Seismic characterization and dynamic site response of a municipal solid waste landfill in Bangalore, India

Seismic design of landfills requires an understanding of the dynamic properties of municipal solid waste (MSW) and the dynamic site response of landfill waste during seismic events. The dynamic response of the Mavallipura landfill situated in Bangalore, India, is investigated using field measurements, laboratory studies and recorded ground motions from the intraplate region. The dynamic shear modulus values for the MSW were established on the basis of field measurements of shear wave velocities. Cyclic triaxial testing was performed on reconstituted MSW samples and the shear modulus reduction and damping characteristics of MSW were studied. Ten ground motions were selected based on regional seismicity and site response parameters have been obtained considering one-dimensional non-linear analysis in the DEEPSOIL program. The surface spectral response varied from 0.6 to 2g and persisted only for a period of 1s for most of the ground motions. The maximum peak ground acceleration (PGA) obtained was 0.5g and the minimum and maximum amplifications are 1.35 and 4.05. Amplification of the base acceleration was observed at the top surface of the landfill underlined by a composite soil layer and bedrock for all ground motions. Dynamic seismic properties with amplification and site response parameters for MSW landfill in Bangalore, India, are presented in this paper. This study shows that MSW has less shear stiffness and more amplification due to loose filling and damping, which need to be accounted for seismic design of MSW landfills in India.

PIB: Profiling Influential Blogger in Online Social Networks, A Knowledge Driven Data Mining Approach

Online Social Networks (OSNs) facilitate to create and spread information easily and rapidly, influencing others to participate and propagandize. This work proposes a novel method of profiling Influential Blogger (IB) based on the activities performed on one's blog documents who influences various other bloggers in Social Blog Network (SBN). After constructing a social blogging site, a SBN is analyzed with appropriate parameters to get the Influential Blog Power (IBP) of each blogger in the network and demonstrate that profiling IB is adequate and accurate. The proposed Profiling Influential Blogger (PIB) Algorithm survival rate of IB is high and stable. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).