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Search: WFRF:(Wei Boan)

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1.
  • Wei, Bo’an, et al. (author)
  • Construction site hazard identification and worker adverse reaction monitoring using electroencephalograms : a review
  • 2024
  • In: Buildings. - : MDPI. - 2075-5309. ; 14:1
  • Research review (peer-reviewed)abstract
    • The construction process is a dynamic one, and the complexity of the working conditions and the high level of uncertainty make the construction industry the third most dangerous industry after mining and agriculture. And since the construction industry is vital to the development of a country, safety during construction is of particular importance. A great deal of research, studies and practices have been conducted to reduce potential risks and improve worker efficiency during the construction process. In recent years, with the rapid development of cognitive neuroscience and the integration of medical technology, various wearable monitoring devices have been widely used in the field of building construction for real-time monitoring of workers’ physical and mental conditions. Among them, the application of EEG (electroencephalogram) in the building construction process enables researchers to gain insight into the physical and mental state of construction workers while performing construction tasks. This paper introduces EEG technology and portable EEG monitoring equipment and summarizes its application in monitoring workers’ adverse reactions (emotion, fatigue, psychological burden, and vigilance) and construction hazard identification during the process of construction in recent years, which provides future EEG research in the field of building construction and construction site safety management.
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2.
  • Yang, Bin, et al. (author)
  • Computer Vision and Machine Learning Methods for Heat Transfer and Fluid Flow in Complex Structural Microchannels : A Review
  • 2023
  • In: Energies. - : MDPI. - 1996-1073. ; 16:3
  • Research review (peer-reviewed)abstract
    • Heat dissipation in high-heat flux micro-devices has become a pressing issue. One of the most effective methods for removing the high heat load of micro-devices is boiling heat transfer in microchannels. A novel approach to flow pattern and heat transfer recognition in microchannels is provided by the combination of image and machine learning techniques. The support vector machine method in texture characteristics successfully recognizes flow patterns. To determine the bubble dynamics behavior and flow pattern in the micro-device, image features are combined with machine learning algorithms and applied in the recognition of boiling flow patterns. As a result, the relationship between flow pattern evolution and boiling heat transfer is established, and the mechanism of boiling heat transfer is revealed.
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  • Result 1-2 of 2
Type of publication
research review (2)
Type of content
peer-reviewed (2)
Author/Editor
Yang, Bin (2)
Lv, Zhihan, Dr. 1984 ... (2)
Wang, Faming (2)
Wei, Bo’an (2)
Liu, Pengju (1)
Fu, Hanliang (1)
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Liu, Minzhang (1)
Li, Yifan (1)
Zhang, Weiling (1)
Zhu, Xin (1)
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University
Uppsala University (2)
Umeå University (1)
Language
English (2)
Research subject (UKÄ/SCB)
Engineering and Technology (2)

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