The objective of this work is to investigate the performance of a conventional three phase induction motor supplied by unbalanced voltages. An effort to study the motor steady state performance under this disturbance is introduced. Using per phase equivalent circuit analysis with the concept of symmetrical components approach, the steady state performance is theoretically calculated. Also, a model for the induction motor with the MATLAB/Simulink SPS tools has been implemented and steady state results were obtained. Both results are compared and show good correlation as well. The simulation model is introduced to support and enhance electrical engineers with a complete understanding for the steady state performance of a fully loaded induc

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining

Discussed the research variables are important, privatization options and strategic analysis of the external environment, and that the purpose of the research is the trade-off between privatization options and choose the most appropriate alternative in proportion to the external environment, the research aims to determine the privatization the most appropriate option for companies and public contracting, showing the importance of the study provide the privatization of public companies as a strategy can all its way public sector organizations from the transfer of work practices or private sector organizations and mechanisms to it as contributing to improving the level of skills Develop the current and future level of performance,

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

Photodynamic Action (PDA) by using appropriate wavelength of irradiation conjugated with porphyrin derivatives is a powerful mechanism of tumor destruction. Hematoporphyrin derivative has been shown to selectively localize in neoplastic cells and then cause destruction of them by generation of singlet oxygen when activated by low power He-Ne laser. Light which used in this study has been emitting from this laser has a wavelength equal to 632.8 nm (red light). Doses of laser had been varied from 3.6 J/cm2 to 14.4 J/cm2 . The beam of laser adjusted with a modified tissue culture plate. Cell lines had exposed to Hematoporphyrin D (HpD) for 24 hours before Laser exposure, their concentrations were varied from 5 µg/ml to 80 µg/ml. Resu