Computer Sciences Commons^™

Use Of Deep Learning In Content-Based Image Retrieval (Cbir), Angelina Das

ATU Research Symposium

In the world of computer vision and data retrieval, a crucial task is finding images within a database based on their visual content. This is known as content-based image retrieval (CBIR). As the number of digital images explodes across fields like online shopping, healthcare, and social media, the need for powerful and precise CBIR systems becomes ever more critical. Early CBIR methods depended on features crafted by hand, like color distributions, texture descriptions, and shape characteristics. However, these techniques often have difficulty capturing the true meaning of an image and might not handle very large datasets effectively. With the rise …

Binder, Tyler A. Peaster, Lindsey M. Davenport, Madelyn Little, Alex Bales

ATU Research Symposium

Binder is a mobile application that aims to introduce readers to a book recommendation service that appeals to devoted and casual readers. The main goal of Binder is to enrich book selection and reading experience. This project was created in response to deficiencies in the mobile space for book suggestions, library management, and reading personalization. The tools we used to create the project include Visual Studio, .Net Maui Framework, C#, XAML, CSS, MongoDB, NoSQL, Git, GitHub, and Figma. The project’s selection of books were sourced from the Google Books repository. Binder aims to provide an intuitive interface that allows users …

Jsper (Just Stablediffusion Plus Easy Retraining), Adam Rusterholz, Meghan Finn, Zach Zolliecoffer, Zach Judy

ATU Research Symposium

JSPER is an an AI art generation Web Application that is both flexible and accessible. Our goal is to enable anyone to create and use their own customized art models, regardless of technical skill level. These models can be trained on almost anything, from a person, to an animal, to a specific object, or even style. The user only has to upload a handful of images of their subject. Then, training settings get optimized at the push of a button to match the type of subject the user is training. After training, their customized model can be used to generate …

Optimizing Campus Chat-Bot Experience Using Puaa: Integrating Large Language Model (Llm) Into University Ai Assistants, Sijan Panday, Zurab Sabakhtarishvili, Clayton Jensen

ATU Research Symposium

The advent of large language models (LLMs) such as Chat-GPT and Bard marks a significant milestone in knowledge acquisition, offering a streamlined alternative to the traditionally labor-intensive process of navigating through multiple checkpoints on the web. This emerging trend in LLMs renders the prevalent rule-based chatbots, commonly utilized by universities, increasingly outdated and subpar. This research project proposes integrating LLM technology into university websites, specifically targeting the needs of students seeking information about their institutions by introducing PUAA (Personal University AI Assistant). Our approach involves using the Retrieval-Augmented Generation (RAG) framework, leveraging the capabilities of the LlamaIndex in conjunction with …

Techniques To Detect Fake Profiles On Social Media Using The New Age Algorithms – A Survey, A K M Rubaiyat Reza Habib, Edidiong Elijah Akpan

ATU Research Symposium

This research explores the growing issue of fake accounts in Online Social Networks [OSNs]. While platforms like Twitter, Instagram, and Facebook foster connections, their lax authentication measures have attracted many scammers and cybercriminals. Fake profiles conduct malicious activities, such as phishing, spreading misinformation, and inciting social discord. The consequences range from cyberbullying to deceptive commercial practices. Detecting fake profiles manually is often challenging and causes considerable stress and trust issues for the users. Typically, a social media user scrutinizes various elements like the profile picture, bio, and shared posts to identify fake profiles. These evaluations sometimes lead users to conclude …

Spoton, Corey A. Naegle, Caleb Mcclure, Chase M. Tallon, Holden J. O'Neal

ATU Research Symposium

SpotOn is a project developed to solve problems with owners losing their pets. The project is in short a solar-powered dog harness with GPS capability with its own application for mobile devices.

Anomaly Detection With Spiking Neural Networks (Snn), Shruti Bhandari, Vyshnavi Gogineni

ATU Research Symposium

Abstract:

Anomaly detection, the identification of rare or unusual patterns that deviate from normal behavior, is a fundamental task with wide-ranging applications across various domains. Traditional machine learning techniques often struggle to effectively capture the complex temporal dynamics present in real-world data streams. Spiking Neural Networks (SNNs), inspired by the spiking nature of biological neurons, offer a promising approach by inherently modeling temporal information through precise spike timing. In this study, we investigate the use of Spiking Neural Networks (SNNs) for detecting anomalies or unusual patterns in data. We propose an SNN model that can learn what constitutes normal …

Blind Fighter – A Video Game For The Visually Impaired, Avery Wayne Harrah

ATU Research Symposium

Blind Fighter is a video game made to be playable by anyone, regardless of any visual impairments the player may have. The game relies on auditory queues to allow players to understand what is happening in the game without ever having to see the screen. The project’s goal is to serve as a proof of concept that video games can be made inclusive with a few additions during development, without sacrificing overall quality. To do this, the game features full graphics in addition to testing many strategies for visually impaired players, including direction-based audio, unique sound effects for each game …

Crime Prediction Using Machine Learning: The Case Of The City Of Little Rock, Zurab Sabakhtarishvili, Sijan Panday, Clayton Jensen

ATU Research Symposium

Crime is a severe problem in the city of Little Rock, Arkansas. In this study, we aim to develop a machine-learning model to predict criminal activities in the city and provide insights into crime patterns. We will analyze publicly available crime datasets from Little Rock Police Department from January 2017 to March 2023 to identify trends and patterns in crime occurrence. We used data cleaning and exploratory data analysis techniques, such as figured-based visualizations, to prepare the data for machine learning. We will employ the Neural Prophet, a time-series machine learning model, to predict daily crime counts. The model will …

Reworking Of The Arkansas Tech Human Resources Employee Records Software, Dalton J. George, Brayan Bonilla-Chavez, John Modica, Angelina Das

ATU Research Symposium

Evisions Argos is a real-time reporting tool used by Arkansas Tech in many record-keeping departments. Reworking HR's software using this tool, security and database access concerns were negated, as Argos is already connected to the University's backend. Using Argos, we have made ATU HR's employee records software more user friendly and built a system that can be pushed to production for use by the university. As a secondary portion to this final project, we developed a proof-of-concept web application using the MEAN (Mongo, Express, Angular, Node) stack. This gave us the opportunity to produce a full-stack application from scratch as …

The Ozark Getaway, Houston Barber, Marcus Gasca, Evan Reece Matlock, Avery Wayne Harrah

ATU Research Symposium

Website designed for usage of renting AirBnb houses outside of the original website under the specific owner.

Premium Wireless, Dakota Burkhart, Andrew Clark, Garrett Kenney, Brandon Monroe

ATU Research Symposium

Our work implements an inventory system and appointment system for the Premium Wireless phone company. It includes separate views for employees to manage inventory and view appointments for the day and the near future and allows customers to view all current inventory and set an appointment.

Arkavalley Liquor: Simplifying Restaurant Alcohol Orders, Isaiah A. Kitts, Dayton Drilling, Bradlee Treece, Cameron Lumpkin

ATU Research Symposium

The ArkaValley Liquor system is a web-based ordering platform designed to simplify the process of ordering alcohol for local restaurants. Currently, restaurants place orders by emailing the store, which makes it difficult to maintain a paper trail and track order details. With the ArkaValley Liquor system, the ordering process is automated, and all order details are saved in one central location. Each restaurant will have a login, ensuring only authorized individuals can place orders. The system will also provide a record of each restaurant's most recent order, making it easy to reorder if necessary. By using the ArkaValley Liquor system, …

A Web User Interface Image Processing Tool For Classifying The Extent Of Dementia Across Alzheimer’S, Sathvik Prasad Palyam, Robin Ghosh

ATU Research Symposium

Alzheimer's disease (AD) is the most common form of dementia. This project used four image specifications to classify the dementia stages in each patient applying the CNN algorithm. Employing the CNN-based in silico model, the authors successfully classified and predicted the different AD stages and got around 97.19% accuracy. Later, a web interface tool was developed to educate doctors or researchers to check the patients' dementia level based on the MRI brain images and suggest symptoms that strengthen the predicted level of AI. A user uploads the brain scan, which is sent to the backend server, where the image is …

Fake Profile Detection On Social Media Using Generative Adversarial Networks (Gans), Edidiong Akpan

ATU Research Symposium

Generative Adversarial Networks (GANs) is an artificial intelligence framework used to make computers inventive. This has been applied in several areas of security such as intrusion detection systems. With the wave of globalization and increased social media presence, security has become a thing of concern. For instance, social media security breaches and faking has become one of the many things people are subjected to ranging from impersonation, cyberbullying, stalking, fraud, fleecing of personal assets, and issuing online threats behind fake profiles, these fake profiles are created either by hacking an existing account or by copying the lifestyle and events shared …