A Projective Weighted DTW Based Monitoring Approach for Multi-Stage Processes with Unequal Durations

Information Science, Computer Science, Automation, Artificial Intelligence,
Dynamic Time Warping   Multi-Stage Processes   Process Monitoring   Unequal Durations   Projective Weighted  

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...

A Practical Micropipette-Image Calibration Method for Somatic Cell Microinjection

Information Science, Automation, Life Sciences, Cell Biology,
micropipette calibration   somatic cell microinjection   automation technology   micromanipulation   image processing  

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...

Effective Probabilistic Neural Networks Model for Model-Based Reinforcement Learning in USV

Engineering, Information Science, Computer Science, Automation,
Probabilistic Neural Networks   Model Predictive Control   Unmanned Surface Vehicles   Reinforcement Learning   Uncertainty Propagation  

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

Engineering, Mechanical Engineering, Information Science, Automation, Artificial Intelligence,
few-shot learning   degradation modeling   remaining useful life prediction   restricted-learning network   observation credibility inference   engineering systems   data-driven methods  

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...

Oral-Anatomical Knowledge-Informed Semi-Supervised Learning for 3D Dental CBCT Segmentation and Lesion Detection

Information Science, Computer Science, Automation, Medicine, Oral Sciences, Medical Imaging,
dental CBCT   semi-supervised learning   lesion detection   oral-anatomical knowledge   3D image segmentation  

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...