The rapid evolution of ICT creates numerous opportunities for agricultural education and training. Digital learning resources are organized in online databases called learning repositories, in which people can search, locate, and access resources. In order to facilitate the exchange of information between such repositories, the issue of metadata interoperability is crucial. In this paper, we particularly focus on metadata interoperability of learning repositories with content relevant to agricultural stakeholders. More specifically, we present results from an analysis of implementations of metadata standards in agricultural learning repositories around the world. The results provide useful feedback to the developers of repositories with educational content for agricultural stakeholders, as well as directions for potential harmonization of work in this area.

The rapid changes in the means of information access occasioned by the emergence of the World Wide Web have spawned an upheaval in the means of describing and managing information resources. Metadata is a primary tool in this work, and an important link in the value chain of knowledge economies. Yet there is much confusion about how metadata should be integrated into information systems. How is it to be created or extended? Who will manage it? How can it be used and exchanged? Whence comes its authority? Can different metadata standards be used together in a given environment? These and related questions motivate this paper. The authors hope to make explicit the strong foundations of agreement shared by two prominent metadata Initiatives: the Dublin Core Metadata Initiative (DCMI) and the Institute for Electrical and Electronics Engineers (IEEE) Learning Object Metadata (LOM) Working Group. This agreement emerged from a joint metadata taskforce meeting in Ottawa in August, 2001. By elucidating shared principles and practicalities of metadata, we hope to raise the level of understanding among our respective (and shared) constituents, so that all stakeholders can move forward more decisively to address their respective problems. The ideas in this paper are divided into two categories. Principles are those concepts judged to be common to all domains of metadata and which might inform the design of any metadata schema or application. Practicalities are the rules of thumb, constraints, and infrastructure issues that emerge from bringing theory into practice in the form of useful and sustainable systems.

he improvement and development of MANET protocols has been widely researched in order to bring about new technology with the rapidly developing field. More emphasis has been placed on development of protocols with some improvements focused on one issue in MANETs (ECMANSI, MANSI, ZRP, DVMRP) than working on all round MANET that would significantly tackle most if not all issues with MANET protocols so far (FLIP). However, there has also been more emphasis on development of non demanding applications that are not included multiplayer gaming and real-time multimedia content rich streaming applications. This paper looks at the use of mobile devices in gaming and multimedia rich applications. It proposes a protocol, which is in development that offers better efficiency, reliability, robustness and adaptability of wireless communication.

The research presented here, attempts to review a range of techniques commonly categorized under the umbrella of artificial intelligence (A.I.) that could be applied when developing agents with emotions in a range of applications. The paper focuses on anger (and its related emotions), an emotion strongly linked with aggression which of course forms the basis of many computer games where killing or attacking other players or in-game agents is often central to the game’s purpose. The paper begins with a psychology focused review of anger and its related emotions, before presenting techniques to encode some of these elements using Finite State Machines and Fuzzy Logic.

The authors propose a single refinement method for B, inspired directly by Gardiner and Morgan’s longstanding single complete rule for data refinement, and rendered practical by application of the current first author’s recent first-order characterisation of refinement between monotonic computations