scholarly journals A new information dimension of complex networks

2014 ◽  
Vol 378 (16-17) ◽  
pp. 1091-1094 ◽  
Author(s):  
Daijun Wei ◽  
Bo Wei ◽  
Yong Hu ◽  
Haixin Zhang ◽  
Yong Deng
Keyword(s):  
Complex Networks ◽  
Information Dimension ◽  
New Information

scholarly journals INFORMATION DIMENSION OF THE PEDAGOGICAL DISCUSSION

2017 ◽  
pp. 76-87
Author(s):  
Victor Vashkevych ◽  
Volodymyr Morozov
Keyword(s):  
Information And Communication Technologies ◽  
Computer Literacy ◽  
Culture Media ◽  
Communication Technologies ◽  
Information Support ◽  
Information Culture ◽  
Information Dimension ◽  
New Information ◽  
Information And Communication ◽  
Pedagogic Discourse

Structure of information support as a system of social and educational transformation of modern education in the context of information systems and technologies application in the context of globalized and information transformation of education was defined and grounded. Among the leading items in the information dimension of pedagogic discourse were considered the following: information support of education; computer literacy and information culture; media literacy; the system of pedagogical technologies of new information and communication technologies introduction; the contents, forms, methods and means of information presentation of pedagogical discourse object.

scholarly journals Tsallis information dimension of complex networks

2015 ◽  
Vol 419 ◽  
pp. 707-717 ◽  
Author(s):  
Qi Zhang ◽  
Chuanhai Luo ◽  
Meizhu Li ◽  
Yong Deng ◽  
Sankaran Mahadevan
Keyword(s):  
Complex Networks ◽  
Information Dimension

A box-covering Tsallis information dimension and non-extensive property of complex networks

2020 ◽  
Vol 132 ◽  
pp. 109590 ◽  
Author(s):  
Aldo Ramirez-Arellano ◽  
Luis Manuel Hernández-Simón ◽  
Juan Bory-Reyes
Keyword(s):  
Complex Networks ◽  
Information Dimension ◽  
Extensive Property

Outside-in box covering method and information dimension of Sierpinski networks

2020 ◽  
Vol 34 (17) ◽  
pp. 2050189
Author(s):  
Min Niu ◽  
Ruixia Li
Keyword(s):  
Complex Networks ◽  
Recurrence Formula ◽  
Self Similarity ◽  
Weighted Network ◽  
Information Dimension ◽  
Covering Method

Self-similarity is a significant property for complex networks. Box coverage method and dimension calculation are vital tools to study the characteristic of complex networks. In this paper, we propose an outside-in (OSI) box covering method for the Sierpinski networks, and it is attested that this coverage algorithm is superior to CBB algorithm. In addition, we deduce the optimal box recurrence formula of weighted and unweighted networks theoretically, and the result is the same as that of the algorithm value. We also obtain the information dimension of weighted network, which verifies the validity and feasibility of our method.

scholarly journals CONTROL CONTRIBUTION IDENTIFIES TOP DRIVER NODES IN COMPLEX NETWORKS

2019 ◽  
Vol 22 (07n08) ◽  
pp. 1950014 ◽  
Author(s):  
YAN ZHANG ◽  
ANTONIOS GARAS ◽  
FRANK SCHWEITZER
Keyword(s):  
Complex Networks ◽  
Real World ◽  
Optimization Method ◽  
Directed Network ◽  
Control Range ◽  
New Information ◽  
Random Samples ◽  
Text Ranking ◽  
The Impact ◽  
Synthetic Networks

We propose a new measure to quantify the impact of a node [Formula: see text] in controlling a directed network. This measure, called “control contribution” [Formula: see text], combines the probability for node [Formula: see text] to appear in a set of driver nodes and the probability for other nodes to be controlled by [Formula: see text]. To calculate [Formula: see text], we propose an optimization method based on random samples of minimum sets of drivers. Using real-world and synthetic networks, we find very broad distributions of [Formula: see text]. Ranking nodes according to their [Formula: see text] values allows us to identify the top driver nodes that can control most of the network. We show that this ranking is superior to rankings based on other control-based measures. We find that control contribution indeed contains new information that cannot be traced back to degree, control capacity or control range of a node.

A Multi-Information Propagation Model on Complex Networks

2011 ◽  
Vol 186 ◽  
pp. 302-306 ◽  
Author(s):  
Shu Jing Li ◽  
Feng Jing Shao ◽  
Ren Cheng Sun ◽  
Yi Sui
Keyword(s):  
Complex Networks ◽  
Propagation Rate ◽  
Propagation Model ◽  
Information Propagation ◽  
Influence Propagation ◽  
New Information

Propagation of two kinds of information on complex networks is studied. With assumption that new kind of information is generated after interacting between these two kinds of information, how rate of generating new information and rate of its recovery influence propagation are researched. Experiments show that when rates of propagation of these three kinds of information are same three kinds of information exist after system reaching stable under condition that the rate of generating new information is big. While rates of propagation of these three kinds of information differ a lot, information with big propagation rate exists after system reaching stable. The results could be extended into research of propagation of multi-information on complex networks.

Lattice Imaging of Twin, Lath and α/Martensite Boundaries in Duplex Low Carbon Steels

1977 ◽  
Vol 35 ◽  
pp. 118-119
Author(s):  
J. Y. Koo ◽  
G. Thomas
Keyword(s):  
High Resolution Electron Microscopy ◽  
Ferrite Matrix ◽  
Carbon Steels ◽  
Bright Field Image ◽  
Low Carbon ◽  
Lattice Imaging ◽  
Bright Field ◽  
Lattice Image ◽  
New Information ◽  
Resolution Electron

High resolution electron microscopy has been shown to give new information on defects(1) and phase transformations in solids (2,3). In a continuing program of lattice fringe imaging of alloys, we have applied this technique to the martensitic transformation in steels in order to characterize the atomic environments near twin, lath and αmartensite boundaries. This paper describes current progress in this program.Figures A and B show lattice image and conventional bright field image of the same area of a duplex Fe/2Si/0.1C steel described elsewhere(4). The microstructure consists of internally twinned martensite (M) embedded in a ferrite matrix (F). Use of the 2-beam tilted illumination technique incorporating a twin reflection produced {110} fringes across the microtwins.

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