A computational framework for tracking grain boundaries in 3D image data: Quantifying boundary curvatures and velocities in polycrystalline materials

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另一个窗户纸则是热效率。增程市场热衷于卷热效率这个纸面参数。友商动辄44%、45%的数据很唬人,但他们没告诉车主,这个“最高”往往只有一个点,只有在实验室那个特定的转速和负载下才能跑出漂亮数据,一旦脱离“最佳工况”,热效率就哗哗往下掉。有媒体把这形容为“一根缝衣线——窄得可怜”。

While it’s not exactly a 1-to-1 relationship1 it’s close. All you need is a sorted list of base64 characters (A..z, 0..9, etc) weighted by their luminance, which, well, apparently that doesn’t exist anywhere, but it’s easy to generate a few (64) images with a single character on each, and count dark/light pixels using numpy.

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I had mixed feelings about the Checkmate 1500 I used for the 486 build. The form factor was splendid but there was a post-processing of the VGA signal that made the image blurry and I did not like it.

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