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Decisional DNA-based embedded systems: A new perspective

Zhang H., Sanin C., Szczerbicki E.

Systems Science

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2010

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Vol. 36, no 1

21-26

EN

Nowadays, knowledge-based embedded systems have become a new trend on embedded systems. They are capable of knowledge acquisition, reusing, evolving and sharing. However, due to the lack of standardized solutions and development platforms, it is not only very hard to share knowledge among different knowledge-based embedded systems, but this also causes huge waste by redesign, redevelopment, and knowledge re-acquiring. In this paper, we propose the Decisional DNA-based Embedded Systems as a new approach to meet this demand. Decisional DNA is a domain-independent, flexible and standard knowledge representation structure. We apply Decisional DNA to embedded systems to make them acquire, reuse, evolve and share knowledge in an easy and standard way. As a result, we propose the features, architecture and application types for the embedded systems.

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A proposal for knowledge sharing in the E-Decisional Community using Decisional DNA

Mancilla-Amaya L., Sanin C., Szczerbicki E.

Systems Science

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2010

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Vol. 36, no 1

13-19

EN

The E-Decisional Community is a proposal that aims at enabling knowledge sharing between individuals and organizations, using the Set of Experience Knowledge Structure (SOEKS) and Decisional DNA as knowledge representations; it is based upon principles from Software Agents, Grid and Cloud computing. In this paper, we present an analysis of different agent communication and knowledge representation languages, with the purpose of defining a set of basic mechanisms to be used in the E-Decisional Community for knowledge exchange between its members.

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Decisional experience: a new approach to intelligent knowledge representation

Sanin C., Szczerbicki E.

Systems Science

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2009

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Vol. 35, no 3

63-67

EN

We learn through experience. Our brain stores knowledge in terms of keeping our own experience from past situations as well as adding knowledge by learning from experiences of others. All these experiences, over generations, are stored in individual's DNA that carries this information into the future. Our idea is to develop an artificial system, an architecture that would support discovering, adding, storing, improving, and sharing knowledge through experience, in a way similar in some very general sense to what happens in nature. We propose a novel approach in which knowledge is represented by Set of Experience Knowledge Structure (SOEKS), and is carried into the future by Decisional DNA. This paper reports on our efforts at the stage of developing and example of SOEKS.

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Implementing decisional DNA in industrial maintenance by a knowledge SOUPA extension

Sanin C., Toro C., Vaquero J., Szczerbicki E., Posada J.

Systems Science

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2007

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Vol. 33, no 2

61-68

EN

In this paper, we present a framework and a system implementation for the exploitation of embedded knowledge in the domain of industrial maintenance in a mobile context, using Augmented Reality techniques. We base our approach in the SOUPA group of ontologies (Standard Ontology for Ubiquitous and Pervasive Applications). Our approach extends SOUPA with two new ontologies: (i) the Set of Experience Knowledge Structure, used to model the user’s experience, and (ii) the AR ontology which models an Augmented Reality environment that is used to enhance the maintenance experience through virtual elements. As test case, we implemented our approach in different portable devices with video input capabilities such as UMPCs and Tablet PCs.