Zobrazeno 1 - 10
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pro vyhledávání: '"SHANG Ling"'
Understanding human mobility behavior is crucial for numerous applications, including crowd management, location-based recommendations, and the estimation of pandemic spread. Machine learning models can predict the Points of Interest (POIs) that indi
Externí odkaz:
http://arxiv.org/abs/2411.15285
Human mobility modeling from GPS-trajectories and synthetic trajectory generation are crucial for various applications, such as urban planning, disaster management and epidemiology. Both of these tasks often require filling gaps in a partially specif
Externí odkaz:
http://arxiv.org/abs/2411.04381
This paper introduces a novel smartphone-enabled localization technology for ambient Internet of Things (IoT) devices, leveraging the widespread use of smartphones. By utilizing the passive movement of a smartphone, we create a virtual large array th
Externí odkaz:
http://arxiv.org/abs/2410.20330
Publikováno v:
IEEE Internet of Things Journal, Early Access, 2024
Internet of Things (IoT) device localization is fundamental to smart home functionalities, including indoor navigation and tracking of individuals. Traditional localization relies on relative methods utilizing the positions of anchors within a home e
Externí odkaz:
http://arxiv.org/abs/2407.02919
In 6G, the trend of transitioning from massive antenna elements to even more massive ones is continued. However, installing additional antennas in the limited space of user equipment (UE) is challenging, resulting in limited capacity scaling gain for
Externí odkaz:
http://arxiv.org/abs/2305.12308
Autor:
Hsu, Shang-Ling, Shah, Raj Sanjay, Senthil, Prathik, Ashktorab, Zahra, Dugan, Casey, Geyer, Werner, Yang, Diyi
Millions of users come to online peer counseling platforms to seek support on diverse topics ranging from relationship stress to anxiety. However, studies show that online peer support groups are not always as effective as expected largely due to use
Externí odkaz:
http://arxiv.org/abs/2305.08982
The dissemination of fake news on social networks has drawn public need for effective and efficient fake news detection methods. Generally, fake news on social networks is multi-modal and has various connections with other entities such as users and
Externí odkaz:
http://arxiv.org/abs/2205.03100
Temporal information extraction plays a critical role in natural language understanding. Previous systems have incorporated advanced neural language models and have successfully enhanced the accuracy of temporal information extraction tasks. However,
Externí odkaz:
http://arxiv.org/abs/2201.06125
Extracting temporal relations among events from unstructured text has extensive applications, such as temporal reasoning and question answering. While it is difficult, recent development of Neural-symbolic methods has shown promising results on solvi
Externí odkaz:
http://arxiv.org/abs/2112.00894