Recent advances on graphical evaluation and review techniques

Graphical evaluation and review techniques (GERT) is a technique to study the stochastic nature of networks consists of different branches. In GERT, all branches are explained in terms of the probability that the branch is traversed and the tile to traverse the branch in case it is realized. This paper presents recent advances of the implementation of GERT in various industries. The study presents a comprehensive description of GERT and recent advances on the implementation of GERT in various industries over the period 2002-2017.Peer reviewedFinal article published.Network designGERTGraphical evaluation and review technique

Security Threat Assessment of an Internet Security System Using Attack Tree and Vague Sets

Security threat assessment of the Internet security system has become a greater concern in recent years because of the progress and diversification of information technology. Traditionally, the failure probabilities of bottom events of an Internet security system are treated as exact values when the failure probability of the entire system is estimated. However, security threat assessment when the malfunction data of the system’s elementary event are incomplete—the traditional approach for calculating reliability—is no longer applicable. Moreover, it does not consider the failure probability of the bottom events suffered in the attack, which may bias conclusions. In order to effectively solve the problem above, this paper proposes a novel technique, integrating attack tree and vague sets for security threat assessment. For verification of the proposed approach, a numerical example of an Internet security system security threat assessment is adopted in this paper. The result of the proposed method is compared with the listing approaches of security threat assessment methods

Micro-macro dynamics of the online opinion evolution: an asynchronous network model approach

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.This paper investigates the complex relationship between endogenous and exogenous, deterministic and stochastic stimulating factors in public opinion dynamics. An asynchronous multi-agent network model is proposed to explore the interaction mechanism between individual opinions and the public opinion in online multi-agent network community, including both the micro and the macro patterns of opinion evolution. In addition, based on random network models, a novel algorithm is provided for opinion evolution prediction. The model property analysis and numerical experiments show that the proposed asynchronous multi-agent network model can assimilate and explain some interesting phenomena that are observed in the real world. Further case studies with numerical simulation and real-world applications confirm the feasibility and flexibility of the proposed model in public opinion analysis. The results challenge the common perception that mass media or opinion facilitators play the fundamental role in controlling the development trends of public opinion. This study shows that the formation and evolution of public opinion in the presence of opinion leaders depend also on an individual’s emotional inertia and conformity pressures from peers in the same topic group