Dick Carrillo Melgarejo

TL;DR: The concept of wireless power transfer and wireless information transmission, which have recently received special attention for improving energy efficiency in wireless communication systems, are investigated and a GFDM waveform–an emerging candidate waveform for the 5G mobile networks and beyond–is considered.

TL;DR: Experimental results show that BoostedEnsML outperformed existing ensemble models in terms of accuracy, precision, recall, F-score, and area under the curve (AUC), reaching 100% in each case on the selected datasets for multiclass classification.

TL;DR: It is demonstrated that even a private LTE network is still incapable of providing the low latency required by industry automation applications, which shall be incorporated in the upcoming 5G wireless systems.

TL;DR: In this article , the authors proposed a transfer learning IDS based on the Convolutional Neural Network (CNN) architecture that has shown excellent results on image classification and used five pre-trained CNN models, including VGG16, VGG19, Inception, MobileNet, and EfficientNets, to train on two selected datasets.

TL;DR: In this paper , a triple network replay algorithm is proposed to maximize the safety problems using a deep learning algorithm, where a novel policy gradient model is presented for detecting vehicular misuse.