Abstract
Electric Vehicles (EVs) sales are increasing in the recent years due to several factors such as cost reduction, fuel cost increase, pollution reductions, government incentives, among others. At the same time, Intelligent Transportation Systems (ITS) are continuously improving, and researchers use different simulators in order to test their proposals before implementing them in real devices. However, traditional communications-aimed simulations do not include fuel consumption issues that are a key factor in transportation systems. This paper presents the addition of Electric Vehicles consumption to the ns-3 simulator, which currently is one of the most used network simulators. Our proposal follows all the models, coding style, as well as engineering guidelines of ns-3, coupled with the characteristics of each vehicle, to accurately estimate the energy consumption. We also analyze the performance of our proposal while simulating a part of the E313 highway, located in Antwerp, Belgium. In particular, we compare the ns-3 results obtained in terms of energy consumption to those obtained in SUMO. In addition, we study the impact of our proposal on the overall simulation time.

Abstract
In the past years, INESC TEC has been working on using ns-3 to reduce the gap between Simulation and Experimentation. Two major contributions resulted from our work: 1) the Fast Prototyping development process, where the same ns-3 protocol model is used in a real experiment; 2) the Trace-based Simulation (TS) approach, where traces of radio link qualities and position of nodes from past experiments are injected into ns-3 to achieve repeatable and reproducible experiments. In this paper we present ns-3 NEXT, our vision for ns-3 to enable simulation and experimentation using the same platform. We envision ns-3 as the platform that can automatically learn from past experiments and improve its accuracy to a point where simulated resources can seamlessly replace real resources. At that point, ns-3 can either replace a real testbed accurately (Offline Experimentation) or add functionality and scale to testbeds (Augmented Experimentation). Towards this vision, we discuss the current limitations and propose a plan to overcome them collectively within the ns-3 community. © 2019 ACM.

Abstract
Although the growth of video content in online platforms has been happening for some time, searching and browsing these assets is still very inefficient as rich contextual data that describes the content is still not available. Furthermore, any available descriptions are, usually, not linked to timed moments of content. In this paper, we present an approach for making social web videos available on YouTube more accessible, searchable and navigable. By using the concept of crowdsourcing to collect the metadata, our proposal can contribute to easily enhance content uploaded in the YouTube platform. Metadata, collected as a collaborative annotation game, is added to the content as time-based information in the form of descriptions and captions using the YouTube API. This contributes for enriching video content and enabling navigation through temporal links.

Abstract
The growing importance of Radar solutions in automotive applications results in new standards to be met and more demanding performances to be assured. As such, Radar developers require testers capable of guaranteeing compliance with the specified criteria. This paper presents a preliminary approach to allow over-the-air (OTA) testing and validation of 76-77 GHz and 77-81 GHz Radar units in production lines, covering not only pass/fail conditions, but also determination of the Radar antenna array radiation diagrams (in azimuth and elevation) through a calibrated external power sensor. Preliminary measurements on an open environment test bench are shown for different Radar bandwidths (1 GHz and 4 GHz), illustrating the importance of a clean and shielded anechoic chamber environment as a baseline approach.

Abstract
The development of efficient methods for searching and browsing large assets of video content has been considered by the academia and content owners for long. Different approaches that range from manual structured annotations, to unstructured metadata collected from several sources, as well as multimedia processing for automatic description of the content, can be identified. The growth on the number of hours of video content put online in video sharing platforms has however shown that video retrieval is still quite inefficient as rich contextual data that describes the content is most of the times still not available. Additionally, metadata is usually not linked to timed moments of content, making direct access to the most relevant moments not possible. In this paper, an approach for making web videos available in the YouTube platform more accessible is presented. The solution is based on a collaborative process presented as a game that enables collecting metadata from the crowd while implementing mechanisms that remove erroneous information usually encountered in this type of information. Metadata, exported to YouTube in the form of captions and descriptions, contributes to enhance video retrieval, guaranteeing a better user experience and exposure of the content.

Abstract
Audiovisual didactic content has been in recent years disseminated, in the Physics domain, mainly through YouTube platform. Many aspects of video production activities can increase students' selfesteem, increase their satisfaction with the learning experience, promote a positive attitude towards the subject, provide weaker students with a broad individual tutoring, encouraging students to discuss with each other, exchange their opinions, and compare the results of lab activities. On the other hand, video can support research activities, offering the researcher access to a rich data aggregation to investigate the learning processes. The main objective of this study is to understand the use of online tools in the context of teaching, for this we make a correlation between studies using audiovisual resources in the study of Physics, and our testbed with an online video annotation tool. Results show that students expressed a gain from oral lectures and access to new sources of learning.