By Daniel J. Olsher (auth.), Huaguang Zhang, Amir Hussain, Derong Liu, Zhanshan Wang (eds.)

This booklet constitutes the refereed lawsuits of the fifth overseas convention on mind encouraged Cognitive platforms, BICS 2012, held in Shenyang, Liaoning, China in July 2012. The forty six top of the range papers awarded have been conscientiously reviewed and chosen from 116 submissions. The papers are equipped in topical sections on biologically encouraged platforms, cognitive neuroscience, types of realization, and neural computation.

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Extra resources for Advances in Brain Inspired Cognitive Systems: 5th International Conference, BICS 2012, Shenyang, China, July 11-14, 2012. Proceedings

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1 Introduction In recent years, researchers have been very interested in building human computer interaction systems that could tap into users existing real world non-digital skills instead of requiring a totally different set of new interaction rules. For instance, many of the iPhone capabilities are successful examples of this context aware, reality-based computing movement [1]. However, different communities couch this idea in different terms. In virtual environments, the most important question has been how developers could leverage factors that enhance users physically transporting themselves to the computer-simulated environments and interact with the environments as if they were real.

More specifically, this study is concerned with plausibility, or the illusion that what is happening in the virtual environment is real (even though participants metacognitively know that it is not) [5]. For example, plausibility was measured in terms of how close to the avatar’s finger (degree of risk) a cut is made in the current experimental task. If a participant demonstrated caution and planning when making cuts, a higher degree of plausibility was assumed. Alternatively, if the participant were to make cuts with greater risk taken and a lack of planning; a lower degree of plausibility was assumed.

20 T. Mazzocco et al. Table 2. Performance comparison Strict acc. Relaxed acc. 0, the extraction of knowledge from the huge amount of available unstructured information – such as opinions and sentiments – derived from blog, wikis and social networks is a very arduous task. While existing approaches mainly work at a syntactic level, we employ computational techniques and tools to analyze text natural language at a semantic level: in particular, opinions and sentiments extracted from the Web are organized using AffectiveSpace, a multi-dimensional vector space for affective common sense reasoning.

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