A5100724713- Fault Detection and Control Systems
- Machine Fault Diagnosis Techniques
- Photonic and Optical Devices
- Optical Network Technologies
- Advanced Chemical Sensor Technologies
- Mineral Processing and Grinding
- Complex Network Analysis Techniques
- Remote-Sensing Image Classification
- Advanced Computational Techniques and Applications
- Adaptive Control of Nonlinear Systems
- Semiconductor Lasers and Optical Devices
- Control Systems and Identification
- Structural Health Monitoring Techniques
- Medical Imaging Techniques and Applications
- Advanced Photonic Communication Systems
- Opinion Dynamics and Social Influence
- Wireless Sensor Networks and IoT
- Spectroscopy and Chemometric Analyses
- Optical Systems and Laser Technology
- Advanced Control Systems Optimization
- Gas Sensing Nanomaterials and Sensors
- Face and Expression Recognition
- Advanced Adaptive Filtering Techniques
- Process Optimization and Integration
- Advanced Sensor and Control Systems
City University of Hong Kong
2025
Aero Engine Corporation of China (China)
2024
Nanjing Forestry University
2024
Huazhong University of Science and Technology
2009-2023
Wuhan Engineering Science & Technology Institute
2023
Wuhan National Laboratory for Optoelectronics
2007-2022
Tianjin University of Technology and Education
2019
Shanghai Institute of Optics and Fine Mechanics
2019
Hunan University of Technology
2019
Imperial College London
2015-2018
Multi-view spectral clustering, which aims at yielding an agreement or consensus data objects grouping across multi-views with their graph laplacian matrices, is a fundamental clustering problem. Among the existing methods, Low-Rank Representation (LRR) based method quite superior in terms of its effectiveness, intuitiveness and robustness to noise corruptions. However, it aggressively tries learn common low-dimensional subspace for multi-view data, while inattentively ignoring local...
Semantic segmentation is a fundamental problem in computer vision. It considered as pixel-wise classification practice, and most models use loss their optimization riterion. However, the ignores dependencies between pixels an image. Several ways to exploit relationship have been investigated, \eg, conditional random fields (CRF) pixel affinity based methods. Nevertheless, these methods usually require additional model branches, large extra memories, or more inference time. In this paper, we...
We proposed and experimental demonstrated all-optical two line-four line encoder bit-wise comparator of RZ data streams at 40Gb/s based on cross gain modulation (XGM) four wave mixing (FWM) in three parallel SOAs. Five logic functions for digital between signals A B: AB, AB AOmicronB, were achieved simultaneously. The first optical logics are realized XGM SOAs, the fourth is with FWM, fifth result fourth. detuning filter employed to improve output performance. extinction ratio (ER) operation...
Diffusion models generate high-quality images but often lack efficient and universally applicable inpainting capabilities, particularly in community-trained models. We introduce LanPaint, a training-free method tailored for widely adopted ODE-based samplers, which leverages Langevin dynamics to perform exact conditional inference, enabling precise visually coherent inpainting. LanPaint addresses two key challenges Langevin-based inpainting: (1) the risk of local likelihood maxima trapping...
Abstract Multimode is the characteristic of industrial manufacturing processes due to different production strategies and environments. For multimode process monitoring, it a challenge identify steady modes transition modes. In this paper, k nearest neighbours (KNN)‐based density peaks clustering (DPC) method applied First, local each sample, which obtained with KNN constraint its minimum distance higher points are calculated as two indicators DPC algorithm find cluster centres training...
Real-time nonlinear multimode process monitoring of actual industrial systems has attracted increasing attention recently. In this article, the time-weighed kernel sparse representation (TWKSR) method is proposed to partition mode training dataset by introducing time-series-dependent characteristics into algorithm. The alternating direction multipliers utilized solve optimization problem TWKSR method. Then, representative samples from each identified are selected update dictionary matrix....
We demonstrate that noise is an important factor contributing to the decline of sensitivity and linear response range velocity measurements for laser speckle contrast imaging. propose use a correction method improve measurements. For kind camera in which mean values dark have been subtracted negative counts set zero, we estimate true based on maximum likelihood estimation, expands application scope method.
This paper is concerned with the question of reconstructing a vector in finite-dimensional real Hilbert space when only magnitudes coefficients under redundant linear map are known. We analyze various Lipschitz bounds nonlinear analysis and we establish theoretical performance any reconstruction algorithm. show that robust stable requires additional redundancy than critical threshold.
With the rapid development of modern industry, actual production processes generally have a variety complex characteristics including nonlinearity, multimodality, and contamination. Those characteristics, as well faults, bring great challenges to traditional process monitoring. To deal with all above-mentioned three problems simultaneously, this paper develops robust nonlinear multimode monitoring scheme. First, decomposition kernel function (RDKF) algorithm is proposed detect outliers....
This paper deals with the problem of estimating frequencies n sinusoidal components a multi-sinusoidal signal. A distinctive feature proposed method is that are directly adapted, thus not requiring further steps eigenvalue extraction or polynomial root-finding to retrieve from characteristic polynomial, as typically done in literature. The frequency estimation approached by formulating new state-space realization signal generator (oscillatory internal model) which characterized minimal...
Frequent operation changes are inevitable to achieve different production aims, which leads mixed periods of stationarity and nonstationarity in industrial processes increases the monitoring difficulty. In this article, a generalized scheme is proposed for with stationary nonstationary operational stages. First, local average similarity (LAS) distance (DAS) developed on offline training data divide stages identify repeating The equilibrium relationship between variables each stage can be...
The predecessor of China Optics was and Applied Digest, which founded in 1985. At that time, it the only retrieval journal field optics China. end 2008, Digest renamed
As resolution of PET increases, subject movement is becoming a significant factor that limits image quality. It important to develop reconstruction methods can compensate motion. The basic approach we have taken in this work use video cameras track the and information algorithms. We developed direct list-mode algorithm incorporates motion likelihood function. method accurately measured it does not require interpolation either events or reconstructed images. applied experimental data from...
The development of highly efficient light-controlled functional fiber elements has become indispensable to optical communication systems. Traditional nonlinearity-based devices suffer from the demerits complex/expensive components, high peak power requirements, and poor efficiency. In this study, we utilize colloidal quantum dots (CQDs) develop a interferometer (FI) for all-optical control transmission spectrum. A specially designed exposed-core microstructure (ECMF) is utilized form...
Background: Invasive coronary arteriography (ICA) is recognized as the gold standard for diagnosing cardiovascular diseases, including unstable angina (UA). The challenge lies in determining optimal timing ICA UA patients, balancing need revascularization high-risk patients against potential complications low-risk ones. Unlike myocardial infarction, does not have specific indicators like ST-segment deviation or cardiac enzymes, making risk assessment complex. Objectives: Our study aims to...