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Relatório Técnico de Desenvolvimento de Software

Carta pedido de transferência de novo membro entre igrejas Presbiterianas do Brasil

An experimental hackety hack to export HTML from LaTeX on Overleaf, using make4ht: Math is exported as MathML and will be rendered using MathJax; EPS and PDF graphics are converted to PNG; JPG and PNG graphics are used as-is; TikZ drawings are exported as SVG. This is provided 'as is' and is not officially supported by Overleaf. In this sample set-up, the HTML export will only be triggered if the project is set to compile with pdfLaTeX. It'll take longer than usual to compile your project; so probably a good idea to only add the latexmkrc file that triggers the HTML export when you're quite down with writing. You can download the generated files using the steps described here. make4ht does not work well with authblk, fontspec and possibly other packages. This is an experimental hackety hack!

Template, para los anteproyectos de laboratorio eléctrico UCR.

UIT Template Report

Alberto Cavallaro's CV

Project Plan Template for NTNU Course TDT39

METATOYs are optical components that can produce light ray fields that were thought to have been forbidden until now. They can be utilised to produce effects that were thought to be science-fiction. Invisibility cloaks, but on a larger scale than previously possible, is the major one as well other abstract effects to light rays. This report will explore what happens when two dove prism arrays are brought together and rotated and how they can produce these supposed illegal light ray fields.

Research about recommendation systems has increased due to the amount of information that it is available to individuals. In the music context these systems help the individual to filter and discover new songs according the individual's taste. Most of the business music companies use a recommendation system, based on the characteristics of a song listened by an individual, but a group recommendation system is still underexplored. For a shared environment when there is music, the songs selection will be more efficient if a group recommendation system is used. The goal of this project is to develop a music recommendation for a group that, is sharing the same environment, taking into consideration the context. For this reason, in this work we will employ the Spotify API to recover the data of playlists that were listened by an individual, collecting its preferences and adding them to the others individuals playlists.