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% respectively. For

COVID-19 is a disease that has abnormal over 170 nations worldwide. The number of infected people (either sick or dead) has been growing at a worrying ratio in virtually all the affected countries. Forecasting procedures can be instructed so helping in scheming well plans and in captivating creative conclusions. These procedures measure the conditions of the previous thus allowing well forecasts around the state to arise in the future. These predictions strength helps to make contradiction of likely pressures and significances. Forecasting procedures production a very main character in elastic precise predictions. In this case study used two models in order to diagnose optimal approach by compared the outputs. This study was introduce

Filed experiment was conducted to test the effect of saline water and potassium fertilizers rate on proline and water potential of Pisum sativum L. (Var.Senador Cambados ) leaves . Treatments of the experiment included two levels of water salinity( 2, 7 dSm-1) as a main plot and fertilizer rates as a sub plot. Results indicated that irrigation of plant with saline water 7 dSm-1 and fertilization 150 kg/donum increased proline accumulation and water potential 0.31 mmol/g,-17.00 bar at 9 AM morning and 0.62 mmol/g , -21.00 bar at 3 PM afternoon ,Irrigating plant with a 2 dSm-1 and fertilization 300 kg/donum decreased proline accumulation and water potential of leaves 0.22 mmol/g, -16.00 bar at 9 A

Eugenol is found in essential oils of many plants. It belongs to a class of naturally occurring phenolic monoterpenoids, chemically it is an allyl chain-substituted guaiacol. A study was conducted on the compound of Eugenol, which included different studies. The first study was the determination of eugenol in body fluid, which includes serum, saliva and urine has been found the highest concentration was in urine then serum and saliva. The second study was the hematological study. Complete blood count was accomplished on the volunteers alredy administrated with eugenol contained mouthwash the analysis was accomplished before and after the mouth wash use. The result observed a slightly negative results and was not that significant, wh

The follower to study the markets in the Islamic Mashreq (Iraq, Persia and the country of Ma
Behind the river for the period from the reign of the Prophet Muhammad until the end of the Islamic era) to find that there
A remarkable development in the pattern, shape, planning and privatization of markets
Islamic cities and places are the main conditions for their existence, which is the mosque of the mosque
And markets, and these markets have evolved from being a space in which there are no building and no ceilings to shade them in
The places of sale and purchase to specialized markets classified according to the materials and goods produced in them
This would facilitate the task of supervising it by the market factor and

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