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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS) Indonesian Journal of Electrical Engineering and Computer Science
Nashaat M. Hussain Hassan
Fayoum University
Control & Systems Engineering Electrical & Electronics Engineering

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Analysis and comparison of single-phase induction motor operation from single- and two-phase power sources using MATLAB simulation results Mohamed Adel Esmaeel; Nashaat M. Hussain Hassan
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i3.pp1380-1389

Abstract

Single phase induction motor (SPIM) has zero torque, this motor has many types and the main objective is to find the starting torque of the motor. This is done by providing auxiliary coils that are mechanically separated or weakened after 75% of the engine speed. The real problem here is that these auxiliary windings occupy a third of the iron core of the motor, and when they are separated or weakened, the capacity of the iron core is not fully used and the main windings must withstand the rated load current alone which shortens the life of the motor and reduces the hours of continuous operation of the motor. In this paper, a single-phase motor is fed from a single-phase power source and again from a two-phase power source, so that the auxiliary coils are not separated after 75% of the motor's speed and have a continuous role in the motor's operation. The torque and current flow in the motor are compared in both cases. Due to the rarity of the two-phase power supply in nominal uses, it can be supplied by a full bridge inverter. This comparison was provided by steady-state analysis and the results of MATLAB Simulink.
Quality of performance evaluation of ten machine learning algorithms in classifying thirteen types of apple fruits Nashaat M. Hussain Hassan; Basma Ramadan Gamal Elshoky; A. M. M. Mabrouk
Indonesian Journal of Electrical Engineering and Computer Science Vol 30, No 1: April 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v30.i1.pp102-109

Abstract

Recently, computer vision technology has become essential for the automatic, accurate, and fast classification of fruits. Actually, there are many challenges in separating the types of fruits that are somewhat similar, such as apples, pears, and peaches. However, the challenges become more difficult if the separation is on different varieties of the same fruit. While the difficulty doubles if the classification takes place with a large number of different varieties of the same fruit. Most of the literature which is presented in this regard, and which is relied on the use of machine learning techniques lacked the following: first; the focus was on certain technologies such as k-nearest neighbor (KNN), support vector machine (SVM) without looking at many other machine learning techniques. Second; the literature was concerned only with measuring the accuracy of the techniques that are used, without looking at the relationship between the accuracy and processing speed (computation times). This manuscript aims to study and analyze the results of measuring accuracy and computation times for ten machine-learning techniques in order to identify and classify thirteen types of apples. After studying and analyzing the results, many observations were made, which will be referred to in the results section.
Co-Authors A. M. M. Mabrouk Basma Ramadan Gamal Elshoky Mohamed Adel Esmaeel