722 research outputs found
Holographic chiral induced W-gravities
We study boundary conditions for 3-dimensional higher spin gravity that admit
asymptotic symmetry algebras expected of 2-dimensional induced higher spin
theories in the light cone gauge. For the higher spin theory based on sl(3, R)
plus sl(3,R) algebra, our boundary conditions give rise to one copy of
classical W3 and a copy of sl(3,R) or su(1,2) Kac-Moody symmetry algebra. We
propose that the higher spin theories with these boundary conditions describe
appropriate chiral induced W-gravity theories on the boundary. We also consider
boundary conditions of spin-3 higher spin gravity that admit u(1) plus u(1)
current algebra.Comment: 19 page
On Asymptotic Symmetries of 3d Extended Supergravities
We study asymptotic symmetry algebras for classes of three dimensional
supergravities with and without cosmological constant. In the first part we
generalise some of the non-Dirichlet boundary conditions of gravity to
extended supergravity theories, and compute their asymptotic symmetries. In
particular, we show that the boundary conditions proposed to holographically
describe the chiral induced gravity and Liouville gravity do admit extension to
the supergravity contexts with appropriate superalgebras as their asymptotic
symmetry algebras. In the second part we consider generalisation of the 3d
computation to extended supergravities without cosmological constant, and
show that their asymptotic symmetry algebras provide examples of nonlinear
extended superalgebras containing the algebra
Research Methodologies used in Knowledge Management: A Literature Review
The concept of knowledge management is becoming increasingly interesting to both academia and practitioners. The aim of the research is to answer a question ‘what type of research methodologies are used in conducting the knowledge management research in the past’. A comprehensive review of literature in knowledge management was conducted to answer this question. To achieve this, thorough reviews of 49 articles are done. A significant body of literature on knowledge management is summarized. Based on the review of the literature it has shown, all the three major research methods, such as qualitative, quantitative and mixed methods are used evenly
Geonex: A NASA-NOAA Collaboration for Producing Land Surface Products from Geostationary Sensors Using Cloud Computing
The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GEONEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GEONEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement.Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GEONEX pipeline including choice CPUs, storage media, and automation. We estimate the cost of deploying GEONEX to be $400 - 750 a month for processing data (every 30 minutes) and producing products over the conterminous US. For products such as Fire, latency can be as little as 10 minutes from the time of data acquisition
An sl(2, R) current algebra from AdS_3 gravity
We provide a set of chiral boundary conditions for three-dimensional gravity
that allow for asymptotic symmetries identical to those of two-dimensional
induced gravity in light-cone gauge considered by Polyakov. These are the most
general boundary conditions consistent with the boundary terms introduced by
Compere, Song and Strominger recently. We show that the asymptotic symmetry
algebra of our boundary conditions is an sl(2,R) current algebra with level
given by c/6. The fully non-linear solution in Fefferman--Graham coordinates is
also provided along with its charges.Comment: 8 page
Earth Observations from Geostationary Satellites
The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of MODIS and VIIRS, useful for monitoring land surface conditions. The NASA Earth Exchange (NEX) team at Ames Research Center has embarked on a collaborative effort among scientists from NASA and NOAA exploring the feasibility of producing operational land surface products similar to those from MODIS/VIIRS. The team built a processing pipeline called GeoNEX that is capable of converting raw geostationary data into routine products of Fires, surface reflectances, vegetation indices, LAI/FPAR, ET and GPP/NPP using algorithms adapted from both NASA/EOS and NOAA/GOES-R programs. The GeoNEX pipeline has been deployed on Amazon Web Services cloud platform and it currently leverages near-realtime geostationary data hosted in AWS public datasets under a NOAA-AWS agreement. Initial analyses of various products from ABI/AHI sensors suggest that they are comparable to those from MODIS in representing the spatio-temporal dynamics of land conditions. Cloud computing offers a variety of options for deploying the GeoNEX pipeline including choice CPUs, storage media, and automation. By making the GEONEX pipeline available on the cloud, we hope to engage a broad community of Earth scientists from around the world in utilizing this new source of data for Earth monitoring
Optical Flow for Intermediate Frame Interpolation of Multispectral Geostationary Satellite Data
Applications in areas such as weather tracking and modeling, ecosystem monitoring, wildfire detection, and land-cover change are heavily dependent on spatial and temporal resolutions of satellite observations. However, there are typically trade-offs between spatial and temporal resolutions in dataset selection. For instance, geostationary weather tracking satellites are designed to take snapshots many times throughout the day but sensor hardware limits data collection. In this work we tackle this limitation, developing a method for temporal upsampling of multi-spectral satellite imagery using optical flow video interpolation deep convolutional neural networks. The presented model, extends Super SloMo (SSM) from single optical flow estimates to multichannel where flows are computed per band. We apply this technique on 8 multi-spectral bands of NOAA/NASA's GOES-16 mesoscale dataset to temporally enhance full disk hemispheric snapshots from 15 minutes to 1 minute. Through extensive experimentation, we show SSM vastly outperforms the linear interpolation baseline and that multichannel optical flows improves performance on GOES-16. A visual analysis of optical flow vectors clearly identifies hurricanes and large-scale atmospheric dynamics. Furthermore, we discuss challenges and open questions related to optical flow and temporal interpolation of multispectral geostationary satellite imagery
Estimation of Regional Surface Resistance to Evapotranspiration from NDVI and Thermal-IR AVHRR Data
Infrared surface temperatures from satellite sensors have been used to infer evaporation and soil moisture distribution over large areas. However, surface energy partitioning to latent versus sensible heat changes with surface vegetation cover and water availability. We tested a hypothesis that the relationship between surface temperature and canopy density is sensitive to seasonal changes in canopy resistance of conifer forests. Surface temperature (Ts) and canopy density were computed for a 20 × 25 km forested region in Montana, from the NOAA/AVHRR for 8 days during the summer of 1985. A forest ecosystem model, FOREST-BGC, simulated canopy resistance (Rc) for the same period.
For all eight days. surface temperatures had high association with canopy density, measured as Normalized Difference Vegetation Index (NDVI) (R2 = 0.73 − 0.91), implying that latent heat exchange is the major cause of spatial variations in surface radiant temperatures. The slope of Ts and NDVI, σ, was sensitive to changes in canopy resistance on two contrasting days of canopy activity. The trajectory of σ followed seasonal changes in canopy resistance simulated by the model. The relationship found between σ and Rc (R2 = 0.92), was nonlinear, expected because Rc values beyond 20 s cm−1 do not influence energy partitioning significantly. The slope of Ts and NDVI, σ, could provide a useful parameterization of surface resistance in regional evapotranspiration research
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