A5101570687- Complex Network Analysis Techniques
- Advanced Graph Neural Networks
- Opinion Dynamics and Social Influence
- scientometrics and bibliometrics research
- Advanced Memory and Neural Computing
- Data Mining Algorithms and Applications
- Optimization and Search Problems
- Radar Systems and Signal Processing
- Cellular Automata and Applications
- Optimization and Packing Problems
- Big Data Technologies and Applications
- Technology Assessment and Management
- Quantum Computing Algorithms and Architecture
- Information and Cyber Security
- Advanced X-ray Imaging Techniques
- Functional Brain Connectivity Studies
- Technology and Data Analysis
- Software System Performance and Reliability
- Technology and Security Systems
- Outsourcing and Supply Chain Management
- Diverse Approaches in Healthcare and Education Studies
- Artificial Immune Systems Applications
- Scheduling and Optimization Algorithms
- Graph theory and applications
- Data Stream Mining Techniques
Sichuan International Studies University
2023-2024
National University of Defense Technology
2006-2024
Xiangtan University
2023
Institute of Advanced Science Facilities, Shenzhen
2022
Wuhan University
2021
Center for Strategic and International Studies
2018
Shenzhen Institutes of Advanced Technology
2013
Yong In University
2010
Hunan Institute of Technology
2008
Betweenness centrality (BC) is a widely used measures for network analysis, which seeks to describe the importance of nodes in terms fraction shortest paths that pass through them. It key many valuable applications, including community detection and dismantling. Computing BC scores on large networks computationally challenging due its high time complexity. Many sampling-based approximation algorithms have been proposed speed up estimation BC. However, these methods still need considerable...
Betweenness centrality (BC) is one of the most used measures for network analysis, which seeks to describe importance nodes in a terms fraction shortest paths that pass through them. It key many valuable applications, including community detection and dismantling. Computing BC scores on large networks computationally challenging due high time complexity. Many approximation algorithms have been proposed speed up estimation BC, are mainly sampling-based. However, these methods still prone...
Network dismantling is one of the most challenging problems in complex systems. This problem encompasses a broad array practical applications. Previous works mainly focus on metrics such as number nodes Giant Connected Component (GCC), average pairwise connectivity, etc. paper introduces novel metric, accumulated 2-core size, for assessing network dismantling. Due to NP-hard computational complexity this problem, we propose SmartCore, an end-to-end model minimizing size by leveraging...
The problem of finding key players in a graph, also known as network dismantling, or disintegration, aims to find an optimal removal sequence nodes (edges, substructures) through certain algorithm, ultimately causing functional indicators such the largest connected component (GCC) pair connectivity graph rapidly decline. As typical NP-hard on graphs, recent methods based reinforcement learning and representation have effectively solved problems. However, existing reinforcement-learning-based...
Abstract Understanding and improving the robustness of networks has significant applications in various areas, such as bioinformatics, transportation, critical infrastructures, social networks. Recently, there been a large amount work on network dismantling, which focuses removing an optimal set nodes to break into small components with sub-extensive sizes. However, our experiments, we found these state-of-the-art methods, although seemingly different, utilize same refinement technique,...
X-ray free-electron lasers (FELs) provide cutting-edge tools for fundamental researches to study nature down the atomic level at a time-scale that fits this resolution. A precise knowledge of temporal information FEL pulses is central issue its applications. Here we proposed and demonstrated novel method determine profiles online. This robust method, designed ultrafast FELs, allows researchers acquire real-time longitudinal as well their arrive times with respect external optical laser...
Tackling the intricacies of network dismantling in complex systems poses significant challenges. This task has relevance across various practical domains, yet traditional approaches focus primarily on singular metrics, such as number nodes Giant Connected Component (GCC) or average pairwise connectivity. In contrast, we propose a unique metric that concurrently targets with highest degree and reduces GCC size. Given NP-hard nature optimizing this metric, introduce MaxShot, an innovative...
Tackling the intricacies of network dismantling in complex systems poses significant challenges. This task has relevance across various practical domains, yet traditional approaches focus primarily on singular metrics, such as number nodes Giant Connected Component (GCC) or average pairwise connectivity. In contrast, we propose a unique metric that concurrently targets with highest degree and reduces GCC size. Given NP-hard nature optimizing this metric, introduce MaxShot, an innovative...
Cyberspace is a global and dynamic domain characterized by the combined use of electrons electromagnetic spectrum, whose purpose to create, store, modify, exchange, share extract, use, eliminate information disrupt physical resources. In this study we adopt comprehensive bibliometric approach analyze literature with aim quantitatively identifying current landscape trends on Cyberspace, which consists scientific outputs analysis (year, document type, subject categories, Countries,...