Realizing the full potential of wireless sensor networks (WSNs) highlights many design issues, particularly the trade-offs concerning multiple conflicting improvements such as maximizing the route overlapping for efficient data aggregation and minimizing the total link cost. While the issues of data aggregation routing protocols and link cost function in a WSNs have been comprehensively considered in the literature, a trade-off improvement between these two has not yet been addressed. In this paper, a comprehensive weight for trade-off between different objectives has been employed, the so-called weighted data aggregation routing strategy (WDARS) which aims to maximize the overlap routes for efficient data aggregation and link cost

In the present study, an attempt has been made to study the change in water quality of the river in terms of turbidity during lockdown associated with COVID-19. Iraq announced the longest-ever lockdown on 25 March 2020 due to COVID-19 pandemic. 

In the absence of ground observations, remote sensing data was adopted, especially during this period. The change in the visible region's spectral reflectance of water in part of the river has been analyzed using the Landsat 8 OLI multispectral remote sensing data at Tigris River, Salah al-Din province (Bayji / near the refinery), Iraq. It was found that the green and red bands are most sensitive and can be used to estimate turbidity. Furthermore, the temporal variation in turbidity was a

A band rationing method is applied to calculate the salinity index (SI) and Normalized Multi-Band Drought Index (NMDI) as pre-processing to take Agriculture decision in these areas is presented. To separate the land from other features that exist in the scene, the classical classification method (Maximum likelihood classification) is used by classified the study area to multi classes (Healthy vegetation (HV), Grasslands (GL), Water (W), Urban (U), Bare Soil (BS)). A Landsat 8 satellite image of an area in the south of Iraq are used, where the land cover is classified according to indicator ranges for each (SI) and (NMDI).

       This paper uses Artificial Intelligence (AI) based algorithm analysis to classify breast cancer Deoxyribonucleic (DNA). Main idea is to focus on application of machine and deep learning techniques. Furthermore, a genetic algorithm is used to diagnose gene expression to reduce the number of misclassified cancers. After patients' genetic data are entered, processing operations that require filling the missing values using different techniques are used. The best data for the classification process are chosen by combining each technique using the genetic algorithm and comparing them  in terms of accuracy.

In our research, several different Statics solutions have been implemented in the processing of seismic data in the south of Iraq for (2D) line seismic survey (AK18)  of Abu-khama project with length 32.4 Km and their corresponding results have been compared in order to find optimum static solutions. The static solutions based on the tomographic-principle or combining the low frequency components of field statics with high frequency ones of refraction statics can provide a reasonable static solution for seismic data in the south of Iraq. The quality of data was bad and unclear in the seismic signal, but after applying field statics there is an enhancement of data quality. The Residual static correction improved the qualities of seis

The gravity and magnetic data of Tikrit-Kirkuk area in central Iraq were considered to study the tectonic situation in the area. The residual anomalies were separated from regional using space windows method with space of about 24, 12 and 10km to delineate the source level of the residual anomalies. The Total Horizontal Derivative (THD) is used to identify the fault trends in the basement and sedimentary rocks depending upon gravity and magnetic data. The identified faults in the study area show (NW-SE), less common (NE-SW) and rare (N-S) trends. Some of these faults extending from the basement to the upper most layer of the sedimentary rocks. It was found that the depth of some gravity and magnetic source range 12-13Km, which confirm th

    It is so much noticeable that initialization of architectural parameters has a great impact on whole learnability stream so that knowing  mathematical properties of dataset results in providing neural network architecture a better expressivity and capacity. In this paper, five random samples of the Volve field dataset were taken. Then a training set was specified and the persistent homology of the dataset was calculated to show impact of data complexity on selection of multilayer perceptron regressor (MLPR) architecture. By using the proposed method that provides a well-rounded strategy to compute data complexity. Our method is a compound algorithm composed of the t-SNE method, alpha-complexity algorithm, and a persistence barcod

Abstract:

The current research included " Diagnosis of the reality of the gap for the requirements of Business Continuity Management System According to International Standard (ISO 22301: 2012) in Midland Refineries Company (Daura Refinery) " , for development of an administrative system for Business Continuity is considered a priority in the present day, and in the light of the organizations dependence on computers and information technology in work and communication with others . the international legitimacy (represented by the international organization for standardization (ISO)) remains the basis for matching and commitment , and the importance of the application of Business Continuity Management Syst