KHAOULA REFAAT

• Study of the reaction stage between phosphoric acid and phosphate rock in the TSP production process.
• Identification of the parameters influencing the free acid percentage, corresponding to the unreacted phosphoric acid in the reaction slurry.
• Processing and analysis of industrial data to improve prediction accuracy and model reliability.
• Development of a predictive model for free acid percentage using Machine Learning techniques.
• Implementation of an optimization approach for the reaction process to enhance the quality and stability of the final product.
• Visualization of results and creation of an interactive interface with Streamlit to facilitate model use by the teams.

• Development of a U-NetR model in Python using PyTorch for precise brain tumor segmentation on MRI images.
• Comprehensive data preprocessing including normalization, augmentation, and preparation for model training.
• Hyperparameter tuning to improve the accuracy and quality of the segmentations.
• Model evaluation and analysis of results to enhance performance.

• Development of a web project management application using Laravel, Bootstrap, and MySQL.
• Enables users to create, assign, and track tasks efficiently, enhancing team collaboration and project monitoring.

• Management of administrative tasks including data entry, responding to visitor inquiries, and directing them to the appropriate department.
• Development of a web application for employee management using HTML, CSS, JavaScript, PHP, and MySQL.