Transactions on Computational Science XXV
The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-qual...
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Main Authors | , , , , |
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Format | eBook |
Language | English |
Published |
Berlin, Heidelberg
Springer Nature
2015
Springer Berlin / Heidelberg Springer Berlin Heidelberg Springer |
Edition | 1 |
Series | Lecture Notes in Computer Science |
Subjects | |
Online Access | Get full text |
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Summary: | The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. It addresses researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings and solutions and enabling industrial users to apply techniques of leading-edge, large-scale, high performance computational methods. This, the 25th issue of the Transactions on Computational Science journal, consists of two parts. Part I, which is guest edited by Khalid Saeed, Nabendu Chaki and Soharab Hossain Shaikh, covers the areas of computer vision, image processing for biometric security, information fusion, and Kinect activity recognition. The papers in Part II focus on optimization through novel methods for data fusion, clustering in WSN, fault-tolerance, probability, weight assignment and risk analysis. |
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ISBN: | 3662470748 9783662470749 9783662470732 366247073X |
ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/978-3-662-47074-9 |