Even one-step prediction of natural time series without delay especially in main phase of storm is difficult for many complicated time series such as Dst index. In this study, with a new method based on singular spectrum analysis, we extract the main components of the time series, model each component with a locally linear neurofuzzy network, and utilize the trained networks for multi-step ahead prediction of a validation set of data, and finally combine the predicted patterns for construction of general prediction. Our methods are compared with several previous studies for Dst index prediction. Several solar geomagnetic extreme events are predicted well with our state-of-the-art method; such as extreme events in 14 March 1989 that led to power black-out in Quebec, as well as other extreme storms.

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In this paper, an automatic faceting robot is studied. The kinematics and dynamics of this robot-faceter are calculated and analyzed. The relationship between shear height and rotational angle assuming a hemisphere perform and the canonical preform is derived accurately which is essential for faceting of gemstone jewelry. Also, we calculate the effect of shear forces on the mechanical arm during the facet of gemstone with canonical preform. Different stress components of faceter robot manipulator are analyzed here.

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