IEEE

A Graph Deep Reinforcement Learning Traffic Signal Control for Multiple Intersections Considering Missing Data

Abstract: Efficient traffic signal control (TSC) for multiple intersections is an important way to solve traffic congestion. With the development of deep reinforcement learning (DRL), an increasing ...
IEEE

Partitioning-based Graph Signal Denoising via Heat Kernel Smoothing

Abstract: The objective of graph signal denoising is to extract a clean signal from a noisy dataset while maintaining the graph's inherent structure. Dealing with large-scale graphs introduce ...
IEEE

Optimal Power Flow With Regression-Based Small-Signal Stability Constraints

Abstract: In modern power systems, with a growing integration of inverter-based resources, small-signal stability is becoming increasingly important. However, current practice in operation and ...
IEEE

Automated Vulnerability Detection in Smart Contracts using Control Flow Graphs and Machine Learning

Abstract: The security of smart contracts, a fundamental component of decentralized applications (dApps) on blockchain platforms, remains a critical concern due to the risk of severe financial losses ...
IEEE

Multi-Modal Graph Neural Networks for Physiological Signal Analysis

Abstract: A critically important application for physiological signal analysis lies in very early diagnosis and monitoring of potential medical conditions: among others, in cardiac dysfunction. This ...
Science Daily

A hidden brain signal may reveal Alzheimer’s long before diagnosis

Researchers have discovered a brain activity pattern that can predict which people with mild cognitive impairment are likely to develop Alzheimer’s disease. Using a noninvasive brain scanning ...
IEEE

A Heterogeneous Graph Reinforcement Learning Framework With Question-Aware Neighborhood Aggregation and Interoption Prompt Attention for Dynamic Flexible Job Shop Scheduling ...

Abstract: Dynamic flexible job shop scheduling (DFJSS) problem is an important scenario in intelligent manufacturing domain with the requirement of real-time decision-making under complex constraints.
IEEE

GTPCR: Graph-Enhanced Transformer for Point Cloud Registration

Abstract: As Industry 4.0 continues to advance, point cloud registration technology is extensively employed in scenarios such as collaborative defect detection in products and digital twin-assisted ...
19 KYTX

HEATING UP Five Out of Six Points for Utah Mammoth—Does This Homestand Signal Playoff SUCCESS?

HEATING UP Five Out of Six Points for Utah Mammoth—Does This Homestand Signal Playoff SUCCESS? To stream CBS19 on your phone, you need the CBS19 app.
IEEE

When Knowledge Graph Meets Retrieval Augmented Generation for Wireless Networks: A Tutorial and Case Study

Abstract: This paper investigates a GraphRAG framework that integrates knowledge graphs into the Retrieval-Augmented Generation (RAG) architecture to enhance networking applications. While RAG has ...
IEEE

Point-Estimate Method for Probabilistic Power Flow in Unbalanced and Distorted Distribution Systems

Abstract: In this paper, a probabilistic power flow (PPF) for unbalanced and distorted distribution systems based on the Point-Estimate Method (PEM) is proposed. The uncertainties of loads and ...
Wired

AI Models Are Starting to Learn by Asking Themselves Questions

An AI model that learns without human input—by posing interesting queries for itself—might point the way to superintelligence. Save this story Save this story Even the smartest artificial intelligence ...