Recent developments in relation to the proposal for securing the international recognition of the Caribbean Sea as a special area in the context of sustainable development

Includes bibliography

Neural networks models for wear patterns recognition of single-point dresser

Grinding is a workpiece finishing process for advanced products and surfaces. However, the constant friction between workpiece and grinding wheel causes the latter to lose its sharpness, thereby impairing the result of the grinding process. When this occurs, the dressing process is essential to sharpen the worn grains of the grinding wheel. The dressing conditions strongly influence the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The purpose of this study was to classify the wear condition of a single-point dresser using intelligent systems whose inputs were obtained by digitally processing acoustic emission signals. Two multilayer perceptron (MLP) neural networks were compared for their classification ability, one using the root mean square (RMS) statistics and another the ratio of power (ROP) statistics as input. In this study, it was found that the harmonic content of the acoustic emission signal is influenced by the condition of the dresser, and that the condition of the tool under study can be classified by using the aforementioned statistics to feed a neural network. © IFAC.

Developments in relation to the proposal for securing the international recognition of the Caribbean sea as a special area in the context of sustainable development

Includes bibliography

Improving face recognition with multispectral fusion and support vector machines

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Comparative recognition by human IgG antibodies of recombinant proteins representing three asexual erythrocytic stage vaccine candidates of Plasmodium vivax

In previous immuno-epidemiological studies of the naturally acquired antibody responses to merozoite surface protein-1 (MSP-1) of Plasmodium vivax, we had evidence that the responses to distinct erythrocytic stage antigens could be differentially regulated. The present study was designed to compare the antibody response to three asexual erythrocytic stage antigens vaccine candidates of P. vivax. Recombinant proteins representing the 19 kDa C-terminal region of MSP-1(PvMSP19), apical membrane antigen n-1 ectodomain (PvAMA-1), and the region II of duffy binding protein (PvDBP-RII) were compared in their ability to bind to IgG antibodies of serum samples collected from 220 individuals from the state of Pará, in the North of Brazil. During patent infection with P. vivax, the frequency of individuals with IgG antibodies to PvMSP119, PvAMA-1, and PvDBP-RII were 95, 72.7, and 44.5% respectively. Although the frequency of responders to PvDBP-RII was lower, this frequency increased in individuals following multiple malarial infections. Individually, the specific antibody levels did not decline significantly nine months after treatment, except to PvMSP119. Our results further confirm a complex regulation of the immune response to distinct blood stage antigens. The reason for that is presently unknown but it may contribute to the high risk of re-infection in individuals living in the endemic areas.

Use of synthetic aperture radar for recognition of Coastal Geomorphological Features, land-use assessment and shoreline changes in Bragança coast, Pará, Northern Brazil

Imagens de radar de abertura sintética (SAR) vem sendo bem mais utilizadas do que antes nas aplicações de geociências em regiões tropicais úmidas. Nesta investigação, uma imagem RADARSAT-1, na banda C, polarização HH adquirida em 1998 foi usada para o mapeamento costeiro e avaliação da cobertura da terra na área de Bragança, norte do Brasil. Imagem do radar aerotransportado GEMS-1000, na banda X, polarização HH, adquirida em 1972 durante o projeto RADAM foi também utilizada para avaliar as variações costeiras ocorridas nas últimas três décadas. A pesquisa tem confirmado a utilidade da imagem RADARSAT-1 para o mapeamento geomorfológico e avaliação da cobertura da terra, particularmente em costas de manguezal de macromaré. Além disso, um novo método para estimar as variações da linha de costa baseado na superposição de vetores extraídos de diferentes imagens SAR, com alta acurácia geométrica, tem mostrado que a planície costeira de Bragança tem estado sujeita a severa erosão responsável pelo recuo de aproximadamente 32 km² e acreção de 20 km², resultando em uma perda de área de manguezal de aproximadamente 12 km². Como perspectiva de aplicação, dados SAR orbitais e aerotransportados provaram ser uma importante fonte de informação tanto para o mapeamento geomorfológico, quando para o monitoramento de modificações costeiras em ambientes tropicais úmidos.

Comparing support vector machines and artificial neural networks in the recognition of steering angle for driving of mobile robots through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by pre-processing them to extract image features. Such features are then submitted to a support vector machine and an artificial neural network in order to find out the most appropriate route. A comparison of the two approaches was performed to ascertain the one presenting the best outcome. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine and of an artificial neural network, which so far presented respectively around 93% and 90% accuracy in predicting the appropriate route. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer review under responsibility of the organizers of the 2013 International Conference on Computational Science

Pattern recognition issues on anisotropic smoothed particle hydrodynamics

This is a preliminary theoretical discussion on the computational requirements of the state of the art smoothed particle hydrodynamics (SPH) from the optics of pattern recognition and artificial intelligence. It is pointed out in the present paper that, when including anisotropy detection to improve resolution on shock layer, SPH is a very peculiar case of unsupervised machine learning. On the other hand, the free particle nature of SPH opens an opportunity for artificial intelligence to study particles as agents acting in a collaborative framework in which the timed outcomes of a fluid simulation forms a large knowledge base, which might be very attractive in computational astrophysics phenomenological problems like self-propagating star formation.

Recognition of two morpho-types in eastern South American brackens (Pteridium-Dennstaedtiaceae-Polypodiopsida)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Deep learning architecture for gesture recognition

Pós-graduação em Engenharia Mecânica - FEG

Scanning Electron Microscopy of Male Terminalia and Its Application to Species Recognition and Phylogenetic Reconstruction in the Drosophila saltans Group

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

Heterorhabditis amazonensis RSC5 (Rhabditida: Heterorhabditidae) movement and host recognition

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

A brief look at the least-squares approach as a classifier applied to restricted-vocabulary speech recognition

In this letter, a speech recognition algorithm based on the least-squares method is presented. Particularly, the intention is to exemplify how such a traditional numerical technique can be applied to solve a signal processing problem that is usually treated by using more elaborated formulations.

The Cuticular Hydrocarbons Profiles in the Colonial Recognition of the Neotropical Eusocial Wasp, Mischocyttarus cassununga (Hymenoptera: Vespidae)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Frontal sinus recognition for human identification

Many methods based on biometrics such as fingerprint, face, iris, and retina have been proposed for person identification. However, for deceased individuals, such biometric measurements are not available. In such cases, parts of the human skeleton can be used for identification, such as dental records, thorax, vertebrae, shoulder, and frontal sinus. It has been established in prior investigations that the radiographic pattern of frontal sinus is highly variable and unique for every individual. This has stimulated the proposition of measurements of the frontal sinus pattern, obtained from x-ray films, for skeletal identification. This paper presents a frontal sinus recognition method for human identification based on Image Foresting Transform and shape context. Experimental results (ERR = 5,82%) have shown the effectiveness of the proposed method.