POWDER: Platform for open wireless data-driven experimental research
J Breen, A Buffmire, J Duerig, K Dutt, E Eide… - Proceedings of the 14th …, 2020 - dl.acm.org
This paper provides an overview of the Platform for Open Wireless Data-driven Experimental
Research (POWDER). POWDER is a city-scale, remotely accessible, end-to-end software …
Research (POWDER). POWDER is a city-scale, remotely accessible, end-to-end software …
Novel dynamic data-driven modeling based on feature enhancement with derivative memory LSTM for complex industrial process
Effective feature extraction is important for accurate data-driven soft sensor modeling in
large-scale dynamic industrial processes. However, due to the temporal, nonlinear, and high …
large-scale dynamic industrial processes. However, due to the temporal, nonlinear, and high …
[HTML][HTML] Seasonal WaveNet-LSTM: A Deep Learning Framework for Precipitation Forecasting with Integrated Large Scale Climate Drivers
Seasonal precipitation forecasting (SPF) is critical for effective water resource management
and risk mitigation. Large-scale climate drivers significantly influence regional climatic …
and risk mitigation. Large-scale climate drivers significantly influence regional climatic …
[HTML][HTML] Spatiotemporal Prediction of Tidal Fields in a Semi-Enclosed Marine Bay Using Deep Learning
Z Zhu, X Yan, Z Wang, S Liu - Water, 2025 - mdpi.com
The prediction of tidal fields is crucial in coastal and marine hydrodynamic analyses,
particularly in complex tidal environments, as it plays an essential role in disaster warning …
particularly in complex tidal environments, as it plays an essential role in disaster warning …
Botm: Basestation-on-the-move, a radio access network management primitive
Software-defined Radio Access Networks (SD-RANs) enable unparalleled flexibility and the
opportunity to customize and/or optimize network operations. In particular, network function …
opportunity to customize and/or optimize network operations. In particular, network function …