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Articles 7711 - 7740 of 63017
Full-Text Articles in Computer Sciences
Gmr-118 Stress Detection By Wearable Devices: Integrating Multimodal Physiological Signals And Machine Learning Techniques, Pranita Subhash Shedage
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 …
Gmr-23 Jamming Signal Detection Using Extreme Gradient Boosting (Xgboost) Algorithm, Keerthana Adamana, Christian K Sao
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 …
Gmr-45 Cloud Based Bus Tracking And Ticketing System, Vyghni Sudha Kommineni, Damacharla Sravani
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 …
Gmr-47 A Two-Stage Prediction Model For House Prices, Nguyen Thi Binh Nguyen, Brandon Bell, Syanthan Reddy Ravula, Hari Krishna Thota
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 …
Gmr-7 A Novel Identity Verification Framework Using A Hybrid Biometric System, Namratha Tavva, Bhanu Prakash Vadlamudi, Sumanth Kunchala, Snigdha Katta
Gmr-7 A Novel Identity Verification Framework Using A Hybrid Biometric System, Namratha Tavva, Bhanu Prakash Vadlamudi, Sumanth Kunchala, Snigdha Katta
C-Day Computing Showcase
In recent years, the field of big data analytics has gained immense attention due to the increasing volume and complexity of data being generated from various sources. One of the key applications of big data analytics is in the field of identity verification, where it is used to process and analyze large amounts of biometric data to authenticate individuals. A hybrid biometric system that combines multiple biometric modalities has been shown to be more effective in identity verification than a single modality system. In this project, we propose an Identity Verification Framework using a Hybrid Biometric System that leverages big …
Gpr-103 Personalized Pedagogy Through A Llm-Based Recommender System, Mourya Teja Kunuku, Bharath Y Yadla
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 …
Gpr-13 Effect Of Noise And Topologies On Multi-Photon Quantum Protocols, Nitin Jha
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 …
Gpr-16 Attention Driven Framework For Detecting Mental Illness Causes From Social Media, Abm Adnan Azmee, Dinesh Chowdary Attota, Francis E Nweke
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 …
Gpr-18 Case Exploration: Automatic Keyword Matching Framework For Behavioral Health, Francis E Nweke, Abm Adnan Azmee
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 …
Uc-105 Model Un Crisis Software, Gregory Hicks, James Ritzi, Vincent K Kipchoge
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 …
Uc-20 Playlist Synch, Joshua Poore, Nikita D Smith, Ben S Pallotti
Uc-20 Playlist Synch, Joshua Poore, Nikita D Smith, Ben S Pallotti
C-Day Computing Showcase
Our project is a web application that allows users to sign in and transfer music playlists from one music streaming service to another. Currently, it is only functional with Apple and Spotify music but there are plans to implement more in the future.
Uc-24 Wildling Rumble, Logan Haines, Ryan A Whisenhunt
Uc-24 Wildling Rumble, Logan Haines, Ryan A Whisenhunt
C-Day Computing Showcase
When it comes to the combined field of digital board games, there needs to be a balance of what is necessary for the physical space and what is necessary for the digital space. The game must be justified as a combination of the two elements and not be able to shift completely to either side. In this study, we are exploring a new modality that uses Near Field Communication cards for transferring game data to the application. Our new method eases the requirement on players to keep track of the game state, as that is handled separately from the program.
Uc-27 Crm Proposal, Luis A Maiocchi Castro, Crystal Misko, Steven Damico, Ethan Groves, Maryah Outlaw
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 …
Uc-43 Aletheianomous Ai: The Chat Bot Providing The Most Accurate Knowledge Information, David E Chavarro, Aimi Tran, Ethan B Byrd, Matthew J Fincher
Uc-43 Aletheianomous Ai: The Chat Bot Providing The Most Accurate Knowledge Information, David E Chavarro, Aimi Tran, Ethan B Byrd, Matthew J Fincher
C-Day Computing Showcase
For this project, our group aimed to create an intelligent chat bot that was accessible through the web client interface. Aletheianomous, our chat bot, was designed to provide accurate information ethically, aligned with human values. When applicable, the AI would offer the user citations to support its responses. For the back-end, a virtual machine (VM) server in AWS with access to the Graphics Processing Unit (GPU) would run three types of models: Sentence Separation Model, Search Query Extractor Model, and the Response Model. The front-end server using Microsoft Azure generates the web page for the user, exchanges chat data with …
Uc-48 Birding With Buddy, Lazare V Sawadogo, Ikhelowa E Adeji, Blake Graham, Zach Alpine, Troy C Sorrells
Uc-48 Birding With Buddy, Lazare V Sawadogo, Ikhelowa E Adeji, Blake Graham, Zach Alpine, Troy C Sorrells
C-Day Computing Showcase
Birding with Buddy is an educational and entertaining immersive virtual 3D low-poly birdwatching to be experienced at the Carter Lake Nature Center to enable kids to embark on a quest to learn more about birds. Buddy the Beaver guides the user through different terrain types to identify diverse bird species with sounds. Integrate a bird identification system where players click on the binocular icon to switch to a binocular view. In this view, players can choose to Identify (multiple-choice) the correct bird, Hear the Call Again, or Consult a Field Guide. Featuring flippable pages with images and notable markings of …
Uc-56 Donation For Dummies, Jayvon L Triplett, Stephen A Mancini, Mitchell Thomason, Kendrell M Niles
Uc-56 Donation For Dummies, Jayvon L Triplett, Stephen A Mancini, Mitchell Thomason, Kendrell M Niles
C-Day Computing Showcase
Donation For Dummies is a VR game designed to help people feel more relaxed and informed when donating blood. It consists of a theater room where a video plays explaining the process as well as what to do before and after donating. For people wanting a distraction, we have an arcade where players can enjoy minesweeper, matching, or solitaire. For those wishing to relax, we have an art gallery where players can virtually walk around and look at various pieces of art. The more relaxed player that do not wish to move around the game world can instead choose to …
Uc-64 Smart Evaluator Of Indirect Supplies Vendibility, Matthew S Periut, Cohen Miller, Carter Ray, Dawniqueca Steele, Justin Hughes
Uc-64 Smart Evaluator Of Indirect Supplies Vendibility, Matthew S Periut, Cohen Miller, Carter Ray, Dawniqueca Steele, Justin Hughes
C-Day Computing Showcase
The Smart Evaluator is a web-based software solution that analyzes industrial tools and their vending possibilities. It aims to streamline inventory research for sales teams, reducing manual data gathering and vendibility determination. To begin, users simply upload a basic item inventory spreadsheet, and start the program. From there, the program uses web scraping and ChatGPT to gather key data about the various tools including dimensions, weight, and fragility. Each item is then evaluated based on the collected data, and the optimum storage method is calculated. Once these tasks are performed, the results are stored in the system’s database for future …
Uc-69 Interactive Training Game Suite, Garrett J Perry, Joscelyn Cauley, Issabella Du, Sergiu Ursu, Rahaf Kokash
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 …
Uc-71 An Environmentally Conscious Roguelike, Andrew Bland, Brendan Strawser, Adele Rousseau, Bewaji Adewunmi
Uc-71 An Environmentally Conscious Roguelike, Andrew Bland, Brendan Strawser, Adele Rousseau, Bewaji Adewunmi
C-Day Computing Showcase
This semester we have been creating an action-adventure video game based on the theme of "Saving the Environment".
Uc-81 Drinkinator App, Maximus A Smith, Toby Mose, Grayson Payne
Uc-81 Drinkinator App, Maximus A Smith, Toby Mose, Grayson Payne
C-Day Computing Showcase
The "Drinkinator" app represents an innovative solution aimed at revolutionizing the beverage industry by providing users with a personalized drink recommendation system. Rooted in a motivation to diversify people's beverage selections and enhance their drinking experiences, the app facilitates exploration of a wide range of mixed drinks, wines, and beers tailored to individual preferences. Leveraging data analysis and user profiling techniques, the app offers tailored suggestions, showcasing a deep understanding of consumer behavior and taste preferences. Utilizing React Native for front-end development and JavaScript for back-end functionality, the app integrates various libraries to ensure seamless user experiences and efficient data …
Uc-82 Trip Logger, Reese D Gassner, Jason Zhou, Justin T Barker
Uc-82 Trip Logger, Reese D Gassner, Jason Zhou, Justin T Barker
C-Day Computing Showcase
We developed an Android mobile app using the Software Development Life Cycle (SDLC) approach to enable users to track their travel distance and time via GPS, fostering greater emissions awareness through their driving habits of distance and time taken. Built with the Flutter framework and Dart language, the app features a user-friendly interface created with Flutter widgets that manage both appearance and user interactions. Our streamlined architecture comprises three layers: the presentation layer for UI elements, the application layer containing the core logic, and the data layer, which locally stores trip data in CSV format to ensure quick access and …
Ur-49 Coronary Artery Segmentation Using Convolutional Neural Network, Connor Bell, Brenda Nyiam, Daron L Pracharn
Ur-49 Coronary Artery Segmentation Using Convolutional Neural Network, Connor Bell, Brenda Nyiam, Daron L Pracharn
C-Day Computing Showcase
The project contributes to the advancement of medical imaging technology by overcoming the challenges associated with segmenting coronary arteries from ICA images. By leveraging deep learning algorithms, the system can effectively extract coronary arteries with high accuracy, providing valuable information for CAD diagnosis and treatment planning. Accurate and efficient coronary artery segmentation can improve the workflow of cardiologists and enhance the quality of patient care. A robust automated segmentation model could potentially reduce the time and resources required for manual annotation by experienced cardiologists, leading to cost savings and increased efficiency in clinical settings. Additionally, the developed model could be …
Ur-62 Deep Learning Approach To Network Anomaly Detection, Rene P Lisasi, Jamia M Jackson
Ur-62 Deep Learning Approach To Network Anomaly Detection, Rene P Lisasi, Jamia M Jackson
C-Day Computing Showcase
A model of network anomaly detection capable of detecting a multitude of network attacks. This model is based on the hypothesis that by studying a system’s network records for irregular patterns during system usage, network anomalies can be identified. This model contains information about the type of attacks and metrics. This model is to be used in any type of distributed environment. The general purpose of this model is to detect when an attack is or has happened using deep learning techniques to optimize the training speed, accuracy and robustness of attack detection. This is done to stop the epidemic …
Ur-78 Transforming Game Play: A Comparative Study Of Cnn And Transformer Based Q-Networks In Reinforcement Learning, William A Stigall
Ur-78 Transforming Game Play: A Comparative Study Of Cnn And Transformer Based Q-Networks In Reinforcement Learning, William A Stigall
C-Day Computing Showcase
In this study we investigate the performance of Deep Q-Networks utilizing Convolutional Neural Networks (CNNs) and Transformer architectures across 3 different Atari Games. The advent of DQNs have significantly advanced Reinforcement Learning, enabling agents to directly learn optimal policy from high dimensional sensory inputs from pixel or RAM data. While CNN based DQNs have been extensively studied and deployed in various domains Transformer based DQNs are relatively unexplored. Our research aims to fill this gap by benchmarking the performance of both DCQNs and DTQNs across the Atari games' Asteroids, Space Invaders and Centipede. Our research finds that our Transformer Agent …
Ur-87 Adversarial Patch Attack In Deep Learning Based Remote Sensing Object Detection Model, Kyle Bratcher
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 …
Gc-104 Edai – Ai Enabled Teaching Robot For Informal Learning, Jennifer Bower, Shane Williams, Justice Fuller
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.
Gc-17 Crm For Ccse Department Of Ksu, Venkatesh Alla, Keerthi Nannapaneni, Vinay Kumar Rapolu
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 …
Gc-22 Fabric Moderation Ticketing Mod For Minecraft, John Lambert, Kathy Nguyen, Hayden B Scarbrough, Dasiane Taplin
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.
Gc-84 Owl Cyber Defense Systems, Randolph S Gilstrap, Christopher Dunbar, Stephanie Aguirre, Ryan M Leblanc, Justin Place
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 …
Gmr-107 An Integrated Architecture For Maintaining Security In Cloud Computing Using Blockchain, Namratha Tavva, Ashrith Kumar Devara, Gar H Lock
Gmr-107 An Integrated Architecture For Maintaining Security In Cloud Computing Using Blockchain, Namratha Tavva, Ashrith Kumar Devara, Gar H Lock
C-Day Computing Showcase
Cloud services are vulnerable to assaults because of their widespread availability. Since cloud computing is still a relatively new service, there is a real risk that sensitive information might be altered while in transit. Because of this, bad actors may gain an edge by manipulating data. Clients using the cloud for a wide range of use cases want to know that their data is reliable and secure. Blockchain, on the other hand, is an immutable digital ledger that may be used with cloud computing to provide an immutable cloudbased data storage and processing system. In this work, we present a …