Epidemics

2017 ◽  
Author(s):  
Paul Charbonneau
Keyword(s):  
Scale Invariance ◽  
Small World ◽  
Complex Nature ◽  
Small World Network ◽  
Epidemic Spread ◽  
Fire Model ◽  
Random Walkers ◽  
Contagious Diseases ◽  
Spread Model ◽  
Forest Fire Model

This chapter examines the complex nature of the epidemic spread of contagious diseases. It first describes the model of epidemic spread constructed by adding random walks on a lattice to the forest-fire model before discussing the implementation of the epidemic “algorithm” using a minimal Python code. It then considers a representative simulation showing a time series of the number of infected and healthy random walkers, along with the behavior of the epidemic spread model and the dynamic self-organization of epidemic surges around a marginal infection rate of exactly unity. It also explores the scale invariance of a small-world network connecting twelve nodes. The chapter includes exercises and further computational explorations, along with a suggested list of materials for further reading.

scholarly journals IMPROVING THE INTEROPERABILITY OF DISASTER MODELS: A CASE STUDY OF PROPOSING FIREML FOR FOREST FIRE MODEL

2018 ◽  
Vol XLII-3 ◽  
pp. 673-677
Author(s):  
W. Jiang ◽  
F. Wang ◽  
Q. Meng ◽  
Z. Li ◽  
B. Liu ◽  
...  
Keyword(s):  
Disaster Management ◽  
Forest Fire ◽  
Fire Hazard ◽  
Fire Spread ◽  
Markup Language ◽  
Fire Model ◽  
Geography Markup Language ◽  
Spread Model ◽  
Forest Fire Model

This paper presents a new standardized data format named Fire Markup Language (FireML), extended by the Geography Markup Language (GML) of OGC, to elaborate upon the fire hazard model. The proposed FireML is able to standardize the input and output documents of a fire model for effectively communicating with different disaster management systems to ensure a good interoperability. To demonstrate the usage of FireML and testify its feasibility, an adopted forest fire spread model being compatible with FireML is described. And a 3DGIS disaster management system is developed to simulate the dynamic procedure of forest fire spread with the defined FireML documents. The proposed approach will enlighten ones who work on other disaster models' standardization work.

Analysis of Oncogene Protein Structure Using Small World Network Concept

2020 ◽  
Vol 15 (7) ◽  
pp. 732-740
Author(s):  
Neetu Kumari ◽  
Anshul Verma
Keyword(s):  
Amino Acids ◽  
Protein Structure ◽  
Degree Distribution ◽  
Protein Structures ◽  
Small World ◽  
Extreme Condition ◽  
Centrality Measures ◽  
Small World Network ◽  
Network Concept ◽  
Oncogene Protein

Background: The basic building block of a body is protein which is a complex system whose structure plays a key role in activation, catalysis, messaging and disease states. Therefore, careful investigation of protein structure is necessary for the diagnosis of diseases and for the drug designing. Protein structures are described at their different levels of complexity: primary (chain), secondary (helical), tertiary (3D), and quaternary structure. Analyzing complex 3D structure of protein is a difficult task but it can be analyzed as a network of interconnection between its component, where amino acids are considered as nodes and interconnection between them are edges. Objective: Many literature works have proven that the small world network concept provides many new opportunities to investigate network of biological systems. The objective of this paper is analyzing the protein structure using small world concept. Methods: Protein is analyzed using small world network concept, specifically where extreme condition is having a degree distribution which follows power law. For the correct verification of the proposed approach, dataset of the Oncogene protein structure is analyzed using Python programming. Results: Protein structure is plotted as network of amino acids (Residue Interaction Graph (RIG)) using distance matrix of nodes with given threshold, then various centrality measures (i.e., degree distribution, Degree-Betweenness correlation, and Betweenness-Closeness correlation) are calculated for 1323 nodes and graphs are plotted. Conclusion: Ultimately, it is concluded that there exist hubs with higher centrality degree but less in number, and they are expected to be robust toward harmful effects of mutations with new functions.

scholarly journals The structure of co-publications multilayer network

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Ghislain Romaric Meleu ◽  
Paulin Yonta Melatagia
Keyword(s):  
Power Law ◽  
Degree Distribution ◽  
Preferential Attachment ◽  
Small World ◽  
Generation Model ◽  
Small World Network ◽  
Power Law Distribution ◽  
Multilayer Networks ◽  
Multilayer Network ◽  
Scientific Papers

AbstractUsing the headers of scientific papers, we have built multilayer networks of entities involved in research namely: authors, laboratories, and institutions. We have analyzed some properties of such networks built from data extracted from the HAL archives and found that the network at each layer is a small-world network with power law distribution. In order to simulate such co-publication network, we propose a multilayer network generation model based on the formation of cliques at each layer and the affiliation of each new node to the higher layers. The clique is built from new and existing nodes selected using preferential attachment. We also show that, the degree distribution of generated layers follows a power law. From the simulations of our model, we show that the generated multilayer networks reproduce the studied properties of co-publication networks.

Top Museums on Instagram

2019 ◽  
Vol 3 (2) ◽  
pp. 18-42 ◽  
Author(s):  
Vasiliki G. Vrana ◽  
Dimitrios A. Kydros ◽  
Evangelos C. Kehris ◽  
Anastasios-Ioannis T. Theocharidis ◽  
George I. Kavavasilis
Keyword(s):  
Social Network ◽  
Network Analysis ◽  
Small World ◽  
Marketing Strategies ◽  
The Other ◽  
Small World Network ◽  
Scale Free ◽  
Centrality Metrics ◽  
Photo Sharing ◽  
Visualization Algorithms

Pictures speak louder than words. In this fast-moving world where people hardly have time to read anything, photo-sharing sites become more and more popular. Instagram is being used by millions of people and has created a “sharing ecosystem” that also encourages curation, expression, and produces feedback. Museums are moving quickly to integrate Instagram into their marketing strategies, provide information, engage with audience and connect to other museums Instagram accounts. Taking into consideration that people may not see museum accounts in the same way that the other museum accounts do, the article first describes accounts' performance of the top, most visited museums worldwide and next investigates their interconnection. The analysis uses techniques from social network analysis, including visualization algorithms and calculations of well-established metrics. The research reveals the most important modes of the network by calculating the appropriate centrality metrics and shows that the network formed by the museum Instagram accounts is a scale–free small world network.

A Small World Routing Protocol in Wireless Sensor Networks

2011 ◽  
Vol 474-476 ◽  
pp. 828-833
Author(s):  
Wen Jun Xu ◽  
Li Juan Sun ◽  
Jian Guo ◽  
Ru Chuan Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Routing Protocol ◽  
Data Transmission ◽  
Small World ◽  
Wireless Sensor ◽  
Small World Network ◽  
Average Delay ◽  
Network Diameter ◽  
Simulation Results

In order to reduce the average path length of the wireless sensor networks (WSNs) and save the energy, in this paper, the concept of the small world is introduced into the routing designs of WSNs. So a new small world routing protocol (SWRP) is proposed. By adding a few short cut links, which are confined to a fraction of the network diameter, we construct a small world network. Then the protocol finds paths through recurrent propagations of weak and strong links. The simulation results indicate that SWRP reduces the energy consumption effectively and the average delay of the data transmission, which leads to prolong the lifetime of both the nodes and the network.

Optimal Routing in a Small-World Network

2006 ◽  
Vol 21 (4) ◽  
pp. 476-481 ◽  
Author(s):  
Jian-Yang Zeng ◽  
Wen-Jing Hsu
Keyword(s):  
Small World ◽  
Optimal Routing ◽  
Small World Network
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