Unlike fault diagnosis approaches based on the direct analysis of current and voltage signals, this paper proposes a diagnosis of induction motor faults through monitoring the variations in motor's parameters when it is subjected to an open circuit or short circuit faults. These parameters include stator and rotor resistances, self-inductances, and mutual inductance. The genetic algorithm and the trust-region method are used for the estimation process. Simulation results confirm the efficiency of both the genetic algorithm and the trust-region method in estimating the motor parameters; however, better performance in terms of estimation time is obtained when the trust-region method is adopted. The results also show the po

         The main objective of this research is to design and select a composite plate to be used in fabricating wing skins of light unman air vehicle (UAV). The mechanical properties, weight and cost are the basis criteria of this selection. The fiber volume fraction, fillers and type of fiber with three levels for each were considered to optimize the composite plate selection. Finite element method was used to investigate the stress distribution on the wing at cruise flight condition in addition to estimate the maximum stress. An experiments plan has been designed to get the data on the basis of Taguchi technique. The most effective parameters at the process to be find out by employing L₉

The objective of this study was tointroduce a recursive least squares (RLS) parameter estimatorenhanced by using a neural network (NN) to facilitate the computing of a bit error rate (BER) (error reduction) during channels estimation of a multiple input-multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system over a Rayleigh multipath fading channel.Recursive least square is an efficient approach to neural network training:first, the neural network estimator learns to adapt to the channel variations then it estimates the channel frequency response. Simulation results show that the proposed method has better performance compared to the conventional methods least square (LS) and the original RLS and it is more robust a

This paper proposes improving the structure of the neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Two learning algorithms are used to adjust the parameters weight of the hybrid neural structure with its serial-parallel configuration; the first one is supervised learning algorithm based Back Propagation Algorithm (BPA) and the second one is an intelligent algorithm n

In this study, the stress-strength model R = P(Y < X < Z)  is discussed as an important parts of reliability system by assuming that the random variables follow Invers Rayleigh Distribution. Some traditional estimation methods are used    to estimate the parameters  namely; Maximum Likelihood, Moment method, and Uniformly Minimum Variance Unbiased estimator and Shrinkage estimator using three types of shrinkage weight factors. As well as, Monte Carlo simulation are used to compare the estimation methods based on mean squared error criteria.  

Background: Glass ionomers have good biocompatibility and the ability to adhere to both enamel and dentin. However, they have certain demerits, mainly low tensile and compressive strengths. Therefore, this study was done to assess consistency and compressive strength of glass ionomer reinforced by different amount of hydroxyapatite. Materials and Methods: In this study hydroxyapatite materials were added to glass ionomer cement at different ratios, 10%, 15%, 20%, 25% and 30% (by weight). The standard consistency test described in America dental association (ADA) specification No. 8 was used, so that all new base materials could be conveniently mixed and the results would be of comparable value and the compressive strength test described by

The twelve samples of agricultural soils from four regions in Al-Najaf governorate with sampling plant with soil. Physical properties of the soil where studied, such as electrical conductivity ranged from (136.33-1070.00)μS/cm^-3, and moisture which ranged between the values (0.39-36.48)%. The chemical analysis of the soil have included the proportion of calcium carbonate the ratio between (44.00-48.00%) has been observed increasing amounts of calcium carbonate in surface models. The pH where results indicate that pH values ​​were close to study models ranged between (6.88-7.42) these values ​​generally within the normal range for the measured pH values ​​of the Iraqi soil. The amount of gypsum ranged betwe