Projective Weighted Dynamic Time Warping-Based Monitoring Method for Multi-Stage Processes with Unequal Durations Academic Background In modern manufacturing industries, online monitoring of multi-stage processes (such as batch and transition processes) is crucial for improving product quality and reducing failure risks. However, due to varying ope...
Micropipette-Image Calibration Method Based on Micromanipulation System for Somatic Cell Microinjection Research Background Microinjection is a technique that employs a fine micropipette to inject a precise amount of genetic material, drugs, or other exogenous substances directly into cells or tissues. This technology plays a pivotal role in biomed...
A New Approach to Model Predictive Control for Unmanned Surface Vehicles (USV): A Probabilistic Neural Network-Based MBRL Framework Academic Background Unmanned Surface Vehicles (USVs) have seen rapid development in recent years within the field of marine science, finding extensive applications in scenarios such as marine transportation, environmen...
A Restricted-Learning Network with Observation Credibility Inference for Few-Shot Degradation Modeling Academic Background In complex engineering systems, multiple sensors are widely used to monitor the degradation processes of equipment and predict their Remaining Useful Life (RUL). However, ensuring predictive performance remains challenging when...
Academic Background and Research Motivation In the field of dental healthcare, Cone Beam Computed Tomography (CBCT) is a widely used three-dimensional imaging technique. CBCT provides three-dimensional images of the oral cavity and is particularly effective in diagnosing odontogenic lesions. However, the segmentation of CBCT images—labeling each vo...
Research on Upper Limb Joint Angle Estimation Based on Visual-Inertial Sensors and the Impact of Calibration Methods Academic Background Upper limb dysfunction, especially in post-stroke patients, significantly impacts their ability to perform daily activities. Rehabilitation training is a critical method for restoring upper limb function, but its ...
Multi-agent Cooperative Navigation in Hybrid Environments: A New Reinforcement Learning Approach Based on Relational Graph Learning Mobile robotics is witnessing a surge in applications, fueled by advancements in artificial intelligence, with navigation capabilities being one of the core focus areas of research. Traditional navigation methods often...
Nonlinear Fixed-Time Reinforcement Learning Optimized Control for Intelligent Ship Autopilots In recent years, intelligent autopilot technology has gradually become a research hotspot in the field of automation control. For complex nonlinear systems, the design of optimized control strategies, especially the achievement of system stability and perf...
Preference Prediction-Based Evolutionary Multiobjective Optimization for Gasoline Blending Scheduling Background Introduction With the continuous evolution of the global energy market, gasoline production and blending processes face increasing challenges. As a key product of the oil industry, gasoline’s blending and scheduling processes directly af...
Breakthrough Research in Multiobjective Dynamic Flexible Job Shop Scheduling: An Innovative Approach to Optimize Biased Objectives via Multitask Learning in Genetic Programming Background Introduction Dynamic Flexible Job Shop Scheduling (DFJSS) is an essential combinatorial optimization problem with extensive real-world applications in areas such ...