Yilun Shang

Dr. Yilun Shang

Computer and Information Sciences, Northumbria University, Newcastle upon Tyne NE1 8ST, UK
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Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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16 January 2021 in Symmetry
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Kinkar Chandra DasKinkar Chandra Das
Kinkar Chandra Das
Ahmet Sinan CevikAhmet Sinan Cevik
Ahmet Sinan Cevik
Ismail Naci CANGULIsmail Naci CANGUL
Ismail Naci CANGUL
Yilun ShangYilun Shang
Yilun Shang
The concept of Sombor index (SO) was recently introduced by Gutman in the chemical graph theory. It is a vertex-degree-based topological index and is denoted by Sombor index SO: SO=SO(G)=∑vivj∈E(G)dG(vi)2+dG(vj)2, where dG(vi) is the degree of vertex vi in G. Here, we present novel lower and upper bounds on the Sombor index of graphs by using some graph parameters. Moreover, we obtain several relations on Sombor index with the first and second Zagreb indices of graphs. Finally, we give some conclusions and propose future work.

1 March 2017 in Information Sciences
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YLYusheng Li
Yusheng Li
Yilun ShangYilun Shang
Yilun Shang
YYYiting Yang
Yiting Yang

15 August 2017 in IEEE Transactions on Systems, Man, and Cybernetics: Systems
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Yilun ShangYilun Shang
Yilun Shang
Network measures derived from empirical observations are often poor estimators of the true structure of system as it is impossible to observe all components and all interactions in many real world complex systems. Here, we study attack robustness of complex networks with data missing caused by: 1) a uniform random sampling and 2) a nonuniform random sampling. By introducing the subgraph robustness problem, we develop analytically a framework to investigate robustness properties of the two types of subgraphs under random attacks, localized attacks, and targeted attacks. Interestingly, we find that the benchmark models, such as Erdos-Rényi graphs, random regular networks, and scale-free networks possess distinct characteristic subgraph robustness features. We show that the network robustness depends on several factors including network topology, attack mode, sampling method and the amount of data missing, generalizing some well-known robustness principles of complex networks. Our results offer insight into the structural effect of missing data in networks and highlight the significance of understanding different sampling processes and their consequences on attack robustness, which may be instrumental in designing robust systems.

1 December 2018 in Systems & Control Letters
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Yilun ShangYilun Shang
Yilun Shang

1 March 2012 in International Journal of Systems Science
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Yilun ShangYilun Shang
Yilun Shang
In this article, we study finite-time state consensus problems for continuous multi-agent systems with nonlinear protocols. Building on the theory of finite-time Lyapunov stability, we propose sufficient criteria which guarantee the system to reach a consensus in finite time, provided that the underlying directed network contains a spanning tree. Novel finite-time consensus protocols are introduced as examples for applying the criteria. Simulations are also presented to illustrate our theoretical results.

7 February 2023 in Mathematics
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Muhammad AzeemMuhammad Azeem
Muhammad Azeem
Muhammad Kamran JamilMuhammad Kamran Jamil
Muhammad Kamran Jamil
Yilun ShangYilun Shang
Yilun Shang
The act of accessing the exact location, or position, of a node in a network is known as the localization of a network. In this methodology, the precise location of each node within a network can be made in the terms of certain chosen nodes in a subset. This subset is known as the locating set and its minimum cardinality is called the locating number of a network. The generalized hexagonal cellular network is a novel structure for the planning and analysis of a network. In this work, we considered conducting the localization of a generalized hexagonal cellular network. Moreover, we determined and proved the exact locating number for this network. Furthermore, in this technique, each node of a generalized hexagonal cellular network can be accessed uniquely. Lastly, we also discussed the generalized version of the locating set and locating number.