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Browsing ESTG - Artigos em revistas internacionais by Sustainable Development Goals (SDG) "07:Energias Renováveis e Acessíveis"
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- Autonomous Wireless Sensor with a Low Cost TEG for Application in Automobile VehiclesPublication . Costa, A.; Costa, D.; Morgado, J.; Santos, Helder; Ferreira, Carlos Daniel HenriquesThe present work consists in the development of an autonomous, low cost, reliable, energy scavenger sensor for automotive applications. Thermoelectric generators typically exhibit low efficiency but high reliability, making them suitable for autonomous, low average energy consumption, applications. A prototype sensor was developed for mounting in the engine exhaust pipe using a step-up voltage converter, a microcontroller, temperature and pressure sensing elements, conditioning electronics and a wireless transceiver, all powered by a low cost TEG (Peltier module TEC1-12706), through the scavenging of exhaust gases thermal energy. During the tests the prototype was able to sustain a regular signal transmission throughout the engine operation. The sensor was installed directly at the measuring point eliminating wired cables to hot and vibrating parts, thus, simplifying the installation of components and improving the reliability of the vehicle systems.
- Development of CART model for prediction of tuberculosis treatment loss to follow up in the state of São Paulo, Brazil: A case–control studyPublication . Yamaguti, Verena Hokino; Alves, Domingos; Rijo, Rui, Rui Pedro Charters Lopes; Miyoshi, Newton Shydeo Brandão; Ruffino-Netto, AntônioBackground: Tuberculosis is the leading cause of infectious disease-related death, surpassing even the immunodeficiency virus. Treatment loss to follow up and irregular medication use contribute to persistent morbidity and mortality. This increases bacillus drug resistance and has a negative impact on disease control. Objective: This study aims to develop a computational model that predicts the loss to follow up treatment in tuberculosis patients, thereby increasing treatment adherence and cure, reducing efforts regarding treatment relapses and decreasing disease spread. Methods: This is a case-controlled study. Included in the data set were 103,846 tuberculosis cases from the state of São Paulo. They were collected using the TBWEB, an information system used as a tuberculosis treatment monitor, containing samples from 2006 to 2016. This set was later resampled into 6 segments with a 1-1 ratio. This ratio was used to avoid any bias during the model construction. Results: The Classification and Regression Trees were used as the prediction model. Training and test sets accounted for 70% in the former and 30% in the latter of the tuberculosis cases. The model displayed an accuracy of 0.76, F-measure of 0.77, sensitivity of 0.80 and specificity of 0.71. The model emphasizes the relationship between several variables that had been identified in previous studies as related to patient cure or loss to follow up treatment in tuberculosis patients. Conclusion: It was possible to construct a predictive model for loss to follow up treatment in tuberculosis patients using Classification and Regression Trees. Although the fact that the ideal predictive ability was not achieved, it seems reasonable to propose the use of Classification and Regression Trees models to predict likelihood of treatment follow up to support healthcare professionals in minimising the loss to follow up.
- Efficiency in an Intensive Energy Industrial ConsumerPublication . Galvão, J.; Nabais, A.; Galvão, M.; Candeias, J.; Pereira, Thiago; Ramos, J.Energy efficiency actions were made in a glass production industry such as reduction in the energy consumption that will reduce greenhouse gas emissions. All measures were applied regarding European Union-EU guidelines and legislation.
- High Sensitivity Micro-machined Piezoresistive Strain SensorPublication . Caseiro, D.; Santos, S.; Ferreira, Carlos Daniel Henriques; Neves, CarlosThis paper presents a micro-machined piezoresistive sensor capable of measuring very small strains. The sensor design, based on piezoresistive sensing technology, was optimized by the numerical method using Finite Element Method (FEM) to enhance sensibility. The high sensibility is achieved through a reduction of section and through the action of the bending moment. As a result, a sensor with a sensitivity of 569.4608 μV/V/με, which can be fabricated by the SensoNor MultiMEMS process, is proposed. Furthermore, practical essays with macro prototypes confirmed and validated the numerical analysis. Such a sensor can be a direct replacement for the strain gauges and its very high sensitivity opens the door to many other applications, that otherwise would not be possible.
- Predictable impact of lighting control on the energy consumption of a building through computational simulationPublication . Bernardo, H.; Leitão, S.; Neves, L.; Amaral, P.; Bernardo, Hermano; Pires Neves, LuísBuilding energy simulation tools provide accurate predictions of the energetic performance of buildings and thermal comfort of its occupants, allowing an evaluation of the impact of proposed improvement measures, in order to support choice for the more economically viable. This paper aims at determining the energy saving potential that can be obtained by adequate measures and investments. It presents the simulated values of the impact on the energy consumptions of a building, caused by artificial lighting control systems set to maximize use of natural lighting. Results show that optimization measures have a significant impact on energy consumptions reduction, and lead to important economical savings.
- 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.
- Rotating speed stability and mechanical vibration analysis of one-stage inertia flexible rotor driven by variable speed drivesPublication . Oliveira, Filipe Tadeu; Donsión, M.P.; Peláez, G.This paper poses some questions as to the adequacy of the widespread use of variable speed drives. It presents a comparison of different variable speed drives, by studying their output wave forms and applying them to a mechanical one stage inertia flexible rotor specially designed for this purpose. The comparison of the output of the variable speed drives used reveals significant differences between them, which affect the way the load is driven and the overall behaviour of the mechanical system. A comparison against a sine wave reference shows that even the best of the variable speed drives used is outperformed, since the “perfect” sine wave ensures constant rotating speed, thus minimizing vibrations along the mechanical shaft.
- Simulation of the effect of voltage transients on an induction motor with ATP/EMTPPublication . Gonçalves, José; Baptista, José; Pires Neves, Luís; Oliveira, Filipe TadeuThe present study aims at understanding the behaviour of the induction motor when subject to different kinds of disturbances. The intention was to broaden the study of some disturbances by using a transient simulation software, ATP/EMTP, and comparing results with laboratory measurements. Obtained simulation results approached very closely the laboratory measurements, with small differences probably due to the model simplifying assumptions and uncertainties associated to the model parameter estimation process. However, although this theoretical model presents a response very similar to the actual model, improvements could be made by better modelling of the mechanical load, and by using different kinds of dynamic loads. Also, the use of more accurate laboratory equipment, and namely, programmable power supplies could lead to more accurate comparisons and better learning.