Streaming covariance selection with applications to adaptive querying in sensor networks

Sensor networks can be naturally represented as graphical models, where the edge set encodes the presence of sparsity in the correlation structure between sensors. Such graphical representations can be valuable for information mining purposes as well as for optimizing bandwidth and battery usage with minimal loss of estimation accuracy. We use a computationally efficient technique for estimating sparse graphical models which fits a sparse linear regression locally at each node of the graph via the Lasso estimator. Using a recently suggested online, temporally adaptive implementation of the Lasso, we propose an algorithm for streaming graphical model selection over sensor networks. With battery consumption minimization applications in mind, we use this algorithm as the basis of an adaptive querying scheme. We discuss implementation issues in the context of environmental monitoring using sensor networks, where the objective is short-term forecasting of local wind direction. The algorithm is tested against real UK weather data and conclusions are drawn about certain tradeoffs inherent in decentralized sensor networks data analysis. © 2010 The Author. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved.

The effect of an upstream turbine on a low-aspect ratio vane

The interaction between a high-pressure rotor and a downstream vane is dominated by vortex-blade interaction. Each rotor blade passing period two co-rotating vortex pairs, the tip-leakage and upper passage vortex and the lower passage and trailing shed vortex, impinge on, and are cut by, the vane leading edge. In addition to the streamwise vortex the tip-leakage flow also contains a large velocity deficit. This causes the interaction of the tip-leakage flow with a downstream vane to differ from typical vortex blade interaction. This paper investigates the effect these interaction mechanisms have on a downstream vane. The test geometry considered was a low aspect ratio second stage vane located within a S-shaped diffuser with large radius change mounted downstream of a shroudless high-pressure turbine stage. Experimental measurements were conducted at engine-representative Mach and Reynolds numbers, and data was acquired using a fast-response aerodynamic probe upstream and downstream of the vane. Time-resolved numerical simulations were undertaken with and without a rotor tip gap in order to investigate the relative magnitude of the interaction mechanisms. The presence of the upstream stage is shown to significantly change the structure of the secondary flow in the vane and to cause a small drop in its performance.

Enhanced robotic body extension with modular units

The adaptation of robots to changing tasks has been explored in modular self-reconfigurable robot research, where the robot structure is altered by adapting the connectivity of its constituent modules. As these modules are generally complex and large, an upper bound is imposed on the resolution of the built structures. Inspired by growth of plants or animals, robotic body extension (RBE) based on hot melt adhesives allows a robot to additively fabricate and assemble tools, and integrate them into its own body. This enables the robot to achieve tasks which it could not achieve otherwise. The RBE tools are constructed from hot melt adhesives and therefore generally small and only passive. In this paper, we seek to show physical extension of a robotic system in the order of magnitude of the robot, with actuation of integrated body parts, while maintaining the ability of RBE to construct parts with high resolution. Therefore, we present an enhancement of RBE based on hot melt adhesives with modular units, combining the flexibility of RBE with the advantages of simple modular units. We explain the concept of this new approach and demonstrate with two simple unit types, one fully passive and the other containing a single motor, how the physical range of a robot arm can be extended and additional actuation can be added to the robot body. © 2012 IEEE.