By Arvid Kappas (auth.), Sidney D’Mello, Arthur Graesser, Björn Schuller, Jean-Claude Martin (eds.)

ISBN-10: 3642245994

ISBN-13: 9783642245992

ISBN-10: 3642246001

ISBN-13: 9783642246005

The two-volume set LNCS 6974 and LNCS 6975 constitutes the refereed lawsuits of the Fourth overseas convention on Affective Computing and clever interplay, ACII 2011, held in Memphis,TN, united states, in October 2011.
The one hundred thirty five papers during this quantity set awarded including three invited talks have been conscientiously reviewed and chosen from 196 submissions. The papers are prepared in topical sections on popularity and synthesis of human impact, affect-sensitive purposes, methodological concerns in affective computing, affective and social robotics, affective and behavioral interfaces, proper insights from psychology, affective databases, review and annotation tools.

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Extra resources for Affective Computing and Intelligent Interaction: 4th International Conference, ACII 2011, Memphis, TN, USA, October 9–12, 2011, Proceedings, Part I

Sample text

OnTask Conv Off Task -- Bored Off Task -- Eng. Conc. OnTask Conv -- Bored OnTask Conv -- Eng. Conc. 10) The Dynamics between Student Affect and Behavior Occurring 21 The pattern between boredom and off-task behavior was somewhat non-intuitive. 02. 54. 01. This finding suggests that off-task behavior relieves boredom, in turn suggesting that off-task behavior may disrupt the “vicious cycles” of continual boredom that have been reported in [1, 6]. The dynamics between frustration and off-task behavior was also interesting.

The pseudo code presented in Table 1 describes the major steps of the algorithm. Table 1. ,Dn}, Initialize all classifier weights; wi = 1. i =1:n ─ Classification: For a new example x, calculate the support for each class as the sum of the weights of all classifiers Di that suggest class label ck for x. Set x to the class with largest support. k=1:number of classes ─ Updating: if x is classified correctly by classifier Di then its weight is increased (promotion) by wi = alpha * wi,, where alpha > 1.

Fig. 1. The virtual laboratory for f chemistry (top window represents the original version botttom window represents the game veersion) Student behavior was co oded as they used both versions of the virtual laboratoory, by a pair of expert coders. The coders used software on a Google Android handhheld nted an observation protocol developed specifically for the computer, which implemen process of coding behaviorr and affect during use of educational software, replicatting the protocol in [1]. All cod ding was conducted by the third and fourth authors.

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Affective Computing and Intelligent Interaction: 4th International Conference, ACII 2011, Memphis, TN, USA, October 9–12, 2011, Proceedings, Part I by Arvid Kappas (auth.), Sidney D’Mello, Arthur Graesser, Björn Schuller, Jean-Claude Martin (eds.)


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