Abstract

Abstract
Nowadays, navigation systems are widely used to find the correct path, or the quickest, between two places. These systems use the Global Positioning System (GPS) and only work well in outdoor environment since GPS signals cannot easily penetrate and/or are greatly degraded inside of buildings. Several technologies have been proposed to make navigation inside of buildings possible. One such technology is Radio-Frequency Identification (RFID). In the case of outside environments, some hybrid systems have been proposed that use GPS as main information source and RFID for corrections and location error minimization. In this article we propose a navigation system that uses RFID as the main technology to guide people with visual impairment in unfamiliar environments, both indoor and outdoor, complementing the traditional white cane and providing information about the user's geographical context. (C) 2013 The Authors. Published by Elsevier B.V.

Abstract
The use of Augmented Reality (AR) techniques to visualize virtual archaeological sites is neither a new or recent issue. In those approaches the virtual models are only visualized using the existent in situ illumination, which does not allow a visitor to have a similar visual experience to that which he would have at the time the structures were built. In Augmented Virtuality (AV) approaches the virtual world prevails, which is augmented with information from the real world, which allows a better control over the parameters of the Mixed Reality (MR) environment created. In some cases, there is the need to use both approaches (AR or AV), depending on some context conditions. This paper proposes an architecture and an information system for an adaptive MR system which main goal is to visualize in situ virtual reconstructions of archaeological sites that are seamlessly merged with the real scene. In this context, a new adaptive methodology will be defined to manage the level of mixing between the real and the virtual scene, identifying in each instant the most proper approach to use (AR or AV), as well as defining the way how transitions between approaches are made. (C) 2014 The Authors. Published by Elsevier Ltd.

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.