Anybody who read the classic American tale Johnny Got His Gun has a slight comprehension of what it’s like to live trapped within your own body, incapable to move, nod, speak or even blink. The mind reels; the body does nothing. Unfortunately, this form of communication-stripped torture isn’t a fictional tale but a reality for many with Locked-in Syndrome (it was featured in the House episode with Mos Def guest starring), which is why the new functional Magnetic Resonance Imaging (fMRI) scanner, Brain Bee, that can translate brain waves into words — is a big deal.
This new system empowers fully paralyzed and ‘locked-in’ people to mentally select letters of the alphabet in their brain, which are recognized and typed out on a screen, serving as a brain-based, non-communicative communication system for those unable to speak, sign or blink to indicate their needs. Researchers are able to recognize letter-based thought patterns by using characteristic blood flow patterns.
Before you conjure up images of telepathy or Vulcan mind melds though, this technology is a little more difficult than that to use. In order to ‘think’ of a letter the technology divides the alphabet into three rows, nine columns and 27 squares (26 letters of the alphabet plus the space bar). Each row is assigned a mental task, a motor-imagery task, a mental calculation task and an inner-speech task, that the subject must perform to select the row. The letters then cycle through and the subject selects the correct one by performing the task as the letter appears on screen. It is a time-consuming process but the technology is rather easy to learn, with test subjects learning it in under an hour.
The system has passed the theoretical and initial testing stages and has become a concept system. Although it is still in its initial phases — it has already shown promising results.
In hindsight, 2010 has definitely been a fantastic year for Open Source; be it software, hardware, applications, etc. Leveraging the same point of view further, 2010 has also been a brilliant year for open source software projects developed for mobile applications. Black Duck Software which serves as a good barometer for several open source software projects, showed that Google Android provided a fantastic mobile software platform for open source developers to produce superlative applications; followed by Apple’s iOS which was also decent in terms of the number of open source applications it owns at present.
Though the advancement of electronic devices & breakthrough gadgets has been advancing progressively; the battery technology still is a few steps behind the other. In the coming years, one can expect their laptops, cars, mobile phones and any other devices running on battery to be replaced by something which is more handy & small in size. This dream is possible to envisage due to a group of researchers engaged in creating new evolution in the battery technology domain.
They have successfully produced the World’s Tiniest Battery. A team headed by Jianyu Huang, a researcher at Sandia National Laboratories, carried out the experiment at the Center for Integrated Nanotecnologies (CINT), where they already got insight of a working battery, which holds key to the future smaller and efficient battery.
Trendistic is a great tool that is used to follow activity on Twitter. As you are probably aware, there are about 30 million Twitter users in the world, so Twitter trends are a great tool for market researchers.
The problem with using Twitter for research is that it is often difficult to gauge what people are really thinking when they post their tweets. When they are only writing 140 characters, they could mean just about anything. However, if you really look carefully at someone’s tweets you are able to have at least a general understanding of how they feel about a particular topic.
The value that Trendistic has over some other trending apps is that users can actually use a search phrase rather to search within the body of an entire tweet rather than looking at #hashtags. This allows a researcher to get a much better approximation of how many tweets are made on a given topic.