Simulating dynamic covariance structures for testing the adaptive behavior of variable selection algorithms (Invited Paper)

Variable selection for regression is a classical statistical problem, motivated by concerns that too large a number of covariates may bring about overfitting and unnecessarily high measurement costs. Novel difficulties arise in streaming contexts, where the correlation structure of the process may be drifting, in which case it must be constantly tracked so that selections may be revised accordingly. A particularly interesting phenomenon is that non-selected covariates become missing variables, inducing bias on subsequent decisions. This raises an intricate exploration-exploitation tradeoff, whose dependence on the covariance tracking algorithm and the choice of variable selection scheme is too complex to be dealt with analytically. We hence capitalise on the strength of simulations to explore this problem, taking the opportunity to tackle the difficult task of simulating dynamic correlation structures. © 2008 IEEE.

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.

Correlation of transport and magnetic critical currents in melt-processed YBa2Cu3O7-δ thick films

Transport critical current measurements have been carried out on melt-processed thick films of YBa2Cu3O7-δ on yttria-stabilized zirconia in fields of up to 8 T both within grains and across grain boundaries. These measurements yield Jc values of ∼3000 A cm-2 at 4.2 K and zero magnetic field and 400 A cm -2 at 77 K and zero magnetic field, taking the entire sample width as the definitive dimension. Optical and scanning electron microscopy reveals that the thick-film grains consist typically of a central "hub" region ∼50 μm in diameter, which is well connected to radial subgrains or "spokes" which extend ∼1 mm to define the complete grain structure. Attempts have been made to correlate the transport measurements of inter- and intra-hub-and-spoke (H-S) critical current with values of this parameter derived previously from magnetization measurements. Analysis of the transport measurements indicates that current flow through H-S grains is constrained to paths along the spokes via the grain hub. Taking the size of the hub as the definitive dimension yields an intra-H-S grain Jc of ∼60 000 A cm-2 at 4.2 K and 0 T, which is in reasonable agreement with the magnetization data. Experiments in which the hub is removed from individual grains confirm that this feature determines critically the J c of the film.

Turbulent flow structure in experimental laboratory wind-generated gravity waves

This paper is the third part of a report on systematic measurements and analyses of wind-generated water waves in a laboratory environment. The results of the measurements of the turbulent flow on the water side are presented here, the details of which include the turbulence structure, the correlation functions, and the length and velocity scales. It shows that the mean turbulent velocity profiles are logarithmic, and the flows are hydraulically rough. The friction velocity in the water boundary layer is an order of magnitude smaller than that in the wind boundary layer. The level of turbulence is enhanced immediately beneath the water surface due to micro-breaking, which reflects that the Reynolds shear stress is of the order u *w 2. The vertical velocities of the turbulence are related to the relevant velocity scale at the still-water level. The autocorrelation function in the vertical direction shows features of typical anisotropic turbulence comprising a large range of wavelengths. The ratio between the microscale and macroscale can be expressed as λ/Λ=a Re Λ n, with the exponent n slightly different from -1/2, which is the value when turbulence production and dissipation are in balance. On the basis of the wavelength and turbulent velocity, the free-surface flows in the present experiments fall into the wavy free-surface flow regime. The integral turbulent scale on the water side alone underestimates the degree of disturbance at the free surface. © 2012 Elsevier B.V.