INESCC-DL - Artigos em Livros de Actas
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Percorrer INESCC-DL - Artigos em Livros de Actas por Objetivos de Desenvolvimento Sustentável (ODS) "07:Energias Renováveis e Acessíveis"
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- An Approach to Assess the Performance of Mobile Applications: A Case Study of Multiplatform Development FrameworksPublication . Mota, Dany; Martinho, RicardoComparative studies between software multiplatform development frameworks lack a proper approach that can be replicated in future performance assessments. Moreover, there is still a deficit in performance comparison tools. Also, performance comparisons realized between mobile applications developed under these multiplatform frameworks should be done with applications running in Release Mode, which ends up not happening in most studies. The objective of this paper is thus to create a whole comparative process as correct and stable as possible, so that we can use it to safely assess performance of mobile applications developed with these frameworks. As a case study, we compare the well-known Flutter and React Native frameworks, and present the obtained results under the proposed approach. With this work, developers can not only assess both these particular frameworks, but also use the approach for further comparisons.
- Architectural Challenges on the Integration of e-Commerce and ERP Systems: A Case StudyPublication . Santos, Fábio; Martinho, RicardoMany retail companies had to go online before their Enterprise Resource Planning (ERP)-type systems were ready to fulfill all business requirements. Their overall daily operation still heavily depends on these highly customized systems often mandatory because of legal obligations, which frequently come without e-commerce “off the shelf” integration. This paper identifies main challenges derived out of the architectural and integration requirements from a case study at an e-tailer company that operates via two sales channels: online store and third-party marketplaces. These challenges led to the definition of a system architecture and implementation considerations for this common integration scenario, which was validated through its implementation. Our proposed approach allows ERP-dependent organizations to start selling online with open-source technologies, avoiding extra ERP licensing and hidden maintenance costs.
- A comparison of the vibration characteristics of a rotating machine with a linear and a keyed shaftPublication . Oliveira, F.; Pelaez, G.; Donsion, M. P.This paper presents some results of an ongoing work aimed at studying a number of characteristics of rotating machines and how they are influenced by both constructive features and the way they are driven. The following will present the main results obtained when a simple one-stage inertia turbomachine is built with a linear, cylindrical shaft or, instead, with a shaft that has a small slot such as those used in many mechanical couplings. Experimental results will show some significant differences in the behavior of the machine, both in terms of the orbit and in the resonance frequencies, as well as in the phase and amplitude of mechanical vibrations.
- Data Acquisition and Monitoring System for Legacy Injection MachinesPublication . Silva, Bruno; Sousa, João; Alenya, GuillemNowadays, companies must embrace the concept of Digitalization and Industry 4.0 to remain competitive in the market. The reality is that most of them do not have their industrial devices prepared to access their data on a real-time basis. As most companies do not have the possibility to renew all their legacy devices and because these devices are still very productive, a retrofit solution is of high interest. In this work, we propose an affordable procedure that allows data collection and monitoring of older injection machines, as a contribution towards legacy devices integration. The developed system neither requires additional proprietary modules, nor contractual annual fees for different devices, sharing the same interface across different machine manufacturers and also contributing to uniform data collection. Evaluation was carried out in a real shop floor, monitoring the injection parameters for different machine models, validating the effectiveness of the developed system.
- End-to-End Management System Framework for Smart Public BuildingsPublication . Jesus, Ivo; Pereira, Tomás; Marques, Pedro; Sousa, João; Perdigoto, Luís; Coelho, PauloThis paper presents a project aiming to design a complete framework to measure energy (electricity and gas) and water consumptions in a local Parish Council building and an adjacent Sports Hall located in the central part of Portugal. The goal is an end-to-end solution, from data acquisition to data analysis. Besides acquiring and storing the data, the aim is to make this information available and valuable to enhance better decisions in building management actions, to enable detection of situations of anomalous consumption and also to promote building users' awareness. To pursue this goal, PLCnext technology solutions from Phoenix Contact are adopted. The system is based on a new generation industrial controller that communicates with energy and water meters distributed throughout the building using a standard Information Technology (IT) network. The solution explores Industry 4.0 concept, such as Cloud Data Management, Cybersecurity, and Machine Learning. With historic consumption records available, Machine Learning strategies are being used to predict load profiles in a short-term horizon and also planned to classify untypical consumption behaviors (for monitor and alarm purposes). This project is being deployed in partnership between Polytechnic of Leiria, EduNet International Education Network and involving the local Parish Council, owner of the monitored buildings.
- 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.
- Influence of a SVC on AC Arc furnaces harmonics, flicker and unbalance. Measurement and analysis.Publication . Donsión, M. P.; Güemes, J. A.; Oliveira, F.An AC arc furnace is an unbalanced, nonlinear and time varying load, which can cause many problems to power system quality. Different studies on arc furnaces harmonics analysis can be found in the bibliography on the topic; however, it is very difficult obtain an exact model that takes into account all the parameters that have influence on the process, therefore it is necessary to take measurements under different conditions. In this paper we'll present the harmonic distortion, flicker and unbalance results and conclusions on three different measurement campaigns in an iron and steel industry (SNL) with an AC arc furnace of 83 MW (170 TM) with a transformer of 120 MVA connected with a dedicated power line of 220 kV (55 km) to the Carregado Substation, where there are another other branches that connect industrial and domestic consumers.
- Machine Learning Methods for Quality Prediction in Thermoplastics Injection MoldingPublication . Silva, Bruno; Sousa, João; Alenya, GuillemNowadays, competitiveness is a reality in all industrial fields and the plastic injection industry is not an exception. Due to the complex intrinsic changes that the parameters undergo during the injection process, it is essential to monitor the parameters that influence the quality of the final part to guarantee a superior quality of service provided to customers. Quality requirements impose the development of intelligent systems capable to detect defects in the produced parts. This article presents a first step towards building an intelligent system for classifying the quality of produced parts. The basic approach of this work is machine learning methods (Artificial Neural Networks and Support Vector Machines) and techniques that combine the two previous approaches (ensemble method). These are trained as classifiers to detect conformity or even defect types in parts. The data analyzed were collected at a plastic injection company in Portugal. The results show that these techniques are capable of incorporating the non-linear relationships between the process variables, which allows for a good accuracy (≈99%) in the identification of defects. Although these techniques present good accuracy, we show that taking into account the history of the last cycles and the use of combined techniques improves even further the performance. The approach presented in this article has a number of potential advantages for online predicting of parts quality in injection molding processes.
- Mental health indicators in the hospitalization process in a Brazilian psychosocial care networkPublication . Lima, Inacia Bezerra de; Alves, Domingos; Vinci, Andre Luiz Teixeira; Rijo, Rui Pedro Charters Lopes; Martinho, Ricardo; Yamada, Diego Bettiol; Bernardi, Filipe Andrade; Furegato, Antonia Regina FerreiraWe aim to present the use and viability of mental health indicators at a Brazilian reference psychiatric hospital. We elaborated a Business Process Model and Notation based model of the patients' hospitalization process based on semi-structured interviews with managers and professionals of the hospital. We analyzed the model and selected a set of 6 mental health indicators, based on evidence-based practice from other countries, using information from several Health Information Systems regarding hospitalizations from 2013 to 2017. In Brazil, there is a lack of methods for the manager to measure the actions carried out in mental health. Thus, the method proposed in this article can be used as metrics to assess the impact of public policy implementation and to assist planning and decision-making based on evidence in mental health.
- 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.