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How to read pdf files using C# .NET including iText, PDFBox, PDF -Excel, etc. A summary of some ... NET; Winnovative PDF Viewers ASP . NET and Windows ...

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Dan Letecky posted a nice code on how to extract text from PDF documents in C# based on PDFBox. Although his solution works well it has a drawback, the size ...


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48. A. Woo and D. E. Culler. A transmission control scheme for media access in sensor networks. In Proceedings of the 7th Annual ACM/IEEE International Conference on Computing and Networking (MobiCom 2001), Rome, Italy, July 2001. 49. W. Ye, J. Heidemann, and D. Estrin. An energy-ef cient MAC protocol for wireless sensor networks. In Proceedings of the 7th Annual ACM/IEEE International Conference on Computing and Networking INFOCOM 2002, New York, June, 2002. 50. K. Nakano and S. Olariu. Randomized initialization protocols for radio networks. In Handbook of Wireless Networks and Mobile Computing, Stojmenovic (ed.), pages 195 218, John Wiley & Sons, 2002. 51. K. Nakano and S. Olariu. Uniform leader election for radio networks. IEEE Transactions on Parallel and Distributed Systems, 13:516 526, 2002. 52. R. G. Graham, D. E. Knuth, and O. Patashnik. Concrete Mathematics, Addison-Wesley, 1989. 53. D. Gracanin, M. Eltoweissy, S. Olariu, and A. Wadaa. On Modeling Wireless Sensor Networks. Paper presented at 18th International Parallel and Distributed Processing Symposium (IPDPS 04), Workshop 12: Fourth International Workshop on Algorithms for Wireless, Mobile, Ad Hoc and Sensor Networks (WMAN), Santa Fe, NM, April 2004. 54. D. Gracanin, M. Eltoweissy, S. Olariu, and A. Wadaa. Dependability support in wireless sensor networks. In Dependable Systems, H. Diab and A. Y. Zomaya (eds.), John Wiley & Sons, 2005. 55. K. Jones, K. N. Lodding, S. Olariu, A. Wadaa, L. Wilson, and M. Eltoweissy. Biomimetic models for wireless sensor networks. In Handbook of BioInspired Algorithms, S. Olariu and A. Y. Zomaya (eds.), CRC Press, 2005.

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Given that the design methodology allows for both size and topology variations, the RF characterization can be evaluated during the RF design phase An RF ESD design methodology that achieves this objective can be a method that forms ESD networks from these primitive p-cell device elements and converts to a higher order parameterized cell [1 3] From the lowest order device primitive parameterized cells, hierarchical parameterized cells can be constructed to form a library of ESD circuits and networks By utilizing the primitive p-cell structures into higher order networks, an ESD CAD strategy is developed to ful ll the objective as follows: design exibility; dc characterization; ac and RF characterization; RF models; choice of ESD network type Developing an ESD design system of hierarchical system of parameterized cells, higher level ESD networks can be constructed without an additional RF characterization.

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among the variables eliminated It does this by partialing out the other variables from the weights The common that is, predictive variance that two or more variables have in common may not be seen at all in the beta weights Hence, a multiple regression can be signi cant even though none of the weights are signi cant; it is the variance that the variables have in common that predicts the dependent variable The solution is to extract as many factors as there are variables and restrict the solution so that the factors are uncorrelated These are then orthogonalized versions of the original variables When these are used as the predictors in a multiple regression, all of the covariation is distributed among the variables and appears in the weights.

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de ning properties about the set of variable interrelationships: that (a) the differences among variables can be reduced to differences in two dimensions; (b) each of the variables has an equal projection in this plane, as represented by the variable s distance from the origin (of a hypothetical circle); and (c) the variables distribution around the hypothetical circle is uniform, generally translated into the property of equal spacing. These properties are increasingly speci c for a circumplex model (see Gurtman, 1994). Indeed, the third criterion (equal spacing) is often used to differentiate between circumplex and simple-structure models (e.g., Hofstee, De Raad, & Goldberg, 1992). The second way in which the circumplex has been conceptualized in the literature is as a particular kind of correlation matrix. This circulant correlation model was rst presented by Guttman (1954), as noted earlier, and has been further explored and developed by others (e.g., Browne, 1992; Cudeck, 1986; Rounds, Tracey, & Hubert, 1992; Wiggins, Steiger, & Gaelick, 1981.) This model de nes the circumplex as a particular kind of nonrestrictive (i.e., not fully constrained) correlation pattern characterized by a circular, repeating pattern of values in each row and column. Table 16.2 formalizes this model for the eight-variable case;

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