Abstract: Fault location and classification are crucial to the reliable and resilient operation of power distribution networks (PDNs). Current machine learning works cannot provide accurate and ...

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

ABSTRACT: This study proposes a decentralized urban traffic optimization approach by integrating Dijkstra’s algorithm with edge computing. The system models road networks as dynamic graphs, using real ...

Large Language Models (LLMs) have revolutionized many areas of natural language processing, but they still face critical limitations when dealing with up-to-date facts, domain-specific information, or ...

Introduction: Emotion recognition based on electroencephalogram (EEG) signals has shown increasing application potential in fields such as brain-computer interfaces and affective computing. However, ...

Sainsbury Wellcome Centre, University College London, United Kingdom; Department of Neuroscience, Physiology and Pharmacology, University College London, United Kingdom; ...

pyCirclizely is a circular visualization python package refactored from pyCirclize to use plotly instead of matplotlib, which in turn was inspired by circlize and pyCircos. It includes useful genome ...