Zobrazeno 1 - 10 of 101 pro vyhledávání: '"Daniel O. Cajueiro"'
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Akademický článek
The COVID-19 (SARS-CoV-2) uncertainty tripod in Brazil: Assessments on model-based predictions with large under-reporting
Autor: Saulo B. Bastos, Marcelo M. Morato, Daniel O. Cajueiro, Julio E. Normey-Rico
Publikováno v: Alexandria Engineering Journal, Vol 60, Iss 5, Pp 4363-4380 (2021)
The COVID-19 pandemic (SARS-CoV-2 virus) is the global crisis of our time. The absence of mass testing and the relevant presence of asymptomatic individuals causes the available data of the COVID-19 pandemic in Brazil to be largely under-reported reg
Externí odkaz: https://doaj.org/article/107ad72de1034527a9740e99eed41288
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2
Report
The COVID-19 (SARS-CoV-2) Uncertainty Tripod in Brazil: Assessments on model-based predictions with large under-reporting
Autor: Bastos, Saulo B., Morato, Marcelo M., Normey-Rico, Daniel O. Cajueiro anda Julio E
The COVID-19 pandemic (SARS-CoV-2 virus) is the defying global health crisis of our time. The absence of mass testing and the relevant presence of asymptomatic individuals causes the available data of the COVID-19 pandemic in Brazil to be largely und
Externí odkaz: http://arxiv.org/abs/2006.15268
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3
The COVID-19 (SARS-CoV-2) uncertainty tripod in Brazil: Assessments on model-based predictions with large under-reporting
Autor: Julio E. Normey-Rico, Saulo B. Bastos, Daniel O. Cajueiro, Marcelo Menezes Morato
Publikováno v: Alexandria Engineering Journal, Vol 60, Iss 5, Pp 4363-4380 (2021)
Alexandria Engineering Journal
Repositório Institucional da UnB
Universidade de Brasília (UnB)
instacron:UNB
The COVID-19 pandemic (SARS-CoV-2 virus) is the global crisis of our time. The absence of mass testing and the relevant presence of asymptomatic individuals causes the available data of the COVID-19 pandemic in Brazil to be largely under-reported reg
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a115b7be22e3b6f719bdb4556fb38bbe
http://www.sciencedirect.com/science/article/pii/S1110016821001599
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4
Who Are You? Cartel Detection Using Unlabeled Data
Autor: Douglas Silveira, Lucas B. de Moraes, Eduardo P. S. Fiuza, Daniel O. Cajueiro
We propose a data-driven machine learning approach to flag bid-rigging cartels in the Brazilian road maintenance sector. First, we apply a clustering algorithm to group the tenders based on their attributes. Second, we use the labels created by the c
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a2afcc2dbf645b53220f020677a1273f
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5
Modeling and forecasting the early evolution of the Covid-19 pandemic in Brazil
Autor: Saulo B. Bastos, Daniel O. Cajueiro
Publikováno v: Scientific Reports, Vol 10, Iss 1, Pp 1-10 (2020)
Scientific Reports
Repositório Institucional da UnB
Universidade de Brasília (UnB)
instacron:UNB
We model and forecast the early evolution of the COVID-19 pandemic in Brazil using Brazilian recent data from February 25, 2020 to March 30, 2020. This early period accounts for unawareness of the epidemiological characteristics of the disease in a n
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0524a2fbf3506bc8720924aa24c7b800
http://link.springer.com/article/10.1038/s41598-020-76257-1
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7
A natural language measure of ideology in the Brazilian Senate
Autor: Felipe C. de Figueredo, Bernardo Mueller, Daniel O. Cajueiro
Publikováno v: Revista Brasileira de Ciência Política.
We estimate a measure of political ideology using as data a corpus of over two decades of speeches delivered by Brazilian Federal Senators across five legislatures. We employ a computational technique that analyses political speech by extracting the
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::74a4f84ffe626c35cb76732a8d4d0341
https://doi.org/10.1590/0103-3352.2022.37.246618
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8
Impact of memory and bias in kinetic exchange opinion models on random networks
Autor: André L. Oestereich, Nuno Crokidakis, Daniel O. Cajueiro
Publikováno v: Physica A: Statistical Mechanics and its Applications. 607:128199
In this work we consider the effects of memory and bias in kinetic exchange opinion models. We propose a model in which agents remember the sign of their last interaction with each one of their pairs. This introduces memory effects in the model, sinc
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::beb28ee4f1c6e99c61814c4705a5ea1b
https://doi.org/10.1016/j.physa.2022.128199
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9
A model of indirect contagion based on a news similarity network
Autor: Saulo B. Bastos, Roberto F. S. Andrade, Daniel O. Cajueiro, Camila Cardoso Pereira
Publikováno v: Journal of Complex Networks. 9
Our objective is to model indirect contagion among companies. We use pieces of news about companies to measure the similarities between them. We assume that two companies are similar if we may associate a story about one company with the story about
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::b6f08cf2a12fe49404b2f59a19433243
https://doi.org/10.1093/comnet/cnab035
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10
An optimal predictive control strategy for COVID-19 (SARS-CoV-2) social distancing policies in Brazil
Autor: Julio E. Normey-Rico, Saulo B. Bastos, Marcelo Menezes Morato, Daniel O. Cajueiro
Publikováno v: Annual Reviews in Control
This paper formulates a Model Predictive Control (MPC) policy to mitigate the COVID-19 contagion in Brazil, designed as optimal On-Off social isolation strategy. The proposed optimization algorithm is able to determine the time and duration of social
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b7c3d3bde506aecfb59a92105dc10792
https://pubmed.ncbi.nlm.nih.gov/32837241
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