Abstrct The Turkish political system has undergone exceptional and unprecedented circumstances, represented by a series of security and political unrest that has cast its shadow over the Turkish state and regional and international challenges. It has never been a pretext or pretext for continuing the comprehensive reform process. The constitutional amendments of the 1982 Constitution, Justice and development, whether political, economic or social, is not a reaction to a difficult reality; it is a system of governance and a national option stemming from within. It promotes national unity and enshrines democracy and the concept of public rights and freedoms.

Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

A new copolymer (MFA) was prepared from condensation of melamine (M) with p- methyl – anisole (A) in the presence of condensation agent like 37% (w/v) of formaldehyde. The new copolymer was characterized by elemental, IR and HNMR spectra. The chelating ion-exchange property of this polymer was studied for methylene blue dye in aqueous solution in 100-200ppm concentrations. The adsorption study was carried out over a wide range of pH, shaking time and in media of various kinetic parameters models. Thermal parameters like enthalpy, entropy and Gibbs free energy of adsorption process of methylene blue on surface of MFA resin were determined on the basis of kinetic parameters at different temperatures. To describe the equilibrium of adsorp

The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A

The curriculum is considered one of the most important corners for the educational process, it participates in achieving the educational equilibrium between its elements.

The curriculum of (History of the Art) in the college of Art Education / dept. of plastic art education and ceramic as the other curriculums and due to the subject of history of the art develop the knowledge, taste and experiment for art studier also this subject has a direct relation with practical educational activities like colors and growth the knowledge of the student in field of contents and symbols and evidences of meaning in old , medium and contemporary arts, due to the fact that this curriculum has been applied since long time more than four years, and

The objective of this study is to apply Artificial Neural Network for heat transfer analysis of shell-and-tube heat exchangers widely used in power plants and refineries. Practical data was obtained by using industrial heat exchanger operating in power generation department of Dura refinery. The commonly used Back Propagation (BP) algorithm was used to train and test networks by divided the data to three samples (training, validation and testing data) to give more approach data with actual case. Inputs of the neural network include inlet water temperature, inlet air temperature and mass flow rate of air. Two outputs (exit water temperature to cooling tower and exit air temperature to second stage of air compressor) were taken in ANN.

The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determ

The present study dealt with the removal of methylene blue from wastewater by using peanut hulls (PNH) as adsorbent. Two modes of operation were used in the present work, batch mode and inverse fluidized bed mode. In batch experiment, the effect of peanut hulls doses 2, 4, 8, 12 and 16 g, with constant initial pH =5.6, concentration 20 mg/L and particle size 2-3.35 mm were studied. The results showed that the percent removal of methylene blue increased with the increase of peanut hulls dose. Batch kinetics experiments showed that equilibrium time was about 3 hours, isotherm models (Langmuir and Freundlich) were used to correlate these results. The results showed that the (Freundlich) model gave the best fitting for adsorption capacity. D