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Institution

Southwest University

EducationChongqing, China
About: Southwest University is a education organization based out in Chongqing, China. It is known for research contribution in the topics: Population & Bombyx mori. The organization has 29772 authors who have published 27755 publications receiving 409441 citations. The organization is also known as: Southwest University in Chongqing & SWU.


Papers
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Journal ArticleDOI
TL;DR: Wang et al. as mentioned in this paper explored stakeholders' influencing power over barriers using two-mode social network analysis and found that the government and developers had the highest degree centrality, betweenness centrality and eigenvector centrality.

119 citations

Journal ArticleDOI
TL;DR: In the new method, each node’s structure feature can be quantified as a special kind of information and the value of relative entropy between each pair of nodes is used to measure nodes’ structure similarity in complex networks.
Abstract: Similarity of nodes is a basic structure quantification in complex networks. Lots of methods in research on complex networks are based on nodes’ similarity such as node’s classification, network’s community structure detection, network’s link prediction and so on. Therefore, how to measure nodes’ similarity is an important problem in complex networks. In this paper, a new method is proposed to measure nodes’ structure similarity based on relative entropy and each node’s local structure. In the new method, each node’s structure feature can be quantified as a special kind of information. The quantification of similarity between different pair of nodes can be replaced as the quantification of similarity in structural information. Then relative entropy is used to measure the difference between each pair of nodes’ structural information. At last the value of relative entropy between each pair of nodes is used to measure nodes’ structure similarity in complex networks. Comparing with existing methods the new method is more accuracy to measure nodes’ structure similarity.

119 citations

Journal ArticleDOI
15 Dec 2018-Energy
TL;DR: Wang et al. as mentioned in this paper presented a bottom-up model for measuring the CACCB values based on decomposing the extended Kaya identity via the Logarithmic Mean Divisia Index (LMDI) method.

119 citations

Journal ArticleDOI
TL;DR: A more pragmatic method is proposed that utilizes ''soft'' computing flexibility to generate BPAs from uncertain information and is compared to traditional Dempster-Shafer theory through numerical examples.
Abstract: Contaminant intrusion in a water distribution network is a complex but a commonly observed phenomenon, which depends on three elements - a pathway, a driving force and a contamination source. However, the data on these elements are generally incomplete, non-specific and uncertain. In an earlier work, Sadiq, Kleiner, and Rajani (2006) have successfully applied traditional Dempster-Shafer theory (DST) to estimate the ''risk'' of contaminant intrusion in a water distribution network based on limited uncertain information. However, the method used for generating basic probability assignment (BPA) was not very flexible, and did not handle and process uncertain information effectively. In this paper, a more pragmatic method is proposed that utilizes ''soft'' computing flexibility to generate BPAs from uncertain information. This paper compares these two methods through numerical examples, and demonstrates the efficiency and effectiveness of modified method.

118 citations

Journal ArticleDOI
TL;DR: In this article, a facile approach to constructing efficiently segregated conductive networks in the poly(lactic acid)/silver (PLA/Ag) nanocomposites were developed by coating Ag particles on PLA microfibers and then compression molding.

118 citations


Authors

Showing all 29978 results

NameH-indexPapersCitations
Frank B. Hu2501675253464
Hongjie Dai197570182579
Jing Wang1844046202769
Chao Zhang127311984711
Jianjun Liu112104071032
Miao Liu11199359811
Jun Yang107209055257
Eric Westhof9847234825
En-Tang Kang9776338498
Chang Ming Li9789642888
Wei Zhou93164039772
Li Zhang9291835648
Heinz Rennenberg8752726359
Tao Chen8682027714
Xun Wang8460632187
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202395
2022461
20213,537
20203,257
20192,923
20182,479