724 research outputs found
Hierarchical Bin Buffering: Online Local Moments for Dynamic External Memory Arrays
Local moments are used for local regression, to compute statistical measures
such as sums, averages, and standard deviations, and to approximate probability
distributions. We consider the case where the data source is a very large I/O
array of size n and we want to compute the first N local moments, for some
constant N. Without precomputation, this requires O(n) time. We develop a
sequence of algorithms of increasing sophistication that use precomputation and
additional buffer space to speed up queries. The simpler algorithms partition
the I/O array into consecutive ranges called bins, and they are applicable not
only to local-moment queries, but also to algebraic queries (MAX, AVERAGE, SUM,
etc.). With N buffers of size sqrt{n}, time complexity drops to O(sqrt n). A
more sophisticated approach uses hierarchical buffering and has a logarithmic
time complexity (O(b log_b n)), when using N hierarchical buffers of size n/b.
Using Overlapped Bin Buffering, we show that only a single buffer is needed, as
with wavelet-based algorithms, but using much less storage. Applications exist
in multidimensional and statistical databases over massive data sets,
interactive image processing, and visualization
Discrete group transforms on SU(2) X SU(2) and SU(3)
Discrete group transforms on SU(2) X SU(2) and SU(3
Centralizers of maximal regular subgroups in simple Lie groups and relative congruence classes of representations
In the paper we present a new, uniform and comprehensive description of
centralizers of the maximal regular subgroups in compact simple Lie groups of
all types and ranks. The centralizer is either a direct product of finite
cyclic groups, a continuous group of rank 1, or a product, not necessarily
direct, of a continuous group of rank 1 with a finite cyclic group. Explicit
formulas for the action of such centralizers on irreducible representations of
the simple Lie algebras are given.Comment: 27 page
On the Classification of Diagonal Coset Modular Invariants
We relate in a novel way the modular matrices of GKO diagonal cosets without
fixed points to those of WZNW tensor products. Using this we classify all
modular invariant partition functions of
for all positive integer level , and for all and infinitely many (in fact, for
each a positive density of ). Of all these classifications, only that
for had been known. Our lists include many
new invariants.Comment: 24 pp (plain tex
Biomarkers of Methylmercury Exposure Immunotoxicity among Fish Consumers in Amazonian Brazil
Background: Mercury (Hg) is a ubiquitous environmental contaminant with neurodevelopmental and immune system effects. An informative biomarker of Hg-induced immunotoxicity could aid studies on the potential contribution to immune-related health effects
Managing tensions and paradoxes between stakeholders in a complex project context: Case study and model proposal
Stakeholder (SH) management has recently undertaken a turn from the traditional management "of" to managing "for" and "with" SH. Relating to this relational trend, identification and management tensions between SH is an important area of study. Indeed, from how to live with and/or resolve or not those tensions depend on the possibility of building the most beneficial cooperation possible between SH for the continuation of the project, to obtain win-win results, and to promote the shared value and common good. For this purpose, a theoretical model is suggested, based on the approaches of paradoxes and conventionalist economy of worth, supporting the identification of tensions between SH and their justifications, and the clarification it helps to bring as to win-win or shared value outcomes, or the absence of such, in the context of a complex project. The suggested model is then used in an exploratory case study. The goal is to assess its relevance, usefulness, and quality. Two theoretical contributions emerge from the data analyzed: 1) several tensions over various categories (allegiance, dimensional, temporal, learning, performance and spatial) can draw on the same justifications (rationale that opposes industrial and domestic conventions); 2) prioritization of tension categories can make it easier to resolve them. © 2016 Editora Mundos Sociais. All rights reserved
Interacting Preformed Cooper Pairs in Resonant Fermi Gases
We consider the normal phase of a strongly interacting Fermi gas, which can
have either an equal or an unequal number of atoms in its two accessible spin
states. Due to the unitarity-limited attractive interaction between particles
with different spin, noncondensed Cooper pairs are formed. The starting point
in treating preformed pairs is the Nozi\`{e}res-Schmitt-Rink (NSR) theory,
which approximates the pairs as being noninteracting. Here, we consider the
effects of the interactions between the Cooper pairs in a Wilsonian
renormalization-group scheme. Starting from the exact bosonic action for the
pairs, we calculate the Cooper-pair self-energy by combining the NSR formalism
with the Wilsonian approach. We compare our findings with the recent
experiments by Harikoshi {\it et al.} [Science {\bf 327}, 442 (2010)] and
Nascimb\`{e}ne {\it et al.} [Nature {\bf 463}, 1057 (2010)], and find very good
agreement. We also make predictions for the population-imbalanced case, that
can be tested in experiments.Comment: 10 pages, 6 figures, accepted version for PRA, discussion of the
imbalanced Fermi gas added, new figure and references adde
A Heuristic Based on the Intrinsic Dimensionality for Reducing the Number of Cyclic DTW Comparisons in Shape Classification and Retrieval Using AESA
Cyclic Dynamic Time Warping (CDTW) is a good dissimilarity of shape descriptors of high dimensionality based on contours, but it is computationally expensive. For this reason, to perform recognition tasks, a method to reduce the number of comparisons and avoid an exhaustive search is convenient. The Approximate and Eliminate Search Algorithm (AESA) is a relevant indexing method because of its drastic reduction of comparisons, however, this algorithm requires a metric distance and that is not the case of CDTW. In this paper, we introduce a heuristic based on the intrinsic dimensionality that allows to use CDTW and AESA together in classification and retrieval tasks over these shape descriptors. Experimental results show that, for descriptors of high dimensionality, our proposal is optimal in practice and significantly outperforms an exhaustive search, which is the only alternative for them and CDTW in these tasks
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