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

Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa

This research investigated the effect of adding two groups of reinforcement materials, including bioactive materials Hydroxyapatite (HA) and halloysite nanoclay and bioinert materials Alumina (AL2O3) and Zirconia (ZrO2), each of them with various weight ratios (1,2,3,4 &5)% to the polymer matrix PMMA. The best ratios were selected, and then a hybrid was preparing Composite red from the best ratios from each group. Thermal properties, including thermal conductivity and Thermomechanical Analysis (TMA) technology, have been studied. The results showed that adding 3% Hydroxyapatite (HA) and 5% halloysite nanoclay to the polymethacrylate (PMMA) mer leads to an increase in thermal conductivity. It was also found from the Thermomechanical Analysis

The study aimed to assess Milk Thistle oi reducing the aflatoxin damage and improve the health status of local breed hens. The study was performed on 60 hens aged 35 weeks, weighing 2-2.5 kg of the body was obtained and housed on a private poultry farm in north of Baghdad (Altaji) for a period of 9 weeks from 22 October until 22 December 2020. Hens were divided to three treatments (20 hens). The first was fed a basal diet free of aflatoxin. The 2nd fed on a contaminated diet with aflatoxin (14.6 ppb) while the 3rd fed as in the 2nd with 0.5% of Milk Thistle oil /kg feed. A 5 hens from each group were slaughtered at the end of the trial for the histopathological inspection of liver, spleen and intestine tissues to evaluate the harmfu

Background: The combination of thermoplastic nylon resin materials and auto polymerizing resin is necessary in some situation for repair and adjustment. This study evaluated shear bond strength between thermoplastic nylon material (flexible) and auto polymerizing acrylic resin subjected to holes and silica coated layer. Materials and Method: Forty five (45) specimens were prepared from flexible acrylic bonded to auto-polymerizing acrylic resin and divided into three groups according to the surface treatments as follows: Group A: 15 specimens of flexible acrylic bonded with cold-cure acrylic by holes. Group B: 15 specimens of flexible acrylic bonded with cold-cure acrylic by silica coated layer. Group C: 15 specimens of flexible acrylic bon

Today, the prediction system and survival rate became an important request. A previous paper constructed a scoring system to predict breast cancer mortality at 5 to 10 years by using age, personal history of breast cancer, grade, TNM stage and multicentricity as prognostic factors in Spain population. This paper highlights the improvement of survival prediction by using fuzzy logic, through upgrading the scoring system to make it more accurate and efficient in cases of unknown factors, age groups, and in the way of how to calculate the final score. By using Matlab as a simulator, the result shows a wide variation in the possibility of values for calculating the risk percentage instead of only 16. Additionally, the accuracy will be calculate