In this paper a new structure for the AVR of the power system exciter is proposed and designed using digital-based LQR. With two weighting matrices R and Q,  this method produces an optimal regulator that is used to generate the feedback control law. These matrices are called state and control weighting matrices and are used to balance between the relative importance of the input and the states in the cost function that is being optimized. A sample power system composed of single machine connected to an infinite- bus bar (SMIB) with both a conventional and a proposed Digital AVR (DAVR) is simulated. Evaluation results show that the DAVR damps well the oscillations of the terminal voltage and presents a faster respo

Wrong behavioral deviations among youth witnessed an obvious growing, some of these deviations are, robbery, drug and internet addiction, and smoking. Additionally, intellectual extremism and the disrespect of the traditions and genuine customs, In light of this issue, the research aims to shed light on the educational and preventative role of the woman in protecting and immunizing children from the wrong behavioral deviations. The woman has a significant and influential role in the society in general and in her family, in particular to the responsibility lies on her. The research shed light on the manifestations of behavioral deviation in children and the mechanisms of prevention and treatment. The research concluded with a set of recom

The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA