collaboration in Research: A Case Study on RAG-Driven Information Retrieval from Scientific Papers
No full textEvery day AI is becoming increasingly important to more and more industries and applications. AI usage is still relatively new to most fields, and many are unfamiliar with how to achieve the best results, which often require heavy interaction and involvement from users. This human and AI teaming while usually producing the best results is still an underdeveloped point of research which has not been explored enough. This research aims to amend this by exploring papers about interactive AI through the development and usage of a tool to collect and study. The tool is a web app that allows for the search, retrieval, and management of papers to then be explored or “talked to” through an LLM. The LLM portion of the tool will allow for the user to select one or more papers to allow for the user to explore the selected papers in creative ways like comparing and contrasting papers, connecting topics, or just deep diving into a paper. Through our research, we’ve developed an innovative, easy-to-use prototype web app that allows users to dynamically engage with scientific papers. This tool has facilitated further research on human-AI collaboration and serves as an example of how humans and AI can collaborate
Is That Cheating? Students’ and Instructors’ Perceptions of Groupchats
No full textAcademic misconduct has long been a concern in academia (McCabe et al., 2012) and appeared to worsen during COVID (Newton et al., 2024). Groupchat applications like GroupMe allow instant communication among many students, which may facilitate cheating. The extent to which students recognize cheating via groupchats as such is unclear. To address this gap, we compared students’ and instructors’ perceptions of what constituted cheating in GroupMe chats. Undergraduate students (n = 312) and instructors (n = 63) at the same university were randomly assigned to read one of four groupchats with one control (meeting up to study) and three cheating conditions (sharing exam questions, sharing exam answers, and taking the exam together). All participants reported the extent to which they perceived the groupchat as including academic violations. Additionally, students indicated how they would respond to the groupchat, and instructors indicated how they expected students would respond (cheating-supportive or cheating-resistant). We found that instructors perceived greater academic violations across the conditions in comparison to students, apart from the control condition (meeting to study). Participants rated meeting up to study as low in perceived violations and the three cheating conditions as being similarly high in perceived violations. Overall, instructors perceived greater violations across conditions than students did. Additionally, instructors tended to believe students were more likely to engage in cheating-supportive responses than students reported, and less likely to engage in cheating-resistant responses than students reported. Because perceptions of cheating predict actual cheating, some students may benefit from guidance regarding inappropriate use of GroupMe. Additionally, given that inaccurate beliefs, particularly those held by multiple individuals, can impact both subsequent perceptions and reality (Madon et al., 2011), making instructors aware of their potential biases may also be useful
A Kennel Built From the Inside: Dog Act & the Sacrifice of Agency
No full textSpring 2025, KSU’s Department of Theatre & Performance Studies produces Dog Act by Liz Duffy Adams, a play about two post-apocalyptic vaudevillians named Zetta Stone and Dog. The latter is a young man who has willingly demoted his species from human to dog. On the surface, their transformation is humorous, but its reasoning is truly, deeply sad. When Dog was a young boy, he made an unintentional decision that led to the genocide of his people, and his grief and atonement manifested with him swallowing those feelings and becoming a dog, or in other words, less than human. The artist-scholar presentation focuses on my background research and strategies as the actor assuming the role of Dog in KSU’s production. In particular, I focus on the concept and embodiment of agency, inspired by György Gergely’s scholarship. If agency is a person’s capability to commit an action or make a decision, agency is absent for Dog-it is not taken by force but willingly given away. I use an analysis of Dog Act, along with a performed selection from the play, to demonstrate how individuals in modern society give up their own agency to protect their own way of life, remove the threat of societal morals, and avoid existentialist dread in an uncertain world
Unsupervised Music Genre Clustering Using Contrastive Learning
Get PDFMusic genre classification is a challenging task, especially in the absence of labeled data. In this project, we leverage unsupervised contrastive learning to cluster music tracks based on their underlying audio features. By applying SimCLR-based feature extraction on the GTZAN dataset, we demonstrate that contrastive learning can capture meaningful representations of different genres. Our approach does not require labeled training data and provides genre similarity clustering based on learned embeddings. Results indicate that the model effectively groups tracks into clusters that align well with traditional genre labels, suggesting contrastive learning as a powerful tool for unsupervised audio analysis
Team Safe Skies: Project Talon Interceptor
Get PDFThis report aims to lay out our design process for the missile interceptor aircraft. Our Talon Interceptor is an inexpensive, scaled-down, autonomous F-16 for mass production. The aircraft can ascend quickly for mission requirements while avoiding detection with its internal weapons bay. Multiple decisions have been made to ensure the initial and maintenance costs are reasonable without compromising the missions. TOPSIS reviews have been used to measure significant components unbiasedly and objectively. Our aircraft meets all the AIAA requirements while coming in under budget
SYSTEMS APPROACH IN PHYSICAL GEOGRAPHY
Get PDFThe concept of a system is not new and the emergence of systems analysis in academia has caused controversy over the significance of this approach as a viable means of scientific analysis. Some geography scholars feel that the use of systems analysis would definitely put us on the research frontier,1 while others view the term systems as nothing more than jargon. Nevertheless, the simplest definition for system is a set of interrelated elements. The demand for the systems approach arose because scholars in a number of disciplines recognized in their own research that individual components of a problem or an entity almost never operate in isolation. Interrelationships were the rule rather than the exception in real problem solving situations