This study investigated the extent that the non-verbal behaviors of virtual humans (VHs) and their socio-demographic attributes altered users' collision avoidance behaviors in Virtual Reality (VR). Users interacted with VHs representing different levels of ethnicities and gender, exhibiting different conditions of physical movement, and gaze behaviors. The VHs were depicted in three major ethnic conditions namely Asian, Caucasian, and Black. The physical movement states of the VHs were either static in the path of the user or walking toward the user in the opposite direction. The non-verbal gaze behavior of the VHs was either direct gaze or averted gaze. We used an HTC Vive tracking system to track users' performing real walking while we collected objective measures (i,e., continuous gaze, fixation gaze, clearance distance, and travel length), and subjective variables (i.e., game experiences and social presence). The results showed that the ethnicity of the VHs significantly impacted the gaze behavior of the users, and the gender of the VHs affected the user avoidance movement and their reciprocal gaze behavior. Our results revealed that users' physical movement, gaze behaviors, and collision avoidance were moderated by the VHs' perceived ethnicity, gender, and gaze behaviors. Understanding the impact of the socio-demographics attributes of VHs and their gaze behavior on users' collision avoidance is critical for applications in which users are navigating through virtual traffic, crowd, and other inter-personal simulations.

In this contribution, we empirically investigated the effect of small talk on the users' non-verbal behaviors and emotions when users interacted with a crowd of virtual humans (VHs) with positive behavioral dispositions. Users were tasked with collecting items in a virtual marketplace via natural speech-based dialogue with a crowd of virtual pedestrians and vendors. The users were able to engage in natural speech-based conversation in a predefined corpus of small talk content that covered various commonplace small talk topics such as conversations about the weather, general concerns, and entertainment based on similar real-life situations. For instance, the VHs with the small talk ability would ask the users some simple questions to make small talk or remind the users of their belongings. We conducted a between-subjects empirical evaluation to investigate whether the user behaviors and emotions were different between a small talk condition and a non-small talk condition, and examined gender effects of the participants. We collected objective and subjective measures of the users to analyze users' emotions and social interaction behaviors, when in conversation with VHs that either possessed small-talk capability or not, besides task or goal oriented dialogue capabilities. Our result revealed that the VHs with small talk capability could alter the emotions and non-verbal behaviors of the users. Furthermore, the non-verbal behaviors between female and male participants differed greatly in the presence or absence of small talk.

Our research proposes an adaptive real-time-service-based distributed scheduling scheme (RTDS) for wireless network system with the Non-Transparent RS architecture which is specified in the IEEE 802.16j standard. The main object of our research is to utilize the RS to decrease the overhead of the BS and enhance the QoS of the real time service connections. We obtain the initial priority value for the order of scheduling through the quantification of each service type specified in IEEE 802.16 standard. The priority value varies according to the bandwidth request and the channel status of each connection, and it may be increased by a emergency packet event or decreased by taking fairness into consideration. The simulation results show that our proposed scheduling scheme performs better than other representative researches and also additionally guarantees the QoS of real time service connections.

Multi-camera systems have been widely used in many video surveillance applications. When an event happens and is monitored across multiple cameras, it is easy for an expert to generate the corresponding spatial representation to comprehend the series of event. However, it is not trivial for users new to the environment. With support from psychological evidences, we propose an approach to mimic generating pictorial-based representation of mental images when a target is moving across the views of cameras. First we conduct a ball-rolling experiment to compare this approach with others. The empirical results demonstrate that the performance of users with this approach is significantly better than others. We suggest that it is because this approach is better for users to preserve spatial representation of the environment while transiting views between cameras. Then we propose a framework to realize this approach. The demonstrations in different situations indicate the validity of such framework.