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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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Tatyana Aksenovich and Vasiliy Selivanov
During geomagnetic storms, which are a result of solar wind?s interaction with the Earth?s magnetosphere, geomagnetically induced currents (GICs) begin to flow in the long, high-voltage electrical networks on the Earth?s surface. It causes a number of ne...
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Andrei Velichko, Maksim Belyaev, Yuriy Izotov, Murugappan Murugappan and Hanif Heidari
Entropy measures are effective features for time series classification problems. Traditional entropy measures, such as Shannon entropy, use probability distribution function. However, for the effective separation of time series, new entropy estimation me...
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Jones Luís Schaefer, Paulo Roberto Tardio, Ismael Cristofer Baierle and Elpidio Oscar Benitez Nara
The adoption of models based on key performance indicators to diagnose and evaluate the competitiveness of companies has been presented as a trend in the operations? management. These models are structured with different variables in complex interrelatio...
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Jianhe Li and Suohai Fan
In recent years, graph neural networks (GNNs) have played an important role in graph representation learning and have successfully achieved excellent results in semi-supervised classification. However, these GNNs often neglect the global smoothing of the...
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George Tzougas and Konstantin Kutzkov
We developed a methodology for the neural network boosting of logistic regression aimed at learning an additional model structure from the data. In particular, we constructed two classes of neural network-based models: shallow?dense neural networks with ...
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Wen-Chang Cheng, Hung-Chou Hsiao, Yung-Fa Huang and Li-Hua Li
This research proposes a single network model architecture for mask face recognition using the FaceNet training method. Three pre-trained convolutional neural networks of different sizes are combined, namely InceptionResNetV2, InceptionV3, and MobileNetV...
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Jinting Zhu, Julian Jang-Jaccard, Amardeep Singh, Paul A. Watters and Seyit Camtepe
Malware authors apply different techniques of control flow obfuscation, in order to create new malware variants to avoid detection. Existing Siamese neural network (SNN)-based malware detection methods fail to correctly classify different malware familie...
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Ernesto Cadena Muñoz, Gustavo Chica Pedraza, Rafael Cubillos-Sánchez, Alexander Aponte-Moreno and Mónica Espinosa Buitrago
The primary user emulation (PUE) attack is one of the strongest attacks in mobile cognitive radio networks (MCRN) because the primary users (PU) and secondary users (SU) are unable to communicate if a malicious user (MU) is present. In the literature, so...
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Saige Lv and Xiong Hu
In order to solve the problems of subjectivity in the extraction of traditional degradation features and incomplete degradation information contained in a single sensor signal, a performance degradation assessment and abnormal health status detection met...
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