scholarly journals Bus transport network analysis in Rio de Janeiro based on topological models using Social Networks

2020 ◽  
Author(s):  
Diego Carvalho ◽  
Rafael Barbastefano ◽  
Louise Pumar
Keyword(s):  
Social Networks ◽  
Rio De Janeiro ◽  
Transportation Network ◽  
Giant Component ◽  
Space Networks ◽  
Minimum Number ◽  
Bus Stops ◽  
Bus Networks ◽  
Topological Models ◽  
Bus System

In recent years, studies on public transport networks have intensified in the Social Networks field, especially in bus networks, motivated by urban mobility’s relevance for the proper functioning of a city. Rio de Janeiro city, Brazil, has undergone recent changes in its municipal bus system, modifying several lines and bus stops due to the preparation for the Olympic games. This paper analyzes the structure of Rio’s bus transportation network of this city using Social Network technics, comparing its topology in 2014 and 2016 – before and after the change and the properties of the bus system investigated based on the topological models B-space, P-space, and C-space. Some essential parameters were calculated, such as giant component, distance, diameter, degree, closeness, and betweenness. The results showed a reduction of 22.75% of the lines and 5.19% of the bus stops from 2014 to 2016. We show that a maximum of four lines is required to move between any two bus stops within the city in both years. However, with three, it is possible to reach more than 99% of the bus stops. Besides, this study also introduces a new C- space network according to the minimum number of frequent bus stops that the lines had. Based on the giant component analysis of these new C-space networks with many common points, it is possible to detect possible expressway corridors.

scholarly journals Hub-Periphery Hierarchy in Bus Transportation Networks: Gini Coefficients and the Seoul Bus System

2020 ◽  
Vol 12 (18) ◽  
pp. 7297 ◽  
Author(s):  
Chansoo Kim ◽  
Segun Goh ◽  
Myeong Seon Choi ◽  
Keumsook Lee ◽  
M. Y. Choi
Keyword(s):  
Gini Coefficient ◽  
City Planning ◽  
Transportation Networks ◽  
Transportation Network ◽  
Growth Dynamics ◽  
Transportation Systems ◽  
The Gini Coefficient ◽  
Bus Stops ◽  
Bus System ◽  
Bus Transportation

Bus transportation networks are characteristically different from other mass transportation systems such as airline or subway networks, and thus the usual approach may not work properly. In this paper, to analyze the bus transportation network, we employ the Gini coefficient, which measures the disparity of weights of bus stops. Applied to the Seoul bus system specifically, the Gini coefficient allows us to classify nodes in the bus network into two distinct types: hub and peripheral nodes. We elucidate the structural properties of the two types in the years 2011 and 2013, and probe the evolution of each type over the two years. It is revealed that the hub type evolves according to the controlled growth process while the peripheral one, displaying a number of new constructions as well as sudden closings of bus stops, is not described by growth dynamics. The Gini coefficient thus provides a key mathematical criterion of decomposing the transportation network into a growing one and the other. It would also help policymakers to deal with the complexity of urban mobility and make more sustainable city planning.

Analysis of Identification Methods of Key Nodes in Transportation Network

2022 ◽  
Author(s):  
Qiang Lai ◽  
Hong-hao Zhang
Keyword(s):  
Transportation Networks ◽  
Transportation Network ◽  
Practical Significance ◽  
Node Degree ◽  
Connected Subgraph ◽  
Network Efficiency ◽  
Identification Methods ◽  
Identification Method ◽  
Bus Networks ◽  
Key Nodes

Abstract The identification of key nodes plays an important role in improving the robustness of the transportation network. For different types of transportation networks, the effect of the same identification method may be different. It is of practical significance to study the key nodes identification methods corresponding to various types of transportation networks. Based on the knowledge of complex networks, the metro networks and the bus networks are selected as the objects, and the key nodes are identified by the node degree identification method, the neighbor node degree identification method, the weighted k-shell degree neighborhood identification method (KSD), the degree k-shell identification method (DKS), and the degree k-shell neighborhood identification method (DKSN). Take the network efficiency and the largest connected subgraph as the effective indicators. The results show that the KSD identification method that comprehensively considers the elements has the best recognition effect and has certain practical significance.

Prediction of Social Influence for Provenance of Misinformation in Online Social Network Using Big Data Approach

2020 ◽  
Author(s):  
Kumaran P ◽  
Rajeswari Sridhar
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Law Enforcement ◽  
Online Social Networks ◽  
Large Scale ◽  
Online Social Network ◽  
Root Cause ◽  
Minimum Number ◽  
Targeted Marketing ◽  
Implicit And Explicit

Abstract Online social networks (OSNs) is a platform that plays an essential role in identifying misinformation like false rumors, insults, pranks, hoaxes, spear phishing and computational propaganda in a better way. Detection of misinformation finds its applications in areas such as law enforcement to pinpoint culprits who spread rumors to harm the society, targeted marketing in e-commerce to identify the user who originates dissatisfaction messages about products or services that harm an organizations reputation. The process of identifying and detecting misinformation is very crucial in complex social networks. As misinformation in social network is identified by designing and placing the monitors, computing the minimum number of monitors for detecting misinformation is a very trivial work in the complex social network. The proposed approach determines the top suspected sources of misinformation using a tweet polarity-based ranking system in tandem with sarcasm detection (both implicit and explicit sarcasm) with optimization approaches on large-scale incomplete network. The algorithm subsequently uses this determined feature to place the minimum set of monitors in the network for detecting misinformation. The proposed work focuses on the timely detection of misinformation by limiting the distance between the suspected sources and the monitors. The proposed work also determines the root cause of misinformation (provenance) by using a combination of network-based and content-based approaches. The proposed work is compared with the state-of-art work and has observed that the proposed algorithm produces better results than existing methods.

scholarly journals FROM DISARMAMENT TO REARMAMENT: ELEMENTS FOR A SOCIOLOGY OF CRITIQUE OF THE PACIFICATION POLICE UNIT PROGRAM

2018 ◽  
Vol 14 (3) ◽  
Author(s):  
Palloma Menezes ◽  
Diogo Corrêa
Keyword(s):  
Social Networks ◽  
Rio De Janeiro ◽  
Temporal Analysis ◽  
Alternative Media ◽  
Entire Period ◽  
Ethnographic Research ◽  
News Reports ◽  
History Of ◽  
The City

Abstract Inspired by the reflections on the concept of critique proposed by Luc Boltanski and Eve Chiapello, this article presents some elements for a sociology of critique of the Pacification Police Unit (Unidade de Polícia Pacificadora - UPPs) program. It offers a brief history of the project, typified in phases. We conduct a mapping and a temporal analysis of critiques made about the UPPs throughout the entire period of their existence from 2008 until today. This analysis is based on ethnographic research and interviews conducted by the authors between 2009 and 2015 in the first two "pacified" favelas in the city of Rio de Janeiro (Santa Marta and the Cidade de Deus), and on the analysis of news reports from the major and alternative media and of social networks.

scholarly journals A Self-Adjusting Method to Resist Bus Bunching Based on Boarding Limits

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Shuzhi Zhao ◽  
Chunxiu Lu ◽  
Shidong Liang ◽  
Huasheng Liu
Keyword(s):  
Travel Time ◽  
The State ◽  
New Method ◽  
Bus Bunching ◽  
Total Travel Time ◽  
Urban Bus ◽  
Bus Stops ◽  
Bus Service ◽  
Bus System

Bus bunching is one of the most serious problems of urban bus systems. Bus bunching increases waiting and travel time of passengers. Many bus systems use schedules to reach equal headways. Compared to the idea of schedules and the target headway introduced later, we propose a new method to improve the efficiency of a bus system and avoid bus bunching by boarding limits. Our solution can be effectively implemented when buses cannot travel as planned because of bad road conditions and dynamic demands at bus stops. Besides, using our method, bus headways reach the state with equal headways dynamically and spontaneously without drivers’ explicit intervention. Moreover, the method can improve the level of the bus service and reduce total travel time of passengers. We verify our method using an ideal bus route and a real bus route, both showing the success of the proposed method.

Obtaining Public Transport Level-of-Service Measures Using In-Vehicle GPS Data and Freely Available GIS Web-Based Tools

2014 ◽  
pp. 258-275 ◽  
Author(s):  
Julián Arellana ◽  
Juan de Dios Ortúzar ◽  
Luis I. Rizzi ◽  
Felipe Zuñiga
Keyword(s):  
Public Transport ◽  
Low Cost ◽  
Waiting Times ◽  
Geographic Location ◽  
Level Of Service ◽  
Gps Data ◽  
Travel Times ◽  
Public Transport System ◽  
Bus Stops ◽  
Bus Networks

In this chapter, the authors present a procedure to obtain some Level-Of-Service (LOS) measures, such as waiting times, travel times, and their variability, at any spatial and temporal aggregation level for dense bus networks using freely available map and geographic software. The proposed methodology is highly flexible, as it can accommodate either fixed or variable space-time aggregations. It can handle vast amounts of GPS data yielding LOS results relatively quickly. Furthermore, it can be implemented at relatively low cost in terms of software requirements using freely available software. An illustration of the proposed procedure and its results to obtain LOS measures such as travel times and their variability among bus stops and waiting times for every bus stop are reported using the geographic location of bus stops and offline GPS data available (every 30 seconds) for all operating buses in Santiago´s public transport system.

Active Node Detection in A Reconfigurable Microgrid using Minimum Spanning Tree Algorithms

2017 ◽  
Vol 5 (3) ◽  
pp. 502 ◽  
Author(s):  
Anay Majee ◽  
Souradeep Nanda ◽  
Gnana Swathika O.V
Keyword(s):  
Renewable Energy ◽  
Spanning Tree ◽  
Power Flow ◽  
Minimum Spanning Tree ◽  
Grid Connection ◽  
Protection Strategies ◽  
Sample Test ◽  
Minimum Number ◽  
Tree Algorithms ◽  
Bus Networks

<p>Microgrids are the solution to the growing demand for energy in the recent times. It has the potential to improve local reliability, reduce cost and increase penetration rates for distributed renewable energy generation. Inclusion of Renewable Energy Systems (RES) which have become the topic of discussion in the recent times due to acute energy crisis, causes the power flow in the microgrid to be bi-directional in nature. The presence of the RES in the microgrid system causes the grid to be reconfigurable. This reconfiguration might also occur due to load or utility grid connection and disconnection. Thus conventional protection strategies are not applicable to micro-grids and is hence challenging for engineers to protect the grid in a fault condition. In this paper various Minimum Spanning Tree (MST) algorithms are applied in microgrids to identify the active nodes of the current topology of the network in a heuristic approach and thereby generating a tree from the given network so that minimum number of nodes have to be disconnected from the network during fault clearance. In the paper we have chosen the IEEE-39 and IEEE-69 bus networks as our sample test systems.</p>

Improved Path Flow Estimator for Origin–Destination Trip Tables

2005 ◽  
Vol 1923 (1) ◽  
pp. 9-17 ◽  
Author(s):  
Piya Chootinan ◽  
Anthony Chen ◽  
Will Recker
Keyword(s):  
Error Bounds ◽  
Lagrange Multipliers ◽  
Transportation Network ◽  
Location Theory ◽  
Set Covering ◽  
Traffic Counts ◽  
Minimum Number ◽  
Covering Model ◽  
Path Flow Estimator

Path flow estimator (PFE) is a one-stage network observer that can estimate path flows and path travel times from traffic counts in a transportation network. Because a unique set of path flows is readily available from the PFE, a trip table can be estimated by simply adding up flows on all the paths connecting individual origin–destination (O-D) pairs. In this paper, the effects of the number and locations of traffic counts on the quality of the O-D trip table estimated by PFE are examined. The set-covering model, studied in the location theory, is applied to determine the minimum number of traffic counts and their corresponding locations required to observe the total demand of the study network. Next, the effects of the error bounds used in PFE to handle the inconsistency problem of traffic counts are examined, and a heuristic using the Lagrange multipliers to facilitate the adjustment of such error bounds is provided. Numerical results show that PFE can correctly estimate the total demand of the study area if a sufficient number of traffic counts collected at appropriate locations is provided. The results further indicate that improper specification of the error bounds could lead to biased estimation of total demand utilizing the network.

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