Abstract
Pedestrian behaviour modelling and simulation play a fundamental role in reducing traffic risks and new policies implementation costs. However, representing human behaviour in this dynamic environment is not a trivial task and such models require an accurate representation of pedestrian behaviour. Virtual environments have been gaining notoriety as a behaviour elicitation tool, but it is still necessary to understand the validity of this technique in the context of pedestrian studies, as well as to create guidelines for its use. This work proposes a proper methodology for pedestrian behaviour elicitation using virtual reality environments in conjunction with surveys or questionnaires. The methodology focuses on gathering data about the subject, the context, and the action taken, as well as on analyzing the collected data to finally output a behavioural model. The resulting model can be used as a feedback signal to improve environment conditions for experiment iterations. A concrete implementation was built based on this methodology, serving as an example for future studies. A virtual reality traffic environment and two surveys were used as data sources for pedestrian crossing experiments. The subjects controlled a virtual avatar using an HTC Vive and were asked to traverse the distance between two points in a city. The data collected during the experiment was analyzed and used as input to a machine learning model capable of predicting pedestrian speed, taking into account their actions and perceptions. The proposed methodology allowed for the successful data gathering and its use to predict pedestrian behaviour with fairly acceptable accuracy. © 2019 IEEE.

Abstract
Readability is determined by the characteristics of the text that influence their understanding. The web is composed of content on various topics and the results retrieved in the top positions by the main search engines are expected to be those with the highest number of views. In this study, we analyzed the readability of web pages according to the topic to which it belongs and their position in the search result. For that, we collected the top-20 results retrieved by Google to 23,779 queries from 20 topics and used several readability metrics. The results of the analysis showed that the content from organizations (like colleges and other institutions) and health-related content have lower readability values. Categories Games and Home are on the opposite side. For the categories identified as having less readability, tools can be developed that help the user understand their content. We also found that top-ranked pages have higher values of readability. One can conclude that, directly or indirectly, readability is a factor that seems to be being considered by the Google search engine or has an influence on page popularity.

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

Abstract
Virtual reality (VR) games have the potential to produce immersive experiences. To better explore the potential of VR games, it becomes necessary to understand what affects the player's presence in VR games. This work measures and compares the levels of presence and cybersickness in VR environments. Two games with different levels of interaction and narrative were compared. Presence and cybersickness were measured in a sample of 32 subjects using the IPQp questionnaire and a Portuguese version of the SSQ respectively. The results indicate that there were no differences in presence and cybersickness between the interaction and the narrative dimensions. To extend the study, the gender of participants was also considered an independent variable where we found significant differences in the metrics of presence and experienced realism, nausea and disorientation with female participants getting higher scores. © 2018 IEEE.

Abstract
Novel data collection tools, methods and new techniques in biotechnology can facilitate improved health strategies that are customised to each individual. One key challenge to achieve this is to take advantage of the massive volumes of personal anonymous data, relating each profile to health and disease, while accounting for high diversity in individuals, populations and environments. These data must be analysed in unison to achieve statistical power, but presently cohort data repositories are scattered, hard to search and integrate, and data protection and governance rules discourage central pooling.

Abstract
Cloud computing has emerged as the de facto approach for providing services over the Internet. Although having increased popularity, challenges arise in the management of such environments, especially when the cloud service providers are constantly evolving their services and technology stack in order to maintain position in a demanding market. This usually leads to a combination of different services, each one managed individually, not providing a big picture of the architecture. In essence, the end state will be too many resources under management in an overwhelming heterogeneous environment. An infrastructure that has considerable growth will not be able to avoid its increasing complexity. Thus, this papers introduces liveness as an attempt to increase the feedback-loop to the developer in the management of cloud architectures. This aims to ease the process of developing and integrating cloud-based systems, by giving the possibility to understand the system and manage it in an interactive and immersive experience, thus perceiving how the infrastructure reacts to change. This approach allows the real-time visualization of a cloud infrastructure composed of a set of Amazon Web Services resources, using visual city metaphors.