id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
pn89d507483	Su Su	Decentralized Damage Detection in Civil Infrastructure Using Multi-Scale Wireless Sensor Networks	2011		.txt	text/plain	444	8	-4	These contributions include (1) a Bivariate Regressive Adaptive INdex (BRAIN) for damage detection that proves to be more robust and accurate than previous formats, (2) a Restricted Input Network Activation Scheme (RINAS) with a new image-based vehicle classification algorithm that not only reduces the size of reference databases and enhances detection reliability, but also relieves computational burdens and extends network lifetime and (3) an offline damage localization technique employing Dempster-Shafer Evidence Theory that is capable of effectively isolating damage positions even for minor loss levels. Thus the primary research tasks in this dissertation can be summarized as: Develop a wireless sensor network philosophy that provides reliable data for detection and localization of damage in complex Civil Infrastructure, while maximizing the performance and lifetime of the hardware Develop an assessment framework suitable for damage detection and localization using data measured from a distributed wireless sensors and suitable for operation within said network, i.e., recognizing the computational resources, communications constraints, and power available to the network Analytically and experimentally verify, at various scales and levels of complexity, the proposed network philosophy and assessment framework.	cache/pn89d507483.txt	txt/pn89d507483.txt