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158 175 [108] Teller A and Stivoric J: The BodyMedia platform: continuous body intelligence Proceedings of the 1st ACM Workshop on Continuous Archival and Retrieval of Personal Experiences (CARPE 2004, New York, New York, October 2004), ACM Press, 2004, pp 114 115 [109] Toyama N, Ota T, Kato F, Toyota Y, Hattori T and Hagino T: Exploiting Multiple Radii to Learn Signi cant Locations Proceedings of the International Workshop on Location- and Context-Awareness (LoCA 2005, Oberpfaffenhofen, Germany, May 2005), Lecture Notes in Computer Science 3479, Springer-Verlag, 2005, pp 157 168 [110] vCard: The Electronic Business Card, Version 21 Speci cation, September 18, 1996 Online: wwwimcorg/ pdi/vcard-21txt [111] Wang X, Zhang DQ, Gu T and Pung HK: Ontology-based Context Modeling and Reasoning using OWL .

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Proceedings of the PerCom Workshop on Context Modeling and Reasoning (CoMoRea 2004, Orlando, Florida, March 2004), pp 18 22 [112] Weith ner T, Liebig T, Luther M and B hm S: What s Wrong with OWL Benchmarks Proceedings of o o the 2nd International Workshop on Scalable Semantic Web Knowledge Base Systems (SSWS 2006, Athens, Georgia, November 2006) [113] Yamabe T, Takagi A and Nakajima T: Citron: a context information acquisition framework for personal devices Proceedings of the 11th IEEE International Conference on Embedded and Real-time Computing Systems and Applications (RTCSA 05, Hong Kong, August 2005), IEEE Computer Society, 2005, pp 489 495 [114] Yau SS and Karim F: An Adaptive Middleware for Context-sensitive Communications for Real-time Applications in Ubiquitous Computing Environments Real-Time Systems, Vol 26, No 1, 2004, pp 29 61 [115] Zhou C, Frankowski D, Ludford P.

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, Shekhar S and Terveen L: Discovering Personal Gazetteers: an interactive clustering approach Proceedings of the 12th Annual ACM International Workshop on Geographic Information Systems (GIS 04, Washington DC, November 2004), ACM Press, 2004, pp 266 273 [116] Zukerman I and Albrecht DW: Predictive Statistical Models for User Modeling User Modeling and UserAdapted Interaction, Vol 11, No 1/2, 2001, pp 5 18..

Polynomials (X ) and W (X ) allow us to calculate the positions of the errors and to determine their values by using expression (27). Additionally, the syndrome polynomial of degree deg{S(X )} 2t 1 is de ned as

(10) X (m x m) p.onsingular, a, b (m x 1) :

After installing a preselected and pretrained of ine inferential sensor in a real dynamic environment, it can be used in different modes of operation, dependent on the level of process changes. The rst alternative is when the inferential sensor predicts reliably with

Locate the router s encryption settings, which are usually in the Wireless Security (or similarly named) section (see Figure 6-5).

beacon time to start their transmissions. It is also important to realize that all synchronizations through the beacon come from the PNC. 8.3.9 Others