Designing random nanofiber networks, optimized for strength and toughness

In nature, random fiber networks such as some of the tissues in the human body, are strong and tough with the ability to hold ...
IEEE

Bayesian Meta Random Graph Implicit Enhanced Network for Lithium-Ion Batteries Remaining Useful Life Prediction With Few-Shot and Uncertainty Interference

Abstract: Accurately predicting and evaluating the remaining useful life (RUL) of lithium-ion batteries (LIBs) is of great significance to develop a maintenance program for replacing batteries ...

Python-based framework makes climate dynamics more approachable for students and researchers

A team of researchers at the University of Miami has developed a global atmospheric modeling framework that blends powerful ...
Frontiers

Network modelling in analysing cyber-related graphs

To improve the resilience of the computer network infrastructure against cyber attacks or causal influences and find ways to mitigate their impact, we need to understand their structure and dynamics.
IEEE

Multi-View Enhancement Graph-Level Clustering Network

Abstract: Graph-level clustering is a fundamental and significant task in data mining. The advancement of graph neural networks has provided substantial impetus to this area of research. However, ...
GitHub

Python Network Security Scanner

A high-performance, multi-threaded network security scanner built in Python. This tool performs comprehensive TCP port scanning, service enumeration through banner grabbing, and HTTP security header ...
GitHub

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

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 ...