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

Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval

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

      In this paper we study and design two feed forward neural networks. The first approach uses radial basis function network and second approach uses wavelet basis function network to approximate the mapping from the input to the output space. The trained networks are then used in an conjugate gradient algorithm to estimate the output. These neural networks are then applied to solve differential equation. Results of applying these algorithms to several examples are presented

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

In this study, the genus Xylocopa Latreille, 1802 (Hymenoptera: Apidae) was revised. There were 4 species registered in our investigations: X. hottentotta Smith, 1854; X. olivieri Lepeletier, 1841; X. pubescens Spinola, 1838 and X. valga Gerstäcker, 1872, the first species was described as being found for the first time for the insect fauna of Iraq, which were obtained from Solanum melogena L. flowers. Key to the species was constructed and supported by figures of the main diagnostic characters and some morphological features, illustrated and compared with other species, which are recorded in the current survey.

The present study aims to investigate the seroprevalence rate of Toxoplasma gondii infection and its relation to some demographic factors among males in Duhok province/Iraq. A total of 424 random blood samples were collected from the male population of different ages (18-60) years and different social-economic classes. Out of 424 samples examined, 108 (25.47%) were seropositive to the anti- T. gondii antibodies; 88 (20.75%) were found seropositive for IgG, while 20 (4.72%) samples were seropositive for IgM. Regarding occupation, the highest percentage for chronic toxoplasmosis was reported in workers followed by policemen and pensioners at rates of 23.96%, 23.6%, and 23.07%, respectively. The age group 18-30 y

Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models

339 individuals , were sorted from 22 samples collected from three sites in Tigris River including , Al- Sarafiya district (S1), Al- Jaderiyah district (S2) and Al-Za'afaraniya district (S3), in addition to one site in the irrigation canal of the Al- Jaderiyah campus of the University of Baghdad (S4) , and in Al- Jeish canal(S5) east Baghdad. The sorting results revealed that the highest number of individuals of 102 was recorded at S4, whereas the lowest number of 24 individuals was recorded at S2. Regarding the sites, site S4 was the richest site with 30% of the total number represented 16 species, while each of S3 and S5 had 8 species only with 17.11% and 28.60% of the total individuals number respectively. The values of Jaccared Sim