The study aims to predict Total Dissolved Solids (TDS) as a water quality indicator parameter at spatial and temporal distribution of the Tigris River, Iraq by using Artificial Neural Network (ANN) model. This study was conducted on this river between Mosul and Amarah in Iraq on five positions stretching along the river for the period from 2001to 2011. In the ANNs model calibration, a computer program of multiple linear regressions is used to obtain a set of coefficient for a linear model. The input parameters of the ANNs model were the discharge of the Tigris River, the year, the month and the distance of the sampling stations from upstream of the river. The sensitivity analysis indicated that the distance and discharge have the most significant affect on the predicted TDS concentrations. The results showed that a network with (8) hidden neurons was highly accurate in predicting TDS concentration. The correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE) between measured data and model outputs were calculated as 0.975, 113.9 and 11.51%, respectively for testing data sets. Comparisons between final results of ANNs and multiple linear regressions (MLR) showed that the ANNs model could be successfully applied and provides high accuracy to predict TDS concentrations as a water quality parameter.
The Ratawi Oil Field (ROF) is one of Iraq's most important oil fields because of its significant economic oil reserves. The major oil reserves of ROF are in the Mishrif Formation. The main objective of this paper is to assess the petrophysical properties, lithology identification, and hydrocarbon potential of the Mishrif Formation using interpreting data from five open-hole logs of wells RT-2, RT-4, RT-5, RT-6, and RT-42. Understanding reservoir properties allows for a more accurate assessment of recoverable oil reserves. The rock type (limestone) and permeability variations help tailor oil extraction methods, extraction methods and improving recovery techniques. The petrophysical properties were calculated using Interactive Petroph
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This article reveals the first record of the parasitoid wasp, Monodontomerus obscurus Westwood (Hymenoptera, Torymidae) from Iraq. A total of 27 specimens were emerged from mud nests of sphecoid wasp of Sceliphron sp. (Hymenoptera, Sphecidae), that collected from a wall at a residential garden in Dohuk province. A short morphological description is presented.
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Twenty-two of the Starling Sturnus vulgaris Linnaeus, 1758 were collected in Baghdad city during the period from January to September, 2014, and examined for endoparasites. Ten (45.45%) were found infected with either the cestode Passerilepis crenata (Goeze, 1782) (31.81%) or the nematode Dispharynx nasuta (Rudolphi, 1819) (13.63 %). Morphometric and meristic features for these worms were expressed. D. nasuta is recorded here for the first time from S. vulgaris for Iraq.
This research aims to provide insight into the Spatial Autoregressive Quantile Regression model (SARQR), which is more general than the Spatial Autoregressive model (SAR) and Quantile Regression model (QR) by integrating aspects of both. Since Bayesian approaches may produce reliable estimates of parameter and overcome the problems that standard estimating techniques, hence, in this model (SARQR), they were used to estimate the parameters. Bayesian inference was carried out using Markov Chain Monte Carlo (MCMC) techniques. Several criteria were used in comparison, such as root mean squared error (RMSE), mean absolute percentage error (MAPE), and coefficient of determination (R^2). The application was devoted on dataset of poverty rates acro
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An Intelligent Internet of Things network based on an Artificial Intelligent System, can substantially control and reduce the congestion effects in the network. In this paper, an artificial intelligent system is proposed for eliminating the congestion effects in traffic load in an Intelligent Internet of Things network based on a deep learning Convolutional Recurrent Neural Network with a modified Element-wise Attention Gate. The invisible layer of the modified Element-wise Attention Gate structure has self-feedback to increase its long short-term memory. The artificial intelligent system is implemented for next step ahead traffic estimation and clustering the network. In the proposed architecture, each sensing node is adaptive and able to
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Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A
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l development in addition to environmental reform, which is not possible at its best, and from this the faculties of physical education and sports science realize the scale of the problem and its importance in the development of society that this all puts on the faculties of education Physical and sports sciences are a very difficult task and an end in holiness, for it is the responsibility of the human development service and its leadership, because the community leaders and its elites are those who value their direction and future more than others. The importance of this study comes from the goal of sustainable development to maximizing pain. The net gain from higher education while ensuring the preservation of the quality of reso
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This work deals with the reporting of four helminthes in the rook partridge Alectoris graeca collected in G'ara area west of Iraq. The infection rates of the cestodes, Raillietina alectori and R. tetragona and the nematode. Hartertia gallinarum, and the trematode. Postharmostomum gallinum were 6.38%, 40.43%, 10.63%, and 10.63% respectively. The host relationships were discussed.