977 resultados para Classification tree


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In 2000, an outbreak of sylvatic yellow fever possibly occurred in gallery forests of the Grande river in the Paraná basin in the northwestern region of São Paulo state. The aim of this study was to obtain information on the bionomics of Haemagogus and other mosquitoes inside tree holes in that area. Eighteen open tree holes were sampled for immature specimens. Adults were collected twice a month in the forest in Santa Albertina county from July 2000 to June 2001. The seasonal frequency of fourth instars was obtained by the Williams geometric mean (Mw), while the adult frequency was estimated either by hourly arithmetic or the Williams' means. Cole's index was applied to evaluate larval inter-specific associations. Among the ten mosquito species identified, the most abundant was Aedes terrens Walker followed by Sabethes tridentatus Cerqueira and Haemagogus janthinomys Dyar. Larval and adult abundance of these species was higher in summer than in winter. Although larval abundance of Hg. janthinomys peaked in the rainy season, correlation with rainfall was not significant. Six groups of larval associations were distinguished, one of which the most positively stable. The Hg. janthinomys and Ae. terrens association was significant, and Limatus durhamii Theobald was the species with most negative associations.

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The weevil subfamily Scolytinae includes beetles which may feed on the bark, trunk or roots of both live and dead trees and are sometimes considered forest and silvicultural pests. Less frequently, some species feed on seeds and may be cause economic losses when associated to plant cultivars. Spermophthorus apuleiae Costa-Lima is a Neotropical Scolytinae formerly recorded to be "associated" with seeds of Caesalpinia ferrea var. leiostachya Benth, a Brazilian tree popularly known in Portuguese as "pau-ferro". Hitherto, it was not clear whether these beetles actually feed on the seeds of that plant. In order to investigate the ability of S. apuleiae to feed on seeds of "pau-ferro", observations were done and colonies of these beetles were established. Both in the field and in captivity the beetles were not observed feeding on the seeds. Even when beetles were exposed to seeds as the only source of food they were incapable of boring or eating the seeds and died. Our data therefore suggest that S. apuleiae is a frugivorous species which peculiarly does not eat seeds of "pau-ferro".

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This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

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Previous studies pointed out that species richness and high density values within the Leguminosae in Brazilian forest fragments affected by fire could be due, at least partially, to the high incidence of root sprouting in this family. However, there are few Studies of the factors that induce root sprouting in woody plants after disturbance. We investigated the bud formation on root cuttings, and considered a man-made disturbance that isolates the root from the shoot apical dominance of three Leguminosae (Bauhinia forficata Link., Centrolobium tomentosum Guill. ex Benth, and Inga laurina (Sw.) Willd) and one Rutaceae (Esenbeckia febrifuga (St. Hit.) Juss. ex Mart.). All these species resprout frequently after fire. We also attempted to induce bud formation on root systems by removing the main trunk, girdling or sectioning the shallow lateral roots from forest tree species Esenbeckia febrifuga and Hymenaea courbaril L. We identified the origin of shoot primordia and their early development by fixing the samples in Karnovsky solution, dehydrating in ethyl alcohol series and embedding in plastic resin. Serial sections were cut on a rotary microtome and stained with toluidine blue O. Permanent slides were mounted in synthetic resin. We observed different modes of bud origin on root cuttings: close to the vascular cambium (C. tomentosum), from the callus (B. forficata and E febrifuga) and from the phloematic parenchyma proliferation (L laurina). Fragments of B. forficala root bark were also capable of forming reparative buds from healing phellogen formed in callus in the bark's inner side. In the attempt of bud induction on root systems, Hymenaea courbaril did not respond to any of the induction tests, probably because of plant age. However, Esenbeckia febrifuga roots formed suckers when the main trunk was removed or their roots were sectioned and isolated from the original plant. We experimentally demonstrated the ability of four tree species to resprout from roots after disturbance. Our results suggest that the release of apical dominance enables root resprouting in the studied species. Rev. Biol. Trop. 57 (3): 789-800. Epub 2009 September 30.

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Due to its relationship with other properties, wood density is the main wood quality parameter. Modern, accurate methods - such as X-ray densitometry - are applied to determine the spatial distribution of density in wood sections and to evaluate wood quality. The objectives of this study were to determinate the influence of growing conditions on wood density variation and tree ring demarcation of gmelina trees from fast growing plantations in Costa Rica. The wood density was determined by X-ray densitometry method. Wood samples were cut from gmelina trees and were exposed to low X-rays. The radiographic films were developed and scanned using a 256 gray scale with 1000 dpi resolution and the wood density was determined by CRAD and CERD software. The results showed tree-ring boundaries were distinctly delimited in trees growing in site with rainfall lower than 25 10 mm/year. It was demonstrated that tree age, climatic conditions and management of plantation affects wood density and its variability. The specific effect of variables on wood density was quantified by for multiple regression method. It was determined that tree year explained 25.8% of the total variation of density and 19.9% were caused by climatic condition where the tree growing. Wood density was less affected by the intensity of forest management with 5.9% of total variation.

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Aims. In this work, we describe the pipeline for the fast supervised classification of light curves observed by the CoRoT exoplanet CCDs. We present the classification results obtained for the first four measured fields, which represent a one-year in-orbit operation. Methods. The basis of the adopted supervised classification methodology has been described in detail in a previous paper, as is its application to the OGLE database. Here, we present the modifications of the algorithms and of the training set to optimize the performance when applied to the CoRoT data. Results. Classification results are presented for the observed fields IRa01, SRc01, LRc01, and LRa01 of the CoRoT mission. Statistics on the number of variables and the number of objects per class are given and typical light curves of high-probability candidates are shown. We also report on new stellar variability types discovered in the CoRoT data. The full classification results are publicly available.

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This study was conducted in the Private Reserve Mata do Jambreiro (912 ha), localized in the Iron Quadrangle, Minas Gerais, southeastern portion of the Espinhaco Range, which is predominantly covered by semideciduous seasonal montane forest. Three topographically and physiognomic similar areas located within a continuum forest fragment, distant by 1.3 to 1.5 km were sampled by the point-quadrat method. In each area, 30 points were marked. Individuals with a minimum perimeter at the breast height (PBH) of 15 cm were sampled, totaling 111 species belonging to 40 families. The most representative family was Fabaceae, with 14.29% of the total number of species. Low floristic similarity (5.3% to 34.4%) was observed between the areas, pointing out the importance of distribution of sample units in continuous fragments. Shannon diversity index (H') found was 4.22 and Pielou equability (J) 0.894. Soil analysis showed some differences in chemical composition between the three studied areas and was an important component for the interpretation of the floristic variation found. The low floristic similarity observed here for close areas justify the requirement of more detailed inventories by Brazilian Environmental Agencies for the legal authorization procedures prior to the establishment of new enterprising projects. Also, the professionals that conduct rapid inventories, mainly the Environmental Consultants, should give more attention to this kind of floristic variation and to the methods used to inventory complex forests.

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An (n, d)-expander is a graph G = (V, E) such that for every X subset of V with vertical bar X vertical bar <= 2n - 2 we have vertical bar Gamma(G)(X) vertical bar >= (d + 1) vertical bar X vertical bar. A tree T is small if it has at most n vertices and has maximum degree at most d. Friedman and Pippenger (1987) proved that any ( n; d)- expander contains every small tree. However, their elegant proof does not seem to yield an efficient algorithm for obtaining the tree. In this paper, we give an alternative result that does admit a polynomial time algorithm for finding the immersion of any small tree in subgraphs G of (N, D, lambda)-graphs Lambda, as long as G contains a positive fraction of the edges of Lambda and lambda/D is small enough. In several applications of the Friedman-Pippenger theorem, including the ones in the original paper of those authors, the (n, d)-expander G is a subgraph of an (N, D, lambda)-graph as above. Therefore, our result suffices to provide efficient algorithms for such previously non-constructive applications. As an example, we discuss a recent result of Alon, Krivelevich, and Sudakov (2007) concerning embedding nearly spanning bounded degree trees, the proof of which makes use of the Friedman-Pippenger theorem. We shall also show a construction inspired on Wigderson-Zuckerman expander graphs for which any sufficiently dense subgraph contains all trees of sizes and maximum degrees achieving essentially optimal parameters. Our algorithmic approach is based on a reduction of the tree embedding problem to a certain on-line matching problem for bipartite graphs, solved by Aggarwal et al. (1996).

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Context tree models have been introduced by Rissanen in [25] as a parsimonious generalization of Markov models. Since then, they have been widely used in applied probability and statistics. The present paper investigates non-asymptotic properties of two popular procedures of context tree estimation: Rissanen's algorithm Context and penalized maximum likelihood. First showing how they are related, we prove finite horizon bounds for the probability of over- and under-estimation. Concerning overestimation, no boundedness or loss-of-memory conditions are required: the proof relies on new deviation inequalities for empirical probabilities of independent interest. The under-estimation properties rely on classical hypotheses for processes of infinite memory. These results improve on and generalize the bounds obtained in Duarte et al. (2006) [12], Galves et al. (2008) [18], Galves and Leonardi (2008) [17], Leonardi (2010) [22], refining asymptotic results of Buhlmann and Wyner (1999) [4] and Csiszar and Talata (2006) [9]. (C) 2011 Elsevier B.V. All rights reserved.

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Efficient automatic protein classification is of central importance in genomic annotation. As an independent way to check the reliability of the classification, we propose a statistical approach to test if two sets of protein domain sequences coming from two families of the Pfam database are significantly different. We model protein sequences as realizations of Variable Length Markov Chains (VLMC) and we use the context trees as a signature of each protein family. Our approach is based on a Kolmogorov-Smirnov-type goodness-of-fit test proposed by Balding et at. [Limit theorems for sequences of random trees (2008), DOI: 10.1007/s11749-008-0092-z]. The test statistic is a supremum over the space of trees of a function of the two samples; its computation grows, in principle, exponentially fast with the maximal number of nodes of the potential trees. We show how to transform this problem into a max-flow over a related graph which can be solved using a Ford-Fulkerson algorithm in polynomial time on that number. We apply the test to 10 randomly chosen protein domain families from the seed of Pfam-A database (high quality, manually curated families). The test shows that the distributions of context trees coming from different families are significantly different. We emphasize that this is a novel mathematical approach to validate the automatic clustering of sequences in any context. We also study the performance of the test via simulations on Galton-Watson related processes.

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The problem of semialgebraic Lipschitz classification of quasihomogeneous polynomials on a Holder triangle is studied. For this problem, the ""moduli"" are described completely in certain combinatorial terms.

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Environmental quality assessment studies have been conducted with tree species largely distributed in the Atlantic Forest. Leaf and soil samples were collected in the conservation unit Parque Estadual da Serra do Mar (PESM) nearby the industrial complex of Cubatao, Sao Paulo State, Brazil, and analyzed for chemical elements by instrumental neutron activation analysis. Results were compared to background values obtained in the Parque Estadual Carlos Botelho (PECB). The higher As, Fe, Hg and Zn mass fractions in the tree leaves of PESM indicated anthropogenic influence on this conservation unit.

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Quality control of toys for avoiding children exposure to potentially toxic elements is of utmost relevance and it is a common requirement in national and/or international norms for health and safety reasons. Laser-induced breakdown spectroscopy (LIBS) was recently evaluated at authors` laboratory for direct analysis of plastic toys and one of the main difficulties for the determination of Cd. Cr and Pb was the variety of mixtures and types of polymers. As most norms rely on migration (lixiviation) protocols, chemometric classification models from LIBS spectra were tested for sampling toys that present potential risk of Cd, Cr and Pb contamination. The classification models were generated from the emission spectra of 51 polymeric toys and by using Partial Least Squares - Discriminant Analysis (PLS-DA), Soft Independent Modeling of Class Analogy (SIMCA) and K-Nearest Neighbor (KNN). The classification models and validations were carried out with 40 and 11 test samples, respectively. Best results were obtained when KNN was used, with corrected predictions varying from 95% for Cd to 100% for Cr and Pb. (C) 2011 Elsevier B.V. All rights reserved.

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The selection of candidate plus trees of desirable phenotypes from tropical forest trees and the rapid devastation of the natural environments in which these trees are found have created the need for a more detailed knowledge of the floral and reproductive biology of tropical tree species. In this article, the organogenic processes related to unisexual flower development in tropical mahogany, Swietenia macrophylla, are described. Mahogany inflorescences at different developmental stages were evaluated using scanning electron microscopy or optical microscopy of histological sections. The unisexual flowers of S. macrophylla are usually formed in a thyrse, in which the positions of the female and male flowers are not random. Differences between male and female flowers arise late during development. Both female and male flowers can only be structurally distinguished after stage 9, where ovule primordia development is arrested in male flowers and microspore development is aborted in female flower anthers. After this stage, male and female flowers can be distinguished by the naked eye as a result of differences in the dimensions of the gynoecium. The floral characteristics of S. macrophylla (distribution of male and female flowers within the inflorescence, and the relative number of male to female flowers) have practical implications for conservation strategies of this endangered species. (c) 2008 The Linnean Society of London, Botanical Journal of the Linnean Society, 2008, 156, 529-535.

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Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.