STABILITY OF SIMPLY SUPPORTED SMART PIEZOLAMINATED COMPOSITE PLATES USING FINITE ELEMENT METHOD
Published In: INTERNATIONAL CONFERENCE ON ADVANCES IN AERONAUTICAL AND MECHANICAL ENGINEERING
Author(s): KAMAL M. BAJORIA , RAJAN L. WANKHADE
Abstract: Piezolaminated smart structures are mostly used as light weight structures to control structural response in various structural applications. Piezoelectric materials possesses a property of direct and converse piezoelectric effects which can be adequately employed to control the deflection, vibration, shape and buckling of the structure. Due to the application of piezoelectric materials to control structural response, stability and control of light weight structures tends to be the governing criterion which requires significant attention. A finite element methodology is developed for stability analysis of smart piezolaminated composite plates subjected to combined action of electrical and mechanical loading. The finite element formulation is based on higher order shear deformation theory. Numerical analysis is made for stability analysis of simply supported piezolaminated plate
- Publication Date: 11-Aug-2012
- DOI: 10.15224/978-981-07-2683-6-104
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PREDICTION OF YAHOO! MUSIC SEQUENCES ON USER’S MUSICAL TASTE
Published In: INTERNATIONAL CONFERENCE ON ADVANCES IN INFORMATION TECHNOLOGY
Author(s): AKSHAY SHARMA , ALPA RESHAMWALA , DIVYA VINEET , NISHA SHARMA , PARSHWA SHAH , SUNITA MAHAJAN
Abstract: Sequential pattern mining is an important data mining problem with broad applications. In this paper, we have implemented Apriori a candidate generation algorithm and SPAM (Sequential Pattern Mining) algorithm on Yahoo! Music KDD Cup 2011, which is the annual Data Mining and Knowledge Discovery competition organized by ACM Special Interest Group on Knowledge Discovery and Data Mining, the leading professional organization of data miners.Yahoo! Music has amassed billions of user ratings for musical pieces. When properly analyzed, the raw ratings encode information on how the popularity of songs, albums and artists vary over time and above all, which songs users would like to listen to. Such an analysis introduces new scientific challenges. From these discovered patterns, we can know what patterns or music sequences which are frequently heard and in what order they are recommended. Experimental results have shown that SPAM performs well for large datasets like Yahoo! Music datasetis due
- Publication Date: 23-Jun-2012
- DOI: 10.15224/978-981-07-2683-6-102
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- Downloads: 0