Recent and future environmental suitability to dengue fever in Brazil using species distribution model

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

Bayesian inference for two-parameter gamma distribution assuming different noninformative priors

In this paper distinct prior distributions are derived in a Bayesian inference of the two-parameters Gamma distribution. Noniformative priors, such as Jeffreys, reference, MDIP, Tibshirani and an innovative prior based on the copula approach are investigated. We show that the maximal data information prior provides in an improper posterior density and that the different choices of the parameter of interest lead to different reference priors in this case. Based on the simulated data sets, the Bayesian estimates and credible intervals for the unknown parameters are computed and the performance of the prior distributions are evaluated. The Bayesian analysis is conducted using the Markov Chain Monte Carlo (MCMC) methods to generate samples from the posterior distributions under the above priors.

Origin and distribution of AT-rich repetitive DNA families in Triatoma infestans (Heteroptera)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Mylar Secondary Emission-energy Distribution and Yields

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Distribution of Brazilian dermatologists according to geographic location, population and HDI of municipalities: an ecological study

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

Distribution, management and diversity of yam local varieties in Brazil: a study on Dioscorea alata L.

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

Measurement of the muon charge asymmetry in inclusive pp -> W plus X production at root s=7 TeV and an improved determination of light parton distribution functions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Spectrum Distribution in Cognitive Radio: Error Correcting Codes Perspective

Cognitive radio is a growing zone in wireless communication which offers an opening in complete utilization of incompetently used frequency spectrum: deprived of crafting interference for the primary (authorized) user, the secondary user is indorsed to use the frequency band. Though, scheming a model with the least interference produced by the secondary user for primary user is a perplexing job. In this study we proposed a transmission model based on error correcting codes dealing with a countable number of pairs of primary and secondary users. However, we obtain an effective utilization of spectrum by the transmission of the pairs of primary and secondary users' data through the linear codes with different given lengths. Due to the techniques of error correcting codes we developed a number of schemes regarding an appropriate bandwidth distribution in cognitive radio.

Diversity, natural history, and geographic distribution of snakes in the Caatinga, Northeastern Brazil

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

Biogeographic Distribution Patterns and Their Correlates in the Diverse Frog Fauna of the Atlantic Forest Hotspot

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

Vertical distribution by demographic groups of ghost crab Ocypode quadrata (Crustacea: Brachyura)

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Distribution of constitutive heterochromatin in Triatoma melanocephala (Hemiptera, Triatominae)

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

A Time-domain Harmonic Power-Flow Analysis in Electrical Energy Distribution Networks, Using Norton Models for Non-linear Loading

The purpose of this paper is to present the application of a three-phase harmonic propagation analysis time-domain tool, using the Norton model to approach the modeling of non-linear loads, making the harmonics currents flow more appropriate to the operation analysis and to the influence of mitigation elements analysis. This software makes it possible to obtain results closer to the real distribution network, considering voltages unbalances, currents imbalances and the application of mitigation elements for harmonic distortions. In this scenario, a real case study with network data and equipments connected to the network will be presented, as well as the modeling of non-linear loads based on real data obtained from some PCCs (Points of Common Coupling) of interests for a distribution company.

Aplicação do algoritmo Rough Sets em um Data Warehouse

This Project aims to develop methods for data classification in a Data Warehouse for decision-making purposes. We also have as another goal the reduction of an attribute set in a Data Warehouse, in which a given reduced set is capable of keeping the same properties of the original one. Once we achieve a reduced set, we have a smaller computational cost of processing, we are able to identify non-relevant attributes to certain kinds of situations, and finally we are also able to recognize patterns in the database that will help us to take decisions. In order to achieve these main objectives, it will be implemented the Rough Sets algorithm. We chose PostgreSQL as our data base management system due to its efficiency, consolidation and finally, it’s an open-source system (free distribution)