Abstract
In this letter, a packaged compact meander-line monopole antenna for Bluetooth communications, manufactured in low-density fan-out technology, is presented. A combined size for the antenna and ground plane of 0.1 lambda(0) x 0.06 lambda(0) x 0.008 lambda(0) is obtained. Such small antennas are usually designed considering their connection to an evaluation board with a large ground plane, which improves their gain and bandwidth, but in this letter, the antenna is designed so it can work standalone without any further connection to printed circuit boards. The challenge of designing such a compact antenna is surpassed by performing a detailed modeling of the radiating meander-line element altogether with its finite ground plane, a tuning inductor, and an inductive coupling feed. The antenna model is developed in Ansys HFSS using the finite element method, which is later validated experimentally. Measurements of the return loss radiation pattern are carried out, and final results show a -6 dB bandwidth of approximately 110 MHz and a gain of -8.7 dBi, at 2.42 GHz.

Abstract
In this paper we evaluate the long-term deployment feasibility of a large-scale network of abandoned underwater sensors, where power is provided by autonomous underwater vehicles (AUVs) in periodic visits.

Abstract

Abstract
In this paper we propose a high-gaussicity spline-profiled horn antenna, which is scalable in length and aperture to achieve higher gains whilst retaining a high Gaussian efficiency. A novel approach is used where a PSO is used for optimizing the spline, using the gaussicities at the operating frequencies as the objective function, which further improves side-lobe level and cross-polarization when compared to the state-of-the-art. With the proposed method, which was validated through FEM simulations in HFSS, reflection coefficients below -15 dB, gains greater than 25 dBi and gaussicities above 91% were obtained in the entire WR-3 band.

Abstract
In this paper we describe the design of a dual polarized packaged patch antenna for 5G communications with improved isolation and bandwidth for Ka-band. The results were validated using FEM and Momentum co-simulations in ADS. The novelty of the approach is the use of parasitic elements in the same layer to circumvent bandwidth limitations, thereby reducing the layer count in contrast to previous designs, combined with a differential feeding technique for improved isolation and radiation pattern stability, albeit at the expense of an increased complexity in the matching process. A peak gain of 5 dBi, isolation above 40 dB and a radiation efficiency of 60% were obtained. © 2019 IEEE.

Abstract
This Letter discusses the benefits of introducing Machine Learning techniques in multi-view streaming applications. Widespread use of machine learning techniques has contributed to significant gains in numerous scientific and industry fields. Nonetheless, these have not yet been specifically applied to adaptive interactive multimedia streaming systems where, typically, the encoding bit rate is adapted based on resources availability, targeting the efficient use of network resources whilst offering the best possible user quality of experience (QoE). Intrinsic user data could be coupled with such existing quality adaptation mechanisms to derive better results, driven also by the preferences of the user. Head-tracking data, captured from camera feeds available at the user side, is an example of such data to which Recurrent Attention Models could be applied to accurately predict the focus of attention of users within videos frames. Information obtained from such models could be used to assist a preemptive buffering approach of specific viewing angles, contributing to the joint goal of maximising QoE. Based on these assumptions, a research line is presented, focusing on obtaining better QoE in an already existing multi-view streaming system