Abstract
This paper presents the Inter-Module Communication (IMC) protocol, a message-oriented protocol designed and implemented in the Underwater Systems and Technology Laboratory (LSTS) to build interconnected systems of vehicles, sensors and human operators that are able to pursue common goals cooperatively by exchanging real-time information about the environment and updated objectives. IMC abstracts hardware and communication heterogeniety by providing a shared set of messages that can be serialized and transferred over different means. The described protocol contrasts with other existing application level protocols by not imposing or assuming a specific software architecture for client applications. Native support can be automatically generated for different programming languages and/or computer architectures resulting in optimized code which can be used both for networked nodes and also for inter-process and inter-thread communication. The protocol has already been tested throughout various experiments led by LSTS where it has taken care of communications between vehicles, sensors and operator consoles. We are now developing the protocol in the direction of having multi-vehicle cooperation using live data from environmental sensors and mixed-initiative user interaction.

Abstract
Factors such as the growing number of multimedia terminals, the constant increase of bandwidth available per user, and the large number of existing data sharing applications, are compelling users to generate and distribute their own content to restricted groups of other users. Inorder to support such scenario, we present an IMS-based solution that enables content distribution, in multicast, to groups of users, where the source of the content is also an end-user The proposed solution allows the source of content to configure the service, indicating a list of authorized receivers and both the transmission date and duration. Moreover, the proposed solution also allows the operator to manage the registered user profiles, to impose access control and to validate the configurations submitted by the users.

Abstract
Learning objects are not a new concept, being currently produced either according to existent specifications, or in an ad hoc way. However, a system that can easily classify them for automatic storage is still missing In this article we propose a repository of learning objects which is capable of automatic classification and categorization based on a semantic organization. The classification is based on a text extraction mechanism which then uses text mining methods. We present a methodology for the initial clustering of objects, and a technique for maintaining the organization with continuous arrival of new objects.

Abstract
The general available tools for analyzing interactions in online discussion forums appear to be insufficient to characterize groups of medium/large dimensions, as they are limited to provide general information of participation, access statistics and message posting. Our research contributes for analyzing and characterizing asynchronous online interactions applying the Social Network Analysis methodology, by providing e-learning platforms with an interactive graph - the iGraph - that illustrates, and analyses, students' interactions. In a graphical interface embedded in an open source learning management system we combine real-time graphs and numerical indicator to provide the educator with a more thorough understanding of relations between course participants. Preliminary results indicate that the iGraph enables an insightful characterization of the interactions between actors and their participations in discussion forums.

Abstract
In this paper we present the architecture of RTPM, a middle-ware framework aimed at supporting the development and management of information systems for high-speed public transportation systems. The framework is based on a peer-to-peer overlay infrastructure with the main focus being on providing a scalable, resilient, reconfigurable, highly available platform for real-time and QoS computing. Copyright 2008 ACM.

Abstract
AGILMAT is a web application designed to help students learn Mathematics, with focus on high-school algebra and calculus drills. A modular and extensible architecture and a wizard-based configuration interface decoupled from the system core are major design features of AGILMAT. The drill expressions are specified by grammars and constraints imposed by default profiles and user options, so that AGILMAT may support distinct learning levels and stages. The core system uses symbolic manipulation and automated reasoning to provide correct answers for the drills. The paper shows how AGILMAT may be used to create and customize drills automatically.