Machine Learning-Based Management of Electric Vehicles Charging: Towards Highly-Dispersed Fast Chargers by Mostafa Shibl (18810412)

“…LSTM provided the best results with an accuracy of 95% for predicting the most appropriate power rating (PR) for EVCS, followed by RF, DT, DNN, SVM, KNN, and NB. Additionally, LSTM was also the model with the smallest error rate, at a value of ±0.7%, followed by RF, DT, KNN, SVM, DNN, and NB. …”

Occurrence and removal characteristics of phthalate esters from bottled drinking water using silver modified roasted date pits by Fedae A. Alhaddad (14152161)

“…The removal percentage was increased from 90 to 99% by increasing the temperature from 30 to 50 °C and then decreased to 92.3% at 60 °C.</p> <h2>Conclusion</h2> <p>RODP was successfully used as an effective adsorbent for phthalate esters removal from drinking water. …”