58 resultados para improved SVM

em CentAUR: Central Archive University of Reading - UK


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An improved algorithm for the generation of gridded window brightness temperatures is presented. The primary data source is the International Satellite Cloud Climatology Project, level B3 data, covering the period from July 1983 to the present. The algorithm rakes window brightness, temperatures from multiple satellites, both geostationary and polar orbiting, which have already been navigated and normalized radiometrically to the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer, and generates 3-hourly global images on a 0.5 degrees by 0.5 degrees latitude-longitude grid. The gridding uses a hierarchical scheme based on spherical kernel estimators. As part of the gridding procedure, the geostationary data are corrected for limb effects using a simple empirical correction to the radiances, from which the corrected temperatures are computed. This is in addition to the application of satellite zenith angle weighting to downweight limb pixels in preference to nearer-nadir pixels. The polar orbiter data are windowed on the target time with temporal weighting to account for the noncontemporaneous nature of the data. Large regions of missing data are interpolated from adjacent processed images using a form of motion compensated interpolation based on the estimation of motion vectors using an hierarchical block matching scheme. Examples are shown of the various stages in the process. Also shown are examples of the usefulness of this type of data in GCM validation.

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Monthly mean water vapour and clear-sky radiation extracted from the European Centre for Medium Range Weather Forecasts 40-year reanalysis (ERA40) forecasts are assessed using satellite observations and additional reanalysis data. There is a marked improvement in the interannual variability of column-integrated water vapour (CWV) over the oceans when using the 24-hour forecasts compared with the standard 6-hour forecasts products. The spatial distribution of CWV are well simulated by the 6-hour forecasts; using the 24-hour forecasts does not degrade this simulation substantially and in many cases improves on the quality. There is also an improved simulation of clear-sky radiation from the 24-hour forecasts compared with the 6-hour forecasts based on comparison with satellite observations and empirical estimates. Further work is required to assess the quality of water vapour simulation by reanalyses over land regions. Over the oceans, it is recommended that 24-hour forecasts of CWV and clear-sky radiation are used in preference to the standard 6-hour forecast products from ERA40

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Urban flood inundation models require considerable data for their parameterisation, calibration and validation. TerraSAR-X should be suitable for urban flood detection because of its high resolution in stripmap/spotlight modes. The paper describes ongoing work on a project to assess how well TerraSAR-X can detect flooded regions in urban areas, and how well these can constrain the parameters of an urban flood model. The study uses a TerraSAR-X image of a 1-in-150 year flood near Tewkesbury, UK , in 2007, for which contemporaneous aerial photography exists for validation. The DLR SETES SAR simulator was used in conjunction with LiDAR data to estimate regions of the image in which water would not be visible due to shadow or layover caused by buildings and vegetation. An algorithm for the delineation of flood water in urban areas is described, together with its validation using the aerial photographs.

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The Integrated Catchment Model of Nitrogen (INCA-N) was applied to the Lambourn and Pang river-systems to integrate current process-knowledge and available-data to test two hypotheses and thereby determine the key factors and processes controlling the movement of nitrate at the catchment-scale in lowland, permeable river-systems: (i) that the in-stream nitrate concentrations were controlled by two end-members only: groundwater and soil-water, and (ii) that the groundwater was the key store of nitrate in these river-systems. Neither hypothesis was proved true or false. Due to equifinality in the model structure and parameters at least two alternative models provided viable explanations for the observed in-stream nitrate concentrations. One model demonstrated that the seasonal-pattern in the stream-water nitrate concentrations was controlled mainly by the mixing of ground- and soil-water inputs. An alternative model demonstrated that in-stream processes were important. It is hoped further measurements of nitrate concentrations made in the catchment soil- and ground-water and in-stream may constrain the model and help determine the correct structure, though other recent studies suggest that these data may serve only to highlight the heterogeneity of the system. Thus when making model-based assessments and forecasts it is recommend that all possible models are used, and the range of forecasts compared. In this study both models suggest that cereal production contributed approximately 50% the simulated in-stream nitrate toad in the two catchments, and the point-source contribution to the in-stream load was minimal. (c) 2006 Elsevier B.V. All rights reserved.

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Real-time rainfall monitoring in Africa is of great practical importance for operational applications in hydrology and agriculture. Satellite data have been used in this context for many years because of the lack of surface observations. This paper describes an improved artificial neural network algorithm for operational applications. The algorithm combines numerical weather model information with the satellite data. Using this algorithm, daily rainfall estimates were derived for 4 yr of the Ethiopian and Zambian main rainy seasons and were compared with two other algorithms-a multiple linear regression making use of the same information as that of the neural network and a satellite-only method. All algorithms were validated against rain gauge data. Overall, the neural network performs best, but the extent to which it does so depends on the calibration/validation protocol. The advantages of the neural network are most evident when calibration data are numerous and close in space and time to the validation data. This result emphasizes the importance of a real-time calibration system.

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Self-Organizing Map (SOM) algorithm has been extensively used for analysis and classification problems. For this kind of problems, datasets become more and more large and it is necessary to speed up the SOM learning. In this paper we present an application of the Simulated Annealing (SA) procedure to the SOM learning algorithm. The goal of the algorithm is to obtain fast learning and better performance in terms of matching of input data and regularity of the obtained map. An advantage of the proposed technique is that it preserves the simplicity of the basic algorithm. Several tests, carried out on different large datasets, demonstrate the effectiveness of the proposed algorithm in comparison with the original SOM and with some of its modification introduced to speed-up the learning.

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Quadrature Phase Shift Keying (QPSK) and Dual Carrier Modulation (DCM) are currently used as the modulation schemes for Multiband Orthogonal Frequency Division Multiplexing (MB-OFDM) in the ECMA-368 defined Ultra-Wideband (UWB) radio platform. ECMA-368 has been chosen as the physical radio platform for many systems including Wireless USB (W-USB), Bluetooth 3.0 and Wireless HDMI; hence ECMA-368 is an important issue to consumer electronics and the users’ experience of these products. To enable the transport of high-rate USB, ECMA-368 offers up to 480 Mb/s instantaneous bit rate to the Medium Access Control (MAC) layer, but depending on radio channel conditions dropped packets unfortunately result in a lower throughput. This paper presents improvement on a high data rate modulation scheme that fits within the configuration of the current standard increasing system throughput by achieving 600 Mb/s (reliable to 3.2 meters) thus maintaining the high rate USB throughput even with a moderate level of dropped packets. The modulation system is termed improved and optimal Dual Circular 32-QAM (DC 32-QAM). The system performance for improved and optimal DC 32-QAM modulation is presented and compared with previous DC 32- QAM, 16-QAM and DCM.

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Improved upland rice cultivars introduced in Volta Region, Ghana, have been perceived to store poorly compared to farmers' traditional cultivars. A survey was conducted in 2003 in the Hohoc district of this region, where a participatory Varietal Selection programme had started in 1997, to gain insight into fanners' seed production and storage practices that are likely to affect seed quality in storage. Farmers rated keeping quality (p < 0.001), tolerance to storage pests (p < 0.001), seed quality (p < 0.001) and establishment of their local cultivars Kawomo, Viono and Wuwulili as much better than the improved cultivar IDSA 85. Initial seed moisture content ranged from 12.8 to 18% and germination from 0 to 82%. There was a significant relationship between seed moisture content and duration of drying prior to storage (p < 0.001) and storage method (p = 0.015). Germination loss in storage was rapid at high moisture content and slow at low moisture content. Between 60 and 80% of seeds germinated after six Months storage at 12.8% moisture content. The viability equation predicted accurately germination of farmer-saved seed stored under ambient temperature in Ghana. Except for the japonica rice cultivar WAB 126-18-HB, the traditional cultivars Kawomo, Viono and Wuwulili survived better in storage than improved cultivars. There is a need to improve seed quality of improved cultivars if farmers are to benefit from their higher yields and grain quality and to improve storage practices.