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Free, publicly-accessible full text available December 1, 2020
MRAM-based Stochastic Oscillators for Adaptive Non-Uniform Sampling of Sparse Signals in IoT ApplicationsRecent advances to hardware integration and realization of highly-efficient Compressive Sensing (CS) approaches have inspired novel circuit and architectural-level approaches. These embrace the challenge to design more optimal nonuniform CS solutions that consider device-level constraints for IoT applications wherein lifetime energy, device area, and manufacturing costs are highly-constrained, but meanwhile the sensing environment is rapidly changing. In this manuscript, we develop a novel adaptive hardware-based approach for non-uniform compressive sampling of sparse and time-varying signals. The proposed Adaptive Sampling of Sparse IoT signals via STochastic-oscillators (ASSIST) approach intelligently generates the CS measurement matrix by distributing the sensing energy among coefficientsmore »
Methods and Outcomes of the NSF Project on Synthesizing Environments for Digitally-Mediated Team LearningThis poster paper describes the authors’ single-year National Science Foundation (NSF) project DRL-1825007 titled, “DCL: Synthesis and Design Workshop on Digitally-Mediated Team Learning” which has been conducted as one of nine awards within NSF-18-017: Principles for the Design of Digital STEM Learning Environments. Beginning in September 2018, the project conducted the activities herein to deliver a three-day workshop on Digitally-Mediated Team Learning (DMTL) to convene, invigorate, and task interdisciplinary science and engineering researchers, developers, and educators to coalesce the leading strategies for digital team learning. The deliverable of the workshop is a White Paper composed to identify one-year, three-year, andmore »