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We propose a signal-channel, adaptive threshold selection technique for binary mask construction, namely APHONIC, (AdaPtive tHreshOlding for NoIse Cancellation) for smart mobile environments. Using this mask, we introduce two noise cancellation techniques that perform robustly in the presence of real-world interfering signals that are typically encountered by mobile users: a violin busker, a subway...
We study the design of energy-efficient stochastic leader-selection algorithms in environments which are sensed by mobile handsets. This work optimizes the energy usage of the interaction between mobile handsets and an application server. The energy- efficiency of mobile handset communications is of increasing importance given the convergence of mobile computing and cloud computing. In some scenarios...
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