On rapid solidification and multiscale modeling in metal additive manufacturing: A review

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Hello. I have recently been spending a lot of time dithering. In image processing, dithering is the act of applying intentional perturbations or noise in order to compensate for the information lost during colour reduction, also known as quantisation. In particular, I’ve become very interested in a specific type of dithering and its application to colour palettes of arbitrary or irregular colour distributions. Before going into detail however, let’s briefly review the basics of image dithering.

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The tee() memory cliff: Stream.share() requires explicit buffer configuration. You choose the highWaterMark and backpressure policy upfront: no more silent unbounded growth when consumers run at different speeds.,更多细节参见爱思助手下载最新版本

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