Engenharia Elétrica
URI permanente desta comunidadehttps://repositorio.fei.edu.br/handle/FEI/21
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6 resultados
Resultados da Pesquisa
- Face-based automatic pain assessment: challenges and perspectives in neonatal intensive care units(2023-06-05) HEIDERICH, T. M.; CARLINI, L. P.; BUZUTI, L. F.; BALDA, R. D. C. X.; BARROS, M. C. M.; GUINSBURG, R.; Carlos E. Thomaz© 2023 Sociedade Brasileira de PediatriaObjective: To describe the challenges and perspectives of the automation of pain assessment in the Neonatal Intensive Care Unit. Data sources: A search for scientific articles published in the last 10 years on automated neonatal pain assessment was conducted in the main Databases of the Health Area and Engineering Journal Portals, using the descriptors: Pain Measurement, Newborn, Artificial Intelligence, Computer Systems, Software, Automated Facial Recognition. Summary of findings: Fifteen articles were selected and allowed a broad reflection on first, the literature search did not return the various automatic methods that exist to date, and those that exist are not effective enough to replace the human eye; second, computational methods are not yet able to automatically detect pain on partially covered faces and need to be tested during the natural movement of the neonate and with different light intensities; third, for research to advance in this area, databases are needed with more neonatal facial images available for the study of computational methods. Conclusion: There is still a gap between computational methods developed for automated neonatal pain assessment and a practical application that can be used at the bedside in real-time, that is sensitive, specific, and with good accuracy. The studies reviewed described limitations that could be minimized with the development of a tool that identifies pain by analyzing only free facial regions, and the creation and feasibility of a synthetic database of neonatal facial images that is freely available to researchers.
- A Survey of Underwater Acoustic Data Classification Methods Using Deep Learning for Shoreline Surveillance(2022-03-02) DOMINGOS, L. C. F.; Paulo Santos; SKELTON, P. S. M.; BRINKWORTH, R. S. A.; SAMMUT, K.© 2022 by the authors. Licensee MDPI, Basel, Switzerland.This paper presents a comprehensive overview of current deep-learning methods for automatic object classification of underwater sonar data for shoreline surveillance, concentrating mostly on the classification of vessels from passive sonar data and the identification of objects of interest from active sonar (such as minelike objects, human figures or debris of wrecked ships). Not only is the contribution of this work to provide a systematic description of the state of the art of this field, but also to identify five main ingredients in its current development: the application of deep-learning methods using convolutional layers alone; deep-learning methods that apply biologically inspired feature-extraction filters as a preprocessing step; classification of data from frequency and time–frequency analysis; methods using machine learning to extract features from original signals; and transfer learning methods. This paper also describes some of the most important datasets cited in the literature and discusses data-augmentation techniques. The latter are used for coping with the scarcity of annotated sonar datasets from real maritime missions.
- The NUMEN Technical Design Report(2021-10-30) CAPPUZZELLO, F.; AGODI, C.; CALABRETTA, L.; CALVO, D.; CARBONE, D.; CAVALLARO, M.; COLONNA, M.; FINOCCHIARO, P.; IAZZI, F.; LINARES, R.; OLIVEIRA, J. R. B.; PANDOLA, L.; SANTOPINTO, E.; TORRESI, D.; TUDISCO, S.; ACOSTA, L.; ALTANA, C.; AMADOR-VALENZUELA, P.; AVANZI, L. H.; BELLONE, J.; BONANNO, D.; BOZTOSUN, I.; BRASOLIN, S.; BRISCHETTO, G. A.; BRUNASSO, O.; CALABRESE, S.; CAMPAJOLA, L.; CAPIROSSI, V.; LOMELI, E. R. C.; CIRALDO, I.; DE AGUIAR, V. A .P.; DELAUNAY, F.; FERRARESI, C.; FISICHELLA, M.; GANDOLFO, E.; Marcilei Aparecida Guazzelli; VIA. F. L.; LAMBARRI, D. J. M.; LENSKE, H.; LUBIAN, J.; MEDINA, N. H.; MEREU, P.; MORALLES, M.; MUOIO, A.; PETRASCU, H.; PINNA, F.; SARTIRANA, D.; SGOUROS, O.; SOLAKCI, S. O.; SOUKERAS, V.; STAPAFORA, A.; RUSSO, A. D.; YILDIRIM, A.© 2021 World Scientific Publishing Company.NUMEN proposes an innovative technique to access the nuclear matrix elements entering the expression of the lifetime of the double beta decay by cross-section measurements of heavy-ion induced Double Charge Exchange (DCE) reactions. Despite the fact that the two processes, namely neutrinoless double beta decay and DCE reactions, are triggered by the weak and strong interaction respectively, important analogies are suggested. The basic point is the coincidence of the initial and final state many-body wave functions in the two types of processes and the formal similarity of the transition operators. The main experimental tools for this project are the K800 Superconducting Cyclotron and MAGNEX spectrometer at the INFN-LNS laboratory. However, the tiny values of DCE cross-sections and the resolution requirements demand beam intensities much higher than those manageable with the present facility. The on-going upgrade of the INFN-LNS facilities promoted by the POTLNSa project in this perspective is intimately connected to the NUMEN project. This paper describes the solutions proposed as a result of the R&D activity performed during the recent years. The goal is to develop suitable technologies allowing for the measurements of DCE cross-section under extremely high beam intensities. a PIR01_00005 - potenziamento dell'infrastruttura di ricerca Laboratori Nazionali del Sud per la produzione di fasci di ioni ad alta intensitá.
- Contribution to application of wavelets in electrostatics Contribuição a aplicação das wavelets na eletrostática(2005-01-05) Aldo Belardi; CARDOSO, J. R.; SARTORI, C. A. F.This work presents the methodology from the determination the charge's superficial density, in two simple structure a to straight thread and in plane plates, both finite and submitted to a constant potential. That involves the method of the moments using as expansion function the wavelets instead of the pulse function, in order to reach a good precision and reducing the computational execution time. We also intends to take advantages of the wavelets application through the Cholesky decomposition, talking about formation of scattered matrixes, and the detection of nulls values.
- The knowledge of knots: an interdisciplinary literature review(2019-10-02) Paulo Santos; CABALAR, P.; CASATI, R.© 2019, © 2019 Taylor & Francis.Knots can be found and used in a variety of situations in the 3D world, such as in vines, in the DNA, polymer chains, electrical wires, in mountaineering, seamanship and when ropes or other flexible objects are involved for exerting forces and holding objects in place. Research on knots as topological entities has contributed with a number of findings, not only of interest to pure mathematics, but also to statistical mechanics, quantum physics, genetics, and chemistry. Yet, the cognitive (or algorithmic) aspects involved in the act of tying a knot are a largely uncharted territory. This paper presents a review of the literature related to the investigation of knots from the topological, physical, cognitive and computational (including robotics) standpoints, aiming at bridging the gap between pure mathematical work on knot theory and macroscopic physical knots, with an eye to applications and modeling.
- To ban or regulate autonomous weapons: A Brazilian response(2016) Santos P.E.