Abstract
Brain-Computer Interface systems based on motor imagery are able to identify an individual's intent to initiate control through the classification of encephalography patterns. Correctly classifying such patterns is instrumental and strongly depends in a robust machine learning block that is able to properly process the features extracted from a subject's encephalograms. The main objective of this work is to provide an overall view on machine learning stages, aiming to answer the following question: "What are the steps in the classification process that we should worry about?". The obtained results suggest that future research in the field should focus on two main aspects: exploring techniques for dimensionality reduction, in particular, supervised linear approaches, and evaluating adequate validation schemes to allow a more precise interpretation of results.

Abstract
This paper looks over the perpetual fight that low density regions must face in what regards the emergence of economic opportunities, employment, income and production growth. It is known that tourism demand for nature and protected areas is increasing in this more and more urban world, what can open some doors for innovation to take place. The project we’ve been working on is focused on sustainable tourism practices in a protected area (Malcata Mountain Reserve), via electric mobility, which is known for its zero emission, non-polluting and noise free travelling. A broader study is taking place under the Interreg Funding Program, known as Moveletur Project. Our goals are to sponsor a model of sustainable and green tourism for visitors of natural areas, to produce a network of green tourism itineraries linking places of natural and/or cultural value using rechargeable vehicles and to encourage tourism sector entrepreneurs with a new service for their activity. Combined work with other natural areas is essential to increase outcomes. After the conclusion of project (by the end of 2018) there will be better information concerning natural and cultural values that natural areas hold and that can be used for tourists’ pleasure, there will be a more dutiful way of doing tourism in natural areas, expectantly it will address job creation and improved territorial competitiveness, tourism experiences will have more quality and, finally, using technological features, will support smart villages further development.

Abstract
The construction of terraces, in the Douro Region, with earthen embankments rises aset of problems related to the hydrological processes. The main objective of this study is the evaluation of the electrical resistivity spatial variation in agriculture terraces atDouro valley (Portugal).To achieve this objective two variables are analysed, the soil electrical resistivity andthe flow direction algorithms. In field survey, 13 electrical resistivity profiles wererecorded. The contributing area calculated with the algorithms D (DeterminiscInfinity Flow) and MFD (Multiple Flow Direction), are the base of the internal runoffmodelling, both supported by the digital elevation model with a special resolution of1m2.Was stablished a correlation between the spatial variation of the soil electrical resistivityrepresented by standard deviation electrical resistivity of each profile and the averagevalue of contributing area coincident with each profile.The electrical resistivity standard deviation seems to be moderately good correlated forthe D algorithm at about 1m of depth and has a good correlaon at 1,5m to 2m ofdepth with the MFD algorithm. The results analysis shows a significant positivestatistical correlation between electrical resistivity standard deviation and thecontributing areas (MFD and D) depending on the soil depths.

Abstract
Although still little-known, glamping has become a nature-based tourism option for people who want a higher level of comfort. The offer of this type of accommodation is growing, namely in Portugal, but there are still few studies that address the motivations and other relevant factors explaining its adoption or refusal by consumers. The present study applied a qualitative approach aimed at exploring consumers’ motivations or obstacles for choosing glamping, and their perceptions as tourists on the differences between glamping and camping. Data were collected through the conduction of focus groups held in 2017 and content analysis techniques for contextualized interpretations were used. The most important motivational driver to go glamping is the direct contact with nature. Glamour, comfort, privacy and a different experience are also important aspects that consumers appreciate. Inversely, the main obstacles are the cost, the limited offer, the lack of knowledge, and the non-authenticity, compared to camping, of the offer.

Abstract
Service design and innovation are receiving greater attention from the service research community because they play crucial roles in creating new forms of value cocreation with customers, organizations, and societal actors in general. Service innovation involves a new process or service offering that creates value for one or more actors in a service network. Service design brings new service ideas to life through a human-centered and holistic design thinking approach. However, service design and innovation build on dispersed multidisciplinary contributions that are still poorly understood. The special issue that follows offers important contributions through the examination of service design and innovation literature, the links between service design and innovation, the role of customers in service design and innovation, and service design and innovation for well-being. Building on these contributions, this article develops a future research agenda in three areas: (1) reinforcing and expanding the foundations of service design and innovation by integrating multiple perspectives and methods; (2) advancing service design and innovation by improving the connection between the two areas, deepening actor involvement, and leveraging the role of technology; and (3) upframing service design and innovation to strengthen research impact by innovating complex value networks and service ecosystems and by building a cornerstone for transformative service research.

Abstract
Since the introduction of Single Instruction Multiple Thread (SIMT) GPU architectures, vectorization has seldom been recommended. However, for efficient use of 8-bit and 16-bit data types, vector types are necessary even on these GPUs. When only integer types were natively supported in sizes of less than 32-bits, the usefulness of vectors was limited, but the introduction of hardware support for packed half-precision floating point computations in recent GPU architectures changes this, as now floating-point programs can also benefit from vector types. Given a GPU kernel, using smaller data-types might not be sufficient to achieve the optimal performance for a given device, even on hardware with native support for half-precision, because the compiler targeting the GPU may not able to automatically vectorize the code. In this paper, we present a number of examples that make use of the OpenCL vector data-types, which we are currently implementing in our tool for automatic vectorization. We present a number of experiments targeting a graphics card with an AMD Vega 10 XT GPU, which has 2x peak arithmetic throughput using half-precision when compared with single-precision. For comparison, we also target an older GPU architecture, without native support for half-precision arithmetic. We found that, on an AMD Vega 10 XT GPU, half-precision vectorization leads to performance improvements over the scalar version using the same precision (geometric mean speedup of 1.50x), which can be attributed to the GPU being able to make use of native native support for arithmetic over packed half-precision data. However, we found that most of the performance improvement of vectorization is caused by related transformations, such as thread coarsening or loop unrolling.