To develop human interface for virtual environment, we have constructed a tensed strings based interface device called SPIDAR, which allow us to manipulate virtual object directly just like in real space. SPIDAR can both measure the movement of user's finger tip and offer force display. Since proper force feedback comes out of the proper position measurement, in this paper, we will analyze the possible reasons that may cause position measurement error, and propose an algorithm which can revise the error and improve position measurement precision.

With the development of the Internet, there are more and more shared resources on the Web. Personalized search becomes increasingly important as users demand higher retrieval quality. Personalized search needs to take users' personalized profiles and information needs into consideration. Collaborative tagging (also known as folksonomy) systems allow users to annotate resources with their own tags (features) and thus provide a powerful way for organizing, retrieving and sharing different types of social resources. To capture and understand user preferences, a user is typically modeled as a vector of tag: value pairs (i.e., a tag-based user profile) in collaborative tagging systems. In such a tag-based user profile, a user's preference degree on a group of tags (i.e., a combination of several tags) mainly depends on the preference degree on every individual tag in the group. However, the preference degree on a combination of tags (a tag-group) cannot simply be obtained from linearly combining the preference on each tag. The combination of a user's two favorite tags may not be favorite for the user. In this article, we examine the limitations of previous tag-based personalized search. To overcome their problems, we model a user profile based on combinations of tags (tag-groups) and then apply it to the personalized search. By comparing it with the state-of-the-art methods, experimental results on a real data set shows the effectiveness of our proposed user profile method.

We review our recent work on ultra-long-haul wavelength division multiplexed (WDM) transmission with high spectral efficiency (SE) employing tight pre-filtering and multi-symbol detection. We start the discussion with a theoretical evaluation of the SE limit of pre-filtered modulation in optical fiber communication systems. We show that pre-filtering induced symbol correlation generates a modulation with memory and thus, a higher SE limit than that of the original memory-less modulation. We also investigate the merits of utilizing the pre-filtering induced symbol correlation with multi-symbol detection to achieve high SE transmission. We demonstrate transoceanic WDM transmission of a pre-filtered polarization division multiplexed return-to-zero quaternary phased shift keying (PDM-RZ-QPSK) modulation format with multi-symbol detection, achieving 419% SE which is higher than the SE limit of the original memory-less PDM-RZ-QPSK format.

For constructing the next generation education system, we have developed a new human-scale virtual reality interface device called Big-SPIDAR. This device can provide not only the visual and auditory information but also haptic/kinaesthetic display. And it has the capability for the operator or participant to move around inside it. In this paper, we introduce the construction of this interface device and show the evaluation experiments and application systems realized by proposed device.