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The exciting potential and daunting challenge of using GPS human-mobility data for epidemic modeling
Large-scale GPS location datasets hold immense potential for measuring human mobility
and interpersonal contact, both of which are essential for data-driven epidemiology …
and interpersonal contact, both of which are essential for data-driven epidemiology …
MobilityDL: a review of deep learning from trajectory data
Trajectory data combines the complexities of time series, spatial data, and (sometimes
irrational) movement behavior. As data availability and computing power have increased, so …
irrational) movement behavior. As data availability and computing power have increased, so …
[HTML][HTML] Confounding associations between green space and outdoor artificial light at night: systematic investigations and implications for urban health
Excessive urbanization leads to considerable nature deficiency and abundant artificial
infrastructure in urban areas, which triggered intensive discussions on people's exposure to …
infrastructure in urban areas, which triggered intensive discussions on people's exposure to …
How do you go where? improving next location prediction by learning travel mode information using transformers
Predicting the next visited location of an individual is a key problem in human mobility
analysis, as it is required for the personalization and optimization of sustainable transport …
analysis, as it is required for the personalization and optimization of sustainable transport …
[HTML][HTML] Context-aware multi-head self-attentional neural network model for next location prediction
Accurate activity location prediction is a crucial component of many mobility applications and
is particularly required to develop personalized, sustainable transportation systems. Despite …
is particularly required to develop personalized, sustainable transportation systems. Despite …
[HTML][HTML] Vehicle-to-grid for car sharing-A simulation study for 2030
The proliferation of car sharing services in recent years presents a promising avenue for
advancing sustainable transportation. Beyond merely reducing car ownership rates, these …
advancing sustainable transportation. Beyond merely reducing car ownership rates, these …
[HTML][HTML] Conserved quantities in human mobility: From locations to trips
Quantifying intra-person variability in travel choices is essential for the comprehension of
activity–travel behaviour. Due to a lack of empirical studies, there is limited understanding of …
activity–travel behaviour. Due to a lack of empirical studies, there is limited understanding of …
Where you go is who you are: a study on machine learning based semantic privacy attacks
Concerns about data privacy are omnipresent, given the increasing usage of digital
applications and their underlying business model that includes selling user data. Location …
applications and their underlying business model that includes selling user data. Location …
[HTML][HTML] Evaluating geospatial context information for travel mode detection
Detecting travel modes from global navigation satellite system (GNSS) trajectories is
essential for understanding individual travel behavior and a prerequisite for achieving …
essential for understanding individual travel behavior and a prerequisite for achieving …
Indoor mobility data encoding with TSTM-in: A topological-semantic trajectory model
The growing ubiquity of location/activity sensing technologies has created unprecedented
opportunities for research on human spatiotemporal interaction behavior in mobile …
opportunities for research on human spatiotemporal interaction behavior in mobile …