Departamento de Matemática
URI permanente desta comunidadehttps://repositorio.fei.edu.br/handle/FEI/789
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3 resultados
Resultados da Pesquisa
- A different statistical approach aiming at EEG parameter investigation for brain machine interface use(2014-03-06) DE CASTRO, M. C. F.; Fábio GerabA lot of effort has been made to investigate EEG features that could better represent signal characteristics. The results are usually based on the best mean recognition rates and statistical analysis is done only when different methods are compared. In this work, we propose a new approach that applies multiple rate intercomparisons based on large samples aiming at detecting differences among treatments in order to recognize their importance for the classification rates. Ten frequency band compositions expressed by power spectral density averages were extracted from 8 EEG channels during 4 motor imageries, and spatial feature selections were also considered during the recognition process. Classification rate in large samples can be represented by a normal distribution and, for multiple rate inter-comparisons, the level of significance was corrected based on the Bonferroni Method. The variables were considered to be independents and the test was performed as non paired samples in a very conservative approach. The results showed that there are significant differences among cases of spatial feature selection and thus the considered electrodes are important parameters. On the other hand, considering or not the Delta and Theta bands along with different arrangements for Gamma band resulted in no significant difference. Copyright © 2014 SCITEPRESS - Science and Technology Publications. All rights reserved.
- Good codes from metacyclic groups(2019) Samir Assuena; MILIES, C. P.© 2019 American Mathematical Society.In this paper, we consider semisimple group algebras Fq G of split metacyclic groups over finite fields. We construct left codes in Fq G in the case when the order G is pm ℓn, where p and ℓ are different primes such that gcd(q, p, ℓ) = 1.
- Methods and concepts for elaborating a decision aided tool for optimizing healthcare medicines dispatching flows(2019-06-24) PINHEIRO, J. C.; DOSSOU, P.-E.; João Chang Junior© 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)Globalization and new technologies are causes of the development of industry 4.0 concepts. Nowadays, Industry is becoming increasingly technological, machines are reaching spaces previously destined in factories to humans. Indeed, industry 4.0 concepts based on scientific, technological, and organizational concepts & tools (Internet of thing, RFID, Cobots, decision aided tools) and including sustainability could be used in different activity sectors. Healthcare sector is being transformed by new technologies and complex problems of this sector are solved by insisting on new technological parameters. FEI and Icam engineering schools are collaborating on healthcare logistics & transport area. The idea is to use the previous approach being elaborated for industrial companies to improve healthcare logistics and transport domain (Healthcare logistics 4.0). This paper presents concepts and tools (healthcare logistics 4.0) for solving real healthcare logistics problems. The approach elaborated is hybrid (combination of experimentation for acquiring real data and design for elaborating concepts and methods required for developing an adapted problem-solving tool). The decision aided tool is elaborated by using formalisms of artificial intelligence (such as expert systems, machine learning, multi-agent systems) in order to optimize medicine dispatching flows in a hospital. After describing healthcare logistics dispatching problems, a literature review will be presented for choosing concepts and formalisms that could be for developing the new decisional tool. Then, an example will be given for illustrating concepts elaborated.