Constrained hyperbolic divergence cleaning in smoothed particle magnetohydrodynamics with variable cleaning speeds

We present an updated constrained hyperbolic/parabolic divergence cleaning algorithm for smoothed particle magnetohydrodynamics (SPMHD) that remains conservative with wave cleaning speeds which vary in space and time. This is accomplished by evolving the quantity $\psi / c_h$ instead of $\psi$. Doing so allows each particle to carry an individual wave cleaning speed, $c_h$, that can evolve in time without needing an explicit prescription for how it should evolve, preventing circumstances which we demonstrate could lead to runaway energy growth related to variable wave cleaning speeds. This modification requires only a minor adjustment to the cleaning equations and is trivial to adopt in existing codes. Finally, we demonstrate that our constrained hyperbolic/parabolic divergence cleaning algorithm, run for a large number of iterations, can reduce the divergence of the field to an arbitrarily small value, achieving $\nabla \cdot B=0$ to machine precision.Comment: 23 pages, 16 figures, accepted for publication in Journal of Computational Physic

Data production methods for harmonized patent statistics : patentee name harmonization.

Patent documents are one of the most comprehensive data sources on technology development. As such, they provide a unique source of information to analyze and monitor technological performance. Patent indicators are now used by companies and by policy and government agencies alike to assess technological progress on the level of regions, countries, domains, and even specific entities such as companies, universities and individual inventors. In this paper, we develop a comprehensive method to achieve harmonization of patentee names in an automated way so that analysis at the level of patentees can be facilitated. The method has been applied to an extensive set of all patentee names found for all EPO patent applications published between 1978 and 2004 and all granted USPTO patents published between 1991 and 2003. As completeness (the extent to which the name-harmonization procedure is able to capture all name variants of the same patentee ) and accuracy (the extent to which the name-harmonization procedure correctly allocates name variants to a single, harmonized patentee name ) do not go hand in hand, priority has been given to accuracy. Before discussing in detail the methodology and its effects as applied to the EPO and USPTO patentee name list, we will first clarify the difference between patentee name harmonization and legal entity identification. In addition, we will briefly expand on the methods and approaches previously developed to address the issue of patentee name harmonization, in order to shed light on our specific contribution. Finally, future refinements and extensions are discussed.Agency; Applications; EPO; USPTO; Name harmonization; Information;

Frame Combination Techniques for Ultra High-Contrast Imaging

We summarize here an experimental frame combination pipeline we developed for ultra high-contrast imaging with systems like the upcoming VLT SPHERE instrument. The pipeline combines strategies from the Drizzle technique, the Spitzer IRACproc package, and homegrown codes, to combine image sets that may include a rotating field of view and arbitrary shifts between frames. The pipeline is meant to be robust at dealing with data that may contain non-ideal effects like sub-pixel pointing errors, missing data points, non-symmetrical noise sources, arbitrary geometric distortions, and rapidly changing point spread functions. We summarize in this document individual steps and strategies, as well as results from preliminary tests and simulations.Comment: 9 pages, 4 figures, SPIE conference pape

Discrete Multi-modal Hashing with Canonical Views for Robust Mobile Landmark Search

Mobile landmark search (MLS) recently receives increasing attention for its great practical values. However, it still remains unsolved due to two important challenges. One is high bandwidth consumption of query transmission, and the other is the huge visual variations of query images sent from mobile devices. In this paper, we propose a novel hashing scheme, named as canonical view based discrete multi-modal hashing (CV-DMH), to handle these problems via a novel three-stage learning procedure. First, a submodular function is designed to measure visual representativeness and redundancy of a view set. With it, canonical views, which capture key visual appearances of landmark with limited redundancy, are efficiently discovered with an iterative mining strategy. Second, multi-modal sparse coding is applied to transform visual features from multiple modalities into an intermediate representation. It can robustly and adaptively characterize visual contents of varied landmark images with certain canonical views. Finally, compact binary codes are learned on intermediate representation within a tailored discrete binary embedding model which preserves visual relations of images measured with canonical views and removes the involved noises. In this part, we develop a new augmented Lagrangian multiplier (ALM) based optimization method to directly solve the discrete binary codes. We can not only explicitly deal with the discrete constraint, but also consider the bit-uncorrelated constraint and balance constraint together. Experiments on real world landmark datasets demonstrate the superior performance of CV-DMH over several state-of-the-art methods