Propagation characteristic of adoption thresholds heterogeneity in double-layer networks with edge weight distribution

Information spreading on multiplex networks has been investigated widely. For multiplex networks, the relations of each layer possess different extents of intimacy, which can be described as weighted multiplex networks. Nevertheless, the effect of weighted multiplex network structures on information spreading has not been analyzed comprehensively. We herein propose an information spreading model on a weighted multiplex network. Then, we develop an edge-weight-based compartmental theory to describe the spreading dynamics. We discover that under any adoption threshold of two subnetworks, reducing weight distribution heterogeneity does not alter the growth pattern of the final adoption size versus information transmission probability while accelerating information spreading. For fixed weight distribution, the growth pattern changes with the heterogeneous of degree distribution. There is a critical initial seed size, below which no global information outbreak can occur. Extensive numerical simulations affirm that the theoretical predictions agree well with the numerical results.

Download Full-text

A New Complex Network Model with Multiweights and Its Synchronization Control

Advances in Mathematical Physics ◽

10.1155/2020/2872795 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Xin-lei An ◽

Li Zhang

Keyword(s):

Complex Network ◽

Network Model ◽

Weight Distribution ◽

Control Strategies ◽

Network Models ◽

Lyapunov Stability Theory ◽

Practical Significance ◽

Node Degree ◽

Edge Weight ◽

Node Weight

Based on the weighted complex network model, this paper establishes a multiweight complex network model, which possesses several different weights on the one edge. According to the method of network split, the complex network with multiweights is split into several different complex networks with single weight. Some new static characteristics, such as node weight, node degree, node weight strength, node weight distribution, edge weight distribution, and diversity of weight distribution are defined. Then, by using Lyapunov stability theory, the adaptive feedback synchronization controller is designed, and the complete synchronization of the new complex network model is investigated. Two numerical examples of a triweight network model with the same and diverse structure are given to demonstrate the effectiveness of the control strategies. The synchronization design can achieve good results in the same and diverse structure network models with multiweights, which enrich complex network and control theory, so has certain theoretical and practical significance.

Download Full-text

Quantification of Graph Complexity Based on the Edge Weight Distribution Balance: Application to Brain Networks

International Journal of Neural Systems ◽

10.1142/s0129065717500320 ◽

2017 ◽

Vol 28 (01) ◽

pp. 1750032 ◽

Cited By ~ 18

Author(s):

Javier Gomez-Pilar ◽

Jesús Poza ◽

Alejandro Bachiller ◽

Carlos Gómez ◽

Pablo Núñez ◽

...

Keyword(s):

Cognitive Processing ◽

Weight Distribution ◽

Brain Network ◽

Node Degree ◽

Edge Weight ◽

Real Dataset ◽

The Real ◽

Graph Size ◽

Eeg Recordings ◽

The Brain

The aim of this study was to introduce a novel global measure of graph complexity: Shannon graph complexity (SGC). This measure was specifically developed for weighted graphs, but it can also be applied to binary graphs. The proposed complexity measure was designed to capture the interplay between two properties of a system: the ‘information’ (calculated by means of Shannon entropy) and the ‘order’ of the system (estimated by means of a disequilibrium measure). SGC is based on the concept that complex graphs should maintain an equilibrium between the aforementioned two properties, which can be measured by means of the edge weight distribution. In this study, SGC was assessed using four synthetic graph datasets and a real dataset, formed by electroencephalographic (EEG) recordings from controls and schizophrenia patients. SGC was compared with graph density (GD), a classical measure used to evaluate graph complexity. Our results showed that SGC is invariant with respect to GD and independent of node degree distribution. Furthermore, its variation with graph size [Formula: see text] is close to zero for [Formula: see text]. Results from the real dataset showed an increment in the weight distribution balance during the cognitive processing for both controls and schizophrenia patients, although these changes are more relevant for controls. Our findings revealed that SGC does not need a comparison with null-hypothesis networks constructed by a surrogate process. In addition, SGC results on the real dataset suggest that schizophrenia is associated with a deficit in the brain dynamic reorganization related to secondary pathways of the brain network.

Download Full-text

THE GENERAL EVOLVING MODEL FOR ENERGY SUPPLY-DEMAND NETWORK WITH LOCAL-WORLD

International Journal of Modern Physics C ◽

10.1142/s0129183113500708 ◽

2013 ◽

Vol 24 (10) ◽

pp. 1350070 ◽

Cited By ~ 3

Author(s):

MEI SUN ◽

DUN HAN ◽

DANDAN LI ◽

CUICUI FANG

Keyword(s):

Weight Distribution ◽

Energy Supply ◽

Power Plants ◽

Mean Field Theory ◽

Mean Field ◽

Edge Weight ◽

Bipartite Network ◽

Scaling Exponent ◽

Node Weight ◽

Evolving Model

In this paper, two general bipartite network evolving models for energy supply-demand network with local-world are proposed. The node weight distribution, the "shifting coefficient" and the scaling exponent of two different kinds of nodes are presented by the mean-field theory. The numerical results of the node weight distribution and the edge weight distribution are also investigated. The production's shifted power law (SPL) distribution of coal enterprises and the installed capacity's distribution of power plants in the US are obtained from the empirical analysis. Numerical simulations and empirical results are given to verify the theoretical results.

Download Full-text

Cracking at the fold in double layer coated paper: the influence of latex and starch composition

TAPPI Journal ◽

10.32964/tj18.2.93 ◽

2019 ◽

Vol 18 (2) ◽

pp. 93-99

Author(s):

SEYYED MOHAMMAD HASHEMI NAJAFI ◽

DOUGLAS BOUSFIELD, ◽

MEHDI TAJVIDI

Keyword(s):

Mechanical Properties ◽

Double Layer ◽

Starch Content ◽

Single Layer ◽

Double Layers ◽

Coated Paper ◽

Coated Papers ◽

Coating Layers ◽

Scanned Images ◽

Packaging Paper

Cracking at the fold of publication and packaging paper grades is a serious problem that can lead to rejection of product. Recent work has revealed some basic mechanisms and the influence of various parameters on the extent of crack area, but no studies are reported using coating layers with known mechanical properties, especially for double-coated systems. In this study, coating layers with different and known mechanical properties were used to characterize crack formation during folding. The coating formulations were applied on two different basis weight papers, and the coated papers were folded. The binder systems in these formulations were different combinations of a styrene-butadiene latex and mixtures of latex and starch for two different pigment volume concentrations (PVC). Both types of papers were coated with single and double layers. The folded area was scanned with a high-resolution scanner while the samples were kept at their folded angle. The scanned images were analyzed within a constant area. The crack areas were reported for different types of papers, binder system and PVC values. As PVC, starch content, and paper basis weight increased, the crack area increased. Double layer coated papers with high PVC and high starch content at the top layer had more cracks in comparison with a single layer coated paper, but when the PVC of the top layer was low, cracking area decreased. No measurable cracking was observed when the top layer was formulated with a 100% latex layer.

Download Full-text

A Survey on Crypto-Steganographic Schemes and A Use Case in Healthcare System

Journal of Engineering Technology and Applied Physics ◽

10.33093/jetap.2019.1.2.6 ◽

2019 ◽

Vol 1 (2) ◽

pp. 25-33

Author(s):

Mei Ling Phang ◽

Swee Huay Heng

Keyword(s):

Social Networking ◽

Information Sharing ◽

Healthcare System ◽

Double Layer ◽

21St Century ◽

Electronic Devices ◽

Third Party ◽

Use Case ◽

Comparison Analysis ◽

Information Assets

Information sharing has become prevalent due to the expansion of social networking in this 21st century. However, electronic devices are vulnerable to various kinds of attacks. Information might be disclosed, modified and accessed by an unauthorised third party which consequently leads to the breach of confidentiality, integrity and availability of the information. Therefore, it is of utmost importance to employ the technology of cryptography and steganography to protect information assets. Cryptography and steganography have weaknesses when they are working alone. Therefore, crypto-steganography, the combination of cryptography and steganography are introduced to overcome the weaknesses in order to provide a double layer of security and protection. This paper provides a general overview of steganography and cryptography as well as a comparison analysis of different crypto-steganographic schemes. A secure crypto-steganographic system for healthcare is then developed with the implementation and integration of the secure crypto-steganographic scheme proposed by Juneja and Sandhu. This healthcare system enables users to store and deliver message in a more secure way while achieving the main goals of both cryptography and steganography.

Download Full-text