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Yanping Shen, Kangfeng Zheng, Yanqing Yang, Shuai Liu and Meng Huang
Various machine-learning methods have been applied to anomaly intrusion detection. However, the Intrusion Detection System still faces challenges in improving Detection Rate and reducing False Positive Rate. In this paper, a Class-Level Soft-Voting Ensem...
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Ying Zhou, Xiaokang Hu and Vera Chung
Paraphrase detection and generation are important natural language processing (NLP) tasks. Yet the term paraphrase is broad enough to include many fine-grained relations. This leads to different tolerance levels of semantic divergence in the positive par...
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Fen Liu and Quan Qian
Classification is among the core tasks in machine learning. Existing classification algorithms are typically based on the assumption of at least roughly balanced data classes. When performing tasks involving imbalanced data, such classifiers ignore the m...
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Santiago Criollo-C, Andrea Guerrero-Arias, Jack Vidal, Ángel Jaramillo-Alcazar and Sergio Luján-Mora
The main objective of this research is a working example of how a hybrid methodology combining traditional methodologies and mobile devices can be used to contribute to the literature on mobile learning in teaching English as a second language. This work...
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Pedro Neves, Salomé Pires, Carlos Miguel Marto, Inês Amaro, Ana Coelho, José Sousa, Manuel Marques Ferreira, Maria Filomena Botelho, Eunice Carrilho, Ana Margarida Abrantes and Anabela Baptista Paula
Hybrid bioactive composite resins combine the benefits of glass ionomer cements with composite resins. Its self-adhesiveness is achieved through functional polyacrylic acids and carboxylic groups, hybridizing the smear layer and establishing ionic intera...
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