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Abstract:The Simulink/Stateflow (SL/SF) modeling framework is widely used in industry for the development of control applications. However, such models are not amenable to formal reasoning. Controllers can also be designed using formal specification languages. Such designs can be formally verified, but the models do not explicitly represent control or data flow information. In this paper, we discuss RRM diagrams (RRMDs), a new modelling notation which incorporates the benefits of these two formalisms. RRMDs are graphical formal models and they also support incremental formal development. We have used synchronising state machines to encode RRMDs. We have also developed a prototype tool which translates RRMDs automatically to SL/SF designs.

Information retrieval and extraction essentially rely on estimating the relevance of words present in a large corpus of documents or text. One of the approaches to measuring relevance is analyzing the importance of words based on their statistical distribution within a document. Quite another approach ensues from their linguistic relevance within a logically perceived context.Literature presents a body of work done employing both statistical as well as contextual approaches. The challenge currently is on enhancing the performance of document analysis and clustering systems. Ever since we witnessed a massive explosion of information and raw data available on the web, their analysis demands more rigorous computations and processing. Given the widely distributed environment as a backbone platform for these systems to operate, there is an urgent need to develop techniques to scale up their performance on multiple processors.We propose a parallelized strategy to estimate the statistical as well as contextual relevance of words, employing master-slave configuration on a cluster of processors. Our parallel algorithm has been successfully tested on a self-made Beowulf cluster comprising ten nodes, showing significant performance improvement over single processor implementation, following Amdahl's speedup law.

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