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

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

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

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

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

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

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...