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Collaborative note taking enables students in a class to take notes on their PDAs and share them with their "study group" in real-time. Students receive instructor's slides on their PDAs as the instructor displays them. As the individual members of the group take notes pertaining to the slide being presented, their notes are automatically sent to all members of the group. In addition, to reduce their typing, students can use text they receive from other students and from the instructors slides to construct their notes. This system has been used in actual practice for a graduate level course on wireless mobile computing.

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Several methodologies on the provisioning of the Location-Based Services (LBSs) solely using GPS-based positioning or combining several positioning techniques like GPS, GSM Cell-ID, Wi-Fi, Bluetooth and RFID etc. have been proposed over the past few years. Most of these systems do not focus on limited battery power, memory-constraint of the mobile devices, the heterogeneity of mobile platform and proper authentication checks before providing LBSs to the mobile user. Our proposed system utilizes low-cost, low-power Bluetooth wireless technology as indoor positioning technique and combines it with GPSbased positioning to accurately sense the location in outdoor environment. The inclusion of HTML-to-WML parser into the Middleware deployed on each Base Station (BS) enables the devices with micro browser to invoke the LBSs properly. The mobile client application developed in Java is portable and interoperable with a diverse set of mobile platforms. The client application can also run on devices not having support of location API. Scatternet support with our proposed LBS Infrastructure makes it scalable with increasing number of client devices. This paper also evaluates the performance of the Middleware in terms of connection setup time and service consumption time with respect to varying number of mobile clients.

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In this report, a supervised methodology has been presented to extract the root forms of the Bengali verbs using the grammatical rules proposed by Panini in Ashtadhyayi. The proposed system has been developed based on tense, person and morphological inflections of the verbs to find their root forms. The work has been executed in two phases: first, the surface level forms or inflected forms of the verbs have been classified into a certain numbers of groups of similar tense and person. For this task, a standard pattern, available in Bengali language has been used. Next, a set of rules have been applied to extract the root form from the surface level forms of a verb. The system has been tested on 10000 verbs collected from the Bengali text corpus developed in the TDIL project of the Govt. of India. The accuracy of the output has been achieved 99% which is verified by a linguistic expert. Root verb identification is a key step in semantic searching, multi-sentence search query processing, understanding the meaning of a language, disambiguation of word sense, classification of the sentences etc.