about
Predicting and controlling infectious disease epidemics using temporal networksNetwork, degeneracy and bow tie. Integrating paradigms and architectures to grasp the complexity of the immune systemIndustry in motion: using smart phones to explore the spatial network of the garment industry in New York CityUsing GPS technology to quantify human mobility, dynamic contacts and infectious disease dynamics in a resource-poor urban environmentDynamical patterns of cattle trade movementsPostural instability detection: aging and the complexity of spatial-temporal distributional patterns for virtually contacting the stability boundary in human stance.Quantifying long-term evolution of intra-urban spatial interactions.Measuring large-scale social networks with high resolutionFundamental structures of dynamic social networksTracking Human Mobility Using WiFi SignalsSensing Urban Patterns with Antenna Mappings: The Case of Santiago, ChileActive and reactive behaviour in human mobility: the influence of attraction points on pedestriansQuantifying the Search Behaviour of Different Demographics Using Google CorrelateDaily Rhythms in Mobile Telephone CommunicationA multi-source dataset of urban life in the city of Milan and the Province of TrentinoQuantifying crowd size with mobile phone and Twitter data.Influence of sociodemographic characteristics on human mobility [corrected]Toward link predictability of complex networksDetecting memory and structure in human navigation patterns using Markov chain models of varying orderUbiquitous geo-sensing for context-aware analysis: exploring relationships between environmental and human dynamicsInferring Stop-Locations from WiFiVariability in Regularity: Mining Temporal Mobility Patterns in London, Singapore and Beijing Using Smart-Card DataMeasures of Human Mobility Using Mobile Phone Records Enhanced with GIS DataCollective Prediction of Individual Mobility Traces for Users with Short Data HistoryThe use of census migration data to approximate human movement patterns across temporal scalesThe strength of friendship ties in proximity sensor data.Assessing the use of mobile phone data to describe recurrent mobility patterns in spatial epidemic modelsMobile Network Data for Public Health: Opportunities and Challenges.Collective human mobility pattern from taxi trips in urban area.Collective response of human populations to large-scale emergencies.The dynamics of audience applause.Mapping internal connectivity through human migration in malaria endemic countries.Unique in the Crowd: The privacy bounds of human mobility.Temporal aggregation impacts on epidemiological simulations employing microcontact data.An infectious disease model on empirical networks of human contact: bridging the gap between dynamic network data and contact matricesThe role of gender in social network organization.Examining the spatial congruence between data obtained with a novel activity location questionnaire, continuous GPS tracking, and prompted recall surveys.Integrating rapid risk mapping and mobile phone call record data for strategic malaria elimination planningIntra-urban human mobility and activity transition: evidence from social media check-in data.Exploring universal patterns in human home-work commuting from mobile phone data.
P2860
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P2860
description
2010 nî lūn-bûn
@nan
2010年の論文
@ja
2010年学术文章
@wuu
2010年学术文章
@zh-cn
2010年学术文章
@zh-hans
2010年学术文章
@zh-my
2010年学术文章
@zh-sg
2010年學術文章
@yue
2010年學術文章
@zh
2010年學術文章
@zh-hant
name
Limits of predictability in human mobility.
@en
Limits of predictability in human mobility.
@nl
type
label
Limits of predictability in human mobility.
@en
Limits of predictability in human mobility.
@nl
prefLabel
Limits of predictability in human mobility.
@en
Limits of predictability in human mobility.
@nl
P2860
P356
P1433
P1476
Limits of predictability in human mobility.
@en
P2093
Nicholas Blumm
P2860
P304
P356
10.1126/SCIENCE.1177170
P407
P577
2010-02-01T00:00:00Z