Exterior orientation of CBERS-2B imagery using multi-feature control and orbital data

The major contribution of this paper relates to the practical advantages of combining Ground Control Points (GCPs), Ground Control Lines (GCLs) and orbital data to estimate the exterior orientation parameters of images collected by CBERS-2B (China-Brazil Earth Resources Satellite) HRC (High-resolution Camera) and CCD (High-resolution CCD Camera) sensors. Although the CBERS-2B is no longer operational, its images are still being used in Brazil, and the next generations of the CBERS satellite will have sensors with similar technical features, which motivates the study presented in this paper. The mathematical models that relate the object and image spaces are based on collinearity (for points) and coplanarity (for lines) conditions. These models were created in an in-house developed software package called TMS (Triangulation with Multiple Sensors) with multi-feature control (GCPs and GCLs). Experiments on a block of four CBERS-2B HRC images and on one CBERS-2B CCD image were performed using both models. It was observed that the combination of GCPs and GCLs provided better bundle block adjustment results than conventional bundle adjustment using only GCPs. The results also demonstrate the advantages of using primarily orbital data when the number of control entities is reduced. © 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

Scale-invariant resonance tagging in multijet events and new physics in Higgs pair production

We study resonant pair production of heavy particles in fully hadronic final states by means of jet substructure techniques. We propose a new resonance tagging strategy that smoothly interpolates between the highly boosted and fully resolved regimes, leading to uniform signal efficiencies and background rejection rates across a broad range of masses. Our method makes it possible to efficiently replace independent experimental searches, based on different final state topologies, with a single common analysis. As a case study, we apply our technique to pair production of Higgs bosons decaying into b\overline{b} pairs in generic New Physics scenarios. We adopt as benchmark models radion and massive KK graviton production in warped extra dimensions. We find that despite the overwhelming QCD background, the 4b final state has enough sensitivity to provide a complementary handle in searches for enhanced Higgs pair production at the LHC. © 2013 SISSA.

Multiple-trait random regression models for the estimation of genetic parameters for milk, fat, and protein yield in buffaloes

In this study, genetic parameters for test-day milk, fat, and protein yield were estimated for the first lactation. The data analyzed consisted of 1,433 first lactations of Murrah buffaloes, daughters of 113 sires from 12 herds in the state of São Paulo, Brazil, with calvings from 1985 to 2007. Ten-month classes of lactation days were considered for the test-day yields. The (co)variance components for the 3 traits were estimated using the regression analyses by Bayesian inference applying an animal model by Gibbs sampling. The contemporary groups were defined as herd-year-month of the test day. In the model, the random effects were additive genetic, permanent environment, and residual. The fixed effects were contemporary group and number of milkings (1 or 2), the linear and quadratic effects of the covariable age of the buffalo at calving, as well as the mean lactation curve of the population, which was modeled by orthogonal Legendre polynomials of fourth order. The random effects for the traits studied were modeled by Legendre polynomials of third and fourth order for additive genetic and permanent environment, respectively, the residual variances were modeled considering 4 residual classes. The heritability estimates for the traits were moderate (from 0.21-0.38), with higher estimates in the intermediate lactation phase. The genetic correlation estimates within and among the traits varied from 0.05 to 0.99. The results indicate that the selection for any trait test day will result in an indirect genetic gain for milk, fat, and protein yield in all periods of the lactation curve. The accuracy associated with estimated breeding values obtained using multi-trait random regression was slightly higher (around 8%) compared with single-trait random regression. This difference may be because to the greater amount of information available per animal. © 2013 American Dairy Science Association.

Neural networks models for wear patterns recognition of single-point dresser

Grinding is a workpiece finishing process for advanced products and surfaces. However, the constant friction between workpiece and grinding wheel causes the latter to lose its sharpness, thereby impairing the result of the grinding process. When this occurs, the dressing process is essential to sharpen the worn grains of the grinding wheel. The dressing conditions strongly influence the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The purpose of this study was to classify the wear condition of a single-point dresser using intelligent systems whose inputs were obtained by digitally processing acoustic emission signals. Two multilayer perceptron (MLP) neural networks were compared for their classification ability, one using the root mean square (RMS) statistics and another the ratio of power (ROP) statistics as input. In this study, it was found that the harmonic content of the acoustic emission signal is influenced by the condition of the dresser, and that the condition of the tool under study can be classified by using the aforementioned statistics to feed a neural network. © IFAC.

Modelo de propagação indoor multi-andar em 2.4 GHz com estimativa de parâmetros de QoS em chamadas VoIP

O advento de novas formas multimídia tem atraído uma clientela exigente, onde preocupação não é somente com o serviço, mas também, com a qualidade que esse serviço pode ser oferecido. As WLAN (Wireless Local Area Networks) tornaram-se a forma mais comum de roteamento de Internet, devido ao seu baixo custo e facilidade de implementação. Para realizar um bom roteamento é necessário um planejamento, utilizando-se modelos. Os modelos de propagação existentes na literatura fazem a predição da intensidade do sinal, mas algumas vezes não contemplam a previsão de um bom serviço. Nesse sentido a presente dissertação propõe-se a elaborar um modelo de propagação empírico indoor multi-andar que não só prediz a potência recebida, mas também faz uma previsão para algumas métricas de QoS (Quality of Service) de chamadas VoIP (Voice over Internet Protocol). Para a elaboração do modelo proposto foram feitas campanhas de medição, em um prédio de dois andares, em pisos distintos mantendo-se a posição do ponto de acesso (PA) fixa. Estudos de geometria analítica para a contagem e agregação de perdas em pisos e paredes. Os resultados do modelo proposto foram comparados com um modelo da literatura que tem um comportamento similar, onde é possível verificar o melhor desempenho do modelo proposto, e para efeito de estudo um andar completamente simulado foi introduzido para avaliação.

Modelagem 2,5D dos campos usados no Método Eletromagnético a Multi-Frequência - EMMF

Esta tese mostra a modelagem 2,5D de dados sintéticos do Método Eletromagnético a Multi-frequência (EMMF). O trabalho é apresentado em duas partes: a primeira apresenta os detalhes dos métodos usados nos cálculos dos campos gerados por uma bobina horizontal de corrente colocada sobre a superfície de modelos bidimensionais; e a segunda, usa os resultados obtidos para simular os dados medidos no método EMMF, que são as partes real e imaginária da componente radial do campo magnético gerado pela bobina. Nesta segunda parte, observamos o comportamento do campo calculado em diversos modelos, incluindo variações nas propriedades físicas e na geometria dos mesmos, com o intuito de verificar a sensibilidade do campo observado com relação às estruturas presentes em uma bacia sedimentar. Com esta modelagem, podemos observar as características dos dados e como as duas partes, real e imaginária, contribuem com informações distintas e complementares. Os resultados mostram que os dados da componente radial do campo magnético apresentam muito boa resolução lateral, mesmo estando a fonte fixa em uma única posição. A capacidade desses dados em distinguir e resolver estruturas alvo será fundamental para o trabalho futuro de inversão, bem como para a construção de seções de resistividade aparente.

Previsão multi-passos a frente do preço de energia elétrica de curto prazo no mercado brasileiro

A predição do preço da energia elétrica é uma questão importante para todos os participantes do mercado, para que decidam as estratégias mais adequadas e estabeleçam os contratos bilaterais que maximizem seus lucros e minimizem os seus riscos. O preço da energia tipicamente exibe sazonalidade, alta volatilidade e picos. Além disso, o preço da energia é influenciado por muitos fatores, tais como: demanda de energia, clima e preço de combustíveis. Este trabalho propõe uma nova abordagem híbrida para a predição de preços de energia no mercado de curto prazo. Tal abordagem combina os filtros autorregressivos integrados de médias móveis (ARIMA) e modelos de Redes Neurais (RNA) numa estrutura em cascata e utiliza variáveis explanatórias. Um processo em dois passos é aplicado. Na primeira etapa, as variáveis explanatórias são preditas. Na segunda etapa, os preços de energia são preditos usando os valores futuros das variáveis exploratórias. O modelo proposto considera uma predição de 12 passos (semanas) a frente e é aplicada ao mercado brasileiro, que possui características únicas de comportamento e adota o despacho centralizado baseado em custo. Os resultados mostram uma boa capacidade de predição de picos de preço e uma exatidão satisfatória de acordo com as medidas de erro e testes de perda de cauda quando comparado com técnicas tradicionais. Em caráter complementar, é proposto um modelo classificador composto de árvores de decisão e RNA, com objetivo de explicitar as regras de formação de preços e, em conjunto com o modelo preditor, atuar como uma ferramenta atrativa para mitigar os riscos da comercialização de energia.

Search for a Higgs boson decaying into a Z and a photon in pp collisions at root s=7 and 8 TeV

A search for a Higgs boson decaying into a Z boson and a photon is described. The analysis is performed using proton-proton collision datasets recorded by the CMS detector at the LHC. Events were collected at center-of-mass energies of 7 TeV and 8 TeV, corresponding to integrated luminosities of 5.0 fb(-1) and 19.6 fb(-1), respectively. The selected events are required to have opposite-sign electron or muon pairs. No excess above standard model predictions has been found in the 120-160 GeV mass range and the first limits on the Higgs boson production cross section times the H -> Z gamma branching fraction at the LHC have been derived. The observed at 95% confidence level limits are between about 4 and 25 times the standard model cross section times the branching fraction. For a standard model Higgs boson mass of 125 GeV the expected limit at the 95% confidence level is 10 and the observed limit is 9.5. Models predicting the Higgs boson production cross section times the H -> Z gamma branching fraction to be larger than one order of magnitude of the standard model prediction are excluded for most of the 125-157 GeV mass range. (C) 2013 CERN. Published by Elsevier B.V. All rights reserved.

Search for a non-standard-model Higgs boson decaying to a pair of new light bosons in four-muon final states

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimates of genetic parameters for total milk yield over multiple ages in Brazilian Murrah buffaloes using different models

The objective of this study was to estimate variance components and genetic parameters for accumulated 305-day milk yield (MY305) over multiple ages, from 24 to 120 months of age, applying random regression (RRM), repeatability (REP) and multi-trait (MT) models. A total of 4472 lactation records from 1882 buffaloes of the Murrah breed were utilized. The contemporary group (herd-year-calving season) and number of milkings (two levels) were considered as fixed effects in all models. For REP and RRM, additive genetic, permanent environmental and residual effects were included as random effects. MT considered the same random effects as did REP and RRM with the exception of permanent environmental effect. Residual variances were modeled by a step function with 1, 4, and 6 classes. The heritabilities estimated with RRM increased with age, ranging from 0.19 to 0.34, and were slightly higher than that obtained with the REP model. For the MT model, heritability estimates ranged from 0.20 (37 months of age) to 0.32 (94 months of age). The genetic correlation estimates for MY305 obtained by RRM (L23.res4) and MT models were very similar, and varied from 0.77 to 0.99 and from 0.77 to 0.99, respectively. The rank correlation between breeding values for MY305 at different ages predicted by REP, MT, and RRM were high. It seems that a linear and quadratic Legendre polynomial to model the additive genetic and animal permanent environmental effects, respectively, may be sufficient to explain more parsimoniously the changes in MY305 genetic variation with age.

Automatic Orientation of Multi-Scale Terrestrial Images for 3D Reconstruction

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

Predicting breeding values for milk yield of Guzera (Bos indicus) cows using random regression models

Given the importance of Guzera breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzera cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, All and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for testday milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzera lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals' ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production. (c) 2014 Elsevier B.V. All rights reserved.

Search for top-squark pairs decaying into Higgs or Z bosons in pp collisions at root s=8 TeV

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Observation of the diphoton decay of the Higgs boson and measurement of its properties

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Áreas prioritárias para conservação e restauração da paisagem utilizando multi-caminhos e informações de avifauna

Habitat loss and fragmentation of landscapes endanger the planet’s biodiversity. Strategies for identify priority areas for conservation and restoration of biodiversity rich areas becomes essential for the planning of the management of these landscape become successful. This study aims to propose a novel, transparent and replicable method for choosing priority areas for restoration, and includes the following steps: (a) identification of regional biodiversity hotspots for conservation; (b) identification of priority areas for restoration with the greatest potential to increase the connectivity of the fragments already existing; (c) estimate the potential richness of understory birds before and after restoration, analyzing the gain of species for the future scenario. In order to identify the corridors to be restored in a future scenario we considered the approach of multiple corridors, which aimed to connect the main fragments within the region through analysis of multi-paths. Already existing regression models were applied to estimate the richness of the landscape considering three models: a) species richness as a function of patch area of the fragment selected as hotspots; b) richness as a function of areas connected by structural corridors and c) connected area for species which are able to access nearby fragments within 20m. The gain of species for future scenario which consider the potential restoration of selected areas was estimated. Based on our results we observed that species that use corridors showed the highest increment of species richness of understory birds. As a result it had to restore corridors to model species with the ability to use forest corridors was the highest gain potential species richness of understory birds. The methods proposed method in this study appears provide new ways to ensures a better cost / benefit relationship for restoration projects by increasing the chances of better reach high levels of...