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Full-Text Articles in Computer Engineering
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 …
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 …
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 …
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 …
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.
Graduate Faculty Directory, Christopher Andrews, Cody Mckenney, Drake Traylor, Joseph Freeman
Graduate Faculty Directory, Christopher Andrews, Cody Mckenney, Drake Traylor, Joseph Freeman
ATU Research Symposium
The Graduate College would like to update the current faculty search page to filter search results by Department and Research in addition to Name. With the current system, a person who wanted to find an unknown professor based upon a department or an interest in research topic would be unable to search because the only option is to type the professor's name. We have created a website linked to a database containing graduate faculty that is able to search by name, filter by department, and search through the professors' listed research topics. This website will be much more useful and …