By Sundarapandian Vaidyanathan (auth.), David C. Wyld, Michal Wozniak, Nabendu Chaki, Natarajan Meghanathan, Dhinaharan Nagamalai (eds.)
This e-book constitutes the court cases of the 1st foreign convention on Advances in Computing and knowledge expertise, ACITY 2011, held in Chennai, India, in July 2011. The fifty five revised complete papers offered have been rigorously reviewed and chosen from a number of submissions. The papers characteristic major contributions to all significant fields of the pc technology and data know-how in theoretical and functional aspects.
Read or Download Advances in Computing and Information Technology: First International Conference, ACITY 2011, Chennai, India, July 15-17, 2011. Proceedings PDF
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Additional info for Advances in Computing and Information Technology: First International Conference, ACITY 2011, Chennai, India, July 15-17, 2011. Proceedings
Homogeneity coefficient is computed for every tile till maximum level has reached. Homogeneity vector constructed is given as input to MultiLayer perceptron for classification. Clustering is performed to divide the database into respective classes. K-means algorithm is used to resolve intra class variability. Continuous classification is performed after clustering to improve the performance of classification. Orientation map is generated using least mean square method. It is further improved by an estimation approach presented in the paper.
The Direction Field can be derived from the gradients by performing averaging operation on the gradients, involving pixels in some neighborhood . Wei and Chen  have suggested an improvement in the computation of direction field which gives more accurate information about the ridges and the valleys as shown in figure 2. Fig. 2. Smoothed Orientation Field 30 D. Parekh and Rekha Vig Cappelli et al.  have presented a new approach for fingerprint classification which uses masks for partitioning orientation image.
Thus, there is a great demand for the control of large scale linear control systems with the use of reduced-order controllers rather than the full-order controllers (-). A recent approach for obtaining reduced-order controllers is via obtaining the reduced-order model of a linear plant preserving the dynamic as well as static properties of the system and then working out controllers for the reduced-order model thus obtained (-). This approach has practical and technical benefits for the reduced-order controller design for large scale linear systems with high dimension and complexity.