scholarly journals Hunting for vital nodes in complex networks using local information

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhihao Dong ◽  
Yuanzhu Chen ◽  
Terrence S. Tricco ◽  
Cheng Li ◽  
Ting Hu
Keyword(s):  
Complex Networks ◽  
Real World ◽  
Structure And Function ◽  
Local Information ◽  
Epidemic Threshold ◽  
Global Knowledge ◽  
The Real ◽  
And Function ◽  
Time Critical ◽  
Taking Action

AbstractComplex networks in the real world are often with heterogeneous degree distributions. The structure and function of nodes can vary significantly, with vital nodes playing a crucial role in information spread and other spreading phenomena. Identifying and taking action on vital nodes enables change to the network’s structure and function more efficiently. Previous work either redefines metrics used to measure the nodes’ importance or focuses on developing algorithms to efficiently find vital nodes. These approaches typically rely on global knowledge of the network and assume that the structure of the network does not change over time, both of which are difficult to achieve in the real world. In this paper, we propose a localized strategy that can find vital nodes without global knowledge of the network. Our joint nomination (JN) strategy selects a random set of nodes along with a set of nodes connected to those nodes, and together they nominate the vital node set. Experiments are conducted on 12 network datasets that include synthetic and real-world networks, and undirected and directed networks. Results show that average degree of the identified node set is about 3–8 times higher than that of the full node set, and higher-degree nodes take larger proportions in the degree distribution of the identified vital node set. Removal of vital nodes increases the average shortest path length by 20–70% over the original network, or about 8–15% longer than the other decentralized strategies. Immunization based on JN is more efficient than other strategies, consuming around 12–40% less immunization resources to raise the epidemic threshold to $$\tau \sim 0.1$$ τ ∼ 0.1 . Susceptible-infected-recovered simulations on networks with 30% vital nodes removed using JN delays the arrival time of infection peak significantly and reduce the total infection scale to 15%. The proposed strategy can effectively identify vital nodes using only local information and is feasible to implement in the real world to cope with time-critical scenarios such as the sudden outbreak of COVID-19.

scholarly journals Hunting for Influential Nodes in Complex Networks Using Local Information

2021 ◽  
Author(s):  
Zhihao Dong ◽  
Yuanzhu Chen ◽  
Terrence S. Tricco ◽  
Cheng Li ◽  
Ting Hu
Keyword(s):  
Complex Networks ◽  
Real World ◽  
Structure And Function ◽  
Epidemic Threshold ◽  
Global Knowledge ◽  
The Real ◽  
Influential Nodes ◽  
Influential Node ◽  
And Function ◽  
High Degree

Abstract Complex networks in the real world are often with heterogeneous degree distributions. The structure and function of nodes can vary significantly, with influential nodes playing a crucial role in information spread and other spreading phenomena. Identifying high-degree nodes enables change to the network’s structure and function. Previous work either redefines metrics used to measure the nodes’ importance or focus on developing algorithms to efficiently find influential nodes. These approaches typically rely on global knowledge of the network and assume that the structure of the network does not change over time, both of which are difficult to achieve in the real world. In this paper, we propose a decentralized strategy that can find influential nodes without global knowledge of the network. Our Joint Nomination (JN) strategy selects a random set of nodes along with a set of nodes connected to those nodes, and together they nominate the influential node set. Experiments are conducted on 12 network datasets, including both synthetic and real-world networks, both undirected and directed networks. Results show that average degree of the identified node set is about 3–8 times higher than that of the full node set, and the degree distribution skews toward higher-degree nodes. Removal of influential nodes increase the average shortest path length by 20–70% over the original network, or about 8–15% longer than the other decentralized strategies. Immunization based on JN is more efficient than other strategies, consuming around 12–40% less immunization resources to raise the epidemic threshold to 𝜏 ~ 0:1. Susceptible-Infected-Recovered (SIR) simulations on networks with 30% influential nodes removed using JN delays the arrival time of infection peak significantly and reduce the total infection scale to 15%.

scholarly journals Designing and coding with BBC micro:bit to solve a real-world task – a challenging movement between contexts

2021 ◽  
Author(s):  
A-M. Cederqvist
Keyword(s):  
Design Process ◽  
Real World ◽  
Structure And Function ◽  
Educational Content ◽  
Dual Nature ◽  
The Real ◽  
And Function ◽  
Point Of Departure ◽  
Critical Aspects

AbstractDesigning programmed technological solutions (PTS) with programming materials has become a way to contextualise educational content related to PTS and programming. However, studies show that pupils have difficulties conceptualising central phenomena involved in the process, which affects their ability to design PTS. In order to understand these difficulties, this study investigates pupils’ ways of experiencing the process of solving a real-world task with a programming material. The study takes its point of departure from a previous study that identified two central phenomena, the dual nature (structure and function) of PTS and the BBC micro:bit material, when pupils, aged 10 and 14, were designing a burglar alarm with the BBC micro:bit. The data was revisited with the aim of analysing pupils’ sequential discernment of critical aspects of the phenomena (i.e. aspects necessary to discern in order to understand phenomena), and how this affects how the design process unfolds. The results show that the movement from the real-world context toward the BBC micro:bit context is challenging. Pupils need to be able to connect conditions in the real-world context both to aspects of the dual nature of their PTS, and to aspects of the BBC micro:bit material that represent the dual nature. This suggests the importance of appreciating the BBC micro:bit context and the real-world context in relation to the dual nature of PTS, and of addressing the sequential stages of the process in which aspects of phenomena and their interrelations are emphasised, to help pupils see the PTS in the changing contexts.

scholarly journals Feedback through graph motifs relates structure and function in complex networks

2018 ◽  
Vol 98 (6) ◽  
Author(s):  
Yu Hu ◽  
Steven L. Brunton ◽  
Nicholas Cain ◽  
Stefan Mihalas ◽  
J. Nathan Kutz ◽  
...  
Keyword(s):  
Complex Networks ◽  
Structure And Function ◽  
And Function

scholarly journals Supervisi Pendidikan

2019 ◽  
Author(s):  
Putriastuti
Keyword(s):  
Learning Process ◽  
Employee Development ◽  
Structure And Function ◽  
Real Situation ◽  
The Real ◽  
And Function

As the teris curriculum develops, these developments often lead to changes in the structure and function of the curriculum. The implementation of the curriculum requires continual adjustments to the real situation on the ground. For this reason, teachers must always try to develop their creativity so that educational efforts based on the curriculum can be carried out properly. Employee development is always a continual effort in an organization. For this reason, it is necessary to supervise education, to improve the performance of teachers and employees in the learning process.

scholarly journals Reconstructing ribosomal genes from large scale total RNA meta-transcriptomic data

2020 ◽  
Vol 36 (11) ◽  
pp. 3365-3371
Author(s):  
Yaxin Xue ◽  
Anders Lanzén ◽  
Inge Jonassen
Keyword(s):  
Microbial Communities ◽  
Real World ◽  
Structure And Function ◽  
Rrna Genes ◽  
Supplementary Information ◽  
Metagenomic Data ◽  
Total Rna ◽  
Transcriptomic Data ◽  
And Function ◽  
Complex Datasets

Abstract Motivation Technological advances in meta-transcriptomics have enabled a deeper understanding of the structure and function of microbial communities. ‘Total RNA’ meta-transcriptomics, sequencing of total reverse transcribed RNA, provides a unique opportunity to investigate both the structure and function of active microbial communities from all three domains of life simultaneously. A major step of this approach is the reconstruction of full-length taxonomic marker genes such as the small subunit ribosomal RNA. However, current tools for this purpose are mainly targeted towards analysis of amplicon and metagenomic data and thus lack the ability to handle the massive and complex datasets typically resulting from total RNA experiments. Results In this work, we introduce MetaRib, a new tool for reconstructing ribosomal gene sequences from total RNA meta-transcriptomic data. MetaRib is based on the popular rRNA assembly program EMIRGE, together with several improvements. We address the challenge posed by large complex datasets by integrating sub-assembly, dereplication and mapping in an iterative approach, with additional post-processing steps. We applied the method to both simulated and real-world datasets. Our results show that MetaRib can deal with larger datasets and recover more rRNA genes, which achieve around 60 times speedup and higher F1 score compared to EMIRGE in simulated datasets. In the real-world dataset, it shows similar trends but recovers more contigs compared with a previous analysis based on random sub-sampling, while enabling the comparison of individual contig abundances across samples for the first time. Availability and implementation The source code of MetaRib is freely available at https://github.com/yxxue/MetaRib. Contact [email protected] or [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

Aspects of professional ethics in the real world

2017 ◽  
Vol 15 (4) ◽  
pp. 362-365
Author(s):  
Declan Brady
Keyword(s):  
Real World ◽  
Professional Ethics ◽  
Design Methodology ◽  
Content Type ◽  
The Real ◽  
Ethics Framework ◽  
Taking Action ◽  
Practical Implications ◽  
Practical Sense

Purpose This paper aims to describe a perspective from the Council of European Professional Informatics Societies (CEPIS) on the role of ethics in IT professionalism, and what that means in a practical sense for IT practitioners. Design/methodology/approach The paper develops ideas generated in a series of micro-conferences hosted by CEPIS on the topic of ethics, in the context of establishing a professional ethics framework as part of CEPIS’ work in support of IT professionalism. Findings Professional ethics is the weakest of the four professional pillars, and development of supports and resources is required. CEPIS is taking action in this areas. Practical implications Without a framework, and without IT Practitioners themselves taking a coordinated action, there risks a fragmentation of responses to ethical questions. Originality/value This paper describes the view of the CEPIS on the need for, and role of, professional ethics, and how that might be supported.

scholarly journals Modularity based Community Detection in Social Networks

2020 ◽  
Vol 9 (3) ◽  
pp. 564-569
Keyword(s):  
Social Networks ◽  
Complex Networks ◽  
Community Detection ◽  
Real World ◽  
Research Community ◽  
Incorrect Result ◽  
The Real

The community detection is an interesting and highly focused area in the analysis of complex networks (CNA). It identifies closely connected clusters of nodes. In recent years, several approaches have been proposed for community detection and validation of the result. Community detection approaches that use modularity as a measure have given much weight-age by the research community. Various modularity based community detection approaches are given for different domains. The network in the real-world may be weighted, heterogeneous or dynamic. So, it is inappropriate to apply the same algorithm for all types of networks because it may generate incorrect result. Here, literature in the area of community detection and the result evaluation has been extended with an aim to identify various shortcomings. We think that the contribution of facts given in this paper can be very useful for further research.

scholarly journals A tensor-based framework for studying eigenvector multicentrality in multilayer networks

2019 ◽  
Vol 116 (31) ◽  
pp. 15407-15413 ◽  
Author(s):  
Mincheng Wu ◽  
Shibo He ◽  
Yongtao Zhang ◽  
Jiming Chen ◽  
Youxian Sun ◽  
...  
Keyword(s):  
Complex Networks ◽  
Prior Knowledge ◽  
General Framework ◽  
Single Layer ◽  
Structure And Function ◽  
Centrality Measures ◽  
Multilayer Networks ◽  
And Function ◽  
The Impact ◽  
Insight Into

Centrality is widely recognized as one of the most critical measures to provide insight into the structure and function of complex networks. While various centrality measures have been proposed for single-layer networks, a general framework for studying centrality in multilayer networks (i.e., multicentrality) is still lacking. In this study, a tensor-based framework is introduced to study eigenvector multicentrality, which enables the quantification of the impact of interlayer influence on multicentrality, providing a systematic way to describe how multicentrality propagates across different layers. This framework can leverage prior knowledge about the interplay among layers to better characterize multicentrality for varying scenarios. Two interesting cases are presented to illustrate how to model multilayer influence by choosing appropriate functions of interlayer influence and design algorithms to calculate eigenvector multicentrality. This framework is applied to analyze several empirical multilayer networks, and the results corroborate that it can quantify the influence among layers and multicentrality of nodes effectively.

WEIGHTED ACCELERATED GROWTH MODEL OF COMPLEX NETWORKS

2007 ◽  
Vol 21 (23n24) ◽  
pp. 4064-4066
Author(s):  
C. C. LEUNG ◽  
H. F. CHAU
Keyword(s):  
Complex Networks ◽  
Structure Formation ◽  
Growth Model ◽  
Real World ◽  
Organizational Structures ◽  
Weighted Network ◽  
The Real ◽  
Accelerated Growth

We introduce and study a toy model which mimics the structure formation of a typical weighted network in the real world. In particular, the organizational structures of our networks are found to be consistent with real-world networks.

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