Zobrazeno 1 - 10
of 282
pro vyhledávání: '"Kong, Qingkai"'
The proliferation of low-cost sensors in smartphones has facilitated numerous applications; however, large-scale deployments often encounter performance issues. Sensing heterogeneity, which refers to varying data quality due to factors such as device
Externí odkaz:
http://arxiv.org/abs/2407.03570
Combining physics with machine learning models has advanced the performance of machine learning models in many different applications. In this paper, we evaluate adding a weak physics constraint, i.e., a physics-based empirical relationship, to the l
Externí odkaz:
http://arxiv.org/abs/2403.04952
Deep learning-based surrogate models have been widely applied in geological carbon storage (GCS) problems to accelerate the prediction of reservoir pressure and CO2 plume migration. Large amounts of data from physics-based numerical simulators are re
Externí odkaz:
http://arxiv.org/abs/2308.09113
Autor:
Kong, Qingkai, Allen, Richard M., Allen, Steve, Bair, Theron, Meja, Akie, Patel, Sarina, Strauss, Jennifer, Thompson, Stephen
MyShake is a free citizen science smartphone app that provides a range of features related to earthquakes. Features available globally include rapid post-earthquake notifications, live maps of earthquake damage as reported by MyShake users, safety ti
Externí odkaz:
http://arxiv.org/abs/2204.12675
Autor:
Kong, Qingkai, Wang, Ruijia, Walter, William R., Pyle, Moira, Koper, Keith, Schmandt, Brandon
This paper combines the power of deep-learning with the generalizability of physics-based features, to present an advanced method for seismic discrimination between earthquakes and explosions. The proposed method contains two branches: a deep learnin
Externí odkaz:
http://arxiv.org/abs/2203.06347
Publikováno v:
Sci Rep 13, 1394 (2023)
For centuries, scientists have observed nature to understand the laws that govern the physical world. The traditional process of turning observations into physical understanding is slow. Imperfect models are constructed and tested to explain relation
Externí odkaz:
http://arxiv.org/abs/2202.01762
Autor:
Kong, Qingkai, Chiang, Andrea, Aguiar, Ana C., Fernández-Godino, M. Giselle, Myers, Stephen C., Lucas, Donald D.
Publikováno v:
Artificial Intelligence in Geosciences 2(2021), 96-106
The idea of using a deep autoencoder to encode seismic waveform features and then use them in different seismological applications is appealing. In this paper, we designed tests to evaluate this idea of using autoencoders as feature extractors for di
Externí odkaz:
http://arxiv.org/abs/2110.11802
Autor:
Chachra, Gaurav, Kong, Qingkai, Huang, Jim, Korlakunta, Srujay, Grannen, Jennifer, Robson, Alexander, Allen, Richard
Publikováno v:
Sci Rep 12, 8968 (2022)
After significant earthquakes, we can see images posted on social media platforms by individuals and media agencies owing to the mass usage of smartphones these days. These images can be utilized to provide information about the shaking damage in the
Externí odkaz:
http://arxiv.org/abs/2110.05762
Publikováno v:
In Applied Mathematics and Computation 15 April 2024 467
Publikováno v:
In Journal of Hydrology February 2024 629