113,670 research outputs found
The navigation system of the JPL robot
The control structure of the JPL research robot and the operations of the navigation subsystem are discussed. The robot functions as a network of interacting concurrent processes distributed among several computers and coordinated by a central executive. The results of scene analysis are used to create a segmented terrain model in which surface regions are classified by traversibility. The model is used by a path planning algorithm, PATH, which uses tree search methods to find the optimal path to a goal. In PATH, the search space is defined dynamically as a consequence of node testing. Maze-solving and the use of an associative data base for context dependent node generation are also discussed. Execution of a planned path is accomplished by a feedback guidance process with automatic error recovery
A search for debris disks in the Herschel-ATLAS
Aims. We aim to demonstrate that the Herschel-ATLAS (H-ATLAS) is suitable for a blind and unbiased survey for debris disks by identifying candidate debris disks associated with main sequence stars in the initial science demonstration field of the survey. We show that H-ATLAS reveals a population of far-infrared/sub-mm sources that are associated with stars or star-like objects on the SDSS main-sequence locus. We validate our approach by comparing the properties of the most likely candidate disks to those of the known population.
Methods. We use a photometric selection technique to identify main sequence stars in the SDSS DR7 catalogue and a Bayesian Likelihood Ratio method to identify H-ATLAS catalogue sources associated with these main sequence stars. Following this photometric selection we apply distance cuts to identify the most likely candidate debris disks and rule out the presence of contaminating galaxies using UKIDSS LAS K-band images.
Results. We identify 78 H-ATLAS sources associated with SDSS point sources on the main-sequence locus, of which two are the most likely debris disk candidates: H-ATLAS J090315.8 and H-ATLAS J090240.2. We show that they are plausible candidates by comparing their properties
to the known population of debris disks. Our initial results indicate that bright debris disks are rare, with only 2 candidates identified in a search
sample of 851 stars. We also show that H-ATLAS can derive useful upper limits for debris disks associated with Hipparcos stars in the field and outline the future prospects for our debris disk search programme
Infrared Dark Cloud Cores in the SCUBA Legacy Catalogue
We present an investigation of candidate Infrared Dark Cloud cores as
identified by Simon et al. (2006) located within the SCUBA Legacy Catalogue.
After applying a uniform noise cut to the Catalogue data we identify 154
Infrared Dark Cloud cores that were detected at 850um and 51 cores that were
not. We derive column densities for each core from their 8um extinction and
find that the IRDCs detected at 850um have higher column densities (a mean of
1.7x10^22 cm-2) compared to those cores not detected at 850um (a mean of
1.0x10^22 cm-2). Combined with sensitivity estimates, we suggest that the cores
not detected at 850um are low mass, low column density and low temperature
cores that are below the sensitivity limit of SCUBA at 850um. For a subsample
of the cores detected at 850um those contained within the MIPSGAL area) we find
that two thirds are associated with 24um sources. Cores not associated with
24um emission are either ``starless'' IRDC cores that perhaps have yet to form
stars, or contain low mass YSOs below the MIPSGAL detection limit. We see that
those ``starless'' IRDC cores and the IRDC cores associated with 24um emission
are drawn from the same column density population and are of similar mass. If
we then assume the cores without 24um embedded sources are at an earlier
evolutionary stage to cores with embedded objects we derive a statistical
lifetime for the quiescent phase of a few 10^3-10^4 years. Finally, we make
conservative predictions for the number of observed IRDCs that will be observed
by the Apex Telescope Galactic Plane Survey (ATLASGAL), the Herschel Infrared
Galactic Plane Survey (Hi-GAL), the JCMT Galactic Plane Survey (JPS) and the
SCUBA-2 ``All Sky'' Survey (SASSy).Comment: 18 pages, 3 tables, 10 figure
Pattern formation in large domains
Pattern formation is a phenomenon that arises in a wide variety of physical, chemical
and biological situations. A great deal of theoretical progress has been made in
understanding the universal aspects of pattern formation in terms of amplitudes of
the modes that make up the pattern. Much of the theory has sound mathematical
justification, but experiments and numerical simulations over the last decade have
revealed complex two-dimensional patterns that do not have a satisfactory theoretical
explanation. This paper focuses on quasi-patterns, where the appearance of small
divisors causes the standard theoretical method to fail, and ends with a discussion
of other outstanding problems in the theory of two-dimensional pattern formation
in large domains
Searching for Globally Optimal Functional Forms for Inter-Atomic Potentials Using Parallel Tempering and Genetic Programming
We develop a Genetic Programming-based methodology that enables discovery of
novel functional forms for classical inter-atomic force-fields, used in
molecular dynamics simulations. Unlike previous efforts in the field, that fit
only the parameters to the fixed functional forms, we instead use a novel
algorithm to search the space of many possible functional forms. While a
follow-on practical procedure will use experimental and {\it ab inito} data to
find an optimal functional form for a forcefield, we first validate the
approach using a manufactured solution. This validation has the advantage of a
well-defined metric of success. We manufactured a training set of atomic
coordinate data with an associated set of global energies using the well-known
Lennard-Jones inter-atomic potential. We performed an automatic functional form
fitting procedure starting with a population of random functions, using a
genetic programming functional formulation, and a parallel tempering
Metropolis-based optimization algorithm. Our massively-parallel method
independently discovered the Lennard-Jones function after searching for several
hours on 100 processors and covering a miniscule portion of the configuration
space. We find that the method is suitable for unsupervised discovery of
functional forms for inter-atomic potentials/force-fields. We also find that
our parallel tempering Metropolis-based approach significantly improves the
optimization convergence time, and takes good advantage of the parallel cluster
architecture
Noncontact GMR measurements of synthetic spin valves using IR reflection spectroscopy
The magnetorefractive effect has been used in infrared reflection spectroscopy to study the magnetotransport properties of synthetic spin valves. This optical noncontact technique shows excellent correlation with the electrical giant magnetoresistance data
A Personalized System for Conversational Recommendations
Searching for and making decisions about information is becoming increasingly
difficult as the amount of information and number of choices increases.
Recommendation systems help users find items of interest of a particular type,
such as movies or restaurants, but are still somewhat awkward to use. Our
solution is to take advantage of the complementary strengths of personalized
recommendation systems and dialogue systems, creating personalized aides. We
present a system -- the Adaptive Place Advisor -- that treats item selection as
an interactive, conversational process, with the program inquiring about item
attributes and the user responding. Individual, long-term user preferences are
unobtrusively obtained in the course of normal recommendation dialogues and
used to direct future conversations with the same user. We present a novel user
model that influences both item search and the questions asked during a
conversation. We demonstrate the effectiveness of our system in significantly
reducing the time and number of interactions required to find a satisfactory
item, as compared to a control group of users interacting with a non-adaptive
version of the system
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