A5085115830- Seismic Waves and Analysis
- Seismology and Earthquake Studies
- Seismic Imaging and Inversion Techniques
- Advanced Sensor and Energy Harvesting Materials
- Sports Performance and Training
- earthquake and tectonic studies
- Electronic and Structural Properties of Oxides
- Geophysics and Sensor Technology
- Mobile Agent-Based Network Management
- Advanced Technologies in Various Fields
- Sparse and Compressive Sensing Techniques
- Multiferroics and related materials
- Industrial Vision Systems and Defect Detection
- Textile materials and evaluations
- Evacuation and Crowd Dynamics
- Power Line Communications and Noise
- PAPR reduction in OFDM
- Grey System Theory Applications
- Sports injuries and prevention
- Innovative Energy Harvesting Technologies
- Winter Sports Injuries and Performance
- Ferroelectric and Piezoelectric Materials
- Energy Load and Power Forecasting
- Energy Harvesting in Wireless Networks
- Robotic Path Planning Algorithms
Soochow University
2023-2025
Shanghai University
2023
City University of Hong Kong
2023
EY Technologies (United States)
2023
Huzhou University
2021
University of Electronic Science and Technology of China
2021
Harvesting wideband and random vibration energy in the vehicle environment is a promising route to power mobile electronic devices. Conventional harvesters cannot realize steady-state output, making management circuit design difficult. This work presents an electromagnetic harvester with counterweight unit, gearbox, generator, which can be adapted automatic storage quantized output release. The unit low-frequency response effectively sense weak vibration. coil spring gear train particular...
In cross-country skiing, ski poles play a crucial role in technique, propulsion, and overall performance. The kinematic parameters of can provide valuable information about the skier’s which is great significance for coaches athletes seeking to improve their skiing this work, new smart pole proposed, combines uniaxial load cell inertial measurement unit (IMU), aiming comprehensive data functions more easily an auxiliary training. collect directly related technical actions, such as force,...
It is crucial to retain as many signal components possible, while noise eliminated for wavelet packet reduction algorithms. Conventional thresholding functions take coefficients smaller than a given threshold the component and get them removed in ways. In this letter, considering potential probability of being signal-related whose value nonnegligible fact that microseismic (MS) event sparse compared with noise, we proposed new packet-based denoising method via fuzzy partition. First, instead...
The large amount of monitoring data has posed enormous challenges to the quick response and accurate analysis microseismic events. Compressed sensing (CS) advantages low resource cost, high efficiency, excellent compression ratio (CR), over conventional methods. However, there are still issues be addressed for its applications: 1) poor quality complex signal structure significantly increased difficulty keeping satisfactory efficiency; 2) systematic design sparse dictionary, measurement...
Accurate first arrival picking plays a crucial role in microseismic data processing. However, it is challenging to guarantee satisfactory accuracy with conventional approaches when the signal-to-noise ratio (SNR) of low. This article proposes an automatic time method based on fuzzy <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$C$ </tex-math></inline-formula> means clustering (FCM) and Akaike information...
Future communication systems must support high-speed mobile scenarios, while the mainstream Orthogonal Frequency Division Multiplexing (OFDM) technology faces severe inter-carrier interference in such environments. Therefore, adoption of Time–Frequency Space (OTFS) modulation 6G is an effective solution. The widely used single-pilot channel estimation OTFS susceptible to path loss and inaccurate fading coefficient estimation, leading reduced accuracy, signal distortion, degraded overall...
Abstract Due to the complex characteristics of annual contribution time series, it is difficult achieve ideal prediction effect by a single prediction. Therefore, electricity model based on Logistic regression analysis studied. The statistical method series combined with fuzzy correlation feature used obtain high-voltage power transmission data business expansion and consumption after transmission. We use clustering theory complete customer segmentation accurately locate same type user...
Joint monitoring is more potent than conventional micro-seismic(MS) in understanding underground processes. With simultaneous observations from the surface and downhole, joint has shown its advantages disaster early-warning tunneling mining, station deployment. However, Sichuan Basin, China, due to complex environment, it intuitively difficult transport, install, maintain stations on surface. Thus, we have developed a new system for real-time long-term MS based novel self-developed stations....
Accurate picking of first arrival time plays a critical role in event localization and further data processing microseismic(MS) monitoring. A large amount from receivers make effective automatic method an urgent issue. In this letter, we proposed adaptive automated approach based on fuzzy c-means (FCM) clustering algorithm. First, by applying FCM, points are assigned to two clusters with certain membership degrees: signal cluster noise cluster. Then the vector describing center is extracted...