This study aimed to IQ test standardization of Marten Lother Johan which used with childreen of the one stage at primary schools who aged (6) years old in Baghdad (Resafaa and Kharh).

 The importance of this study are :

1-The  importance of childhood and its role to develop the personality.

2-The importance of this age as the child will exposure to different kind of official teaching .

3-The capability for early detection of special category for early intervention in order to provide the necessary care .

4-Using the current test could consider as a predictive tool to screen the intelligent children .

In order to achieve the study aim, the researcher had followed the follow

The use of worn-out agricultural nozzles in pesticide application has a negative effect on the efficiency and cost of the application process. It also has an effect on environmental pollution due to an excessive amount of pesticide being applied when spraying with worn-out nozzles. In this paper, the resistance to wear of three different internal design hydraulic nozzles was ascertained. Changes in the flow rate and spray distribution as a result of this wear were also investigated. The wear test was done inside a closed system, and it was accelerated using an abrasive material to generate 100 h of wear. The tested nozzles were the Turbo TeeJet (TT)-twin chambered, Turbo Twinjet (TTj60)-dual outlet, and Drift Guard (DG)-pre-orifice.

In this research an Artificial Neural Network (ANN) technique was applied for the prediction of Ryznar Index (RI) of the flowing water from WTPs in Al-Karakh side (left side) in Baghdad city for year 2013. Three models (ANN1, ANN2 and ANN3) have been developed and tested using data from Baghdad Mayoralty (Amanat Baghdad) including drinking water quality for the period 2004 to 2013. The results indicate that it is quite possible to use an artificial neural networks in predicting the stability index (RI) with a good degree of accuracy. Where ANN 2 model could be used to predict RI for the effluents from Al-Karakh, Al-Qadisiya and Al-Karama WTPs as the highest correlation coefficient were obtained 92.4, 82.9 and 79.1% respe

    One of ciphering systems depends on transposition of letters in plain text to generate cipher text. The programming of transposition depends mainly on 2-dimension matrix in either methods but the difference is in columnar .We print columns in the matrix according to their numbers in key but in the fixed, the cipher text will be obtained by printing matrix by rows.

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

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