Abstract The DC motor drives one of the high performance drives that still in competition in industrial application, because of its high performance, robustness, and its lower cost compared with AC motor drives.Due to its majority applications, the separately excited DC motor driver is studied. In order to improve, three independent controller design using classical proportional - integral – derivative, linear quadratic regulator and artificial neural network are considered.The Performance of these controllers has been verified through simulation based on MATLAB/SIMULINK software tools. According to the obtained simulation results, it is found that, an artificial neural network can achieve a better transient and steady state response in comparing to the other two design method. Consequently, the superiority of ANN controller over conventional proportional - integral – derivative is demonstrated this shows the superiority of artificial neural network controller over conventional and linear quadratic regulator controllers.
.زينب إبراهيم علي (2014)

Technology is all around us and it’s changing rapidly, expanding Internet access has had huge impacts on everyday lives as people do everything on their phones and computers. The widespread growth in the use of digital computers, have an increasing need to be able to communicate with machines in a simpler manner. One of the main tasks that can simplify communication with machines is speech recognition. In this work, we introduce the Arabic speech commands database that contains six Arabic control order words and Arabic spoken digits. The created database is used to analyze and compare the recognition accuracy and performance of three recognition techniques which are, Wavelet Time Scattering feature extraction with Support Vector Machine (SVM) classifier, Wavelet Time Scattering feature extraction with Long Short-Term Memory (LSTM) classifier, and Mel-Frequency Cepstrum Coefficients (MFCC) feature extraction with K-Nearest Neighbor (KNN) classifier. Finally, the experimental results show that the most accurate prediction of the database commands was 98.1250% given by Wavelet Time Scattering feature extraction and LSTM classifier and the fastest training time for the database was 144 minutes given by MFCC and KNN classifier. arabic 5 English 42
Osama A. Alkishriwo, Lina Tarek Benamer(12-2020)

Experimental investigation has been carried out to study the effect og gamma ray radiations on silicon solar cells. The measured experimental data are compared with the theoretical results obtained by computer simulation programs before and after radiation. P-N junction silicon cell samples were used for the study showing degradation behavior for the output power and the short circuit current with less effect on the open circuit voltage as the radiation doses increases. Enhanced series resistance was added to the solar cell model due to deformation of I –V characteristics resulting from gamma ray radiations. Wide spread spectrum of doses were employed to study the effect of the radiation on the crystal deformation and damages on different parameters of solar cells. Study reveals an improvement in the output power and short circuit current due to post annealing effect of gamma ray radiations. The conclusion consist of suggestions to protect the solar cells in space satellites.
W. ABUGHRES, M. EL-MURADI, H. EL-FITOURI(9-1992)