Jun Su

Work place: Hubei University of Technology, China

E-mail: sjhosix@gmail.com

Website: https://ieeexplore.ieee.org/author/37085806865

Research Interests: Network Security, Measurement Technology, Computer Science & Information Technology, Network Engineering, Wireless Sensor Networks


Jun Su received the bachelor’s degree in computer engineering and the M.Sc. degree in computer systems and networks from the Department of Applied Mathematics, National Technical University of Ukraine “Kyiv Polytechnic Institute,” Kyiv, Ukraine, in June 2002 and June 2004, and the Ph.D. degree in computer systems and components from the Department of Information and Computing Systems and Control, West Ukrainian National University, Ternopil, Ukraine, in February 2013. He is an Associate Professor with the Department of Big Data and Artificial Intelligence, School of Computer Science, Hubei University of Technology, Wuhan, China. His research interests include big data analysis, mining technology, intelligent information processing, and visualization technology.

Author Articles
An Image Impulsive Noise Denoising Method Based on Salp Swarm Algorithm

By Wei Liu Ran Wang Jun Su

DOI: https://doi.org/10.5815/ijeme.2020.01.05, Pub. Date: 8 Feb. 2020

Image noise denoising is a very important task in image processing. Aiming at the shortcomings of traditional median filtering to handle image impulse noise, an approach based on Salp Swarm Algorithm (SSA) to eliminate image impulse noise is presented in the paper. In this method, the improved extremum method is used to detect the position of impulse noise pixels, and then the Salp Swarm algorithm is used to find the optimal pixel value instead of the noise pixel to complete the denoising process of the image. Experimental results testfies that image impulse noise could be effectively filtered out through the proposed method and the manipulated image is clear and more detail could be revealed for human vision. 

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The Method of Variant Synthesis of Information and Communication Network Structures on the Basis of the Graph and Set-Theoretical Models

By Vadym Mukhin Yury Romanenkov Julia Bilokin Anton Rohovyi Anna Kharazii Viktor Kosenko Nataliia Kosenko Jun Su

DOI: https://doi.org/10.5815/ijisa.2017.11.06, Pub. Date: 8 Nov. 2017

The subject matter of the article is developing information and communication network (ICN) for critical infrastructure systems (CIS). The aim of the work is to provide high-quality information and telecommunication processes by developing the optimal version of distributing CIS functional tasks and ICN processes to the network nodes. The article deals with following problems: developing a model for mapping the information and technical ICN structures, developing a method for variant synthesis of ITS structural models, a formalized representation of the problem of selecting CIS optimal structure. The methods used are: the system method, the set-theoretic and graphic analytic approaches, methods of hierarchic structures synthesis, optimization methods. The following results were obtained: the use of system approach for formalizing the information processing process in CIS was justified; mapping the ICS functional system into the information and technical one was presented as multilevel graph chain; the generalized representation of graph structures hierarchy was developed for the set of data transmitting tasks; this approach enabled formal representing alternative variants that consider the main links, sequencing, the amount and flows of the processed information among the different structure levels; the scheme of variant synthesis method of ICN models according to graph structures mapping was developed; the problem of selecting optimal ICN structures was formally presented; a complex efficiency criterion for solving problems of optimizing variant synthesis of structures; the problem of optimal synthesis of the structure of the given level factored in resource constraints was formulated. Conclusions. The article deals with such novelty aspects as improving the model of problem of selecting the optimal ICN structure by set-theoretic formalization factored in the criterion of maximum intensity of computational resource application, which enabled determining structural links among the major elements considering the decomposition of the model up to the basic elements such as "node" and "task" and the development of a new method of optimal ICN structuring which unlike the existing ones involves the variant synthesis of structures hierarchy and formalizing selection problems on the basis of set-theoretic models, which enables providing the efficiency of application of information and technical net resources.

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