Results for 'Maj Rafn Hollesen'

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  1. Ksenologia i ksenotopografia Bernharda Waldenfelsa wobec podstawowych założeń światotwórczych literatury fantastycznej (Orson Scott Card, Neil Gaiman, George R. R. Martin).Krzysztof M. Maj - 2014 - Hybris, Revista de Filosofí­A (27):072-095.
    XENOLOGY AND XENOTOPOGRAPHY OF BERNHARD WALDENFELS The paper strives to adapt Bernhard Waldenfels’ xenology and so called ‘xenotopography’ for the philosophico-literary studies in fantastic world-building with a special concern of the ‘portal-quest’ model of fantasy and SF. Following Waldenfel’s remarks on the nature of post- Husserlian diastasis of our world [Heimwelt] and otherworld [Fremdwelt] and acknowledging the consequences of allocating one’s attitude towards the otherness in the symbolical borderland [‘sphere of intermonde’] in between, it is examined whether such a model (...)
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  2. Games 2.0 jako próba konstrukcji społeczno-kulturowego perpetuum mobile.Andrzej Klimczuk - 2008 - Homo Communicativus 5:177--187.
    Increase in popularity of games like "Second Life" has contributed not only to significant changes in the development of the electronic entertainment industry. Promoting Games 2.0, the new trend of video game production that are assumed to be the virtual worlds that contain user-generated content makes both measured with a specific technological innovation, as well as a serious change in the organization of socio-cultural heritage. The article presents problems of the existing difficulties of terminology, the implications of the availability of (...)
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  3. Real Attribute Learning Algorithm.Julio Michael Stern, Marcelo de Souza Lauretto, Fabio Nakano & Celma de Oliveira Ribeiro - 1998 - ISAS-SCI’98 2:315-321.
    This paper presents REAL, a Real-Valued Attribute Classification Tree Learning Algorithm. Several of the algorithm's unique features are explained by úe users' demands for a decision support tool to be used for evaluating financial operations strategies. Compared to competing algorithms, in our applications, REAL presents maj or advantages : (1) The REAL classification trees usually have smaller error rates. (2) A single conviction (or trust) measure at each leaf is more convenient than the traditional (probability, confidence-level) pair. (3) No need (...)
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