Users regularly experience a crisis of confidence on the Internet. Is that email truly originating from the claimed individual? Is that Facebook invitation indeed from that person or is it a fake page set up by an impersonator? These doubts are usually resolved through a leap of faith, expressing

in partial ful2llment of the requirements for the degree of

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of the Lasso at the individual feature level, with the block-sparsity property of the Group Lasso, where sparse groups of features are jointly encoded, obtaining a sparsity pattern hierarchically structured. This results in the Hierarchical Lasso (HiLasso), which shows important practical advantages. We

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This thesis presents CraneTracker, a multi-modal sensing and communication system for monitoring migratory species at the continental level. By exploiting the robust and extensive cellular infrastructure across the continent, traditional mobile wireless sensor networks can be extended to enable reliable, low-cost monitoring of migratory species. The developed multi-tier architecture yields ecologists with unconventional behavior in-formation not furnished by alternative tracking systems at such a large scale and for a low-cost. The simulation, development and implementation of the CraneTracker soft-ware system is presented. The system is shown effective through multiple proxy deploy-

-tuned tasks for the circuit level. Sampling theory, the gate to the digital world, is the key enabling this revolution, encompassing all aspects related to the conversion of continuous-time signals to discrete streams of numbers. The famous Shannon-Nyquist theorem has become a landmark: a mathematical

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applications, developing software for these types of networks is extremely dffcult, preventing their wide-spread use. Three primary challenges are (1) the high level of dynamics within the network in terms of changing wireless links and node hardware con gurations, (2) the wide variety of hardware present

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