Sahana Google Code-In Students work on CAP Broker

Once again Sahana participated in 2011 Google Code-In. Happy to have been part of it mentoring students. A big thrill was that they worked on the few research tasks that were related to the Common Alerting Protocol (CAP) Broker. The two main tasks were:

1. develop a blueprint with wireframe to port the Sahana Agasti CAP Broker to Sahana Eden (because Sahana Agasti CAP Broker is no longer supported by the community; moreover, the new version that will be built in to Eden would build on the lessons learned and improve the shortcomings from the piece-wise build original version)
2. develop a wireframe to build an XSL Editor (mainly to develop XSL files to transform full CAP messages to deliver through short-text, long-text, and voice-text messages through email, SMS, IVR, Twitter, etc)
   

The CAP Broker is a tool that I have been researching on and developing over the past six years. The real need of a CAP Broker is in early warning. Based on the systems definition for early warning system, it requires a Broker to acts as a messaging pivot between those who publish alerts/warnings and those who subscribe to them.

The first works were with the HazInfo project, when we tested various wireless technologies for their ability to carry CAP messages to last-mile communities. There was an opportunity to further develop and test it for cyclones and hurricanes but we failed to win the hearts of NSA to nail the grant. There was also interest to build the libraries and test components that would carry CAP messages over Radio Data Systems; however, could not secure any funding to try this as well.

What we did achieve was testing CAP over HF data platform. The first working Sahana CAP broker was tested for health alerting with delivery over HTTP, Email, SMS, and RSS. Then recently, the field testing of CAP messages disseminated through an IVR.

STANDBY ... There's more work to be done and shared.

Social Network Stats are Wrong Wrong

I caught this InfoGraphic on "how the world uses social networks" off a tweet. Once you read it you notice that it excludes India and China the two worlds largest populations. Those two countries are also Internet giants; especially China. I don't know about India but living in Kunming, China I know and see how people use, the famous QQ (here's the link to the International version). This author: Tony D’Altorio (Investment U Research) does a nice economic analysis on "How Does Renren Compare to Facebook?". One would say that the Chinese versions are not international and if it was would foreigners use it. Tencent does offer QQ in six languages for now. This article: "Will Foreigners Use a Chinese Microblog if the Version is in English?" tells a good story how certain industries can capitalize. I have a QQ account but the problem is that Tencent does not offer a desktop QQ Linux version of the international package yet. Moreover, for me to Weibo (microblog like twitter) I need a Chinese ID number; i.e. for citizens only! These requirements are not barriers to enter Twitter or Facebook.

A nifty way to test Speech-To-Text uncertainties with ITU's Difficulty Percentage measure

In these experiments the LIRNEasia researchers used Freedom Fone Interactive Voice Response (IVR) system. First they conducted a survey with known values for the subjects to pick from. These answers were submitted through the IVR. Since the values were known to the human quality testers, this part of the experiment was associated with a speech-to-text trained system (or a speaker-dependent system or voice recognition type system). The second part involved the subjects submitting data that was not based on preset values. They were free to submit answers to questions as they pleased. This was regarded as an untrained or speaker-independent system.

Emulating Speech-To-Text Reliability with ITU Difficulty Scores

"The results show that with a speaker dependent system 95% of the information could be clearly deciphered opposed a speaker independent system that was only 70% clear (blue areas in Figure 1 and Figure 2). It is not surprising, the outcomes are intuitive. In our study reliability had two components, one was efficiency and the other was voice quality. The voice quality also took in to consideration the Mean Opinion Score and the Comparison Categorical Rating. The researchers wish to acknowledge that their may be disagreements in the sample sizes and number of Evaluators. These results are not ideal for drawing a ‘for-all” kind of conclusion. However, at this realize stage of the research it provides a quick and easy method to draw initial conclusions." ...Click to read full article