Jaewoong Lee

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In this paper we propose a two-phase methodology for designing datasets that can be used to test and evaluate activity recognition algorithms. The trade offs between time, cost and recognition performance is one challenge. The effectiveness of a dataset, which contrasts the incremental performance gain with the increase in time, efforts, and number and cost(More)
Experimental investigations were conducted to determine the influence of polydimethylsiloxane (PDMS) microfluidic channels containing aligned circular obstacles (with diameters of 172 µm and 132 µm) on the flow velocity and pressure drop under steady-state flow conditions. A significant PDMS bulging was observed when the fluid flow initially contacted the(More)
Emerging smart space applications are increasingly relying on capabilities for recognizing human activities. Activity recognition research is however challenged and slowed by the lack of data necessary for testing and validation. Collecting data through live-in trials in real world deployments is often very expensive and complicated. Legitimate limitations(More)