21 resultados para binary to multi-class classifiers


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Complex systems have stimulated much interest in the scientific community in the last twenty years. Examples this area are the Domany-Kinzel cellular automaton and Contact Process that are studied in the first chapter this tesis. We determine the critical behavior of these systems using the spontaneous-search method and short-time dynamics (STD). Ours results confirm that the DKCA e CP belong to universality class of Directed Percolation. In the second chapter, we study the particle difusion in two models of stochastic sandpiles. We characterize the difusion through diffusion constant D, definite through in the relation h(x)2i = 2Dt. The results of our simulations, using finite size scalling and STD, show that the diffusion constant can be used to study critical properties. Both models belong to universality class of Conserved Directed Percolation. We also study that the mean-square particle displacement in time, and characterize its dependence on the initial configuration and particle density. In the third chapter, we introduce a computacional model, called Geographic Percolation, to study watersheds, fractals with aplications in various areas of science. In this model, sites of a network are assigned values between 0 and 1 following a given probability distribution, we order this values, keeping always its localization, and search pk site that percolate network. Once we find this site, we remove it from the network, and search for the next that has the network to percole newly. We repeat these steps until the complete occupation of the network. We study the model in 2 and 3 dimension, and compare the bidimensional case with networks form at start real data (Alps e Himalayas)

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The Metropolitan Region of Natal, like other metropolitan regions in Brazil, was marked by intense and rapid urbanization of the country occurred only in the second half of the twentieth century, coinciding with the process of consolidation of the industry in the country, resulting in serious urban social problems, such as the increase in slums, lack of infrastructure and this increase in violence in urban centers. When enters the reality of the metropolitan region, assessing the impacts of restructuring productive in the context of globalization, analyzing how the socio-economic factors influencing the dynamic of the population, whose configuration was shown to be contradictory according to social class busy. Accordingly, we studied the demographic configuration of the Metropolitan Region of Natal, analyzing their spatial distribution and their socio-demographic differences in light of building a type socio-space, which cuts the metropolitan space in homogeneous areas

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The expansion of cultivated areas with genetically modified crops (GM) is a worldwide phenomenon, stimulating regulatory authorities to implement strict procedures to monitor and verify the presence of GM varieties in agricultural crops. With the constant growing of plant cultivating areas all over the world, consumption of aflatoxin-contaminated food also increased. Aflatoxins correspond to a class of highly toxic contaminants found in agricultural products that can have harmful effects on human and animal health. Therefore, the safety and quality evaluation of agricultural products are important issues for consumers. Lateral flow tests (strip tests) is a promising method for the detection both proteins expressed in GM crops and aflatoxins-contaminated food samples. The advantages of this technique include its simplicity, rapidity and cost-effective when compared to the conventional methods. In this study, two novel and sensitive strip tests assay were developed for the identification of: (i) Cry1Ac and Cry8Ka5 proteins expressed in GM cotton crops and; (ii) aflatoxins from agricultural products. The first strip test was developed using a sandwhich format, while the second one was developed using a competitive format. Gold colloidal nanoparticles were used as detector reagent when coated with monoclonal antibodies. An anti-species specific antibody was sprayed at the nitrocellulose membrane to be used as a control line. To validate the first strip test, GM (Bollgard I® e Planta 50- EMBRAPA) and non-GM cotton leaf (Cooker 312) were used. The results showed that the strip containing antibodies for the identification of Cry1Ac and Cry8Ka5 proteins was capable of correctly distinguishing between GM samples (positive result) and non-GM samples (negative result), in a high sensitivity manner. To validate the second strip test, artificially contaminated soybean with Aspergillus flavus (aflatoxin-producing fungus) was employed. Food samples, such as milk and soybean, were also evaluated for the presence of aflatoxins. The strip test was capable to distinguish between samples with and without aflatoxins samples, at a sensitivity concentration of 0,5 μg/Kg. Therefore, these results suggest that the strip tests developed in this study can be a potential tool as a rapid and cost-effective method for detection of insect resistant GM crops expressing Cry1Ac and Cry8Ka5 and aflatoxins from food samples.

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The expansion of cultivated areas with genetically modified crops (GM) is a worldwide phenomenon, stimulating regulatory authorities to implement strict procedures to monitor and verify the presence of GM varieties in agricultural crops. With the constant growing of plant cultivating areas all over the world, consumption of aflatoxin-contaminated food also increased. Aflatoxins correspond to a class of highly toxic contaminants found in agricultural products that can have harmful effects on human and animal health. Therefore, the safety and quality evaluation of agricultural products are important issues for consumers. Lateral flow tests (strip tests) is a promising method for the detection both proteins expressed in GM crops and aflatoxins-contaminated food samples. The advantages of this technique include its simplicity, rapidity and cost-effective when compared to the conventional methods. In this study, two novel and sensitive strip tests assay were developed for the identification of: (i) Cry1Ac and Cry8Ka5 proteins expressed in GM cotton crops and; (ii) aflatoxins from agricultural products. The first strip test was developed using a sandwhich format, while the second one was developed using a competitive format. Gold colloidal nanoparticles were used as detector reagent when coated with monoclonal antibodies. An anti-species specific antibody was sprayed at the nitrocellulose membrane to be used as a control line. To validate the first strip test, GM (Bollgard I® e Planta 50- EMBRAPA) and non-GM cotton leaf (Cooker 312) were used. The results showed that the strip containing antibodies for the identification of Cry1Ac and Cry8Ka5 proteins was capable of correctly distinguishing between GM samples (positive result) and non-GM samples (negative result), in a high sensitivity manner. To validate the second strip test, artificially contaminated soybean with Aspergillus flavus (aflatoxin-producing fungus) was employed. Food samples, such as milk and soybean, were also evaluated for the presence of aflatoxins. The strip test was capable to distinguish between samples with and without aflatoxins samples, at a sensitivity concentration of 0,5 μg/Kg. Therefore, these results suggest that the strip tests developed in this study can be a potential tool as a rapid and cost-effective method for detection of insect resistant GM crops expressing Cry1Ac and Cry8Ka5 and aflatoxins from food samples.

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In Brazilian semiarid region, the majority of water bodies are temporary and the biodiversity in these ecosystems is poorly known. The goal of this study was to describe the temporal variation of benthic macroinvertebrates in an intermittent stream in the Brazilian semiarid region. From March to July of 2009, surveys of benthic macroinvertebrates and water physiochemical parameters were done in a first order stream located at Piranhas-Açu River basin. 25 macroinvertebrates families were found, 21 belonging to Insecta class. The chironomids were the most abundant group during all study period and were represented by 19 genus. The largest densities and taxonomic richness were seen in the drying phase of the stream while the smallest values were found in the period with the heaviest rainfalls ( wet phase ). Only the families Chironomidae and Ceratopogonidae were found during all study period, suggesting that these groups have better adaptations to support floods and droughts. Furthermore, these two groups seemed to be pioneering in this stream. Among the chironomids, Paratendipes dominated the period of floods while Tanytarsus were more abundant in the drying phase . This study showed that hydrological fluctuation is the main force influencing the macroinvertebrate community in this stream, therefore, efforts seeking the conservation and management of Brazilian semiarid water bodies should consider this high natural variability in flow regime

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Although some individual techniques of supervised Machine Learning (ML), also known as classifiers, or algorithms of classification, to supply solutions that, most of the time, are considered efficient, have experimental results gotten with the use of large sets of pattern and/or that they have a expressive amount of irrelevant data or incomplete characteristic, that show a decrease in the efficiency of the precision of these techniques. In other words, such techniques can t do an recognition of patterns of an efficient form in complex problems. With the intention to get better performance and efficiency of these ML techniques, were thought about the idea to using some types of LM algorithms work jointly, thus origin to the term Multi-Classifier System (MCS). The MCS s presents, as component, different of LM algorithms, called of base classifiers, and realized a combination of results gotten for these algorithms to reach the final result. So that the MCS has a better performance that the base classifiers, the results gotten for each base classifier must present an certain diversity, in other words, a difference between the results gotten for each classifier that compose the system. It can be said that it does not make signification to have MCS s whose base classifiers have identical answers to the sames patterns. Although the MCS s present better results that the individually systems, has always the search to improve the results gotten for this type of system. Aim at this improvement and a better consistency in the results, as well as a larger diversity of the classifiers of a MCS, comes being recently searched methodologies that present as characteristic the use of weights, or confidence values. These weights can describe the importance that certain classifier supplied when associating with each pattern to a determined class. These weights still are used, in associate with the exits of the classifiers, during the process of recognition (use) of the MCS s. Exist different ways of calculating these weights and can be divided in two categories: the static weights and the dynamic weights. The first category of weights is characterizes for not having the modification of its values during the classification process, different it occurs with the second category, where the values suffers modifications during the classification process. In this work an analysis will be made to verify if the use of the weights, statics as much as dynamics, they can increase the perfomance of the MCS s in comparison with the individually systems. Moreover, will be made an analysis in the diversity gotten for the MCS s, for this mode verify if it has some relation between the use of the weights in the MCS s with different levels of diversity