• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.9
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• pp.815-820
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• 2016

An elastic polymer (e.g., PDMS) blended with EFG particles is a promising conductive composite for fabricating soft sensors that can detect an object's deformation up to or more than 50%. Here, we develop large-strain, sprayable soft sensors using a mixture of PDMS and EFG particles, which are used as a host elastomer and electrically conductive particles, respectively. A solution for a conductive composite mixture is prepared by the microwave-assisted graphite exfoliation, followed by ultrasonication-induced fragmentation of the exfoliated graphite and ultrasonic blending of PDMS and EFG. Using the prepared solutions for composite and pure PDMS, 1-, 2-, and 3-axis soft sensors are fabricated by airbrush stencil technique where composite mixture and pure PDMS are materials for sensing and insulating layers, respectively. We characterize the soft strain sensors after investigating the effect of PDMS/EFG wt% on mechanical compliance and electrical conductance of the conductive composite.

• Korean Journal of Remote Sensing
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• v.24 no.4
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• pp.309-324
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• 2008

In this study the retrieval algorithms have been developed to retrieve total precipitable water (TPW) from Terra/Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) infrared measurements using a physical iterative retrieval method and a split-window technique over East Asia. Retrieved results from these algorithms were validated against Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) over ocean and radiosonde observation over land and were analyzed for investigating the key factors affecting the accuracy of results and physical processes of retrieval methods. Atmospheric profiles from Regional Data Assimilation and Prediction System (RDAPS), which produces analysis and prediction field of atmospheric variables over East Asia, were used as first-guess profiles for the physical retrieval algorithm. We used RTTOV-7 radiative transfer model to calculate the upwelling radiance at the top of the atmosphere. For the split-window technique, regression coefficients were obtained by relating the calculated brightness temperature to the paired radiosonde-estimated TPW. Physically retrieved TPWs were validated against SSM/I and radiosonde observations for 14 cases in August and December 2004 and results showed that the physical method improves the accuracy of TPW with smaller bias in comparison to TPWs of RDAPS data, MODIS products, and TPWs from split-window technique. Although physical iterative retrieval can reduce the bias of first-guess profiles and bring in more accurate TPWs, the retrieved results show the dependency upon initial guess fields. It is thought that the dependency is due to the fact that the water vapor absorption channels used in this study may not reflect moisture features in particular near surface.