By Dunhai Wang, Yubo Han, Ancun Jiao (auth.), Yuanzhi Wang (eds.)
This quantity contains prolonged and revised types of a collection of chosen papers from the 2011 2d overseas convention on schooling and academic know-how (EET 2011) held in Chengdu, China, October 1-2, 2011.
The project of EET 2011 quantity 2 is to supply a discussion board for researchers, educators, engineers, and executive officers focused on the overall parts of schooling administration, schooling concept and schooling program to disseminate their most recent learn effects and trade perspectives at the destiny examine instructions of those fields. 133 comparable subject papers have been chosen into this quantity. the entire papers have been reviewed by means of 2 software committee contributors and chosen via the quantity editor Prof. Yuanzhi Wang, from clever details expertise program learn organization, Hong Kong.
The convention will collect top researchers, engineers and scientists within the area of curiosity. we are hoping each player could have a very good chance to interchange their study principles and effects and to debate the cutting-edge within the components of the schooling administration, schooling concept and schooling application.
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Info know-how and academic administration within the wisdom Society is an important reference for either educational researchers within the box of data know-how and academic administration. because the mid-1980's, machine assisted academic info platforms were constructing in a variety of elements of the area and the data surrounding the advance and implementation of those structures has been transforming into.
Many networked desktops are some distance too liable to cyber assaults which may inhibit their functioning, corrupt vital facts, or reveal deepest info. now not strangely, the sphere of cyber-based structures seems to be a fertile floor the place many projects will be formulated as studying difficulties and approached when it comes to desktop studying algorithms.
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In August and September during 2006 and 2008, education activities with the theme of "green Olympics, hi-tech Olympics, humanistic Olympics" and "one world, one dream" were launched nationwide in primary and secondary schools, such as photography, painting, poetry, calligraphy, seal cutting, composition, foreign language speech contests, organization of Olympic summer camp and other activities. Third, the international exchange activities of “knot of one heart” were conducted. Depending on the experience of each organizing committee of Olympic Games, qualified primary and middle schools in Beijing were organized to be paired off with teams and the schools of the countries (regions) for the 2008 Olympic Games and the Paralympics games.
Design of Analog CMOS Integrated Circuits. R. com Abstract. The correlation and path analysis on relationship between the academic achievement and social responsibility for teachers were studied in university in Chongqing The results showed that the social responsibility for teachers had significant positive correlations with the title of outstanding teachers, to upgrading diploma , paper, and revenue in last 3 years. 0301) ． ． ， ， ． Keywords: University, Teachers, Academic achievement, Social Responsibility.
The input layer unit only plays the role of signal transmission while the output layer unit for the linear weighted, the transfer function of hidden layer units can be linear or non-linear function, furthermore, the following layer takes the memory of previous time output value of the hidden layer units, is a step delay operator, which allows the network have dynamic memory function. Fig. 1. 2 Learning Process of the Elman Neural Network Elman neural network sets input vector u(k), output vector y(k), hidden layer vector x(k), following layer vector xc(k), so the input-output function of Elman neural network was: x(k)=f(w1xc(k)+w2u(k-1)) 1 2 (1) xc(k)=x(k-1) (2) y(k)=g(w3x(k)) (3) 3 Which, w , w , w , respectively expresses the connection weight of following layer to hidden layer, input layer to hidden layer, hidden layer to output layer, while f (•) and g (•) were the transfer function of neurons about the hidden layer and output layer.