A Bayesian-based inspection-monitoring data fusion approach for historical buildings and its post-earthquake application to a monumental masonry palace

L Ierimonti, N Cavalagli, I Venanzi… - Bulletin of Earthquake …, 2023 - Springer
Many countries exposed to high levels of seismic risk, including Italy, are facing a huge
challenge in promptly quantifying post-earthquake damages to their built historical heritage …

Deep learning–based building attribute estimation from google street view images for flood risk assessment using feature fusion and task relation encoding

FC Chen, A Subedi, MR Jahanshahi… - Journal of Computing …, 2022 - ascelibrary.org
Floods are the most common and damaging natural disaster worldwide in terms of both
economic losses and human casualties. Currently, policymakers rely on data collected …

Future cities demand smart and equitable infrastructure resilience modeling perspectives

JE Padgett, R Rincon, P Panakkal - npj Natural Hazards, 2024 - nature.com
Risk-informed decisions that promote infrastructure resilience (or the ability to withstand,
recover from, and adapt to stressors like natural hazards) require confident predictions of …

Prediction of mean and RMS wind pressure coefficients for low-rise buildings using deep neural networks

Y Huang, G Ou, J Fu, H Zhang - Engineering Structures, 2023 - Elsevier
Although the problems of wind pressure prediction on roofs have been studied extensively,
the prediction accuracy is still unsatisfactory owing to the limited capacity of shallow learning …

[HTML][HTML] BDD-Net: An end-to-end multiscale residual CNN for earthquake-induced building damage detection

ST Seydi, H Rastiveis, B Kalantar, AA Halin, N Ueda - Remote Sensing, 2022 - mdpi.com
Building damage maps can be generated from either optical or Light Detection and Ranging
(Lidar) datasets. In the wake of a disaster such as an earthquake, a timely and detailed map …

Performance-based post-earthquake decision making for instrumented buildings

M Roohi, EM Hernandez - Journal of Civil Structural Health Monitoring, 2020 - Springer
This paper develops a decision making framework for post-earthquake assessment of
instrumented buildings in a manner consistent with performance-based design criteria. This …

Assessing Climate Disaster Vulnerability in Peru and Colombia Using Street View Imagery: A Pilot Study

C Wang, SE Antos, JG Gosling-Goldsmith, LM Triveno… - Buildings, 2023 - mdpi.com
Community and household vulnerability to natural hazards, eg, earthquakes, hurricanes,
and floods, is a concern that transcends geographic and economic boundaries. Despite the …

Disaster risk management through the designsafe cyberinfrastructure

JP Pinelli, M Esteva, EM Rathje, D Roueche… - International Journal of …, 2020 - Springer
DesignSafe addresses the challenges of supporting integrative data-driven research in
natural hazards engineering. It is an end-to-end data management, communications, and …

AIDM: artificial intelligent for digital museum autonomous system with mixed reality and software-driven data collection and analysis

T Jiang, X Gan, Z Liang, G Luo - Automated Software Engineering, 2022 - Springer
The construction of digital museum is the inevitable trend of the development of museum
cause. At present, there are some problems in the construction of digital museum in China …

Machine-supported bridge inspection image documentation using artificial intelligence

X Zhang, B Eric Wogen, Z Chu… - Transportation …, 2023 - journals.sagepub.com
The purpose of a routine bridge inspection is to assess the physical and functional condition
of a bridge according to a regularly scheduled interval. The Federal Highway Administration …