139,184 research outputs found
Cygnus A super-resolved via convex optimisation from VLA data
We leverage the Sparsity Averaging Reweighted Analysis (SARA) approach for
interferometric imaging, that is based on convex optimisation, for the
super-resolution of Cyg A from observations at the frequencies 8.422GHz and
6.678GHz with the Karl G. Jansky Very Large Array (VLA). The associated average
sparsity and positivity priors enable image reconstruction beyond instrumental
resolution. An adaptive Preconditioned Primal-Dual algorithmic structure is
developed for imaging in the presence of unknown noise levels and calibration
errors. We demonstrate the superior performance of the algorithm with respect
to the conventional CLEAN-based methods, reflected in super-resolved images
with high fidelity. The high resolution features of the recovered images are
validated by referring to maps of Cyg A at higher frequencies, more precisely
17.324GHz and 14.252GHz. We also confirm the recent discovery of a radio
transient in Cyg A, revealed in the recovered images of the investigated data
sets. Our matlab code is available online on GitHub.Comment: 14 pages, 7 figures (3/7 animated figures), accepted for publication
in MNRA
Adaptively Secure Computationally Efficient Searchable Symmetric Encryption
Searchable encryption is a technique that allows a client to store documents on a server in encrypted form. Stored documents can be retrieved selectively while revealing as little information as\ud
possible to the server. In the symmetric searchable encryption domain, the storage and the retrieval are performed by the same client. Most conventional searchable encryption schemes suffer\ud
from two disadvantages.\ud
First, searching the stored documents takes time linear in the size of the database, and/or uses heavy arithmetic operations.\ud
Secondly, the existing schemes do not consider adaptive attackers;\ud
a search-query will reveal information even about documents stored\ud
in the future. If they do consider this, it is at a significant\ud
cost to updates.\ud
In this paper we propose a novel symmetric searchable encryption\ud
scheme that offers searching at constant time in the number of\ud
unique keywords stored on the server. We present two variants of\ud
the basic scheme which differ in the efficiency of search and\ud
update. We show how each scheme could be used in a personal health\ud
record system
MonetDB/XQuery - Consistent & Efficient Updates on the Pre/Post Plane
Relational XQuery processors aim at leveraging mature relational DBMS query processing technology to provide scalability and efficiency. To achieve this goal, various storage schemes have been proposed to encode the tree structure of XML documents in flat relational tables. Basically, two classes can be identified: (1) encodings using fixed-length surrogates, like the preorder ranks in the pre/post encoding [5] or the equivalent pre/size/level encoding [8], and (2) encodings using variable-length surrogates, like, e.g., ORDPATH [9] or P-PBiTree [12]. Recent research [1] showed a clear advantage of the former for efficient evaluation of XPath location steps, exploiting techniques like cheap node order tests, positional lookup, and node skipping in staircase join [7]. However, once updates are involved, variable-length surrogates are often considered the better choice, mainly as a straightforward implementation of structural XML updates using fixed-length surrogates faces two performance bottlenecks: (i) high physical cost (the preorder ranks of all nodes following the update position must be modifiedāon average 50% of the document), and (ii) low transaction concurrency (updating the size of all ancestor nodes causes lock contention on the document root)
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