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The main aim of this experiment is to investigate the effects of Nano-size Al2O3 on the mechanical properties and microstructure of multi-passes friction stir welding of Al 2024 lap joint. Nano particles were added into the joint line. A combination of rotational speed and travelling speeds were performed. Optical microscopy and scanning electron microscope were used to investigate the microstructure and fracture surface of samples respectively. Optimum condition (sample) was selected due to highest ultimate tensile strength (UTS). It was seen that sample which included Nano particles and fabricated by 1400 rev/min rotational speed and 16 mm/min travelling speed in second pass of continues welding had improvement in UTS in comparison to one pass welded sample of particle free and after that increasing the number of passes reduce the UTS. The average micro hardness of the sample which was particle rich were increased in comparison to particle free sample in nugget zone. Increasing the number of passes was not effect average micro hardness in nugget zone significantly. Grain sizes were reduced by 2 passes welding and after that no significant reduction has been seen.

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Accurate estimate of the land cover is of particular importance in environmental management and planning. Different methods have so far been developed for the classification of satellite imagery. Regarding the weakness of the hard classifiers in the presence of the mixed pixels, soft classification methods have been designed to estimate the fractions of different classes within mixed pixels. Linear spectral mixture model could be considered as the most popular method of soft classification. The accuracy of this model is extremely depended on the quality of the input pure pixels. The extraction of these pixels is often hard and challengeable. In this paper, making use of physical parameters (brightness, wetness, and greenness) is proposed for extraction of pure pixels. The evaluation criteria of unconstrained linear spectral mixture model were used assess the quality of pure pixels extracted from the proposed method. By Implementing of this model on the satellite image of the study area, the total number of under-shoot and over-shoot pixels was determined as 4.43 percent of the total image pixels. Also RMSE equaled to 2.68. Consequently, the proposed method demonstrated promising accuracy in the results of the linear spectral mixture model without considering any constraint.