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Trashing the Vodafone Station

How to replace the Vodafone Station with your very own router

Vodafone forces its customers to use their modem/router, the "Vodafone Station": using any other router is impossible because authentication is being done via a custom PPPoE setup.
In the PPPoE packet there is a field named Host-Uniq which is used to separate packets from different PPPoE sessions: Vodafone requires the Station serial number to be put in this field as authentication.

Hardware setup

A Linux router with root access is needed to replace the Station with. With an xDSL connection a modem with a custom firmware like OpenWrt has to be used, most likely one based on a Lantiq SoC.
For a FTTH internet connection then every machine with at least two gigabit ethernet interface and a decent CPU will do it.

@GilLevi
GilLevi / README.md
Last active June 17, 2023 20:58
Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns

Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns

Convolutional neural networks for emotion classification from facial images as described in the following work:

Gil Levi and Tal Hassner, Emotion Recognition in the Wild via Convolutional Neural Networks and Mapped Binary Patterns, Proc. ACM International Conference on Multimodal Interaction (ICMI), Seattle, Nov. 2015

Project page: http://www.openu.ac.il/home/hassner/projects/cnn_emotions/

If you find our models useful, please add suitable reference to our paper in your work.

@fabianp
fabianp / partial_corr.py
Last active March 21, 2024 09:00
Partial Correlation in Python (clone of Matlab's partialcorr)
"""
Partial Correlation in Python (clone of Matlab's partialcorr)
This uses the linear regression approach to compute the partial
correlation (might be slow for a huge number of variables). The
algorithm is detailed here:
http://en.wikipedia.org/wiki/Partial_correlation#Using_linear_regression
Taking X and Y two variables of interest and Z the matrix with all the variable minus {X, Y},