Abstract
This paper introduces a fast Traffic Sign Recognition system developed for a robot, participant in the Autonomous Driving Competition in the Portuguese Festival of Robotics. The Autonomous Driving Robot performs detection and classification of traffic signs and traffic lights based on the analysis of images acquired by a camera mounted on its chassis. The proposed algorithm is composed of three processing stages: detection, pictogram extraction and classification. After the two firsts processing stages, a binary pattern matrix is obtained by color segmentation. In the classification stage two different neural networks were trained to recognize the traffic signs or the traffic light sign. Experimental results show that the system precision is very close to 100% whereas recall presents values above 90% in most of the signs. The proposed system also proves to be reliable and suitable for real-time processing.

Abstract
The internet is increasingly present in people's lives, being used in diverse tasks, such as checking e-mail up to online gaming and streaming. The so-called "killer applications" are applications that, when not properly identified and prevented, have more impact on the network, making it slow. When these applications are used on networks with limited resources, as happens in rural networks, they cause a large load on the network, making it difficult its use for work purposes. It is important then to recognize and characterize this traffic to take action so that it does not cause network problems. With that in mind, the work presented in this paper describes the research and identification of cost free traffic analysis solutions that can help to overcome such problems. For that, we perform preliminary testing and a performance comparison of those tools, focusing on testing particular types of network traffic. After that, we describe the analysis and subsequent modification of the source code for storing important traffic data for the tests, as well as the test scenarios in laboratory and reallife environments. These tasks are aimed on collecting information that assists in taking action to improve the allocation of network resources to priority traffic.

Abstract
This work draws upon the theoretical foundations of Special Education for People with Disability, Environmental Education and the Human Computer Interaction (HCI), from the Activity Theory perspective, to propose the MusicPaint software. Initially, the design considerations of MusicPaint are presented. Then, its pilot use by seven students with disability is described. From the qualitative and quantitative evidence of performance that was gathered, the key findings are presented and discussed. Despite the limited number of participants in the experimental validation scenarios, the findings reveal the potentiality of the MusicPaint to enhance the accessibility of students with disability to Environmental Education opportunities, contributing to the HCI-based enhancement of accessibility in the educational settings. © 2014 Springer International Publishing.

Abstract
In a world overwhelmed by constant data creation and manipulation, where privacy is becoming a real concern, topics like data usage control, accountability, provenance, protected sharing of resources and trustworthiness of knowledge sources are becoming main topics of discussion among communities of interest. In this paper enhancements are proposed for an existing framework that tackles some of the afore mentioned issues namely data provenance, usage control and accountability. Such proposals consist of providing means for publishing resources in a private manner hereby making websites behave like meshes of hyperlinked resources from different domains, not only for resources publicly published but also for the ones protected by access policies. © 2014, Society, Privacy and the Semantic Web Policy and Technology.

Abstract
Today's software feature user interface (UI) patterns. Those patterns describe generic solutions for common recurrent problems. However, to the best of our knowledge, there is no specific testing methodology that is particularly suited for testing those patterns providing generic testing solutions that can be reused after minor configurations in order to test slightly different implementations. Pattern-Based Graphical User Interface Testing (PBGT) is a recent methodology that aims at systematizing and automating the GUI testing process, by sampling the input space using "UI Test Patterns" that express generic solutions to test common recurrent GUI's behaviour. This paper describes the development process of PARADIGM, a domain specific language (DSL) to be used in the context of PBGT and empirically evaluates PARADIGM to assess its diminished modeling efforts, usefulness, graphical power, and acceptability.

Abstract
Graphical user interfaces (GUIs) have become popular as they appear in everydays' software. GUIs have become an ideal way of interacting with computer programs, making the software friendlier to its users. GUIs have grown, and so has the usage of UI Patterns featured in GUIs. UI Patterns are recurring solutions to solve common GUI design problems. We developed the notion of UI Test Patterns that, are able to test different implementations of UI Patterns. Therefore, we created a new methodology called Pattern-Based GUI Testing (PBGT) that aims at systematizing and automating the GUI testing process. PBGT samples the input space using UI Test Patterns, which provide a reusable and configurable test strategy, in order to test a GUI that was implemented using a set of UI Patterns. In this paper we present three UI Test Patterns: Login, Master/Detail and Sort. Copyright © 2014 ACM.