Based on the cellular automaton （CA） method, a numerical model was developed to simulate the dendritic growth of magnesium alloy with HCP crystal structure. The growth kinetics was calculated from the complete solut...Based on the cellular automaton （CA） method, a numerical model was developed to simulate the dendritic growth of magnesium alloy with HCP crystal structure. The growth kinetics was calculated from the complete solution of the transport equations. By defining a special neighborhood configuration with the square CA cell, and using a set of capturing rules which were proposed by BELTRAN-SANCHEZ and STEFANESCU for the dendritic growth of cubic crystal metals during solidification, modeling of dendritic growth of magnesium alloy with different growth orientations was achieved. Simulation of equiaxed dendritic growth and columnar dendritic growth under directional solidification was carried out, and validation was performed by comparing the simulated results with the experimental results and those in the previously published works.展开更多
Most existing classification studies use spectral information and those were adequate for cities or plains. This paper explores classification method suitable for the ALOS （Advanced Land Observing Satellite） in moun...Most existing classification studies use spectral information and those were adequate for cities or plains. This paper explores classification method suitable for the ALOS （Advanced Land Observing Satellite） in mountainous terrain. Mountainous terrain mapping using ALOS image faces numerous challenges. These include spectral confusion with other land cover features, topographic effects on spectral signatures （such as shadow）. At first, topographic radiometric correction was carried out to remove the illumination effects of topography. In addition to spectral features, texture features were used to assist classification in this paper. And texture features extracted based on GLCM （Gray Level Co- occurrence Matrix） were not only used for segmentation, but also used for building rules. The performance of the method was evaluated and compared with Maximum Likelihood Classification （MLC）. Results showed that the object-oriented method integrating spectral and texture features has achieved overall accuracy of 85.73% with a kappa coefficient of 0.824, which is 13.48% and o.145 respectively higher than that got by MLC method. It indicated that texture features can significantly improve overall accuracy, kappa coefficient, and the classification precision of existing spectrum confusion features. Object-oriented method Integrating spectral and texture features is suitable for land use extraction of ALOS image in mountainous terrain.展开更多
Accurate classification of EEG left and right hand motor imagery is an important issue in brain-computer interface. Firstly, discrete wavelet transform method was used to decompose the average power of C3 electrode an...Accurate classification of EEG left and right hand motor imagery is an important issue in brain-computer interface. Firstly, discrete wavelet transform method was used to decompose the average power of C3 electrode and C4 electrode in left-right hands imagery movement during some periods of time. The reconstructed signal of approximation coefficient A6 on the 6al level was selected to build up a feature signal. Secondly, the performances by Fisher Linear Discriminant Analysis with two different threshold calculation ways and Support Vector Machine methods were compared. The final classification results showed that false classification rate by Support Vector Machine was lower and gained an ideal classification results.展开更多
基金Projects (2010DFA72760, 2011BAE22B02, 2011ZX04014-052, 2011ZX04001-071) supported by the Ministry of Science and Technology of China
文摘Based on the cellular automaton （CA） method, a numerical model was developed to simulate the dendritic growth of magnesium alloy with HCP crystal structure. The growth kinetics was calculated from the complete solution of the transport equations. By defining a special neighborhood configuration with the square CA cell, and using a set of capturing rules which were proposed by BELTRAN-SANCHEZ and STEFANESCU for the dendritic growth of cubic crystal metals during solidification, modeling of dendritic growth of magnesium alloy with different growth orientations was achieved. Simulation of equiaxed dendritic growth and columnar dendritic growth under directional solidification was carried out, and validation was performed by comparing the simulated results with the experimental results and those in the previously published works.
基金supported jointly by Key Laboratory of Geo-special Information Technology, Ministry of Land and Resources (Grant No. KLGSIT2013-12)Knowledge Innovation Program (Grant No. KSCX1-YW-09-01) of Chinese Academy of Sciences
文摘Most existing classification studies use spectral information and those were adequate for cities or plains. This paper explores classification method suitable for the ALOS （Advanced Land Observing Satellite） in mountainous terrain. Mountainous terrain mapping using ALOS image faces numerous challenges. These include spectral confusion with other land cover features, topographic effects on spectral signatures （such as shadow）. At first, topographic radiometric correction was carried out to remove the illumination effects of topography. In addition to spectral features, texture features were used to assist classification in this paper. And texture features extracted based on GLCM （Gray Level Co- occurrence Matrix） were not only used for segmentation, but also used for building rules. The performance of the method was evaluated and compared with Maximum Likelihood Classification （MLC）. Results showed that the object-oriented method integrating spectral and texture features has achieved overall accuracy of 85.73% with a kappa coefficient of 0.824, which is 13.48% and o.145 respectively higher than that got by MLC method. It indicated that texture features can significantly improve overall accuracy, kappa coefficient, and the classification precision of existing spectrum confusion features. Object-oriented method Integrating spectral and texture features is suitable for land use extraction of ALOS image in mountainous terrain.
基金The Open Project of the State Key Laboratory of Robotics and System (HIT)the State Key Laboratory of Cognitive Neuroscience and Learning+3 种基金Natural Science Fund for Colleges and Universities in Jiangsu Provincegrant number:105TB51003Natural Science Fund in Changzhougrant number:CJ20110023
文摘Accurate classification of EEG left and right hand motor imagery is an important issue in brain-computer interface. Firstly, discrete wavelet transform method was used to decompose the average power of C3 electrode and C4 electrode in left-right hands imagery movement during some periods of time. The reconstructed signal of approximation coefficient A6 on the 6al level was selected to build up a feature signal. Secondly, the performances by Fisher Linear Discriminant Analysis with two different threshold calculation ways and Support Vector Machine methods were compared. The final classification results showed that false classification rate by Support Vector Machine was lower and gained an ideal classification results.
