Projects  |  Complex Networks  |  Power Electronics

Complex Networks and Applications

New Network-based Models for Power System’s Robustness Assessment and Cascading Failure Simulation — Our model is able to capture the salient characteristics of cascading failure patterns consistent with all historical blackout data. IEEEXplore Innovation Spotlight featured our work in November 2015.

Key Reference:

X. Zhang, C. Zhan, and C. K. Tse, "Modeling the dynamics of cascading failures in power systems," IEEE Journal on Emerging and Selected Topics in Circuits and Systems, vol. 6, no. 2, pp. 192-204, June 2017. [Link to IEEEXplore]

Our Universal Growth Equation describes how user population of products and services, membership subscriptions, even your publications and citations, grow as time goes. — We derive from first principle a growth equation that fits all data of growing user population, such as Facebook signups, electronic products, services, app downloads, and virtually everything that grows as time goes, like the number of papers you publish and the number of times your papers get cited. If x(t) is the quantity of the item you are interested in, it will grow according to

where c1 and c2 are growth parameters corresponding to personal decision and peer influence, respectively, and N is the total potential user population. The basis of our theory is a network of people who make decision on whether to sign up for a service or use a product according to the individuals’ independent judgement as well as peer influence. Statistical analysis is used to derive the above growth equation.

Key Reference:

C. Zhan and C.K. Tse, "A universal model for growth of user population of products and services," Network Science, vol. 4, no. 4, pp. 491-507, December 2016. [Link to Publisher]

Communication Network Design and Performance — Research on complex networks has been a subject of rigorous theoretical research in the mathematics and physics research communities in the past decade. The many discoveries that human interactions, man-made and natural networks share a power-law degree distribution and small-world property have clearly indicated a high level of relevance of the study of complex networks with real-world applications. However, progress in applying the theoretical results to solving practical problems is still slow. In this project we develop useful insights into how performance of communication networks is related to the key network properties. One breakthrough is the introduction of NODE USAGE PROBABILITY and the unified viewpoint of the factors affecting congestion and network throughput.

Key Reference:

J. Wu, C. K. Tse, F. C. M. Lau and I. W. H. Ho, "Analysis of communication network performance from a complex network perspective," IEEE Transactions on Circuits and Systems I: Regular Papers, vol. 60, no. 12, pp. 3303-3316, December 2013.

Applications in Finance — In this project we apply results of complex networks research in real-world problems. The emphasis is on how complex networks would provide a new perspective on the way problems can be formulated, leading to possible new solution approaches. Examples in engineering, disease transmission, language, music and finance are given. Our recent work: “A Network Perspective of Stock Market”


Key References:

C. K. Tse, J. Liu, and F. C. M. Lau, “A network perspective of stock markets,” Journal of Empirical Finance, vol. 17, no. 4, pp. 659-667, September 2010. [Download]

Modeling Disease Propagation with Complex Networks (with Michael Small (UWA))  — In the Spring of 2003, an epidemic outbreak of an unknown virus affected a few Asian cities (beginning in Guangzhou, propagating to Beijing, and spreading through Hong Kong to Vietnam, Toronto, Singapore and Taiwan), claiming the lives of hundreds and infecting thousands of people. In this project we attempt to model the propagation of the now called SARS virus in terms of small-world networks. The model has been found able to fit the Hong Kong data very well. Based on this model we are able to develop predictive software to aid the prediction and control of the propagation of this disease.

Key References:

M. Small, C. K. Tse and D. M. Walker, "Super-spreaders and the rate of transmission of the SARS virus," Physica D, vol. 215, pp. 146-158, March 2006.

M. Small, D. M. Walker and C. K. Tse, "Scale free distribution of avian influenza outbreaks," Physical Review Letters, vol. 99, 188702, November 2007.

Creating Appealing Music with Complex Networks — We find that musical scores which are widely perceived to be "good" generate complex networks with certain invariant properties: scale-free networks with strong clustering of nodes within the network. We describe a method to generate random musical compositions from these networks (essentially, as a weighted random walk on the network) and find that scores generated in this manner are also perceived to be "good" and are qualitatively similar to the specific score from which the generating network was produced.

Key References:
X. Liu, C. K. Tse, and M. Small, "Complex network structure of musical compositions: Algorithmic generation of appealing music," Physica A, vol. 389, no. 1, pp. 126-132, January 2010.

Other Research Projects

Wireless Sensor Network Applications — We study the practical factors affecting performance of wireless sensor networks, including routing, power saving, scheduling, and data fusion, and derive effective methods for transferring data through the networks.

Traffic Network Modelling — We study the metro systems of major cities and apply concepts from network science to identify the relative advantages and disadvantages of certain network properties relevant to traffic performance. (See: X. Wu, H. Dong, C. K. Tse, I. W-H. Ho, and F. C. M. Lau, "Analysis of metro network performance from a complex network perspective," Physica A, vol. 492, pp. 553-563, February, 2018.)

Coding — Theoretical analysis and decoder design of a novel class of quasi-cyclic low-density parity-check block codes with extremely low error floor have been pursued.

The Flying Drones FYP Project

This is a group project using a community collaborative approach. Students design, build, test, develop applications for flying drones, all by themselves with the group forming a learning community, with design plan meetings, Whatsapp exchanges, face-to-face discussions and mutual cooperation.

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