[HTML][HTML] State of science: Why does rework occur in construction? What are its consequences? And what can be done to mitigate its occurrence?

PED Love, J Matthews, MCP Sing, SR Porter, W Fang - Engineering, 2022 - Elsevier
There has been a wealth of research that has examined the nature of rework in construction.
Progress toward addressing the rework problem has been limited—it still plagues practice …

Deep learning-based applications for safety management in the AEC industry: A review

L Hou, H Chen, G Zhang, X Wang - Applied Sciences, 2021 - mdpi.com
Safety is an essential topic to the architecture, engineering and construction (AEC) industry.
However, traditional methods for structural health monitoring (SHM) and jobsite safety …

Construction quality information management with blockchains

D Sheng, L Ding, B Zhong, PED Love, H Luo… - Automation in …, 2020 - Elsevier
The information generated from a nonconformance can be used to determine the party
responsible for ensuring that quality standards are assured. However, in the construction …

A deep learning-based approach for mitigating falls from height with computer vision: Convolutional neural network

W Fang, B Zhong, N Zhao, PE Love, H Luo… - Advanced Engineering …, 2019 - Elsevier
Structural supports (eg, concrete and steel) provide engineering structures with stability by
transferring loads. During the construction of an engineering structure, individuals are often …

Hazard analysis: A deep learning and text mining framework for accident prevention

B Zhong, X Pan, PED Love, J Sun, C Tao - Advanced Engineering …, 2020 - Elsevier
Learning from past accidents is pivotal for improving safety in construction. However, hazard
records are typically documented and stored as unstructured or semi-structured free-text …

Knowledge graph for identifying hazards on construction sites: Integrating computer vision with ontology

W Fang, L Ma, PED Love, H Luo, L Ding… - Automation in …, 2020 - Elsevier
Hazards potentially affect the safety of people on construction sites include falls from heights
(FFH), trench and scaffold collapse, electric shock and arc flash/arc blast, and failure to use …

Automated text classification of near-misses from safety reports: An improved deep learning approach

W Fang, H Luo, S Xu, PED Love, Z Lu, C Ye - Advanced Engineering …, 2020 - Elsevier
Examining past near-miss reports can provide us with information that can be used to learn
about how we can mitigate and control hazards that materialise on construction sites. Yet …

Do mistakes acceptance foster innovation? Polish and US cross-country study of tacit knowledge sharing in IT

W Kucharska - Journal of Knowledge Management, 2021 - emerald.com
Purpose This study aims to understand and compare how the mechanism of innovative
processes in the information technology (IT) industry–the most innovative industry worldwide …

Knowledge sharing and knowledge hiding in light of the mistakes acceptance component of learning culture-knowledge culture and human capital implications

W Kucharska, T Rebelo - The Learning Organization, 2022 - emerald.com
Knowledge sharing and knowledge hiding in light of the mistakes acceptance component of
learning culture- knowledge culture and human capital implications | Emerald Insight Books …

Quality management for sustainable manufacturing: Moving from number to impact of defects

A Goyal, R Agrawal, CR Saha - Journal of Cleaner Production, 2019 - Elsevier
Abstract Number of defects is a simple way to determine the quality of a product. Quality of a
process can also be determined on the basis of number of defects being produced by the …