This paper presents a real time simulation for virtual end milling process. Alyuda NeuroIntelligence was used to design and implement an artificial neural network. Artificial neural networks (ANN’s) is an approach to evolve an efficient model for estimation of surface roughness, based on a set of input cutting conditions. Neural network algorithms are developed for use as a direct modeling method, to predict surface roughness for end milling operations. Prediction of surface roughness in end milling is often needed in order to establish automation or optimization of the machining processes. Supervised neural networks are used to successfully estimate the cutting forces developed during end milling processes. The training of the networks is preformed with experimental machining data. The neural network is used to predict surface roughness of the virtual milling machine to analyze and preprocess pre measured test data. The simulation for the geometrical modeling of end milling process and analytical modeling of machining parameters was developed based on real data from experiments carried out using Prolight2000 (CNC) milling machine. This application can simulate the virtual end milling process and surface roughness Ra (µm) prediction graphs against cutting conditions simultaneously. The user can also analyze parameters that influenced the machining process such as cutting speed, feed rate of worktable. Key words: Surface roughness, virtual reality, simulation, surface roughness, virtual end milling process, neural

Urban sprawl on agricultural lands considers one of the permanent problems, which face all the governments that govern Egypt last decades, especially with the fact that all urban areas distributed on 6% of all Egyptian territories accompanied with accelerated population growth (2% yearly). Therefore, this research aims to study factors affecting urban sprawl on agricultural lands in Egypt, theoretical studies focused on understanding all aspects of the research problem (economical, demographical, political and spatial aspects

In this paper a hybrid energy system combining variable speed wind turbine, solar photovoltaic and fuel cell generation systems is presented to supply continuous power to residential power applications as stand-alone loads. The wind and photovoltaic systems are used as main energy sources while the fuel cell is used as secondary or back-up energy source. Three individual dc–dc boost converters are used to control the power flow to the load. A simple and cost effective control with dc–dc converters is used for maximum power ...