ICA can be used in brain activation studies to reduce the number of dimension and filter out independent and interesting activations. This demonstration shows two studies. One provided by Hvidovre Universitets Hospital, Denmark, that consists of fMRI scannings of humans. Another provided by the EU sponsored MAPAWAMO project from fMRI scannings of monkeys. In the demo comparison between icaMS, icaML, icaMF, icaMF (positive sources) and PCA can be made. More detailes can found in [2].
ICA is used to classify text in extension to the latent semantic indexing framework. ICA show to align the context grouping structure well in a human sense [1], thus can be used for unsupervised classification. The demonstration shows this on medical abstracts (MED dataset), that uses BIC to estimate the number of classes and produces keywords for each class. The icaML algorithm is used.
* A ncurses user interface.
* Network statistics to view the amount of packets and data in many
different protocols, interfaces and hosts.
* View what active TCP connections are on the network.
* View UDP packets.
* View and log ICMP packets.
* View and log the 48bit arp protocol.
And also view what make of network card is in each machine
* Multithreaded so that the user interface does not interfere with any of the packet
captureing methods.
* View and log the following user space protocols
FTP, POP3, HTTP
