A Dummy Location Selection Algorithm Based on Location Semantics and Physical Distance

Author(s):  
Dongdong Yang ◽  
Baopeng Ye ◽  
Yuling Chen ◽  
Huiyu Zhou ◽  
Xiaobin Qian
Computing ◽  
2014 ◽  
Vol 97 (4) ◽  
pp. 403-423 ◽  
Author(s):  
Yu Sun ◽  
Jianzhong Qi ◽  
Rui Zhang ◽  
Yueguo Chen ◽  
Xiaoyong Du

This article presents the case of Chatterley and Clifford, the two main characters in Lady Chatterley’s Lover, to consider tenderness a basic working emotion to shape human relationships. The lack of tenderness causes emotional as well as physical distance in relation, especially that of male-female’s relation. The first part of the article reviews tenderness. The second part reviews how tenderness and lack of tenderness affect a male-female relationship in the selected novel, Lady Chatterley’s Lover. On the basis of a careful analysis of Lady Chatterley’s Lover, the present writer tries to prove that the lack of tenderness is the main culprit for the broken relationship between husband and wife: a major one of the relations between man and woman in human society and mutual tenderness elicits people awakening to a new way of living in an exterior world that is uncracking after the long winter hibernation. Lawrence, through a revelation of Connie’s gradual awakening from tenderness, has made his utmost effort to explore possible solutions to harmonious androgyny between men and women so as to revitalize the distorted human nature caused by the industrial civilization. Key words: relationship, husband and wife, tenderness, main culprit, Connie


2014 ◽  
Vol 1 ◽  
pp. 652-655
Author(s):  
Takumi.Matsui Takumi.Matsui ◽  
Mikio.Hasegawa Mikio.Hasegawa ◽  
Hiroshi.Hirai Hiroshi.Hirai ◽  
Kiyohito.Nagano Kiyohito.Nagano ◽  
Kazuyuki.Aihara Kazuyuki.Aihara

Author(s):  
Manpreet Kaur ◽  
Chamkaur Singh

Educational Data Mining (EDM) is an emerging research area help the educational institutions to improve the performance of their students. Feature Selection (FS) algorithms remove irrelevant data from the educational dataset and hence increases the performance of classifiers used in EDM techniques. This paper present an analysis of the performance of feature selection algorithms on student data set. .In this papers the different problems that are defined in problem formulation. All these problems are resolved in future. Furthermore the paper is an attempt of playing a positive role in the improvement of education quality, as well as guides new researchers in making academic intervention.


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