The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est

A detailed systematic study of calcareous nannofossils was carried out for the Jaddala Formation in (Aj-10) well, Central Iraq. Seventy one species belong to twenty four genera of calcareous nannofossils were identified including sixty two of them were previously named and nine species were identified for the first time and they would not be given names until more information is obtained in the future to support this identification.
It is a recorded of five biostratigraphic zone, which suggested the age of the Jaddala Formation to be of early to late Eocene. The recorded biozone includes the following: Reticulofenestra dictyoda (Deflandre in Deflandre & Fert, 1954) Stradner & Edwards, 1968 Partial Range Biozone (CNE 5); Discoa

       This study aims to assess the formation evaluation of the Jeribe Formation in Hamrin oilfield. The present study involved four selected wells of (Early- Mid Miocene) Jeribe Formation in Hamrin structure-Allas field; HR-2, HR-8, HR-9, and HR-16 located North of Iraq. The work deals with the available data that includes the most required information to improve such studies. Techlog Software V.2015 was used to carry out a reliable calculation of petrophysical properties utilizing conventional logs to determine the reservoir characteristics (lithology, porosity, and saturation). The computed CPI (software resulted) based on log information divided the Jeribe reservoir into two reservoir units (Jr-1 and Jr

The research dealt with the reservoir division for Upper Shale Member from Zubair formation in Luhais field, Where it was divided into six units of reservoir and non-reservoir, including the main reservoir unit 1C, which is the subject of research in this study, and studied in terms of thickness and lithology.                                                                       

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I n  this  paper ,we 'viii  consider  the density  questions  associC;lted with  the single  hidden layer feed forward  model. We proved  that a FFNN   with   one   hidden   layer  can   uniformly   approximate   any continuous  function  in C(k)(where k is a compact set in R11 ) to any required accuracy.

However, if the set of basis function is dense then the ANN's can has al most one hidden layer. But if the set of basis function  non-dense, then we  need more  hidden layers. Also, we have shown  that there exist  localized functions and that there is no t

The middle Cenomanian – early Turonian Mishrif Formation, a major carbonate reservoir unit in southern Iraq, was studied using cuttings and core samples and wireline logs (gamma‐ray, density and sonic) from 66 wells at 15 oilfields. Depositional facies ranging from deep marine to tidal flat were recorded. Microfacies interpretations together with wireline log interpretations show that the formation is composed of transgressive and regressive hemicycles. The regressive hemicycles are interpreted to indicate the progradation of rudist lithosomes (highstand systems tract deposits) towards distal basinal locations such as the Kumait, Luhais and Abu Amood oilfield areas. Transgressive hemicycles (transgressive systems tract deposits)

Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,