We present a novel approach to parameterize a mesh with disk topology to the plane in a shapeWe present also a more general "hybrid" parameterization model which provides a continuous spectrum of possibilities, controlled by a single parameter. The two cases described above lie at the two ends of the spectrum. We generalize our local/global algorithm to compute these parameterizations. The local phase may also be accelerated by parallelizing the independent computations per triangle.

Abstract-We present a novel approach to localization of sensors in a network given a subset of noisy inter-sensor distances. The algorithm is based on "stitching" together local structures by solving an optimization problem requiring the structures to fit together in an "As-Rigid-As-Possible" manner, hence the name ARAP. The local structures consist of reference "patches" and reference triangles, both obtained from inter-sensor distances. We elaborate on the relationship between the ARAP algorithm and other state-of-the-art algorithms, and provide experimental results demonstrating that ARAP is significantly less sensitive to sparse connectivity and measurement noise. We also show how ARAP may be distributed.

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As a low-dimensional optical fiber with diameter close to or below the wavelength of light, optical micro/nanofiber (MNF) offers a number of favorable properties for optical sensing, which have been exploited in a variety of sensing applications, including physical, chemical, and biological sensors. In this paper we review the principles and applications of silica, glass, and polymer optical micro/nanofibers for physical and chemical sensing.

In-network data aggregation in wireless sensor networks (WSNs) is a technique aimed at reducing the communication overhead-sensed data are combined into partial results at intermediate nodes during message routing. However, in the above technique, some sensor nodes need to send their individual sensed values to an aggregator node, empowered with the capability to decrypt the received data to perform a partial aggregation. This scenario raises privacy concerns in applications like personal health care and the military surveillance. A few other solutions exist where the data are not disclosed to the aggregator (e.g., using privacy homomorphism (PH)), but these solutions are not robust to node or communication failure. The contributions of this paper are two-fold: first, we design a private data aggregation protocol that does not leak individual sensed values during the data aggregation process. In particular, neither the base station (BS) nor the other nodes are able to compromise the privacy of an individual node's sensed value. Second, the proposed protocol is robust to data-loss; if there is a node-failure or communication failure, the protocol is still able to compute the aggregate and to report to the base station the number of nodes that participated in the aggregation. To the best of our knowledge, our scheme is the first one that efficiently addresses the above issues all at once. Copyright © 2009 John Wiley & Sons, Ltd