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Securing Privacy Using Optimization and Statistical Models in Cognitive Radio Networks

Computer Systems Science & Engineering 2022年第8期42卷 523-533页

作者： R.Neelaveni B.Sridevi j.sivasankari Department of Electronics and Communication Engineering MNM Jain Engineering CollegeChennai60009India Department of Electronics and Communication Engineering Velammal Institute of TechnologyChennai602001India Department of Electronics and Communication Engineering Ultra College of Engineering and TechnologyMadurai625104India

Cognitive Radio Networks(CRN)are the possible and ideal solution for meeting the spectrum needs of next-generation communication *** is a promising alternative approach that allows spectrum sharing in many *** licensed users considered Primary Users(PU)and unlicensed users as Secondary Users(SU).Time and power consumption on security issues are considered degrading factors in performance for improving the Quality of Service(QoS).Irrespective of using different optimization techniques,the same methodology is to be updated for the *** that,learning and optimization go hand in *** ensures the security in CRN,risk factors in spectrum sharing to SU for secure *** objective of the proposed work is to preserve the location of the SU from attackers and attain the clustering of SU to utilize the *** Colony Optimization(ACO)is implemented to increase the overall efficiency and utilization of the *** is used to form clusters of SUs in the co-operative spectrum sensing *** paper deals with threat detection and classifying threats using parameters such as unlikability,context privacy,anonymity,conditional traceability,and *** this privacy-preserving model,overall accuracy is 97.4%,and it is 9%higher than the conventional models without Privacy-Preserving Architecture(PPA).

关键词： Attacks secondary users cognitive radio networks security

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Hybrid scientific article recommendation system with COOT optimization

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Data Science and Management 2024年第2期7卷 99-107页

作者： R.sivasankari j.Dhilipan Department of Computer Science SRM Institute of Science and TechnologyChennai600089India

Today, recommendation systems are everywhere, making a variety of activities considerably more manageable. These systems help users by personalizing their suggestions to their interests and needs. They can propose various goods, including music, courses, articles, agricultural products, fertilizers, books, movies, and foods. In the case of research articles, recommendation algorithms play an essential role in minimizing the time required for researchers to find relevant articles. Despite multiple challenges, these systems must solve serious issues such as the cold-start problem, article privacy, and changing user interests. This research addresses these issues through the use of two techniques: hybrid recommendation systems and COOT optimization. To generate article recommendations, a hybrid recommendation system integrates features from content-based and graph-based recommendation systems. COOT optimization is used to optimize the results, inspired by the movement of water birds. The proposed method combines a graph-based recommendation system with COOT optimization to increase accuracy and reduce result inaccuracies. When compared to the baseline approaches described, the model provided in this study improves precision by 2.3%, recall by 1.6%, and mean reciprocal rank (MRR) by 5.7%.

关键词： Recommendation system COOT optimization Citation network Classification Long short-term memory(LSTM)

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Characterization of magnetically impelled arc butt welded T11 tubes for high pressure applications

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Defence Technology（防务技术） 2015年第3期11卷 244-254页

作者： R.sivasankari V.BALUSAMY P.R.VENKATESWARAN G.BUVANASHEKARAN K.GANESH KUMAR Department of Metallurgical Engineering PSG College of Engineering Welding Research Institute Bharat Heavy Electricals Limited

Magnetically impelled arc butt(MIAB) welding is a pressure welding process used for joining of pipes and tubes with an external magnetic field affecting arc rotation along the tube circumference. In this work, MIAB welding of low alloy steel(T11) tubes were carried out to study the microstructural changes occurring in thermo-mechanically affected zone(TMAZ). To qualify the process for the welding applications where pressure could be up to 300 bar, the MIAB welds are studied with variations of arc current and arc rotation time. It is found that TMAZ shows higher hardness than that in base metal and displays higher weld tensile strength and ductility due to bainitic transformation. The effect of arc current on the weld interface is also detailed and is found to be defect free at higher values of arc currents. The results reveal that MIAB welded samples exhibits good structural property correlation for high pressure applications with an added benefit of enhanced productivity at lower *** study will enable the use of MIAB welding for high pressure applications in power and defence sectors.

关键词：磁控电弧磁场影响高压力应用压力焊接特性对焊驱动

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