Botão "Ranking"

Ilustração componente do jogo “Quimolécula (http://www.loa.sead.ufscar.br/quimolecula.html)” desenvolvido pela equipe do Laboratório de Objetos de Aprendizagem da Universidade Federal de São Carlos (LOA/UFSCar).

Ranking

Ilustração componente do jogo “Quimolécula (http://www.loa.sead.ufscar.br/quimolecula.html)” desenvolvido pela equipe do Laboratório de Objetos de Aprendizagem da Universidade Federal de São Carlos (LOA/UFSCar).

ALGORITHM FOR PROBABILISTIC ANALYSIS of DISTRIBUTION SYSTEMS WITH DISTRIBUTED GENERATION

In this paper an efficient algorithm for probabilistic analysis of unbalanced three-phase weakly-meshed distribution systems is presented. This algorithm uses the technique of Two-Point Estimate Method for calculating the probabilistic behavior of the system random variables. Additionally, the deterministic analysis of the state variables is performed by means of a Compensation-Based Radial Load Flow (CBRLF). Such load flow efficiently exploits the topological characteristics of the network. To deal with distributed generation, a strategy to incorporate a simplified model of a generator in the CBRLF is proposed. Thus, depending on the type of control and generator operation conditions, the node with distributed generation can be modeled either as a PV or PQ node. To validate the efficiency of the proposed algorithm, the IEEE 37 bus test system is used. The probabilistic results are compared with those obtained using the Monte Carlo method.

Taxonomic status of the genus Sotalia: Species level ranking for tucuxi (Sotalia fluviatilis) and costero (Sotalia guianensis) dolphins

Dolphins of the genus Sotalia are found along the Caribbean and Atlantic coasts of Central and South America and in the Amazon River and most of its tributaries. At present, the taxonomy of these dolphins remains unresolved. Although five species were described in the late 1800s, only one species is recognized currently (Sotalia fluviatilis) with two ecotypes or subspecies, the coastal subspecies (Sotalia fluviatilis guianensis) and the riverine subspecies (Sotalia fluviatilis fluviatilis). Recent morphometric analyses, as well as mitochondrial DNA analysis, suggested recognition of each subspecies as separate species. Here we review the history of the classification of this genus and present new genetic evidence from ten nuclear and three mitochondrial genes supporting the elevation of each subspecies to the species level under the Genealogical/Lineage Concordance Species Concept and the criterion of irreversible divergence. We also review additional evidence for this taxonomic revision from previously published and unpublished genetic, morphological, and ecological studies. We propose the common name costero for the coastal species, Sotalia guianensis (Van Beneden 1864), and accept the previously proposed tucuxi dolphin, Sotalia fluviatilis (Gervais, 1853), for the riverine species.

A probabilistic model for elastic-plastic fracture analysis of plane and axisymmetric structures

This work presents a methodology for elastic-plastic fracture reliability analysis of plane and axisymmetric structures. The structural reliability analysis is accomplished by means of the FORM analytical method. The virtual crack extension technique based on a direct minimization of potencial energy is utililized for the calculation of the energy release rate. Results are presented to illustrate the performance of the adopted methodology.

Probabilistic neural network to predict cracks in taphole mud used in blast furnaces

One of the major problems facing Blast Furnaces is the occurrence of cracks in taphole mud, as the underlying causes are not easily identifiable. The absence of this knowledge makes it difficult the use of conventional techniques for predictability and mitigation. This paper will address the application of Probabilistic Neural Network using the Matlab software as a means to detect and control such cracks. The most relevant BF operational variables were picked through the statistic tool "Principal Component Analysis - PCA." Based upon the selection of these variables a probabilistic neural network was built. A set of BF operational data, consisting of 30 controlling variables, was divided into 2 groups, one of which for network training, and the other one to validate the neural network. The neural network got 98% of the cases right. The results show the effectiveness of this tool for crack prediction in relation to clay intrinsic properties and as a result of the fluctuation in operational variables.

Mathematical decomposition technique applied to the probabilistic power flow problem

In this paper a framework based on the decomposition of the first-order optimality conditions is described and applied to solve the Probabilistic Power Flow (PPF) problem in a coordinated but decentralized way in the context of multi-area power systems. The purpose of the decomposition framework is to solve the problem through a process of solving smaller subproblems, associated with each area of the power system, iteratively. This strategy allows the probabilistic analysis of the variables of interest, in a particular area, without explicit knowledge of network data of the other interconnected areas, being only necessary to exchange border information related to the tie-lines between areas. An efficient method for probabilistic analysis, considering uncertainty in n system loads, is applied. The proposal is to use a particular case of the point estimate method, known as Two-Point Estimate Method (TPM), rather than the traditional approach based on Monte Carlo simulation. The main feature of the TPM is that it only requires resolve 2n power flows for to obtain the behavior of any random variable. An iterative coordination algorithm between areas is also presented. This algorithm solves the Multi-Area PPF problem in a decentralized way, ensures the independent operation of each area and integrates the decomposition framework and the TPM appropriately. The IEEE RTS-96 system is used in order to show the operation and effectiveness of the proposed approach and the Monte Carlo simulations are used to validation of the results. © 2011 IEEE.

Probabilistic analysis of the distributed power generation in weakly meshed distribution systems

This paper presents an approach for probabilistic analysis of unbalanced three-phase weakly meshed distribution systems considering uncertainty in load demand. In order to achieve high computational efficiency this approach uses both an efficient method for probabilistic analysis and a radial power flow. The probabilistic approach used is the well-known Two-Point Estimate Method. Meanwhile, the compensation-based radial power flow is used in order to extract benefits from the topological characteristics of the distribution systems. The generation model proposed allows modeling either PQ or PV bus on the connection point between the network and the distributed generator. In addition allows control of the generator operating conditions, such as the field current and the power delivery at terminals. Results on test with IEEE 37 bus system is given to illustrate the operation and effectiveness of the proposed approach. A Monte Carlo Simulations method is used to validate the results. © 2011 IEEE.

A proposal for reliability evaluation of components on electric power distribution system integrating probabilistic models and fuzzy inference systems

The system reliability depends on the reliability of its components itself. Therefore, it is necessary a methodology capable of inferring the state of functionality of these components to establish reliable indices of quality. Allocation models for maintenance and protective devices, among others, have been used in order to improve the quality and availability of services on electric power distribution systems. This paper proposes a methodology for assessing the reliability of distribution system components in an integrated way, using probabilistic models and fuzzy inference systems to infer about the operation probability of each component. © 2012 IEEE.

Guide for ranking project profiles

Desarrolla un esquema básico para el diseño de un Banco de Proyectos para Belice con el fin de ayudar en el proceso de toma de decisiones en cada una de las etapas de un proyecto.

Project ranking and logical design of an investment programming support system

Includes bibliography

NodePM: A Remote Monitoring Alert System for Energy Consumption Using Probabilistic Techniques

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A scalable re-ranking method for content-based image retrieval

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Unsupervised manifold learning using Reciprocal kNN Graphs in image re-ranking and rank aggregation tasks

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)