A5100609383- Advanced Sensor and Energy Harvesting Materials
- Innovative Energy Harvesting Technologies
- Smart Grid and Power Systems
- Flow Measurement and Analysis
- Tactile and Sensory Interactions
- High-Voltage Power Transmission Systems
- Advanced Neural Network Applications
- Machine Fault Diagnosis Techniques
- Advanced MEMS and NEMS Technologies
- Advanced Image and Video Retrieval Techniques
- Advanced Computational Techniques and Applications
- Infrared Target Detection Methodologies
- Advanced Fiber Optic Sensors
- Landfill Environmental Impact Studies
- Engineering Diagnostics and Reliability
- Cloud Data Security Solutions
- Non-Invasive Vital Sign Monitoring
- Advanced Machining and Optimization Techniques
- HVDC Systems and Fault Protection
- Plasma and Flow Control in Aerodynamics
- Advanced Sensor Technologies Research
- Conducting polymers and applications
- Voice and Speech Disorders
- Hip and Femur Fractures
- Data Quality and Management
Chongqing University
2019-2024
First People's Hospital of Chongqing
2024
China University of Mining and Technology
2024
Jiangxi Agricultural University
2019-2022
Nanjing University of Aeronautics and Astronautics
2022
National University of Singapore
2009-2015
Institute for Infocomm Research
2012
WuXi AppTec (China)
2008
Fudan University
2004
Abstract Fire warning and monitoring are very important for public safety environmental protection. However, most of the proposed wind energy conversion devices based on triboelectric nanogenerator (TENG) only work unidirectional high‐speed face challenge fatigue damage even failure caused by cyclic stress. Moreover, TENG guided theory fluid dynamics needs further exploration. Herein, a flow‐induced vibration effect (F‐TENG) continuously capturing multidirectional breeze (1.8–4.3 m s −1 ) is...
In this note, we propose and develop a piezoelectric airflow sensor with novel configuration composed of bimorph cantilever (PBC) an internal miniature diversion channel (IMDC) structure. With the existence IMDC, velocity in tapered region IMDC can be magnified compared to inlet velocity, vibration amplitude PBC also enlarged that directly exposed same velocity. A fluid-solid interaction (FSI) model computed by finite element method (FEM) is presented clarify physical mechanism contained...
As an irreplaceable element for obtaining airflow information in many engineering scenarios, sensors have gained increasing attention across the fields of aerospace engineering, environmental sustainable energy exploitation, meteorology research, and so on. one mainstream sensing principles, piezoresistive velocity experienced rapid growth over years, while effective vector with ability detecting both direction based on principle are scarce. Here, basis our developed pressure loading mode,...
A local electric field distribution in the midplane between two spherical metal particles under an applied is measured for comparison with real electrorheological system. It was found that ratio of maximum value to not a constant as most theoretical models predicted.
The probe-type and substrate-type ultrasonic micro/nano manipulation systems have proven to be two kinds of powerful tools for manipulating micro/nanoscale materials. Numerical simulations acoustofluidic fields in these can not only used explain analyze the physical mechanisms experimental phenomena, but also provide guidelines optimization device parameters working conditions. However, in-depth quantitative study analysis scarcely been reported. In this paper, based on finite element method...
In the era of big data, issue data quality has become increasingly prominent. One main challenges is problem duplicate which can arise from repeated entry or merging multiple sources. These "dirty data" problems significantly limit effective application data. To address deduplication, we propose a pre-trained deduplication model based on active learning, first work that utilizes learning to at semantic level. The built Transformer and fine-tuned solve as sequence classification task, firstly...
Transformer is one of the key equipment in power industry and its safe operation very important to ensure reliability network. Therefore, transformer fault diagnosis has engineering value scientific significance. The method based on vibration characteristics advantages strong anti-interference good stability. In order determine types signal surface tank, this paper combines K-means clustering BP neural network, adopts distributed computing framework train model by massive data stored storage...
By launching a 80-GHz pulsed pump and 3-channel CW lights into 1-km highly-nonlinear fiber, 6-channel C+L band short pulse trains are generated based on four-wave mixing (FWM).
Abstract not Available.