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The periodic table allows students to easily understand the chemical elements and predict the behavior of theoretical yet undiscovered new elements. Many memorization techniques have been used for learning the periodic table, yet serious games (i.e., designed for a primary purpose other than pure entertainment) have been underexplored to complement or even replace such memorization techniques. Since CHEMMEND, an existing physical card game, was found to assist with learning the periodic table, we explore the potential of E-CHEMMEND, a digital version of the game as an aid to memorize the group and period numbers of the elements. E-CHEMMEND is a single-player serious game to explore the effect of four different game conditions involving two experimental factors that account for different educational scenarios. The first factor investigates the role of playing through levels of increasing difficulty versus playing with all elements from the very beginning. The second factor investigates the role of displaying the group and period numbers of the chemical element along with its symbol versus only displaying the element symbol. Preliminary results show that E-CHEMMEND is perceived as more enjoyable when the group and period numbers are displayed. In contrast, the game is found to better assist learning when this information is hidden and levels are shown. Taken together, our results suggest that a variety of educational purposes can be accommodated with a range of game settings. Ultimately, the design rationale and the lessons learned while testing E-CHEMMEND will be valuable for chemistry instructors and education researchers. A desktop-based Windows executable version of the game is available at http://www.chemmend.uji.es/game.

Affect decoding through brain-computer interfacing (BCI) holds great potential to capture users' feelings and emotional responses via non-invasive electroencephalogram (EEG) sensing. Yet, little research has been conducted to understand efficient decoding when users are exposed to dynamic audiovisual contents. In this regard, we study EEG-based affect decoding from videos in arousal and valence classification tasks, considering the impact of signal length, window size for feature extraction, and frequency bands. We train both classic Machine Learning models (SVMs and k-NNs) and modern Deep Learning models (FCNNs and GTNs). Our results show that: (1) affect can be effectively decoded using less than 1 minute of EEG signal; (2) temporal windows of 6 and 10 seconds provide the best classification performance for classic Machine Learning models but Deep Learning models benefit from much shorter windows of 2 seconds; and (3) any model trained on the Beta band alone achieves similar (sometimes better) performance than when trained on all frequency bands. Taken together, our results indicate that affect decoding can work in more realistic conditions than currently assumed, thus becoming a viable technology for creating better interfaces and user models. [ABSTRACT FROM AUTHOR]

Positive player's experiences greatly rely on a balanced gameplay where the game difficulty is related to player's skill. Towards this goal, the gameplay can be modulated to make it easier or harder. In this work, a modulating mechanism based on visual computing is explored. The main hypothesis is that simple visual modifications of some elements in the game can have a significant impact on the game experience. This concept, which is essentially unexplored in the literature, has been experimentally tested with a web-based cube puzzle game where participants played either the original game or the visually modified game. The analysis is based on players' behavior, performance, and replies to a questionnaire upon game completion. The results provide evidence on the effectiveness of visual computing on gameplay modulation. We believe the findings are relevant to game researchers and developers because they highlight how a core gameplay can be easily modified with relatively simple ingredients, at least for some game genres. Interestingly, the insights gained from this study also open the door to automate the game adaptation based on observed player's interaction. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.robot.2009.10.002 Byline: V. Javier Traver (a)(b), Alexandre Bernardino (c) Abstract: Log-polar imaging consists of a type of methods that represent visual information with a space-variant resolution inspired by the visual system of mammals. It has been studied for about three decades and has surpassed conventional approaches in robotics applications, mainly the ones where real-time constraints make it necessary to utilize resource-economic image representations and processing methodologies. This paper surveys the application of log-polar imaging in robotic vision, particularly in visual attention, target tracking, egomotion estimation, and 3D perception. The concise yet comprehensive review offered in this paper is intended to provide novel and experienced roboticists with a quick and gentle overview of log-polar vision and to motivate vision researchers to investigate the many open problems that still need solving. To help readers identify promising research directions, a possible research agenda is outlined. Finally, since log-polar vision is not restricted to robotics, a couple of other areas of application are discussed. Author Affiliation: (a) Computer Languages and Systems Dept., Universitat Jaume I, Castellon, Spain (b) Institute of New Imaging Technologies (INIT), Universitat Jaume I, Castellon, Spain (c) Instituto de Sistemas e Robotica, Instituto Superior Tecnico, Lisbon, Portugal Article History: Received 31 July 2008; Revised 6 October 2009; Accepted 13 October 2009

Nowadays, there are a very large number of patients that need specific health support at home. The deployment of broadband communication networks is making feasible the provision of home care services with a proper quality of service. This paper presents a telehomecare multimedia platform that runs over integrated services digital network and internet protocol using videoconferencing standards H.320 and H.323, and standard TV set for patient interaction. This platform allows online remote monitoring: ECG, heart sound, blood pressure. Usability, affordability, and interoperability were considered for the design and development of its hardware and software components. A first evaluation of technical and usability aspects were carried forward with 52 patients of a private clinic and 10 students in the University. Results show a high rate (mean = 4.33, standard deviation--SD = 1.63 in a five-points Likert scale) in the global perception of users on the quality of images, voice, and feeling of virtual presence. Index Terms--Home care assistance, multimedia, set top box, telemedicine.