A estrutura da comunidade ictioplanctônica na região de desembocadura do rio Paranapanema no reservatório de Jurumirim, (SP)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Potential of adjuvants to reduce drift in agricultural spraying

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Effect of working pressure at different spray nozzles on drift quantification in wind tunnel

Each year, there is an increase in pesticide consumption and in its importance of use in the large-scale agricultural production, being fundamental the knowledge of application technology to the activity success. The objective of the present study was to evaluate the influence of working pressure on the drift generated by different spray nozzles, assessed in wind tunnel. The treatments were composed of two spray nozzles AXI 110015 and AXI 11002 with pressure levels of 276 and 414 kPa. The spray solution was composed by water and NaCl at 10%. The applications were conducted at wind speed of 2.0 m s-1, being the drift collected at 5.0; 10.0 and 15.0 m away from the spray boom and at heights of 0.2; 0.4; 0.6; 0.8 e 1.0 m from the tunnel floor. To both spray nozzles, the greatest drift was collected at the smallest distance to the spray-boom and at the lowest height. The AXI 11002 nozzle gave a smaller drift relative to the AXI 110015 nozzle for the two tested pressures and for all the collection points. Regardless of the nozzle, a rise in the working pressure increases the spray drift percentage at all distances in the wind tunnel.

Semi-supervised learning with concept drift using particle dynamics applied to network intrusion detection data

Concept drift, which refers to non stationary learning problems over time, has increasing importance in machine learning and data mining. Many concept drift applications require fast response, which means an algorithm must always be (re)trained with the latest available data. But the process of data labeling is usually expensive and/or time consuming when compared to acquisition of unlabeled data, thus usually only a small fraction of the incoming data may be effectively labeled. Semi-supervised learning methods may help in this scenario, as they use both labeled and unlabeled data in the training process. However, most of them are based on assumptions that the data is static. Therefore, semi-supervised learning with concept drifts is still an open challenging task in machine learning. Recently, a particle competition and cooperation approach has been developed to realize graph-based semi-supervised learning from static data. We have extend that approach to handle data streams and concept drift. The result is a passive algorithm which uses a single classifier approach, naturally adapted to concept changes without any explicit drift detection mechanism. It has built-in mechanisms that provide a natural way of learning from new data, gradually "forgetting" older knowledge as older data items are no longer useful for the classification of newer data items. The proposed algorithm is applied to the KDD Cup 1999 Data of network intrusion, showing its effectiveness.

Spray adjuvant characteristics affecting agricultural spraying drift

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Changes in the phytoplankton structure downstream a large reservoir: effects of tributaries on the assemblages attributes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Construção e validação de um túnel de vento para ensaios de estimativa da deriva em pulverizações agrícolas

The aim of this study was to build and validate a low cost reduced-scale wind tunnel for drift evaluation on pesticide application technology. The work was carried out at the NEMPA - Núcleo de Ensaio de Máquinas e Pneus Agroflorestais (NEMPA), FCA/UNESP, Departamento de Engenharia Rural, Botucatu/SP, Brazil. The wind tunnel main characteristics were an open circuit and a closed working section with a fan blowing air into the tunnel. Screens were fitted downstream after the fan in order to stabilize the air flow on the working section. The tunnel was built with 3.0 mm eucalyptus hardboard, with a total length of 4.8 m and a squared section of 0.56 m. The air flow was provided by a 180 W axial fan. The system was adjusted and calibrated to provide a laminar and stable flow at 2.0 m s-1. Validation studies were carried out by using a Teejet XR 8003 flat fan nozzle at 200 kPa (medium droplets) to apply a spray solutions containing water plus a food dye (Blue FDC) at 0,6% m v-1 mixed with two adjuvants: a polymer based anti drift formulation at 0,06% m v-1 and a sodium lauryl ether sulfate based surfactant at 0,2% v v-1. After a 10-second application the drift was collected on nylon strips transversally fixed along the tunnel at different distances from the nozzle and different high from the bottom part of the tunnel. Drift deposits were evaluated by spectrophotometry. The wind tunnel had low levels of turbulence and high repeatability of the data, which means that the flow was uniform and able to be used for carrying out measures to estimate drift. The validation results showed that the tunnel was effective to enable comparative drift measurements on the spray solution used in this work making possible the evaluation of drift risk potential under those spray technologies. The use of an adjuvant based on a polymer reduced the amount of drift from the nozzle compared to the surfactant.