Application of Robust Fuzzy Cooperative Strategy in Global Consensus of Stochastic Multi-Agent Systems

Research on Global Consensus of Stochastic Multi-Agent Systems Based on Robust Fuzzy Cooperative Strategy Academic Background In modern technological fields such as automation, robotics, network communication, intelligent transportation systems, and distributed decision-making, Multi-Agent Systems (MAS) play a crucial role. MAS can efficiently exec...

Distributed Intelligent Control Method Based on State Self-Learning and Its Application in Cascade Processes

Research on Distributed Intelligent Control Method Based on State Self-Learning and Its Application in Cascade Processes Academic Background In the process industry, multi-reactor cascade operation is a distinctive characteristic. However, establishing an accurate and global model for multi-reactor cascade processes presents numerous challenges. Th...

Resource-Efficient Decentralized Sequential Planner for Spatiotemporal Wildfire Mitigation

Efficient Decentralized Sequential Planner for Spatiotemporal Wildfire Mitigation Using Multiple UAVs Academic Background Wildfires pose a significant threat to global biodiversity and resource sustainability, especially in their early stages. If not controlled in time, wildfires can rapidly expand, leading to severe ecological damage. In recent ye...

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

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 Restricted-Learning Network with Observation Credibility Inference for Few-Shot Degradation Modeling

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...

Influence of Visual-Inertial Sensor-to-Segment Calibration on Upper Limb Joint Angles Estimation

Influence of Visual-Inertial Sensor-to-Segment Calibration on Upper Limb Joint Angles Estimation

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-Task Aquatic Toxicity Prediction Model Based on Multi-Level Features Fusion

Academic Background With the growing threat of organic compounds to environmental pollution, studying the toxic responses of different aquatic organisms to these compounds has become crucial. Such research not only helps assess the potential ecological impacts of pollutants on the overall aquatic ecosystem but also provides significant scientific f...

Deep-Learning-Enhanced Metal-Organic Framework E-Skin for Health Monitoring

Deep Learning-Enhanced Metal-Organic Framework E-Skin for Health Monitoring Academic Background Electronic skin (e-skin) is a technology capable of sensing physiological and environmental stimuli, mimicking human skin functions. In recent years, the potential applications of e-skin in fields such as robotics, sports science, and healthcare monitori...

An Inkjet-Printable Organic Electrochemical Transistor Array with Differentiated Ion Dynamics for Sweat Fingerprint Identification

An Inkjet-Printable Organic Electrochemical Transistor Array with Differentiated Ion Dynamics for Sweat Fingerprint Identification

Sweat Fingerprint Identification Technology Based on Ion Dynamics: Research on Inkjet-Printed Organic Electrochemical Transistor Arrays Academic Background Sweat, as a non-invasive biomarker, contains rich physiological information that can reflect human health conditions, such as hydration balance and disease markers. However, sweat has complex co...

Resistive Memory-Based Zero-Shot Liquid State Machine for Multimodal Event Data Learning

Novel Resistive Memory-Driven Zero-Shot Multimodal Event Learning System: A Report on Hardware-Software Co-Design Academic Background The human brain is a complex spiking neural network (SNN) capable of zero-shot learning in multimodal signals with minimal power consumption, allowing generalization of existing knowledge to address new tasks. Howeve...