14 Genome Informatics 12: 14–23 (2001) Selecting Informative Genes with Parallel Genetic Algorithms in Tissue Classification

Recent advances in biotechnology offer the ability to measure the levels of expression of thousands of genes in parallel. Analysis of such data can provide understanding and insight into gene function and regulatory mechanisms. Several machine learning approaches have been used to aid to understand the functions of genes. However, these tasks are made more difficult due to the noisy nature of array data and the overwhelming number of gene features. In this paper, we use the parallel genetic algorithm to filter out the informative genes relative to classification. By combing with the classification method proposed by Golub et al. [10] and Slonim et al. [17], we classify the data sets with tissues of different classes, and the preliminary results are presented in this paper

Humanoid robot presentation controlled by multimodal presentation markup language MPML

We have developed a Multimodal Presentation Markup Language, called MPML. In our previous studies, we have succeeded to make attractive multimodal presentation with animated virtual characters easily. Then we have combined the MPML with a two-legged humanoid robot, instead of the animated character on 2D screen. It enables an end-user to control freely the humanoid robot presenter for his/her own web-based multimodal presentation. The humanoid robot introduces the multimedia contents with a voice with pointing at a screen using a laser pointer. A single MPML program can generate both animated character presentation on 2D screen and humanoid robot presentation in 3D space. We also show empirically how controllable and expressive the presentation is by means of the humanoid robot.