The Experts below are selected from a list of 91722 Experts worldwide ranked by ideXlab platform
B. Ziv - One of the best experts on this subject based on the ideXlab platform.
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A subtropical rainstorm associated with a tropical plume overAfrica and the Middle-East
Theoretical and Applied Climatology, 2001Co-Authors: B. ZivAbstract:Cloud bands that extend from the ITCZ along the subtropical jet toward the subtropics are known as ‘tropical plumes’. At times rainstorms develop at their subtropical edges. One such rainstorm swept eastern North Africa and the Middle East on 23–24 December 1988, with rainfall comparable with the annual averages there. This study examines the storm using the ECMWF Initialized Data together with surface observations and satellite imageries. The analysis indicates that the storm developed at the inflection region ahead of a pronounced trough in the subtropical jet, with which a mid-latitude trough was merged. Two ageostrophic effects taking place along the jet ahead of the trough contributed to the intensity of the rainstorm. One was associated with acceleration at the jet entrance, located at tropical latitudes, which contributed to the enhancement of both tropical convection and the southerly wind component, which enhanced the moisture tropical transport toward the subtropics. The second was the enhanced near-tropospheric divergence associated with positive vorticity advection at the inflection region itself. Since both effects have a quadratic dependence on wind speed, the observed jet speed, 50% larger than its average value, explains the observed divergence at the inflection point at the 200 hPa level, over 6 × 10^−5 s^−1, and the vertical velocity at the 700 hPa level, about 10^−1 ms^−1. It is suggested here that the merging of a mid-latitude with the trough in the subtropical jet, with which the tropical plume is associated, is the cause for the intensification of the subtropical jet and hence of its related rainstorms.
T. N. Krishnamurti - One of the best experts on this subject based on the ideXlab platform.
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Impact of physical initialization on cloud forecasts
Meteorology and Atmospheric Physics, 1995Co-Authors: H. -s. Lee, T. N. KrishnamurtiAbstract:The impact of initial Data on cloud forecasts by the Florida State University Global Spectral Model (FSUGSM) has been investigated. This work has shown that improving the information content of the initial Data by physical initialization has a very strong, positive impact on cloud forecasts. Model spin-up of clouds is considerably reduced. There is an overall better representation of high, middle, low, and total clouds over the tropics and there is a discernible improvement in the prediction of clouds. A strong correlation between cloud shortwave forcing and longwave forcing has been noted in model forecasts with the physically Initialized Data. This result compares very well with observations from the Earth Radiation Budget Experiment (ERBE).
Alaa Abdulhussain Refeis - One of the best experts on this subject based on the ideXlab platform.
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isolated uttered words recognition based on gmm hmm algorithms using sopc nios ii processor build on altera cyclone ii fpga chip
National Conference for Engineering Sciences, 2012Co-Authors: Eyad I. Abbas, Alaa Abdulhussain RefeisAbstract:This paper introduced an approach to design and implement an embedded SoPC (System on a Programmable Chip) technique with Altera Nios II processor for real-time speech recognition system by developing hardware/software with minimum usage of resources (hardware components) and relatively small size software to reduce memory utilization. This is achieved by using Mel Frequency Cepstral Coefficients (MFCCs) technique as speech signal feature extraction (observation vector). Using Gaussian Mixture Model (GMM) to model the observation vector of voice information. Finally, this model passed to the Hidden Markov Model (HMM) as probabilistic model to process the GMM statistically to make decision on utterance words recognition, whether a single or composite, one or more syllable words (i.e. one, six, target). The total framework was implemented on Altera Cyclone II EP2C70F896C6N FPGA chip sitting on ALTERA DE2-70 Development Board. The utility software which are used as tools for design and development hardware/software are Quartus II 11.0sp1 (32-Bit) and Nios II 11.0spl IDE/C++ respectively. Each word model (template) stored as Transition Matrix, Diagonal Covariance Matrices, and Mean Vectors in the system memory. Each word model utilizes only 4.45Kbytes regardless of the spoken word length. Accuracy of the recognition words (digit/0 to digit/10) given 100% for the individual speaker. Training and recognition software has size (code + Initialized Data) equal to 312Kbytes.
H. -s. Lee - One of the best experts on this subject based on the ideXlab platform.
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Impact of physical initialization on cloud forecasts
Meteorology and Atmospheric Physics, 1995Co-Authors: H. -s. Lee, T. N. KrishnamurtiAbstract:The impact of initial Data on cloud forecasts by the Florida State University Global Spectral Model (FSUGSM) has been investigated. This work has shown that improving the information content of the initial Data by physical initialization has a very strong, positive impact on cloud forecasts. Model spin-up of clouds is considerably reduced. There is an overall better representation of high, middle, low, and total clouds over the tropics and there is a discernible improvement in the prediction of clouds. A strong correlation between cloud shortwave forcing and longwave forcing has been noted in model forecasts with the physically Initialized Data. This result compares very well with observations from the Earth Radiation Budget Experiment (ERBE).
Eyad I. Abbas - One of the best experts on this subject based on the ideXlab platform.
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isolated uttered words recognition based on gmm hmm algorithms using sopc nios ii processor build on altera cyclone ii fpga chip
National Conference for Engineering Sciences, 2012Co-Authors: Eyad I. Abbas, Alaa Abdulhussain RefeisAbstract:This paper introduced an approach to design and implement an embedded SoPC (System on a Programmable Chip) technique with Altera Nios II processor for real-time speech recognition system by developing hardware/software with minimum usage of resources (hardware components) and relatively small size software to reduce memory utilization. This is achieved by using Mel Frequency Cepstral Coefficients (MFCCs) technique as speech signal feature extraction (observation vector). Using Gaussian Mixture Model (GMM) to model the observation vector of voice information. Finally, this model passed to the Hidden Markov Model (HMM) as probabilistic model to process the GMM statistically to make decision on utterance words recognition, whether a single or composite, one or more syllable words (i.e. one, six, target). The total framework was implemented on Altera Cyclone II EP2C70F896C6N FPGA chip sitting on ALTERA DE2-70 Development Board. The utility software which are used as tools for design and development hardware/software are Quartus II 11.0sp1 (32-Bit) and Nios II 11.0spl IDE/C++ respectively. Each word model (template) stored as Transition Matrix, Diagonal Covariance Matrices, and Mean Vectors in the system memory. Each word model utilizes only 4.45Kbytes regardless of the spoken word length. Accuracy of the recognition words (digit/0 to digit/10) given 100% for the individual speaker. Training and recognition software has size (code + Initialized Data) equal to 312Kbytes.