By Sundarapandian Vaidyanathan (auth.), David C. Wyld, Michal Wozniak, Nabendu Chaki, Natarajan Meghanathan, Dhinaharan Nagamalai (eds.)

ISBN-10: 3642225543

ISBN-13: 9783642225543

ISBN-10: 3642225551

ISBN-13: 9783642225550

This e-book constitutes the complaints of the 1st overseas convention on Advances in Computing and knowledge expertise, ACITY 2011, held in Chennai, India, in July 2011. The fifty five revised complete papers provided have been rigorously reviewed and chosen from various submissions. The papers function major contributions to all significant fields of the pc technological know-how and data know-how in theoretical and sensible aspects.

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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

Sample text

Approach is dependent on SPs • • • • SPs are not required. • Combining Backpropagati on network with SVM gives better results for classification. • • Training consumes a lot of time. Requires target values. 38 D. Parekh and Rekha Vig Table 3. No Approach Characteristic Advantages 1. 2. 3. B. Kim, J. Bae, I. Yoo, 2000 • Y. Liu, S. Yuan, X. Zhu, Y. Wang, W. Zhang and Y. Wang, 2002 • • • • 4. 5. Tico, 2002 C. Klimanee and D. Nguyen • • • • • 6. Rakesh,20 06 • • • Disadvantages Poincare Index is used to detect core.

Use of Formal techniques in Requirement Engineering would be of immense importance as it would provide automated support in deriving use case models from the functional requirements. In this paper we propose a formal syntax for requirements called Adv-EARS. We define a grammar for this syntax such that a requirements document in this format can be grammatically parsed and the prospective actors and use cases are automatically derived from the parse tree. The use case diagram is then automatically generated based on the actors and use cases and their relationships.

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 ([4]-[8]). This approach has practical and technical benefits for the reduced-order controller design for large scale linear systems with high dimension and complexity. The motivation for the observer-based reduced order controllers stems from the fact that the dominant state of the linear plant may not be available for measurement and hence for implementing the pole placement law, only the reduced order exponential observer can be used in lieu of the dominant state of the given discrete-time linear system.

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Advances in Computing and Information Technology: First International Conference, ACITY 2011, Chennai, India, July 15-17, 2011. Proceedings by Sundarapandian Vaidyanathan (auth.), David C. Wyld, Michal Wozniak, Nabendu Chaki, Natarajan Meghanathan, Dhinaharan Nagamalai (eds.)


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