BN Rashid, Nasaq, 2015

In the present paper, an eco-epidemiological model consisting of diseased prey consumed by a predator with fear cost, and hunting cooperation property is formulated and studied. It is assumed that the predator doesn’t distinguish between the healthy prey and sick prey and hence it consumed both. The solution’s properties such as existence, uniqueness, positivity, and bounded are discussed. The existence and stability conditions of all possible equilibrium points are studied. The persistence requirements of the proposed system are established. The bifurcation analysis near the non-hyperbolic equilibrium points is investigated. Numerically, some simulations are carried out to validate the main findings and obtain the critical values of th

This paper proposes a new structure of the hybrid 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. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

Abstract This study seeks to deal academically with how the EU treats clandestine immigration, through adopting a purley security approach, based on the European understanding of security threats posed to the security of communities and States in EU at all levels. So they agreed upon criminalizing this threat within the bloc while using repressive tools and steps to limit illegal immigrants flow to European territories. Accordingly, the EU gave the phenomen a security character. So it takes it from low politics level , that of employment and economic field to that of high politics, as a new security problem lying within a new security language embraced by ruling European elites, in other words EU touched on this issue as a speech act emp

The present study aimed to determine the frequency of ABO and Rh blood group antigens among Sabians (Mandaeans) population. This paper document the frequency of ABO and Rh blood groups among the Sabians (Mandaeans) population of Iraq.There is no data available on the ABO/Rh (D) frequencies in the Sabians (Mandaeans) population. Total 341 samples analyzed; phenotype O blood type has the highest frequency 49.9%, followed by A 28.7%, and B 13.8% whereas the lowest prevalent blood group was AB 7.6%. The overall phenotypic frequencies of ABO blood groups were O>A>B>AB. The allelic frequencies of O, A, and B alleles were 0.687, 0.2 and 0.1122 respectively. Rhesus study showed that with a percentage of 96.2% Rh (D) positive is by far the mo

Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN

Abstract

This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model