Zobrazeno 1 - 10
of 156
pro vyhledávání: '"Tran Kim Phuc"'
Autor:
Truong Thu Huong, Ta Phuong Bac, Dao M. Long, Bui D. Thang, Nguyen T. Binh, Tran D. Luong, Tran Kim Phuc
Publikováno v:
IEEE Access, Vol 9, Pp 29696-29710 (2021)
Internet of Things (IoT) and its applications are becoming commonplace with more devices, but always at risk of network security. It is therefore crucial for an IoT network design to identify attackers accurately, quickly and promptly. Many solutions
Externí odkaz:
https://doaj.org/article/05df603c2e314db5a82d73ef96d4b641
Publikováno v:
International Journal of Clothing Science and Technology, 2024, Vol. 36, Issue 3, pp. 454-473.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJCST-07-2023-0099
Ensemble learning combines results from multiple machine learning models in order to provide a better and optimised predictive model with reduced bias, variance and improved predictions. However, in federated learning it is not feasible to apply cent
Externí odkaz:
http://arxiv.org/abs/2212.14050
Adversarial attacks such as poisoning attacks have attracted the attention of many machine learning researchers. Traditionally, poisoning attacks attempt to inject adversarial training data in order to manipulate the trained model. In federated learn
Externí odkaz:
http://arxiv.org/abs/2207.08486
Autor:
Ha, Do Thu, Hoang, Nguyen Xuan, Hoang, Nguyen Viet, Du, Nguyen Huu, Huong, Truong Thu, Tran, Kim Phuc
Industrial Control Systems (ICSs) are becoming more and more important in managing the operation of many important systems in smart manufacturing, such as power stations, water supply systems, and manufacturing sites. While massive digital data can b
Externí odkaz:
http://arxiv.org/abs/2205.01930
In recent years, the monitoring of compositional data using control charts has been investigated in the Statistical Process Control field. In this study, we will design a Phase II Multivariate Exponentially Weighted Moving Average (MEWMA) control cha
Externí odkaz:
http://arxiv.org/abs/2203.15438
Publikováno v:
In Process Safety and Environmental Protection November 2024 191 Part B:2013-2025