5th IEEE International Workshop on Robot and Human by Japan) IEEE International Workshop on Robot and Human

By Japan) IEEE International Workshop on Robot and Human Communication (5th : 1996 : Tsukuba-shi

Viability of human conversation with robots and automations through speech and different human modalities of verbal exchange are tested. Projections of VLSI circuit density raises and value mark downs influence on financial purposes in and purchaser items are projected.

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Extra info for 5th IEEE International Workshop on Robot and Human Communication Ro-Man '96 Tsukuba: November 11-14, 1996 Auditorium, Aist Tsukuba Research Center Tsukuba, Ibaraki, Japan: Proceedings

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As noted in [5] and many other up-to-date publications, the time of “naïve IT-romanticism” is over. V. ), Information Fusion and Geographic Information Systems, Lecture Notes in Geoinformation and Cartography. 1007/978-3-642-00304-2_3, © Springer-Verlag Berlin Heidelberg 2009 39 40 V. Popovich is defined by IT specific influence upon the core activities or businesses either of the advanced companies or of the managerial and technical systems rather than by the existence of advanced techniques and standard software.

Kangas JA, Kohonen TK, and Laaksonem JT (1990) Variants of self-organizing maps. IEEE Trans Neural Networks 1(1):93–99 21. Bação F, Lobo V, and Painho M (2005) The self-organizing map, the Geo-SOM, and relevant variants for geosciences. Comput and Geosci 31(2):155–163 22. Ambroise C, et al. (1996) Analyzing dissimilarity matrices via Kohonen maps. In: 5th Conference of the International Federation of Classification Societies (IFCS 1996). Kobe, Japan 23. Cottrell M, Ibbou S, and Letremy P (2004) SOM-based algorithms for qualitative variables.

The original SOM algorithm and most of its variants deal with vector data only. Some variants for nonvector data have also been proposed namely the dissimilarity SOM [22], the Kohonen multiple correspondence analysis and the Kohonen algorithm on disjunctive table [23]. For the simpler case of binary valued data, both the original algorithm using 0 and 1 as real numbers and binary variants of SOM produce good results [24, 25]. SOMs have frequently been used to analyze temporal data, such as EEG or Stock Exchange data.

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