A5103234155- Smart Agriculture and AI
- Neural Networks Stability and Synchronization
- Stability and Control of Uncertain Systems
- Spectroscopy and Chemometric Analyses
- Gene Regulatory Network Analysis
- Adaptive Control of Nonlinear Systems
- Remote Sensing in Agriculture
- Optical Imaging and Spectroscopy Techniques
- stochastic dynamics and bifurcation
- Remote Sensing and Land Use
- Frequency Control in Power Systems
- Visual perception and processing mechanisms
- RNA Research and Splicing
- Remote Sensing and LiDAR Applications
- Mathematical Biology Tumor Growth
- Neural dynamics and brain function
- Leaf Properties and Growth Measurement
- Probiotics and Fermented Foods
- Advanced Control Systems Design
- Distributed Control Multi-Agent Systems
- Stability and Controllability of Differential Equations
- Photoreceptor and optogenetics research
- Infant Nutrition and Health
- Advanced Chemical Sensor Technologies
- Fault Detection and Control Systems
Shandong First Medical University
2024-2025
Hebei Agricultural University
2019-2025
Beijing Academy of Food Sciences
2023-2024
Northeast Agricultural University
2023-2024
Nanjing University of Information Science and Technology
2021-2023
Jilin Engineering Normal University
2023
Northeastern University
2018-2021
State Key Laboratory of Synthetical Automation for Process Industries
2018-2021
Dalian University of Technology
2021
Heilongjiang University
2016-2018
This paper is centered upon the state estimation for delayed genetic regulatory networks. Our aim at estimating concentrations of mRNAs and proteins by designing reduced-order full-order observers based on available network outputs. We introduce a Lyapunov-Krasovskii functional including quadruplicate integrals, estimate its derivative employing Wirtinger-type integral inequalities, reciprocal convex technique, technique. From which, delay-dependent sufficient conditions, in form linear...
Traditionally, the classification of seed defects mainly relies on characteristics color, shape, and texture. This method requires repeated extraction a large amount feature information, which is not efficiently used in detection. In recent years, deep learning has performed well field image recognition. We introduced convolutional neural networks (CNNs) transfer into quality seeds compared them with traditional machine algorithms. Experiments showed that algorithm was significantly better...
This paper is concerned with the finite-time stability problem of delayed genetic regulatory networks (GRNs) reaction-diffusion terms under Dirichlet boundary conditions. By constructing a Lyapunov-Krasovskii functional including quad-slope integrations, we establish delay-dependent criteria by employing Wirtinger-type integral inequality, Gronwall convex technique, and reciprocally technique. In addition, obtained are also reaction-diffusion-dependent. Finally, numerical example provided to...
This article investigates the stability analysis and stabilization problems for fractional-order T–S fuzzy systems via Lyapunov function method. A membership-function-dependent instead of general quadratic is employed to obtain criteria. Different from function, functions contain product three term functions. Since Leibniz formula cannot be satisfied fractional derivative, current results on derivative extended Therefore, estimate functions, rule proposed. Based proposed rule, corresponding...
Potato early blight and late are devastating diseases that affect potato planting production. Thus, precise diagnosis of the is critical in treatment application management farm. However, traditional computer vision technology pattern recognition methods have certain limitations detection crop diseases. In recent years, development deep learning convolutional neural networks has provided new solutions for rapid accurate this study, an integrated framework combines instance segmentation...
Corn seed materials of different quality were imaged, and a method for defect detection was developed based on watershed algorithm combined with two-pathway convolutional neural network (CNN) model. In this study, RGB near-infrared (NIR) images acquired multispectral camera to train the model, which proved be effective in identifying defective seeds defect-free seeds, an averaged accuracy 95.63%, recall rate 95.29%, F1 (harmonic average evaluation) 95.46%. Our proposed superior traditional...
Broccoli is a highly nutritious vegetable that favored worldwide. Assessing and predicting the shelf life of broccoli holds considerable importance for effective resource optimization management. The physicochemical parameters spectral characteristics are important indicators partially reflecting its life. However, few studies have used image information to predict evaluate broccoli. In this study, multispectral imaging combined with multi-feature data fusion was Spectral textural features...
This study focuses on the discrete-time sliding mode control (SMC) based event-triggered approach for singular system. The purpose is to design a SMC law under ensure that system admissible. A novel surface constructed, and sufficient condition, in form of linear matrix inequality (LMI), investigated guarantee admissibility One can verify this condition by utilising toolbox YALMIP MATLAB. In addition, expected controller gain be represented feasible solution LMI. Then, above solved gain, new...
An event-triggered sliding-mode control problem is investigated for a class of multiple-input Takagi-Sugeno (T-S) fuzzy systems via designing linear switching function. assumption that all local share common input matrix removed. Then, novel controller with asynchronous premise variables designed, which can ensure the trajectory T-S be driven onto region near sliding surface after finite time. A sufficient condition established to guarantee stability motion, and gain obtained by solving set...
The phenotypic parameters of crop plants can be evaluated accurately and quickly using an unmanned aerial vehicle (UAV) equipped with imaging equipment. In this study, hundreds images Chinese cabbage (Brassica rapa L. ssp. pekinensis) germplasm resources were collected a low-cost UAV system used to estimate width, length, relative chlorophyll content (soil plant analysis development [SPAD] value). super-resolution generative adversarial network (SRGAN) was improve the resolution original...
In the process of rice production and storage, there are many defects in traditional detection methods appearance quality, but using modern high-precision instruments to detect quality has gradually developed into a new research trend at home abroad with development agricultural artificial intelligence.In this study, we independently designed fast automatic system based on machine vision technology by introducing convolutional neural network image processing technology. NIR RGB images were...
Abstract Background Pepper Phytophthora blight is a devastating disease during the growth process of peppers, significantly affecting their yield and quality. Accurate, rapid, non-destructive early detection pepper great importance for production management. This study investigated possibility using multispectral imaging combined with machine learning to detect in peppers. Peppers were divided into two groups: one group was inoculated blight, other left untreated as control. Multispectral...
A pupillary light reflex (PLR) model was proposed in this paper by considering the iris muscle mechanical properties and modulation inputs from both parasympathetic sympathetic systems. The can describe very well experimental PLR responses induced a short flash of various intensities. In addition, an inverse method developed to fit numerically data. tested human data extract separately modulations during PLR. results indicated higher lower activity females than males, which consistent with...
Existing maize production is grappling with the hurdles of not applying nitrogen fertilizer accurately due to subpar detection accuracy and responsiveness. This situation presents a significant challenge, as it has potential impact optimal yield ultimately, profit margins associated its cultivation. In this study, an automatic modeling prediction method for content in leaves was proposed based on machine vision convolutional neural network. We developed program designed streamline image...