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A Method of Representing Knowledge of Toolkits in a Pervasive Toolroom Maintenance System

Authors: A. Mohamed Mydeen, Pallapa Venkataram

Abstract:

The learning process needs to be so pervasive to impart the quality in acquiring the knowledge about a subject by making use of the advancement in the field of information and communication systems. However, pervasive learning paradigms designed so far are system automation types and they lack in factual pervasive realm. Providing factual pervasive realm requires subtle ways of teaching and learning with system intelligence. Augmentation of intelligence with pervasive learning necessitates the most efficient way of representing knowledge for the system in order to give the right learning material to the learner. This paper presents a method of representing knowledge for Pervasive Toolroom Maintenance System (PTMS) in which a learner acquires sublime knowledge about the various kinds of tools kept in the toolroom and also helps for effective maintenance of the toolroom. First, we explicate the generic model of knowledge representation for PTMS. Second, we expound the knowledge representation for specific cases of toolkits in PTMS. We have also presented the conceptual view of knowledge representation using ontology for both generic and specific cases. Third, we have devised the relations for pervasive knowledge in PTMS. Finally, events are identified in PTMS which are then linked with pervasive data of toolkits based on relation formulated. The experimental environment and case studies show the accuracy and efficient knowledge representation of toolkits in PTMS.

Keywords: Generic knowledge representation, toolkit, toolroom, pervasive computing.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1111795

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References:


[1] William Pike, Mark Gahegan, Beyond ontologies: Toward situated representations of scientific knowledge, In International Journal of Human-Computer Studies, pp. 659-673, Elsevier 2007.
[2] Vinu P.V., Sherimon P.C., Reshmy Krishnan, Towards pervasive mobile learning - the vision of 21st century, In 3rd World Conference on Educational Sciences, vol. 15, pp. 3067-3073, Elsevier 2011.
[3] Stephen Grimm, Pascal Hitzler, Andreas Abecker, Knowledge Representation and Ontologies: Logic, Ontologies and Semantic Web Languages.
[4] YAN Lei, WANG Xinying, DONG Junlei, A power grid knowledge representation using agent based representation in pervasive computing, In Information Management and Engineering (ICIME), The 2nd IEEE International Conference on pp. 297-300. IEEE 2010.
[5] Stephen Peters, Howard E. Shrobe, Using Semantic Networks for Knowledge Representation in an Intelligent Environment, The 1st IEEE Conference on Pervasive Computing and Communications (PerCom 2003), pp. 323-329, IEEE 2003.
[6] Harry Chen, Tim Finin, Anupam Joshi, An Ontology for Context Aware Pervasive Computing Environments, In The Knowledge Engineering Review, Vol. 18:3, pp. 197-207, Cambridge University Press, 2004.
[7] Petridis. K, Kompatsiaris. I, Strintzis. M.G., Knowledge Representation for Semantic Multimedia Content Analysis and Reasoning, EWIMT, 2004.
[8] Mikko Perttunen, Jukka Riekki, Ora Lassila, Context Representation and Reasoning in Pervasive Computing: A Review, In International Journal of Multimedia and Ubiquitous Engineering, Vol. No.4, October 2009.
[9] Christopher Brewster, Kieron O’Hara, Knowledge Representation with Ontologies: Present challenges Future possibilities, In International Journal of Human-Computer Studies, pp. 563-568, Elsevier, 2007.
[10] Matthias Lampe, Martin Strassner, Elgar Fleisch, A Ubiquitous Computing Environment for Aircraft Maintenance, In Symposium on Applied Computing, ACM 2004.
[11] Yuh-Jen Chen, Development of a method for ontology-based empirical knowledge representation and reasoning, In Decision Support Systems, Elsevier 2010.
[12] Alan Jovic, Marin Prcela, Dragan Gamberger, Ontologies in Medical Knowledge Representation, In 29th International Conference on Information Technology Interfaces, 2007.
[13] Sabine Graf, Kathryn Mac Callum, Tzu-Chien Liu, Maiga Chang, Dunwei Wen, Qing Tan, Jon Dron, Fuhua Lin, Nian-Shing Chen, Rory McGreal, Kinshuk, An Infrastructure for Developing Pervasive Learning Environments, In Pervasive Computing and Communications, 2008. 6th International Conference on, pp. 389-394. IEEE 2008.
[14] Yuvan Pete, Benjamin Barbry, Thomas Vantroys, Philippe Laporte, Sylvie Lerouge, Design and Evaluation of Pervasive Workplace Learning System for Retail Stores, In Advanced Learning Technologies, 12th International Conference on, pp. 202-204, IEEE 2012.
[15] Habil.sc.ing, Anis Grundspenkis, Fundamentals of Artificial Intelligence.
[16] http://protege.stanford.edu/, Software from online from this web page, downloaded on June 2014.
[17] S. Chakravarthy, V. Krishnaprasad, Z. Tamizuddin, R. H. Badani, ECA Rule Integration into an OODBMS: Architecture and Implementation, In Data Engineering, 11th International Conference on, pp.341-348, IEEE, 1995.