23300838
Hierarchical models for analysis and recognition of handwritten characters
Different hierarchical models in pattern analysis and recognition are proposed, based on occurrence probability of patterns. As an important application of recognizing handprinted characters, three typical kinds of hierarchical models such asM89-89,M89-36 andM36-36 have been presented, accompanied by the computer algorithms for computing recognition rates of pattern parts. Moreover, a comparative study of their recognition rates has been conducted theoretically; and numerical experiments have been carried out to verify the analytical conclusions made. Various hierarchical models deliberated in this paper can provide users more or better choices of pattern models in practical application, and lead to a uniform computational scheme (or code). The recognition rates of parts can be improved remarkably by a suitable hierarchical model. For the modelM89-36 in which case some of the Canadian standard handprinted characters have multiple occurrence probabilities, the total mean recognition rates of the given sample may reach 120% of that by the model proposed by Li et al., and 156% of that obtained from the subjective experiments reported by Suen.
5312051
Analysis and recognition of alphanumeric handprints by parts
In this paper, an advanced hierarchical model has been proposed to produce a more effective character recognizer based on the probability of occurrence of the patterns. New definitions such as crucial parts, efficiency ratios, degree of confusion, similar character pairs, etc. are also given to facilitate pattern analysis and character recognition. Using these definitions, computer algorithms have been developed to recognize the characters by parts, including halves, quarters, and sixths. The recognition rates have been analyzed and compared to those obtained from subjective experiments. Based on the results of both computer and human experiments, a detailed analysis of the crucial parts and the Canadian standard alphanumeric character set has been made which revealed some fundamental characteristics of these handprint models. The results should be useful to pattern analysis and recognition, character understanding, handwriting education, and human-computer communication. >
128973346
Quantitative study of net radiation from MODIS data in the lower boundary layer in Poyang Lake area of Jiangxi Province, China
This paper focuses on quantitative calculation of longwave radiation and shortwave radiation from MODIS data in the Poyang Lake area of Jiangxi Province, China. The sum of the net longwave radiation and the shortwave radiation is the net radiation. These parameters are critical for the study of energy exchange in the lower boundary layer on land surface. Two of the most important factors for the retrieval of longwave radiation are the land surface temperature and emissivity. In this paper, the land surface temperature and emissivity were calculated from MODIS data using the regional self‐iterative split‐window method. The most important factor in the determination of the shortwave radiation is Earth surface albedo. The spectral reflectance and surface albedo were derived from MODIS data using the Synergy of TERRA and AQUA MODIS data (SYNTAM) algorithm. The net shortwave and longwave radiation were calculated and compared with the in situ measurement data. Our results indicate that the methods for quantitative calculation of net longwave radiation, shortwave radiation and net radiation from MODIS data can have a good accuracy. The relative errors are between 2.1% to 9.72% for longwave radiation, 0.15% to 10.48% for shortwave radiation and 0.64% to 13.7% for net radiation. We can conclude that a good accuracy can be achieved for deriving longwave radiation, shortwave radiation and net radiation, which are helpful for heat exchange, environmental, hydrology and ecology research in land areas.
21048589
Parallel Computing at the NASA Data Assimilation Office (DAO)
The goal of atmospheric data assimilation is to produce accurate gridded datasets of fields by assimilating a range of observations along with physically consistent model forecasts. The NASA Data Assimilation Office (DAO) is currently upgrading its end-to-end data assimilation system (GEOS DAS) to support NASA's Mission To Planet Earth (MTPE) Enterprise. This effort is also part of a NASA HPCC Earth and Space Sciences (ESS) Grand Challenge PI project. Future Core computing, using a modular Fortran 90 design and distributed memory (MPI) software, will be carried out at Ames Research Center. The algorithmic and performance issues involved in the Core system are the main subjects of this presentation.
40928796
Research of the Gyro Signal De-Noising Method Based on Stationary Wavelets Transform
28408363
Nonlinear Generalized Predictive Control Based on Inverse System Using Wavelet Networks
45863333
Generic Programming with Reusable Wavelet Transforms