Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 4 of 4
Full-Text Articles in Education
Volume 10 Full Text, Bjur Staff
Volume 10 Full Text, Bjur Staff
Butler Journal of Undergraduate Research
No abstract provided.
Stream Gauging: Investigating The Flow Rate And Residence Time In Laguna Bacalar, Mexico, Elizabeth J. Kowalczyk
Stream Gauging: Investigating The Flow Rate And Residence Time In Laguna Bacalar, Mexico, Elizabeth J. Kowalczyk
Butler Journal of Undergraduate Research
Stream gauging is a standard tool used to measure the flow rate of various bodies of water. Knowing the flow rate of a body of water allows for the residence time of a body of water to be calculated. Currently, there is very little information regarding the flow rate and residence times of Laguna Bacalar. This system has been observed hydrologically consistently only in the past 6 years. In this study, 13 stream-gauging locations of interest were identified and gauged for their respective flow rates using the midsection method. Once the flow rates were acquired, maps depicting the Laguna Bacalar …
Table Of Contents And Front Matter, Bjur Staff
Table Of Contents And Front Matter, Bjur Staff
Butler Journal of Undergraduate Research
No abstract provided.
Enhanced Breast Cancer Tumor Classification Using Mobilenetv2: A Detailed Exploration On Image Intensity, Error Mitigation, And Streamlit-Driven Real-Time Deployment, Aaditya Surya, Aditya Keshary Shah, Subash Tarun Sasikumar, Jarnell Kabore
Enhanced Breast Cancer Tumor Classification Using Mobilenetv2: A Detailed Exploration On Image Intensity, Error Mitigation, And Streamlit-Driven Real-Time Deployment, Aaditya Surya, Aditya Keshary Shah, Subash Tarun Sasikumar, Jarnell Kabore
Butler Journal of Undergraduate Research
This research introduces a sophisticated transfer learning model based on Google’s MobileNetV2 for breast cancer tumor classification into normal, benign, and malignant categories, utilizing a dataset of 1576 ultrasound images (265 normal, 891 benign, 420 malignant). The model achieves an accuracy of 0.82, precision of 0.83, recall of 0.81, ROC-AUC of 0.94, PR-AUC of 0.88, and MCC of 0.74. It examines image intensity distributions and misclassification errors, offering improvements for future applications. Addressing dataset imbalances, the study ensures a generalizable model. This work, using a dataset from Baheya Hospital, Cairo, Egypt, compiled by Walid Al- Dhabyani and colleagues (2020), emphasizes …