Feature selection is one of the most important research topics in high dimensional array data analysis. We propose a two-way filtering based method that utilizes a pair of statistics coupled with rigorous cross-validation to identify the most informative features from different types of distributions. We evaluate the utility of the proposed adaptive feature selection method on six MicroArray Quality Control Phase II (MAQC-II) datasets. The results show that our method yields models with significantly fewer features and can achieve comparable or superior classification performance compared to models generated from other feature selection methods, suggesting high quality feature selection.

Impromptu is a mobile audio device which uses wireless Internet Protocol (IP) to access novel computer-mediated voice communication channels. These channels show the richness of IP-based communication as compared to conventional mobile telephony, adding audio processing and storage in the network, and flexible, user-centered call control protocols. These channels may be synchronous, asynchronous, or eventtriggered, or even change modes as a function of other user activity. The demands of these modes plus the need to navigate with an entirely non-visual user interface are met with a number of audio-oriented user interaction techniques.