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- 저자 : Mehdi Maleki (검색결과 2 건)
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Mehdi Maleki,Roohollah Ahmady Jazany,Mohammad Soheil Ghobadi 대한토목학회 2019 KSCE JOURNAL OF CIVIL ENGINEERING Vol.23 No.4
Seismic behavior of Steel Moment Resisting Frames (SMRFs) with Drilled Flange (DF) connections as well as Reduced Beam Section (RBS) and Welded Unreinforced Flange-Bolted web (WUF-B) as a Pre-Northridge connection have been compared analytically considering Far-field earthquake-induced. The backbone curves of RBS and WUF connections are extracted from available studies and the backbone curve of DF connection is presented in this study in order to simulating the buildings models. DF, RBS, WUF connections and Panel Zone (PZ) are numerically modeled based on the proposed models provided by the prior researches and these models are applied to analyze low- and high-rise buildings designed in accordance with the relevant standards. Incremental Dynamic Analysis (IDA) process is utilized to evaluate the effects of DF connection on structural seismic response of SMRFs. Afterwards, the structures’ performance in different response levels is probabilistically assessed by means of IDA and fragility curves. The results show that the seismic demand of SMRFs with DF and RBS connections are so similar, specifically for low-rise buildings. Likewise, SMRFs with DF connection provide up to 43% higher seismic demand in high-rise buildings compared to RBS connection. Eventually, DF connection can be used as an authentic option in SMRFs.
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Evaluating Performance of Intrusion Detection System using Support Vector Machines : Review
Leila Mohammadpour,Mehdi Hussain,Alihossein Aryanfar,Vahid Maleki Raee,Fahad Sattar 보안공학연구지원센터 2015 International Journal of Security and Its Applicat Vol.9 No.9
The basic task in intrusion detection system is to classify network activities as normal or abnormal while minimizing misclassification. In literature, various machine learning and data mining techniques have been applied to Intrusion Detection Systems (IDSs) to protect the special computer systems, vulnerable traffics cyber-attacks for computer networks. In addition, Support Vector Machine (SVM) is applied as the classification techniques in literature. However, there is a lack of review for the IDS method using SVM as the classifier. The objective of this paper is to review the contemporary literature and to provide a critical evaluation of various techniques of intrusion detection using SVM as classifier. We analyze and identify the strengths and limitations of various SVM usages as classifier in IDS systems. This paper also highlights the usefulness of SVM in IDS system for network security environment with future direction.
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