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Emergency watch wins M2M Challenge

Mar 21, 2013 Categories: Recognitions & Awards, Technology, Industry
Limmex Senator

M2M has never looked so stylish, nor been so accessible. Limmex, the Swiss emergency watch, has won first place in the M2M Challenge, a new global competition highlighting the best innovations in machine-to-machine communication.

Hans Vestberg: MWC Wrap Up

Mar 4, 2013 Categories: Industry, Technology
Hans Vestberg: MWC Wrap Up

Ericsson President and CEO Hans Vestberg looks back at the trends from Mobile World Congress 2013, which was held in Barcelona, February 25-28.

Ericsson keynote at Mobile World Congress brings the Networked Society to Life

Feb 27, 2013 Categories: Industry, Technology
Hans Vestberg

This year’s keynote was all about Bringing the Networked Society to Life and Ericsson President and CEO, Hans Vestberg showed examples of innovation, and business models that are already coming to life in the Networked Society.

IPv6 - meeting the challenge of connecting everyone and everything

Feb 22, 2013 Categories: White Papers
IPv6 - meeting the challenge of connecting everyone and everything

IPv6 is a reality. Network technologies, services and support systems are ready for it, with IPv6 device support widely available and operators already deploying IPv6 in their networks.

OSS BSS solutions key to the success of niche Brazilian operator Datora Telecom

Feb 21, 2013 Categories: Industry
Wilson Otero

Wilson Otero, the CEO of Brazilian operator Datora Telecom, discusses how OSS BSSS solutions are helping his company to target niche markets.

Capturing the Real Influencing Factors of Traffic for Accurate Traffic Identification

Feb 14, 2013 Categories: Conference papers

In this paper we introduce a novel framework for traffic identification that employs machine learning techniques focusing on the estimation of multiple traffic influencing factors. The effect of these factors is handled with the training of several machine learning models. We utilize the outcome of the multiple models via a recombination algorithm to achieve high overall true positive and true negative and low overall false positive and false negative classification ratio. The proposed method can improve the performance of every kind of machine learning based traffic identification engine making them capable of efficient operation in changing network environment i.e., when the probing node is trained and tested in different sites.

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