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This e-book constitutes the refereed court cases of the 1st foreign convention on built-in Computing expertise, INTECH 2011, held in Sao Carlos, Brazil, in may well/ June 2011. The 14 revised complete papers awarded have been rigorously reviewed and chosen from 103 submissions. The convention fosters discussions in integrating versions, framework, designs, content,networks and the information via extra powerful and top of the range research.
Read or Download Integrated Computing Technology: First International Conference, INTECH 2011, Sao Carlos, Brazil, May 31 – June 2, 2011. Proceedings PDF
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Additional resources for Integrated Computing Technology: First International Conference, INTECH 2011, Sao Carlos, Brazil, May 31 – June 2, 2011. Proceedings
2 Task Modeling In the context of adaptive hypermedia systems, user tasks are sometimes considered for developing personalized recommendations inside e-commerce Web sites, where the path to commending a product is considered a desired task.  adopts the proposed task-oriented user modeling approach in the context of Web pages recommendations development. The relations between the common navigational “tasks” and Web pages or users are characterized through the Probability Latent Semantic Analysis (PLSA) model.
TannUs, for potts mrf model parameter estimation on higher order neighborhood systems. IEEE Geoscience and Remote Sensing Letters 5(3), 522–526 (2008) 11. : A novel map-mrf approach for multispectral image contextual classiﬁcation using combination of suboptimal iterative algorithms. Pattern Recognition Letters 31(13), 1795–1808 (2010) 12. : Sar image segmentation based on mixture context and wavelet hidden-class-label markov random ﬁeld. Computers & Mathematics with Applications 57(6), 961–969 (2009) 13.
The higher the Kappa (at a maximum value of MAP-MRF 35 one), the better the results. To analyse the obtained results, we used the T statistic to test the diﬀerence between mean performances on second (k1 ) and third order systems (k2 ). This statistc is distribuited according a tn−1 law, where n is ¯ ¯ is the diﬀerence the number of samples, and is deﬁned as T = σd /k√n , where k between the group means (k¯ = k1 − k2 ) and σd is the standard deviation of the punctual diﬀerences. The higher the diﬀerence between the means (numerator), the higher the chance of having two distinct groups.