diff --git a/_applications/2026-urban-flows.md b/_applications/2026-urban-flows.md index 121dd602e39a..984cea187a15 100644 --- a/_applications/2026-urban-flows.md +++ b/_applications/2026-urban-flows.md @@ -50,7 +50,7 @@ Link to notebook: *Coming soon...* The complete step-by-step tutorial is available in the Urban Sensors 3D Reconstruction page. This link goes to the workflow explaining sparse-sensor selection, low-cost decomposition, field reconstruction, error evaluation and comparison with the original CFD solution. -The related research page is available here: From Sensors to 3D Reconstruction. This link goes to the research summary describing the motivation, methodology, datasets and reconstruction results for the low-cost 3D reconstruction work. +The related research page is available here: From Sensors to 3D Reconstruction. This link goes to the research summary describing the motivation, methodology, datasets and reconstruction results for the low-cost 3D reconstruction work. ## 2. Temporal Prediction of Urban Flow Fields @@ -70,7 +70,7 @@ Link to notebook: Low-Cost Sensor Calibration page. This link goes to the workflow explaining data cleaning, feature preparation, temporal sequence generation, LSTM model training and calibrated sensor output. -The related research page is available here: Temporal Deep Learning Calibration of Low-Cost Air Quality Sensors. This link goes to the research summary and paper information for the low-cost sensor calibration study. +The related research page is available here: Temporal Deep Learning Calibration of Low-Cost Air Quality Sensors. This link goes to the research summary and paper information for the low-cost sensor calibration study. # Resources & Databases