Research in Encoding And Decoding of
Nomikos Conference Centre
28 June – 2 July 2022
It might seem odd to require both PDF and LaTeX/DOC formats. This page explains why we make this request.
The PDF format is a highly portable representation that we use in the review process to guarantee that the author's intent is visualized correctly. To provide a uniform presentation in the conference book, however, we re-typeset from the original LaTeX or DOC file, to eliminate the inevitable minor formatting differences from abstract to abstract. We therefore request both formats at the time of submission in order to serve both purposes, and thus allow us to streamline the production process for accepted abstracts.
Please note that re-typesetting the abstracts presents significant effort and any change that is required to bring an accepted abstract into the unified format (like correcting the font, putting the title into all caps, editing affiliation information, etc.) increases the chances of an error being introduced into the abstract. It is therefore in the author's best interests to adhere as closely as possible to the templates provided. The fewer adjustments we have to make on an abstract, the smaller the chance of an unintentional change creeping in to the text.
We do not accept submissions created with Apple Computer's Pages software because of compatibility issues in the past. We strongly encourage creation of submissions using LibreOffice software instead; LibreOffice is an open-source office suite that is available for all major operating systems.
We preferentially accept abstracts written in LaTeX because it is a favored format for a substantial number of researchers, including one of the AREADNE founders who is a hard-core plain TeX user. Between 20 and 25% of submissions are in LaTeX; the conference proceedings are written in TeX and typeset using pdftex. The TikZ package is a favored way of creating figures in TeX.
When finalizing an abstract before submission, please review the checklist provided with your selected template to look for and correct common mistakes.
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