Simulated annealing for building roof contours identification from lidar data

This paper proposes a method by simulated annealing for building roof contours identification from LiDAR-derived digital elevation model. Our method is based on the concept of first extracting aboveground objects and then identifying those objects that are building roof contours. First, to detect aboveground objects (buildings, trees, etc.), the digital elevation model is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. The solution of this function is a polygon set corresponding to building roof contours and is found by using a minimization technique, like the Simulated Annealing algorithm. Experiments carried out with laser scanning digital elevation model showed that the methodology works properly, as it provides roof contour information with approximately 90% shape accuracy and no verified false positives.

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.

OPF-MRF: Optimum-path forest and Markov random fields for contextual-based image classification

Some machine learning methods do not exploit contextual information in the process of discovering, describing and recognizing patterns. However, spatial/temporal neighboring samples are likely to have same behavior. Here, we propose an approach which unifies a supervised learning algorithm - namely Optimum-Path Forest - together with a Markov Random Field in order to build a prior model holding a spatial smoothness assumption, which takes into account the contextual information for classification purposes. We show its robustness for brain tissue classification over some images of the well-known dataset IBSR. © 2013 Springer-Verlag.

Influence of potassium and sodium nutrition on leaf area components in Eucalyptus grandis trees

Background and Aims: Recent studies showed a positive tree response to Na addition in K-depleted tropical soils. Our study aimed to gain insight into the effects of K and Na fertilizations on leaf area components for a widely planted tree species. Methods: Leaf expansion rates, as well as nutrient, polyol and soluble sugar concentrations, were measured from emergence to abscission of tagged leaves in 1-year-old Eucalyptus grandis plantations. Leaf cell size and water status parameters were compared 1 and 2 months after leaf emergence in plots with KCl application (+K), NaCl application (+Na) and control plots (C). Results: K and Na applications enhanced tree leaf area by increasing both leaf longevity and the mean area of individual leaves. Higher cell turgor in treatments +K and +Na than in the C treatment resulting from higher concentrations of osmotica contributed to increasing both palisade cell diameters and the size of fully expanded leaves. Conclusions: Intermediate total tree leaf area in treatment +Na compared to treatments C and +K might result from the capacity of Na to substitute K in osmoregulatory functions, whereas it seemed unable to accomplish other important K functions that contribute to delaying leaf senescence. © 2013 Springer Science+Business Media Dordrecht.

Qualidade do sombreamento natural de três espécies arbóreas visando ao conforto térmico animal

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Comparação entre três critérios de amostragem para a avaliação da densidade básica da madeira de florestas implantadas de eucaliptos

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

Variação genética, herdabilidades e ganhos na seleção para caracteres de crescimento e forma, em teste de progênies de polinização aberta de Eucalyptus cloeziana, aos 24 anos de idade em Luiz Antônio-SP

Pós-graduação em Agronomia - FEIS

Extração automática de contornos de telhados de edifícios em um modelo digital de elevação, utilizando inferência Bayesiana e campos aleatórios de Markov

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise filogenética das espécies de Hemigrammus Gill, 1858 (Characiformes, Characidae)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Análise da composição e estrutura da comunidade arbustivo-arbórea de savana no sudoeste de Mato Grosso-Brasil

Pós-graduação em Ciências Biológicas (Biologia Vegetal) - IBRC

Estrutura e diversidade da família Lauraceae na Mata Atlântica do Parque Estadual da Serra do Mar, São Paulo, Brasil

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

Nutritional balance and yield for green manure orange trees

Intercropping could efficiently prevent soil nutrient losses caused by extensive agriculture. The present study aimed to assess the effect of green manure on the nutritional status of orange trees cultivar 'Pera' (Citrus sinensis (L.) Osbeck). The plants were grafted on 'Cravo' lime trees and were then planted in a 7x4m space. Four different treatments corresponding to the evaluated green manures were employed: jack bean (JB) (Canavalia ensiformis DC), lablab (LL) (Dolichos lablab L.), pigeon pea (PP) (Cajanus cajan L. Millsp), and Brachiaria (BQ) (Brachiaria brizantha Hochst ex A. Rich. Stapf) as control. The experimental design was in randomized blocks, in split-plot time, with six replicates, with four treatments (green manures) and two plants per evaluation. The nutritional status was assessed by using the DRIS method (Diagnosis and Recommendation Integrated System); the yield and the macro and micronutrient levels contained in green manures and in the control was also determined. The nutritional diagnosis indicated that, in the two years of experiment, plants treated with green manure showed better nutritional balance index compared to Brachiaria. This suggests that, over time, green manure can lead to better nutritional balance. Pigeon pea treatment showed the highest yields, compared to control, in the two evaluated crop cycles (2004/05 and 2005/06).

Random laser action from flexible biocellulose-based device

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Time-resolved random laser spectroscopy of inhomogeneously broadened systems

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Genetic parameters for body weight in buffaloes (Bubalus bubalis) in Colombia using random regression models

The objective of this research was to estimate (co) variance functions and genetic parameters for body weight in Colombian buffalo populations using random regression models with Legendre polynomials. Data consisted of 34,738 weight records from birth to 900 days of age from 7815 buffaloes. Fixed effects in the model were contemporary group and parity order of the mother. Random effects were direct and maternal additive genetic, as well as animal and maternal permanent environmental effects. A cubic orthogonal Legendre polynomial was used to model the mean curve of the population. Eleven models with first to sixth order polynomials were used to describe additive genetic direct and maternal effects, and animal and maternal permanent environmental effects. The residual was modeled considering five variance classes. The best model included fourth and sixth order polynomials for direct additive genetic and animal permanent environmental effects, respectively, and third-order polynomials for maternal genetic and maternal permanent environmental effects. The direct heritability increased from birth until 120 days of age (0.32 +/- 0.05), decreasing thereafter until one year of age (0.18 +/- 0.04) and increased again, reaching 0.39 +/- 0.09, at the end of the evaluated period. The highest maternal heritability estimates (0.11 +/- 0.05), were obtained for weights around weaning age (weaning age range is between 8 and 9.5 months). Maternal genetic and maternal permanent environmental variances increased from birth until about one year of age, decreasing at later ages. Direct genetic correlations ranged from moderate (0.60 +/- 0.060) to high (0.99 +/- 0.001), maternal genetic correlations showed a similar range (0.41 +/- 0.401 and 0.99 +/- 0.003), and all of them decreased as time between weighings increased. Direct genetic correlations suggested that selecting buffalos for heavier weights at any age would increase weights from birth through 900 days of age. However, higher heritabilities for direct genetic weights effects after 600 days of age suggested that selection for these effects would be more effective if done during this age period. A greater response to selection for maternal ability would be expected if selection used maternal genetic predictions for weights near weaning. (C) 2013 Elsevier B.V. All rights reserved.