- Volume 10, Number 3 (2023)
CRUNCHING THE NUMBERS: COMPARATIVE ANALYSIS OF CLASSIFICATION MODELS FOR ACCURATE GRADUATION PREDICTIONS
Abdullah A Al-Majardh
Data mining, also known as knowledge discovery in databases (KDD), involves extracting valuable, previously unknown information from large data volumes. This field is gaining significant importance in the educational sector, particularly within universities. This paper aims to predict students' final year grades using classification-based data mining techniques, assessing the performance of three algorithms – Naïve Bayes, J48, and SVM – to improve educational quality. By comparing these classification algorithms, we can evaluate their current efficiency and effectiveness. Various performance measures are utilized to compare the results from these classifiers. Our findings indicate that the J48 classifier achieves the highest accuracy...
CURRENTS OF CORRECTION: UNMASKING THERMAL VOLTAGE CONVERTERS (TVCS) CORRECTION FACTORS VIA ELECTRICAL SIMULATION AND MODELING
Dr. Mohamed S. Abdel-Meguid, Ahmed M Hassan
Thermal voltage converters (TVCs) are essential components in various industries, including power generation, aerospace, and automotive applications, due to their ability to measure AC voltage accurately. However, TVCs are inherently susceptible to errors that can arise from factors such as temperature, frequency, and waveform. Consequently, determining correction factors is imperative to improve the accuracy and reliability of TVC measurements. This study aims to investigate the correction factors for TVCs through electrical simulation and modeling. By employing state-of-the-art electrical simulation tools and advanced modeling techniques, a detailed analysis of the factors affecting TVC performance will be conducted. This analysis will enable...