scholarly journals SRMM: A Social Relationship-Aware Human Mobility Model

Electronics ◽  
2020 ◽  
Vol 9 (2) ◽  
pp. 221 ◽  
Author(s):  
Dat Van Anh Duong ◽  
Seokhoon Yoon
Keyword(s):  
Social Context ◽  
Social Relationships ◽  
Social Relationship ◽  
Human Mobility ◽  
Real Life ◽  
Human Movement ◽  
Mobility Model ◽  
Power Law Distribution ◽  
Road Map ◽  
Human Movements

Since human movement patterns are important for validating the performance of wireless networks, several traces of human movements in real life have been collected. However, collecting data about human movements is costly and time-consuming. Moreover, multiple traces are demanded to test various network scenarios. As a result, a lot of synthetic models of human movement have been proposed. Nevertheless, most of the proposed models were often based on random generation, and cannot produce realistic human movements. Although there have been a few models that tried to capture the characteristics of human movement in real life (e.g., flights, inter-contact times, and pause times following the truncated power-law distribution), those models still cannot reflect realistic human movements due to a lack of consideration for social context among people. To address those limitations, in this paper, we propose a novel human mobility model called the social relationship–aware human mobility model (SRMM), which considers social context as well as the characteristics of human movement. SRMM partitions people into social groups by exploiting information from a social graph. Then, the movements of people are determined by considering the distances to places and social relationships. The proposed model is first evaluated by using a synthetic map, and then a real road map is considered. The results of SRMM are compared with a real trace and other synthetic mobility models. The obtained results indicate that SRMM is consistently better at reflecting both human movement characteristics and social relationships.

scholarly journals Characterizing Pairwise Social Relationships Quantitatively: Interest-Oriented Mobility Modeling for Human Contacts in Delay Tolerant Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Jiaxu Chen ◽  
Yazhe Tang ◽  
Chengchen Hu ◽  
Guijuan Wang
Keyword(s):  
Social Relationships ◽  
Mobile Networks ◽  
Human Mobility ◽  
Synthetic Data ◽  
Delay Tolerant Networks ◽  
Mobility Model ◽  
Interaction Matrix ◽  
Mobility Modeling ◽  
The Social ◽  
Delay Tolerant

Human mobility modeling has increasingly drawn the attention of researchers working on wireless mobile networks such as delay tolerant networks (DTNs) in the last few years. So far, a number of human mobility models have been proposed to reproduce people’s social relationships, which strongly affect people’s daily life movement behaviors. However, most of them are based on the granularity of community. This paper presents interest-oriented human contacts (IHC) mobility model, which can reproduce social relationships on a pairwise granularity. As well, IHC provides two methods to generate input parameters (interest vectors) based on the social interaction matrix of target scenarios. By comparing synthetic data generated by IHC with three different real traces, we validate our model as a good approximation for human mobility. Exhaustive experiments are also conducted to show that IHC can predict well the performance of routing protocols.

scholarly journals Real Life Human Movement Realization in Multimodal Group Communication Using Depth Map Information and Machine Learning

2020 ◽  
Vol 2 (2) ◽  
pp. 93-101
Author(s):  
Dr. Ranganathan G.
Keyword(s):  
Data Gathering ◽  
Real Life ◽  
Depth Map ◽  
Human Movement ◽  
Recognition System ◽  
Research Field ◽  
Movement Detection ◽  
The Real ◽  
Human Movements ◽  
Almost All

The latest advancements in the evolution of depth map information’s has paved way for interesting works like object recognition sign detection and human movement detection etc. The real life human movement detection or their activity identification is very challenging and tiresome. Since the real life activities of the humans could be of much interest in almost all areas, the subject of identifying the human activities has gained significance and has become a most popular research field. Identifying the human movements /activities in the public places like airport, railways stations, hospital, home for aged become very essential due to the several benefits incurred form the human movement recognition system such as surveillance camera, monitoring devices etc. since the changes in the space and the time parameters can provide an effective way of presenting the movements, yet in the case of natural color vision, as the flatness is depicted in almost all portions of images. So the work laid out in the paper in order to identify the human movement in the real life employs the space and the time depth particulars (Spatial-Temporal depth details –STDD) and the random forest in the final stage for movement classification. The technology put forth utilize the Kinect sensors to collecting the information’s in the data gathering stage. The mechanism laid out to identify the human movements is test with the MATLAB using the Berkley and the Cornell datasets. The mechanism proposed through the acquired results proves to deliver a better performance compared to the human movements captured using the normal video frames.

scholarly journals Emergence of Urban Growth Patterns from Human Movements

2020 ◽  
Author(s):  
Fengli Xu ◽  
Yong Li ◽  
Chaoming Song
Keyword(s):  
Urban Growth ◽  
Large Scale ◽  
Scaling Laws ◽  
Human Mobility ◽  
Human Movement ◽  
Urban Morphology ◽  
Growth Patterns ◽  
Spatial Correlations ◽  
Movement Model ◽  
Human Movements

Abstract Cities grow in a bottom-up manner, leading to fractal-like urban morphology characterized by scaling laws. Correlated percolation has succeeded in modeling urban geometries by imposing strong spatial correlations. However, the origin of such correlations remains largely unknown. Very recently, our understanding of human movements has been revolutionized thanks to the increasing availability of large-scale human mobility data. This paper proposes a novel human movement model that offers a micro-foundation for the dynamics of urban growth. We compare the proposed model with three empirical datasets, which evidences that strong social couplings and long-memory effects are two fundamental principles responsible for the mystical spatial correlations. The model accounts for the empirically observed scaling laws, but also allows us to understand the city evolution dynamically.

Trace- and Social-Based Modeling of Human Mobility Patterns

2016 ◽  
pp. 318-354
Author(s):  
Ali Diab ◽  
Andreas Mitschele-Thiel
Keyword(s):  
Communication Networks ◽  
Mobile Communication ◽  
Human Mobility ◽  
Movement Patterns ◽  
Human Movement ◽  
Mobility Patterns ◽  
Community Based ◽  
Human Movements ◽  
Mobile Communication Networks ◽  
Synthetic Models

The 5th Generation (5G) of mobile communication networks is being developed to address the demands and business contexts of 2020 and beyond. Its vision is to enable a fully mobile and connected society and also to trigger socio-economic transformations in ways eventually unimagined today. This means that the physical world to be covered with planned 5G networks including communication networks, humans and objects is becoming a type of an information system. So as to improve the experience of individuals, communities, societies, etc. within such systems, a thorough comprehension of intelligence processes responsible of generating, handling and controlling those data is fundamental. One of the major aspects in this context and also the focus of this chapter is the development of novel methods to model human mobility patterns, which have crucial role in forthcoming communication technologies. Human mobility patterns models can be categorized into synthetic, trace-based and community-based models. Synthetic models are largely preferred and widely applied to simulate mobile communication networks. They try to capture the patterns of human movements by means of a set of equations. These models are traceable, however, not capable of generating realistic mobility models. The key idea of trace-based models is the exploitation of available measurements and traces achieved in deployed systems to reproduce synthetic traces characterized by the same statistical properties of real traces. A main drawback of trace-based modeling of human patterns is the tight coupling between the trace-based model and the traces collected, the network topology deployed and even the geographic location, where the traces were collected. This is why the results of various trace-based models deviate clearly from each other. Sure, this prohibits the generalization of trace-based models. When one also considers that the traces themselves are rarely available, one can understand why synthetic models are preferred over trace-based ones. Community-based modeling of human movements depends on the fact stating that mobile devices are usually carried by humans, which implies that movement patterns of such devices are necessarily related to human decisions and socialization behaviors. So, human movement routines heavily affect the overall movement patterns resulting. One of the major contributions in this context is the application of social networks theory to generate more realistic human movement patterns. The chapter highlights the state of art and provides a comprehensive investigation of current research efforts in the field of trace- and social-based modeling of human mobility patterns. It reviews well-known approaches going through their pros and cons. In addition, the chapter studies an aspect that heavily relates to human mobility patterns, namely the prediction of future locations of users.

scholarly journals On Teaching Im/Migration in an Undergraduate Classroom

2021 ◽  
Vol 120 ◽  
pp. 61-68
Author(s):  
Amrita Dhar
Keyword(s):  
English Language ◽  
Human Mobility ◽  
Human Movement ◽  
The United States ◽  
First Century ◽  
Migrant Status ◽  
Human Movements ◽  
The Us ◽  
Pedagogical Aspect ◽  
Literature Class

This article examines the urgencies, challenges, and rewards of teaching about migration, emigration, and immigration in our time of massive human movement across the globe. I describe and analyse the beginnings, structure, and takeaways from my undergraduate course on the literature of human movements (whether for reasons of refuge, asylum, choice, adventure, exploration, survival). I argue that despite growing collective acknowledgment of increasing human mobility across our planet, it is the power and wisdom of stories through which we best engage with the specific and multifaceted realities of persons losing home, making home, making other, and making own. I also suggest, from my classroom experience, that a slow, reflective, and immersed sharing of stories of those who have been displaced, misplaced, replaced, and strangely-placed is a key pedagogical aspect of discussing im/migration in the twenty-first century, and that especially in the United States, we owe it to ourselves and our students to know and interrogate the longer vocabularies and histories of othering and belonging in the English language. Through my discussion of the class activities and conversations, I show, similarly, the ways in which a literature class on the topic of im/migration functions also as a generative venue for intersectional considerations of race, gender, ethnicity, class, caste, disability, sexuality, nationality, and un/documented status. I also include reflections about future iterations of this course as I draw on summative comments from my students. Finally: although my pedagogy is informed by my own migrant status in the US, I offer means for pedagogues from a range of backgrounds and instructional levels to engage with and further this conversation in different parts of the world.

scholarly journals INVESTIGATING THE RHYTHMS OF HUMAN MOVEMENTS IN GENEVA LAKE REGION USING MDC DATA

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 583-588
Author(s):  
R. Javanmard ◽  
R. Esmaeili ◽  
M. Malekzadeh ◽  
F. Karimipour
Keyword(s):  
Oil Spills ◽  
Social Issues ◽  
Human Mobility ◽  
Human Movement ◽  
Movement Behavior ◽  
Mobility Pattern ◽  
Traffic Forecasting ◽  
Movement Data ◽  
Human Movements ◽  
Wide Range

Abstract. Movement data are becoming extensive and comprehensive with the advent of GPS (global positioning system) and pervasive use of smartphones, which has led to an increasing rate of studies about movement such as mobility pattern of oil spills, taxies, storms and animals. Studying the movement of people has long been the topic of much thought and debate among researchers within the field of transportation, social issues, and policy. One of the basic prerequisites for studying human movement behavior is modeling the movement, which show how people move so that the effect of different variables can be revealed. For this purpose, this research intends to deploy the concept of activity space (i.e., the part of the space in which a person is active) and its determinants to display the trajectory of individuals, and then modeling the effect of different variables on human mobility behavior. This study explores the effect of time (movement on weekends and weekdays) and demographic (age, gender, occupation state) factors on the characteristics of human mobility pattern and analyzes the extent to which the mobility pattern of different group of people is related to time by using Swiss human movement sample dataset, called MDC. These movement characteristics can be used later in a wide range of applications, such as predictions, urban planning, and traffic forecasting.

Doctor-Patient Relationship: The Difficult Balance between Patient Psychology and Community Sociology

2019 ◽  
Vol 1 (1) ◽  
pp. 40-50
Author(s):  
Jose Luis Turabian
Keyword(s):  
Social Context ◽  
Interpersonal Relationship ◽  
Real Life ◽  
Community Relations ◽  
Patient Relationship ◽  
Doctor Patient Relationship ◽  
Important Place ◽  
Usual Model ◽  
Individual Personality ◽  
Object Of Study

Psychology and sociology share a common object of study, human behaviour, but from different perspectives. Sociologists have focused on macro variables, such as social structure, education, gender, age, race, etc., while psychology has focused on micro variables such as individual personality and behaviours, beliefs, empathy, listening, etc. Despite the importance of interpersonal relationship skills, they depend on the community or social context in which communication takes place, and by themselves may have little relevance in the consultation. The purely psychological analysis of the doctor-patient relationship often leads to an idyllic vision, with the patient-centred consultation as the greatest exponent, which rarely occurs in real life. The purely sociological or community / social analysis of the doctor-patient relationship leads to a negative view of the consultation, which is always shown as problematic. But, the psychological system in the doctor-patient relationship cannot be neglected, and its study is of importance, at least as an intermediate mechanism that is created through socio-community relations. Although the same social causes are behind the doctor-patient relationship, when acting on psychological factors in the consultation, they act as an optical prism scattering socio-community relations that affect the doctor and the patient, giving rise to a beam of different colors of doctor-patient relationship. In doctor-patient relationship there is a modality of psychotherapy, where attitudes, thoughts and behaviour of the patient, can be change, as well as it can be extended on the way of understanding and therefore changing, his social context. Because of the distance between socio-community relations and the form of doctor-patient relations is growing in complex societies, under these conditions, the sociological factor gives the important place to the psychological factor. Given these difficulties of the doctor-patient relationship one may ask how general medical practice can persist with the usual model of doctor-patient relationship. Pain and the desire to relieve them are the basic reasons for the patient and the doctor, and they do not disappear due to the contradictions of the doctor-patient relationship. In this way, the confrontation between sociological and psychological vision is replaced by an alliance of both currents, and each of them takes on meaning only in the general vision.

Examining the Kinships System of the Bodo

Think India ◽  
2019 ◽  
Vol 22 (3) ◽  
pp. 186-192
Author(s):  
Dr. Oinam Ranjit Singh ◽  
Dr. Nushar Bargayary
Keyword(s):  
Social Relationships ◽  
Social Cohesion ◽  
Social Relationship ◽  
Vital Role ◽  
Eastern Region ◽  
The North ◽  
Kinship System ◽  
North Eastern ◽  
The World ◽  
The Relationship

The Bodo of the North Eastern region of India have their own kinship system to maintain social relationship since ancient periods. Kinship is the expression of social relationship. Kinship may be defined as connection or relationships between persons based on marriage or blood. In each and every society of the world, social relationship is considered to be the more important than the biological bond. The relationship is not socially recognized, it fall outside the realm of kinship. Since kinship is considered as universal, it plays a vital role in the socialization of individuals and the maintenance of social cohesion of the group. Thus, kinship is considered to be the study of the sum total of these relations. The kinship of the Bodo is bilateral. The kin related through the father is known as Bahagi in Bodo whereas the kin to the mother is called Kurma. The nature of social relationships, the kinship terms, kinship behaviours and prescriptive and proscriptive rules are the important themes of the present study.

scholarly journals Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Meng-Chun Chang ◽  
Rebecca Kahn ◽  
Yu-An Li ◽  
Cheng-Sheng Lee ◽  
Caroline O. Buckee ◽  
...  
Keyword(s):  
Disease Surveillance ◽  
Initial Conditions ◽  
Human Mobility ◽  
Human Movement ◽  
Disease Spread ◽  
Spatial Spread ◽  
Movement Data ◽  
Intercity Travel ◽  
Travel Restrictions ◽  
The Impact

Abstract Background As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or linked to imported cases. Methods In collaboration with Facebook Data for Good, we characterized changes in movement patterns in Taiwan since February 2020, and built metapopulation models that incorporate human movement data to identify the high risk areas of disease spread and assess the potential effects of local travel restrictions in Taiwan. Results We found that mobility changed with the number of local cases in Taiwan in the past few months. For each city, we identified the most highly connected areas that may serve as sources of importation during an outbreak. We showed that the risk of an outbreak in Taiwan is enhanced if initial infections occur around holidays. Intracity travel reductions have a higher impact on the risk of an outbreak than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact. Conclusions To prepare for the potential spread within Taiwan, we utilized Facebook’s aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. We developed an interactive application that allows users to vary inputs and assumptions and shows the spatial spread of the disease and the impact of intercity and intracity travel reduction under different initial conditions. Our results can be used readily if local transmission occurs in Taiwan after relaxation of border control, providing important insights into future disease surveillance and policies for travel restrictions.

scholarly journals Tracking the global reduction of marine traffic during the COVID-19 pandemic

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
David March ◽  
Kristian Metcalfe ◽  
Joaquin Tintoré ◽  
Brendan J. Godley
Keyword(s):  
Large Scale ◽  
Human Mobility ◽  
Western Mediterranean ◽  
Western Mediterranean Sea ◽  
Marine Traffic ◽  
Human Movements ◽  
Exclusive Economic Zones ◽  
Global Impacts ◽  
Economic Zones

AbstractThe COVID-19 pandemic has resulted in unparalleled global impacts on human mobility. In the ocean, ship-based activities are thought to have been impacted due to severe restrictions on human movements and changes in consumption. Here, we quantify and map global change in marine traffic during the first half of 2020. There were decreases in 70.2% of Exclusive Economic Zones but changes varied spatially and temporally in alignment with confinement measures. Global declines peaked in April, with a reduction in traffic occupancy of 1.4% and decreases found across 54.8% of the sampling units. Passenger vessels presented more marked and longer lasting decreases. A regional assessment in the Western Mediterranean Sea gave further insights regarding the pace of recovery and long-term changes. Our approach provides guidance for large-scale monitoring of the progress and potential effects of COVID-19 on vessel traffic that may subsequently influence the blue economy and ocean health.

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