Abstract
The problem of selecting learning algorithms has been studied by the meta-learning community for more than two decades. One of the most important task for the success of a meta-learning system is gathering data about the learning process. This data is used to induce a (meta) model able to map characteristics extracted from different data sets to the performance of learning algorithms on these data sets. These systems are built under the assumption that the data are generated by a stationary distribution, i.e., a learning algorithm will perform similarly for new data from the same problem. However, many applications generate data whose characteristics can change over time. Therefore, a suitable bias at a given time may become inappropriate at another time. Although meta-learning has been used to continuously select a learning algorithm in data streams, data characterization has received less attention in this context. In this study, we provide a set of guidelines to support the proposal of characteristics able to describe non-stationary data over time. This guidance considers both the order of arrival of the examples and the type of variables involved in the base-level learning. In addition, we analyze the influence of characteristics regarding their dependence on data morphology. Experimental results using real data streams showed the effectiveness of the proposed data characterization general scheme to support algorithm selection by meta-learning systems. Moreover, the dependent metafeatures provided crucial information for the success of some meta-models.

Abstract
A simple and inexpensive POS for application to light airborne platforms was developed, and a modified Kalman Filtering was designed to integrate GNSS/IMU/Image data, which uses the relative orientation information to improve the accuracy of the exterior orientation parameters. The precise relative orientation of conjugate images was obtained using a SIFT/SFM matching algorithm. The relative exterior orientations were transformed from the camera frame to the navigation frame before they were used as external update information of the Kalman Filter. Combining all the relative orientation information retrieved from images, the Kalman Filter can give an improved output for the exterior orientation parameters. Airborne result from the tests of one straight strip shows that the heading accuracy of a GNSS/MEMS-IMU was improved from 0.26 degrees to 0.10 degrees, and the result from one closed strip shows that heading accuracy was improved from 1.11 degrees to 0.85 degrees and roll accuracy from 0.54 degrees to 0.43 degrees.

Abstract
In this work it is presented a system to help the users to maintain an active lifestyle. Our main objective is to evaluate the current mobile technologies for the development of systems to monitor the users' health and to promote a healthy lifestyle. It was developed a full system, including: an application for smartwatch; an application for smartphone; a back-end with a webservice in PHP. The application provides the functionalities to acquire the user's: heart rate; location, based on the GPS position; the number of steps; the position's elevation; etc. The back-end is used to register the data acquired and processed by the applications. The design was user centric and the development methodology was based on the agile paradigm, for which are described three development iterations.

Abstract
Portuguese Higher Education Institutions have more and more data that needs to be processed in order to get information and, therefore, Knowledge. In order to respond to this need, over time there have been several types of IS supported by ICT, which enables them to achieve these features and, at the same time, help with their daily activities. However, the continuous evolution of this technological component has led to a current high degree of complexity, from which the Information Systems Architectures emerged as means of increasing the effectiveness of its management and maintenance. Using the University of Tras-os-Montes e Alto Douro as a case study, the research team proposed a generic ISA that enabled it to have a transversal vision of its IS, allowing the validation of existence/need IS focused on Information Management and decision-making under a multidimensional perspective, i.e., geared towards the various organizational levels, since the Operational level to the Strategic level, taking into account the information needs associated with each player.

Abstract
This article seeks to add to the body of knowledge on the role played by brand experience and its relationship with satisfaction, trust and service quality in the development of loyalty. Structural Equation Modelling (sem) is used to analyze 690 telecommunications multiple-play users in the Portuguese telecommunications market. Our conclusions show that brand experiences can be used to generate loyalty, trust and quality perceptions; although satisfaction was confirmed to be the main loyalty predictor, service quality has an important indirect effect. In order to build customer loyalty, marketers must manage brand experiences, service quality, satisfaction and trust. Brand experiences can be explored as a way to differentiate services, to change customers’ perceptions toward a brand and, ultimately, lead to customer retention. Furthermore, providing reliable services is of the utmost importance for service providers.

Abstract
For docking manoeuvres, the detection of the objects to dock needs to be precise as the minimum deviation from the objective may lead to the failure of this task. The objective of this article is to test possible ways to detect a landmark using a laser rangefinder for docking manoeuvres. We will test a beacon-based localisation algorithm and an algorithm based on natural landmarks already implemented, however, we will apply modifications to such methods. To verify the possibility of docking using these methods, we will conduct experiments with a real robot. © Springer International Publishing AG 2018.