Percorrer por autor "Silva, José"
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- Comparative analysis of the ground reaction forces, during the support phase, in a group of pregnant women on their 3rd trimester of pregnancy and in a group of not pregnant womenPublication . Santos, Rubim; Gil, Belandina; Marques, Alda; Vilas Boas, João; Silva, JoséTo analyze and compare the Ground Reaction Forces (GRF), during the stance phase of walking in pregnant women in the 3rd trimester of pregnancy, and non pregnant women. 20 women, 10 pregnant and 10 non pregnant, voluntarily took part in this study. GRF were measured (1000 Hz) using a force platform (BERTEC 4060-15), an amplifier (BERTEC AM 6300) and an analogical-digital converter of 16 Bits (Biopac). The study showed that there were significant differences among the two groups concerning absolute values of time of the stance phase. In what concerns to the normalized values the most significant differences were verified in the maximums values of vertical force (Fz3, Fz1) and in the impulse of the antero-posterior force (Fy2), taxes of growth of the vertical force, and in the period of time for the antero-posterior force (Fy) be null. It is easier for the pregnant to continue forward movement (push-off phase). O smaller growth rates in what concerns to the maximum of the vertical force (Fz1) for the pregnant, can be associated with a slower speed of gait, as an adaptation strategy to maintain the balance, to compensate the alterations in the position of her center of gravity due to the load increase. The data related to the antero-posterior component of the force (Fy), shows that there is a significant difference between the pregnant woman’s left foot and right foot, which accuses a different functional behavior in each one of the feet, during the propulsion phase (TS).
- Energy Consumption Forecasting Using Ensemble Learning AlgorithmsPublication . Silva, José; Praça, Isabel; Pinto, Tiago; Vale, ZitaThe increase of renewable energy sources of intermittent nature has brought several new challenges for power and energy systems. In order to deal with the variability from the generation side, there is the need to balance it by managing consumption appropriately. Forecasting energy consumption becomes, therefore, more relevant than ever. This paper presents and compares three different ensemble learning methods, namely random forests, gradient boosted regression trees and Adaboost. Hour-ahead electricity load forecasts are presented for the building N of GECAD at ISEP campus. The performance of the forecasting models is assessed, and results show that the Adaboost model is superior to the other considered models for the one-hour ahead forecasts. The results of this study compared to previous works indicates that ensemble learning methods are a viable choice for short-term load forecast.
- Improvement of planning and time control in the project management of a metalworking industry - case studyPublication . Silva, José; Ávila, Paulo; Patrício, Leonel; Sá, José Carlos; Pinto Ferreira, Luís; Bastos, João; Castro, HelioDue to the competitiveness in the job shop nature of the metalworking industry, project management plays an important role in improving performance, efficiently and effectively managing its performance. Many of the generic problems observed in project management in metalworking industries were in the domain of document management, communication, multiple projects simultaneously, organizational structure, and poorly time estimation of project activities. The aim of this study was to improve the planning and time control in the project management of a metalworking industry in order to reduce the delivery delays. Using the existing data, an analysis of the project management process was carried out with the view to optimize the production system. In order to meet the established objectives, some of the project management tools were used, such as the Ishikawa diagram, PERT (three points estimating times), Monte Carlo simulation, as well as the involvement of people in the estimation and sequencing of activities, and holding weekly meetings to ensure the alignment of professionals. After the implementation of the actions proposed for the production process, there were gains of 50% and 38% in the average of deviations of times for two different projects of the case study and the Monte Carlo gave the best approximation.
- Literature review of decision models for the sustainable implementation of Robotic Process AutomationPublication . Patrício, Leonel; Ávila, Paulo; Varela, Leonilde; Cruz-Cunha, Maria Manuela; Pinto Ferreira, Luís; Bastos, João; Castro, Helio; Silva, JoséRobotic Process Automation (RPA) is a rules-based system for automating business processes by software bots that mimic human interactions to relieve employees from tedious work. It was verified in the literature that there are few works related to RPA decision support models. This technology is in great growth and, therefore, it becomes important to study the evaluation of the implementation of RPA. The objective of this work is focused on a literature review for the identification and analysis of Robotic Process Automation implementation models. This work analyses some models or studies available in the literature and, in addition, analyses it from a perspective relating to the Triple Bottom Line (TBL) related to environmental, social and economic effects. Regarding the results obtained, it appears that there is still a lot of room to improve research in this field, for example, with regard to the development of an evaluation model for the implementation of the RPA, taking into account the TBL of the sustainability concept.
- A Pilot for Proactive Maintenance in Industry 4.0Publication . Lino Ferreira, Luis; Albano, Michele; Silva, José; Martinho, Diogo; Marreiros, Goreti; di Orio, Giovanni; Maló, Pedro; Ferreira, HugoThe reliability and safety of industrial machines depends on their timely maintenance. The integration of Cyber Physical Systems within the maintenance process enables both continuous machine monitoring and the application of advanced techniques for predictive and proactive machine maintenance. The building blocks for this revolution – embedded sensors, efficient preprocessing capabilities, ubiquitous connection to the internet, cloud-based analysis of the data, prediction algorithms, and advanced visualization methods – are already in place, but several hurdles have to be overcome to enable their application in real scenarios, namely: the integration with existing machines and existing maintenance processes. Current research and development efforts are building pilots and prototypes to demonstrate the feasibility and the merits of advanced maintenance techniques, and this paper describes a system for the industrial maintenance of sheet metal working machinery
- Quality of Service on the Arrowhead FrameworkPublication . Albano, Michele; Barbosa, Paulo; Silva, José; Duarte, Roberto; Lino Ferreira, Luis; Delsing, JerkerQuality of Service (QoS) is an important enabler for communication in industrial environments. The Arrowhead Framework was created to support local cloud functionalities for automation applications by means of a Service Oriented Architecture. To this aim, the framework offers a number of services that ease application development, among them the QoSSetup and the Monitor services, the first used to verify and configure QoS in the local cloud, and the second for online monitoring of QoS. This paper describes how the QoSSetup and Monitor services are provided in a Arrowhead-compliant System of Systems, detailing both the principles and algorithms employed, and how the services are implemented. Experimental results are provided, from a demonstrator built over a real-time Ethernet network.