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An agent-based DDM for high level architecture
The Data Distribution Management (DDM) service is one of the six services provided in the Runtime Infrastructure (RTI) of High Level Architecture (HLA). Its purpose is to perform data filtering and reduce irrelevant data communicated between federates. The two DDM schemes proposed for RTI, region based and grid based DDM, are oriented to send as little irrelevant data to subscribers as possible, but only manage to filter part of this information and some irrelevant data is still being communicated. Previously (G. Tan et al., 2000), we employed intelligent agents to perform data filtering in HLA, implemented an agent based DDM in RTI (ARTI) and compared it with the other two filtering mechanisms. The paper reports on additional experiments, results and analysis using two scenarios: the AWACS sensing aircraft simulation and the air traffic control simulation scenario. Experimental results show that compared with other mechanisms, the agent based approach communicates only relevant data and minimizes network communication, and is also comparable in terms of time efficiency. Some guidelines on when the agent based scheme can be used are also give
The Luminosity - E_p Relation within Gamma--Ray Bursts and Implications for Fireball Models
Using a sample of 2408 time-resolved spectra for 91 BATSE gamma-ray bursts
(GRBs) presented by Preece et al., we show that the relation between the
isotropic-equivalent luminosity (L_iso) and the spectral peak energy (E_p) in
the cosmological rest frame, L_iso \propto E_p^2, not only holds within these
bursts, but also holds among these GRBs, assuming that the burst rate as a
function of redshift is proportional to the star formation rate. The possible
implications of this relation for the emission models of GRBs are discussed. We
suggest that both the kinetic-energy-dominated internal shock model and the
magnetic-dissipation-dominated external shock model can well interpret this
relation. We constrain the parameters for these two models, and find that they
are in a good agreement with the parameters from the fittings to the afterglow
data (abridged).Comment: 3 pages plus 5 figures, emulateapj style, accepted for publication in
ApJ Letter
Semantic Object Parsing with Graph LSTM
By taking the semantic object parsing task as an exemplar application
scenario, we propose the Graph Long Short-Term Memory (Graph LSTM) network,
which is the generalization of LSTM from sequential data or multi-dimensional
data to general graph-structured data. Particularly, instead of evenly and
fixedly dividing an image to pixels or patches in existing multi-dimensional
LSTM structures (e.g., Row, Grid and Diagonal LSTMs), we take each
arbitrary-shaped superpixel as a semantically consistent node, and adaptively
construct an undirected graph for each image, where the spatial relations of
the superpixels are naturally used as edges. Constructed on such an adaptive
graph topology, the Graph LSTM is more naturally aligned with the visual
patterns in the image (e.g., object boundaries or appearance similarities) and
provides a more economical information propagation route. Furthermore, for each
optimization step over Graph LSTM, we propose to use a confidence-driven scheme
to update the hidden and memory states of nodes progressively till all nodes
are updated. In addition, for each node, the forgets gates are adaptively
learned to capture different degrees of semantic correlation with neighboring
nodes. Comprehensive evaluations on four diverse semantic object parsing
datasets well demonstrate the significant superiority of our Graph LSTM over
other state-of-the-art solutions.Comment: 18 page
Delivering zero carbon homes in the UK
The conference paper can be viewed at: http://www.arcom.ac.uk/-docs/proceedings/ar2012-1445-1454_Heffernan_Pan_Liang.pdfIn the UK and internationally, a plethora of voluntary and mandatory energy efficiency standards for new buildings exist, with the common aim of mitigating the impact of new buildings on climate change. However, the take-up of voluntary schemes has been limited and, as a result, many governments have seen the need to introduce mandatory schemes through legislation; from 2016 all new build homes in England and Wales will be required to achieve zero carbon in regulated energy consumption. The international context of voluntary and mandatory building energy efficiency standards is examined through a review of the literature. The review is expanded by a series of semi-structured interviews with construction professionals involved in the delivery of low and zero carbon homes in the UK. In order to establish why zero carbon homes are not being developed, themes of drivers and barriers and challenges in relation to the delivery of zero carbon homes are explored. The drivers which emerged are categorized into four groups: legislative; economic; social responsibility and individual; and the barriers and challenges into a further four groups: skills and knowledge; legislative and governmental; economic and industry. Skills shortages and knowledge gaps for all involved in the delivery of zero carbon homes were seen as the primary barriers and a gap in the literature also exists in this area. Gaining a greater understanding of the skills and knowledge required for the delivery of zero carbon homes is therefore confirmed as the focus for further research
Bragg spectroscopy of a superfluid Bose-Hubbard gas
Bragg spectroscopy is used to measure excitations of a trapped,
quantum-degenerate gas of 87Rb atoms in a 3-dimensional optical lattice. The
measurements are carried out over a range of optical lattice depths in the
superfluid phase of the Bose-Hubbard model. For fixed wavevector, the resonant
frequency of the excitation is found to decrease with increasing lattice depth.
A numerical calculation of the resonant frequencies based on Bogoliubov theory
shows a less steep rate of decrease than the measurements.Comment: 11 pages, 4 figure
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