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The basic problem rooted in Information Theory (IT) foundations (Shannon, Bell Syst Tech J 27:379–423 and 623–656, 1948; Volkenstein, Entropy and Information. Series: Progress in Mathematical Physics, 2009) is to reconstruct, as closely as possible, the input signal after observing the received output signal. The Shannon information measure is the only possible one in this context, but it must be clear that it is only valid within the more restricted scope of coding problems that C. E. Shannon himself had seen in his lifetime (Shannon, Bell Syst Tech J 27:379–423 and 623–656, 1948). As pointed out by Alfred Rényi (1961), in his essential paper (Rényi, Proc. of the 4th Berkeley Symposium on Mathematics, Statistics and Probability, 547–561, 1961) on generalized information measures, for other sorts of problems other quantities may serve just as well as measures of information, or even better. This would be supported either by their operational significance or by a set of natural postulates characterizing them, or preferably by both. Thus, the idea of generalized entropies arises in scientific literature. We analyze here some new measures of Entropy, very useful to be applied on Biocomputing (Ulanowicz and Hannon, Proc R Soc Lond B 232:181–192, 1987; Volkenstein, Entropy and Information. Series: Progress in Mathematical Physics, 2009). [ABSTRACT FROM AUTHOR]

The capability of perceiving and expressing emotions through different modalities is a key issue for the enhancement of human-computer interaction. In this paper we present a novel architecture for the development of intelligent multimodal affective interfaces. It is based on the integration of Sentic Computing, a new opinion mining and sentiment analysis paradigm based on AI and Semantic Web techniques, with a facial emotional classifier and Maxine, a powerful multimodal animation engine for managing virtual agents and 3D scenarios. One of the main distinguishing features of the system is that it does not simply perform emotional classification in terms of a set of discrete emotional labels but it operates in a continuous 2D emotional space, enabling the integration of the different affective extraction modules in a simple and scalable way. [ABSTRACT FROM AUTHOR]

Emotions are a fundamental component in human experience, cognition, perception, learning and communication. In this paper we explore how the use of Common Sense Computing can significantly enhance computers΄ emotional intelligence i.e. their capability of perceiving and expressing emotions, to allow machines to make more human-like decisions and improve the human-computer interaction. [ABSTRACT FROM AUTHOR]

Research in the field of knowledge representation system is usually focused on methods for providing high-level descriptions of the world that can be effectively used to build intelligent applications. This paper shares the development process of ontology which involves preparing questionnaires, design decisions, and interviewing key persons. This is an ongoing work resulting in the development of ontology for knowledge management in an enterprise. The final result is a knowledge ontology, coined as Know-Ont, is a collection of concepts and their related properties from maintenance and new product design domain that fit together to process and store knowledge thus making it available for later reuse. [ABSTRACT FROM AUTHOR]