Highlights Effect of lockdown relaxation on COVID-19 spread in India. Brief literature review of epidemic forecasting models. Model validation and standardization using actual lockdown time series. A self-organized data mining technique for forecasting active cases time series. Forecast of medical infrastructure requirement as per active cases.

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A novel two-stage directional multi-pass median filter (DMPMF) for reducing impulse noise has been proposed in this paper. It is a progressive technique wherein for each pass, median is substituted for each noisy pixel even if one noise free pixel exists in its surrounding 3x3 window otherwise the pixel is kept intact. The initial pass replaces only a fraction of the total number of noise-corrupted pixels in the corrupted image. With increasing number of passes, the number of pixels covered increases, and after a few passes, all or most of the noisy pixels are covered. Each pass gradually improves the quality of the restored image. Thereafter, directional filtering is applied to restore the fine details of the final image. The efficacy of the proposed algorithm is determined by applying it to different images. It produces better results in terms of the qualitative and quantitative measures of the image for both low and high density noise in comparison to many existing techniques.

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