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Articles 1 - 18 of 18
Full-Text Articles in Engineering
Ieee Robotics Competition, Emily Webb, Arath Sanchez, Genesis V. Garay, Caleb Bynum, Brandon Bunton
Ieee Robotics Competition, Emily Webb, Arath Sanchez, Genesis V. Garay, Caleb Bynum, Brandon Bunton
ATU Research Symposium
No abstract provided.
Breast Cancer Classification With Machine Learning, Rahanuma Tarannum
Breast Cancer Classification With Machine Learning, Rahanuma Tarannum
ATU Research Symposium
Breast cancer is one of the foremost causes of death amongst women worldwide. Breast tumours are characteristically classified as either benign (non-cancerous) or malignant (cancerous). Benign tumours do not spread external side of the breast and are not fatal, whereas malignant tumours can metastasize and be incurable if untreated. Rapidly and accurate diagnosis of malignant tumours is significant for efficient treatment and advanced outcomes. In 2022, breast cancer claimed 670 000 lives worldwide. Women without any particular risk factors other than age and sex account for half of all cases of breast cancer. In 157 out of 185 nations, breast …
Arkansas Tech University Modular Robotics Training System, Andrew L. Hilsdon, Jacob L. Crawford, Luke C. Hartman, Samuel E. Allen, Anthony W. Knudson, Kyle B. Mcmillan
Arkansas Tech University Modular Robotics Training System, Andrew L. Hilsdon, Jacob L. Crawford, Luke C. Hartman, Samuel E. Allen, Anthony W. Knudson, Kyle B. Mcmillan
ATU Research Symposium
Arkansas Tech University Modular Robotic Training System (ATUM RTS) project aims to combine two existing systems: The Georgia Tech Robotarium and the Micromouse maze-solving competition. The goal of ATUM RTS is to incorporate the challenge and excitement of maze-solving robots with the cloud-based learning system of the Robotarium. We intend to develop an automatic maze table with future remote capabilities to further student learning and engagement. By being able to create custom mazes with ATUM RTS, students will have access to a resource that will allow them to practically apply what they are learning in the classroom. The ATUM RTS …
E-Bike Improvements, Reuben M. Eye, Cole Huddleston, Jeffery Scott, Cade Lewis, Ethan Ridenour
E-Bike Improvements, Reuben M. Eye, Cole Huddleston, Jeffery Scott, Cade Lewis, Ethan Ridenour
ATU Research Symposium
No abstract provided.
Applications Of Supercapacitors In Robotic Systems, Charles Davis, Zachary Giese, Joseph Gober, Samuel Grisham, Avery Mahan
Applications Of Supercapacitors In Robotic Systems, Charles Davis, Zachary Giese, Joseph Gober, Samuel Grisham, Avery Mahan
ATU Research Symposium
This project explores the utilization of a bespoke supercapacitor system to energize and propel a robot across various challenging courses. The custom supercapacitor setup serves as the primary power source, providing rapid charging capabilities and high energy density. The research investigates the integration of this innovative power solution into the robot's design, aiming to optimize its performance and endurance in competitive environments.
Advisync: A Dynamic Academic Course Scheduler, Spencer M. Anderson, Wilson Escobar, Devin Scott Sandlin, Nathan Patrick Doyle
Advisync: A Dynamic Academic Course Scheduler, Spencer M. Anderson, Wilson Escobar, Devin Scott Sandlin, Nathan Patrick Doyle
ATU Research Symposium
Academic advising at universities can be a tedious and disorganized process for both students and advisors. Each advisor may have several dozen advisees to manage each semester, and each individual student has unique sets of classes they need to take to graduate. This might lead to scheduling errors. These errors can put the student behind in their degree, thus extending the time it takes for them to graduate past financial aid periods and delay their entry into the workforce. To address this issue, we create AdviSync. It is a tool for both students and advisors that aims to provide a …
Pyroscan: Wildfire Behavior Prediction System, Derek H. Thompson, Parker A. Padgett, Timothy C. Johnson
Pyroscan: Wildfire Behavior Prediction System, Derek H. Thompson, Parker A. Padgett, Timothy C. Johnson
ATU Research Symposium
During a wildfire, it is of the utmost importance to be updated about all information of the wildfire. Wind speed, wind direction and dry grass often works as fuel for the fire allowing it to spread in multiple directions. These different factors are often issues for any firefighting organization that is trying to help fight the fire. An uncontrolled wildfire is often a threat to wildlife, property, and worse, human and animal lives. In our paper, we propose an artificial intelligence (AI) powered fire tracking and prediction application utilizing Unmanned Aerial Vehicles (UAV) to inform fire fighters regarding the probability …
Promoting Electric Propulsion (Pep) For Small Craft, Robert Manatt, Brad Fletcher, Hector Campos, Johnathon Poindexter, Quinn Reynolds
Promoting Electric Propulsion (Pep) For Small Craft, Robert Manatt, Brad Fletcher, Hector Campos, Johnathon Poindexter, Quinn Reynolds
ATU Research Symposium
The Promoting Electric Propulsion (PEP) For Small Craft event is a competition held every year by the American Society of Naval Engineers (ASNE) and the United States Coast Guard (USCG), and this coming year’s event is being held in Virginia Beach. It is aimed at inspiring students from universities all over the country and allowing them to design innovative fully electrically propelled boats, present their designs and builds, and race them against each other to show off their finished projects. Using fully electric propulsion systems for marine use can be challenging, but if done right they can provide a clean, …
Ambulatory Electrocardiographic Monitoring, Genesis V. Garay, Arath Sanchez
Ambulatory Electrocardiographic Monitoring, Genesis V. Garay, Arath Sanchez
ATU Research Symposium
•Cardiovascular disease (CVD) is the world's leading cause of death, especially prevalent in low- and middle-income countries. Up to 80% of premature heart attacks and strokes are preventable. •Current ambulatory electrocardiographic (ECG) monitors, while effective in diagnosing heart rhythm issues, are often cost-prohibitive and have limitations like short monitoring periods, user-initiated recording, and offline data analysis. •This poster summarizes the foundation of the creation of a monitoring system that attempts to address these issues.
League Of Learning: Deep Learning For Soccer Action Video Classification, Musfikur Rahaman
League Of Learning: Deep Learning For Soccer Action Video Classification, Musfikur Rahaman
ATU Research Symposium
The field of sports video analysis using deep learning is rapidly advancing. Proper classification and analysis of sports videos are essential to manage the growing sports media content. It offers numerous benefits for the media, advertising, analytics, and education sectors. Soccer, also known as football, worldwide, is among the most popular sports. This research study used a deep learning-based approach for soccer action detection. Deep learning has become a popular machine learning technique, especially for image and video classification. We have used the SoccerAct dataset, which consists of ten soccer actions like corner, foul, freekick, goal kick, long pass, on …
Analyzing The Impact Of Socioeconomic Factors On Cancer Clinical Trials Accessibility In The U.S. Using Machine Learning, Krysta L. Ray, Hiromi Honda
Analyzing The Impact Of Socioeconomic Factors On Cancer Clinical Trials Accessibility In The U.S. Using Machine Learning, Krysta L. Ray, Hiromi Honda
ATU Research Symposium
While cancer impacts all segments of the United States population, specific groups experience a disproportionate burden of the disease due to social, environmental, and economic disadvantages. This research examines the correlation between socioeconomic factors and the accessibility of cancer clinical trials across U.S. counties, employing a comprehensive dataset, County-Level Socioeconomic and Cancer Clinical Trial Data from Noah Ripper, and advanced machine-learning techniques. Our findings, derived from regression analysis and machine learning models like gradient boosting, highlight significant disparities in trial availability linked to socioeconomic indicators, including poverty rates, population estimates, median income, incidence rates, and mortality rates. Many regression models …
Multi-Rotor Hexicopter, Corbin G. Beard, Payton Riddle, John Washburn, Nate Burckhartzmeyer, Alejandro Gamez
Multi-Rotor Hexicopter, Corbin G. Beard, Payton Riddle, John Washburn, Nate Burckhartzmeyer, Alejandro Gamez
ATU Research Symposium
The Multi-Rotor Hexicopter is an original design for an eighteen motor, hydrogen fuel cell powered drone. After initial success with the hydrogen fuel cell powered drone created by previous students, our goal was take their success and create a much larger drone that could be controlled both from the ground and in the air. Our design was based on a drone created by the company Lift Aircraft. The drone is separated into four components that were designed in Autodesk Inventor. The bottom, known as the sled, is used for the storage of the two hydrogen fuel tanks. The second section, …
Hybrid Pv-Teg System, Anna-Marie Pesaresi, Paige Woolheater, Chance Eoff, Nicholas Colburn
Hybrid Pv-Teg System, Anna-Marie Pesaresi, Paige Woolheater, Chance Eoff, Nicholas Colburn
ATU Research Symposium
This research is focused on an innovative approach to improving the efficiency of a well- established renewable energy source. Solar cells are becoming more prominent as the power industry is shifting towards using more clean energy sources. Photovoltaic (PV) solar cells can only absorb a portion of the irradiance spectrum. The portion that is not absorbed raises the temperature of the system. The efficiency of PV cells drastically decreases as the temperature of the module rises and more energy is lost in the form of heat waste. Thermoelectric generator (TEG), when combined with PV cell, thrives off of the PV …
Enhancing Disease Detection In South Asian Freshwater Fish Aquaculture Through Convolutional Neural Networks, Hayin Tamut, Musfikur Rahaman, Dr. Robin Ghosh
Enhancing Disease Detection In South Asian Freshwater Fish Aquaculture Through Convolutional Neural Networks, Hayin Tamut, Musfikur Rahaman, Dr. Robin Ghosh
ATU Research Symposium
Aquaculture expansion necessitates innovative disease detection methods for sustainable production. This study investigates the efficacy of Convolutional Neural Networks (CNNs) in classifying diseases affecting South Asian freshwater fish species. The dataset comprises 1747 images representing 7 class, healthy specimens and various diseases: bacterial, fungal, parasitic, and viral. The CNN architecture includes convolutional layers for feature extraction, max-pooling layers for down sampling, dense layers for classification, and dropout layers for regularization. Training employs categorical cross-entropy loss and the Adam optimizer over 30 epochs, monitoring both training and validation performance. Results indicate promising accuracy levels, with the model achieving 92.14% and test …
Anomaly Detection With Spiking Neural Networks (Snn), Shruti Bhandari, Vyshnavi Gogineni
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 …
College Of Business Prospective Students Application, Caden Bewley, Joseph Morton, Brayden Reddin, Marvin Martinez, Ashlyn Ward
College Of Business Prospective Students Application, Caden Bewley, Joseph Morton, Brayden Reddin, Marvin Martinez, Ashlyn Ward
ATU Research Symposium
The College of Business wanted a webpage that makes applying to one of their majors more user-friendly. Currently, incoming freshmen tend to choose the wrong major as the application process can be confusing. They needed to reduce the redundancy of inputting information, so they asked for the application on their webpage to auto-fill on Arkansas Tech University's application webpage.
Demonstration Of Hydrogen Combustion Properties, Stephen M. Baker
Demonstration Of Hydrogen Combustion Properties, Stephen M. Baker
ATU Research Symposium
The Hydrogen Flame Demonstration project encompasses the design, fabrication, and usage of a pressure vessel system with the goal of demonstrating the hazardous flammable properties that are associated with gaseous hydrogen. This project was completed as a part of a 16-week internship at the NASA White Sands Test Facility in Las Cruces, New Mexico during the Spring of 2022. As the interest of technologies using hydrogen as a fuel, or otherwise, increases, informing and setting ‘best practices’ for use of pressure systems containing hydrogen becomes increasingly necessary. Gaseous hydrogen is highly flammable with the presence of air or oxygen. Since …
Rc Flying Car, Andrew Hood, Ethan Jacobs, Nicholas Jones, Joshua Phifer
Rc Flying Car, Andrew Hood, Ethan Jacobs, Nicholas Jones, Joshua Phifer
ATU Research Symposium
For this project, the goal is to build a 3D printed RC flying car with actuating wings and to show the modularity and adaptability of using 3D printing to create a multifunctional RC flying car. The goal with the actuating wings is to showcase how adaptable and modular 3D printing is and to also have a drivable car. Also, with a multifunctional 3D printed flying car, an end user could customize the flying car to their desired needs or wants. The reason for choosing to build a flying car instead of just a plane or a car is that it …