JOURNAL OF COMPUTERS (JCP)
ISSN : 1796-203X
Volume : 4    Issue : 9    Date : September 2009

Sharing Biomedical Learning Knowledge for Social Ambient Intelligence
Sabah Mohammed, Jinan Fiaidhi, and Osama Mohammed
Page(s): 905-912
Full Text:
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Abstract
In this paper, we describe a Bio-SAmI system, which is a Biomedical learning system that is context-
aware and responsive to mobile learners sharing information on a social network. Bio-SAmI is a
Web 2.0 enabled system which employees Social Ambient Intelligence techniques. The Bio-SAmI
infrastructure is based on the Actor model that treats mobile users or “actors" as the universal
primitives of computation. The actor model is implemented using a combination of Java enabled
APIs including SALSA, JADE, LEAP and tuPrologME. The implemented prototype enable learners to
share biomedical information represented by the DICOM SR standard in relation to the notion of
inflammation as well as to respond to variety of learning queries including classifying learning case
studies, finding learning case studies, locating a FOAF learner and syndication and aggregation of
learning case studies .

Index Terms
Ambient Intelligence, Web 2.0, Biomedical Learning, JADE, Actor-Oriented Programming, SALSA,
tuPrologME, DICOM