The DC electrical conductivity properties of Ge60Se40-xTex alloy with x = 0, 5, 10, 15 and 20). The samples were formed in the form of discs with the thickness of 0.25–0.30 cm and the diameter of 1.5 cm. Samples were pressed under a pressure of 6 tons per cm2 , using a ton hydraulic press. They were prepared after being pressed using a ton hydraulic press using a hydraulic press. Melting point technology use to preper the samples. Continuous electrical conductivity properties were recorded from room temperature to 475 K. Experimental data indicates that glass containing 15% Te has the highest electrical conductivity allowing maximum current through the sample compared to Lu with other samples. Therefore, it is found that the DC co

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

A .technology analysis image using crops agricultural of grading and sorting the test to conducted was experiment The device coupling the of sensor a with camera a and 75 * 75 * 50 dimensions with shape cube studio made-factory locally the study to studio the in taken were photos and ,)blue-green - red (lighting triple with equipped was studio The .used were neural artificial and technology processing image using maturity and quality ,damage of fruits the of characteristics external value the quality 0.92062, of was value regression the damage predict to used was network neural artificial The .network the using scheme regression a of means by 0.98654 of was regression the of maturity and 0.97981 of was regression the of .algorithm Marr

Background: Determination of local bone mineral density (BMD) immediately after implant insertion play an important role in implant success rate, may offer comprehensive description of the bone, and give enough information to the surgeon prior to implant insertion and at follow up status. The aim of the present study is to evaluate the changes of local bone density in the dental implant recipient sites by using computerized tomography. Material and method: The sample consisted of (20) dental implants recipient sites, bone density assessment was done twice, immediately after implants insertion and after six months. Results: The mean HU of the bone around the implant insertion site, immediately after implant placement was 552.28 HU, and inc

The indirect monetary policy tools led to financial stability for the period being studied through the use of indicators of financial stability (aggregate) to show the effect of the foreign reserves of the Central Bank of Iraq and its indirect instruments in achieving financial and economic stability, especially after the significant decline in oil prices and dependence of the Iraqi economy on Oil (rent) and lower reserves of the Central Bank of Iraq after 2014 and now compared to previous years, the goal of this research is to achieve financial stability according to selected indicators and achieve an optimal monetary policy to achieve the development goals of The economic policy in the country. Standard models were used to test

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp

Urban Balance is one of the important indicators that leads to an assessment of the urbanization process in a particular country  , province or even a city that is multi-centered. By examining  the data related to Anba  province, it was found that the value of this indicator is equal to 0.96, which is less than the absolute one, and therefore the urbanization in the province is distributed collectively  

The development of a mathematical or statistical model for estimating urban growth is a complex process due to the overlap between indicators or variables that can be adopted to calculate estimate growth rates Al-Qaim city has been considered as an example to develop a statistical method by which changes

The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be

      In this paper we study and design two feed forward neural networks. The first approach uses radial basis function network and second approach uses wavelet basis function network to approximate the mapping from the input to the output space. The trained networks are then used in an conjugate gradient algorithm to estimate the output. These neural networks are then applied to solve differential equation. Results of applying these algorithms to several examples are presented