Activities associated with mining of uranium have generated significant quantities of waste materials containing uranium and other toxic metals. A qualitative and quantitative study was performed to assess the situation of nuclear pollution resulting from waste of drilling and exploration left on the surface layer of soil surrounding the abandoned uranium mine hole located in the southern of Najaf province in Iraq state. To measure the specific activity, twenty five surface soil samples were collected, prepared and analyzed by using gamma- ray spectrometer based on high counting efficiency NaI(Tl) scintillation detector. The results showed that the specific activities in Bq/kg are 37.31 to 1112.47 with mean of 268.16, 0.28 to 18.57 with

Objectives: To assess the premenstrual syndrome among the working women in Baghdad City.
Methodology: A cross-sectional analytic study, using probability sampling cluster (multi-stage) sampling of
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designed and consisted of (4) parts, including demographic, reproductive, menstrual cycle characteristics, and
premeustmual syndrome symptoms. Content validity and reliability of the questionnaire were detemined by
conducting a pilot study. Descriptive and inferential statistical procedures were used to analyze the data.
Results: The results of the study revealed that the age of women ranged betwee

The alluvial fan of Mandali located between latitude 30˚45’00” N longitude 45˚30’00” E in east of Diyala Governorate, Iraq. Thirty-five wells were identified in the study area with average depth of 84 m and estimated area of 21550 ha. A three-dimensional conceptual model was prepared by using GMS program. From wells cross sections, four geological layers have been identified. The hydraulic conductivity of these layers was calculated for steady state condition, where the water levels for nine wells distributed over the study area were observed at same time. Afterward, PEST facility in the GMS was used to estimate the aquifer hydraulic characteristics. Other characteristics such as storage coefficient and specific yield have

     This research examines the quantitative analysis to assess the efficiency of the transport network in Sadr City, where the study area suffers from a large traffic movement  for the variability of traffic flow and intensity at peak hours as a result of inside traffic and outside of it, especially in the neighborhoods of population with  economic concentration.                                                           &n

It is believed that Organizations around the world should be prepared for the transition to IPv6 and make sure they have the " know how" to be able to succeed in choosing the right migration to start time. This paper focuses on the transition to IPv6 mechanisms. Also, this paper proposes and tests a deployment of IPv6 prototype within the intranet of the University of Baghdad (BUniv) using virtualization software. Also, it deals with security issues, improvements and extensions of IPv6 network using firewalls, Virtual Private Network ( VPN), Access list ( ACLs). Finally, the performance of the obtainable intrusion detection model is assessed and compared with three approaches.

Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered