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Dr.Omid Mahdi Ebadati E.
Kharazmi University, Iran
Title: Classification Spam Email with Elimination of Unsuitable Features with Hybrid Algorithms
Abstract: Email spam is a security problem that involves different techniques in machine learning to solve this problem. The rise of this security issue makes organisation email service unreliable and has a direct relation with vulnerability of clients through unexpected spam mails, like ransomware. There are several methods to identifying spam emails. Most of these methods focused on feature selection; however, these models decreased the accuracy of the detection. This paper proposed a novel spam detection method that is not only to decrease the accuracy, but eliminates unsuitable features with less processing. The features are in the terms of contents, and the number of features is very big, so it can decrease the memory complexity. We use Hewlett-Packet (HP) laboratory samples text emails. First, GA algorithm is employed to select features without limited number of feature selection with the aid of Bayesian theory as a fitness function and checked with a different number of repetitions. The result improved with GA by increasing number of repetitions, and tested with distinctive selection method, Random selection and Tournament selection. In the second stage, the dataset classifies emails as Spam or Ham by Naive Bayes. The results show that Naive Bayes and hybrid GA-Naive Bayes are almost identical, but GA-Naive Bayes has a better performance.
Prof. Shey-Huei Sheu | 徐世輝教授
Asia University, Taiwan
Title: Optimal Replacement Policy based on cumulative damage for a Two-unit System
Abstract: The extended optimal replacement policy for a two-unit system subject to two types of shock is investigated in this paper. A type I shock, rectified by a minimal repair, causes a minor failure of unit A, and type II shock results in a complete system failure that is removed by a corrective replacement. The probability of type II shock is permitted to depend on the number of shocks from the last replacement. Each unit A minor failure also suffers some damage to unit B. These damages to unit B are additive, and the system fails when the total damage has exceeded a failure level K. Unit B also may become minor failed with a random probability. This paper proposes a more general replacement policy which prescribes that the system is preventively replaced at the Nth type I shock or when the total damage to unit B exceeds a pre-specified level Z (<K) or is replaced correctively either at the first type II shock or when the total damage to unit B exceeds a failure level K, whichever occurs first.