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

Introduction The Hybrid Gamma Camera (HGC) is being developed to enhance the localisation of radiopharmaceutical uptake in targeted tissues during surgical procedures such as sentinel lymph node (SLN) biopsy. Purpose To assess the capability of the HGC, a lymph-node-contrast (LNC) phantom was constructed for an evaluative study simulating medical scenarios of varying radioactivity concentration and SLN size. Materials and methods The phantom was constructed using two methyl methacrylate PMMA plates (8 mm thick). The SLNs were simulated by drilling circular wells of diameters ranging between 10 mm and 2.5 mm (16 wells in total) in one plate. These simulated SLNs were placed underneath scattering material with thicknesses ranging between 5 mm

This paper presents a hybrid genetic algorithm (hGA) for optimizing the maximum likelihood function ln(L(phi(1),theta(1)))of the mixed model ARMA(1,1). The presented hybrid genetic algorithm (hGA) couples two processes: the canonical genetic algorithm (cGA) composed of three main steps: selection, local recombination and mutation, with the local search algorithm represent by steepest descent algorithm (sDA) which is defined by three basic parameters: frequency, probability, and number of local search iterations. The experimental design is based on simulating the cGA, hGA, and sDA algorithms with different values of model parameters, and sample size(n). The study contains comparison among these algorithms depending on MSE value. One can conc

Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti

Background: one of the complications of power bleaching is surface roughness of enamel which increases the possibility of post bleaching teeth discoloration. The aim of the present study is to evaluate the effect of toothpaste containing nano hydroxyapatite, NovaMin and kin sense fluoride on surface roughness of human tooth enamel after laser bleaching with 35% hydrogen peroxide bleaching gel. Materials and Methods: Twenty human enamel incisors were cleaned and their labial surface polished up to #1200, then categorized into four equal groups; first group kept without bleaching as a control group, while the remaining three experimental groups were bleached with 35% hydrogen peroxide, and each group treated with a restore paste containing o

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

Background: The present in-vitro study was undertaken to evaluate and compare fracture resistance of weakened endodontically treated premolars with class II MOD cavities restored with different bulk fill composite restorations (EverX posterior, Alert, Tetric EvoCeram Bulk Fill, and SDR). The type and mode of fracture were also assessed for all the experimental groups. Materials and Method: Forty-eight human adult maxillary premolar teeth were selected for this study. Standardized extensive class II MOD cavities with endodontic treatment were prepared for all teeth, except those that were saved as intact control. The teeth were divided into six groups of eight teeth each (n=8): (Group 1) intact control group, (Group 2) unrestored teeth with

Objective: To enhance bonding strength between thermoplastic denture base and acrylic soft liner through ethyl acetate surface treatment. Materials and Methods: Modifications of thermoplastic acrylic denture base surface were investigated with SEM. FTIR was used to detect whether there was a chemical bond between thermoplastic acrylic and the organic solvent. A total of 80 samples were prepared and divided into 20 samples for the surface roughness test and 60 samples for the shear bond strength test. Failure type was assessed visually. Results: Shear bond strength and surface roughness values of un treated samples were lower in comparison to surface treated groups; the greatest post thermocycling bond strength value was recorded for the sam