Hybrid Malware Classification Method Using Segmentation-Based Fractal Texture Analysis and Deep Convolution Neural Network Features

As the number of internet users increases so does the number of malicious attacks using malware.The detection of malicious code is becoming critical, and the existing approaches need to be improved.Here, we propose a feature fusion method to combine the features extracted from pre-trained AlexNet and Inception-v3 deep neural networks with features

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Coercivity enhancement of hot-deformed NdFeB magnets by in situ two-end-diffusion with R70Cu30 alloy powders (R = NdPr and Ce)

We hereby present a simple process, called in situ two-end diffusion (TED), to reach coercivity enhancement with almost unchanged energy product for hot deformed (HD) NdFeB magnets.Coercivity of the HD magnets is increased from 15.1 to 18.7 kOe for the magnet TED with (Nd0.75Pr0.25)70Cu30 (NdPrCu), which is larger than 17.6 kOe for the magnet direc

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Task Assignment Optimization in Multi-UAV-Assisted WSNs Considering Energy Budget and Sensor Distribution Characteristics

In emergency situations, such as disaster area monitoring, deadlines for data collection are strict.The task time minimization problem concerning multi-UAV-assisted data collection in wireless sensor networks (WSNs), with different distribution characteristics, such as the geographical or importance of the information of the sensors, is studied.Our

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