Article Fingerprint
ReserarchID
CSTNWSRN6BV
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
Explore published articles in an immersive Augmented Reality environment. Our platform converts research papers into interactive 3D books, allowing readers to view and interact with content using AR and VR compatible devices.
Your published article is automatically converted into a realistic 3D book. Flip through pages and read research papers in a more engaging and interactive format.
This paper attempted to assess the attitudes of students in
Advances in technology have created the potential for a new
Inclusion has become a priority on the global educational agenda,
In the present world scenario network-based computer systems have started to play progressively more vital roles. As a result they have become the main targets of our adversaries. To apply high security against intrusions and attacks, a number of software tools are being currently developed. To solve the problem of intrusion detection a number of pattern recognition and machine learning algorithms has been proposed. The paper states the problem of classifier fusion with soft labels for Intrusion Detection. Performance of Artificial Neural Networks (ANN) and Support Vector Machines (SVM) is presented here. The performance of fusing these classifiers using approaches based on Dempster-Shafer Theory, Average Bayes Combination and Neural Network is proposed. As shown through the experimental results combined classifiers perform better than the individual classifiers.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.
