Strategies for Cultivating Public Funded Targeted Normal Students Based on Goal Management Theory : A Case Study of East, West and North Guangdong

Public funded targeted normal students are an important component of China's teacher team construction.Since its implementation in 2007,a large number of outstanding rural teachers who have been striving on the front line of education have been trained.Based on the theory of goal management,this paper explores the problems and countermeasures in the training of public funded targeted normal students.It strives to solve the problems of low willingness to teach and high default rates among public funded normal students,and hopes that the suggestions proposed in this paper can further promote the effective implementation of policies for public funded normal students.

Representation of global precipitation anomalies using four major climate patterns

This study aims at finding the dominant climate patterns that influence the precipitation anomalies for different regions over the world. To this end, a multiple linear regression model is employed to represent the impact of four major climate patterns(El Ni?o-Southern Oscillation(ENSO), Indian Ocean Dipole(IOD), Arctic Oscillation(AO) and Antarctic Oscillation(AAO)) on the global precipitation anomalies. The normalized climate pattern indexes and normalized precipitation anomalies are used in the regression model. For the Northern Hemisphere, the three predictors used are the normalized NINO3.4 index(representing ENSO), normalized DMI(representing IOD) and normalized AO index; for the Southern Hemisphere, also three indexes are used as three predictors, and the normalized AO index is replaced by the normalized AAO index. The influences brought by each climate pattern can be represented by the magnitude of the corresponding regression coefficients, and the dominant climate patterns are those with the largest magnitude. The study results show that the precipitation anomalies in the northern part of South America and the northwestern part of Southeast Asia are mainly influenced by ENSO. The precipitation anomalies in East Africa and the southwestern part of Southeast Asia are mainly influenced by IOD. The precipitation anomalies in Europe and west coast of North America are mainly influenced by AO; the precipitation anomalies in the eastern part and southern part of South America, southern part of Africa, and the northeastern Australia are mainly influenced by AAO. These findings are consistent with the general understanding on the teleconnection features of the four climate patterns. Further, the regression model can be used for predicting precipitation anomalies through use of these major climate patterns.

No-reference image quality assessment based on nonsubsample shearlet transform and natural scene statistics

A novel no-reference(NR) image quality assessment(IQA) method is proposed for assessing image quality across multifarious distortion categories. The new method transforms distorted images into the shearlet domain using a non-subsample shearlet transform(NSST), and designs the image quality feature vector to describe images utilizing natural scenes statistical features: coefficient distribution, energy distribution and structural correlation(SC) across orientations and scales. The final image quality is achieved from distortion classification and regression models trained by a support vector machine(SVM). The experimental results on the LIVE2 IQA database indicate that the method can assess image quality effectively, and the extracted features are susceptive to the category and severity of distortion. Furthermore, our proposed method is database independent and has a higher correlation rate and lower root mean squared error(RMSE) with human perception than other high performance NR IQA methods.