Computational Intelligence in Data Mining—Volume 2: by Himansu Sekhar Behera, Durga Prasad Mohapatra

By Himansu Sekhar Behera, Durga Prasad Mohapatra

The ebook is a set of fine quality peer-reviewed learn papers awarded within the moment foreign convention on Computational Intelligence in facts Mining (ICCIDM 2015) held at Bhubaneswar, Odisha, India in the course of five – 6 December 2015. The two-volume complaints tackle the problems and demanding situations for the seamless integration of 2 center disciplines of machine technological know-how, i.e., computational intelligence and knowledge mining. The ebook addresses varied tools and strategies of integration for boosting the final objective of information mining. The publication is helping to disseminate the data approximately a few cutting edge, energetic examine instructions within the box of knowledge mining, laptop and computational intelligence, in addition to a few present concerns and functions of comparable topics.

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Tech. (IJCSET) 14. : Brain enabled mechanized speech synthesizer using brain mobile interface. Int. J. Eng. Tech. (IJET) 12 S. V. Divya 15. : Real-time EEG Analysis with Subject-Specific Spatial Patterns for a Brain-Computer Interface 16. : A self training semi-supervised SVM algorithm and its application in an EEG based brain computer interface speller system. Sci. Direct Pattern Recogn. Lett. 29 (2008) 17. : Classifying Human-robot interaction: an updated taxonomy 18. : A robotic wheelchair based on the integration of human and environmental observations.

Eng. Manag. 9 (2), 104–113 (2014) 16. : A two-warehouse inventory model for deteriorating items under conditionally permissible delay in payment. Appl. Math. Model. 35, 2221–2231 (2011) Effect of Outlier Detection on Clustering Accuracy and Computation Time of CHB K-Means Algorithm K. Aparna and Mydhili K. Nair Abstract Data clustering is one of the major areas of research in data mining. Of late, high dimensionality dataset is becoming popular because of the generation of huge volumes of data.

The main layers in this protocol are Application layer (APL), Application framework, Application objects, ZigBee Device Object (ZDO), Application Support Sub layer (APS), Service Security Provider (SSP), Network layer, Medium Access Control layer (MAC), Physical layer. The key features of this protocol are (1) high performance, (2) low cost, (3) advanced networking and security, (4) low power, (5) easy to use. ZigBee is always used as a pair. One is used for receiving the commands from the computer and the other is used to transmit these input commands to the robotic module.

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