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(287 page document)

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The principal purpose of this document is to assist programme teams throughout the development process when they are considering the development or review of a route through the award where it will be delivered wholly, or primarily, via online distance learning. Please note that this document is current as of Sept 2015 but it is considered to be an evolving document and is updated/tweaked from time to time.

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Commissioned paper from Cameron Neylon (Curtin University) on citation practices for research data. Includes information on current (2016) global activity in the field, parallels with traditional citation, and recommendations.

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We propose a highly efficient content-lossless compression scheme for Chinese document images. The scheme combines morphologic analysis with pattern matching to cluster patterns. In order to achieve the error maps with minimal error numbers, the morphologic analysis is applied to decomposing and recomposing the Chinese character patterns. In the pattern matching, the criteria are adapted to the characteristics of Chinese characters. Since small-size components sometimes can be inserted into the blank spaces of large-size components, we can achieve small-size pattern library images. Arithmetic coding is applied to the final compression. Our method achieves much better compression performance than most alternative methods, and assures content-lossless reconstruction. (c) 2006 Society of Photo-Optical Instrumentation Engineers.

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