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...

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...

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...

AI Explanation Type Affects Physician Diagnostic Performance and Trust in AI

Information Science, Computer Science, Artificial Intelligence, Medicine, Medical Imaging,
Artificial Intelligence   Chest Radiograph   Diagnostic Performance   Physician Trust   Explanation Type  

The Impact of AI Explanation Types on Physician Diagnostic Performance and Trust Academic Background In recent years, the development of artificial intelligence (AI) diagnostic systems in healthcare and radiology has progressed rapidly, particularly in assisting overburdened healthcare providers, showcasing the potential to improve patient care. As...

Precision Autofocus in Optical Microscopy with Liquid Lenses Controlled by Deep Reinforcement Learning

Physics, Optics, Engineering, Mechanical Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence,
microscopy   autofocus   liquid lens   deep reinforcement learning   optical system  

Precision Autofocus in Optical Microscopy with Liquid Lenses Controlled by Deep Reinforcement Learning Academic Background Microscopic imaging plays a crucial role in scientific research, biomedical studies, and engineering applications. However, traditional microscopes and autofocus techniques face hardware limitations and slow software speeds in ...

Parallel Mechanical Computing: Metamaterials That Can Multitask

Materials Science, Information Science, Computer Science,
parallel computing   metamaterials   mechanical computing   frequency multiplexing   wave-based computing  

Parallel Mechanical Computing: Metamaterials That Can Multitask Academic Background Decades after being replaced by digital computing platforms, analog computing has regained significant interest due to advancements in metamaterials and intricate fabrication techniques. Particularly, wave-based analog computers, which perform spatial transformation...

Basis Restricted Elastic Shape Analysis Framework for Surfaces

Mathematics, Physics, Mechanics, Information Science, Computer Science, Artificial Intelligence,
Elastic Shape Analysis   Surface Meshes   Geometric Deep Learning   Riemannian Shape Metrics   Human Body Analysis   Shape Registration   Random Shape Generation  

# Basis Restricted Elastic Shape Analysis on the Space of Unregistered Surfaces ## Introduction Analyzing three-dimensional (3D) surfaces has become increasingly important in computer vision, driven by the emergence of high-accuracy 3D scanning devices. These devices have significantly increased the availability of 3D data, enabling applications in...

Improving 3D Finger Traits Recognition via Generalizable Neural Rendering

Engineering, Electrical Engineering, Materials Science, Information Science, Electronic Information, Computer Science, Artificial Intelligence, Life Sciences, Bioengineering,
3D fingerprint recognition   neural rendering   finger biometrics   3D biometric traits   multi-modal biometrics  

Summary of FingerNeRF-Based 3D Finger Biometrics Research Report Background and Research Significance With the advancement of biometric technologies, three-dimensional (3D) biometrics have become a promising research direction due to their higher accuracy, robust anti-spoofing capabilities, and resistance to variations in capture angles. Among thes...

A Memory-Assisted Knowledge Transferring Framework with Curriculum Anticipation for Weakly Supervised Online Activity Detection

Engineering, Electrical Engineering, Information Science, Electronic Information, Computer Science, Artificial Intelligence,
weakly supervised learning   online activity detection   knowledge distillation   memory networks   curriculum learning  

Research Background and Significance In recent years, weakly supervised online activity detection (WS-OAD), as an important topic in high-level video understanding, has garnered widespread attention. Its primary goal is to detect ongoing activities frame-by-frame in streaming videos using only inexpensive video-level annotations. This task holds si...