The turning process has various factors, which affecting machinability and should be investigated. These are surface roughness, tool life, power consumption, cutting temperature, machining force components, tool wear, and chip thickness ratio. These factors made the process nonlinear and complicated. This work aims to build neural network models to correlate the cutting parameters, namely cutting speed, depth of cut and feed rate, to the machining force and chip thickness ratio. The turning process was performed on high strength aluminum alloy 7075-T6. Three radial basis neural networks are constructed for cutting force, passive force, and feed force. In addition, a radial basis network is constructed to model the chip thickness ratio. T

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In this research, estimated the reliability of water system network in Baghdad was done. to assess its performance during a specific period. a fault tree through static and dynamic gates was belt and these gates represent logical relationships between the main events in the network and analyzed using dynamic Bayesian networks . As it has been applied Dynamic Bayesian networks estimate reliability by translating dynamic fault tree to Dynamic Bayesian networks and reliability of the system appreciated. As was the potential for the expense of each phase of the network for each gate . Because there are two parts to the Dynamic Bayesian networks and two part of gate (AND), which includes the three basic units of the

Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites

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This Research aims to define role of the system of evaluating the performance for higher leadership in determining the level of institutional work quality in the Ministry of Agriculture, by measuring system efficiency of evaluating the performance for higher leadership and its effect in institutional work quality, the searcher reached through the theoretical framing and involved studies to build default plan define the relation between Research variables formed from system of evaluating leadership performance as independent variable contains six subsidiary dimensions: (Polarization, evaluating the performance of personnel, training, motivation, se

There is no doubt that Agricultural Policy is the main responsible for the degrading in Agricultural sector in Iraq during the period 2003-2013, and that was very clear from magnitude of indicators because of little sharing of each of agricultural product in GDP because it was (9.38%) in average during the study period and the annual changing of it was negative (-5.82%), and there is increasing in deficit of trade balance in Agriculture during the study period about (4185.73) million US$, and the percentage of agricultural exports from total exports was (0.14%) in average only. The foreign trade policy in Agricultural products also cannot determine map of Revealed Comparative Advantage (RCA) of Agricultural products and crops. The study sh

         The economy is exceptionally reliant on agricultural productivity. Therefore, in domain of agriculture, plant infection discovery is a vital job because it gives promising advance towards the development of agricultural production. In this work, a framework for potato diseases classification based on feed foreword neural network is proposed. The objective of this work  is presenting a system that can detect and classify four kinds of potato tubers diseases; black dot, common scab, potato virus Y and early blight based on their images. The presented PDCNN framework comprises three levels: the pre-processing is first level, which is based on K-means clustering algorithm to detect the infected area from potato image. The s