INESCC-DL - Artigos em Revistas Internacionais
Permanent URI for this collection
Browse
Recent Submissions
- 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.
- Using the eServices Platform for Detecting Behavior Patterns Deviation in the Elderly Assisted Living: A Case StudyPublication . Marcelino, Isabel; Lopes, David; Reis, Michael; Silva, Fernando; Laza, Rosalía; Pereira, AntónioWorld’s aging population is rising and the elderly are increasingly isolated socially and geographically. As a consequence, in many situations, they need assistance that is not granted in time. In this paper, we present a solution that follows the CRISP-DM methodology to detect the elderly’s behavior pattern deviations that may indicate possible risk situations. To obtain these patterns, many variables are aggregated to ensure the alert system reliability and minimize eventual false positive alert situations. These variables comprehend information provided by body area network (BAN), by environment sensors, and also by the elderly’s interaction in a service provider platform, called eServices—Elderly Support Service Platform. eServices is a scalable platform aggregating a service ecosystem developed specially for elderly people. This pattern recognition will further activate the adequate response. With the system evolution, it will learn to predict potential danger situations for a specified user, acting preventively and ensuring the elderly’s safety and well-being. As the eServices platform is still in development, synthetic data, based on real data sample and empiric knowledge, is being used to populate the initial dataset. The presented work is a proof of concept of knowledge extraction using the eServices platform information. Regardless of not using real data, this work proves to be an asset, achieving a good performance in preventing alert situations.
- Text Mining Applied to Electronic Medical RecordsPublication . Pereira, Luis; Rijo, Rui, Rui Pedro Charters Lopes; Silva, Catarina; Martinho, RicardoThe analysis of medical records is a major challenge, considering they are generally presented in plain text, have a very specific technical vocabulary and are nearly always unstructured. It is an interdisciplinary work that requires knowledge from several fields. The analysis may have several goals, such as assistance on clinical decision, classification of medical procedures, and to support hospital management decisions. This work presents the concepts involved, the relevant existent related work, and the main open issues for future research within the analysis of electronic medical records, using data and text mining techniques. It provides a comprehensive contextualization to all those who wish to perform an analytical work of medical records, enabling the identification of fruitful research fields. With the digitalization of medical records and the large amount of medical data available, this is an area of wide research potential.
- 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.
- 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.
- 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.
- 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.
- 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.
- Wireless Environmental Monitoring and Control in Poultry Houses: A Conceptual StudyPublication . Godinho, António; Vitorino, Romeu; Sérgio Manuel da Silva; Paulo Jorge CoelhoModern commercial poultry farming typically occurs indoors, where partial or complete environmental control is employed to enhance production efficiency. Maintaining optimal conditions, such as temperature, relative humidity, carbon dioxide, and ammonia levels, is essential for ensuring bird comfort and maximizing productivity. Monitoring the conditions of poultry houses requires reliable and intelligent management systems. This study introduces a Wireless Monitoring and Control System developed to regulate environmental conditions within poultry facilities. The system continuously monitors key parameters via a network of distributed sensor nodes, which transmit data wirelessly to a centralized control unit using Wi-Fi. The control unit processes the incoming data, stores it in a database, and adjusts actuators accordingly to maintain ideal conditions. A web-based dashboard allows users to monitor and control the environment in real time. Field testing confirmed the system’s effectiveness in keeping conditions optimal, supporting poultry welfare and operational efficiency.
- 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.
- «
- 1 (current)
- 2
- 3
- »