Self-Model-Free Learning versus Learning with External Rewards in Information-Constrained Environments

Information Science, Computer Science, Artificial Intelligence,
Reinforcement Learning   Information Loss   Adversarial Learning   Jamming Attacks   Autonomous Decision Making  

Self-Model-Free Learning vs. Learning with External Rewards in Information-Constrained Environments: A New Reinforcement Learning Framework In recent years, with the development of networks and artificial intelligence systems, networked learning mechanisms face significant security challenges. In the domain of reinforcement learning (RL), the loss ...

Spatio-Temporal Graph-Based Generation and Detection of Adversarial False Data Injection Evasion Attacks in Smart Grids

Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence,
smart grids   false data injection attacks   adversarial attacks   spatio-temporal graphs   graph neural networks   machine learning   cybersecurity  

Title: Generating and Detecting Spatio-Temporal Graph-Based Adversarial False Data Injection Evasion Attacks in Smart Grids Background With the continuous development of modern smart grids, the grid, as a typical Cyber-Physical System (CPS), faces numerous security threats due to the extensive exchange of data between its components. Among these, F...

Partial Domain Adaptation for Building Borehole Lithology Model Under Weaker Geological Prior

Earth Sciences, Geochemistry, Geology, Geophysics, Information Science, Automation, Artificial Intelligence,
lithology identification   partial domain adaptation   sample transferability weighting   convolutional neural network   channel attention mechanism   target sample reconstruction   geological exploration  

Report on the Paper: “Partial Domain Adaptation for Building Borehole Lithology Model Under Weaker Geological Prior” Background and Research Problem Lithology identification plays a critical role in stratigraphic characterization and reservoir exploration. However, existing AI and machine learning-based lithology identification methods face substan...

Simplified Kernel-Based Cost-Sensitive Broad Learning System for Imbalanced Fault Diagnosis

Engineering, Mechanical Engineering, Information Science, Computer Science, Artificial Intelligence,
fault diagnosis   imbalanced data   broad learning system   cost-sensitive learning   kernel mapping  

Research Report on the Simplified Kernel-Based Cost-Sensitive Broad Learning System (SKCSBLS) for Imbalanced Fault Diagnosis Research Background and Significance With the advent of Industry 4.0, smart manufacturing increasingly relies on industrial big data analytics. By extracting critical insights from machine operation data, the effectiveness of...

Event-Triggered Fuzzy Adaptive Stabilization of Parabolic PDE–ODE Systems

Mathematics, Engineering, Electrical Engineering, Information Science, Automation, Artificial Intelligence,
Event-Triggered Control   Fuzzy Logic Systems   Parabolic PDE-ODE Systems   Stabilization Control   Adaptive Backstepping  

Scientific Report: On “Event-Triggered Fuzzy Adaptive Stabilization of Parabolic PDE–ODE Systems” Research Background and Significance In modern engineering systems, such as flexible manipulators, heat transfer devices, and reactor controllers, many complex systems must be modeled using partial differential equations (PDEs). Due to their unique rea...

Optimal Control of Stochastic Markovian Jump Systems with Wiener and Poisson Noises: Two Reinforcement Learning Approaches

Mathematics, Engineering, Information Science, Computer Science, Artificial Intelligence,
Stochastic Markovian Jump Systems   Wiener Noise   Poisson Noise   Reinforcement Learning   Optimal Control   Policy Iteration Algorithm   Numerical Verification  

Optimal Control of Stochastic Markovian Jump Systems with Wiener and Poisson Noises: Two Reinforcement Learning Approaches Academic Context In modern control theory, optimal control is a crucial research field, aiming to design an optimal control strategy under various constraints for dynamic systems to minimize a given cost function. For stochasti...

Intelligent Headset System with Real-Time Neural Networks for Creating Programmable Sound Bubbles

Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence,
intelligent headset   sound bubble   real-time neural networks   noise cancellation   distance perception   embedded CPU   acoustic scene  

Discussion of “Sound Bubbles” and the Future of Hearable Devices: Innovations Based on Real-Time Neural Networks In daily life, noise and complex acoustic scenes often make speech difficult to distinguish, particularly in crowded environments such as restaurants, conference rooms, or airplanes. While traditional noise-canceling headphones can suppr...

Reconfigurable In-Sensor Processing Based on a Multi-Phototransistor–One-Memristor Array

Chemistry, Nanoscience, Engineering, Electrical Engineering, Materials Science, Information Science, Semiconductors and Information Devices, Artificial Intelligence,
in-sensor computing   photonic memristors   neural network architectures   image processing   machine vision  

Report on the Academic Paper: “Reconfigurable In-Sensor Processing Based on a Multi-Phototransistor-One-Memristor Array: A New Visual Computing Platform Combining Machine Learning and Brain-Inspired Neural Networks” Academic Background and Problem Identification Artificial vision systems play a significant role in intelligent edge computing. Howeve...

A Wearable Echomyography System Based on a Single Transducer

Engineering, Electrical Engineering, Information Science, Artificial Intelligence, Medicine, Respiratory System, Neurology, Medical Imaging, Life Sciences, Bioengineering,
wearable devices   echomyography   single transducer   deep learning   muscle activity monitoring   wireless circuit   ultrasound  

Innovative Advances in Wearable Single-Transducer Echomyography Systems: From Muscle Dynamics Monitoring to Complex Gesture Tracking Academic Background and Research Significance In recent years, wearable electronic devices have garnered significant attention for their enormous potential in health monitoring and human-machine interaction. Electromy...

Memristors with Analogue Switching and High On/Off Ratios Using a Van der Waals Metallic Cathode

Physics, Chemistry, Nanoscience, Engineering, Electrical Engineering, Materials Science, Information Science, Semiconductors and Information Devices, Artificial Intelligence,
memristor   van der Waals metal   analogue switching   high on/off ratio   neuromorphic computing   silver ion intercalation   low power consumption  

Research on Analog Memristors with Large On/Off Ratios Using 2D Van der Waals Metallic Cathodes Academic Background With the rapid development of artificial intelligence (AI) applications, traditional Von Neumann architectures are facing performance bottlenecks in data-intensive computing tasks. Neuromorphic computing is an emerging paradigm capabl...