Abstract
Many of the 17 million Europeans who suffer from food allergies could benefit from a more direct information system in the identification of the 14 allergens regulated by the Parliament and Council Regulation (EU) no 1169/2011 in packages of food products. This study aimed at creating pictograms representing these 14 allergens along visual and tactile lines, through relief printing. Based on Inclusive Design approach, the project meant to overcome restrictions such as sight impairment or illiteracy. Making use of User Centered Design (UCD) methodology, and with the support of the SAED (Disabled Students Support Services of the University of Porto) and GAENEE-UP (Support Office for Students with Special Educational Needs of the University of Porto), it employed field observation processes, in which potential users recorded their tactile perception of basic elements of visual communication. The result is the creation of a universal code, which is meant to satisfy the expectations and needs of potential users, namely people with impaired sight.

Abstract
In the last few years, sustainability has become one of the priority lines for many companies and organizations, especially public administrations. This trend has been even more evident in some regions where the preservation of natural resources is of utmost importance, not only from an environmental perspective, but also from an economic one. In this context, technology has become one of the key factors to achieve sustainability goals. An example of these technologies are Unmanned Aerial Vehicles (UAVs) which are being used more and more with sustainability purposes. However, although some efforts have been made to propose software approaches to model sustainability, some examples that model the impact of technology on sustainability are still needed. This paper presents an instance of a sustainability metamodel for the UAVs domain. This model allows to specify the impact of UAV-based processes on sustainability, and also to identify potential limitations that may hinder its applicability. Finally, the paper provides some suggestions to complete the metamodel based on the instantiation process.

Abstract
The continuous process industry is currently facing a serious need for systems that allow to monitor and manage their factories. Despite the existing industrial visualization screens provide for a partial answer to the identified issue, there is a set of new technologies who might help on developing the existing industrial visualization systems and provide and improved aid to the human controllers who monitor and manage the production processes. The presented paper aims at not only delivering a serious and focused characterization on the existing industry visualization screens, but above all, it intends to present several opportunities, challenges and new perspectives for the use of innovative visualization technologies (such as 2.5D/3D screens, augmented and virtual reality) in those industries whose production process assumes itself as continuous. This contribute, from our perspective will serve as a basis for further research on the field.

Abstract
Purpose - This paper aims to address a mobile robot localization system that avoids using a dedicated laser scanner, making it possible to reduce implementation costs and the robot's size. The system has enough precision and robustness to meet the requirements of industrial environments. Design/methodology/approach - Using an algorithm for artificial beacon detection combined with a Kalman Filter and an outlier rejection method, it was possible to enhance the precision and robustness of the overall localization system. Findings - Usually, industrial automatic guide vehicles feature two kinds of lasers: one for navigation placed on top of the robot and another for obstacle detection (security lasers). Recently, security lasers extended their output data with obstacle distance (contours) and reflectivity. These new features made it possible to develop a novel localization system based on a security laser. Research limitations/implications - Once the proposed methodology is completely validated, in the future, a scheme for global localization and failure detection should be addressed. Practical implications - This paper presents a comparison between the presented approach and a commercial localization system for industry. The proposed algorithms were tested in an industrial application under realistic working conditions. Social implications - The presented methodology represents a gain in the effective cost of the mobile robot platform, as it discards the need for a dedicated laser for localization purposes. Originality/value - This paper presents a novel approach that benefits from the presence of a security laser on mobile robots (mandatory sensor when considering industrial applications), using it simultaneously with other sensors, not only to guarantee safety conditions during operation but also to locate the robot in the environment. This paper is also valuable because of the comparison made with a commercialized system, as well as the tests conducted in real industrial environments, which prove that the approach presented is suitable for working under these demanding conditions.

Abstract
Thousands of news are published everyday reporting worldwide events. Most of these news obtain a low level of popularity and only a small set of events become highly popular in social media platforms. Predicting rare cases of highly popular news is not a trivial task due to shortcomings of standard learning approaches and evaluation metrics. So far, the standard task of predicting the popularity of news items has been tackled by either of two distinct strategies related to the publication time of news. The first strategy, a priori, is focused on predicting the popularity of news upon their publication when related social feedback is unavailable. The second strategy, a posteriori, is focused on predicting the popularity of news using related social feedback. However, both strategies present shortcomings related to data availability and time of prediction. To overcome such shortcomings, we propose a hybrid strategy of time-based ensembles using models from both strategies. Using news data from Google News and popularity data from Twitter, we show that the proposed ensembles significantly improve the early and accurate prediction of rare cases of highly popular news.

Abstract
The growing dependency of our society on increasingly complex software systems, combining mobile and cloud-based applications and services, makes the test activities even more important and challenging. However, sometimes software tests are not properly performed due to tight deadlines, due to the time and skills required to develop and execute the tests or because the developers are too optimistic about possible faults in their own code. Although there are several frameworks for mobile test automation, they usually require programming skills or complex configuration steps. Hence, in this paper, we propose a framework that allows creating and executing tests for Android applications without requiring programming skills. It is possible to create automated tests based on a set of pre-defined actions and it is also possible to inject data into device sensors. An experiment with programmers and non-programmers showed that both can develop and execute tests with a similar time. A real world example using a fall detection application is presented to illustrate the approach.