Produtividade e compactação do solo em diferentes ciclos anuais da cultura de cana-de-açúcar

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Minimizing inter-genotypic competition effects to predict genetic values and selection in forestry genetic tests

The effect of competition is an important source of variation in breeding experiments. This study aimed to compare the selection of plants of open-pollinated families of Eucalyptus with and without the use of competition covariables. Genetic values were determined for each family and tree and for the traits height, diameter at breast height and timber volume in a randomized block design, resulting in the variance components, genetic parameters, selection gains, effective size and selection coincidence, with and without the use of covariables. Intergenotypic competition is an important factor of environmental variation. The use of competition covariables generally reduces the estimates of variance components and influences genetic gains in the studied traits. Intergenotypic competition biases the selection of open-pollinated eucalypt progenies, and can result in an erroneous choice of superior genotypes; the inclusion of covariables in the model reduces this influence.

Vibration Attenuation in Rotating Machines Using Smart Spring Mechanism

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Automatic Classification of Three-Phase Flow Patterns of Heavy Oil in a Horizontal Pipe Using Support Vector Machines

The pipe flow of a viscous-oil-gas-water mixture such as that involved in heavy oil production is a rather complex thereto-fluid dynamical problem. Considering the complexity of three-phase flow, it is of fundamental importance the introduction of a flow pattern classification tool to obtain useful information about the flow structure. Flow patterns are important because they indicate the degree of mixing during flow and the spatial distribution of phases. In particular, the pressure drop and temperature evolution along the pipe is highly dependent on the spatial configuration of the phases. In this work we investigate the three-phase water-assisted flow patterns, i.e. those configurations where water is injected in order to reduce friction caused by the viscous oil. Phase flow rates and pressure drop data from previous laboratory experiments in a horizontal pipe are used for flow pattern identification by means of the 'support vector machine' technique (SVM).

The thrust and the relation factor kr in linear induction machines

This paper shows a new manner to establish the thrust of a linear induction machine. A new factor is established, named ''Relation Factor, which provides conditions to establish the thrust and other important variables of the linear and sector induction machines.

Unbalanced Three-Phase Induction Motors Starting and Arc Welding Machines Short-Circuit Modeling

Three-Phase Induction Motors (TIM) and Arc Welding Machines (AWM) are loads of special behavior widely used in industrial and commercial installations, and therefore may contribute significantly to the deterioration of the quality of energy supplied by utilities. This paper proposes a modeling in constant power of the unbalanced TIM starting using Genetic Algorithm (GA) and AWM short-circuit based on their statics characteristics curves. The proposed models are compared with the conventional models in the literature. The results showed the good performance of the proposed models, allowing a more precise analysis of the real requests of these loads.

Synchronous machines parameters identification using load rejection test data

This work shows a computational methodology for the determination of synchronous machines parameters using load rejection test data. The quadrature axis parameters are obtained with a rejection under an arbitrary reference, reducing the present difficulties.

Otimização da distância de extração de madeira com forwarder

The activities and management operations of wood harvesting do not have good computational tools available to help the forest technicians with the task of cost reduction. In many cases, machines of high investment are used in wood harvesting without adequate operation planning; consequently, the cost per hour of these machines, which is high, could be reduced. Using technological resources such as the Geographic Information Systems (GIS) integrated with the Global Positioning System (GPS), which are the basis of precision harvesting. In this research, a technological tool capable of calculating and optimizing the average skidding distance of the forwarder was developed. It was used in stands of different sizes and formats through mathematical techniques and available functionalities in the Geographic Information System GRASS. The developed tool, called optimized model, divides the stand in small parts in relation to shorter skidding distances. The main variable considered was the alignment of plantation. The model was tested in eucalypt stands located in the State of São Paulo. Sixteen stands were randomly selected: eight with a rectangular polygon form, and eight with irregular polygon form. The main variables were collected in these stands. Results showed that the optimized model developed, is efficient and flexible. It was possible to divide the stands in small parts resulting in smaller skidding medium distances. The stands with irregular form had shorter skidding medium distances than the rectangular stands.

The application of distributed virtual machines for enterprise computer management: A two-tier network file system for image provisioning and management

In order to simplify computer management, several system administrators are adopting advanced techniques to manage software configuration of enterprise computer networks, but the tight coupling between hardware and software makes every PC an individual managed entity, lowering the scalability and increasing the costs to manage hundreds or thousands of PCs. Virtualization is an established technology, however its use is been more focused on server consolidation and virtual desktop infrastructure, not for managing distributed computers over a network. This paper discusses the feasibility of the Distributed Virtual Machine Environment, a new approach for enterprise computer management that combines virtualization and distributed system architecture as the basis of the management architecture. © 2008 IEEE.

Infuěncia do relevo na produtividade e custos do harvester

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.

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.

Optimal moment to change pressure regulator and sprayer kit on center pivot irrigation machines: a theoretical proposal

A theoretical model was developed in order to determine the optimal moment for substituting the sprayer and pressure regulator kit on a center pivot irrigation machine. The model is based on the hypothesis that pressure regulator and sprayer deterioration decrease irrigation uniformity. To compensate the deficit that happens at under irrigated areas, an increase on irrigation depth is required. The model considers: additional water consumption and energy costs, maintenance and labor costs, as well as yield losses associated with under or over irrigated areas. The sum of all these components is compared to buying and installing a new spray kit cost, allowing the farmer to decide the best moment to renovate the sprayer and pressure regulator kits on a center pivot irrigation machine based on economic criteria.

Optimal moment to change pressure regulator and sprayer kit on center pivot irrigation machines: application to a study case

A theoretical model developed by the authors for determining the optimal moment to substitute sprayer and pressure regulator kit on a center pivot irrigating potatoes and beans has been applied. The methodology compares the sum of the costs due to additional consumption of water and energy, maintenance and labor, as well as yield losses associated to areas with deficit or over irrigation to the costs due to buy and install a new sprinkling set on the pivot. The results showed that for a reduction of 3.07% of the Hermann and Hein’s Uniformity Coefficient (UCh), the substitution of the sprinkling module on the pivot is justified when potatoes and beans are cultivated.

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.