Network attack detection scheme based on variational quantum neural network

Han Qi and Changqing Gong and Weiqi Guan and Abdullah Gani (2022) Network attack detection scheme based on variational quantum neural network. The Journal of Supercomputing, 78. pp. 1-22. ISSN 0920-8542

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Abstract

During the Borneo Geographic Expedition 2019 in Kadamaian area in Kota Belud, a survey on butterfly fauna was conducted for four days from 21st to 24th October, 2019. Three sites selected for the butterfly sampling were Site 1, Site 2 and Site 4. The methods applied were fruit and carrion baited traps, and aerial netting. A total of 56 individuals were sampled and belonged to 25 species from four families (Nymphalidae, Pieridae, Lycaenidae and Papilionidae). Nymphalidae was the dominant family with Ragadia makuta recorded as the most abundant species. About 60% of the butterflies sampled in the area are forest species, while 40% of the overall species have narrow geographical distribution restricted to Sundaland. The butterfly fauna in Kadamaian area is comparable to other forest types in Sabah in terms of their diversity and species richness. The findings reflected the potential of Kadamaian area as a nature tourism site, and the area could also serve as a corridor for the conservation of flora and fauna as it is located adjacent to Kinabalu Park.

Item Type:	Article
Keyword:	Quantum neural network · Quantum machine learning · Variational quantum circuit · Quantum computing
Subjects:	Q Science > QA Mathematics > QA1-939 Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Department:	FACULTY > Faculty of Computing and Informatics
Depositing User:	SITI AZIZAH BINTI IDRIS -
Date Deposited:	04 Jul 2023 11:15
Last Modified:	04 Jul 2023 11:15
URI:	https://eprints.ums.edu.my/id/eprint/33491

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