Frontiers in Aging Neuroscience, 2017 For understanding the heterogeneity of tinnitus, large samples are required. However, investigations on how samples recruited by different methods differ from each other are lacking.
Thomas Probst +12 more
doaj +1 more source
Path Forming of Healthcare Practitioners in an Indoor Space Using Mobile Crowdsensing. [PDF]
Sensors (Basel), 2022 Panlaqui BJ, Fuad M, Deb D, Mickle C.
europepmc +1 more source
A Hybrid Sensor Calibration Scheme for Mobile Crowdsensing-based City-Scale Environmental Measurements [PDF]
, 2016 Seung-Chul Son +3 more
openalex +1 more source
IEEE Access, 2019 Edge computing recently is increasingly popular due to the growth of data size and the need of sensing with the reduced center. Based on Edge computing architecture, we propose a novel crowdsensing framework called Edge-Mediated Spatial-Temporal ...
Sijia Yang +5 more
doaj +1 more source
A Personalized Task Allocation Strategy in Mobile Crowdsensing for Minimizing Total Cost. [PDF]
Sensors (Basel), 2022 Gao H, Zhao H.
europepmc +1 more source
Stackelberg Game Based Dynamic Admission and Scheduling in Mobile Crowdsensing [PDF]
, 2019 Zhifei Wang +5 more
openalex +1 more source
Self-Adaptive Learning and Cellular Automata based Mobile Crowdsensing
, 2022 openalex +1 more source
Edge-enabled Mobile Crowdsensing to Support Effective Rewarding for Data Collection in Pandemic Events. [PDF]
J Grid Comput, 2021 Foschini L +3 more
europepmc +1 more source
Space-Air-Ground Integrated Mobile Crowdsensing for Partially Observable Data Collection by Multi-Scale Convolutional Graph Reinforcement Learning. [PDF]
Entropy (Basel), 2022 Ren Y, Ye Z, Song G, Jiang X.
europepmc +1 more source
Towards the Interpretation of Sound Measurements from Smartphones Collected with Mobile Crowdsensing in the Healthcare Domain: An Experiment with Android Devices. [PDF]
Sensors (Basel), 2021 Kraft R, Reichert M, Pryss R.
europepmc +1 more source