Latent space transformers for generalizing deep networks

Sharing information between deep networks is not a simple task nowadays. In a traditional approach, researchers change and train layers at the end of a pretrained deep network while the other layers remain the same to adapt it to their purposes or develop a new deep network. In this paper, we propose a novel concept for interoperability in deep networks. Generalizing such networks’ usability will facilitate the creation of new hybrid models promoting innovation and disruptive use cases for deep networks in the fifth generation of wireless communications (5G) networks and increasing the accessibility, usability, and affordability for these products. The main idea is to use standard latent space transformation to share information between such networks. First, each deep network should be split into two parts by creators. After that, they should provide access to standard latent space. As each deep network should do that, we suggest the standard for the procedure. By adding the latent space, we can combine two deep networks using the latent transformer block, the only block that needs to train while connecting different pretrained deep networks. The results from the combination create a new network with a unique ability. This paper contributes to a concept related to the generalization of deep networks using latent transformers, optimizing the utilization of the edge and cloud in 5G telecommunication, controlling load balancing, saving bandwidth, and decreasing the latency caused by cumbersome computations. We provide a review of the current standardization associated with deep networks and Artificial Intelligence in general. Lastly, we present some use cases in 5G supporting the proposed concept.info:eu-repo/semantics/acceptedVersio

Partial discharge detection using low cost RTL-SDR model for wideband spectrum sensing

Partial discharge (PD) is one of the predominant factors to be controlled to ensure reliability and undisrupted functions of power generators, motors, Gas Insulated Switchgear (GIS) and grid connected power distribution equipment, especially in the future smart grid. The emergence of wireless technology has provided numerous opportunities to optimise remote monitoring and control facilities that can play a significant role in ensuring swift control and restoration of HV plant equipment. In order to monitor PD, several approaches have been employed, however, the existing schemes do not provide an optimal approach for PD signal analysis, and are very costly. In this paper an RTL-SDR (Software Defined Radio) based spectrum analyser has been proposed in order to provide a potentially low cost solution for PD detection and monitoring. Initially, a portable spectrum analyser has been used for PD detection that was later replaced by an RTL-SDR device. The proposed schemes exhibit promising results for spectral detection within the VHF and UHF band

Comparative overview of UWB and VLC for data-intensive applications

This paper provides a comparative overview of two short-range wireless technologies with high potential for use in various data-intensive and security-sensitive applications, namely, ultra wideband (UWB) and visible light communications (VLC). Both are emerging technologies with some unique features that draw a great research and commercial interest, also because of their applicability to the research in other fields, such as wireless robotics and communications, remote sensing and location-based communications, the medical field, and so forth. The paper outlines the most recent research and standardization developments for both technologies and gives a proposal for their suitability based on a comparative view, of the strengths and weaknesses for use in applications, such as home networking, vehicular communications, and medical care, including the main technical challenges