AIMC Topic: Brazil
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Dengue forecasting in São Paulo city with generalized additive models, artificial neural networks and seasonal autoregressive integrated moving average models.
PloS one
Apr 2, 2018
Globally, the number of dengue cases has been on the increase since 1990 and this trend has also been found in Brazil and its most populated city-São Paulo. Surveillance systems based on predictions allow for timely decision making processes, and in ...
Empirical radio propagation model for DTV applied to non-homogeneous paths and different climates using machine learning techniques.
PloS one
Mar 29, 2018
The establishment and improvement of transmission systems rely on models that take into account, (among other factors), the geographical features of the region, as these can lead to signal degradation. This is particularly important in Brazil, where ...
Screening of Mangifera indica L. functional content using PCA and neural networks (ANN).
Food chemistry
Feb 1, 2018
A method using reversed-phase high-performance liquid chromatography with diode array detection (HPLC-DAD) was applied after extraction with acidified methanol, to determine 12 bioactive phenolic compounds in the peel and pulp of the mango fruit (Man...
Assessing the impact of PM on respiratory disease using artificial neural networks.
Environmental pollution (Barking, Essex : 1987)
Jan 5, 2018
Understanding the impact on human health during peak episodes in air pollution is invaluable for policymakers. Particles less than PM can penetrate the respiratory system, causing cardiopulmonary and other systemic diseases. Statistical regression mo...
Microwave-assisted digestion using diluted HNO and HO for macro and microelements determination in guarana samples by ICP OES.
Food chemistry
Dec 26, 2017
A microwave-assisted digestion procedure using diluted HNO and HO was developed for multi-element determination in guarana samples by ICP OES. Optimization step was performed employing a mixture design with pseudocomponents using HNO, HO and HO. The ...
FUZZY COMPUTATIONAL MODELS TO EVALUATE THE EFFECTS OF AIR POLLUTION ON CHILDREN.
Revista paulista de pediatria : orgao oficial da Sociedade de Pediatria de Sao Paulo
Nov 13, 2017
OBJECTIVE: To build a fuzzy computational model to estimate the number of hospitalizations of children aged up to 10 years due to respiratory conditions based on pollutants and climatic factors in the city of São José do Rio Preto, Brazil.
Evaluation of genotoxic effects in Brazilian agricultural workers exposed to pesticides and cigarette smoke using machine-learning algorithms.
Environmental science and pollution research international
Oct 30, 2017
Monitoring exposure to xenobiotics by biomarker analyses, such as a micronucleus assay, is extremely important for the precocious detection and prevention of diseases, such as oral cancer. The aim of this study was to evaluate genotoxic effects in ru...
Assessment of the water quality monitoring network of the Piabanha River experimental watersheds in Rio de Janeiro, Brazil, using autoassociative neural networks.
Environmental monitoring and assessment
Aug 7, 2017
Water quality monitoring is a complex issue that requires support tools in order to provide information for water resource management. Budget constraints as well as an inadequate water quality network design call for the development of evaluation too...
Fuzzy model to estimate the number of hospitalizations for asthma and pneumonia under the effects of air pollution.
Revista de saude publica
Jun 22, 2017
OBJECTIVE: Predict the number of hospitalizations for asthma and pneumonia associated with exposure to air pollutants in the city of São José dos Campos, São Paulo State.
History matching through dynamic decision-making.
PloS one
Jun 5, 2017
History matching is the process of modifying the uncertain attributes of a reservoir model to reproduce the real reservoir performance. It is a classical reservoir engineering problem and plays an important role in reservoir management since the resu...
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