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Physical Sciences and Mathematics Commons™
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Articles 1 - 30 of 53
Full-Text Articles in Physical Sciences and Mathematics
The Classification Of Internet Memes Through Supervised And Unsupervised Machine Learning Algorithms, William H. Little
The Classification Of Internet Memes Through Supervised And Unsupervised Machine Learning Algorithms, William H. Little
Symposium of Student Scholars
Memes, those captivating internet phenomena, effortlessly deliver online entertainment. By leveraging time-series data from Google Trends, we can vividly illustrate and dissect the dynamic trends in meme popularity. Previous studies have discerned four distinct post-peak popularity patterns— "smoothly decaying," "spikey decaying," "leveling off," and "long-term growth"—and elegantly modeled these using ordinary differential equations.
This research introduces a programmatic approach that harnesses both supervised and unsupervised machine learning algorithms. The dataset, now expanded to over 2000 elements, becomes the canvas for exploration. The K-means algorithm identifies clusters, which then serve as labels for the supervised SVC algorithm. The overarching goal is …
Exploring Neural Networks For Breast Cancer Tissue Classification, Stephen Jacobs, Md Abdullah Al Hafiz Khan
Exploring Neural Networks For Breast Cancer Tissue Classification, Stephen Jacobs, Md Abdullah Al Hafiz Khan
Symposium of Student Scholars
Last year, more than 240 thousand women in the United States were diagnosed with breast cancer. These patients are benefitting from decades of data that have been collected by cancer research institutions around the world. Tissue samples are analyzed and cataloged by these institutions, and several facilities like the University of Wisconsin are sharing this historical data to promote the advancement of new cancer treatments. Deep learning and neural network models are being built for this data to help doctors diagnose faster and design treatment options for patients by comparing their tissue samples with these historical datasets. We will use …
Requiring Students To Integrate Chatgptinto Course Assignments, Mark Small, Venera Balidemaj
Requiring Students To Integrate Chatgptinto Course Assignments, Mark Small, Venera Balidemaj
Clemson Teaching Excellence Conference 2024: Teaching in the Age of AI
No abstract provided.
Toxic Comment Classification Project, Brandon Solon
Toxic Comment Classification Project, Brandon Solon
Symposium of Student Scholars
The digital landscape has blossomed thanks to the surge of online platforms, boosting the variety and volume of user-created content. But it's not without its shadows; cyberbullying and hate speech have also proliferated, making web spaces less safe. At our project centerstage, we work on creating a machine learning model skilled at spotting toxic comments with precision - this way contributing towards an internet society free from fear or discomfort. We put well-documented datasets to good use along with careful preprocessing maneuvers while trialing diverse machina-learning protocols as part of constructing solid classification architecture for usages beyond current limitations within …
Blind Fighter – A Video Game For The Visually Impaired, Avery Wayne Harrah
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
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
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
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
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
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, …
Generation Z Cybersecurity Learners: The Identification Of Cybersecurity Instructor Strategies And Attributes That Maximize Student Engagement, Jeffrey Rice
Scholar Week 2016 - present
There exists a significant shortage of cybersecurity specialists in the workforce. Universities should endeavor to keep cybersecurity students engaged if they desire to be competitive and contribute graduates to the remediation efforts of this cybersecurity deficit. Instructors significantly contribute to student engagement and there is a correlation between student engagement and student retention. The purpose of this regional qualitative exploratory study was to identify attributes that Generation Z collegiate cybersecurity learners felt kept them engaged in their cybersecurity courses. The sample comprised 10 individuals identified as GenZ and used purposeful and snowball sampling to select participants. A semi-structured interview strategy …
Temporal Tensor Factorization For Multidimensional Forecasting, Jackson Cates, Karissa Scipke, Randy Hoover, Kyle Caudle
Temporal Tensor Factorization For Multidimensional Forecasting, Jackson Cates, Karissa Scipke, Randy Hoover, Kyle Caudle
SDSU Data Science Symposium
In the era of big data, there is a need for forecasting high-dimensional time series that might be incomplete, sparse, and/or nonstationary. The current research aims to solve this problem for two-dimensional data through a combination of temporal matrix factorization (TMF) and low-rank tensor factorization. From this method, we propose an expansion of TMF to two-dimensional data: temporal tensor factorization (TTF). The current research aims to interpolate missing values via low-rank tensor factorization, which produces a latent space of the original multilinear time series. We then can perform forecasting in the latent space. We present experimental results of the proposed …
Simulating Salience: Developing A Model Of Choice In The Visual Coordination Game, Adib Sedig
Simulating Salience: Developing A Model Of Choice In The Visual Coordination Game, Adib Sedig
Undergraduate Student Research Internships Conference
This project is primarily inspired by three papers: Colin Camerer and Xiaomin Li’s (2019 working paper)—Using Visual Salience in Empirical Game Theory, Ryan Oprea’s (2020)—What Makes a Rule Complex?, and Caplin et. al.’s (2011)—Search and Satisficing. Over the summer, I worked towards constructing a model of choice for the visual coordination game that can model player behavior more accurately than traditional game theoretic predictions. It attempts to do so by incorporating a degree of bias towards salience into a cellular automaton search algorithm and utilizing it alongside a sequential search mechanism of satisficing. This …
Phishing For Fun, Madeline Moran
Phishing For Fun, Madeline Moran
Computer Science Research Seminars and Symposia
The process of a phishing experiment that will be used to investigate a possible correlation between a person thinking style and their susceptibility to phishing scams.
Rotoscoping Image Processing, David J. Blackstone
Rotoscoping Image Processing, David J. Blackstone
Student Scholar Showcase
I wrote a program to perform rotoscoping image processing. Rotoscoping is an animation technique that is used to turn real images into cartoon images. This is a lengthy process to do by hand, taking hundreds of hours. To make this job easier, I have written a program to do automated rotoscoping. This program uses many algorithms and techniques such as edge detection, blurring, directional detection, and edge tracking. What once would take hours by hand, takes seconds!
Seizure Prediction In Epilepsy Patients, Gary Dean Cravens
Seizure Prediction In Epilepsy Patients, Gary Dean Cravens
NSU REACH and IPE Day
Purpose/Objective: Characterize rigorously the preictal period in epilepsy patients to improve the development of seizure prediction techniques. Background/Rationale: 30% of epilepsy patients are not well-controlled on medications and would benefit immensely from reliable seizure prediction. Methods/Methodology: Computational model consisting of in-silico Hodgkin-Huxley neurons arranged in a small-world topology using the Watts-Strogatz algorithm is used to generate synthetic electrocorticographic (ECoG) signals. ECoG data from 18 epilepsy patients is used to validate the model. Unsupervised machine learning is used with both patient and synthetic data to identify potential electrophysiologic biomarkers of the preictal period. Results/Findings: The model has shown states corresponding to …
Student Academic Conference, Caitlin Brooks
Student Academic Conference, Caitlin Brooks
Student Academic Conference
No abstract provided.
The Origin & Evolution Of The Chinese Language, Charity Bullis, Yan Xie
The Origin & Evolution Of The Chinese Language, Charity Bullis, Yan Xie
Liberty University Research Week
Undergraduate
Textual or Investigative
Javafx Application, Pengfei Huang
Javafx Application, Pengfei Huang
Student Academic Conference
Developing java GUI application by using JavaFX.
Automated Tool Support - Repairing Security Bugs In Mobile Applications, Larry Singleton
Automated Tool Support - Repairing Security Bugs In Mobile Applications, Larry Singleton
UNO Student Research and Creative Activity Fair
Cryptography is often a critical component in secure software systems. Cryptographic primitive misuses often cause several vulnerability issues. To secure data and communications in applications, developers often rely on cryptographic algorithms and APIs which provide confidentiality, integrity, and authentication based on solid mathematical foundations. While many advanced crypto algorithms are available to developers, the correct usage of these APIs is challenging. Turning mathematical equations in crypto algorithms into an application is a difficult task. A mistake in cryptographic implementations can subvert the security of the entire system. In this research, we present an automated approach for Finding and Repairing Bugs …
Security Camera Using Raspberry Pi, Tejendra Khatri
Security Camera Using Raspberry Pi, Tejendra Khatri
Student Academic Conference
Making a security camera using raspberry pi utilizing OpenCV for facial recognition, upper body recognition or full-body recognition
Transfer Equivalency Site For The Registrar, Janelle N. Rohrbach, Alissa C. Cielecki, Jules A. Turner
Transfer Equivalency Site For The Registrar, Janelle N. Rohrbach, Alissa C. Cielecki, Jules A. Turner
Capstone Showcase
The website, arcadia-transfer-equiv.com, was drafted and created for Bill Enick, Registrar at Arcadia University. This was an expansion of a preliminary version of the website created by Caleigh Diefenthaler, Christian Charney, and Dylan Power. The site includes two transfer equivalency tools which can be used to search for course equivalencies by academic institution or by a given Arcadia course. The tools, which pull from a database maintained by the Registrar, will display courses that have transferred to the University successfully. The website also hosts two interactive forms. These forms allow Arcadia students to request approval for courses that have or …
3d Procedural Maze & Cave Generation, Jacob Sharp
3d Procedural Maze & Cave Generation, Jacob Sharp
Student Scholar Showcase
The goal of this project is to generate a maze or cave procedurally so that a player may be able to explore infinitely without a reoccurring pattern. The project also utilizes Virtual Reality (VR); the user will be able to put on a VR Headset and become more immersed in a procedural environment. One of the challenges that needed to be overcome was simple random number generators did not generate natural looking worlds. Introducing VR to the project created the additional challenge of preventing the user from becoming motion sick. These challenges were both addressed through many hours of research …
Autonomous Watercraft Simulation And Programming, Nicholas J. Savino
Autonomous Watercraft Simulation And Programming, Nicholas J. Savino
Student Scholar Showcase
Automation of various modes of transportation is thought to make travel more safe and efficient. Over the past several decades, advances to semi-autonomous and autonomous vehicles have led to advanced autopilot systems on planes and boats, and an increasing popularity of self-driving cars. We predicted the motion of an autonomous vehicle using simulations in Python. The simulation models the motion of a small scale watercraft, which can then be built and programmed using an Arduino Microcontroller. We examined different control methods for a simulated rescue craft to reach a target. We also examined the effects of different factors, such as …
Death Arena Game, Ryan Deasy, Nick Snan, Albert Anderson, David Cole, Shahzada Aqib Gill
Death Arena Game, Ryan Deasy, Nick Snan, Albert Anderson, David Cole, Shahzada Aqib Gill
Student Scholar Showcase
Death Arena is a 3D first-person action shooter with a horror twist. The player has 30 seconds to collect guns and health before a monster spawns. The map will be large with indoor and outdoor play. In each round a more powerful boss spawns with minions. Our goal is to appeal to horror and action fans alike.
Design For Safety: Decreasing First Responder Health Risks Through Real-Time Bio-Sensor Alerts, Suzy Fendrick
Design For Safety: Decreasing First Responder Health Risks Through Real-Time Bio-Sensor Alerts, Suzy Fendrick
UNO Student Research and Creative Activity Fair
The focus of this research project is using the Design Thinking process to create an informative dashboard for first responders. Design Thinking involves empathizing with the user, defining the problems to be solved, ideation, creating prototypes, and testing. This iterate process focuses on the user, resulting in the most effective product possible. The dashboard will display real-time biosensor data from sensors in the first responders’ uniforms. This project is part of a larger project with the goal of vastly improving the safety of first responders during emergency hazardous material incidents.
Data Analytics Pipeline For Rna Structure Analysis Via Shape, Quinn Nelson
Data Analytics Pipeline For Rna Structure Analysis Via Shape, Quinn Nelson
UNO Student Research and Creative Activity Fair
Coxsackievirus B3 (CVB3) is a cardiovirulent enterovirus from the family Picornaviridae. The RNA genome houses an internal ribosome entry site (IRES) in the 5’ untranslated region (5’UTR) that enables cap-independent translation. Ample evidence suggests that the structure of the 5’UTR is a critical element for virulence. We probe RNA structure in solution using base-specific modifying agents such as dimethyl sulfate as well as backbone targeting agents such as N-methylisatoic anhydride used in Selective 2’-Hydroxyl Acylation Analyzed by Primer Extension (SHAPE). We have developed a pipeline that merges and evaluates base-specific and SHAPE data together with statistical analyses that provides confidence …
Forecasting Smart Meter Energy Usage Using Distributed Systems And Machine Learning, Feiran Ji, Chris Dong, Lingzhi Du, Zizhen Song, Yuedi Zheng, Paul Intrevado
Forecasting Smart Meter Energy Usage Using Distributed Systems And Machine Learning, Feiran Ji, Chris Dong, Lingzhi Du, Zizhen Song, Yuedi Zheng, Paul Intrevado
Creative Activity and Research Day - CARD
In this research, we explore the technical and computational merits of a machine learning algorithm on a large data set, employing distributed systems. Using 167 million(10 GB) energy consumption observations collected by smart meters from residential consumers in London, England, we predict future residential energy consumption using a Random Forest machine learning algorithm. Distributed systems such as AWS S3 and EMR, MongoDB and Apache Spark are used. Computational times and predictive accuracy are evaluated. We conclude that there are significant computational advantages to using distributed systems when applying machine learning algorithms on large-scale data. We also observe that distributed systems …
An Optimization Approach To Automate The Generation Of Radiotherapy Treatment Plans, Qian Li
An Optimization Approach To Automate The Generation Of Radiotherapy Treatment Plans, Qian Li
Creative Activity and Research Day - CARD
The main goal of radiotherapy is to deliver a specified dose of radiation directly to the tumor while minimizing radiation damage to healthy tissues. Currently, the treatment plan is being developed by professional planners using a commercial treatment planning system. In this treatment planning system, the planner modifies the objectives and weights of the objectives until an ideal combination of doses is achieved. This arbitrary process can cost a few hours or a day to finish. My research aims to automate the generation of the plans by implementing an optimization algorithm on top of the treatment planning system using gradient …
Topical Analysis Of The Enron Emails Using Graph Theory, Casey Kalinowski
Topical Analysis Of The Enron Emails Using Graph Theory, Casey Kalinowski
Student Scholar Showcase
The Enron Scandal of the early 2000s shook the financial world. The subsequent investigation of the Enron Corporation resulted in the arrests of many top-level executives, but are these employees the only ones responsible for the wide scale fraud in the company? A topical analysis of a social network of over 150 employees of the Enron Corporation using Graph Theory could result in new findings or prove that the investigators were correct in their original findings. The research is a retrospective analysis of a corpus of over 500,000 emails from more than 150 employees and top-level executives of the Enron …