In this study we focused on the determination of influence the novel synthesized thiosemicarbazide derivative "2-(2-hydroxy-3-methoxybenzylidene) hydrazinecarbothioamide" (HMHC) influenced the corrosion inhibition of mild steel (MS) in a 1.0 M hydrochloric acid acidic solution.This is in an effort to preserve the metal material by maintaining it from corrosion.The synthesized inhibitor was characterized using elemental analysis, and NMR-spectroscopy. Then the corrosion inhibition capability of (HMHC) was studied on mild steel in an acidic medium by weight loss technique within variables [temperature, inhibitor concentration, and time]. The immersion periods were [1:00, 3:00, 5:00, 10:00, 24:00, and 72:00] hours and the tem

Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was

The aim of this work is study the partical distribution function g(r12,r1) for Carbon ion cases (C+2,C+3,C+4) in the position space using Hartree-Fock's Wave function, and the partitioning technique for each shell which is represented by Carbon Ions [C+2 (1s22s2)], [C+3 (1s22s)] and [C+4 (1s2)]. A comparision has been made among the three Carbon ions for each shell. A computer programs (MATHCAD ver. 2001i) has been used texcute the results.

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

A new benzylidene derivative, namely N-benzylidene-5-phenyl-1,3,4-thiadiazol-2-amine (BPTA), has been synthesized and instrumentally confirmed with Elemental Analysis (CHN), Nuclear Magnetic Resonance (NMR), and Fourier Transform Infrared Spectroscopy (FT-IR). Titanium Dioxide (TiO2) nanoparticles (NPs) were synthesized and characterized by X-ray. The mutualistic complementary dependence of BPTA with TiO2 nanoparticles as anti-corrosive inhibitor on mild steel (MS) in 1.0 M hydrochloric acid has been tested at various concentrations and various temperatures. The methodological work was achieved by gravimetric measurement methods complemented with surface analysis. The synthesized inhibitor concentrations were 0.1 mM to 0.5 mM and the temper

Radiotherapy is medical use of ionizing radiation, and commonly applied to the cancerous tumor because of its ability to control cell growth. The amount of radiation used in photon radiation therapy called dose (measured in grey unit), which depend on the type and stage of cancer being treated. In our work, we studied the dose distribution given to the tumor at different depths (zero-20 cm) treated with different field size (4×4- 23×23 cm). Results show that the deeper treated area has less dose rate at the same beam quality and quantity. Also it has been noted increasing in the field increasing in the depth dose at the same depth even if the radiation energy is constant. Increasing in radiation dose attributed to the scattere

The research targets study of influence of additives on sand mold’s properties and, consequently, on
that of carbon steel CK45 casts produced by three molds. Three materials were selected for addition
to sand mix at weight percentages. These are sodium carbonates, glycerin and oat flour. Sand molds
of studied properties were produced to get casts from such molds. The required tests were made to
find the best additives with respect to properties of cast. ANSYS software is used to demonstrate
the stresses distribution of each produced materials. It is shown that the mechanical properties of
casts produced is improved highly with sodium carbonates and is less with oat flour and it is seem a
few with glycerin additives

This study uses an Artificial Neural Network (ANN) to examine the constitutive relationships of the Glass Fiber Reinforced Polymer (GFRP) residual tensile strength at elevated temperatures. The objective is to develop an effective model and establish fire performance criteria for concrete structures in fire scenarios. Multilayer networks that employ reactive error distribution approaches can determine the residual tensile strength of GFRP using six input parameters, in contrast to previous mathematical models that utilized one or two inputs while disregarding the others. Multilayered networks employing reactive error distribution technology assign weights to each variable influencing the residual tensile strength of GFRP. Temperatur

 In this paper we study the effect of the number of training samples for  Artificial neural networks ( ANN ) which is necessary for training process of feed forward neural network  .Also we design 5 Ann's and train 41 Ann's which illustrate how good the training samples that represent the actual function for Ann's.