963 resultados para Eucaliptus forestry
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This study aimed at characterizing the potential for natural regeneration of native vegetation in the under-story of an earlier Eucalyptus saligna Smith production stand. The study was carried out at the Parque das Neblinas, Bertioga municipality, SP, in a 45 ha third rotation stand; which had been abandoned 15 years ago for natural regeneration to occur. The sampling was done in 24 plots of 20 × 40 m. The sampled area was of 19,200 m2, with inventory made of 100% of the eucalyptus trees. All regeneration trees with a height ≥ 1.30 m and DBH ≥ 5.0 cm were measured, as well as adult individuals with DBH ≥ 5.0 cm; surveyed in two size classes. 1,417 individuals of E. saligna were measured, with a density of 738,02 individuals/ha and a basal area of 22.69 m2/ha. Among 2,763 natural regeneration individuals, 111 species belonged to 66 genera and 34 botanical families. The species represented 43.7% of the tree richness of neighboring native forest fragments. The total estimated density and the basal area were respectively 1,052.6 individuals/ha and 6.4 m2/ha of autochthonous trees with DBH ≥ 5.0 cm (Class 1); while for regeneration there were 3,864.58 individuals/ha, and 2.76 m2/ha of individuals with a height ≥ 1.30 m and DBH < 5.0 cm (Class 2). Shannon diversity (H') was 2.83 and 3.68, respectively, for Classes 1 and 2, and the corrected species richness for a 1000-individual sample (R1000) were 75.6 and 87.29 (Fisher's a index) for the same classes. The majority of the species (34.84%) was typical from the understory of wet tropical forest and had zoochoric fruit dispersal (67.57%). The results indicate that, under these conditions, a eucalyptus forest is able to provide adequate regeneration niches for native vegetation, and may represent a sink habitat for local populations.
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Among the several variables that influence timber harvesting is the slope, which influences the productivity of forest machines. In this experiment the harvester was evaluated technically and economically while cutting and processing eucalyptus activity on different slope classes. The technical analysis included a study of time and movements by the method of continuous time; productivity was determined by the volume in cubic meters of wood processing. The economic analysis included the parameters of operational cost, production cost and energy consumption. The analysis of the data showed that productivity decreased according to the increase of the percent slope inclination, resulting in an effective work hour productivity increase from 18.72 to 39.71 m 3sc, with a mean of operating cost of US$ 78.78 per work hour.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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The aims of this study were to evaluate the variation and to estimate genetic parameters for silvicultural anatomic wood traits for genetic breeding of a Myracrodruon urundeuva (Engler) Fr. Allem, population from Selvíria-MS. For this, from samples of a progeny test established in the Fazenda de Ensino, Pesquisa e Extensão da Faculdade de Engenharia de Ilha Solteira/UNESP, macroscopic anatomic wood traits of M. urundeuva (tangential diameter and vases frequency per mm2) and growth traits were measured (height, DBH and stem form). Genetic parameters were estimated in 28 open-pollinated progenies, in three replications and 10 plants per plot, using a REML/BLUP approach. Between the analysed traits, the DBH is the most indicated for selection for timber production, because it presented the highest values of coefficient of genetic variation, heritabilities and selective accuracy. Between the anatomic traits, the vessels frequency in the pith showed the highest values for genetic parameters. For pulp yield, based on the multi-effect index, the strategy of selecting the best trees for vessels frequency in the pith, independent of the progeny, permitted to obtain substantial gains by mass selection, without progeny test.
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Includes bibliography
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Two discussions are imposed to the designers of wood constructions. The first one deals with the technical knowledge to project and execute buildings; the second one is concerned with the preservation of the environment, use of the wood in a sustainable way. The work presents the tendencies of the wood used in the Brazilian habitation architecture characterizing the used woods; how the construction technical solutions have developed and discusses about the necessity of using the wood in a conscious way, knowing its origin and control, sustainable use of the forests resources. It focalizes, mainly, the search of the designers to harmonize the use of the wood and the preservation of the forest biodiversity, when it deals with the native forest.
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The sugarcane juice is a relatively low-cost agricultural resource, abundant in South Asia, Central America and Brazil, with vast applications in producing ethanol biofuel. In that way, a good knowledge of the rheological properties of this raw material is of crucial importance when designing and optimizing unit operations involved in its processing. In this work, the rheological behavior of untreated (USCJ, 17.9 °Brix), clarified (CSCJ, 18.2 °Brix) and mixed (MSCJ, 18.0 °Brix) sugarcane juices was studied at the temperature range from 277K to 373K, using a cone-and-plate viscometer. These fluids were found to present a Newtonian behavior and their flow curves were well-fitted by the viscosity Newtonian model. Viscosity values lied within the range 5.0×10 -3Pas to 0.04×10 -3Pas in the considered temperature interval. The dependence of the viscosity on the temperature was also successfully modeled through an Arrhenius-type equation. In addition to the dynamic viscosity, experimental values of pressure loss in tube flow were used to calculate friction factors. The good agreement between predicted and measured values confirmed the reliability of the proposed equations for describing the flow behavior of the clarified and untreated sugarcane juices. © 2010 Elsevier B.V.
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The research on multiple classifiers systems includes the creation of an ensemble of classifiers and the proper combination of the decisions. In order to combine the decisions given by classifiers, methods related to fixed rules and decision templates are often used. Therefore, the influence and relationship between classifier decisions are often not considered in the combination schemes. In this paper we propose a framework to combine classifiers using a decision graph under a random field model and a game strategy approach to obtain the final decision. The results of combining Optimum-Path Forest (OPF) classifiers using the proposed model are reported, obtaining good performance in experiments using simulated and real data sets. The results encourage the combination of OPF ensembles and the framework to design multiple classifier systems. © 2011 Springer-Verlag.
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Different from the first attempts to solve the image categorization problem (often based on global features), recently, several researchers have been tackling this research branch through a new vantage point - using features around locally invariant interest points and visual dictionaries. Although several advances have been done in the visual dictionaries literature in the past few years, a problem we still need to cope with is calculation of the number of representative words in the dictionary. Therefore, in this paper we introduce a new solution for automatically finding the number of visual words in an N-Way image categorization problem by means of supervised pattern classification based on optimum-path forest. © 2011 IEEE.
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Intrusion detection systems that make use of artificial intelligence techniques in order to improve effectiveness have been actively pursued in the last decade. Neural networks and Support Vector Machines have been also extensively applied to this task. However, their complexity to learn new attacks has become very expensive, making them inviable for a real time retraining. In this research, we introduce a new pattern classifier named Optimum-Path Forest (OPF) to this task, which has demonstrated to be similar to the state-of-the-art pattern recognition techniques, but extremely more efficient for training patterns. Experiments on public datasets showed that OPF classifier may be a suitable tool to detect intrusions on computer networks, as well as allow the algorithm to learn new attacks faster than the other techniques. © 2011 IEEE.
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Pattern recognition in large amount of data has been paramount in the last decade, since that is not straightforward to design interactive and real time classification systems. Very recently, the Optimum-Path Forest classifier was proposed to overcome such limitations, together with its training set pruning algorithm, which requires a parameter that has been empirically set up to date. In this paper, we propose a Harmony Search-based algorithm that can find near optimal values for that. The experimental results have showed that our algorithm is able to find proper values for the OPF pruning algorithm parameter. © 2011 IEEE.
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Musical genre classification has been paramount in the last years, mainly in large multimedia datasets, in which new songs and genres can be added at every moment by anyone. In this context, we have seen the growing of musical recommendation systems, which can improve the benefits for several applications, such as social networks and collective musical libraries. In this work, we have introduced a recent machine learning technique named Optimum-Path Forest (OPF) for musical genre classification, which has been demonstrated to be similar to the state-of-the-art pattern recognition techniques, but much faster for some applications. Experiments in two public datasets were conducted against Support Vector Machines and a Bayesian classifier to show the validity of our work. In addition, we have executed an experiment using very recent hybrid feature selection techniques based on OPF to speed up feature extraction process. © 2011 International Society for Music Information Retrieval.
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In the paper we discuss the potential of the new Galileo signals for pseudorange based surveying and mapping in open areas under optimal reception conditions (open sky scenarios) and suboptimal ones (multipath created by moderate to thick tree coverage). The paper reviews the main features of the Galileo E5 AltBOC and E1 CBOC signals; describes the simulation strategy, models and algorithms to generate realistic E5 and E1 pseudoranges with and without multipath sources; describes the ionosphere modeling strategy, models and algorithms and discusses and presents the expected positioning accuracy and precision results. According to the simulations performed, pseudoranges can be extracted from the Galileo E5 AltBOC signals with tracking errors (1-σ level) ranging from 0.02 m (open sky scenarios) to 0.08 m (tree covered scenarios) whereas for the Galileo E1 CBOC signals the tracking errors range between 0.25 m to 2.00 m respectively. With these tracking errors and with the explicit estimation of the ionosphere parameters, simulations indicate real-time open sky cm-level horizontal positioning precisions and dm-level vertical ones and dm-level accuracies for both the horizontal and vertical position components.
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In this paper we propose an accurate method for fault location in underground distribution systems by means of an Optimum-Path Forest (OPF) classifier. We applied the Time Domains Reflectometry method for signal acquisition, which was further analyzed by OPF and several other well known pattern recognition techniques. The results indicated that OPF and Support Vector Machines outperformed Artificial Neural Networks classifier. However, OPF has been much more efficient than all classifiers for training, and the second one faster for classification. © 2011 IEEE.
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Non-technical losses identification has been paramount in the last decade. Since we have datasets with hundreds of legal and illegal profiles, one may have a method to group data into subprofiles in order to minimize the search for consumers that cause great frauds. In this context, a electric power company may be interested in to go deeper a specific profile of illegal consumer. In this paper, we introduce the Optimum-Path Forest (OPF) clustering technique to this task, and we evaluate the behavior of a dataset provided by a brazilian electric power company with different values of an OPF parameter. © 2011 IEEE.