Transportation network could be considered as a function of the developmental level of the Iraq, that it is representing the sensitive nerve of the economic activity and the corner stone for the implementation of development plans and developing the spatial structure.
The main theme of this search is to show the characteristics of the regional transportation network in Iraq and to determine the most important effective spatial characteristics and the dimension of that effect negatively or positively. Further this search tries to draw an imagination for the connection between network as a spatial phenomenon and the surrounded natural and human variables within the spatial structure. This search aiming also to determine the nature of the regional transportation of Iraq, how it has been developed, what are its characteristics, types, and patterns that have been came from the spatial differentiation in the region to evaluate it spatially and as an indicator for the socio-economic development in the study area(Iraq(
This study aims to explain the purposes of thinking in light of the Holy Qur’an. The study adopted the deductive method by analyzing the meanings of the eighteen thinking verses mentioned in the Holy Qur’an That is by referring to the ancient and contemporary book interpretations and inferring the purposes of thinking from the context of those verses. The study concluded that there are seven main purposes, for thinking in the light of the Holy Qur’an, are understanding the universal regulations, contemplating the social codes, inferring, extracting maxims and meanings from the Qur’anic proverbs, analyzing the situation objectively, balancing between interests and evils, and freeing the mind from the authority of the paranormal. T
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This research includes a detailed morphological description of the Pollenia mesopotamica sp. nov. in Iraq. Locality, host plant and data of collection were given.
The purpose of this study is to elucidate the microfacies and the biozones present in the studied rocks as well as to determine their environments or deposition. The study depends mainly on the benthonic foraminiferal assemblages identified from (27) rock thin sections made available from an outcrop at Wadi Banat Al-Hassan area in the Upper Euphrates Valley. X-Ray diffraction was also used to determine the type of carbonate minerals present in the studied rocks.
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In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf
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Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t
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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
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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
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