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This book presents an overview over smart structures - its concepts, its active involvement in the vibration control, their applications and the extensive research work done.

Carbon capture and storage (CCS) refers to a set of technologies and methods for the mitigation, remediation, and storage of industrial CO2 emissions, the most imminent and virile of the greenhouse gases (GHG). The book addresses the methods and technologies currently being applied, developed, and most in need of further research.

The book:

Discusses methods of carbon capture in industrial settings

Presents biological and geological approaches to carbon sequestration

Introduces ionic liquids as a method of carbon capture

Introduces new approaches to capturing CO2 from...

This book offers a broad overview of techniques used in the design of Wavelength Division Multiplexing (WDM) networks for efficient dissemination of information in computer networks. It starts with an overview of the hardware components then provides a thorough review of WDM. Each topic is covered rigorously with emphasis on detailed explanations of the approaches used. Numerous exercises are included.

This book explains the concept of education divide in rural India and identifies various factors that shape and sustain such a divide. In doing so, it also discusses a range of attempts undertaken to bridge the education divide. Subsequently, the book has attempted in providing a socio-technical framework towards optimally deploying social technologies for addressing the issue of education divide of marginalized communities. The proposed framework offers a transition from traditional content-centric, teacher-centric and centralized education ecosystem to a connection-centric,...

This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. It examines how a search technique, the genetic algorithm, can be used for pattern classification mainly through approximating decision boundaries. Coverage also demonstrates the effectiveness of the genetic classifiers vis-a-vis several widely used classifiers, including neural networks.