In the Big Data era, workflow systems must embrace data parallel computing techniques for efficient data analysis and analytics. Here, an easy-to-use, scalable approach is presented to build and execute Big Data appli...
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In the Big Data era, workflow systems must embrace data parallel computing techniques for efficient data analysis and analytics. Here, an easy-to-use, scalable approach is presented to build and execute Big Data applications using actor-oriented modeling in data parallel computing. Two bioinformatics use cases for next-generation sequencing data analysis demonstrate the approach's feasibility.
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...
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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.
The article presents a software architecture to optimize the process of prototyping and deploying robot controllers that are synthesized using model-based design methodologies. The architecture is composed of a framew...
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The article presents a software architecture to optimize the process of prototyping and deploying robot controllers that are synthesized using model-based design methodologies. The architecture is composed of a framework and a pipeline. Therefore, the contribution of the article is twofold. First, we introduce an open-source actor-oriented framework that abstracts the common robotic uses of middlewares, optimizers, and simulators. Using this framework, we then present a pipeline that implements the model-based design methodology. The components of the proposed framework are generic, and they can be interfaced with any tool supporting model-based design. We demonstrate the effectiveness of the approach describing the application of the resulting synchronous dataflow architecture to the design of a balancing controller for the YARP-based humanoid robot iCub. This example exploits the interfacing with Simulink (R) and Simulink (R) Coder (TM).
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