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Reenu Mohandas, Mark Southern, Eoin O?Connell and Martin Hayes
Deep learning based visual cognition has greatly improved the accuracy of defect detection, reducing processing times and increasing product throughput across a variety of manufacturing use cases. There is however a continuing need for rigorous procedure...
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Mazen Gazzan and Frederick T. Sheldon
Ransomware attacks have emerged as a significant threat to critical data and systems, extending beyond traditional computers to mobile and IoT/Cyber?Physical Systems. This study addresses the need to detect early ransomware behavior when only limited dat...
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Yiming Chen and Shuang Liang
In the field of education, cognitive diagnosis is crucial for achieving personalized learning. The widely adopted DINA (Deterministic Inputs, Noisy And gate) model uncovers students? mastery of essential skills necessary to answer questions correctly. Ho...
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Mojtaba Nayyeri, Modjtaba Rouhani, Hadi Sadoghi Yazdi, Marko M. Mäkelä, Alaleh Maskooki and Yury Nikulin
One of the main disadvantages of the traditional mean square error (MSE)-based constructive networks is their poor performance in the presence of non-Gaussian noises. In this paper, we propose a new incremental constructive network based on the correntro...
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Juan Wang, Jing Zhong and Jiangqi Li
With the development of IoT, IoT devices have proliferated. With the increasing demands of network management and security evaluation, automatic identification of IoT devices becomes necessary. However, existing works require a lot of manual effort and f...
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Li-Na Wang, Hongxu Wei, Yuchen Zheng, Junyu Dong and Guoqiang Zhong
Ensemble learning, online learning and deep learning are very effective and versatile in a wide spectrum of problem domains, such as feature extraction, multi-class classification and retrieval. In this paper, combining the ideas of ensemble learning, on...
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Zhehu Yuan, Yinqi Sun and Dennis Shasha
Database and data structure research can improve machine learning performance in many ways. One way is to design better algorithms on data structures. This paper combines the use of incremental computation as well as sequential and probabilistic filterin...
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Kongpei Wu, Huiqin Qu and Conggui Huang
For the current stage of complex and changing network environments and correlated and synchronized vulnerability attacks, this study first fuses attack graph technology and Bayesian networks and constructs Bayesian attack graphs toportray the correlation...
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Sijia Jia, Zhenkai Zhang, Qi Dang, Chen Song and Chao Yang
Compared with traditional wings equipped with conventional control surfaces, variable-camber morphing wings have become a hot research topic in the field of aviation due to their ability to maintain a smooth and continuous overall shape while ensuring ex...
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Guilherme Yukio Sakurai, Jessica Fernandes Lopes, Bruno Bogaz Zarpelão and Sylvio Barbon Junior
The stream mining paradigm has become increasingly popular due to the vast number of algorithms and methodologies it provides to address the current challenges of Internet of Things (IoT) and modern machine learning systems. Change detection algorithms, ...
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