A new hybrid brain-computer interface (BCI), which is based on sequential controls by eye tracking and steady-state visual evoked potentials (SSVEPs), has been proposed for high-speed spelling in virtual reality (VR) with a 40-target virtual keyboard. During target selection, gaze point was first detected by an eye-tracking accessory. A 4-target block was then selected for further target selection by a 4-class SSVEP BCI. The system can type at a speed of 1.25 character/sec in a cue-guided target selection task. Online experiments on three subjects achieved an averaged information transfer rate (ITR) of 360.7 bits/min.

The continuous advances in sensing and positioning technologies have resulted in a dramatic increase in popularity of Location-Based Services (LBS). Nevertheless, the LBS can lead to user privacy breach due to sharing location information with potentially malicious services. A high degree of location privacy preservation for LBS is extremely required. In this paper, a clustering K-anonymity scheme for location privacy preservation (namely CK) is proposed. The CK scheme does not rely on a trusted third party to anonymize the location information of users. In CK scheme, the whole area that all the users reside is divided into clusters recursively in order to get cloaked area. The exact location information of the user is replaced by the cloaked spatial temporal boundary (STB) including K users. The user can adjust the resolution of location information with spatial or temporal constraints to meet his personalized privacy requirement. The experimental results show that CK can provide stringent privacy guarantees, strong robustness and high QoS (Quality of Service).

We investigate an online problem of a robot exploring the outer boundary of an unknown simple polygon P. The robot starts from a specified vertex s and walks an exploration tour outside P. It has to see all points of the polygon's outer boundary and to return to the start. We provide lower and upper bounds on the ratio of the distance traveled by the robot in comparison to the length of the shortest path. We consider P in two scenarios: convex polygon and concave polygon. For the first scenario, we prove a lower bound of 5 and propose a 23.78-competitive strategy. For the second scenario, we prove a lower bound of 5.03 and propose a 26.5-competitive strategy.