Abstract
This paper simulates an islanding network including wind turbine, battery energy storage systems (BESS), and load. The purpose is to control voltage and frequency of the load following wind speed variations by proper control of BESS. A decentralized control scheme including two control loops is designed on BESS. One control loop is implemented for voltage regulation and the other loop is designed for frequency control. Both loops are equipped with PI (Proportional-Integral) type controllers as internal controllers. Furthermore, both loops are equipped with supplementary stabilizers as external controllers. The internal controllers regulate frequency and voltage and the external stabilizers enhance stability. This paper optimally tunes all the parameters of internal controllers and external stabilizers at the same time. The problem for tuning a large number of the design variables is mathematically expressed as a mixed integer nonlinear optimization programming and solved by modified-adaptive PSO technique. The proposed methodology is simulated on a typical standalone network including wind turbine, BESS, and load. The accurate model of BESS and wind turbine is incorporated to cope with real conditions. Moreover, in order to demonstrate the real-world results, non-linear time domain simulations are carried out in MATLAB software. The results verify that the proposed control scheme can efficiently utilize BESS to control voltage, regulate frequency, and damp out oscillations under wind and load variations.

Abstract
This study aims to build and test a theoretical model of tourist nostalgia (nostalgia proneness and food nostalgia) and seeks to explore the gender differences regarding how tourists feel their nostalgia towards food, and if it impacts in the global experience of the event. Survey data were collected in a gastronomic event, from 400 visitors. Two research models grounded on gender-female and male-highlighted the predictive role of food. Surprisingly, the all-purpose nostalgic proneness construct had a very limited impact. The newly developed construct (food nostalgia) was able to capture complex multidimensional visitor's experiences in both male and female models, whereas the broadspectrum measure of nostalgia expressed a higher propensity of nostalgia feeling among men. The managerial implications comprise market segmentation strategy, the definition of specific nostalgia triggers associated with traditional food as attributes to promote the event, and a festivalscape environment designed to express those triggers. © 2018 Cognizant, LLC.

Abstract
This study aims to develop a telemedicine platform for self-motor rehabilitation and remote monitoring by health professionals, in order to enhance recovery in patients after hip replacement. The implementation of such a technology is justified by medical (improvement of the recovery process by the possibility to perform rehabilitation exercises more frequently), economic (reduction of the number of medical appointments and the time patients spend at the hospital), mobility (diminution of the transportation to and from the hospital) and ethics (healthcare democratization and increased empowerment of the patient) purposes. The Kinect camera is used as a Natural User Interface to capture the physical exercises performed at home by the patients. The quality of the movement is evaluated in real-time by an assessment module implemented according to a Hidden-Markov Model approach. The results show a high accuracy in the evaluation of the movements (92% of correct classification). Finally, the usability of the platform is tested through the System Usability Scale (SUS). The overall SUS score is 81 out of 100, which suggests a good usability of the Web application. Further work will focus on the development of additional functionalities and an evaluation of the impact of the platform on the recovery process.

Abstract
This paper describes the work done during REX'17, an exercise conducted by the Portuguese Navy in cooperation with Portuguese universities to test, demonstrate, and develop research projects, and to approach the academic and military communities. This year the exercise took place in the Tagus river estuary, and its main aim was to assess shallow water areas, regarding bottom, and acoustic characteristics. The experiments involved testing of vector sensors development at the University of Algarve, an UUV developed by INESC-T EC, a marsupial robotic team of a USV and a hex acopter capable of landing on water developed by the New University of Lisbon (Nova), and a hydrophone network used by the Portuguese Naval Academy.

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
Tourism crowdsourcing platforms have a profound influence on the tourist behaviour particularly in terms of travel planning. Not only they hold the opinions shared by other tourists concerning tourism resources, but, with the help of recommendation engines, are the pillar of personalised resource recommendation. However, since prospective tourists are unaware of the trustworthiness or reputation of crowd publishers, they are in fact taking a leap of faith when then rely on the crowd wisdom. In this paper, we argue that modelling publisher Trust & Reputation improves the quality of the tourism recommendations supported by crowdsourced information. Therefore, we present a tourism recommendation system which integrates: (i) user profiling using the multi-criteria ratings; (ii) k-Nearest Neighbours (k-NN) prediction of the user ratings; (iii) Trust & Reputation modelling; and (iv) incremental model update, i.e., providing near real-time recommendations. In terms of contributions, this paper provides two different Trust & Reputation approaches: (i) general reputation employing the pairwise trust values using all users; and (ii) neighbour-based reputation employing the pairwise trust values of the common neighbours. The proposed method was experimented using crowdsourced datasets from Expedia and TripAdvisor platforms.