We consider RFID bookshelves, which detect the location of books using RFID. An RFID bookshelf has the antennas of RFID readers in the boards, and detects the location of an RFID tag attached to a book. However, the accuracy is not good with the experience of the existing system, and sometimes reads the tag of the next or even further area. In this paper, we propose a method to improve the location detection using naive Bayes classifer, and show the experimental result. We obtained 78.6% of F-measure for total 12658 instances, and show the advantage against the straightforward approach of calculating the center of gravity of the read readers. More importantly, we show the performance is less dependent of a change of layouts and a difference of books by leave-1-layout/book-out cross validation. This is favorable for the feasibility in library operation.

Mobile devices have acceleratedly penetrated into our daily lives. Though they were originally designed as a communication tool or for personal use, and due to the rapid availability of wireless network technologies, people have begun to use mobile devices for supporting collaborative work and learning. There is, however, a serious problem in mobile devices related to their user interfaces. In this paper, we try to alleviate the problem and propose intuitive techniques for information transfer, which is one of the typical usages of mutually-connected computers. Our system, Toss-It, enables a user to send information from the user's PDA to other electronic devices with a "toss" or "swing" action, like a user would toss a ball or deal cards to others. The implementation of Toss-It consists of three principle parts - gesture recognition, location recognition, and file transfer. We especially describe the details of gesture recognition and location recognition. We then evaluate the practicability and usability of Toss-It through the experiments. We also discuss user scenarios describing how Toss-It can support users' collaborative activities.