Zobrazeno 1 - 10
of 154
pro vyhledávání: '"Affonso Guedes"'
Publikováno v:
Machine Learning and Knowledge Extraction, Vol 6, Iss 1, Pp 316-341 (2024)
This study introduces an efficient methodology for addressing fault detection, classification, and severity estimation in rolling element bearings. The methodology is structured into three sequential phases, each dedicated to generating distinct mach
Externí odkaz:
https://doaj.org/article/52e9ad7e34dd4043abb62c9dd556a4af
Autor:
Lucileide M. D. Da Silva, Maria G. F. Coutinho, Carlos E. B. Santos, Mailson R. Santos, M. Dolores Ruiz, Luiz Affonso Guedes, Marcelo A. C. Fernandes
Publikováno v:
IEEE Access, Vol 9, Pp 103141-103152 (2021)
The amount of data in real-time, such as time series and streaming data, available today continues to grow. Being able to analyze this data the moment it arrives can bring an immense added value. However, it also requires a lot of computational effor
Externí odkaz:
https://doaj.org/article/3b0f8f8e78a7456785a46f87167e6d10
Publikováno v:
Applied Sciences, Vol 12, Iss 14, p 7161 (2022)
This paper proposes a new evolving algorithm named Macro SOStream with entirely online learning and based on self-organizing density for data stream clustering. The Macro SOStream is based on the SOStream algorithm, but we incorporate macroclusters c
Externí odkaz:
https://doaj.org/article/a21fb229bb324960b85963c981164d44
Autor:
Érica Pereira Affonso Guedes, Thiago Pereira Frias, Andréa Sousa da Cunha Fernandes, José Luiz Fernandes, Marcelo de Jesus Rodrigues Da Nóbrega
Publikováno v:
Brazilian Journal of Development. 8:74873-74886
O presente trabalho teve como objetivo promover a conscientização da gestão de projetos na área da construção civil, principalmente no que diz respeito ao meio ambiente. Atualmente, há uma imensa preocupação com a sustentabilidade ambiental
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d222297fa78fb2083add794e0476287
https://doi.org/10.34117/bjdv8n11-279
https://doi.org/10.34117/bjdv8n11-279
Publikováno v:
Sensors, Vol 15, Iss 5, Pp 9703-9740 (2015)
Wireless communication is a trend nowadays for the industrial environment. A number of different technologies have emerged as solutions satisfying strict industrial requirements (e.g., WirelessHART, ISA100.11a, WIA-PA). As the industrial environment
Externí odkaz:
https://doaj.org/article/7390a0bcb2474162ba2d6e12ee5b0e99
Publikováno v:
Anais do XXXIII Simpósio Brasileiro de Informática na Educação (SBIE 2022).
As tecnologias digitais da Indústria 4.0 estão cada vez mais presentes na sociedade, demandando reflexões acerca dos processos formativos nas mais diversas áreas e níveis de ensino. Neste contexto, este artigo descreve uma proposta concebida por
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::85409615656cd7d6f2c755d0df1e1cb4
https://doi.org/10.5753/sbie.2022.225171
https://doi.org/10.5753/sbie.2022.225171
Publikováno v:
Journal of Process Control. 106:142-154
Advances in technology allowed the fast and easy creation and configuration of industrial alarms. The growth in the number of alarms, however, brought some problems to the alarm management systems, for example, alarm flooding. In this paper, it is pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ab0a4c61e602a6e326e386975ddc5065
https://doi.org/10.1016/j.jprocont.2021.09.001
https://doi.org/10.1016/j.jprocont.2021.09.001
Publikováno v:
Sensors, Vol 15, Iss 1, Pp 1760-1784 (2015)
The development of wireless sensor networks for control and monitoring functions has created a vibrant investigation scenario, where many critical topics, such as communication efficiency and energy consumption, have been investigated in the past few
Externí odkaz:
https://doaj.org/article/44ca0be17b034cc79c68968f79564a88
Publikováno v:
Education Sciences, Vol 9, Iss 4, p 275 (2019)
Predicting school dropout rates is an important issue for the smooth execution of an educational system. This problem is solved by classifying students into two classes using educational activities related statistical datasets. One of the classes mus
Externí odkaz:
https://doaj.org/article/ab14de0a110043ee8ad7162cf25c5801
Autor:
Aguinaldo Bezerra, Ivanovitch Silva, Luiz Affonso Guedes, Diego Silva, Gustavo Leitão, Kaku Saito
Publikováno v:
Sensors, Vol 19, Iss 12, p 2772 (2019)
Alarm and event logs are an immense but latent source of knowledge commonly undervalued in industry. Though, the current massive data-exchange, high efficiency and strong competitiveness landscape, boosted by Industry 4.0 and IIoT (Industrial Interne
Externí odkaz:
https://doaj.org/article/2457e5fe33874b388ef98a5511501b0c