scholarly journals Robustez de las redes urbanas densamente pobladas en relación con la propagación del tráfico / Robustness of densely populated urban networks in relation to the spread of traffic

Author(s):  
Hugo Alatrista-Salas ◽  
Miguel Núñez del Prado Cortez ◽  
Manuel Guillermo Rodríguez-López

ABSTRACTAnalyzing, the morphology, robustness or vulnerability of densely populated cities is a challenge for contemporary researchers. Studies on the resilience of urban infrastructures are given by the presence of recurrent adverse events or sporadic disasters. These events force the interruption of intersections or sections of streets momentarily or permanently. For measurements we use network graph properties and computational algorithms, simulating random and targeted attacks. Finally, in the results we identify the location of critical places that contain intersections and sections of street with greater centrality of intermediation and lower average of proximity.RESUMENAnalizar, la morfología, robustez o vulnerabilidad de ciudades densamente pobladas es un desafío para los investigadores contemporáneos. Los estudios sobre la resiliencia de infraestructuras urbanas se dan por la presencia de eventos adversos recurrentes o desastres esporádicos. Estos acontecimientos, obligan a interrumpir intersecciones o tramos de calles momentánea o permanentemente. Para las mediciones usamos las propiedades de grafos de redes y algoritmos computacionales, simulando ataques aleatorios y dirigidos. Finalmente, en los resultados identificamos la ubicación de lugares críticos que contienen intersecciones y secciones de calle con mayor centralidad de intermediación y menor promedio de cercanía.

2020 ◽  
Vol 13 (2) ◽  
pp. 5
Author(s):  
Akshay Tripathi ◽  
Ankush Kumar Gaur ◽  
Sweta Sri

Social graph describes the graphical model of users and how they are related to each other online. Social network consists of a set of nodes (sometimes referred to as actors or vertices in graph theory) connected via some type of relations which are known as edges. Actors are the smallest unit of the network. It can be Persons, Organizations, and Families etc. Relations can be of many types such as directed, undirected, and weighted. Social network analysis consists of two phases. One is data collection phase and another is analysis phase. Data is collected with the help of surveys, Social sites such as face book, LinkedIn. We first input the user information in form of two dimensional matrices. Then we construct a graph based on the relationships among users from adjacency matrix. We can draw a directed graph or a simple graph based on the user input information from adjacency matrix. After analyzing the graph properties based on degree of node, centrality and other parameters we will give effective solution. There are many applications of analyzing social network for example examine a network of farm animals, to analyze how disease spread from one cow to another, discover emergent  communities of interest among faculty at various universities, Some public sector uses include development of leader engagement strategies, analysis of individual and group engagement and media use, and community-based problem solving etc. Social network analysis is used widely in the social and behavioral sciences, as well as in economics, marketing, and industrial engineering. The social network perspective focuses on the relationships among social entities and is an important addition to standard social and behavioral research which is primarily concerned with attributes of the social units.


2010 ◽  
Vol 44 (12) ◽  
pp. 16
Author(s):  
STEPHEN I. PELTON
Keyword(s):  

2007 ◽  
Vol 3 (10) ◽  
pp. 27
Author(s):  
TIMOTHY F. KIRN
Keyword(s):  

2011 ◽  
Vol 4 (5) ◽  
pp. 27
Author(s):  
MARY ELLEN SCHNEIDER

2008 ◽  
Vol 1 (2) ◽  
pp. 1-4
Author(s):  
JANE ANDERSON
Keyword(s):  

2006 ◽  
Author(s):  
Erin Turman ◽  
Kymbra Potter ◽  
Elizabeth Hinojosa ◽  
Brian Parry

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