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Full-Text Articles in Physical Sciences and Mathematics

Gpr-103 Personalized Pedagogy Through A Llm-Based Recommender System, Mourya Teja Kunuku, Bharath Y Yadla Apr 2024

Gpr-103 Personalized Pedagogy Through A Llm-Based Recommender System, Mourya Teja Kunuku, Bharath Y Yadla

C-Day Computing Showcase

The educational domain is undergoing transformation due to the incorporation of Artificial Intelligence (AI), Large Language Models (LLMs), and generative AI technologies, raising the need for educators to integrate cutting-edge technological advancements and methodologies into their teaching approaches. Pedagogical Design Patterns (PDPs) have become prominent for their role in sharing effective educational practices and narrowing the divide between academic research and actual teaching methods. Despite their potential, the lack of widely accessible resources and the scattered nature of publishing outlets pose significant barriers to the broad application of PDPS. To address this issue, we propose the application of large language …

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Gc-104 Edai – Ai Enabled Teaching Robot For Informal Learning, Jennifer Bower, Shane Williams, Justice Fuller Apr 2024

Gc-104 Edai – Ai Enabled Teaching Robot For Informal Learning, Jennifer Bower, Shane Williams, Justice Fuller

C-Day Computing Showcase

We began our project by researching various popular, open-source AI tools that are available today. After we chose to focus on ChatGPT as our AI tool, we decided on cybersecurity as our subject matter. Next, we researched traditional cybersecurity training methods used by companies to train their employees on cybersecurity issues. Our project focused on determining whether or not open-source AI tools such as ChatGPT could replace traditional cybersecurity training tools and methods for companies.

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Gc-8 Informal Learning Artificial Intelligence Large Language Model Fine-Tuning On The Select Topic Of Entrepreneurship, Kristen Gabby, Melina Castellon, Jyothi Sampathirao Apr 2024

Gc-8 Informal Learning Artificial Intelligence Large Language Model Fine-Tuning On The Select Topic Of Entrepreneurship, Kristen Gabby, Melina Castellon, Jyothi Sampathirao

C-Day Computing Showcase

This project explored the usage and development of open-source Large Language Model (LLM) Artificial Intelligence (AI) with a chat feature, specifically to fine-tune on the topic of entrepreneurship. This project sought to showcase the adaptability of open-source LLMs and highlight challenges and solutions faced in leveraging those LLMs. The primary goal was to show proof of concept that training a LLM on the selected subject can create a specialized AI chat for informal learning.

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Gc-101 Learning Resource Finder: A Web Scraping Tool For Educational Materials, Ashrith Kumar Devara Apr 2024

Gc-101 Learning Resource Finder: A Web Scraping Tool For Educational Materials, Ashrith Kumar Devara

C-Day Computing Showcase

The Learning Resource Finder is a pioneering tool designed to alleviate the challenges associated with navigating the vast landscape of online educational content. Leveraging sophisticated web scraping techniques and API integrations, this tool empowers users to efficiently discover relevant learning materials tailored to their specific needs. Through a user-friendly Flask-based web interface, users initiate search queries, which are then encoded and utilized to fetch pertinent URLs from leading educational platforms such as JavaTPoint, W3Schools, Coursera, Udemy, and GeeksforGeeks, as well as Google search results. The core of the web scraping process lies in the meticulous extraction of URLs from HTML …

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Gc-17 Crm For Ccse Department Of Ksu, Venkatesh Alla, Keerthi Nannapaneni, Vinay Kumar Rapolu Apr 2024

Gc-17 Crm For Ccse Department Of Ksu, Venkatesh Alla, Keerthi Nannapaneni, Vinay Kumar Rapolu

C-Day Computing Showcase

This project outlines the development of a bespoke Customer Relationship Management (CRM) system specifically designed for the College of Computer and Software Engineering (CCSE). The initiative aims to centralize customer information into a unified repository, thereby enhancing the confidentiality, management, and optimization of data and communication processes within the college. The CRM system will integrate features for detailed profiles, communication optimization, complex workflow management, document repository, and data migration to ensure efficiency and data integrity. It will also facilitate seamless interaction with Microsoft 365 and Outlook, supporting the college's operational needs and maintaining its commitment to excellence in education and …

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Gc-22 Fabric Moderation Ticketing Mod For Minecraft, John Lambert, Kathy Nguyen, Hayden B Scarbrough, Dasiane Taplin Apr 2024

Gc-22 Fabric Moderation Ticketing Mod For Minecraft, John Lambert, Kathy Nguyen, Hayden B Scarbrough, Dasiane Taplin

C-Day Computing Showcase

This project targets enhancing the KSU Esports program’s Minecraft server by implementing an in-game ticketing system. The system will enable players to report any instances of in-game incidents/issues seamlessly within the game environment. The integration with the KSU Minecraft Discord server will facilitate efficient communication between players and administrators. With a user-friendly interface and optimized resource usage, the system aims to streamline moderation processes.

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Gmr-29 Identification Of Ai-Generated Images, Chris Foster, Joshua Brock, Harini Kottala, Srilatha Korrapati Apr 2024

Gmr-29 Identification Of Ai-Generated Images, Chris Foster, Joshua Brock, Harini Kottala, Srilatha Korrapati

C-Day Computing Showcase

With the quick rise of Artificial Intelligence (AI), generative AI models have greatly increased the volume and velocity of data creation. Among that data, AI-generated images have become a highly discussed topic, especially when discussing the potential dangers of these AI models. Due to these dangers, being able to distinguish AI-generated art from human-made art is becoming a necessity. Additionally, as these AI-models improve, it is becoming increasingly difficult for humans to determine whether art is AI-generated or human-made. This paper proposes the further exploration of the effectiveness of a current state of the art AI-image identification model.

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Gmr-45 Cloud Based Bus Tracking And Ticketing System, Vyghni Sudha Kommineni, Damacharla Sravani Apr 2024

Gmr-45 Cloud Based Bus Tracking And Ticketing System, Vyghni Sudha Kommineni, Damacharla Sravani

C-Day Computing Showcase

In many urban areas, public transportation systems frequently fail to fulfill passenger demand, causing aggravation owing to a lack of real-time information about bus locations, timetables and delays. Outdated ticketing processes, which are labor-intensive and prone to mistakes, compound the annoyance by failing to match current travelers' expectations. Furthermore, transportation operators encounter difficulties with fleet management, route optimisation, and issue response due to a lack of comprehensive data analytics. Reliable monitoring systems are required to prioritize passenger and bus safety, and achieving sustainability targets necessitates efficient operations to reduce fuel consumption and emissions. A scalable and customizable cloud-based bus tracking …

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Gmr-118 Stress Detection By Wearable Devices: Integrating Multimodal Physiological Signals And Machine Learning Techniques, Pranita Subhash Shedage Apr 2024

Gmr-118 Stress Detection By Wearable Devices: Integrating Multimodal Physiological Signals And Machine Learning Techniques, Pranita Subhash Shedage

C-Day Computing Showcase

In the medical field, the most common complaint of patients is “stress”. Stress can cause severe effects on the human body. For example, prolonged mental stress can cause serious health issues in long term such as hypertension, cardiovascular diseases, increased susceptibility to infections, and depression. These health issues can be prevented by early detection of stress and by taking preventive measures. The most common detecting stress was determined from the questionnaires or from the interactive sessions conducted to assess the people's affective state. However, this method is not highly reliable and can be biased depending on the person who is …

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Gmr-59 Customer Segmentation For Marketing Campaigns Using K-Means Clustering, Jaswanthi Vellanki, Hrithik Singh Chandel, Vyghni Sudha Kommineni, Priyanka A Bagal, Rutvikkumar K Ramani Apr 2024

Gmr-59 Customer Segmentation For Marketing Campaigns Using K-Means Clustering, Jaswanthi Vellanki, Hrithik Singh Chandel, Vyghni Sudha Kommineni, Priyanka A Bagal, Rutvikkumar K Ramani

C-Day Computing Showcase

The objective of this project is to use K-means clustering an unsupervised machine learning algorithm to categorize customers based on characteristics such as demograp hics, purchasing history and interaction behavior. The purpose is to discover different client segments that can be targeted with specialized marketing techniques that improve marketing campaign efficiency and increase consumer satisfaction and engagement.

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Gmr-23 Jamming Signal Detection Using Extreme Gradient Boosting (Xgboost) Algorithm, Keerthana Adamana, Christian K Sao Apr 2024

Gmr-23 Jamming Signal Detection Using Extreme Gradient Boosting (Xgboost) Algorithm, Keerthana Adamana, Christian K Sao

C-Day Computing Showcase

Radar jamming involves sending intentionally disruptive radio waves toward the target radar, which might over-saturate its receiver so it can’t receive anything or deceive it into interpreting false information. Machine learning (ML) techniques increased the capability to automatically learn the experience without being explicitly programmed. Machine learning models usually require a large, labeled sample to perform. Building a robust jamming detection model will be challenging due to the wide variability of jamming signals and less available labeled samples. In this project, we developed an eXtreme Gradient Boosting(XGBoost) algorithms for radar jamming signal classification and achieved superior performance compared with Random …

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Gc-84 Owl Cyber Defense Systems, Randolph S Gilstrap, Christopher Dunbar, Stephanie Aguirre, Ryan M Leblanc, Justin Place Apr 2024

Gc-84 Owl Cyber Defense Systems, Randolph S Gilstrap, Christopher Dunbar, Stephanie Aguirre, Ryan M Leblanc, Justin Place

C-Day Computing Showcase

Owl Cyber Defense Systems is a fictitious (for now?) start-up offering comprehensive cybersecurity solutions for small and medium businesses. Our premier flagship product is an AI Chatbot that answers security related questions and provides vetted code and security settings to secure and harden a variety of systems. Starting with the initial concept, we methodically progressed through the business planning process, carefully considering technology usage and design. This comprehensive approach ultimately enabled us to develop a robust set of client offerings. We used a hybrid approach combining Agile Scrum and traditional Waterfall methodologies to complete the project. We utilized Jira Project …

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Uc-27 Crm Proposal, Luis A Maiocchi Castro, Crystal Misko, Steven Damico, Ethan Groves, Maryah Outlaw Apr 2024

Uc-27 Crm Proposal, Luis A Maiocchi Castro, Crystal Misko, Steven Damico, Ethan Groves, Maryah Outlaw

C-Day Computing Showcase

This project addresses concerns raised by a Sponsor regarding inefficiencies in managing CCSE capstone projects. Key pain points include organization, project management, and communication among stakeholders. The proposed solution involves implementing Customer Relationship Management (CRM) software. Upon gathering requirements from the Sponsor, including contact information capture, workflow management, document control, and customization capabilities, we evaluated several CRM platforms. A total of thirty-two CRMs were reviewed and Vtiger, OroCRM, and SuiteCRM were selected for testing. SuiteCRM was chosen for its comprehensive features and user-friendliness. The second step of the project involved testing SuiteCRM functionalities on a dedicated server, leading to its …

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Uc-33 Big Munchin', Tabitha Reynolds, Steven M Amerson, David J Buck, Jacques P Gatipon, Aaliyah Mcelrath, Nick S Watson Apr 2024

Uc-33 Big Munchin', Tabitha Reynolds, Steven M Amerson, David J Buck, Jacques P Gatipon, Aaliyah Mcelrath, Nick S Watson

C-Day Computing Showcase

Big Munchin' is a video game designed to help teach portioning skills and promote healthy eating habits. The overall metabolic health of individuals in America is comparatively low to other countries. Metabolic health is bolstered by several factors including exercise and a proper diet consisting of essential vitamins, proteins, and other important biomolecules.The increased cost of healthy nutrient-rich foods and a lack of proper nutritional education have hindered the overall metabolic health of modern Americans. Engaging individuals in learning more about nutritional health can be a difficult task made easier by an engaging experience that stays in the user’s minds. …

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Uc-35 Ksu Ccse Crm, Alex Curran, Dj Mitchell, Christian Miller Apr 2024

Uc-35 Ksu Ccse Crm, Alex Curran, Dj Mitchell, Christian Miller

C-Day Computing Showcase

Our task was to select, implement and customize a CRM solution for the College of Computing and Software Engineering to more effectively manage communication with industry partners and manage projects such as capstones, and C-Day. Our team selected SuiteCRM as our recommendation and have implemented an instance on a virtual machine provided by UITS. We have customized branding including using a KSU logo provided by the Office of Strategic Communications and Marketing, as well as customizations based on the official KSU color pallete. The process we used to select our CRM recommendation involved gathering requirements from our sponsor and comparing …

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Uc-64 Cribmaster Smart Evaluator Of Mro Supplies Vendibility, Matthew S Periut, Cohen Miller, Carter Ray, Dawniqueca Steele, Justin Hughes Apr 2024

Uc-64 Cribmaster Smart Evaluator Of Mro Supplies Vendibility, Matthew S Periut, Cohen Miller, Carter Ray, Dawniqueca Steele, Justin Hughes

C-Day Computing Showcase

The CribMaster Smart Evaluator of MRO Supplies, or SEMROS, is a comprehensive web-based solution that gathers and analyzes data about specific industrial tools, their characteristics, and vending possibilities. The system will achieve this by allowing users to import spreadsheets of their client’s inventory, and then perform both data collection and vendibility analysis. The process of data collection includes utilizing web-scraping tools and OpenAI API, which will gather key information such as item manufacturer details, SKUs, item cost, and physical details that can impact the vendibility of said item. Next, the system will analyze the vendibility of each item based on …

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Gmr-47 A Two-Stage Prediction Model For House Prices, Nguyen Thi Binh Nguyen, Brandon Bell, Syanthan Reddy Ravula, Hari Krishna Thota Apr 2024

Gmr-47 A Two-Stage Prediction Model For House Prices, Nguyen Thi Binh Nguyen, Brandon Bell, Syanthan Reddy Ravula, Hari Krishna Thota

C-Day Computing Showcase

Predicting house prices is a challenging task that researchers from various fields (economics, statistics, politics, etc.) have attempted to answer. An accurate house prediction is useful not only to policymakers to improve their policies, but also to help sellers and buyers in the real estate market make well- informed decisions. Commonly, prediction models are trained on the whole dataset. However, as Azimlu et al [1] suggested, such models might not perform very well on dispersed data. They propose a new approach which first divides the whole dataset into smaller clusters, and then each cluster would be trained with an appropriate …

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Gmr-72 Ai-Based Discourse Analysis System (Adas) For Improved Stem Education, Varun Gottam Apr 2024

Gmr-72 Ai-Based Discourse Analysis System (Adas) For Improved Stem Education, Varun Gottam

C-Day Computing Showcase

In the rapidly evolving fields of Artificial Intelligence and Natural Language Processing, significant opportunities have emerged to transform educational practices. Discourse analysis, particularly in science education, plays a critical role in fostering scientific thinking among students. However, the manual application of tools like the Classroom Discourse Analysis Tool is resource-intensive and impractical on a large scale. This abstract proposes the development of an AI-based Discourse Analysis System tailored for educational settings, designed to automate and enrich the analysis of classroom discourse. Leveraging the latest in Artificial Intelligence and Natural Language Processing, this web-based application will provide teachers nationwide with the …

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Ur-87 Adversarial Patch Attack In Deep Learning Based Remote Sensing Object Detection Model, Kyle Bratcher Apr 2024

Ur-87 Adversarial Patch Attack In Deep Learning Based Remote Sensing Object Detection Model, Kyle Bratcher

C-Day Computing Showcase

Advancements in the field of machine learning have led to object detection systems that can approach or even improve upon human performance. Based on deep learning, these systems play a crucial role in many aspects, and continue to be improved on and see expanded adoption. However, these systems are vulnerable to adversarial attacks that rely on targeted noise to spoof detection. Researchers have applied this concept to increase real world adversarial performance by restricting this noise to a patch that can be placed on new images to disrupt object detection. Previous research has focused on patches applied to person recognition …

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Ur-94 Emohydra: Multimodal Emotion Classification Using Heterogenous Modality Fusion, William A Stigall Apr 2024

Ur-94 Emohydra: Multimodal Emotion Classification Using Heterogenous Modality Fusion, William A Stigall

C-Day Computing Showcase

Affective computing is a field of growing importance, as human society becomes more integrated with machines. Human feelings are both complex and multi-modal, expressed through various methods and nuances in behavior. In this work we introduce EmoHydra, a multi-modal model created through the fusion of three top-level models fine-tuned on text, vision, and speech respectively. Despite heterogenous heads performing well on the unseen data, as well as generalizing well to other benchmarks, logit concatenation proves to be ineffective at predicting Multimodal data, therefore we implement Multi-Head Attention as our fusion mechanism.

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Uc-69 Interactive Training Game Suite, Garrett J Perry, Joscelyn Cauley, Issabella Du, Sergiu Ursu, Rahaf Kokash Apr 2024

Uc-69 Interactive Training Game Suite, Garrett J Perry, Joscelyn Cauley, Issabella Du, Sergiu Ursu, Rahaf Kokash

C-Day Computing Showcase

It is now common knowledge that simple lectures are not the most effective way for the average person to learn and retain knowledge. The Core of Engineers at the Warner Robins Air Logistic Center have tasked us to transform their PowerPoint presentations into interactive training games to improve comprehension, interaction and retention while saving time and logistical resources compared to giving a traditional lecture. We been tasked with creating game modules covering STINFO or what is or is not considered classified information, Records Management, and the No FEAR Act detailing whistleblower rights and protocols. Our team has developed a log …

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Uc-105 Model Un Crisis Software, Gregory Hicks, James Ritzi, Vincent K Kipchoge Apr 2024

Uc-105 Model Un Crisis Software, Gregory Hicks, James Ritzi, Vincent K Kipchoge

C-Day Computing Showcase

Utilizing an Agile approach, this project develops a web-based solution, the Model UN Crisis Software, to streamline the management of crisis committees in Model UN conferences. The software is developed using Microsoft Visual Studio and Microsoft SQL Server Management Studio, adhering to the .NET framework and related conventions. It leverages Microsoft Azure SQL Database for back-end data storage and follows the ASP.NET core MVC framework, utilizing powerful .NET tools such as C# and Razor. The developed software provides comprehensive features to reduce the strain of hosting a crisis committee, such as directive and news management, user management, and a messaging …

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Gpr-16 Attention Driven Framework For Detecting Mental Illness Causes From Social Media, Abm Adnan Azmee, Dinesh Chowdary Attota, Francis E Nweke Apr 2024

Gpr-16 Attention Driven Framework For Detecting Mental Illness Causes From Social Media, Abm Adnan Azmee, Dinesh Chowdary Attota, Francis E Nweke

C-Day Computing Showcase

Mental health is a critical aspect of our overall well-being. Mental illness refers to conditions that impact an individual's psychological state, resulting in considerable distress, and limitations in functioning day-to-day tasks. Due to the progress of technology, social media has merged as the platform, for individuals to share their thoughts and emotions. The psychological state of individuals can be accessed with the help of data from these platforms. However, it is challenging for conventional machine learning models to analyze the diverse linguistic contexts of social media data. In this work, we propose a novel attention-driven deep framework to overcome these …

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Gpr-18 Case Exploration: Automatic Keyword Matching Framework For Behavioral Health, Francis E Nweke, Abm Adnan Azmee Apr 2024

Gpr-18 Case Exploration: Automatic Keyword Matching Framework For Behavioral Health, Francis E Nweke, Abm Adnan Azmee

C-Day Computing Showcase

In this demonstration, we propose a framework for exploring, identifying, and matching repeated behavioral health keywords in first-responder reports to the current set of Behavioral Health Index Terms provided by subject matter experts (SMEs). The tool incorporates behavioral health-related keywords and has a Graphical User Interface (GUI) that allows non-technical users to explore and analyze 911 first-responder reports. We utilized an inverted index, best-matching (BM25), and plain-text searching algorithms to match keywords in first-responder reports. This tool provides a comprehensive approach to report analysis by identifying indicators of mental health disorders and taking into account the assessments of humanities and …

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Gpr-63 Adaptive Attention Aware Fusion For Human-In-Loop Behavioral Health Detection, Martin Brown, Abm Adnan Azmee Apr 2024

Gpr-63 Adaptive Attention Aware Fusion For Human-In-Loop Behavioral Health Detection, Martin Brown, Abm Adnan Azmee

C-Day Computing Showcase

Identifying behavioral health is paramount for law enforcement officers to provide appropriate follow-up community care. In the current practice, law enforcement offices manually identify these behavioral health cases to allow the designation of the relevant follow-up resources. In this work, we develop a tool to automatically detect behavioral health cases from police public narrative reports by identifying behavioral health indicator signals. We propose a novel adaptive attention-aware fusion model for detecting behavioral health signals in sensitive police reports. Our model leverages contextual and semantic information from the reports and relevant behavioral health cues as keywords from a pre-trained attention-weighted keyword-based …

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Uc-100 Indy 7 - Nutrition App, Silas E Hammond, Tho Mai, Christopher P Sarzen, Michael Ehme Apr 2024

Uc-100 Indy 7 - Nutrition App, Silas E Hammond, Tho Mai, Christopher P Sarzen, Michael Ehme

C-Day Computing Showcase

This project’s objective is to develop a fully functioning and polished mobile app for keeping track of caloric intake and monitoring other aspects of one’s health. To accomplish this, we will be using React Native to develop a front end which allows users to select their goals and get active assistance in moderating what they eat. This will be done through the scanning of barcodes of any food purchased. These barcodes will then be used to query the Food Data Central API to provide the user with as much information as needed. This will include possible allergies, calorie totals, protein …

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Gpr-108 Revolutionizing Reflective Learning In Higher Education: An Llm-Based Analytical Approach, Bharath Y Yadla, Mourya Teja Kunuku Apr 2024

Gpr-108 Revolutionizing Reflective Learning In Higher Education: An Llm-Based Analytical Approach, Bharath Y Yadla, Mourya Teja Kunuku

C-Day Computing Showcase

This project introduces a novel LLM-based system to automate The analysis of student reflections, enhancing reflective learning in higher education. Leveraging advanced ML and NLP technologies, the system provides personalized, in-depth feedback by identifying learning outcomes and challenges. Employing the OpenAI API and LangChain framework, it offers a nuanced understanding of student learning trajectories. The methodology involves collecting data via the Minute Paper technique, enabling targeted instructional adjustments. Preliminary results indicate a significant improvement in analyzing and addressing students' educational needs.

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Gpr-13 Effect Of Noise And Topologies On Multi-Photon Quantum Protocols, Nitin Jha Apr 2024

Gpr-13 Effect Of Noise And Topologies On Multi-Photon Quantum Protocols, Nitin Jha

C-Day Computing Showcase

Quantum-augmented networks aim to use quantum phenomena to improve detection and protection against malicious actors in a classical communication network. This may include multiplexing quantum signals into classical fiber optical channels and incorporating purely quantum links alongside classical links in the network. In such hybrid networks, quantum protocols based on single photons become a bottleneck for transmission distances and data speeds, thereby reducing entire network performance. Furthermore, many of the security assumptions of the single-photon protocols do not hold up in practice because of the impossibility of manufacturing single-photon emitters. Multi-photon quantum protocols, on the other hand, are designed to …

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Uc-40 Asynchronous, Ryan A Whisenhunt, Peyton T Lee, Kenneth Wardlaw, Benjamin T Haaf, Carter L Good, Cory A Ridley Apr 2024

Uc-40 Asynchronous, Ryan A Whisenhunt, Peyton T Lee, Kenneth Wardlaw, Benjamin T Haaf, Carter L Good, Cory A Ridley

C-Day Computing Showcase

Cultural assimilation is the topic on the mind of the protagonist of our game, Asynchronous. Maxwell, a diplomat from a real-time world, must adapt in a foreign land where the people live turn-based lives. We explore this topic through the lens of traditional JRPG gameplay where the player must decide when to adapt to this new culture and when to act on their own accord. By representing this idea ludically, we hope to better convey the mindset and emotional state of being an outsider to the player.

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Uc-99 Interactive Training Games - Robins Air Force Base, Sean J Tenney, Vt Nguyen, Ian Ford, Mason Farmer, Aaron Hannah Apr 2024

Uc-99 Interactive Training Games - Robins Air Force Base, Sean J Tenney, Vt Nguyen, Ian Ford, Mason Farmer, Aaron Hannah

C-Day Computing Showcase

Our project involves converting three PowerPoint training presentations on STINFO, No Fears Act, and Records Management into engaging web-based games. Commissioned by Robins Air Force Base, our team utilizes Unity WebGL for game development and React/Firebase for website hosting. The goal is to provide Air Force personnel with interactive training modules accessible from their desks, enhancing learning retention and engagement. By gamifying the content, we aim to make learning enjoyable while ensuring critical information retention. This interdisciplinary project merges game development and web technologies to modernize training methods and improve educational outcomes for military personnel.

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