Abstract
In this paper, we present the design of an analog transmitter based on a blue LD targeting optical wireless communications, suitable for OFDM signals. The approach relies on a thorough characterization of the individual components of the module, whence a detailed circuit model is obtained to design an impedance matching circuit for improved performance, prior to fabrication. The impedance matching is based on non-uniform transmission lines and works well over a wide frequency range (100 MHz to 2 GHz). The results are experimentally validated by the transmitter response exhibiting an increased 6 dB bandwidth limit and 1 GHz bandwidth improvement. © 2020 IEEE.

Abstract
An OFDM transmission system is reported based on a directly modulated blue LASER diode, for high bit rate under-water optical communication applications. The 256 subcarriers 16-QAM signal is transmitted over a total distance of 2.4 m underwater with an EVM lower than -28.5 dB for a 250 MHz bandwidth and -16.5 dB for a 2 GHz bandwidth, the BER being lower than the forward error corrector limit. At the maximum bandwidth of 2 GHz a transmission rate of 5.36 Gbit/s is achieved. © 2020 IEEE.

Abstract
Multimedia content production is nowadays widespread due to technological advances, namely supported by smartphones and social media. Although the massive amount of media content brings new opportunities to the industry, it also obfuscates the relevance of marketing content, meant to maintain and lure new audiences. This leads to an emergent necessity of producing these kinds of contents as quickly and engagingly as possible. Creating these automatically would decrease both the production costs and time, particularly by using static media for the creation of short storytelling animated clips. We propose an innovative approach that uses context and content information to transform a still photo into an appealing context-aware video clip. Thus, our solution presents a contribution to the state-of-the-art in computer vision and multimedia technologies and assists content creators with a value-added service to automatically build rich contextualized multimedia stories from single photographs. © 2020 Owner/Author.

Abstract
This work seeks to design and implement a humanoid robotic kick for situations where the robot is moving for the RoboCup simulation 3D robotic soccer league. It employs Reinforcement Learning (RL) techniques, namely the Proximal Policy Optimization (PPO) algorithm to create fast and reliable skills. The kick was divided into 6 cases according to initial conditions and separately trained for each of the cases. A series of kicks, both static and in motion, using two different gaits were developed. The kicks obtained show very high reliability and, when compared to state of the art kicks, displayed a very high time performance improvement. This opens the door to more dynamic games with faster kicks in the RoboCup simulation 3D league.

Abstract
The media sector is constantly evolving and, in the last few years, such evolution has been driven by a number of convergence paradigms, notably, that between broadband and broadcast technologies with the introduction of IT and IP technology. The present trend is to switch totally from a closed niche that uses highly specialized equipment to off-the-shelf IT-centric solutions, offering easy configuration and remote operation. The aim is to enable common computers to be turned into highly capable media devices and act as connected objects adopting an IoT-like paradigm. This vision, though, is not implemented easily, given that most media industry professionals do not yet feel comfortable operating in the IT technology space and also due to the stringent requirements that exist in this industry. The Joint Task Force on Networked Media is defining specifications that aim at overcoming such existing barriers. In this article we present a novel solution that follows the guidelines delivered by this group to set up a remotely operated media production facility, totally based on IP and IT technology, constituting a step forward the realization of the IoT concept in professional media environments. The focus is on two complementary components, namely, the GUI Agent and the MW Agent, which are not covered by the defined specifications but that are crucial to speed up the deployment of concrete solutions that can be easily operated by non-IT and non-IP experts in a transparent and ubiquitous way. © 2020 TRON Forum.

Abstract
This paper investigates the learning of both low-level behaviors for humanoid robot controllers and of high-level coordination strategies for teams of robots engaged in simulated soccer. Regarding controllers, current approaches typically hand-tune behaviors or optimize them without realistic constraints, for example allowing parts of the robot to intersect with others. This level of optimization often leads to low-performance behaviors. Regarding strategies, most are hand-tuned with arbitrary parameters (like agents moving to pre-defined positions on the field such that eventually they can score a goal) and the thorough analysis of learned strategies is often disregarded. This paper demonstrates how it is possible to use a distributed framework to learn both low-level behaviors, like sprinting and getting up, and high-level strategies, like a kick-off scenario, outperforming previous approaches in the FCPortugal3D Simulated Soccer team.