ABSTRACT Background: Dental anomalies of teeth are major issue that contributes to dental problems encountered in general practice. The aim of this study is to measure the prevalence of dental anomalies and the associated etiological factors among 15 years old students in Basrah city –Iraq. Materials and methods: The total sample composed of 1000 students (435 males and 565 females) from urban area selected randomly from different high schools in the city. Diagnosis of dental anomalies were recorded by present or absent, diagnosis and recording of enamel defects were done according to the criteria of WHO (1997). Results: The prevalence of hypodontia was 4.6%, Females have higher prevalence than males (5.8% females and 3.0% males), ta

The genus of Chrysobothris Eschscholtz, 1829 is one of the most diverse and widespread genera of the family Buprestidae of some 700 described species distributed throughout the world. In Iraq, particularly in the Kurdistan region, about 4 species had been recorded so far, many of these species are sympatric, share larval host plants, and are difficult to reliably separate morphologically. The current study investigates species limits and relationships among the recognized species occurring within the Erbil Province; mitochondrial cytochrome C oxidase (COX I) molecular analysis confirmed the monophyly of two Chrysobothris species, Ch. affinis (Fabricius, 1794) and Ch. chrysostigma (Linnaeus, 1758). Implications of the resultant larval mor

Abstract The wavelet shrink estimator is an attractive technique when estimating the nonparametric regression functions, but it is very sensitive in the case of a correlation in errors. In this research, a polynomial model of low degree was used for the purpose of addressing the boundary problem in the wavelet reduction in addition to using flexible threshold values in the case of Correlation in errors as it deals with those transactions at each level separately, unlike the comprehensive threshold values that deal with all levels simultaneously, as (Visushrink) methods, (False Discovery Rate) method, (Improvement Thresholding) and (Sureshrink method), as the study was conducted on real monthly data represented in the rates of theft crimes f

Abstract:

                The internal audit is considered the safety valve for senior management in all institutions. It aims to protect property, and raise the efficiency and effectiveness of the administrative performance, by following up on compliance with laws and instructions and the application of regulations in a way that increases the administrative performance of the department. The internal audit is possible to determine Weaknesses or imbalances in the administrative performance. To achieve this goal, an analytical descriptive methodology was adopted. The Baghdad Health Department / Al-Rosana was considered as society for this s

In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

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