Scale-free structure of town road network in southern Jiangsu Province of China

2007 ◽  
Vol 17 (4) ◽  
pp. 311-316 ◽  
Author(s):  
Weizhong Su ◽  
Guishan Yang ◽  
Shimou Yao ◽  
Yingbao Yang
2014 ◽  
Vol 26 (3) ◽  
pp. 235-242 ◽  
Author(s):  
Katarzyna KOCUR-BERA

This paper discusses the issue of statistical analysis of traffic flow in different regions of Poland. Such analysis allows us to identify “valuable (sensitive) areas” whose damage or blockage may provoke considerable disturbances or even a stoppage of traffic flow in the examined road network. The results of the studies indicate that the road network in Poland has the properties of a scale-free network. The distribution of the examined variables does not have a normal character, whereas the relationship between the number of nodes and the number of connections is a power-law feature. 


2014 ◽  
Vol 34 (2) ◽  
Author(s):  
陈小华 CHEN Xiaohua ◽  
李小平 LI Xiaoping ◽  
王菲菲 WANG Feifei ◽  
陈无歧 CHEN Wuqi ◽  
刘晓臣 LIU Xiaochen

2017 ◽  
Vol 9 (8) ◽  
pp. 212 ◽  
Author(s):  
Xu Lingjuan ◽  
Wang Yanjun ◽  
Zhu Huailei

The paper takes Jiangsu province as example in Yangtze River Delta, which is economically developed regions. According to previous research and characteristics of rural banks in Jiangsu Province, the input indexes are selected as the number of employees, the number of outlets, total deposits, business and management fees. And the output indexes include total loans, net interest income and net profit. Using DEA model to analyze the operating efficiency of the 65 rural banks in 2016, the paper compares the operating efficiency in different regions and different types of originating bank. The analysis shows that, compared with the central and northern Jiangsu, operating efficiency of rural banks in southern Jiangsu is generally high. The comprehensive technical efficiency value of sample banks that originated by the state-owned banks and joint-stock banks is significantly higher than that originated by rural commercial banks and city commercial banks. Finally, the paper puts forward some suggestions on how to improve the operating efficiency of rural banks.


Author(s):  
Jeroen van de Weijer ◽  
Marjoleine Sloos ◽  
Yunyun Ran

Huangyan dialect (, local name: [wɔ̤ɲjɛ˜̤wa̤]) is a variety of Taizhou dialect () as spoken in Zhejiang Province in China1 (see Figure 1).2 Huangyan District had a population of 616,000 people in 2019.3 The Zhejiang Taizhou dialect belongs to the Wu dialect group, which forms the second largest dialect group in China (after Mandarin). The language genealogy of Huangyan is presented in Figure 2. Wu dialects are spoken in the city of Shanghai, Zhejiang Province, southern Jiangsu Province and bordering areas (see Figure 3), an area with an estimated population of 80 million people in 2013 (Lewis 2009). The Wu dialects are not mutually intelligible with (Standard) Mandarin and often not even with each other (Norman 2003, Wang 2014).


2013 ◽  
Vol 448-453 ◽  
pp. 4079-4084
Author(s):  
Zong Yu Chen ◽  
Qian Xu ◽  
Yao Zhi Huang

With the unique geographic position and our own resources advantage, the functions undertaken by small towns in southern Jiangsu Province shall be transformed under the background of aging. By analyzing the key nodes of function transformation in small towns in southern Jiangsu Province and combining the requirements of current urban development situation, we make clear that the urban functions must transform to adapt to aging. Moreover, combing our own resource endowment of adaptive aging development, we make an analysis from the four aspects of location advantage, economic strength, land resource advantage and ecological environment advantage and propose the countermeasures for function transformation to adapt to aging development in small towns in southern Jiangsu Province in order to make them become a gathering place for the aged and the gather of silver age industry, and adapt to the challenges brought by aging development.


IERI Procedia ◽  
2014 ◽  
Vol 9 ◽  
pp. 176-184 ◽  
Author(s):  
Xuyin Yuan ◽  
Tianyuan Li ◽  
Ling Zhou ◽  
Xueqiang Zhao

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