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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

In this paper, a new analytical method is introduced to find the general solution of linear partial differential equations. In this method, each Laplace transform (LT) and Sumudu transform (ST) is used independently along with canonical coordinates. The strength of this method is that it is easy to implement and does not require initial conditions.

Background: Oral cancer is a highly lethal and disfiguring disease. Squamous cell carcinoma of the oral cavity constitutes about 90% of all oral malignancies. The aims of the study was to achieve an epidemiological description of the oral squamous cell carcinoma in Iraq in general and in Iraqi governorates except Kurdistan region retrospectively during period 2001-2013 Materials and Methods: Data were collected from department of oral and maxillofacial pathology, college of dentistry, university of Baghdad, Nuclear medicine and radiotherapy hospital, Iraqi cancer registry center, Main hospitals in Baghdad and Iraqi governorates, Private labs. for histopathological examinations. The descriptive and inferential statistical methods were used

Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. One of the main advantages of using these techniques is that they require no knowledge or gradient information about the response surface. The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically reduces the number of bits reqyuired to store the poulation and has a faster convergence speed. In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). Simulation results