Upper Atmosphere Research Satellite (UARS) trade analysis

The Upper Atmosphere Research Satellite (UARS) which will collect data pertinent to the Earth's upper atmosphere is described. The collected data will be sent to the central data handling facility (CDHF) via the UARS ground system and the data will be processed and distributed to the remote analysis computer systems (RACS). An overview of the UARS ground system is presented. Three configurations were developed for the CDHF-RACS system. The CDHF configurations are discussed. The IBM CDHF configuration, the UNIVAC CDHF configuration and the vax cluster CDHF configuration are presented. The RACS configurations, the IBM RACS configurations, UNIVAC RACS and VAX RACS are detailed. Due to the large on-line data estimate to approximately 100 GB, a mass storage system is considered essential to the UARS CDHF. Mass storage systems were analyzed and the Braegan ATL, the RCA optical disk, the IBM 3850 and the MASSTOR M860 are discussed. It is determined that the type of mass storage system most suitable to UARS is the automated tape/cartridge device. Two devices of this type, the IBM 3850 and the MASSTOR MSS are analyzed and the applicable tape/cartridge device is incorporated into the three CDHF-RACS configurations

Using learned action models in execution monitoring

Planners reason with abstracted models of the behaviours they use to construct plans. When plans are turned into the instructions that drive an executive, the real behaviours interacting with the unpredictable uncertainties of the environment can lead to failure. One of the challenges for intelligent autonomy is to recognise when the actual execution of a behaviour has diverged so far from the expected behaviour that it can be considered to be a failure. In this paper we present further developments of the work described in (Fox et al. 2006), where models of behaviours were learned as Hidden Markov Models. Execution of behaviours is monitored by tracking the most likely trajectory through such a learned model, while possible failures in execution are identified as deviations from common patterns of trajectories within the learned models. We present results for our experiments with a model learned for a robot behaviour

The identification and exploitation of almost symmetry in planning problems

Previous work in symmetry detection for planning has identified symmetries between domain objects and shown how the exploitation of this information can help reduce search at plan time. However these methods are unable to detect symmetries between objects that are almost symmetrical: where the objects must start (or end) in slightly different configurations but for much of the plan their behaviour is equivalent. In the paper we outline a method for identifying such symmetries and discuss how this symmetry information can be positively exploited to help direct search during planning we have implemented this method and integrated it with the FF-v2.3 planner and in the paper we present results of experiments with this approach that demonstrate its potential

Abstraction-based action ordering in planning

Many planning problems contain collections of symmetric objects, actions and structures which render them difficult to solve efficiently. It has been shown that the detection and exploitation of symmetric structure in planning problems can dramatically reduce the size of the search space and the time taken to find a solution. We present the idea of using an abstraction of the problem domain to reveal symmetric structure and guide the navigation of the search space. We show that this is effective even in domains in which there is little accessible symmetric structure available for pruning. Proactive exploitation represents a flexible and powerfulalternative to the symmetry-breaking strategies exploited in earlier work in planning and CSPs. The notion of almost symmetry is defined and results are presented showing that proactive exploitation of almost symmetry can improve the performance of a heuristic forward search planner

Vibrational-Rotational Spectroscopy for Planetary Atmospheres, volume 2

The planetary atmospheres are investigated for their chemical composition. Hydrogen, methane, ethylene, acetylene, and ethane were studied. Various spectroscopic investigations were made

Vibrational-Rotational Spectroscopy For Planetary Atmospheres, volume 1

Comprehensive information on the composition and dynamics of the varied planetary atmospheres is summarized. New observations resulted in new demands for supporting laboratory studies. Spectra observed from spacecraft used to interpret planetary atmospheric structure measurements, to aid in greenhouse and cloud physics calculations, and to plan future experiments are discussed. Current findings and new ideas of physicists, chemists, and planetry astronomers relating to the knowledge of the structure of things large and small, of planets and of molecules are summarized