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Machinery multi-sensor fault diagnosis based on adaptive multivariate feature mode decomposition and multi-attention fusion residual convolutional neural network Journal article
Yan Xiaoan, Yan Wangji, Xu Yadong, Yuen Kaveng. Machinery multi-sensor fault diagnosis based on adaptive multivariate feature mode decomposition and multi-attention fusion residual convolutional neural network[J]. Mechanical Systems and Signal Processing, 2023, 202, 110664.
Authors:  Yan Xiaoan;  Yan Wangji;  Xu Yadong;  Yuen Kaveng
Adobe PDF | Favorite | TC[WOS]:28 TC[Scopus]:31  IF:7.9/8.0 | Submit date：2023/08/30
Multivariate Feature Mode Decomposition  Multi-attention Fusion Residual Convolutional Neural Network  Multi-sensor Data  Machinery Fault Diagnosis  
Indoor navigation and information sharing for collaborative fire emergency response with BIM and multi-user networking Journal article
Wong, Mun On, Lee, Sanghoon. Indoor navigation and information sharing for collaborative fire emergency response with BIM and multi-user networking[J]. AUTOMATION IN CONSTRUCTION, 2023, 148, 104781.
Authors:  Wong, Mun On;  Lee, Sanghoon
Favorite | TC[WOS]:8 TC[Scopus]:9  IF:9.6/10.6 | Submit date：2023/02/28
Building Information Modeling (Bim)  Industry Foundation Classes (Ifc)  Shortest Pathfinding Algorithm  Multi-sensor Data Fusion  Particle Filter  Indoor Localization  Multi-user System  Information Sharing  
A 1.1 μW CMOS smart temperature sensor with an inaccuracy of ±0.2 °C (3σ) for clinical temperature monitoring Journal article
Man-Kay Law, Sanfeng Lu, Tao Wu, Amine Bermak, Pui-In Mak, Rui P. Martins. A 1.1 μW CMOS smart temperature sensor with an inaccuracy of ±0.2 °C (3σ) for clinical temperature monitoring[J]. IEEE Sensors Journal, 2016, 16(8), 2272-2281.
Authors:  Man-Kay Law;  Sanfeng Lu;  Tao Wu;  Amine Bermak;  Pui-In Mak; et al.
Favorite | TC[WOS]:32 TC[Scopus]:43 | Submit date：2019/02/11
Smart Temperature Sensor  Ultra-low Power  High Accuracy  Incremental Analog-to-digital Converter (I-adc),  Multi-ratio Pre-gain  Block-based Data Weighted Averaging (Bdwa)  
A 1.1 µW CMOS Smart Temperature Sensor with an Inaccuracy of ±0.2oC (3σ) for Clinical Temperature Monitoring Journal article
Law, M. K., Lu, S., Wu, T., Bermak, A., Mak, P. I., Martins, R. P.. A 1.1 µW CMOS Smart Temperature Sensor with an Inaccuracy of ±0.2oC (3σ) for Clinical Temperature Monitoring[J]. IEEE Sensors Journal, 2016, 2272-2281.
Authors:  Law, M. K.;  Lu, S.;  Wu, T.;  Bermak, A.;  Mak, P. I.; et al.
Favorite |   IF:4.3/4.2 | Submit date：2022/01/24
Smart temperature sensor  ultra-low power  high accuracy  incremental analog-to-digital converter (I-ADC)  multi-ratio pre-gain  block-based data weighted averaging (BDWA)  
Multi-attribute decision making for data-centric routing in wireless sensor network Conference paper
Zhou J., Chen C.L.P., Chen L.. Multi-attribute decision making for data-centric routing in wireless sensor network[C], 2013, 429-434.
Authors:  Zhou J.;  Chen C.L.P.;  Chen L.
Favorite | TC[WOS]:1 TC[Scopus]:1 | Submit date：2019/02/11
Data-centric Routing  Wireless Sensor Network  Multi-attribute Decision Making