scholarly journals An Eigenvector Centrality for Multiplex Networks with Data

Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 763 ◽  
Author(s):  
Francisco Pedroche ◽  
Leandro Tortosa ◽  
José F. Vicent
Keyword(s):  
Complex Systems ◽  
Network Theory ◽  
Essential Feature ◽  
Eigenvector Centrality ◽  
Centrality Measure ◽  
Multiplex Networks ◽  
Primitive Matrix ◽  
The Core ◽  
Proposed Model ◽  
Node Classification

Networks are useful to describe the structure of many complex systems. Often, understanding these systems implies the analysis of multiple interconnected networks simultaneously, since the system may be modelled by more than one type of interaction. Multiplex networks are structures capable of describing networks in which the same nodes have different links. Characterizing the centrality of nodes in multiplex networks is a fundamental task in network theory. In this paper, we design and discuss a centrality measure for multiplex networks with data, extending the concept of eigenvector centrality. The essential feature that distinguishes this measure is that it calculates the centrality in multiplex networks where the layers show different relationships between nodes and where each layer has a dataset associated with the nodes. The proposed model is based on an eigenvector centrality for networks with data, which is adapted according to the idea behind the two-layer approach PageRank. The core of the centrality proposed is the construction of an irreducible, non-negative and primitive matrix, whose dominant eigenpair provides a node classification. Several examples show the characteristics and possibilities of the new centrality illustrating some applications.

scholarly journals Work Motivation in Temporary Organizations: Establishing Theoretical Corpus

2018 ◽  
Vol 5 (3) ◽  
pp. 29
Author(s):  
Ravikiran Dwivedula ◽  
Christophe Bredillet ◽  
Ralf Müller
Keyword(s):  
Network Theory ◽  
Work Motivation ◽  
Actor Network Theory ◽  
Systematic Investigation ◽  
Job Design ◽  
Project Work ◽  
Moderation Effect ◽  
Temporary Organizations ◽  
Proposed Model ◽  
Design Theories

The purpose of this article is to organize this literature, which will facilitate a systematic investigation of work motivation in temporary organizations. First, we highlight the limitations of current theoretical lenses of work motivation specific to temporary organizations. Second, we synthesize three major theories- Event-Systems (E-S) theory, Socio-Technical Systems (STS) Perspective/Job Design, and Actor-Network Theory (ANT) to establish the theoretical corpus for our proposed model of work motivation. Our model conceptualizes project work characteristics as an ‘Event’ capable of producing an ‘event outcome’ which is work motivation. This is explained using E-S and STS/ Job Design theories. Propositions are introduced. The moderation effect is explained using ANT. Third, we present the academic contribution of our proposed model.

scholarly journals The South African Banking Director Network: An Investigation Into Interlocking Directorships Using Social Network Analysis (SNA)

2014 ◽  
Vol 13 (5) ◽  
pp. 963
Author(s):  
Burgert A. Senekal ◽  
Karlien Stemmet
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Complex Systems ◽  
South African ◽  
Complex Network ◽  
Network Theory ◽  
Complex Network Theory ◽  
International Trends ◽  
Director Network

The theory of complex systems has gained significant ground in recent years, and with it, complex network theory has become an essential approach to complex systems. This study follows international trends in examining the interlocking South African bank director network using social network analysis (SNA), which is shown to be a highly connected social network that has ties to many South African industries, including healthcare, mining, and education. The most highly connected directors and companies are identified, along with those that are most central to the network, and those that serve important bridging functions in facilitating network coherence. As this study is exploratory, numerous suggestions are also made for further research.

scholarly journals Integration Development of Urban Agglomeration in Central Liaoning, China, by Trajectory Gravity Model

2021 ◽  
Vol 10 (10) ◽  
pp. 698
Author(s):  
Ruren Li ◽  
Shoujia Li ◽  
Zhiwei Xie
Keyword(s):  
Gravity Model ◽  
Gravitational Force ◽  
Main Idea ◽  
Correlation Coefficients ◽  
Urban Agglomeration ◽  
Economic Research ◽  
The Core ◽  
Proposed Model ◽  
Two Indices ◽  
Spatial Trajectory

Integration development of urban agglomeration is important for regional economic research and management. In this paper, a method was proposed to study the integration development of urban agglomeration by trajectory gravity model. It can analyze the gravitational strength of the core city to other cities and characterize the spatial trajectory of its gravitational direction, expansion, etc. quantitatively. The main idea is to do the fitting analysis between the urban axes and the gravitational lines. The correlation coefficients retrieved from the fitting analysis can reflect the correlation of two indices. For the different cities in the same year, a higher value means a stronger relationship. There is a clear gravitational force between the cities when the value above 0.75. For the most cities in different years, the gravitational force between the core city with itself is increasing by years. At the same time, the direction of growth of the urban axes tends to increase in the direction of the gravitational force between cities. There is a clear tendency for the trajectories of the cities to move closer together. The proposed model was applied to the integration development of China Liaoning central urban agglomeration from 2008 to 2016. The results show that cities are constantly attracted to each other through urban gravity.

scholarly journals Model of the Process of Conducting Computer Attacks Using Special Information Influences

2021 ◽  
pp. 12-20
Author(s):  
Sergey Kondakov ◽  
◽  
Ilya Rud ◽  
Keyword(s):  
Information Systems ◽  
Comparative Analysis ◽  
Complex Systems ◽  
Research Method ◽  
System Analysis ◽  
Level Of Abstraction ◽  
Proposed Model ◽  
Analysis And Synthesis ◽  
Computer Attacks ◽  
Special Information

Purpose of work: development of a model of the process of conducting a computer attack. Research method: theory of complex systems, comparative analysis within the framework of system analysis and synthesis. Result: it is shown that the application of the proposed model of the process of conducting computer attacks allows you to fully describe the process, taking into account its inherent features and characteristics. The use in the model of information from the MITRE ATTACK database of Mitre, which contains a description of the tactics, techniques and methods used by cybercriminals, allows you to reduce the level of abstraction and describe specific scenarios for conducting complex targeted computer attacks with the maximum approximation to practice. The developed model is supposed to be used to form scenarios of computer attacks when assessing the security of information systems.

Self-Organization in Multiplex Networks

2018 ◽  
pp. 148-158
Author(s):  
Nikos E. Kouvaris ◽  
Albert Díaz-Guilera
Keyword(s):  
Complex Systems ◽  
Network Structure ◽  
Reaction Diffusion ◽  
Reaction Diffusion Equations ◽  
Diffusion Equations ◽  
Self Organization ◽  
Multiplex Networks ◽  
The Way

The chapter “Self-Organization in Multiplex Networks” discusses the use of multiplex networks in studying complex systems and synchronization. An important question in the research of complex systems concerns the way the network structure shapes the hosted dynamics and leads to a plethora of self-organization phenomena. Complex systems consist of nodes having some intrinsic dynamics, usually nonlinear, and are connected through the links of the network. Such systems can be studied by means of discrete reaction–diffusion equations; reaction terms account for the dynamics in the nodes, whereas diffusion terms describe the coupling between them. This chapter discusses how multiplex networks are suitable for studying such systems by providing two illustrative examples of self-organization phenomena occurring in them.

scholarly journals Modelling the Characteristics of Ring-Shaped Magnetoelastic Force Sensor in Mohri’s Configuration

Sensors ◽  
2020 ◽  
Vol 20 (1) ◽  
pp. 266 ◽  
Author(s):  
Anna Ostaszewska-Liżewska ◽  
Roman Szewczyk ◽  
Peter Raback ◽  
Mika Malinen
Keyword(s):  
Experimental Data ◽  
High Sensitivity ◽  
Force Sensor ◽  
Inhomogeneous Distribution ◽  
The Finite Element Method ◽  
The Core ◽  
Magnetoelastic Effect ◽  
Proposed Model ◽  
Distribution Of Stresses ◽  
Good Agreement

Magnetoelastic force sensors exhibit high sensitivity and robustness. One commonly used configuration of force sensor with a ring-shaped core was presented by Mohri at al. In this configuration force is applied in the direction of a diameter of the core. However, due to inhomogeneous distribution of stresses, model of such sensor has not been presented yet. This paper is filling the gap presenting a new method of modelling the magnetoelastic effect, which is especially suitable for the finite element method. The presented implementation of proposed model is in good agreement with experimental data and creates new possibilities of modelling other devices utilizing magnetoelastic effect.

Innovativeness in the context of technological and market dynamism

2017 ◽  
Vol 30 (4) ◽  
pp. 548-568 ◽  
Author(s):  
Job Rodrigo-Alarcón ◽  
Pedro Manuel García-Villaverde ◽  
Gloria Parra-Requena ◽  
María José Ruiz-Ortega
Keyword(s):  
Network Theory ◽  
Interactive Effect ◽  
Interactive Effects ◽  
Network Density ◽  
Critical Aspect ◽  
Content Type ◽  
Proposed Model ◽  
The Relationship ◽  
Positive Effect

Purpose Innovativeness is a critical aspect for the survival and success of the company in the long term. The purpose of this paper is to study how the density of the network in which the company is immersed influences the relationship between environment, dynamism and innovativeness. More specifically, the authors analyse whether the network density acts in a heterogeneous way, worsening or improving the effects of technological and market dynamism on innovativeness, respectively. Design/methodology/approach The empirical study was conducted on a sample of 292 companies in the agri-food industry in Spain. In order to test the proposed model, the authors used partial least squares. Findings The results show that technological dynamism has a positive effect on the generation and development of a firm’s innovativeness. However, market dynamism does not influence innovativeness. The authors also observe that the interactive effects between network density and dynamism are significant, but in a divergent way. Whereas the interactive effect between density and technological dynamism is negative, the interaction between density and market dynamism is positive. Originality/value The main contribution of the study is to show how the level of network density alters the effect of technological and market dynamism on innovativeness. The authors highlight the relevance of network theory to explain the contextual background to innovativeness. The authors also stress the importance of differentiating between the market and technological components of dynamism to further elucidate their effects.

Multi-Radius Density Clustering Algorithm Based on Outlier Factor

2014 ◽  
Vol 472 ◽  
pp. 427-431
Author(s):  
Zong Lin Ye ◽  
Hui Cao ◽  
Li Xin Jia ◽  
Yan Bin Zhang ◽  
Gang Quan Si
Keyword(s):  
Clustering Algorithm ◽  
Spatial Clustering ◽  
Similar Process ◽  
The Core ◽  
Dbscan Algorithm ◽  
Proposed Model ◽  
Density Clustering ◽  
Relationship Of ◽  
Core Points ◽  
The Relationship

This paper proposes a novel multi-radius density clustering algorithm based on outlier factor. The algorithm first calculates the density-similar-neighbor-based outlier factor (DSNOF) for each point in the dataset according to the relationship of the density of the point and its neighbors, and then treats the point whose DSNOF is smaller than 1 as a core point. Second, the core points are used for clustering by the similar process of the density based spatial clustering application with noise (DBSCAN) to get some sub-clusters. Third, the proposed algorithm merges the obtained sub-clusters into some clusters. Finally, the points whose DSNOF are larger than 1 are assigned into these clusters. Experiments are performed on some real datasets of the UCI Machine Learning Repository and the experiments results verify that the effectiveness of the proposed model is higher than the DBSCAN algorithm and k-means algorithm and would not be affected by the parameter greatly.

Motif discovery algorithms in static and temporal networks: A survey

2020 ◽  
Vol 8 (4) ◽  
Author(s):  
Ali Jazayeri ◽  
Christopher C Yang
Keyword(s):  
Complex Systems ◽  
Motif Discovery ◽  
Temporal Networks ◽  
Frequent Subgraph Mining ◽  
The Core ◽  
The Past ◽  
Frequent Subgraph ◽  
Social Media Platforms ◽  
Discovery Algorithms ◽  
Big Data Technology

Abstract Motifs are the fundamental components of complex systems. The topological structure of networks representing complex systems and the frequency and distribution of motifs in these networks are intertwined. The complexities associated with graph and subgraph isomorphism problems, as the core of frequent subgraph mining, directly impact the performance of motif discovery algorithms. Researchers have adopted different strategies for candidate generation and enumeration and frequency computation to cope with these complexities. Besides, in the past few years, there has been an increasing interest in the analysis and mining of temporal networks. In contrast to their static counterparts, these networks change over time in the form of insertion, deletion or substitution of edges or vertices or their attributes. In this article, we provide a survey of motif discovery algorithms proposed in the literature for mining static and temporal networks and review the corresponding algorithms based on their adopted strategies for candidate generation and frequency computation. As we witness the generation of a large amount of network data in social media platforms, bioinformatics applications and communication and transportation networks and the advance in distributed computing and big data technology, we also conduct a survey on the algorithms proposed to resolve the CPU-bound and I/O bound problems in mining static and temporal networks.

Sign in / Sign up

Export Citation Format

Share Document