Recent research has shown growing interest in the process by which narcissism triggers immersion in social network games (SNG). Highly narcissistic individuals are motivated not only by the achievement of goals and monopoly of materials (i.e., self-enhancement), but also by comparison and competition with others (i.e., social comparison). We predicted that the common rules and environments of SNG and massively multiplayer online role-playing games (MMORPG), such as systems of exchanging items and ranking players, facilitate immersion of highly narcissistic individuals during the game. Structural equation modeling of data from 378 SNG players and 150 MMORPG players recruited online showed that self-esteem inhibited game immersion, whereas narcissism increased game immersion via motivation for goal attainment. SNG players were more likely to be immersed in the game via motivation for goal attainment than MMORPG players. These findings suggest that, compared with MMORPG, the environments of SNG provide strong incentives not for those high in self-esteem who seek acceptance of others, but for those high in narcissism who are motivated by self-enhancement via competition with others.
The purpose of this research is to improve the position and angle estimation accuracy of the wheelchair guide system for Hemiplegic patients. The wheelchair guide system aims to assist the patients to transfer between their wheelchair and bed. This system prompts properly to user depending on the situation as same as care worker. Therefore, the system is developed to prompt the measured position and angle of wheelchair. The position estimator uses an AR marker to detect the wheelchair position. However, its estimation is contaminated by measurement noises and sometimes fails because the marker is out of the camera’s field of view. To improve the estimation of position and moving direction, we introduce the kinematic model of the wheelchair and utilize the Extended Kalman Filter with the model. In this paper, we describe the self-position estimation method of the navigation system and AR marker, with the estimation method using Kalman Filter.
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