INESCC-DL - Artigos em Revistas Internacionais
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- Dynamics parameters estimation of an asynchronous machine plus mechanical shaft set through orbit frequency response analysisPublication . Oliveira, F.; Donsión, M. P.; Peláez, G.This paper presents some of the results obtained upon the experimental study of the behaviour of a prototype mechanical shaft driven by an induction electric machine. The main focus of this paper will be on the mechanical response of the set, based on the measurement of a number of mechanical variables and its integration in well-known mechanical models, allowing a more accurate estimation of the actual parameters of the prototype machine. The results thus obtained can then be used to test the theoretical models, estimate mechanical parameters more accurately and generally increase knowledge on the mechanical response of the prototype set.
- The Effect of a Naturally Ventilated Roof on the Thermal Behaviour of a Building under Mediterranean Summer ConditionsPublication . Ramos, João; Aires, LuisWith the increasing cost associated with energy consumption, climate change and the greater awareness of the population to issues related to energy and environmental efficiency, energy conservation in buildings has been encouraged, along with the development of several solutions based on a more sustainable construction. Building cooling is the most challenging issue in the Mediterranean climate. The roof is one of the main elements of the building’s opaque envelope, where the choice of materials and the implementation of appropriate passive technologies determine the thermal performance of a building. The present work aims to assess the impact of natural ventilation of a roof cavity on the thermal environment of a dwelling house under Mediterranean summer conditions. An experimental study was developed in a small-scale prototype of a typical dwelling house, comprising a ceramic tile roof with vented eaves and insulated sub-tile panels according to the construction solution of the Humbelino Monteiro SA company. The thermal performance of this roof solution was assessed under real climatic conditions based on continuous measurements of the air velocity inside the air gap, the temperature of the air and the surface temperature of all roof layers. Weather conditions were also monitored continuously. Connected with the heat transfer mechanisms, the obtained temperature and air velocity profiles data were analysed and discussed.
- Evaluation of soft possibilistic classifications with non-specificity uncertainty measuresPublication . Gonçalves, Luisa M. S.; Fonte, Cidália C.; Júlio, Eduardo N. B. S.; Caetano, MarioThe aim of this paper was to investigate the usefulness of non-specificity uncertainty measures to evaluate soft classifications of remote sensing images. In particular, we analysed whether these measures could be used to identify the difficulties found by the classifier and to estimate the classification accuracy. Two nonspecificity uncertainty measures were considered, the non-specificity measure (NSp) and the U-uncertainty measure, and their behaviour was analysed to evaluate which is the most appropriate for this application. To overcome the fact that these two measures have different ranges, a normalized version (Un) of the U-uncertainty measure was used. Both measures were applied to evaluate the uncertainty of a soft classification of a very high spatial resolution multispectral satellite image, performed with an object-oriented image analysis based on a fuzzy classification. The classification accuracy was evaluated using an error matrix and the user's and producer's accuracies were computed. Two uncertainty indexes are proposed for each measure, and the correlation between the information given by them and the user's and producer's accuracies was determined to assess the relationship and compatibility of both sources of information. The results show that there is a positive correlation between the information given by the uncertainty and accuracy indexes, but mainly between the uncertainty indexes and the user's accuracy, where the correlation achieved 77%. This study shows that uncertainty indexes may be used, along with the possibility distributions, as indicators of the classification performance, and may therefore be very useful tools.
- No polarization–Expected Values of Climate Change Impacts among European Forest Professionals and ScientistsPublication . Persson, Johannes; Blennow, Kristina; Gonçalves, Luisa; Borys, Alexander; Dutcă, Ioan; Hynynen, Jari; Janeczko, Emilia; Lyubenova, Mariyana; Martel, Simon; Merganic, Jan; Merganičová, Katarína; Peltoniemi, Mikko; Petr, Michal; Reboredo, Fernando H.; Vacchiano, Giorgio; Reyer, Christopher P. O.The role of values in climate-related decision-making is a prominent theme of climate communication research. The present study examines whether forest professionals are more driven by values than scientists are, and if this results in value polarization. A questionnaire was designed to elicit and assess the values assigned to expected effects of climate change by forest professionals and scientists working on forests and climate change in Europe. The countries involved covered a north-to-south and west-to-east gradient across Europe, representing a wide range of bio-climatic conditions and a mix of economic-social-political structures. We show that European forest professionals and scientists do not exhibit polarized expectations about the values of specific impacts of climate change on forests in their countries. In fact, few differences between forest professionals and scientists were found. However, there are interesting differences in the expected values of forest professionals with regard to climate change impacts across European countries. In Northern European countries, the aggregated values of the expected effects are more neutral than they are in Southern Europe, where they are more negative. Expectations about impacts on timber production, economic returns, and regulatory ecosystem services are mostly negative, while expectations about biodiversity and energy production are mostly positive.
- Quantifying Marine Macro Litter Abundance on a Sandy Beach Using Unmanned Aerial Systems and Object-Oriented Machine Learning MethodsPublication . Gonçalves, Gil; Andriolo, Umberto; Gonçalves, Luisa; Sobral, Paula; Bessa, FilipaUnmanned aerial systems (UASs) have recently been proven to be valuable remote sensing tools for detecting marine macro litter (MML), with the potential of supporting pollution monitoring programs on coasts. Very low altitude images, acquired with a low-cost RGB camera onboard a UAS on a sandy beach, were used to characterize the abundance of stranded macro litter. We developed an object-oriented classification strategy for automatically identifying the marine macro litter items on a UAS-based orthomosaic. A comparison is presented among three automated object-oriented machine learning (OOML) techniques, namely random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN). Overall, the detection was satisfactory for the three techniques, with mean F-scores of 65% for KNN, 68% for SVM, and 72% for RF. A comparison with manual detection showed that the RF technique was the most accurate OOML macro litter detector, as it returned the best overall detection quality (F-score) with the lowest number of false positives. Because the number of tuning parameters varied among the three automated machine learning techniques and considering that the three generated abundance maps correlated similarly with the abundance map produced manually, the simplest KNN classifier was preferred to the more complex RF. This work contributes to advances in remote sensing marine litter surveys on coasts, optimizing the automated detection on UAS-derived orthomosaics. MML abundance maps, produced by UAS surveys, assist coastal managers and authorities through environmental pollution monitoring programs. In addition, they contribute to search and evaluation of the mitigation measures and improve clean-up operations on coastal environments.
- The role of beliefs, expectations and values in decision-making favoring climate change adaptation - Implications for communications with European forest professionalsPublication . Blennow, K.; Persson, J.; Gonçalves, Luísa M.S.; Borys, A.; Dutcă, I.; Hynynen, J.; Janeczko, E.; Lyubenova, M.; Merganič, J.; Merganičová, K.; Peltoniemi, M.; Petr, M.; Reboredo, F.; Vacchiano, G.; Reyer, C. P. O.Beliefs, expectations and values are often assumed to drive decisions about climate change adaptation. We tested hypotheses based on this assumption using survey responses from 508 European forest professionals in ten countries. We used the survey results to identify communication needs and the decision strategies at play, and to develop guidelines on adequate communications about climate change adaptation. We observed polarization in the positive and negative values associated with climate change impacts accepted by survey respondents. We identified a mechanism creating the polarization that we call the 'blocked belief' effect. We found that polarized values did not correlate with decisions about climate change adaptation. Strong belief in the local impacts of climate change on the forest was, however, a prerequisite of decision-making favoring adaptation. Decision-making in favor of adaptation to climate change also correlated with net values of expected specific impacts on the forest and generally increased with the absolute value of these in the absence of 'tipping point' behavior. Tipping point behavior occurs when adaptation is not pursued in spite of the strongly negative or positive net value of expected climate change impacts. We observed negative and positive tipping point behavior, mainly in SW Europe and N-NE Europe, respectively. In addition we found that advice on effective adaptation may inhibit adaptation when the receiver is aware of effective adaptation measures unless it is balanced with information explaining how climate change leads to negative impacts. Forest professionals with weak expectations of impacts require communications on climate change and its impacts on forests before any advice on adaptation measures can be effective. We develop evidence-based guidelines on communications using a new methodology which includes Bayesian machine learning modeling of the equivalent of an expected utility function for the adaptation decision problem.