| Abstrakt: |
This paper introduces the concept of a smart menstrual cup, incorporating advanced technology to address challenges associated with traditional menstrual health management methods. The proposed method, Hybrid Bidirectional Encoder Generative Transformer based Bees Search (Hybrid BEGT-BS), aims to enhance the longevity and reliability of smart menstrual cups. The Generative Pre-trained Transformer (GPT) is employed to extract key information and determine emotional tones related to menstruation, while the Bidirectional Encoder Representations from Transformer (BERT) classifies menstrual-related data such as cycle tracking, hygiene, and symptoms. Further different validation metrics such as F1-score, specificity, Area Under the Curve-Receiver Operating Characteristic (AUC-ROC), Mean Squared Error (MSE), recall, energy consumption, accuracy, and precision are employed to assess the method's effectiveness. From the comparative results it demonstrates the superior performance of the Hybrid BEGT-BS method in enhancing the performance of smart menstrual cups. [ABSTRACT FROM AUTHOR] |
