2026-09-19T12:43:35Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/49761 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Abdelzaher, Tarek F. Gu, Siyu 2014-05-30T17:08:18Z 2014-05-30T17:08:18Z 2016-09-22T20:59:31Z 2014-05 2014-05-30T17:08:18Z 2014-05 "This thesis complements the large body of social sensing literature by developing means for augmenting sensing data with inference results that ""fill-in"" missing pieces. Unlike trend-extrapolation methods, we focus on prediction in disaster scenarios where disruptive trend changes occur. A set of prediction heuristics (and a standard trend extrapolation algorithm) are compared that use either predominantly-spatial or predominantly-temporal correlations for data extrapolation purposes. The evaluation shows that none of them do well consistently. This is because monitored system state, in the aftermath of disasters, alternates between periods of relative calm and periods of disruptive change (e.g., aftershocks). A good prediction algorithm, therefore, needs to intelligently combine time-based data extrapolation during periods of calm, and spatial data extrapolation during periods of change. The thesis develops such an algorithm. The algorithm is tested using data collected during the New York City crisis in the aftermath of Hurricane Sandy in November 2012. Results show that consistently good predictions are achieved. The work is unique in addressing the bi-modal nature of damage propagation in complex systems subjected to stress, and offers a simple solution to the problem." Item withdrawn by Mark Zulauf (zulauf@illinois.edu) on 2014-04-30T17:55:25Z Item was in collections: University of Illinois Theses & Dissertations (ID: 1) No. of bitstreams: 1 Gu_Siyu.pdf: 1443990 bytes, checksum: b2a058b4ea1a13d798c607e1ed9269cc (MD5) Made available in DSpace on 2014-05-30T17:08:18Z (GMT). No. of bitstreams: 2 Siyu_Gu.pdf: 1443990 bytes, checksum: b2a058b4ea1a13d798c607e1ed9269cc (MD5) license.txt: 4056 bytes, checksum: e64a975cc75cf392e2a86dd0b1dc76ae (MD5) Restriction data tranferred 2014-07-01T11:39:32-05:00 Original Data Group with Access UIUC Users [automated] Release Date: 2016-05-30 12:09:03 UTC Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Seth Robbins (robbins.sd@gmail.com) on 2014-05-30T17:10:02Z Item is restricted until 2016-05-30T17:09:03Z U of I Only Restriction Lifted for Item 49812 on 2016-09-22T20:59:31Z. http://hdl.handle.net/2142/49761 en Copyright 2014 Siyu Gu Social Sensing Disaster Response Data Extrapolation Data extrapolation in social sensing for disaster response text Computer Science 1434 Computer Science 0112 University of Illinois at Urbana-Champaign Thesis M.S. MS:Computer Science -UIUC 10KS0112MS