Unidade de Investigação - INESCC-DL – Instituto de Engenharia de Sistemas e Computadores de Coimbra [delegação Politécnico de Leiria]
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- Analysis of Power Quality Disturbances in Industry in the Centre Region of PortugalPublication . Moreira, Licinio; Leitão, Sérgio; Vale, Zita; Galvão, João; Franco Marques, Pedro JoséPower quality issues have taken a more prominent role in power systems over the last years. These issues are of major concern for energy customers, primarily for customers with a widespread use of electronic devices in their manufacturing processes. Even though the quality of service is increasing, customers are becoming more demanding of the energy provider. This research aims to provide some industrial managers the technical support in deciding of investments in the mitigation of power quality disturbances, such as the use of less sensitive devices or the use of interface devices (UPS, DVR...) In order to recommend an appropriate solution, the problem is characterized. The technical and economic influences of the PQ disturbances in the manufacturing processes are assessed resorting to power quality audits in the customer facilities. This research covered a significant number of facilities in several industrial activities.
- Assessing the influence of uncertainty in land cover mapping and digital elevation models on flood risk mappingPublication . Gonçalves, Luísa M.S.; Fonte, Cidália C.; Gomes, RicardoThis paper proposes an approach to assess the influence of the uncertainty present in the parameters dependent on the land cover and elevation data over the peak flow values and the subsequent delineation of flooded areas. The proposed approach was applied to produce vulnerability and risk maps that integrate uncertainty for the urban area of Leiria, Portugal. A SPOT-4 satellite image and DEMs of the region were used. The peak flow was computed using the Soil Conservation Service method and HECHMS, HEC-RAS, Matlab and ArcGIS software programs were used. The analysis of the results obtained for the presented case study enables the identification of the order of magnitude of uncertainty associated to the watershed peak flow value and the identification of the areas which are more susceptible to flood risk to be identified.
- Blind Guide: An Ultrasound Sensor-based Body Area Network for Guiding Blind PeoplePublication . Pereira, António; Nunes, Nelson; Vieira, Daniel; Costa, Nuno; Fernandes, Hugo; Barroso, JoãoWireless Sensor Networks, in particular Wireless Body Area Networks, is a technology suggested by the research community as allowing elderly people, or people with some kind of disability, to live in a safer, responsive and comfortable environment while at their homes. One of the most active threats to the autonomous life of blind people is the quantity and variety of obstacles they face while moving, whether they are obstacles in the footpath or obstacles coming out from the walls of buildings. Hence, it is necessary to develop a solution that helps or assists blind people while moving either in indoor or outdoor scenarios, simultaneously allowing the use of the use of white cane or the Seeing Eye dog. In this article, the authors propose the use of an ultra-sound based body area network for obstacle detection and warning as a complementary and effective solution for aiding blind people when moving from place to place. According to the cost estimates of the solution and to the negligible setup time, this could be a real effective complementary solution for blind people.
- Data Integration in the Brazilian Public Health System for Tuberculosis: Use of the Semantic Web to Establish InteroperabilityPublication . Pellison, Felipe Carvalho; Rijo, Rui Pedro Charters Lopes; Lima, Vinicius Costa; Crepaldi, Nathalia Yukie; Bernardi, Filipe Andrade; Galliez, Rafael Mello; Kritski, Afrânio; Abhishek, Kumar; Alves, DomingosBackground: Interoperability of health information systems is a challenge due to the heterogeneity of existing systems at both the technological and semantic levels of their data. The lack of existing data about interoperability disrupts intra-unit and inter-unit medical operations as well as creates challenges in conducting studies on existing data. The goal is to exchange data while providing the same meaning for data from different sources. Objective: To find ways to solve this challenge, this research paper proposes an interoperability solution for the tuberculosis treatment and follow-up scenario in Brazil using Semantic Web technology supported by an ontology. Methods: The entities of the ontology were allocated under the definitions of Basic Formal Ontology. Brazilian tuberculosis applications were tagged with entities from the resulting ontology. Results: An interoperability layer was developed to retrieve data with the same meaning and in a structured way enabling semantic and functional interoperability. Conclusions: Health professionals could use the data gathered from several data sources to enhance the effectiveness of their actions and decisions, as shown in a practical use case to integrate tuberculosis data in the State of São Paulo.
- 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.
- An Evolutionary Algorithm based on an outranking relation for sorting problemsPublication . Oliveira, Eunice; Antunes, Carlos HenggelerA new approach for using the preferences elicited from a Decision Maker (DM) into the operational framework of an Evolutionary Algorithm (EA) is presented. The preference representation is achieved using the parameters and principles of the ELECTRE TRI method devoted to the sorting problem. The outranking relation is used to replace the non-dominance relation in the usual operators in the EA (crossover, mutation and selection operator). The aim of this approach is to focus the search on the region of interest defined by the DM's preferences and consequently restrict the number of solutions in the Pareto-optimal front to be subject to further screening. This aspect is particularly important when dealing with problems that lead to a large number of non-dominated solutions.
- Indoor air quality audit in two office buildings in PortugalPublication . Ramos, Joao; Pinto, FernandoThe indoor air quality that a building presents is not always from our knowledge. In fact, we may find ourselves exposed to an indoor air which can be harmful to human health, affecting the quality of life and productivity, which also will have economic repercussions at this level. Given the Portuguese law for energy and indoor air quality (IAQ) certification of large service buildings, the indoor air quality requirements were here presented and, in addition, this paper provides an overview of the current Portuguese IAQ technical procedures to audit existent buildings. It was also intended with this study to evaluate the indoor air quality experienced by the occupants of two office buildings, an old and a recent, with the same activity and occupancy, without air-conditioning systems, where were carried out indoor air quality characterizations and, in particular, have been assessed the CO2 concentration and the typical renewal air exchange rates in different zones of the buildings, as a ventilation effectiveness monitoring. During the building's regular occupancy period, the authors have been done monitoring campaigns, which took place in winter and summer seasons. They have been detected that the values of some parameters under review were non-compliance situations in winter, in contrast with the summer due to the increase of ventilation promoted by the occupants taking advantage of the favourable conditions of the Mediterranean weather. Consequently, the proposed IAQ audit approach may be helpful to characterize indoor air pollutants, to evaluate the ventilation effectiveness and to correlate it with the indoor air quality perception and self-control actions of the occupants.
- A multi-objective genetic algorithm applied to autonomous underwater vehicles for sewage outfall plume dispersion observationsPublication . Moura, Ana; Rijo, Rui; Silva, Pedro; Crespo, SidónioThis work presents a multi-objective genetic algorithm to solve route planning problem for multiple autonomous underwater vehicles (AUVs) for interdisciplinary coastal research. AUVs are mobile unmanned platforms that carry their own energy and are able to move themselves in the water without intervention from an external operator. Using AUVs one can provide high-quality measurements of physical properties of effluent plumes in a very effective manner under real oceanic conditions. The AUV's route planning problem is a combinatorial optimization problem, where the vehicles must travel through a three-dimensional irregular space with all dimensions known. Therefore, minimization of the total travel distance while considering the maximum number of water samples is the main objective. Besides the AUV kinematics restrictions other considerations must be taken into account to the problem, like the ocean currents. The practical applications of this approach are the environmental monitoring missions which typically require the sampling of a volume of water with non-trivial geometry for which parallel line sweeping might be a costly solution. Some real-life test problems and related solutions are presented.
- 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.
- On the information provided by uncertainty measures in the classification of remote sensing imagesPublication . Gonçalves, Luisa; Fonte, Cidália C.; Júlio, Eduardo N.B.S.; Caetano, MarioThis paper investigates the potential information provided to the user by the uncertainty measures applied to the possibility distributions associated with the spatial units of an IKONOS satellite image, generated by two fuzzy classifiers, based, respectively, on the Nearest Neighbour Classifier and the Minimum Distance to Means Classifier. The deviation of the geographic unit characteristics from the prototype of the class to which the geographic unit is assigned is evaluated with the Un non-specificity uncertainty measures proposed by [1] and the exaggeration uncertainty measure proposed by [2]. The classifications were evaluated using accuracy and uncertainty indexes to determine their compatibility. Both classifications generated medium to high levels of uncertainty for almost all classes, and the global accuracy indexes computed were 70% for the Nearest Neighbour Classifier and 53% for the Minimum Distance to Means Classifier. The results show that similar conclusions can be obtained with accuracy and uncertainty indexes and the latter, along with the analysis of the possibility distributions, may be used as indicators of the classification performance and may therefore be very useful tools. Since the uncertainty indexes may be computed to all spatial units, the spatial distribution of the uncertainty was also analysed. It's visualization shows that regions where less reliability is expected present a great amount of detail that may be potentially useful to the user.