Testes de envelhecimento acelerado e de condutividade elétrica em sementes de Dictyoloma vendellianum A. Juss.

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Variação genética para caracteres silviculturais e anatômicos da madeira em progênies de Myracrodruon urundeuva (Engler) Fr. Allem

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.

A snapshot of Chile's 20 largest multinational enterprises in 2011: Sustained growth in South America

Includes bibliography

The Brazilian architecture in wood and the confrontations with the questions of the environment

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.

Rheology and fluid dynamics properties of sugarcane juice

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.

A Markov random field model for combining optimum-path forest classifiers using decision graphs and game strategy approach

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.

Image categorization through optimum path forest and visual words

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.

Intrusion detection system using optimum-path forest

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.

Optimum-Path Forest pruning parameter estimation through Harmony Search

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.

New trends in musical genre classification using optimum-path forest

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.

The accuracy potential of Galileo E5/E1 pseudoranges for surveying and mapping

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.

Fault location in underground systems through optimum-path forest

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.

Electrical consumers data clustering through optimum-path forest

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.

Avaliação das propriedades químicas em solo de cerrado SOB reflorestamento ciliar

The rapid growth of agriculture, promoted by public government initiatives, favored an out of control deforestation of our forests; today, reforestation of permanent preservation areas are necessary for the conservation of our natural resources, and recovery of such areas are required by public laws. In an area of 5.26 acres of riparian reforestation in the savanna soil chemical properties were evaluated after twenty years of planting. It was analyzed the following variables: (P, organic matter (MO), pH, K, Ca, Mg, H+Al, Al and S) in 13 modules, with three replicas in two depths (0 - 20 and 20 - 40 cm) in a randomized block design in hierarchical scheme. Reforestation with tree species on the edge of Parana river in Selvíria (MS) contributes to chemical soil attributes, under riparian reforestation, as similar as a soil without human disturbance in this region; it is also possible to verify that forestry plantation promotes deposition of organic material which is essential for nutrient cycling, which keep the chemical properties of such soil in good condition for the establishment of riparian vegetation.

Restauração florestal visando à conservação de recursos hídricos por meio da combinação linear ponderada

This study evaluated using of Multicriteria Evaluation in a GIS, specifically by Weighted Linear Combination Method for generation of map of priority areas for forest restoration in the initial part of River Pardo Basin, SP, in order to water resources conservation. Aiming to define criteria and restrictions it was used Participatory Techniques, and the following factors had been selected: proximity of the hydrographic network, proximity of forest cover, slope and erodibility of soil. To calculate the weight to each factor it was used the decision-making process, known as Analytic Hierarchy Analysis, this method consists of a paired comparison of factors to determine the relative importance of each. According to Weighted Linear Combination, the very high priority areas have a more limited spatial distribution, with an apparent concentration around the water bodies, outlining a buffer to the river system. The proximity factor of the hydrographic network, and enables the connection forestry, contributed, along with the factor of proximity to forest cover, so there would be the definition of most of the areas with the highest priority in the basin, which concentrate the largest areas of forest and native riparian areas along the hydrographic.